1499

Central and South America

Coordinating Lead Authors:

Graciela O. Magrin (Argentina), José A. Marengo (Brazil)

Lead Authors:

Jean-Phillipe Boulanger (France), Marcos S. Buckeridge (Brazil), Edwin Castellanos

(Guatemala), Germán Poveda (Colombia), Fabio R. Scarano (Brazil), Sebastián Vicuña (Chile)

Contributing Authors:

Eric Alfaro (Costa Rica), Fabien Anthelme (France), Jonathan Barton (UK), Nina Becker

(Germany), Arnaud Bertrand (France), Ulisses Confalonieri (Brazil), Amanda Pereira de Souza

(Brazil), Carlos Demiguel (Spain), Bernard Francou (France), Rene Garreaud (Chile),

Iñigo Losada (Spain), Melanie McField (USA), Carlos Nobre (Brazil), Patricia Romero Lankao

(Mexico), Paulo Saldiva (Brazil), Jose Luis Samaniego (Mexico), María Travasso (Argentina),

Ernesto Viglizzo (Argentina), Alicia Villamizar (Venezuela)

Review Editors:

Leonidas Osvaldo Girardin (Argentina), Jean Pierre Ometto (Brazil)

Volunteer Chapter Scientist:

Nina Becker (Germany)

This chapter should be cited as:

Magrin

, G.O., J.A. Marengo, J.-P. Boulanger, M.S. Buckeridge, E. Castellanos, G. Poveda, F.R. Scarano, and S. Vicuña,

2014: Central and South America. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B:

Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel

on Climate Change [Barros, V.R., C.B. Field, D.J. Dokken, M.D. Mastrandrea, K.J. Mach, T.E. Bilir, M. Chatterjee,

K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White

(eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1499-1566.

1500

Executive Summary ......................................................................................................................................................... 1502

27.1. Introduction .......................................................................................................................................................... 1504

27.1.1. The Central and South America Region .......................................................................................................................................... 1504

27.1.2. Summary of the Fourth Assessment Report and IPCC Special Report on Managing the Risks of

Extreme Events and Disasters to Advance Climate Change Adaptation Findings ............................................................................ 1504

27.1.2.1. Fourth Assessment Report Findings ................................................................................................................................. 1504

27.1.2.2. IPCC Special Report on Managing the Risks of Extreme Events and Disasters

to Advance Climate Change Adaptation Findings ............................................................................................................ 1504

27.2. Major Recent Changes and Projections in the Region ......................................................................................... 1506

27.2.1. Climatic Stressors ........................................................................................................................................................................... 1506

27.2.1.1. Climate Trends, Long-Term Changes in Variability, and Extremes .................................................................................... 1506

Box 27-1. Extreme Events, Climate Change Perceptions, and Adaptive Capacity in Central America ........................... 1508

27.2.1.2. Climate Projections ......................................................................................................................................................... 1510

27.2.2. Non-Climatic Stressors .................................................................................................................................................................... 1513

27.2.2.1. Trends and Projections in Land Use and Land Use Change ............................................................................................. 1513

27.2.2.2. Trends and Projections in Socioeconomic Conditions ...................................................................................................... 1515

27.3. Impacts, Vulnerabilities, and Adaptation Practices ............................................................................................... 1516

27.3.1. Freshwater Resources ..................................................................................................................................................................... 1516

27.3.1.1. Observed and Projected Impacts and Vulnerabilities ....................................................................................................... 1516

27.3.1.2. Adaptation Practices ....................................................................................................................................................... 1521

27.3.2. Terrestrial and Inland Water Systems .............................................................................................................................................. 1522

27.3.2.1. Observed and Projected Impacts and Vulnerabilities ....................................................................................................... 1522

27.3.2.2. Adaptation Practices ....................................................................................................................................................... 1523

27.3.3. Coastal Systems and Low-Lying Areas ............................................................................................................................................ 1524

27.3.3.1. Observed and Projected Impacts and Vulnerabilities ....................................................................................................... 1524

27.3.3.2. Adaptation Practices ....................................................................................................................................................... 1526

27.3.4. Food Production Systems and Food Security ................................................................................................................................... 1527

27.3.4.1. Observed and Projected Impacts and Vulnerabilities ....................................................................................................... 1527

27.3.4.2. Adaptation Practices ....................................................................................................................................................... 1530

27.3.5. Human Settlements, Industry, and Infrastructure ............................................................................................................................ 1530

27.3.5.1. Observed and Projected Impacts and Vulnerabilities ....................................................................................................... 1530

Box 27-2. Vulnerability of South American Megacities to Climate Change:

The Case of the Metropolitan Region of São Paulo ....................................................................................... 1532

27.3.5.2. Adaptation Practices ....................................................................................................................................................... 1533

Table of Contents

1501

Central and South America Chapter 27

27.3.6. Renewable Energy .......................................................................................................................................................................... 1533

27.3.6.1. Observed and Projected Impacts and Vulnerabilities ....................................................................................................... 1533

27.3.6.2. Adaptation Practices ....................................................................................................................................................... 1534

27.3.7. Human Health ................................................................................................................................................................................ 1535

27.3.7.1. Observed and Projected Impacts and Vulnerabilities ....................................................................................................... 1535

27.3.7.2. Adaptation Strategies and Practices ................................................................................................................................ 1537

27.4. Adaptation Opportunities, Constraints, and Limits .............................................................................................. 1537

27.4.1. Adaptation Needs and Gaps ........................................................................................................................................................... 1537

27.4.2. Practical Experiences of Autonomous and Planned Adaptation, Including Lessons Learned ........................................................... 1538

27.4.3. Observed and Expected Barriers to Adaptation .............................................................................................................................. 1539

27.5. Interactions between Adaptation and Mitigation ................................................................................................ 1539

27.6. Case Studies .......................................................................................................................................................... 1540

27.6.1. Hydropower .................................................................................................................................................................................... 1540

27.6.2. Payment for Ecosystem Services ..................................................................................................................................................... 1540

27.7. Data and Research Gaps ....................................................................................................................................... 1541

27.8. Conclusions ........................................................................................................................................................... 1542

References ....................................................................................................................................................................... 1545

Frequently Asked Questions

27.1: What is the impact of glacier retreat on natural and human systems in the tropical Andes? ......................................................... 1522

27.2: Can payment for ecosystem services be used as an effective way for helping local communities to adapt to climate change? ..... 1526

27.3: Are there emerging and reemerging human diseases as a consequence of climate variability and change in the region? ............ 1536

1502

Chapter 27 Central and South America

Executive Summary

Significant trends in precipitation and temperature have been observed in Central America (CA) and South America (SA) (high

confidence). In addition, changes in climate variability and in extreme events have severely affected the region (medium

confidence).

Increasing trends in annual rainfall in southeastern South America (SESA; 0.6 mm day

–1

50 yr

–1

during 1950–2008) contrast with

decreasing trends in CA and central-southern Chile (–1 mm day

–1

50 yr

–1

during 1950–2008). Warming has been detected throughout CA and

SA (near 0.7°C to 1°C 40 yr

–

since the mid-1970s), except for a cooling off the Chilean coast of about –1 °C 40 yr

–

. Increases in temperature

extremes have been identified in CA and most of tropical and subtropical SA (medium confidence), while more frequent extreme rainfall in

SESA has favored the occurrence of landslides and flash floods (medium confidence). {27.2.1.1; Table 27-1; Box 27-1}

Climate projections suggest increases in temperature, and increases or decreases in precipitation for CA and SA by 2100

(medium confidence). In post-Fourth Assessment Report (AR4) climate projections, derived from dynamic downscaling forced by Coupled

Model Intercomparison Project Phase 3 (CMIP3) models for various Special Report on Emission Scenarios (SRES) scenarios, and from different

global climate models from the CMIP5 for various Representative Concentration Pathways (RCPs) (4.5 and 8.5), warming varies from +1.6°C to

+4.0°C in CA, and +1.7°C to +6.7°C in SA (medium confidence). Rainfall changes for CA range between –22 and +7% by 2100, while in SA

rainfall varies geographically, most notably showing a reduction of –22% in northeast Brazil, and an increase of +25% in SESA (low confidence).

By 2100 projections show an increase in dry spells in tropical SA east of the Andes, and in warm days and nights in most of SA (medium

confidence). {27.2.1.2; Table 27-2}

Changes in streamflow and water availability have been observed and projected to continue in the future in CA and SA, affecting

already vulnerable regions (high confidence). The Andean cryosphere is retreating, affecting the seasonal distribution of streamflows

(high confidence). {Table 27-3} Increasing runoffs in the La Plata River basin and decreasing ones in the Central Andes (Chile, Argentina) and in

CA in the second half of the 20th century were associated with changes in precipitation (high confidence). Risk of water supply shortages will

increase owing to precipitation reductions and evapotranspiration increases in semi-arid regions (high confidence) {Table 27-4}, thus affecting

water supply for cities (high confidence) {27.3.1.1, 27.3.5}, hydropower generation (high confidence) {27.3.6, 27.6.1}, and agriculture.

{27.3.1.1} Current practices to reduce the mismatch between water supply and demand could be used to reduce future vulnerability (medium

confidence). Ongoing constitutional and legal reforms toward more efficient and effective water resources management and coordination

constitute another adaptation strategy (medium confidence). {27.3.1.2}

Land use change contributes significantly to environmental degradation, exacerbating the negative impacts of climate change

(high confidence). Deforestation and land degradation are attributed mainly to increased extensive and intensive agriculture. The agricultural

expansion, in some regions associated with increases in precipitation, has affected fragile ecosystems, such as the edges of the Amazon forest

and the tropical Andes. Even though deforestation rates in the Amazon have decreased substantially since 2004 to a value of 4,656 km

–1

2012, other regions such as the Cerrado still present high levels of deforestation, with average rates as high as 14,179 km

–1

for the period

2002–2008. {27.2.2.1}

Conversion of natural ecosystems is the main cause of biodiversity and ecosystem loss in the region, and is a driver of

anthropogenic climate change (high confidence). Climate change is expected to increase the rates of species extinction (medium

confidence).

For instance, vertebrate species turnover until 2100 will be as high as 90% in specific areas of CA and the Andes Mountains. In

Brazil, distribution of some groups of birds and plants will be dislocated southward, where there are fewer natural habitats remaining. However,

CA and SA have still large extensions of natural vegetation cover for which the Amazon is the main example. {27.3.2.1} Ecosystem-based

adaptation practices are increasingly common across the region, such as the effective management and establishment of protected areas,

conservation agreements, and community management of natural areas. {27.3.2.2}

Socioeconomic conditions have improved since AR4; however, there is still a high and persistent level of poverty in most countries,

resulting in high vulnerability and increasing risk to climate variability and change (high confidence).

Poverty levels in most countries

remain high (45% for CA and 30% for SA for year 2010) in spite of the sustained economic growth observed in the last decade. The Human

Development Index varies greatly between countries, from Chile and Argentina with the highest values to Guatemala and Nicaragua with the

1503

Central and South America Chapter 27

lowest values in 2007. The economic inequality translates into inequality in access to water, sanitation, and adequate housing, particularly for

the most vulnerable groups, translating into low adaptive capacities to climate change. {27.2.2.2}

Sea level rise (SLR) and human activities on coastal and marine ecosystems pose threats to fish stocks, corals, mangroves,

recreation and tourism, and control of diseases (high confidence). SLR varied from 2 to 7 mm yr

–1

between 1950 and 2008. Frequent

coral bleaching events associated with ocean warming and acidification occur in the Mesoamerican Coral Reef. In CA and SA, the main drivers

of mangrove loss are deforestation and land conversion to agriculture and shrimp ponds. {27.3.3.1} Brazilian fisheries’ co-management (a

participatory multi-stakeholder process) is an example of adaptation as it favors a balance between conservation of marine biodiversity, the

improvement of livelihoods, and the cultural survival of traditional populations. {27.3.3.2}

Changes in agricultural productivity with consequences for food security associated with climate change are expected to exhibit

large spatial variability (medium confidence).

In SESA, where projections indicate more rainfall, average productivity could be sustained or

increased until the mid-century (medium confidence; SRES: A2, B2). {Table 27-5} In CA, northeast of Brazil, and parts of the Andean region,

increases in temperature and decreases in rainfall could decrease the productivity in the short term (by 2030), threatening the food security of

the poorest population (medium confidence). {Table 27-5} Considering that SA will be a key food-producing region in the future, one of the

challenges will be to increase the food and bioenergy quality and production while maintaining environmental sustainability under climate

change. {27.3.4.1} Some adaptation measures include crop, risk, and water use management along with genetic improvement (high confidence).

{27.3.4.2}

Renewable energy based on biomass has a potential impact on land use change and deforestation and could be affected by

climate change (medium confidence).

Sugarcane and soy are likely to respond positively to CO

and temperature changes, even with a

decrease in water availability, with an increase in productivity and production (high confidence). The expansion of sugarcane, soy, and oil palm

may have some effect on land use, leading to deforestation in parts of the Amazon and CA, among other regions, and loss of employment in

some countries (medium confidence). {27.3.6.1} Advances in second-generation bioethanol from sugarcane and other feedstocks will be

important as a measure of mitigation. {27.3.6.2}

Changes in weather and climatic patterns are negatively affecting human health in CA and SA, by increasing morbidity, mortality,

and disabilities (high confidence), and through the emergence of diseases in previously non-endemic areas (high confidence).

With very high confidence, climate-related drivers are associated with respiratory and cardiovascular diseases, vector- and water-borne diseases

(malaria, dengue, yellow fever, leishmaniasis, cholera, and other diarrheal diseases), hantaviruses and rotaviruses, chronic kidney diseases, and

psychological trauma. Air pollution is associated with pregnancy-related outcomes and diabetes, among others. {27.3.7.1} Vulnerabilities vary

with geography, age, gender, race, ethnicity, and socioeconomic status, and are rising in large cities (very high confidence). {27.3.7.2} Climate

change will exacerbate current and future risks to health, given the region’s population growth rates and vulnerabilities in existing health,

water, sanitation and waste collection systems, nutrition, pollution, and food production in poor regions (medium confidence).

In many CA and SA countries, a first step toward adaptation to future climate changes is to reduce the vulnerability to present

climate.

Long-term planning and the related human and financial resource needs may be seen as conflicting with the present social deficit in

the welfare of the CA and SA population. Various examples demonstrate possible synergies between development, adaptation, and mitigation

planning, which can help local communities and governments to allocate efficiently available resources in the design of strategies to reduce

vulnerability. However, the generalization of such actions at a continental scale requires that both the CA and SA citizens and governments

address the challenge of building a new governance model, where imperative development needs, vulnerability reduction, and adaptation

strategies to climate stresses will be truly intertwined. {27.3.4, 27.4-5}

1504

Chapter 27 Central and South America

27.1. Introduction

7.1.1. The Central and South America Region

he Central America (CA) and South America (SA) region harbors unique

ecosystems and has the highest biodiversity on the planet and a variety

of eco-climatic gradients. Unfortunately, this natural wealth is threatened

by advancing agricultural frontiers resulting from a rapidly growing

agricultural and cattle production (Grau and Aide, 2008). The region

experienced a steady economic growth, accelerated urbanization, and

important demographic changes in the last decade; poverty and inequality

are decreasing continuously, but at a low pace (ECLAC, 2011c). Adaptive

capacity is improving in part thanks to poverty alleviation and development

initiatives (McGray et al., 2007).

The region has multiple stressors on natural and human systems derived

in part from significant land use changes and exacerbated by climate

variability/climate change. Climate variability at various time scales has

been affecting social and natural systems, and extremes in particular have

affected large regions. In Central and South America, 613 climatological

and hydro-meteorological extreme events occurred in the period 2000–

2013, resulting in 13,883 fatalities, 53.8 million people affected, and

economic losses of US$52.3 billion (www.emdat.be). Land is facing

increasing pressure from competing uses such as cattle ranching, food

production, and bioenergy.

The region is regarded as playing a key role in the future world economy

because countries such as Brazil, Chile, Colombia, and Panama, among

others, are rapidly developing and becoming economically important in

the world scenario. The region is bound to be exposed to the pressure

related to increasing land use and industrialization. Therefore, it is

expected to have to deal with increasing emission potentials. Thus,

science-based decision making is thought to be an important tool to

control innovation and development of the countries in the region.

Two other important contrasting features characterize the region: having

the biggest tropical forest of the planet on the one side, and possessing

the largest potential for agricultural expansion and development during

the next decades on the other. This is the case because the large

countries of SA, especially, would have a major role in food and bioenergy

production in the future, as long as policies toward adaptation to global

climate change will be strategically designed. The region is already one

of the top producers and user of bioenergy and this experience will

serve as an example to other developing regions as well as developed

regions.

27.1.2. Summary of the Fourth Assessment Report and

IPCC Special Report on Managing the Risks of

Extreme Events and Disasters to Advance Climate

Change Adaptation Findings

27.1.2.1. Fourth Assessment Report Findings

According to the Working Group II contribution to the Fourth Assessment

Report (WGII AR4), Chapter 13 (Latin America), during the last decades

of the 20th century, unusual extreme weather events have been

everely affecting the Latin America (LA) region, contributing greatly

to the strengthening of the vulnerability of human systems to natural

disasters. In addition, increases in precipitation were observed in

southeastern South America (SESA), northwest Peru, and Ecuador; while

decreases were registered in southern Chile, southwest Argentina,

southern Peru, and western CA since 1960. Mean warming was near

0.1ºC per decade. The rate of sea level rise (SLR) has accelerated over

the last 20 years, reaching 2 to 3 mm yr

–1

. The glacier-retreat trend has

intensified, reaching critical conditions in the Andean countries. Rates

of deforestation have been continuously increasing, mainly due to

agricultural expansion, and land degradation has been intensified for

the entire region.

Mean warming for LA at the end of 21st century could reach 1ºC to 4ºC

(SRES B2) or 2ºC to 6ºC (SRES A2) (medium confidence; WGII AR4

Chapter 13, p. 583). Rainfall anomalies (positive or negative) will be

larger for the tropical part of LA. The frequency and intensity of weather

and climate extremes is likely to increase (medium confidence).

Future impacts include: “significant species extinctions, mainly in tropical

LA” (high confidence); “replacement of tropical forest by savannas, and

semi-arid vegetation by arid vegetation” (medium confidence); “increases

in the number of people experiencing water stress” (medium confidence);

“probable reductions in rice yields and possible increases of soy yield

in SESA” (WGII AR4 Chapter 13, p. 583); and “increases in crop pests

and diseases” (medium confidence; WGII AR4 Chapter 13, p. 607)—

with “some coastal areas affected by sea level rise, weather and climatic

variability and extremes” (high confidence; WGII AR4 Chapter 13, p.

584).

Some countries have made efforts to adapt to climate change and

variability, for example, through the conservation of key ecosystems

(e.g., biological corridors in Mesoamerica, Amazonia, and Atlantic forest;

compensation for ecosystem services in Costa Rica), the use of early

warning systems and climate forecast (e.g., fisheries in eastern Pacific,

subsistence agriculture in northeast Brazil), and the implementation of

disease surveillance systems (e.g., Colombia) (WGII AR4 Chapter 13, p.

591). However, several constraints such as the lack of basic information,

observation, and monitoring systems; the lack of capacity-building and

appropriate political, institutional, and technological frameworks; low

income; and settlements in vulnerable areas outweigh the effectiveness

of these efforts.

27.1.2.2. IPCC Special Report on Managing the Risks

of Extreme Events and Disasters to Advance

Climate Change Adaptation Findings

As reported in Section 3.4 of the IPCC Special Report on Managing

the Risks of Extreme Events and Disasters to Advance Climate Change

Adaptation (SREX; IPCC, 2012b), a changing climate leads to changes

in the frequency, intensity, spatial extent, or duration of weather and

climate extremes, and can result in unprecedented extremes. Levels of

confidence in historical changes depend on the availability of high-

quality and homogeneous data and relevant model projections. This

has been a major problem in CA and SA, where a lack of long-term

homogeneous and continuous climate and hydrological records and of

1505

Central and South America Chapter 27

omplete studies on trends has not allowed for an identification of

trends in extremes, particularly in CA.

Recent observational studies and projections from global and regional

models suggest changes in extremes. With medium confidence, increases

in warm days and decreases in cold days, as well as increases on warm

nights and decreases in cold nights, have been identified in CA, northern

SA, northeast Brazil (NEB), SESA, and the west coast of SA. In CA, there

is low confidence that any observed long-term increase in tropical

cyclone activity is robust, after accounting for past changes in observing

capabilities. In other regions, such as Amazonia (insufficient evidence),

inconsistencies among studies and detected trends result in low

confidence of observed rainfall trends. Although it is likely that there has

been an anthropogenic influence on extreme temperature in the region,

there is low confidence in attribution of changes in tropical cyclone

activity to anthropogenic influences.

Projections for the end of the 21st century for differing emissions

scenarios (SRES A2 and A1B) show that for all CA and SA, models

project substantial warming in temperature extremes. It is likely that

ncreases in the frequency and magnitude of warm daily temperature

extremes and decreases in cold extremes will occur in the 21st century

on the global scale. With medium confidence, it is very likely that the

length, frequency, and/or intensity of heat waves will experience a large

increase over most of SA, with a weaker tendency toward increasing in

SESA. With low confidence, the models also project an increase of the

proportion of total rainfall from heavy falls for SESA and the west coast

of SA, while for Amazonia and the rest of SA and CA there are not

consistent signals of change. In some regions, there is low confidence

in projections of changes in fluvial floods. Confidence is low owing to

limited evidence and because the causes of regional changes are complex.

There is medium confidence that droughts will intensify along the 21st

century in some seasons and areas due to reduced precipitation and/or

increased evapotranspiration in Amazonia and NEB.

The character and severity of the impacts from climate extremes

depend not only on the extremes themselves but also on exposure and

vulnerability. These are influenced by a wide range of factors, including

anthropogenic climate change, climate variability, and socioeconomic

development.

Continued next page

Region Variable Reference Period Observed changes

Central

America and

northern

South

America

Precipitation in NAMS Englehart and Douglas (2006) 1943 – 2002 +0.94 mm day

–

over 58 years

Rainfall onset in NAMS Grantz et al. (2007) 1948 – 2004 – 10 to – 20 days over 57 years

Summertime precipitation in NAMS Anderson et al. (2010) 1931 – 2000 +17.6 mm per century

Rainfall extremes (P95) in NAMS Cavazos et al. (2008) 1961 – 1998 +1.3% per decade

Cold days and nights in CA and northern SA Donat et al. (2013) 1951 – 2010 Cold days: –1 day per decade.

Cold nights: –2 days per decade

Warm days and nights in northern SA Donat et al. (2013) 1951 – 2010 Warm days: +2 to +4 days per decade.

Warm nights: +1 to +3 days per decade

Heavy precipitation (R10) in northern SA Donat et al. (2013) 1951 – 2010 +1 to +2 days per decade

CDDs in northern SA Donat et al. (2013) 1951 – 2010 – 2 days per decade

West coast

of South

America

Sea surface temperature and air temperatures off coast of Peru and Chile

(15°S – 35°S)

Falvey and Garreaud (2009);

Gutiérrez et al. (2011a,b);

Kosaka and Xie (2013)

1960 – 2010 – 0.25°C per decade, – 0.7°C over 11

years for 2002 – 2012

Temperature, precipitation, cloud cover, and number of rainy days since the mid-

1970s off the coast of Chile (18°S – 30°S)

Schulz et al. (2012) 1920 – 2009 – 1°C over 40 years, – 1.6 mm over 40

years, – 2 oktas over 40 years, and – 0.3

day over 40 years

Wet days until 1970, increase after that, reduction in the precipitation rate in

southern Chile (37°S – 43°S)

Quintana and Aceituno (2012) 1900 – 2007 – 0.34% until 1970 and +0.37% after

that, – 0.12%

Cold days and nights on all SA coast Donat et al. (2013) 1951 – 2010 Cold days: – 1 day per decade. Cold

nights: – 2 days per decade

Warm nights on all SA coast, warm days in the northern coast of SA, warm days

off the coast of Chile

Donat et al. (2013) 1951 – 2010 Warm nights: – 1 day per decade. Warm

days: +3 days per decade. Warm days: – 1

day per decade

Warm nights on the coast of Chile Dufek et al. (2008) 1961 – 1990 +5% to +9% over 31 years

Dryness as estimated by the PDSI for most of the west coast of SA (Chile,

Ecuador, northern Chile)

Dai (2011) 1950 – 2008 – 2 to – 4 over 50 years

Heavy precipitation (R95) in northern and central Chile Dufek et al. (2008) 1961 – 1990 – 45 to – 105 mm over 31 years

Temperature and extreme precipitation in southern Chile Vicuña et al. (2013) 1976 – 2008 Increase in annual maximum

temperature from +0.5°C to +1.1°C per

decade; change in number of days with

intense rainfall events from – 2.7 to +4.2

days per decade.

Table 27-1 | Regional observed changes in temperature, precipitation, and climate extremes in various sectors of Central America (CA) and South America (SA). Additional

information on changes in observed extremes can be found in the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change

Adaptation (SREX; Seneviratne et al., 2012) and the IPCC WGI AR5, Sections 2.4 – 2.6. (CDDs = consecutive dry days; NAMS = North American Monsoon System; PDSI = Palmer

Drought Severity Index; SAMS = South American Monsoon System; SD = standard deviation.)

1506

Chapter 27 Central and South America

27.2. Major Recent Changes

and Projections in the Region

27.2.1. Climatic Stressors

27.2.1.1. Climate Trends, Long-Term Changes

in Variability, and Extremes

In CA and SA, decadal variability and changes in extremes have been

affecting large sectors of the population, especially those more vulnerable

and exposed to climate hazards. Observed changes in some regions

have been attributed to natural climate variability, while in others they

have been attributed to land use change (e.g., increased urbanization),

meaning that land use change is a result of anthropogenic drivers. Table

27-1 summarizes the observed trends in the region’s climate.

Since around 1950, in CA and the North American Monsoon System

(NAMS), rainfall has been starting increasingly later and has become

more irregular in space and time, while rainfall has been increasing and

the intensity of rainfall has been increasing during the onset season

(see references in Table 27-1). Arias et al. (2012) relate those changes

to decadal rainfall variations in NAMS.

The west coast of SA experienced a prominent but localized coastal

cooling of about 1°C during the past 30 to 50 years extending from

central Peru down to central Chile. This occurs in connection with an

increased upwelling of coastal waters favored by the more intense trade

winds (Falvey and Garreaud, 2009; Narayan et al., 2010; Gutiérrez et

al., 2011a,b; Schulz et al., 2012; Kosaka and Xie, 2013). In the extremely

arid northern coast of Chile, rainfall, temperature, and cloudiness show

strong interannual and decadal variability, and since the mid-1970s,

Continued next page

Region Variable Reference Period Observed changes

Southeastern

South

America

ean annual air temperature in southern Brazil Sansigolo and Kayano (2010) 1913 – 2006 +0.5°C to +0.6°C per decade

requency of cold days and nights, warm days in Argentina and Uruguay Rusticucci and Renom (2008) 1935 – 2002 – 1.2% per decade, – 1% per decade,

+0.2% per decade

ighest annual maximum temperature, lowest annual minimum air temperature

in Argentina and Uruguay

usticucci and Tencer (2008) 1956 – 2003 +0.8°C over 47 years,

+0.6°C over 47 years

arm nights in Argentina and Uruguay and southern Brazil Rusticucci (2012) 1960 – 2009 +10 – 20% over 41 years

arm nights in most of the region Dufek et al. (2008) 1961 – 1990 +7% to +9% over 31 years

Cold nights in most of the region Dufek et al. (2008) 1961 – 1990 – 5% to – 9% over 31 years

Warm days and nights in most of the region Donat et al. (2013) 1951 – 2010 Warm nights: +3 days per decade.

arm days: +4 days per decade

Cold days and nights in most of the region Donat et al. (2013) 1951 – 2010 Cold nights: – 3 days per decade.

old days: – 3 days per decade

CDDs in the La Plata Basin countries (Argentina, Bolivia, and Paraguay) and

decrease of CDDs in SA south of 30°S

Dufek et al. (2008) 1961 – 1990 +15 to +21 days over 31 years,

– 21 to – 27 days over 31 years

umber of dry months during the warm season (October– March) in the Pampas

region between 25°S and 40°S

arrucand et al. (2007) 1904 – 2000 From 2 – 3 months in 1904–1920 to 1 – 2

months in 1980 – 2000

oister conditions as estimated by the PDSI in most of southeastern SA Dai (2011) 1950 – 2008 0 – 4 PDSI over 50 years

ainfall trends in the Paraná River Basin Dai et al. (2009) 1948 – 2008 +1.5 mm day

– 1

over 50 years

Number of days with precipitation above 10 mm (R10) in most of the region Donat et al. (2013) 1951 – 2010 +2 days per decade

eavy precipitation (R95) in most of the region Donat et al. (2013) 1951 – 1910 +1% per decade and – 4 days per decade

Heavy precipitation (R95) in most of the region Dufek et al. (2008) 1961 – 1990 +45 to +135 mm over 31 years

Heavy precipitation (R95) in the state of São Paulo Dufek and Ambrizzi (2008) 1950 – 1999 +50 to +75 mm over 40 years

CDDs in the state of São Paulo Dufek and Ambrizzi (2008) 1950 – 1990 –25 to –50 days over 40 years

Lightning activity varies signiﬁ cantly with change in temperature in the state of

São Paulo

Pinto and Pinto (2008);

Pinto et al. (2013)

1951 – 2006 +40% per 1°C for daily and monthly

time scales and approximately +30% per

1°C for decadal time scale

Number of days with rainfall above 20 mm in the city of São Paulo Silva Dias et al. (2012);

Marengo et al. (2013)

2005 – 2011 +5 to +8 days over 11 years

Excess rainfall events duration after 1950 Krepper and Zucarelli (2010) 1901 – 2003 +21 months over 53 years

Dry events and events of extreme dryness from 1972 to 1996 Vargas et al. (2011) 1972 – 1996 – 29 days over 24 years

Number of dry days in Argentina Rivera et al. (2013) 1960 – 2005 – 2 to – 4 days per decade

Extreme daily rainfall in La Plata Basin Penalba and Robledo (2010) 1950 – 2000 +33% to +60% increase in spring,

summer, and autumn, – 10% to – 25%

decrease in winter

Frequency of heavy rainfall in Argentina, southern Brazil, and Uruguay Re and Barros (2009) 1959 – 2002 +50 to +150 mm over 43 years

Annual precipitation in the La Plata Basin Doyle and Barros (2011);

Doyle et al. (2012)

1960 – 2005 +5 mm year

– 1

Table 27-1 (continued)

1507

Central and South America Chapter 27

the minimum daily temperature, cloudiness, and precipitation have

decreased. In central Chile, a negative precipitation trend was observed

over the period 1935–1976, and an increase after 1976, while further

south, the negative trend in rainfall that prevailed since the 1950s has

intensified by the end of the 20th century (Quintana and Aceituno,

2012). To the east of the Andes, NEB exhibits large interannual rainfall

variability, with a slight decrease since the 1970s (Marengo et al. 2013a).

Droughts in this region (e.g., 1983, 1987, 1998) have been associated

with El Niño and/or a warmer Tropical North Atlantic Ocean. However,

not all El Niño years result in drought in NEB, as the 2012–2013 drought

occurred during La Niña (Marengo et al., 2013a).

In the La Plata Basin in SESA, various studies have documented interannual

and decadal scale circulation changes that have led to decreases in the

Region Variable Reference Period Observed changes

Andes

Mean maximum temperature along the Andes, and increase in the number of

rost days

Marengo et al. (2011b) 1921 – 2010 +0.10°C to +0.12°C per decade in

921 – 2010, and +0.23 – 0.24°C per

decade during 1976 – 2010; +8 days per

ecade during 1996 – 2002

Air temperature and changes in precipitation in northern Andes (Colombia,

cuador)

Villacís (2008) 1961 – 1990 +0.1°C to +0.22°C per decade,

–

4% to +4% per decade

emperature and precipitation in northern and central Andes of Peru SENAMHI (2005, 2007,

2009a,c,d)

963 – 2006 +0.2°C to +0.45°C per decade,

– 20% to – 30% over 40 years

emperature and precipitation in the southern Andes of Peru SENAMHI (2007, 2009a,b,c,d);

Marengo et al. (2011b)

964 – 2006 +0.2°C to +0.6°C per decade,

– 11 to +2 mm per decade

Air temperature and rainfall over Argentinean and Chilean Andes and Patagonia Masiokas et al. (2008);

alvey and Garreaud (2009)

1950 – 1990 +0.2°C to +0.45°C per decade,

–

10% to – 12% per decade

Number of days with rainfall above 10 mm (R10) Donat et al. (2013) 1950 – 2010 – 3 days per decade

ryness in the Andes between 35.65°S and 39.9°S using the PDSI Christie et al. (2011) 1950 – 2003 – 7 PDSI over 53 years

Rainfall decrease in the Mantaro Valley, central Andes of Peru SENAMHI (2009c) 1970 – 2005 – 44 mm per decade

ir temperature in Colombian Andes Poveda and Pineda (2009) 1959 – 2007 +1°C over 20 years

Amazon

region

Decadal variability of rainfall in northern and southern Amazonia Marengo et al. (2009b);

Satyamurty et al. (2010)

1920 – 2008 – 3 SDs over 30 years in northern

Amazonia and +4 SDs over 30 years in

outhern Amazonia since the mid-1970s

Rainfall in all the region Espinoza et al. (2009a,b) 1975 – 2003 – 0.32% over 28 years

Onset of the rainy season in southern Amazonia Butt et al. (2011);

arengo et al. (2011b)

1950 – 2010 – 1 month since 1976 – 2010

Precipitation in the SAMS core region Wang et al. (2012) 1979 – 2008 +2 mm day

– 1

per decade

Onset becomes steadily earlier from 1948 to early 1970s, demise dates have

remained later, and SAMS duration was longer after 1972

Carvalho et al. (2011) 1948 – 2008 SAMS from 170 days (1948 – 1972) to

195 days (1972 – 1982)

Spatially varying trends of heavy precipitation (R95), increase in many areas and

insufﬁ cient evidence in others

Marengo et al. (2009b) 1961 – 1990 +100 mm over 31 years in western and

extreme eastern Amazonia

Spatially varying trends in dry spells (CDDs), increase in many areas and

decrease in others

Marengo et al. (2009b, 2010) 1961 – 1990 +15 mm over 31 years in western

Amazonia, – 20 mm in southern

Amazonia

Rainfall in most of Amazonia and in western Amazonia Dai et al. (2009); Dai (2011) 1948 – 2008 +1 mm day

– 1

over 50 years,

– 1.5 mm day

– 1

over 50 years

Dryness as estimated by the PDSI in southern Amazonia and moister conditions

in western Amazonia

Dai (2011) 1950 – 2008 – 2 to – 4 over 50 years,

+2 to +4 over 50 years

Seasonal mean convection and cloudiness Arias et al. (2011) 1984 – 2007 +30 W m

– 2

over 23 years,

– 8% over 23 years

Onset of rainy season in southern Amazonia due to land use change Butt et al. (2011) 1970 – 2010 – 0.6 days over 30 years

Precipitation in the region Gloor et al. (2013) 1990 – 2010 – 20 mm over 21 years

Northeastern

Brazil

Rainfall trends in interior northeastern Brazil and in northern northeastern Brazil Dai et al. (2009); Dai (2011) 1948 – 2008 – 0.3 mm day

– 1

over 50 years,

+1.5 mm day

– 1

over 50 years

Heavy precipitation (R95) in some areas, and in southern northeastern Brazil Silva and Azevedo (2008) 1970 – 2006 – 2 mm over 24 years to +6 mm over

24 years

CDDs in most of southern northeastern Brazil Silva and Azevedo (2008) 1970 – 2006 – 0.99 day over 24 years

Total annual precipitation in northern northeastern Brazil Santos and Brito (2007) 1970 – 2006 +1 to +4 mm year

– 1

over 24 years

Spatially varying trends in heavy precipitation (R95) in northern northeastern

Brazil

Santos and Brito (2007) 1970 – 2006 – 0.1 to +5 mm year

– 1

over 24 years

Spatially varying trends in heavy precipitation (R95) and CDDs in northern

northeastern Brazil

Santos et al. (2009) 1935 – 2006 – 0.4 to +2.5 mm year

– 1

over 69 years,

– 1.5 to +1.5 days year

– 1

over 69 years

Dryness in southern northeastern Brazil as estimated by the PDSI, and northern

northeastern Brazil

Dai (2011) 1950 – 2008 – 2 to – 4 over 50 years,

0 to +1 over 50 years

Table 27-1 (continued)

1508

Chapter 27 Central and South America

frequency of cold nights in austral summer, as well as to increases

in warm nights and minimum temperatures during the last 40 years.

Simultaneously, a reduction in the number of dry months in the warm

season is found since the mid-1970s, while heavy rain frequency is

increasing in SESA (references in Table 27-1). In SESA, increases in

precipitation are responsible for changes in soil moisture (Collini et al.,

2008; Saulo et al., 2010), and although feedback mechanisms are

present at all scales, the effect on atmospheric circulation is detected

at large scales. Moreover, land use change studies in the Brazilian

southern Amazonia for the last decades showed that the impact on the

hydrological response is time lagged at larger scales (Rodriguez, D.A.

et al., 2010).

In the central Andes, in the Mantaro Valley (Peru), precipitation shows

a strong negative trend, while warming is also detected (SENAMHI,

2007). In the southern Andes of Peru air temperatures have increased

during 1964–2006, but no clear signal on precipitation changes has been

detected (Marengo et al., 2009a). In the northern Andes (Colombia,

Ecuador), changes in temperature and rainfall in 1961–1990 have been

identified by Villacís (2008). In the Patagonia region, Masiokas et al.

(2008) have identified an increase of temperature together with

precipitation reductions during 1912–2002. Vuille et al. (2008a) found

that climate in the tropical Andes has changed significantly over the

past 50 to 60 years. Temperature in the Andes has increased by

approximately 0.1°C per decade, with only 2 of the last 20 years being

below the 1961–1990 average. Precipitation has slightly increased in

the second half of the 20th century in the inner tropics and decreased

in the outer tropics. The general pattern of moistening in the inner

tropics and drying in the subtropical Andes is dynamically consistent

with observed changes in the large-scale circulation, suggesting a

strengthening of the tropical atmospheric circulation. Moreover, a

positive significant trend in mean temperature of 0.09°C per decade

during 1965–2007 has been detected over the Peruvian Andes by

Lavado et al. (2012).

Box 27-1 | Extreme Events, Climate Change Perceptions, and Adaptive Capacity in Central America

Central America (CA) has traditionally been characterized as a region with high exposure to geo-climatic hazards derived from its

location and topography and with high vulnerability of its human settlements (ECLAC, 2010c). It has also been identiﬁed as the most

responsive tropical region to climate change (Giorgi, 2006). Evidence for this has been accumulating particularly in the last 30 years,

with a steady increase in extreme events including storms, ﬂoods, and droughts. In the period 2000–2009, 39 hurricanes occurred in

the Caribbean basin compared to 15 and 9 in the 1980s and 1990s, respectively (UNEP and ECLAC, 2010). The impacts of these events

on the population and the economy of the region have been tremendous: the economic loss derived from 11 recent hydrometereological

events evaluated amounted to US$13.64 billion and the number of people impacted peaked with Hurricane Mitch in 1998, with more

than 600,000 persons affected (ECLAC, 2010c). A high percentage of the population in CA live on or near highly unstable steep terrain

with sandy, volcanic soils prone to mudslides, which are the main cause of casualties and destruction (Restrepo and Alvarez, 2006).

The increased climatic variability in the past decade certainly changed the perception of people in the region with respect to climate

change. In a survey to small farmers in 2003, Tucker et al. (2010) found that only 25% of respondents included climate events as a

major concern. A subsequent survey in 2007 (Eakin et al., 2013) found that more than 50% of respondents cited drought conditions

and torrential rains as their greatest concern. Interestingly, there was no consensus on the direction in climate change pattern: The

majority of households in Honduras reported an increase in the frequency of droughts but in Costa Rica and Guatemala a decrease or

no trend at all was reported. A similar discrepancy in answers was reported with the issue of increased rainfall. But there was general

agreement in all countries that rainfall patterns were more variable, resulting in higher difﬁculty in recognizing the start of the rainy

season.

The high levels of risk to disasters in CA are the result of high exposure to hazards and the high vulnerability of the population and

its livelihoods derived from elevated levels of poverty and social exclusion (Programa Estado de la Nación-Región, 2011). Disaster

management in the region has focused on improving early warning systems and emergency response for speciﬁc extreme events

(Saldaña-Zorrilla, 2008) but little attention has been paid to strengthening existing social capital in the form of local organizations

and cooperatives. These associations can be central in increasing adaptive capacity through increased access to ﬁnancial instruments

and strategic information on global markets and climate (Eakin et al., 2011). There is a need to increase the communication of the

knowledge from local communities involved in processes of autonomous adaptation to policymakers responsible for strengthening

the adaptive capacities in CA (Castellanos et al., 2013).

1509

Central and South America Chapter 27

or the Amazon basin, Marengo (2004) and Satyamurty et al. (2010)

concluded that no systematic unidirectional long-term trends toward

drier or wetter conditions in both the northern and southern Amazon

have been identified since the 1920s. Rainfall fluctuations are more

characterized by interannual scales linked to El Niño-Southern Oscillation

(ENSO) or decadal variability. Analyzing a narrower time period, Espinoza

et al. (2009a,b) found that mean rainfall in the Amazon basin for 1964–

2003 has decreased, with stronger amplitude after 1982, especially in

the Peruvian western Amazonia (Lavado et al., 2012), consistent with

reductions in convection and cloudiness in the same region (Arias et

al., 2011). Recent studies by Donat et al. (2013) suggest that heavy rains

re increasing in frequency in Amazonia. Regarding seasonal extremes

in the Amazon region, two major droughts and three floods have affected

the region from 2005 to 2012, although these events have been related

to natural climate variability rather than to deforestation (Marengo et

al., 2008, 2012, 2013a; Espinoza et al., 2011, 2012, 2013; Lewis et al.,

2011; Satyamurty et al., 2013).

On the impacts of land use changes on changes in the climate and

hydrology of Amazonia, Zhang et al. (2009) suggest that biomass-burning

aerosols can work against the seasonal monsoon circulation transition,

and thus reinforce the dry season rainfall pattern for southern Amazonia,

Continued next page

Region Variable Reference Models and scenarios Projected changes

Central

America and

northern

South

America

Leaf Area Index, evapotranspiration by

070 – 2099 in CA

Imbach et al. (2012) 23 CMIP3 models, A2 Evapotranspiration: +20%; Leaf Area Index:

–

20% + 0.94 mm / day/ 58 years

ir temperature by 2075 and 2100 in CA Aguilar et al. (2009) 9 CMIP3 models, A2 +2.2°C by 2075; +3.3°C by 2100

Rainfall in CA and Venezuela, air temperature

n the region

Kitoh et al. (2011);

all et al. (2013)

20 km MRI-AGCM3.1S model, A1B Rainfall decrease / increase of about –10% /+10%

y 2079. Temperature increases of about +2.5°C

to +3.5°C by 2079

Precipitation and evaporation in most of the

region. Soil moisture in most land areas in all

seasons

Nakaegawa et al. (2013b) 20 km MRI-AGCM3.1S model, A1B Precipitation decrease of about – 5 mm day

– 1

evaporation increase of about +3 to +5 mm

day

– 1

; soil moisture to decrease by – 5 mm day

– 1

Rainfall in Nicaragua, Honduras, northern

Colombia, and northern Venezuela; rainfall

in Costa Rica and Panama. Temperature in all

regions by 2071– 2100

Campbell et al. (2011) PRECIS forced with HadAM3, A2 Rainfall: – 25% to – 50%, and +25% to +50%;

temperature: +3°C to +6°C

Precipitation and temperature in northern SA,

decrease in interior Venezuela, temperature

increases by 2071– 2100

Marengo et al. (2011a) Eta forced with HadCM3, A1B Increases by +30% to +50%;

reductions by –10% to – 20%;

temperature: +4°C to +5°C

Precipitation and temperature by 2100 in CA Karmalkar et al. (2011) PRECIS forced with HadAM3, A2 Precipitation: – 24% to – 48%;

temperature: +4°C to +5°C

Warm nights, CDDs, and heavy precipitation in

Venezuela by 2100

Marengo et al. (2009a, 2010) PRECIS forced with HadAM3, A2 Increase of +12% to +18%, +15 to +25 days,

and reduction of 75 to 105 days

Air temperature and precipitation in CA by 2100 Giorgi and Diffenbaugh (2008) 23 CMIP3 models, A1B Increase of +3°C to +5°C;

reduction of –10% to – 30%

CDDs and heavy precipitation by 2099 Kamiguchi et al. (2006) 20 km MRI-AGCM3.1S model, A1B Increase of +5 days, increase of +2% to +8%

Rainfall over Panama by 2099 Fábrega et al. (2013) 20 km MRI-AGCM3.1S model, A1B Increase of +5%

West coast

of South

America

Precipitation, runoff, and temperature at the

Limari river basin in semi-arid Chile by 2100

Vicuña et al. (2011) PRECIS forced with HadAM3, A2 Precipitation: –15% to – 25%; runoff: – 6% to

– 27%; temperature: +3°C to +4°C

Air temperature and surface winds in west coast

of SA (Chile) by 2100

Garreaud and Falvey (2009) 15 CMIP3 models, PRECIS forced

with HadAM3, A2

Temperature: +1°C; coastal winds: +1.5 m s

– 1

Precipitation in the bands 5°N –10°S,

25°S – 30°S, 10°S – 25°S, and 30°S – 50°S;

temperature increase by 2100

Marengo et al. (2011a) Eta forced with HadCM3, A1B Increases of 30 – 40%; increases of 3°C to 5°C

Warm nights, CDDs, and heavy precipitation in

5°N – 5°S by 2100

Marengo et al. (2009a, 2010) PRECIS forced with HadAM3, A2 Increase of +3% to +18%, reduction of – 5 to – 8

days, increase of +75 to +105 days

Air temperature, increase in precipitation

between 0° and 10°S, and between 20°S and

40°S by 2100

Giorgi and Diffenbaugh (2008) 23 CMIP3 models, A1B Increase of +2°C to +3°C; increase of 10%,

reduction of –10% to – 30%

CDDs between 5°N and 10°S and south of 30°S;

heavy precipitation between 5°S and 20°S and

south of 20°S by 2099

Kamiguchi et al. (2006) 20 km MRI-AGCM3.1S model, A1B Increase of 10 days and between +2% and +10%

Precipitation between 15°S and 35°S and south

of 40°S; temperature by 2100

Nuñez et al. (2009) MM5 forced with HadAM3, A2 Precipitation: – 2 mm day

– 1

; +2 mm day

– 1

;

temperature: +2.5°C

Precipitation in Panama and Venezuela by 2099 Sörensson et al. (2010) RCA forced with ECHAM5 – MPI

OM model, A1B

Precipitation: –1 to – 3 mm day

– 1

Table 27-2 | Regional projected changes in temperature, precipitation, and climate extremes in different sectors of Central America (CA) and South America (SA). Various studies

used A2 and B2 scenarios from Coupled Model Intercomparison Project Phase 3 (CMIP3) and various Representative Concentration Pathway (RCP) scenarios for CMIP5, and

different time slices from 2010 to 2100. To make results comparable, the CMIP3 and CMIP5 at the time slice ending in 2100 are included. Additional information on changes in

projected extremes can be found in the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX; see IPCC,

2012), and in IPCC WGI AR5 Sections 9.5, 9.6, 14.2, and 14.7. (CDDs = consecutive dry days.)

1510

Chapter 27 Central and South America

while Wang et al. (2011) suggests the importance of deforestation and

vegetation dynamics on decadal variability of rainfall in the region. Costa

and Pires (2010) have suggested a possible decrease in precipitation

due to soybean expansion in Amazonia, mainly as a consequence of its

very high albedo. In the SouthAmerican Monsoon System (SAMS) region,

positive trends in rainfall extremes have been identified in the last 30

years, with a pattern of increasing frequency and intensity of heavy

rainfall events, and earlier onsets and late demise of the rainy season

(see Table 27-1).

27.2.1.2. Climate Projections

Since the AR4, substantial additional regional analysis has been carried

out using the Coupled Model Intercomparison Project Phase 3 (CMIP3)

model ensemble. In addition, projections from CMIP5 models and new

experiences using regional models (downscaling) have allowed for a

better description of future changes in climate and extremes in CA and

SA. Using CMIP3 and CMIP5 models, Giorgi (2006), Diffenbaugh et al.

(2008), Xu et al. (2009), Diffenbaugh and Giorgi (2012), and Jones and

Carvalho (2013) have identified areas of CA/western North America and

the Amazon as persistent regional climate change hotspots throughout

the 21st century of the Representative Concentration Pathway (RCP)8.5

and RCP4.5. Table 27-2 summarizes projected climatic changes derived

from global and regional models for the region, indicating the projected

change, models, emission scenarios, time spans, and references.

In CA and Northern Venezuela, projections from CMIP3 models and

from downscaling experiments suggest precipitation reductions and

warming together with an increase in evaporation, and reductions in

Region Variable Reference Models and scenarios Projected changes

Southeastern

South

America

recipitation and runoff, and air temperature

by 2100

arengo et al. (2011a) Eta forced with HadCM3, A1B Precipitation: +20% to +30%; runoff: +10% to

+20%; air temperature: +2.5°C to +3.5°C

recipitation and temperature in the La Plata

basin by 2050

abré et al. (2010) MM5 forced with HadAM3, A2 Precipitation: +0.5 to 1.5 mm day

– 1

;

temperature: +1.5°C to 2.5°C

arm nights, CDDs, and heavy precipitation

y 2100

enendez and Carril (2010) 7 CMIP3 models, A1B Warm nights: +10% to +30%; CDDs: +1 to +5

ays; heavy precipitation: +3% to +9%

Precipitation during summer and spring, and in

all and winter by 2100

Seth et al. (2010) 9 CMIP3 models, A2 Precipitation: +0.4 to +0.6 mm day

– 1

–

0.02 to – 0.04 mm day

– 1

Warm nights, CDDs, and heavy precipitation

y 2100

Marengo et al. (2009a, 2010) PRECIS forced with HadAM3, A2 Increase of +6% to +12%, +5 to +20 days,

75 to +105 days

ir temperature and rainfall by 2100 Giorgi and Diffenbaugh (2008) 23 CMIP3 models, A1B Increase of +2°C to +4°C,

increase of +20% to +30%

DDs and heavy precipitation by 2099 Kamiguchi et al. (2006) 20 km MRI-AGCM3.1S model, A1B Increase of +5% to +10% and of +2% to +8%

Precipitation in north central Argentina,

ecrease in southern Brazil, increase of air

temperature by 2100

Nuñez et al. (2009) MM5 forced with HadAM3, A2 Increase of +0.5 to +1 mm day

– 1

eduction of – 0.5 mm day

– 1

increase of +3°C to +4.5°C

Drought frequency, intensity, and duration in

A south of 20°S for 2011– 2040 relative to

1979 – 2008

Penalba and Rivera (2013) 15 CMIP5 models, RCP4.5 and 8.5 Frequency increase of 10 – 20%, increase in

everity of 5 – 15%, and reduction in duration of

10 – 30%

recipitation, heavy precipitation, reduction of

CDDs in the eastern part of the region, increase

n the western part of the region by 2099

örensson et al. (2010) RCA forced with ECHAM5, A1B Increase of +2 mm day

– 1

of +5 to +15 mm,

reduction of – 10 days and increase of +5 days

Precipitation in southeastern SA by 2100 Sörensson et al. (2010) 9 CMIP3 models, A1B Increase of +0.3 to +0.5 mm day

– 1

Andes

Precipitation and temperature, increase by 2100

in the Altiplano

Minvielle and Garreaud (2011) 11 CMP3 models, A2 Precipitation: – 10% to – 30%; temperature: > 3°C

Precipitation at 5°N – 5°S and 30°S – 45°S, at

5°S – 25°S; temperature by 2100

Marengo et al. (2011a) Eta forced with HadCM3, A1B Increase of +10% to +30%, decrease of – 20% to

– 30%, increase of +3.5°C to +4.5°C

Warm nights, heavy precipitation, and CDDs

south of 15°S by 2100

Marengo et al. (2009a) PRECIS forced with HadAM3, A2 Increase of +3% to +18%, reduction of – 10 to

– 20 days, and reduction of – 75 to – 105 days

Air temperature, rainfall between 0° and 10°S,

and reduction between 10°S and 40°S

Giorgi and Diffenbaugh (2008) 23 CMIP3 models, A1B Increase of +3°C to +4°C, increase of 10%, and

reduction of – 10%

CDDs and increase of heavy precipitation by

2099

Kamiguchi et al. (2006) 20 km MRI-AGCM3.1S model, A1B Reduction of – 5 days, increase of +2 to +4%

south of 20°S

Precipitation, heavy precipitation, and CDDs by

2070 – 2099

Sörensson et al. (2010) RCA forced with ECHAM5, A1B Increases of +1 to +3 mm day

– 1

, +5 mm and of

+5 to +10 days

Summer precipitation and surface air

temperature in the Altiplano region by 2099

Minvielle and Garreaud (2011) 9 CMIP3 models, A2 Reduction in precipitation between – 10% and

– 30%, and temperature increase of +3°C

Temperature and rainfall in lowland Bolivia in

2070 – 2099

Seiler et al. (2013) 5 CMIP3 models (A1B) and 5

CMIP5 models (RCP4.5, 8.5)

Increase of 2.5°C to 5°C, reduction of 9% annual

precipitation

Precipitation in the dry season, temperature,

and evapotranspiration 2079 – 2098

Guimberteau et al. (2013) CMIP3 models, A1B – 1.1 mm; +2°C; +7%

Table 27-2 (continued)

Continued next page

1511

Central and South America Chapter 27

soil moisture for most of the land during all seasons by the end of the

21st century (see references in Table 27-2). However, the spread of

projections is high for future precipitation.

Analyses from global and regional models in tropical and subtropical

SA show common patterns of projected climate in some sectors of the

continent. Projections from CMIP3 regional and high-resolution global

models show by the end of the 21st century, for the A2 emission scenario,

a consistent pattern of increase of precipitation in SESA, northwest of

Peru and Ecuador, and western Amazonia, while decreases are projected

for northern SA, eastern Amazonia, central eastern Brazil, NEB, the

Altiplano, and southern Chile (Table 27-2). For some regions, projections

show mixed results in rainfall projections for Amazonia and the SAMS

region, suggesting high uncertainties on the projections (Table 27-2).

As for extremes, CMIP3 models and downscaling experiments show

increases in dry spells are projected for eastern Amazonia and NEB,

while rainfall extremes are projected to increase in SESA, in western

Amazonia, northwest Peru, and Ecuador, while over southern Amazonia,

NEB, and eastern Amazonia, the maximum number of consecutive dry

days tends to augment, suggesting a longer dry season. Increases in

warm nights throughout SA are also projected by the end of the 21st

century (see references in Table 27-2). Shiogama et al. (2011) suggest

that, although the CMIP3 ensemble mean assessment suggested

wetting across most of SA, the observational constraints indicate a

higher probability of drying in the eastern Amazon basin.

The CMIP5 models project an even larger expansion of the monsoon

regions in NAMS in future scenarios (Jones and Carvalho, 2013; Kitoh

et al., 2013). A comparison from eight models from CMIP3 and CMIP5

identifies some improvements in the new generation models. For

example, CMIP5 inter-model variability of temperature in summer was

lower over northeastern Argentina, Paraguay, and northern Brazil, in

the last decades of the 21st century, as compared to CMIP3. Although

Region Variable Reference Models and scenarios Projected changes

Amazon

region

Rainfall in central and eastern Amazonia and

n western Amazonia; air temperature in all

regions by 2100

Marengo et al. (2011a) Eta forced with HadCM3, A1B Precipitation: – 20% to – 30%, +20% to +30%;

emperature: +5°C to +7°C

ntensity of the South Atlantic Convergence

one and in rainfall in the South American

monsoon region, 2081– 2100

ombardi and Carvalho (2009) 10 CMIP3 models, A1B Precipitation: – 100 to – 200 mm over 20 years

Precipitation in western Amazonia during

ummer and in winter in Amazonia by 2100

Mendes and Marengo (2010) 5 CMIP3 models, A2 and ANN +1.6% in summer and – 1.5% in winter

Number of South American Low Level Jet

(

SALLJ) events east of the Andes, and the

oisture transport from Amazonia to the La

Plata basin by 2090

Soares and Marengo (2009) PRECIS forced with HadAM3, A2 +50% SALLJ events during summer,

ncrease in moisture transport by 50%

recipitation in the South American monsoon

during summer and spring, and during fall and

inter by 2100

eth et al. (2010) 9 CMIP3 models, A2 Increase of +0.15 to +0.4 mm / day,

reductions of – 0.10 to – 0.26 mm / day

Warm nights, CDDs in eastern Amazonia; heavy

precipitation in western Amazonia and in

astern Amazonia by 2100

Marengo et al. (2009a) PRECIS forced with HadAM3, A2 Increase of +12% to +15%, of 25 – 30 days in

eastern Amazonia, increase in western Amazonia

f 75 – 105 days, and reduction of – 15 to – 75

days in eastern Amazonia

ncrease in air temperature; rainfall increase

in western Amazonia and decrease in eastern

mazonia by 2100

iorgi and Diffenbaugh (2008) CMIP3 models, A1B Increase of +4°C to +6°C, increase of +10%, and

decrease between – 10% and – 30%

Reduction of CDDs and increase in heavy

precipitation by 2099

Kamiguchi et al. (2006) 20 km MRI-AGCM3.1S model, A1B Reduction of – 5 to – 10 days,

increase of +2% to +8%

nset and late demise of the rainy season in

South American Monsoon System (SAMS) by

2040 – 2050 relative to 1951– 1980

ones and Carvalho (2013) 10 CMIP5 models, RCP8.5 Onset 14 days earlier than present,

demise 17 days later than present

Precipitation in SAMS during the monsoon wet

season in 2071– 2100 relative to 1951– 1980

Jones and Carvalho (2013) 10 CMIP5 models, RCP8.5 Increase of 300 mm during the wet season

Precipitation in western Amazonia, heavy

precipitation in northern Amazonia and in

southern Amazonia, CDDs in western Amazonia

and increase by 2099

Sörensson et al. (2010) RCA forced with ECHAM5, A1B Increase of +1 to +3 mm day

– 1

, reduction of – 1

to – 3 mm, increase of +5 to +10 mm, decrease of

– 5 to – 10 days, increase of +20 to +30 days

Northeastern

Brazil

Rainfall and temperature in the entire region

by 2100

Marengo et al. (2011a) Eta forced with HadCM3, A1B Precipitation: – 20% to +20%;

temperature: +3°C to +4°C

Warm nights, CDDs, heavy precipitation by 2100 Marengo et al. (2009a) PRECIS forced with HadAM3, A2 Increase of +18% to +24%, of +25 to +30 days,

and –15 to –75 days

Air temperature and precipitation by 2100 Giorgi and Diffenbaugh (2008) 23 CMIP3 models, A1B Increase of +2°C to +4°C,

reduction of – 10% to – 30%

CDDs and heavy precipitation by 2099 Kamiguchi et al. (2006) 20 km MRI-AGCM3.1S model, A1B Reduction of – 5% to – 10%,

increase of +2% to +6%

Precipitation, heavy precipitation, and CDDs

by 2099

Sörensson et al. (2010) RCA forced with ECHAM5, A1B Increase of +1 to +2 mm day

– 1

, increase of +5 to

+10 mm, and increase of +10 to +30 days

Table 27-2 (continued)

1512

Chapter 27 Central and South America

Central America/Mexico

(6)

Amazon

(7)

Northeast Brazil

(8)

West coast South America

(9)

Southeast South America

(10)

1900 1950 2000 2050 2100

900 1950 2000 2050 2100

1900 1950 2000 2050 2100

–

°C

–2

°C

–2

°C

–2

°C

–2

°C

–20

–40

–

–40

–20

–40

–20

–40

–20

–40

ear-surface air temperature (land)

Precipitation (land)

atural

Historical

atural

OverlapOverlap

CP2.6

RCP8.5

bserved

Figure 27-1 | Observed and simulated variations in past and projected future annual average temperature over the Central and South American regions deﬁned in IPCC

(2012a). Black lines show various estimates from observational measurements. Shading denotes the 5th to 95th percentile range of climate model simulations driven with

“historical” changes in anthropogenic and natural drivers (63 simulations), historical changes in “natural” drivers only (34), the Representative Concentration Pathway (RCP)2.6

emissions scenario (63), and RCP8.5 (63). Data are anomalies from the 1986–2006 average of the individual observational data (for the observational time series) or of the

corresponding historical all-forcing simulations. Further details are given in Table SM21-5.

1513

Central and South America Chapter 27

o major differences were observed in both precipitation data sets,

CMIP5 inter-model variability was lower over northern and eastern

Brazil in the summer by 2100 (Blázquez and Nuñez, 2013; Jones and

Carvalho, 2013).

The projections from the CMIP5 models at regional level for CA and SA

(using the same regions from SREX) are shown in Figure 27-1, and update

some of these previous projections based on SRES A2 and B2 emission

scenarios from CMIP3. Figure 27-1 shows that in relation to the baseline

period 1986–2005, for CA and northern SA–Amazonia, temperatures are

projected to increase by approximately 0.6°C and 2°C for the RCP2.6

scenario, and by 3.6°C and 5.2°C for the RCP8.5 scenario. For the rest

of SA, increases by about 0.6°C to 2°C are projected for the RCP4.5 and

by about 2.2°C to 7°C for the RCP8.5 scenario. The observed records

show increases of temperature from 1900 to 1986 by about 1°C. For

precipitation, while for CA and northern SA–Amazonia precipitation is

projected to vary between +10 and –25% (with a large spread among

models). For NEB, there is a spread among models between +30 and

–30%, making it hard to identify any projected rainfall change. This

spread is much lower in the western coast of SA and SESA, where the

spread is between +20 and –10% (Chapter 21; Box 21-3).

CMIP5-derived RCP8.5 projections for the late 21st century, as depicted

in Figure 27-2, follow: CA – mean annual warming of 2.5ºC and rainfall

eduction of 10%, and reduction in summertime precipitation; SA –

mean warming of 4ºC, with rainfall reduction up to 15% in tropical SA

east of the Andes, and an increase of about 15 to 20% in SESA and in

other regions of the continent. Changes shown for the mid-21st century

are small. Both Figures 27-1 and 27-2 illustrate that there is some degree

of uncertainty on climate change projections for regions, particularly for

rainfall in CA and tropical SA.

27.2.2. Non-Climatic Stressors

27.2.2.1. Trends and Projections

in Land Use and Land Use Change

Land use change is a key driver of environmental degradation for the

region that exacerbates the negative impacts from climate change

(Sampaio et al., 2007; Lopez-Rodriguez and Blanco-Libreros, 2008). The

high levels of deforestation observed in most of the countries in the

region have been widely discussed in the literature as a deliberate

development strategy based on the expansion of agriculture to satisfy

the growing world demand for food, energy, and minerals (Benhin,

2006; Grau and Aide, 2008; Müller et al., 2008). Land is facing increasing

pressure from competing uses, among them cattle ranching, food, and

bioenergy production. The enhanced competition for land increases the

Annual Precipitation Change

Solid Color

Strong

agreement

Very strong

agreement

Little or

no change

Gray

Divergent

changes

Diagonal LinesWhite Dots

Annual Temperature Change

late 21st centurymid 21st century

Difference from

1986–2005 mean (%)

Difference from

1986–2005 mean (˚C)

–20 0 20 40

late 21st centurymid 21st century

RCP8.5RCP2.6

02 46

Figure 27-2 | Projected changes in annual average temperature and precipitation. CMIP5 multi-model mean projections of annual average temperature changes (left panel) and

average percent changes in annual mean precipitation (right panel) for 2046–2065 and 2081–2100 under RCP2.6 and 8.5, relative to 1986–2005. Solid colors indicate areas

with very strong agreement, where the multi-model mean change is greater than twice the baseline variability (natural internal variability in 20-yr means) and ≥90% of models

agree on sign of change. Colors with white dots indicate areas with strong agreement, where ≥66% of models show change greater than the baseline variability and ≥66% of

models agree on sign of change. Gray indicates areas with divergent changes, where ≥66% of models show change greater than the baseline variability, but <66% agree on

sign of change. Colors with diagonal lines indicate areas with little or no change, where <66% of models show change greater than the baseline variability, although there may

be signiﬁcant change at shorter timescales such as seasons, months, or days. Analysis uses model data and methods building from WGI AR5 Figure SPM.8. See also Annex I of

WGI AR5. [Boxes 21-2 and CC-RC]

1514

Chapter 27 Central and South America

isk of land use changes, which may lead to negative environmental

and socioeconomic impacts. Agricultural expansion has relied in many

cases on government subsidies, which have often resulted in lower land

productivity and more land speculation (Bulte et al., 2007; Roebeling and

Hendrix, 2010). Some of the most affected areas due to the expansion of

the agricultural frontier are fragile ecosystems such as the edges of the

Amazon forest in Brazil, Colombia, Ecuador, and Peru, and tropical Andes

including the Paramo, where activities such as deforestation, agriculture,

cattle ranching, and gold mining are causing severe environmental

degradation (ECLAC, 2010d), and the reduction of environmental services

provided by these ecosystems.

Deforestation rates for the region remain high in spite of a reducing

trend in the last decade (Ramankutty et al., 2007; Fearnside, 2008).

Brazil is by far the country with the highest area of forest loss in the

world according to the latest Food and Agriculture Organization (FAO)

statistics (2010): 21,940 km

–1

, equivalent to 39% of world deforestation

for the period 2005–2010. Bolivia, Venezuela, and Argentina follow in

deforested area (Figure 27-3), with 5.5, 5.2, and 4.3% of the total world

deforestation, respectively. The countries of CA and SA lost a total of

38,300 km

of forest per year in that period (69% of the total world

deforestation; FAO, 2010). These numbers are limited by the fact that

many countries do not have comparable information through time,

particularly for recent years. Aide et al. (2013) completed a wall-to-wall

analysis for the region for the period 2001–2010, analyzing not only

deforestation but also reforestation, and reported very different results

than FAO (2010) for some countries where reforestation seems to be

higher than deforestation, particularly in Honduras, El Salvador, Panama,

Colombia, and Venezuela. For Colombia and Venezuela, these results

are contradictory with country analyses that align better with the FAO

data (Rodríguez, J.P. et al., 2010; Armenteras et al., 2013).

Deforestation in the Amazon forest has received much international

attention in the last decades, both because of its high rates and its

rich biodiversity. Brazilian Legal Amazon is now one of the best-

monitored ecosystems in terms of deforestation since 1988 (INPE, 2011).

Deforestation for this region peaked in 2004 and has steadily declined

since then to a lowest value of 4656 km

–1

for the year 2012 (see

Figure 27-4). Such reduction results from a series of integrated policies

to control illegal deforestation, particularly enforcing protected areas,

which now shelter 54% of the remaining forests of the Brazilian Amazon

(Soares-Filho et al., 2010). Deforestation in Brazil is now highest in the

Cerrado (drier ecosystem south of Amazon), with an average value of

14,179 km

–

for the period 2002–2008 (FAO, 2009).

The area of forest loss in CA is considerably less than in SA, owing to

smaller country sizes (Carr et al., 2009), but when relative deforestation

rates are considered, Honduras and Nicaragua show the highest values

for CA and SA (FAO, 2010). At the same time, CA includes some countries

where forest cover shows a small recovery trend in the last years: Costa

Rica, El Salvador, Panama, and possibly Honduras, where data are

conflicting in the literature (FAO, 2010; Aide et al., 2013). This forest

transition is the result of (1) economies less dependent on agriculture,

and more on industry and services (Wright and Samaniego, 2008); (2)

processes of international migration with the associated remittances

(Hecht and Saatchi, 2007); and (3) a stronger emphasis on the recognition

of environmental services of forest ecosystems (Kaimowitz, 2008). The

same positive trend is observed in some SA countries (Figure 27-3).

However, a substantial amount of forest is gained through (single-crop)

plantations, most noticeably in Chile (Aguayo et al., 2009), which has a

much lower ecological value than the depleted natural forests (Echeverría

et al., 2006; Izquierdo et al., 2008).

Land degradation is also an important process compromising extensive

areas of CA and SA very rapidly. According to data from the Global Land

Degradation Assessment and Improvement (GLADA) project of the

Global Environmental Facility (GEF), additional degraded areas reached

16.4% of the entire territory of Paraguay, 15.3% of Peru, and 14.2% of

Ecuador for the period 1982–2002. In CA, Guatemala shows the highest

proportion of degraded land, currently at 58.9% of the country’s territory,

followed by Honduras (38.4%) and Costa Rica (29.5%); only El Salvador

shows a reversal of the land degradation process, probably due to eased

land exploitation following intensive international migratory processes

(ECLAC, 2010d).

Deforestation and land degradation are attributed mainly to increased

extensive and intensive agriculture. Two activities have traditionally

3500300025002000150010005000

Uruguay

Chile

Costa Rica

Guatemala

Nicaragua

Honduras

Argentina

Venezuela

Bolivia

Brazil

zil

via

zil

ela

via

ela

ala

ile

Reforestation

(+2.79%)

(+0.23%)

(+0.90%)

(–1.47%)

(–2.11%)

(–2.16%)

(–0.80%)

(–0.61%)

(–0.42%)

(–0.53%)

Deforestation

21,940

(km

–1

)

Observed rate of change:

Figure 27-3 | Forest cover change per year for selected countries in Central and

South America (2005–2010). Notice three countries listed with a positive change in

forest cover (based on data from FAO, 2010).

12,911

7464

7000

6418

4656

11,651

14,286

19,014

7,772

25,396

21,651

18,16518,226

30,000

25,000

20,000

15,000

5000

2000 2002 2004 2006 2008 2010 2012

10,000

Annual Deforestation Rate (km

–1

)

igure 27-4 | Deforestation rates in Brazilian Amazonia (km² yr

–

)

based on

measurements by the PRODES project (INPE, 2011).

1515

Central and South America Chapter 27

ominated the agricultural expansion: soy production (only in SA) and

beef. But, more recently, biomass for biofuel production has become as

important (Nepstad and Stickler, 2008) with some regions also affected

by oil and mining extractions. Deforestation by small farmers, coming

mainly from families who migrate in search for land, is relatively low:

extensive cattle production is the predominant land use in deforested

areas of tropical and subtropical Latin America (Wassenaar et al., 2007).

Cattle is the only land use variable correlated with deforestation in

Colombia (Armenteras et al., 2013), and in the Brazilian Amazon the

peak of deforestation in 2004 (Figure 27-4) was primarily the result of

increased cattle ranching (Nepstad et al., 2006). Mechanized farming,

agro-industrial production, and cattle ranching are the major land

use change drivers in eastern Bolivia but subsistence agriculture by

indigenous colonists is also important (Killeen et al., 2008).

In recent years, soybean croplands have expanded continuously in SA,

becoming increasingly more important in the agricultural production of

the region. Soybean-planted area in Amazonian states (mainly Mato

Grosso) in Brazil expanded 12.1% per year during the 1990s, and 16.8%

per year from 2000 to 2005 (Costa et al., 2007). This landscape-scale

conversion from forest to soy and other large-scale agriculture can alter

substantially the water balance for large areas of the region, resulting

in important feedbacks to the local climate (Hayhoe et al., 2011; Loarie

et al., 2011; see Section 27.3.4.1).

Soybean and beef production have also impacted other ecosystems

next to the Amazon, such as the Cerrado (Brazil) and the Chaco dry

forests (Bolivia, Paraguay, Argentina, and Brazil). Gasparri et al. (2008)

estimated carbon emissions from deforestation in northern Argentina,

and concluded that deforestation in the Chaco forest has accelerated

in the past decade from agricultural expansion and is now the most

important source of carbon emissions for that region. In northwest

Argentina (Tucumán and Salta provinces), 14,000 km

of dry forest were

cleared from 1972 to 2007 as a result of technological improvements and

increasing rainfall (Gasparri and Grau, 2009). Deforestation continued

during the 1980s and 1990s, resulting in cropland area covering up to

63% of the region by 2005 (Viglizzo et al., 2011). In central Argentina

(northern Córdoba province), cultivated lands have increased from 3 to

30% (between 1969 and 1999); and the forest cover has decreased from

52.5 to 8.2%. This change has also been attributed to the synergistic

effect of climatic, socioeconomic, and technological factors (Zak et al.,

2008). Losses in the Atlantic forest are estimated in 29% of the original

area in 1960, and in 28% of the Yunga forest area, mainly due to cattle

ranching migration from the Pampas and Espinal (Viglizzo et al., 2011).

Palm oil is a significant biofuel crop also linked to recent deforestation

in tropical CA and SA. Its magnitude is still small compared with

deforestation related to soybean and cattle ranching, but is considerable

for specific countries and expected to increase due to increasing demands

for biofuels (Fitzherbert et al., 2008). The main producers of palm oil in

the region are Colombia and Ecuador, followed by Costa Rica, Honduras,

Guatemala, and Brazil; Brazil has the largest potential for expansion,

as nearly half of the Amazonia is suitable for oil palm cultivation (Butler

and Laurance, 2009). Palm oil production is also growing in the

Amazonian region of Peru, where 72% of new plantations have expanded

into forested areas, representing 1.3% of the total deforestation for that

country for the years 2000–2010 (Gutiérrez-Vélez et al., 2011).

owever, forests are not the only important ecosystems threatened in

the region. An assessment of threatened ecosystems in SA by Jarvis et

al. (2010) concluded that grasslands, savannahs, and shrublands are

more threatened than forests, mainly from excessively frequent fires

(>1 yr

–1

) and grazing pressure. An estimation of burned land in LA by

Chuvieco et al. (2008) also concluded that herbaceous areas presented

the highest occurrence of fires. In the Río de la Plata region (central-

east Argentina, southern Brazil, and Uruguay), grasslands decreased from

67.4 to 61.4% between 1985 and 2004. This reduction was associated

with an increase in annual crops, mainly soybean, sunflower, wheat,

and maize (Baldi and Paruelo, 2008).

Even with technological changes that might result in agricultural

intensification, the expansion of pastures and croplands is expected to

continue in the coming years (Wassenaar et al., 2007; Kaimowitz and

Angelsen, 2008), particularly from an increasing global demand for food

and biofuels (Gregg and Smith, 2010) with the consequent increase in

commodity prices. This agricultural expansion will be mainly in LA and

sub-Saharan Africa as these regions hold two-thirds of the global land

with potential to expand cultivation (Nepstad and Stickler, 2008). It is

important to consider the policy and legal needs to keep this process of

large-scale change under control as much as possible; Takasaki (2007)

showed that policies to eliminate land price distortions and promote

technological transfers to poor colonists could reduce deforestation. It

is also important to consider the role of indigenous groups; there is a

growing acknowledgment that recognizing the land ownership and

authority of indigenous groups can help central governments to better

manage many of the natural areas remaining in the region (Oltremari

and Jackson, 2006; Larson, 2010). The impact of indigenous groups on

land use change can vary: de Oliveira et al. (2007) found that only 9%

of the deforestation in the Peruvian Amazon between 1999 and 2005

happened in indigenous territories, but Killeen et al. (2008) found that

Andean indigenous colonists in Bolivia were responsible for the largest

land cover changes in the period 2001–2004. Indigenous groups are

important stakeholders in many territories in the region and their well-

being should be considered when designing responses to pressures on

the land by a globalized economy (Gray et al., 2008; Killeen et al., 2008).

27.2.2.2. Trends and Projections in Socioeconomic Conditions

Development in the region has traditionally displayed four characteristics:

low growth rates, high volatility, structural heterogeneity, and very unequal

income distribution (ECLAC, 2008; Bárcena, 2010). This combination of

factors has generated high and persistent poverty levels (45% for CA and

30% for SA for year 2010), with the rate of poverty being generally higher

in rural than urban areas (ECLAC, 2009b). SA has based its economic

growth in natural resource exploitation (mining, energy, agricultural),

which involves direct and intensive use of land and water, and in energy-

intensive and, in many cases, highly polluting natural resource-based

manufactures. In turn, CA has exploited its proximity to the North

American market and its relatively low labor costs (ECLAC, 2010e). The

region shows a marked structural heterogeneity, where modern

production structures coexist with large segments of the population with

low productivity and income levels (ECLAC, 2010g). The gross domestic

product (GDP) per capita in SA is twice that of CA; in addition, in the

latter, poverty is 50% higher (see Figure 27-5).

1516

Chapter 27 Central and South America

The 2008 financial crisis reached CA and SA through exports and credits,

remittances, and worsening expectations by consumers and producers

(Bárcena, 2010; Kacef and López-Monti, 2010). This resulted in the

sudden stop of six consecutive years of robust growth and improving

social indicators (ECLAC, 2010e), which contributed to higher poverty

in 2009 after 6 years where poverty had declined by 11%. Poverty rates

fell from 44 to 33% of the total population from 2003 to 2008 (Figure

27-5), leaving 150 million people in this situation while extreme poverty

diminished from 19.4 to 12.9% (which represents slightly more than 70

million people) (ECLAC, 2009b).

In the second half of 2009, industrial production and exports began to

recover and yielded a stronger economic performance (GDP growth of

6.4% in SA and 3.9% in CA in 2010; ECLAC, 2012b). SA benefited the

most because of the larger size of their domestic markets and the

greater diversification of export markets. Conversely, slower growth was

observed in CA, with more open economies and a less diversified

portfolio of trading partners and a greater emphasis on manufacturing

trade (ECLAC, 2010g).

The region is expected to continue to grow in the short term, albeit at

a pace that is closer to potential GDP growth, helped by internal

demand as the middle class becomes stronger and as credit becomes

more available. In SA, this could be boosted by external demand from

the Asian economies as they continue to grow at a rapid pace. The

macroeconomic challenge is to act counter cyclically, creating conditions

for productive development that is not based solely on commodity

exports (ECLAC, 2010f).

In spite of its economic growth, CA and SA still display high and

persistent inequality: most countries have Gini coefficients between

.5 and 0.6, whereas the equivalent figures in a group of 24 developed

countries vary between under 0.25 and around 0.4. The average per

capita income of the richest 10% of households is approximately 17 times

that of the poorest 40% of households (ECLAC, 2010g). Nevertheless,

during the first decade of the century, prior to the financial crisis, the

region has shown a slight but clear trend toward a more equitable

distribution of income and a stronger middle class population, resulting

in a higher demand for goods (ECLAC, 2010g,h, 2011b). Latin American

countries also reported gains in terms of human development, although

these gains have slowed down slightly over recent years. In comparative

terms, as measured by the Human Development Index (HDI), the

performance of countries varied greatly in 2007 (from Chile with 0.878

and Argentina with 0.866 to Guatemala with 0.704 and Nicaragua with

0.699), although those with lower levels of HDI showed notably higher

improvements than countries with the highest HDI (UNDP, 2010).

Associated with inequality are disparities in access to water, sanitation,

and adequate housing for the most vulnerable groups—for example,

indigenous peoples, Afro-descendants, children, and women living in

poverty—and in their exposure to the effects of climate change. The

strong heterogeneity of subnational territorial entities in the region

takes the form of high spatial concentration and persistent disparities

in the territorial distribution of wealth (ECLAC, 2010g,h, 2011b).

The region faces significant challenges in terms of environmental

sustainability and adaptability to a changing climate (ECLAC, 2010h),

resulting from the specific characteristics of its population and economy

already discussed and aggravated with a significant deficit in infrastructure

development. CA and SA countries have made progress in incorporating

environmental protection into decision-making processes, particularly

in terms of environmental institutions and legislation, but there are still

difficulties to effectively incorporate environmental issues into relevant

public policies (ECLAC, 2010h). Although climate change imposes new

challenges, it also provides an opportunity to shift development and

economic growth patterns toward a more environmentally friendly course.

27.3. Impacts, Vulnerabilities,

and Adaptation Practices

27.3.1. Freshwater Resources

CA and SA are regions with high average but unevenly distributed water

resources availability (Magrin et al., 2007a). The main user of water is

agriculture, followed by the region’s 580 million inhabitants (including

the Caribbean), of which 86% had access to water supply by 2006

(ECLAC, 2010b). According to the International Energy Agency (IEA),

the region meets 60% of its electricity demand through hydropower

generation, which contrasts with the 20% average contribution of other

regions (see Table 27-6 and case study in Section 27.6.1).

27.3.1.1. Observed and Projected Impacts and Vulnerabilities

In CA and SA there is much evidence of changing hydrologic related

conditions. The most robust trend for major rivers is found in the sub-

basins of the La Plata River basin (high confidence, based on robust

(

a) GDP per capita

(b) % poverty

(%)

(US$ per capita)

1000

2000

3000

000

19951990 201020052000

outh America Central America

Figure 27-5 | Evolution of GDP per capita and poverty (income below US$2 per day)

from 1990–2010: Central and South America (US$ per inhabitant at 2005 prices and

percentages) (ECLAC, 2011c; 2012a).

1517

Central and South America Chapter 27

vidence, high agreement). This basin, second only to the Amazon in

size, shows a positive trend in streamflow in the second half of the

20th century at different sites (Pasquini and Depetris, 2007; Krepper et

al., 2008; Saurral et al., 2008; Amsler and Drago, 2009; Conway and

Mahé, 2009; Dai et al., 2009; Krepper and Zucarelli, 2010; Dai, 2011;

Doyle and Barros, 2011). An increase in precipitation and a reduction in

evapotranspiration from land use changes have been associated with the

trend in streamflows (Saurral et al., 2008; Doyle and Barros, 2011), with

he former being more important in the southern sub-basins and the

latter in the northern ones (Doyle and Barros, 2011; see Section 27.2.1).

Increasing trends in streamflows have also been found in the Patos

Lagoon in southern Brazil (Marques, 2012) and Laguna Mar Chiquita

(a closed lake), and in the Santa Fe Province, both in Argentina, with

ecological and erosive consequences (Pasquini et al., 2006; Rodrigues

Capítulo et al., 2010; Troin et al., 2010; Venencio and García, 2011; Bucher

and Curto, 2012).

Continued next page

Country Documented massifs Latitude

Signiﬁ cant changes recorded

References

Variable

code

number

Description of trend [period of observed trend]

Venezuela

ordillera de Mérida 10°N 1 +300 to +500 m [between LIA maximum and today] Morris et al. (2006); Polissar

et al. (2006)

5 Accelerated melting [since 1972]. Risk of disappearing completely, as equilibrium line

altitude is close to the highest peak (Pico Bolívar, 4979 m)

Colombia

Parque Los Nevados 4°50’N 3 LIA maximum between 1600 and 1850 Ceballos et al. (2006); Ruiz

et al. (2008); Poveda and

ineda (2009); IDEAM

(2012); Rabatel et al. (2013)

Sierra Nevada del Cocuy 6°30’N 3 Many small / low elevation glaciers (<5000 meters above sea level) have disappeared.

ierra Nevada de Santa

Marta

0°40’N 3 – 60 to – 84% [1850 – 2000]; – 50% [last 50 years]; – 10 to – 50% [past 15 years];

retreat 3.0 km² year

–

[since 2000]

Ecuador

ntisana 0°28’S 1 +300 m [between the middle of the 18th century (LIA maximum) and the last

decades of the 20th century]; about +200 m [20th century]

rancou et al. (2007); Vuille

et al. (2008); Jomelli et

al. (2009); Cáceres (2010);

Rabatel et al. (2013)

Chimborazo and

Carihuayrazo

1°S 3 About – 45% [1976 – 2006]. Glaciers below 5300 m in process of extinction

Peru

Cordillera Blanca 9°S 1 About +100 m [between LIA maximum and beginning of the 20th century];

+150 m [20th century]

Raup et al. (2007); Jomelli et

al. (2009); Mark et al. (2010);

UGHR (2010); Bury et al.

(2011); Baraer et al. (2012);

Rabatel et al. (2013)

3 – 12 to – 17% [18th century]; – 17 to – 20% [19th century]; – 20 to – 35% [1960s – 2000s]

4 – 8 m decade

– 1

[since 1970] (Yanamarey glacier)

8 +1.6% (±1.1) (watersheds with >20% glacier area)

8 Seven out of nine watersheds decreasing dry-season discharge

Coropuna volcano 15°33’S 3 – 26% [1962 – 2000] Racoviteanu et al. (2007)

Cordillera Vilcanota 13°55’S 3 10 times faster [in 1991– 2005 compared to 1963 – 2005] Thompson et al. (2006, 2011)

3, 5 About – 30% area and about – 45% volume [since 1985] Salzmann et al. (2013)

Bolivia

Cordillera Real and

Cordillera Quimsa Cruz

16°S 1 +300 m [between LIA maximum and late 20th century]; +180 to +200 m [20th century] Rabatel et al. (2006, 2008);

Francou et al. (2007); Vuille

et al. (2008); Soruco et al.

(2009); Gilbert et al. (2010);

Jomelli et al. (2011); Rabatel

et al. (2013)

3 – 48% [1976 – 2006] in the Cordillera Real; Chacaltaya vanished [in 2010].

5 Zongo glacier has lost a mean of 0.4 m (w.e.) year

–

[in the 1991– 2011 period];

glaciers in the Cordillera Real lost 43% of their volume [1963 – 2006; maximum rate

of loss in 1976 – 2006].

2 +1.1°C ± 0.2°C [over the 20th century] at about 6340 meters above sea level

Caquella rock glacier

(South Bolivian Altiplano)

21°30’S 7 Evidence of recent degradation Francou et al. (1999)

Table 27-3 | Observed trends related to Andean cryosphere. (LIA = Little Ice Age; w.e. = water equivalent.)

Region

Documented

m a s s i f s / s i t e s

Latitude

Signiﬁ cant changes recorded

References

Variable

code

number

Value of trend [period of observed trend]

Chile, Argentina,

Bolivia, and

Argentinean

Patagonia

South of

15°S

6 No signiﬁ cant trend Foster et al. (2009)

Desert Andes

(17°S – 31°S)

Huasco basin

glaciers

29°S 5 − 0.84 m (w.e.) year

– 1

[2003 / 2004 – 2007/ 2008] Nicholson et al. (2009);

Gascoin et al. (2011);

Rabatel et al. (2011)

(b) Extratropical Andean cryosphere (glaciers, snowpack, runoff effects) trends.

(a) Andean tropical glacier trends.

1518

Chapter 27 Central and South America

There is no clear long-term trend for the Amazon River. Espinoza et al.

(2009a, 2011) showed that the 1974–2004 apparent stability in mean

discharge at the main stem of the Amazon in Obidos is explained by

opposing regional features of Andean rivers (e.g., increasing trends

during the high-water period in Peruvian and Colombian Amazons and

decreasing trend during the low-water period in Peruvian and Bolivian

Amazons (Lavado et al., 2012). In recent years extremely low levels were

experienced during the droughts of 2005 and 2010, while record high

levels were detected during the 2009 and 2012 floods (Section 27.2.1).

Major Colombian rivers draining to the Caribbean Sea (Magdalena and

Cauca) exhibit decreasing trends along their main channels (Carmona

and Poveda, 2011), while significant trends are absent for all other

major large rivers in NEB and northern SA (Dai et al., 2009). Dai (2011)

showed a drying trend in CA rivers.

A rapid retreat and melting of the tropical Andes glaciers of Venezuela,

Colombia, Ecuador, Peru, and Bolivia has been further reported following

the IPCC AR4, through use of diverse techniques (high confidence, based

Region

Documented

m a s s i f s / s i t e s

Latitude

Signiﬁ cant changes recorded

References

Variable

code

number

Value of trend [period of observed trend]

Central Andes

(31°S – 36°S)

iloto / Las Cuevas 32°S 5 – 10.50 m (w.e.) [last 24 years] Leiva et al. (2007)

Aconcagua basin

laciers

33°S 3 – 20% [last 48 years] Pellicciotti et al. (2007);

own et al. (2008)

3 – 14% [1955 – 2006]

Signiﬁ cant decrease in Aconcagua basin streamﬂ ow

Central Andes

laciers

33°S – 36°S 3 – 3% [since 1955] Le Quesne et al. (2009)

4 − 50 to − 9 m year

−

[during 20th century]

– 0.76 to – 0.56 m (w.e.) year

– 1

[during 20th century]

Central Andes 1 +122 ± 8 m (winter) and +200 ± 6 m (summer) [1975 – 2001] Carrasco et al. (2005)

nowpack 30°S – 37°S 6 Positive, though nonsigniﬁ cant, linear trend [1951– 2005] Masiokas et al. (2006); Vich

et al. (2007); Vicuña et al.

(

2013)

8 Mendoza River streamﬂ ow: possible link to rising temperatures and snowpack /

lacier effects. Not conclusive; increase in high and low ﬂ ows possibly associated

with increase in temperature and effects on snowpack

Morenas Coloradas

ock glacier

32°S – 33°S 7Signiﬁ cant change in active layer possibly associated with warming processes Trombotto and Borzotta

(

2009)

Cryosphere in the

ndes of Santiago

33.5°S 5 Expansion of thermokarst depressions Bodin et al. (2010)

Basins 28°S – 47°S 8Non-signiﬁ cant increase in February runoff; possible increase of glacier melt

[

1950 – 2007]

Casassa et al. (2009)

30°S – 40°S 8Signiﬁ cant negative timing trend (centroid timing date shifting toward earlier in the

year) for 23 out of the 40 analyzed series

Cortés et al. (2011)

Patagonian

Andes

(36°S – 55°S)

Basins 28°S – 47°S 8 Not signiﬁ cant increase in February runoff trends that might suggest an increase of

glacier melt in the Andes [1950 – 2007]

Casassa et al. (2009)

Northwest

Patagonia

38°S – 45°S 4 Recession of six glaciers based on aerial photograph analysis Masiokas et al. (2008)

Proglacial lakes 40°S – 50°S 8 Summertime negative trend on lakes indicating that melt water is decreasing Pasquini et al. (2008)

Casa Pangue glacier 41°S 5 − 2.3 ± 0.6 m (w.e.) year

–

[1961– 1998] Bown and Rivera (2007)

4 − 3.6 ± 0.6 m year

– 1

[1981– 1998]

Manso Glacier 41°S 8 Reduction in discharge associated with reduction in melt and precipitation Pasquini et al. (2013)

Patagonian Ice Field 47°S – 51°S 5 – 1.6 m (w.e.) year

– 1

or – 27.9 ± 11 km

(w.e.) year

– 1

[2002 – 2006] Chen et al. (2007)

Northern

Patagonian Ice Field

47°S 8 Glacial lake outburst ﬂ ood possible response to retreat of Calafate glacier [20th

century]

Harrison et al. (2006)

Southern

Patagonian Ice Field

48°S – 51°S 4 Larger retreating rates observed on the west side coinciding with lower elevations of

equilibrium line altitudes

Barcaza et al. (2009)

Northern Patagonian,

Southern Patagonian,

and Cordillera

Darwin ice ﬁ elds

47°S – 51°S,

54°S

4 5.7 to 12.2 km [1945 – 2005] Lopez et al. (2010)

Gran Campo Nevado 53°S 4 – 2.8% of glacier length per decade [1942 – 2002] Schneider et al. (2007)

3 – 2.4% per decade [1942 – 2002]

Cordón Martial

glaciers

54°S 5 Slow retreat from late LIA. Acceleration started 60 years ago. Sterlin and Iturraspe (2007)

Variable coding: (1) Increase in equilibrium line altitude; (2) atmospheric warming revealed by englacial temperature measured at high elevation; (3) area reduction; (4) frontal

retreat; (5) volume reduction; (6) snow cover; (7) rock glaciers; (8) runoff change.

Table 27-3(b) (continued)

1519

Central and South America Chapter 27

Continued next page

Region Basins studied

Variable

code

number

Projected change Period

General circulation model

(greenhouse gas scenario)

References

Río de La Plata

Basin and

Southeastern

South America

araná River 1 +4.9% (not robust) 2081– 2100 CMIP3 models (A1B) Nohara et al. (2006)

10 to +20% 2100 Eta-HadCM3 (A1B) Marengo et al.

(2011a)

18.4% (signiﬁ cant) 2075 – 2100 CMIP3 models (A1B) Nakaegawa et al.

(2013a)

io Grande 1 +20 to – 20% Different periods 7 CMIP3 models Gosling et al. (2011);

Nóbrega et al. (2011);

odd et al. (2011)

Itaipu Power Plant

(on the Paraná River)

1 Left bank: − 5 to −15%; right bank: +30% 2010 – 2040 CCCMA–CGCM2 (A2) Rivarola et al. (2011)

0 to − 30% 2070 – 2100

oncórdia River 1 – 40% 2070 – 2100 HadRM3P (A2, B2) Perazzoli et al. (2013)

Carcarañá River 2 Increase 2010 – 2030 HadCM3 (A2) Venencio and García

(

2011)

Slight reduction

Amazon Basin

Peruvian Amazon

asins

1 Increase in some basins; reduction in others Three time slices BCM2, CSMK3 and MIHR (A1B, B1) Lavado et al. (2011)

Basins in region of

lto Beni, Bolivia

1 Increase and reduction 2070 – 2100 CMIP3 models (A1B) Fry et al. (2012)

Always reduction

5 Increase in water stress

aute and

Tomebamba Rivers

Increase in some scenarios; reduction in others 2070 – 2100 CMIP3 models (A1B) Buytaert et al. (2011)

Amazon River 1 +5.4% (not robust) 2081– 2100 CMIP3 models (A1B) Nohara et al. (2006)

+6% 2000– 2100 ECBilt–CLIO–VECODE (A2) Aerts et al. (2006)

+3.7% (signiﬁ cant) 2075 – 2100 CMIP3 models (A1B) Nakaegawa et al.

(2013a)

At Óbidos Station: no change in high ﬂ ow;

reduction in low ﬂ ow

2046 – 2065/

2079 – 2098

8 AR4 GCMs (B1, A1B, and A2) Guimberteau et al.

(2013)

Amazon and Orinoco

Rivers

1 – 20% 2050s HadCM3 (A2) Palmer et al.(2008)

Basins in Brazil 1 Consistent decrease 2050s HadCM3 and CMIP3 models

(A1B)

Arnell and Gosling

(2013)

Tropical Andes

Colombian glaciers 4 Disappearance by 2020s Linear extrapolation Poveda and Pineda

(2009)

Cordillera Blanca

glacierized basins

1 Increase for next 20 – 50 years, reduction

afterwards

2005 – 2020 Temperature output only (B2) Chevallier et al.

(2011)

4 Area – 38 to – 60%. Increased seasonality 2050 Not speciﬁ ed (A1, A2, B1, B2) Juen et al. (2007)

Area – 49 to –75%. Increased seasonality 2080

Increased seasonality 2030 16 CMIP3 models (A1B, B1) Condom et al. (2012)

Basins providing

water to cities of

Bogotá, Quito, Lima,

and La Paz

5 Inner tropics: only small change; increase in

precipitation and increase in evapotranspiration

2010 – 2039 and

2040 – 2069

19 CMIP3 models (A1B, A2) Buytaert and De

Bièvre (2012)

Outer tropics: severe reductions; decrease in

precipitation and increase in evapotranspiration

Central Andes

Limarí River 1 – 20 to – 40% 2070 – 2100 HadCM3 (A2, B2) Vicuña et al. (2011)

– 20% 2010 – 2040 15 CMIP3 models (A1B, B2, B1) Vicuña et al. (2012)

– 30 to – 40%; change in seasonality 2070 – 2100

Maipo River 1 – 30% Three 30-year periods HadCM3 (A2, B2) ECLAC (2009a);

Melo et al. (2010);

Meza et al. (2012)

5 Unmet demand up to 50% 2070 – 2090

Mataquito River 1 Reduction in average and low ﬂ ows

Increase in high ﬂ ows

Three 30-year periods CMIP3 (A2, B1) and CMIP5

(RCP4.5 and 8.5) models

Demaria et al. (2013)

Maule and Laja

Rivers

1 – 30% Three 30-year periods HadCM3 (A2, B2) ECLAC (2009a);

McPhee et al. (2010)

Bío Bío River 1 – 81 to +7% 2070 – 2100 8 GCMs (6 SRES) Stehr et al. (2010)

Limay River 1 –10 to – 20% 2080s HadCM2 (NS) Seoane and López

(2007)

Table 27-4 | Synthesis of projected climate change impacts on hydrological variables in Central American and South American basins and major glaciers.

1520

Chapter 27 Central and South America

on robust evidence, high agreement). Rabatel et al. (2013) provides a

synthesis of these studies (specific papers are presented in Table 27-3a).

Tropical glaciers’ retreat has accelerated in the second half of the 20th

century (area loss between 20 and 50%), especially since the late 1970s

in association with increasing temperature in the same period (Bradley

et al., 2009). In early stages of glacier retreat, associated streamflow

tends to increase due to an acceleration of glacier melt, but after a peak

in streamflow as the glacierized water reservoir gradually empties,

runoff tends to decrease, as evidenced in the Cordillera Blanca of Peru

(Chevallier et al., 2011; Baraer et al., 2012), where seven out of nine

river basins have probably crossed a critical threshold, exhibiting a

decreasing dry-season discharge (Baraer et al., 2012). Likewise, glaciers

and ice fields in the extratropical Andes located in central-south Chile

and Argentina face significant reductions (see review in Masiokas et al.

(2009) and details in Table 27-3b), with their effect being compounded

by changes in snowpack extent, thus magnifying changes in hydrograph

seasonality by reducing flows in dry seasons and increasing them in

wet seasons (Pizarro et al., 2013; Vicuña et al., 2013). Central-south

Chile and Argentina also face significant reductions in precipitation as

shown in Section 27.2.1, contributing to runoff reductions in the last

decades of the 20th century (Seoane and López, 2007; Rubio-Álvarez

and McPhee, 2010; Urrutia et al., 2011; Vicuña et al., 2013), corroborated

with long-term trends found through dendrochronology (Lara et al.,

2007; Urrutia et al., 2011). Trends in precipitation and runoff are less

evident in the central-north region in Chile (Fiebig-Wittmaack et al., 2012;

Souvignet et al., 2012).

As presented in Table 27-4, the assessment of future climate scenarios

implications in hydrologic related conditions shows a large range of

uncertainty across the spectrum of climate models (mostly using CMIP3

simulations with the exception of Demaria et al. (2013)) and scenarios

considered. Nohara et al. (2006) studied climate change impacts on 24

of the main rivers in the world considering a large number of General

Circulation Models (GCMs), and found no robust change for the Paraná

Region Basins studied

Variable

code

number

Projected change Period

General circulation model

(greenhouse gas scenario)

References

Northeastern

Brazil

Basins in the

razilian states of

Ceará and Piauí

1 No signiﬁ cant change up to 2025. After 2025:

trong reduction with ECHAM4; slight increase

with HadCM2.

2000 – 2100 HadCM2, ECHAM4 (NS) Krol et al. (2006);

rol and Bronstert

(2007)

aracatu River 1 +31 to +131% 2000 – 2100 HadCM3 (A2) De Mello et al.

(

2008)

o signiﬁ cant change 2000 – 2100 HadCM3 (B2)

Jaguaribe River 2 Demand: +33 to +44% 2040 HadCM3 (A2, B2) Gondim et al. (2008,

012)

rrigation water needs: +8 to +9% 2025 – 2055 HadCM3 (B2)

arnaíba River 1 – 80% 2050s HadCM3 (A2) Palmer et al. (2008)

Mimoso River 1 Dry scenario: – 25 to –75% 2010 – 2039,

040 – 2069, and

2070 – 2099

CSMK3 and HadCM3 (A2, B1) Montenegro and

agab (2010)

et scenario: +40 to +140%

3 No change

apacurá River 1 B1: – 4.89%, –14.28%, – 20.58% Three 30-year periods CSMK3 and MPEH5 (A2, B1) Montenegro and

Ragab (2012)

A2: +25.25%, +39.48%, +21.95%

Benguê Catchment 1 –15% reservoir yield Sensitivity scenario in 2100 selected from Third and

ourth Assessment Report general circulation models with

good skill. +15% potential evapostranspiration, –10%

recipitation

Krol et al. (2011)

quifers in

northeastern Brazil

Reduction 2040 – 2070 HadCM3, ECHAM4 (A2,B2) Hirata and Conicelli

(2012)

Northern

South America

Essequibo River 1 – 50% 2050s HadCM3 (A2) Palmer et al. (2008)

Magdalena River 1Non-signiﬁ cant changes in near future. End of

21st century changes in seasonality.

2015 – 2035 and

2075 – 2099

CMIP3 multi-model ensemble

(A1B)

Nakaegawa and

Vergara (2010)

Sinú River 1 – 2 to – 35% 2010 – 2039 CCSRNIES, CSIROMK2B, CGCM2,

HadCM3 (A2)

Ospina-Noreña et al.

(2009a,b)

Central

America

Lempa River 1 –13% 2070 – 2100 CMIP3 models (B1) Maurer et al. (2009)

– 24% 2070 – 2100 CMIP3 models (A2)

Río Grande

de Matagalpa

1 –70% 2050s HadCM3 (A2) Palmer et al. (2008)

Basins in

Mesoamerica

1 Decrease across the region 2070 – 2100 CMIP3 (A2, A1B, B1) Imbach et al. (2012)

Consistent decrease 2050s HadCM3 and CMIP3 models

(A1B)

Arnell and Gosling

(2013)

Consistent reduction in northern CA 2050 – 2099 30 GCMs (A1B) Hidalgo et al. (2013)

Basins in Panama 1 Basins discharging into the Paciﬁ c: +35 to +40% 2075 – 2099 MRI-AGCM3.1 (A1B) Fábrega et al. (2013)

Basins in the Bocas del Toro region: – 50%

Variable coding: (1) Runoff/discharge; (2) demand; (3) recharge; (4) glacier change; (5) unmet demand/water availability.

Table 27-4 (continued)

1521

Central and South America Chapter 27

(

La Plata Basin) and Amazon Rivers. Nevertheless, in both cases the

average change showed a positive value consistent, at least with

observations for the La Plata Basin. In a more recent work Nakaegawa

et al. (2013a) showed a statistically significant increase for both basins

in a study that replicated that of Nohara et al. (2006) but with a different

hydrologic model. Focusing in extreme flows Guimberteau et al. (2013)

show that by the middle of the century no change is found in high flow

on the main stem of the Amazon River but there is a systematic reduction

in low-flow streamflow. In contrast, the northwestern part of the

Amazon River shows a consistent increase in high flow and inundated

area (Guimberteau et al., 2013; Langerwisch et al., 2013). On top of

such climatic uncertainty, future streamflows and water availability

projections are confounded by the potential effects of land use changes

(Moore et al., 2007; Coe et al., 2009; Georgescu et al., 2013).

The CA region shows a consistent future runoff reduction. Maurer et al.

(2009) studied climate change projections for the Lempa River basin, one

of the largest basins in CA, covering portions of Guatemala, Honduras,

and El Salvador. They showed that future climate projections (increase

in evaporation and reduction in precipitation) imply a reduction of 20%

in inflows to major reservoirs in this system (see Table 27-4). Imbach et

al. (2012) found similar results using a modeling approach that also

considered potential changes in vegetation. These effects could have

large hydropower generation implications as discussed in the case study

in Section 27.6.1.

The evolution of tropical Andes glaciers associated future climate

scenarios has been studied using trend (e.g., Poveda and Pineda, 2009),

regression (e.g., Juen et al., 2007; Chevallier et al., 2011), and explicit

modeling (e.g., Condom et al., 2012) analysis. These studies indicate that

glaciers will continue their retreat (Vuille et al., 2008a) and even disappear

as glacier equilibrium line altitude rises, with larger hydrological effects

during the dry season (Kaser et al., 2010; Gascoin et al., 2011). This is

expected to happen during the next 20 to 50 years (Juen et al., 2007;

Chevallier et al., 2011; see Table 27-4). After that period water availability

during the dry months is expected to diminish. A projection by Baraer

et al. (2012) for the Santa River in the Peruvian Andes finds that once

the glaciers are completely melt, annual discharge would decrease by

2 to 30%, depending on the watershed. Glacier retreat can exacerbate

current water resources-related vulnerability (Bradley et al., 2006; Casassa

et al., 2007; Vuille et al., 2008b; Mulligan et al., 2010), diminishing the

mountains’ water regulation capacity, making the supply of water for

diverse purposes, as well as for ecosystems integrity, more expensive

and less reliable (Buytaert et al., 2011). Impacts on economic activities

associated with conceptual scenarios of glacier melt reduction have been

monetized (Vergara et al., 2007), representing about US$100 million in

the case of water supply for Quito, and between US$212 million and

US$1.5 billion in the case of the Peruvian electricity sector due to losses

of hydropower generation (see the case study in Section 27.6.1). Andean

communities will face an important increase in their vulnerability, as

documented by Mark et al. (2010), Pérez et al. (2010), and Buytaert and

De Bièvre (2012).

In central Chile, Vicuña et al. (2011) project changes in the seasonality of

streamflows of the upper snowmelt-driven watersheds of the Limarí River,

associated with temperature increases and reductions in water availability

owing to a reduction (increase) in precipitation (evapotranspiration).

imilar conclusions are derived across the Andes on the Limay River in

Argentina by Seoane and López (2007). Under these conditions, semi-

arid highly populated basins (e.g., Santiago, Chile) and with extensive

agriculture irrigation and hydropower demands are expected to increase

their current vulnerability (high confidence; ECLAC, 2009a; Souvignet

et al., 2010; Fiebig-Wittmaack et al., 2012; Vicuña et al., 2012; see Table

27-4). Projected changes in the cryosphere conditions of the Andes

could affect the occurrence of extreme events, such as extreme low and

high flows (Demaria et al., 2013), Glacial Lake Outburst Floods (GLOF)

occurring in the ice fields of Patagonia (Dussaillant et al., 2010; Marín et

al., 2013), volcanic collapse and debris flow associated with accelerated

glacial melting in the tropical Andes (Carey, 2005; Carey et al., 2012b;

Fraser, 2012), and with volcanoes in southern Chile and Argentina

(Tormey, 2010), as well as scenarios of water quality pollution by exposure

to contaminants as a result of glaciers’ retreat (Fortner et al., 2011).

Another semi-arid region that has been studied thoroughly is northeast

Brazil (Hastenrath, 2012). de Mello et al. (2008), Gondim et al. (2008),

Souza et al. (2010), and Montenegro and Ragab (2010) have shown

that future climate change scenarios would decrease water availability

for agriculture irrigation owing to reductions in precipitation and increases

in evapotranspiration (medium confidence). Krol and Bronstert (2007)

and Krol et al. (2006) presented an integrated modeling study that

linked projected impacts on water availability for agriculture with

economic impacts that could potentially drive full-scale migrations in

the NEB region.

27.3.1.2. Adaptation Practices

At an institutional level, a series of policies have been developed to reduce

vulnerability to climate variability as faced today in different regions

and settings. In 1997, Brazil instituted the National Water Resources

Policy and created the National Water Resources Management System

under the shared responsibility between the states and the federal

government. Key to this new regulation has been the promotion of

decentralization and social participation through the creation of National

Council of Water Resources and their counterparts in the states, the

States Water Resources Councils. The challenges and opportunities

dealing with water resources management in Brazil in the face of climate

variability and climate change have been well studied (Abers, 2007;

Kumler and Lemos, 2008; Medema et al., 2008; Engle et al., 2011; Lorz et

al., 2012). Other countries in the region are following similar approaches.

In the last years, there have been constitutional and legal reforms

toward more efficient and effective water resources management and

coordination among relevant actors in Honduras, Nicaragua, Ecuador,

Peru, Uruguay, Bolivia, and Mexico; although in many cases, these

innovations have not been completely implemented (Hantke-Domas,

2011). Institutional and governance improvements are required to

ensure an effective implementation of these adaptation measures (e.g.,

Halsnæs and Verhagen, 2007; Engle and Lemos, 2010; Lemos et al.,

2010; Zagonari, 2010; Pittock, 2011; Kirchhoff et al. 2013).

With regard to region-specific freshwater resources issues it is important

to consider adaptation to reduce vulnerabilities in the communities along

the tropical Andes and the semi-arid basins in Chile-Argentina, NEB,

and the northern CA basins. Different issues have been addressed in

1522

Chapter 27 Central and South America

assessment of adaptation strategies for tropical Andean communities

such as the role of governance and institutions (Young and Lipton, 2006;

Lynch, 2012), technology (Carey et al., 2012a), and the dynamics of

multiple stressors (McDowell and Hess, 2012; Bury et al., 2013). Semi-

arid regions are characterized by pronounced climatic variability and

often by water scarcity and related social stress (Krol and Bronstert,

2007; Scott et al., 2012, 2013). Adaptation tools to face the threats of

climate change for the most vulnerable communities in the Chilean

semi-arid region are discussed by Young et al. (2010) and Debels et al.

(2009). In CA, Benegas et al. (2009), Manuel-Navarrete et al. (2007),

and Aguilar et al. (2009) provide different frameworks to understand

vulnerability and adaptation strategies to climate change and variability

in urban and rural contexts, although no specific adaptation strategies

are suggested. The particular experience in NEB provides other examples

of adaptation strategies to manage actual climate variability. Broad et

al. (2007) and Sankarasubramanian et al. (2009) studied the potential

benefits of streamflow forecast as a way to reduce the impacts of

climate change and climate variability on water distribution under stress

conditions. An historical review and analysis of drought management

in this region are provided by Campos and Carvalho (2008). de Souza

Filho and Brown (2009) studied different water distribution policy

scenarios, finding that the best option depended on the degree of

water scarcity. The study by Nelson and Finan (2009) provides a critical

perspective of drought-related policies, arguing that they constitute an

example of maladaptation as they do not try to solve the causes of

vulnerability and instead undermine resilience. Tompkins et al. (2008)

are also critical of risk reduction practices in this region because they

have fallen short of addressing the fundamental causes of vulnerability

needed for efficient longer term drought management. Other types of

adaptation options that stem from studies on arid and semi-arid regions

are related to (1) increase in water supply from groundwater pumping

(Döll, 2009; Kundzewicz and Döll, 2009; Zagonari, 2010; Burte et al.,

2011; Nadal et al., 2013), fog interception practices (Holder, 2006;

Klemm et al., 2012), and reservoirs and irrigation infrastructure (Fry et

al., 2010; Vicuña et al., 2010, 2012); and (2) improvements in water

demand management associated with increased irrigation efficiency

and practices (Geerts et al., 2010; Montenegro and Ragab, 2010; van

Oel et al., 2010; Bell et al., 2011; Jara-Rojas et al., 2012) and changes

toward less water-intensive crops (Montenegro and Ragab, 2010).

Finally, flood management practices also provide a suite of options to

deal with actual and future vulnerabilities related to hydrologic extremes,

such as the management of ENSO-related events in Peru via participatory

(Warner and Oré, 2006) or risk reduction approaches (Khalil et al., 2007),

the role of land use management (Bathurst et al., 2010, 2011; Coe et al.,

2011), and flood hazard assessment (Mosquera-Machado and Ahmad,

2006) (medium confidence).

27.3.2. Terrestrial and Inland Water Systems

27.3.2.1. Observed and Projected Impacts and Vulnerabilities

CA and SA house the largest biological diversity and several of the

world’s megadiverse countries (Mittermeier et al., 1997; Guevara and

Laborde, 2008). However, land use change has led to the existence of

six biodiversity hotspots, that is, places with a great species diversity

that show high habitat loss and also high levels of species endemism:

Mesoamerica, Chocó-Darien-Western Ecuador, Tropical Andes, Central

Chile, Brazilian Atlantic forest, and Brazilian Cerrado (Mittermeier et al.,

2005). Thus, conversion of natural ecosystems is the main proximate cause

of biodiversity and ecosystem loss in the region (Ayoo, 2008). Tropical

deforestation is the second largest driver of anthropogenic climate

change on the planet, adding up to 17 to 20% of total greenhouse gas

(GHG) emissions during the 1990s (Gullison et al., 2007; Strassburg et al.,

2010). In parallel, the region still has large extensions of wilderness areas

for which the Amazon is the most outstanding example. Nevertheless,

some of these areas are precisely the new frontier of economic expansion.

For instance, between 1996 and 2005, Brazil deforested about 19,500

–1

, which represented 2 to 5% of global annual carbon dioxide (CO

)

emissions (Nepstad et al., 2009). Between 2005 and 2009, deforestation

in the Brazilian Amazon dropped by 36%, which is partly related to the

Frequently Asked Questions

FAQ 27.1 | What is the impact of glacier retreat on

natural and human systems in the tropical Andes?

The retreat of glaciers in the tropical Andes mountains, with some ﬂuctuations, started after the Little Ice Age

(

16th to 19th centuries), but the rate of retreat (area reduction between 20 and 50%) has accelerated since the

late 1970s. The changes in runoff from glacial retreat into the basins fed by such runoff vary depending on the size

and phase of glacier retreat. In an early phase, runoff tends to increase as a result of accelerated melting, but after

peak, as the glacierized water reservoir gradually empties, runoff tends to decrease. This reduction in runoff is

more evident during dry months, when glacier melt is the major contribution to runoff (high conﬁdence).

reduction in runoff could endanger high Andean wetlands (bofedales) and intensify conﬂicts between different

water users among the highly vulnerable populations in high-elevation Andean tropical basins. Glacier retreat has

also been associated with disasters such as glacial lake outburst ﬂoods that are a continuous threat in the region.

Glacier retreat could also impact activities in high mountainous ecosystems such as alpine tourism, mountaineering,

and adventure tourism (high conﬁdence).

1523

Central and South America Chapter 27

etwork of protected areas that now covers around 45.6% of the biome

in Brazil (Soares-Filho et al., 2010). Using the LandSHIFT modeling

framework for land use change and the IMPACT projections of crop/

livestock production, Lapola et al. (2011) projected that zero deforestation

in the Brazilian Amazon forest by 2020 (and of the Cerrado by 2025)

would require either a reduction of 26 to 40% in livestock production

until 2050 or a doubling of average livestock density from 0.74 to 1.46

head per hectare. Thus, climate change may imply reduction of yields

and entail further deforestation.

Local deforestation rates or rising GHGs globally drive changes in the

regional SA that during this century might lead the Amazon rainforest

into crossing a critical threshold at which a relatively small perturbation

can qualitatively alter the state or development of a system (Cox et al.,

2000; Salazar et al., 2007; Sampaio et al., 2007; Lenton et al., 2008;

Nobre and Borma, 2009). Various models are projecting a risk of reduced

rainfall and higher temperatures and water stress, which may lead to

an abrupt and irreversible replacement of Amazon forests by savanna-

like vegetation, under a high emission scenario (A2), from 2050–2060

to 2100 (Betts et al., 2004, 2008; Cox et al., 2004; Salazar et al., 2007;

Sampaio et al., 2007; Malhi et al., 2008, 2009; Sitch et al., 2008; Nobre

and Borma, 2009; Marengo et al., 2011c ). The possible “savannization”

or “die-back” of the Amazon region would potentially have large-scale

impacts on climate, biodiversity, and people in the region. The possibility

of this die-back scenario occurring, however, is still an open issue and

the uncertainties are still very high (Rammig et al., 2010; Shiogama et

al., 2011).

Plant species are rapidly declining in CA, SA, Central and West Africa,

and Southeast Asia (Bradshaw et al., 2009). Risk estimates of plant

species extinction in the Amazon, which do not take into account

possible climate change impacts, range from 5 to 9% by 2050 with a

habitat reduction of 12 to 24% (Feeley and Silman, 2009) to 33% by

2030 (Hubbell et al., 2008). The highest percentage of rapidly declining

amphibian species occurs in CA and SA. Brazil is among the countries

with most threatened bird and mammal species (Bradshaw et al., 2009).

A similar scenario is found in inland water systems. Among components

of aquatic biodiversity, fish are the best-known organisms (Abell et al.,

2008), with Brazil accounting for the richest icthyofauna of the planet

(Nogueira et al., 2010). For instance, the 540 Brazilian small microbasins

host 819 fish species with restrict distribution. However, 29% of these

microbasins have historically lost more than 70% of their natural

vegetation cover and only 26% show a significant overlap with protected

areas or indigenous reserves. Moreover, 40% of the microbasins overlap

with hydrodams (see Section 27.6.1 and Chapter 3) or have few protected

areas and high rates of habitat loss (Nogueira et al., 2010).

The faster and more severe the rate of climate change, the more severe

the biological consequences such as species decline (Brook et al., 2008).

Vertebrate fauna in North and South America is projected to suffer

species losses until 2100 of at least 10%, as forecasted in more than

80% of the climate projections based on a low-emissions scenario

(Lawler et al., 2009). Vertebrate species turnover until 2100 will be as

high as 90% in specific areas of CA and the Andes Mountains for

emission scenarios varying from low B1 to mid-high A2 (Lawler et al.,

2009). Elevational specialists, that is, a small proportion of species with

mall geographic ranges restricted to high mountains, are most frequent

in the Americas (e.g., Andes and Sierra Madre) and might be particularly

vulnerable to global warming because of their small geographic ranges

and high energetic and area requirements, particularly birds and

mammals (Laurance et al., 2011). In Brazil, projections for Atlantic

forest birds (Anciães and Peterson, 2006), endemic bird species (Marini

et al., 2009), and plant species (by 2055, scenarios HHGSDX50 and

HHGGAX50; Siqueira and Peterson, 2003) of the Cerrado indicate that

distribution will dislocate toward the south and southeast, precisely

where fragmentation and habitat loss are worse. Global climate change

is also predicted to increase negative impacts worldwide, including SA,

on freshwater fisheries due to alterations in physiology and life histories

of fish (Ficke et al., 2007).

In addition to climate change impacts at the individual species level,

biotic interactions will be affected. Modifications in phenology, structure

of ecological networks, predator-prey interactions, and non-trophic

interactions among organisms have been forecasted (Brooker et al.,

2008; Walther, 2010). The outcome of non-trophic interactions among

plants is expected to shift along with variation in climatic parameters,

with more facilitative interactions in more stressful environments, and

more competitive interactions in more benign environments (Brooker

et al., 2008; Anthelme et al., 2012). These effects are expected to have a

strong influence of community and ecosystem (re-)organization given the

key engineering role played by plants on the functioning of ecosystems

(Callaway, 2007). High Andean ecosystems, especially those within the

tropics, are expected to face exceptionally strong warming effects during

the 21st century because of their uncommonly high altitude (Bradley

et al., 2006). At the same time they provide a series of crucial ecosystem

services for millions of people (Buytaert et al., 2011). For these reasons

shifts in biotic interactions are expected to have negative consequences

on biodiversity and ecosystem services in this region.

Although in the region biodiversity conservation is largely confined to

protected areas, with the magnitude of climatic changes projected for

the century, it is expected that many species and vegetational types will

lose representativeness inside such protected areas (Heller and Zavaleta,

2009).

27.3.2.2. Adaptation Practices

The subset of practices that are multi-sectoral, multi-scale, and based on

the premise that ecosystem services reduce the vulnerability of society

to climate change are known as Ecosystem-based Adaptation (EbA;

Vignola et al., 2009; see Glossary and Box CC-EA). Schemes such as the

payment for environmental services (PES) and community management

fit the concept of EbA that begins to spread in CA and SA (Vignola et al.,

2009). The principle behind these schemes is the valuation of ecosystem

services that should reflect both the economic and cultural benefits

derived from the human-ecosystem interaction and the capacity of

ecosystems to secure the flow of these benefits in the future (Abson

and Termansen, 2011).

Because PES schemes have developed more commonly in CA and SA

than in other parts of the world (Balvanera et al., 2012), this topic will

be covered as a case study (see Section 27.6.2).

1524

Chapter 27 Central and South America

cological restoration, conservation in protected areas, and community

management can all be important tools for adaptation. A meta-analysis

of 89 studies by Benayas et al. (2009) (with a time scale of restoration

varying from <5 to 300 years), including many in SA, showed that

ecological restoration enhances the provision of biodiversity and

environmental services by 44 and 25%, respectively, as compared to

degraded systems. Moreover, ecological restoration increases the

potential for carbon sequestration and promotes community organization,

economic activities, and livelihoods in rural areas (Chazdon, 2008), as

seen in examples of the Brazilian Atlantic Forest (Calmon et al., 2011;

Rodrigues et al., 2011). In that sense, Locatelli et al. (2011) revised

several ecosystem conservation and restoration initiatives in CA and

SA that simultaneously help mitigate and adapt to climate change.

Chazdon et al. (2009) also highlight the potential of restoration efforts

to build ecological corridors (see Harvey et al., 2008, for an example in

Central America).

The effective management of natural protected areas and the creation

of new protected areas within national protected area systems and

community management of natural areas are also efficient tools to

adapt to climate change and to reconcile biodiversity conservation with

socioeconomic development (e.g., Bolivian Andes: Hoffmann et al., 2011;

Panama: Oestreicher et al., 2009). Porter-Bolland et al. (2012) compared

protected areas with areas under community management in different

parts of the tropical world, including CA and SA, and found that protected

areas have higher deforestation rates than areas with community

management. Similarly, Nelson and Chomitz (2011) found for the region

that (1) protected areas of restricted use reduced fire substantially, but

multi-use protected areas are even more effective; and (2) in indigenous

reserves the incidence of forest fire was reduced by 16% as compared

to non-protected areas. This contrasts with the findings of Miteva et al.

(2012), who found protected areas more efficient in constraining

deforestation than other schemes. Other good examples of adaptive

community management in the continent include community forest

concessions (e.g., Guatemala: Radachowsky et al., 2012), multiple-use

management of forests (Guariguata et al., 2012; see also examples in

Brazil: Klimas et al., 2012, Soriano et al., 2012, and Bolivia: Cronkleton

et al., 2012); and local communities where research and monitoring

protocols are in place to pay the communities for collecting primary

scientific data (Luzar et al., 2011).

27.3.3. Coastal Systems and Low-Lying Areas

27.3.3.1. Observed and Projected Impacts and Vulnerabilities

Climate change is altering coastal and marine ecosystems (Hoegh-

Guldberg and Bruno, 2010). Coral reefs (Chapter 5; Box CC-CR), seagrass

beds, mangroves, rocky reefs and shelves, and seamounts have few to

no areas left in the world that remain unaffected by human influence

(Halpern et al., 2008). Anthropogenic drivers associated with climate

change decreased ocean productivity, altered food web dynamics,

reduced the abundance of habitat-forming species, shifted species

distributions, and led to a greater incidence of disease (Hoegh-Guldberg

and Bruno, 2010). Coastal and marine impacts and vulnerability are often

associated with collateral effects of climate change such as SLR, ocean

warming, and ocean acidification (Box CC-OA). Overfishing, habitat

ollution and destruction, and the invasion of species also negatively

impact biodiversity and the delivery of ecosystem services (Guarderas

et al., 2008; Halpern et al., 2008). Such negative impacts lead to losses

that pose significant challenges and costs for societies, particularly in

developing countries (Hoegh-Guldberg and Bruno, 2010). For instance,

the Ocean Health Index (Halpern et al., 2012), which measures how

healthy the coupling of the human-ocean system is for every coastal

country (including parameters related to climate change), indicates that

CA countries rank among the lowest values. For SA, Suriname stands

out with one of the highest scores.

Coastal states of LA and the Caribbean have a human population of

more than 610 million, three-fourths of whom live within 200 km of

the coast (Guarderas et al., 2008). For instance, studying seven countries

in the region (El Salvador, Nicaragua, Costa Rica, Panama, Colombia,

Venezuela, Ecuador), Lacambra and Zahedi (2011) found that more

than 30% of the population lives in coastal areas directly exposed to

climatic events. Large coastal populations are related to the significant

transformation marine ecosystems have been undergoing in the region.

Fish stocks, places for recreation and tourism, and controls of pests and

pathogens are all under pressure (Guarderas et al., 2008; Mora, 2008).

Moreover, SLR varied from 2 to 7 mm yr

–

between 1950 and 2008 in

CA and SA. The Western equatorial border, influenced by the ENSO

phenomenon, shows a lower variation (of about 1 mm yr

–

) and a range

of variation under El Niño events of the same order of magnitude

that sustained past changes (Losada et al., 2013). The distribution of

population is a crucial factor for inundation impact, with coastal

areas being non-homogeneously impacted. A scenario of 1 m SLR would

affect some coastal populations in Brazil and the Caribbean islands (see

Figure 27-6; ECLAC, 2011a).

27.3.3.1.1. Coastal impacts

Based on trends observed and projections, Figure 27-6 shows how

potential impacts may be distributed in the region. (a) Flooding: Since

flooding probability increases with increasing sea level, one may expect a

higher probability of flooding in locations showing >40% of change over

the last 60 years in the 100-years total sea level (excluding hurricanes).

The figure also identifies urban areas where the highest increase in

flooding level has been obtained. (b) Beach erosion: It increases with

potential sediment transport, thus locations where changes in potential

sediment transport have increased over a certain threshold have a

higher probability to be eroded. (c) Sea ports and reliability of coastal

structures: The figure shows locations where, in the case of having a

protection structure in place, there is a reduction in the reliability of the

structures owing to the increase in the design wave height estimates

(ECLAC, 2011a).

27.3.3.1.2. Coastal dynamics

Information on coastal dynamics is based on historical time series that

have been obtained by a combination ofdatareanalysis,available

instrumental information, and satellite information. Advanced statistical

techniques have been used for obtaining trends including uncertainties

(Izaguirre et al., 2013; Losada et al., 2013).

1525

Central and South America Chapter 27

The greatest flooding levels (hurricanes not considered) in the region

are found in Rio de La Plata area, which combine a 5 mm yr

–1

change

in storm surge with SLR changes in extreme flooding levels (ECLAC,

2011a; Losada et al., 2013). Extreme flooding events may become more

frequent because return periods are decreasing, and urban coastal areas

in the eastern coast will be particularly affected, while at the same time

beach erosion is expected to increase in southern Brazil and in scattered

areas at the Pacific coast (ECLAC, 2011a).

The majority of the literature concerning climate change impacts for

coastal and marine ecosystems considers coral reefs (see also Chapter 5;

Box CC-CR), mangroves, and fisheries. Coral reefs are particularly

sensitive to climate-induced changes in the physical environment (Baker

et al., 2008) to an extent that one-third of the more than 700 species

of reef-building corals worldwide are already threatened with extinction

(Carpenter et al., 2008). Coral bleaching and mortality are often associated

with ocean warming and acidification (Baker et al., 2008). If extreme

sea surface temperatures were to continue, the projections using SRES

scenarios (A1FI, 3ºC sensitivity, and A1B with 2ºC and 4.5ºC sensitivity)

indicate that it is possible that the Mesoamerican coral reef will collapse

by mid-century (between 2050 and 2070), causing major economic

losses (Vergara, 2009). Extreme high sea surface temperatures have

been increasingly documented in the western Caribbean near the coast

of CA and have resulted in frequent bleaching events (1993, 1998, 2005,

and again in 2010) of the Mesoamerican coral reef, located along the

coasts of Belize, Honduras, and Guatemala (Eakin et al., 2010). Reef and

also mangrove ecosystems are estimated to contribute greatly to goods

and services in economic terms. In Belize, for example, this amount is

approximately US$395 to US$559 million annually, primarily through

marine-based tourism, fisheries, and coastal protection (Cooper et al.,

2008). In the Eastern Tropical Pacific, seascape trace abundance of

cement and elevated nutrients in upwelled waters are factors that help

explain high bioerosion rates of local coral reefs (Manzello et al., 2008).

In the southwestern Atlantic coast, eastern Brazilian reefs might suffer

a massive coral cover decline in the next 50 years (Francini-Filho et al.,

2008). This estimate is based on coral disease prevalence and progression

rate, along with growth rate of Mussismilia braziliensis—a major reef-

building coral species that is endemic in Brazil. These authors also

pointed out that coral diseases intensified between 2005 and 2007 based

on qualitative observations since the 1980s and regular monitoring since

2001. They have also predicted that the studied coral species will be

nearly extinct in less than a century if the current rate of mortality due

to disease is not reversed.

Mangroves are largely affected by anthropogenic activities whether or

not they are climate driven. All mangrove forests, along with important

ea level rise of 2 mm yr

–1

(

long-term trends in the

Atlantic coast)

−2 mm yr

–1

torm surges

0.3° yr

–1

>0.3° yr

–1

Counter-

lockwise (CCW)

mm yr

–1

storm surges

(a) Coastal impacts

(b) Coastal dynamics

0.3 m yr

–1

in signiﬁcant wave

height exceeded 12 hours per

ear on average (Hs12)

<0.1 m yr

–1

in annual mean wave

heights

0−40% of change in the

50-year ﬂooding event between

decades of 1950−1960 and

998−2008

Lower sea level rise detected

(

approximately 1 mm yr

–1

)

nnual Mean Energy Flux

Direction shift (°C per year)

Strong trends found in storm

urge extremes

>40% of change over the last 60 years in the

00-year total sea level (excluding hurricanes)

Changes in potential sediment transport rate

Possible sea ports affected for

navigation due to increase in wave heights

Reduction in the reliability of coastal structures

Beach erosion

rosion due to beach rotation

Infrastructures affected below 1 m

ﬂ

>6mm yr

–

in extreme coastal ﬂooding

Flooding

0.2° yr

–1

clockwise (CW)

NSO interannual variability

of the same order of

agnitude than sea level

rise in the last 6 decades

eneralized beach erosion due to

ea level rise from 0.16 to 0.3 m yr

–1

(regional scale)

>2–3 mm yr

–1

xtreme ﬂooding

Sea ports

Figure 27-6 | Current and predicted coastal impacts (a) and coastal dynamics (b) in response to climate change. (a) Coastal impacts: Based on trends observed and projections,

the ﬁgure shows how potential impacts may be distributed in the region (ECLAC, 2011a). Flooding: Since ﬂooding probability increases with increasing sea level, one may

expect a higher probability of ﬂooding in locations showing >40% of change over the last 60 years in 100-year total sea level (excluding hurricanes). The ﬁgure also identiﬁes

urban areas where the highest increase in ﬂooding level has been obtained. Beach erosion: Increases with potential sediment transport, and thus locations where changes in

potential sediment transport have increased over a certain threshold have a higher probability of being eroded. Sea ports and reliability of coastal structures: Shows

locations where, in the case of having a protection structure in place, there is a reduction in the reliability of the structures due to the increase in the design wave height

estimates. (b) Coastal dynamics: Information based on historical time series that have been obtained by a combination of data reanalysis, available instrumental information, and

satellite information. Advanced statistical techniques have been used for obtaining trends including uncertainties (Izaguirre et al., 2013; Losada et al., 2013).

1526

Chapter 27 Central and South America

cosystem goods and services, could be lost in the next 100 years if the

present rate of loss continues (1 to 2% a year; Duke et al., 2007). Moreover,

estimates are that climate change may lead to a maximum global loss

of 10 to 15% of mangrove forest by 2100 (Alongi, 2008). In CA and SA,

some of the main drivers of loss are deforestation and land conversion,

agriculture, and shrimp ponds (Polidoro et al., 2010). The Atlantic and

Pacific coasts of CA are some of the most endangered on the planet

with regard to mangroves, as approximately 40% of present species

are threatened with extinction (Polidoro et al., 2010). Approximately

75% of the global mangrove extension is concentrated in 15 countries,

among which Brazil is included (Giri et al., 2011). The rate of survival of

original mangroves lies between 12.8 and 47.6% in the Tumaco Bay

(Colombia), resulting in ecosystem collapse, fisheries reduction, and

impacts on livelihoods (Lampis, 2010). Gratiot et al. (2008) project for the

current decade an increase of mean high water levels of 6 cm followed

by 90 m shoreline retreat, implying flooding of thousands of hectares

of mangrove forest along the coast of French Guiana.

Peru and Colombia are two of the eight most vulnerable countries to

climate change impacts on fisheries, owing to the combined effect of

observed and projected warming, to species and productivity shifts in

upwelling systems, to the relative importance of fisheries to national

economies and diets, and limited societal capacity to adapt to potential

impacts and opportunities (Allison et al., 2009). Fisheries production

systems are already pressured by overfishing, habitat loss, pollution,

invasive species, water abstraction, and damming (Allison et al., 2009).

In Brazil, a decadal rate of 0.16 trophic level decline (as measured by

the Marine Trophic Index, which refers to the mean trophic level of the

catch) has been detected through most of the northeastern coast,

between 1978 and 2000, which is one of the highest rates documented

in the world (Freire and Pauly, 2010).

Despite the focus in the literature on corals, mangroves, and fisheries,

there is evidence that other benthic marine invertebrates that provide key

services to reef systems, such as nutrient cycling, water quality regulation,

and herbivory, are also threatened by climate change (Przeslawski et al.,

2008). The same applies for seagrasses, for which a worldwide decline

has accelerated from a median of 0.9% yr

–1

before 1940 to 7% yr

–1

since

990, which is comparable to rates reported for mangroves, coral reefs,

and tropical rainforests, and place seagrass meadows among the most

threatened ecosystems on earth (Waycott et al., 2009).

A major challenge of particular relevance at local and global scales will

be to understand how these physical changes will impact the biological

environment of the ocean (e.g., Gutiérrez et al., 2011b), as the Humboldt

Current system—flowing along the west coast of SA—is the most

productive upwelling system of the world in terms of fish productivity.

27.3.3.2. Adaptation Practices

Designing marine protected areas (MPAs) that are resilient to climate

change is a key adaptation strategy in coastal and marine environments

(McLeod et al., 2009). By 2007, LA and the Caribbean (which includes CA

and SA countries) had more than 700 MPAs established covering around

1.5% of the coastal and shelf waters, most of which allow varying levels

of extractive activities (Guarderas et al., 2008). This protected area cover,

however, is insufficient to preserve important habitats or connectivity

among populations at large biogeographic scales (Guarderas et al., 2008).

Nevertheless, examples of adaptation in CA and SA are predominantly

related to MPAs. In Brazil, a protected area type known as “Marine

Extractive Reserves” currently benefits 60,000 small-scale fishermen along

the coast (de Moura et al., 2009). Examples of fisheries’ co-management,

a form of a participatory process involving local fishermen communities,

government, academia, and non-governmental organizations, are reported

to favor a balance between conservation of marine fisheries, coral reefs,

and mangroves on the one hand (Francini-Filho and de Moura, 2008),

and the improvement of livelihoods, as well as the cultural survival of

traditional populations on the other (de Moura et al., 2009; Hastings,

2011).

Significant financial and human resources are expended annually in the

marine reserves to support reef management efforts. These actions,

including the creation of marine reserves to protect from overfishing,

improvement of watershed management, and protection or replanting of

Frequently Asked Questions

FAQ 27.2 | Can payment for ecosystem services be used as an effective way

to help local communities adapt to climate change?

Ecosystems provide a wide range of basic services, such as providing breathable air, drinkable water, and moderating

ﬂood risk (very high conﬁdence). Assigning values to these services and designing conservation agreements based

on these (broadly known as payment for ecosystem services, or PES) can be an effective way to help local communities

adapt to climate change. It can simultaneously help protect natural areas and improve livelihoods and human well-

being (medium conﬁdence). However, during design and planning, a number of factors need to be taken into

consideration at the local level to avoid potentially negative results. Problems can arise if (1) the plan sets poor

deﬁnitions about whether the program should focus just on actions to be taken or the end result of those actions,

(2) many perceive the initiative as commoditization of nature and its intangible values, (3) the action is inefﬁcient

to reduce poverty, (4) difﬁculties emerge in building trust between various stakeholders involved in agreements,

and (5) there are eventual gender or land tenure issues.

1527

Central and South America Chapter 27

oastal mangroves, are proven tools to improve ecosystem functioning.

In Mesoamerican reefs Carilli et al. (2009) found out that such actions

may also actually increase the thermal tolerance of corals to bleaching

stress and thus the associated likelihood of surviving future warming.

In relation to mangroves, in addition to marine protected areas that

include mangroves and functionally linked ecosystems, Gilman et al. (2008)

list a number of other relevant adaptation practices: coastal planning

to facilitate mangrove migration with SLR, management of activities

within the catchment that affect long-term trends in the mangrove

sediment elevation, better management of non-climate stressors, and

the rehabilitation of degraded areas. However, such types of practices

are not frequent in the region.

On the other hand, the implementation of adaptation strategies to SLR

or to address coastal erosion is more commonly seen in many countries

in the region (Lacambra and Zahedi, 2011). For instance, redirecting new

settlements to better-protected locations and to promote investments

in appropriate infrastructure shall be required in the low elevation

coastal zones (LECZ) of the region, particularly in lower income countries

with limited resources, which are especially vulnerable. The same applies

to countries with high shares of land (e.g., Brazil ranking 7th worldwide

of the total land area in the LECZ) and/or population (e.g., Guyana and

Suriname ranking 2nd and 5th by the share of population in the LECZ,

having respectively 76 and 55% of their populations in such areas)

(McGranahan et al., 2007). Adaptation will demand effective and

enforceable regulations and economic incentives, all of which require

political will as well as financial and human capital (McGranahan et al.,

2007). Adaptive practices addressing river flooding are also being

made available as in the study of Casco et al. (2011) for the low Paraná

River in Argentina (see also Chapters 5 and 6 for coastal and marine

adaptation).

27.3.4. Food Production Systems and Food Security

27.3.4.1. Observed and Projected Impacts and Vulnerabilities

Increases in the global demand for food and biofuels promoted a sharp

increase in agricultural production in SA and CA, associated mainly

with the expansion of planted areas (see Chapter 7), and this trend is

predicted to continue in the future (see Section 27.2.2.1). Ecosystems

are being and will be affected in isolation and synergistically by climate

variability/change and land use changes, which are comparable drivers

of environmental change (see Sections 27.2.2.1, 27.3.2.1). By the end

of the 21st century (13 GCMs, under SRES A1B and B1) SA could lose

between 1 and 21% of its arable land due to climate change and

population growth (Zhang and Cai, 2011).

Optimal land management could combine efficient agricultural and

biofuels production with ecosystem preservation under climate change.

However, current practices are leading to a deterioration of ecosystems

throughout the continent (see Section 27.3.2). In southern Brazilian

Amazonia water yields (mean daily discharge (mm d

–1

)) were near four

times higher in soy than in forested watersheds, and showed greater

seasonal variability (Hayhoe et al., 2011). In the Argentinean Pampas

current land use changes disrupt water and biogeochemical cycles and

ay result in soil salinization, altered carbon and nitrogen storage,

surface runoff, and stream acidification (Nosetto et al., 2008; Berthrong

et al., 2009; Farley et al., 2009). In central Argentina flood extension

was associated with the dynamics of groundwater level, which has been

influenced by precipitation and land use change (Viglizzo et al., 2009).

7.3.4.1.1. Observed impacts

The SESA region has shown significant increases in precipitation and

wetter soil conditions during the 20th century (Giorgi, 2002; see Table

27-1) that benefited summer crops and pastures productivity, and

contributed to the expansion of agricultural areas (Barros, 2008a; Hoyos

et al., 2012). Wetter conditions observed during 1970–2000 (in relation

to 1930–1960) led to increases in maize and soybean yields (9 to 58%)

in Argentina, Uruguay, and southern Brazil (Magrin et al., 2007b). Even

if rainfall projections estimate increases of about 25% in SESA for 2100,

agricultural systems could be threatened if climate reverts to a drier

situation due to inter-decadal variability. This could put at risk the viability

of continuous agriculture in marginal regions of Argentina’s Pampas

(Podestá et al., 2009). During the 1930s and 1940s, dry and windy

conditions together with deforestation, overgrazing, overcropping, and

non-suitable tillage produced severe dust storms, cattle mortality, crop

failure, and rural migration (Viglizzo and Frank, 2006).

At the global scale (see Chapter 7), warming since 1981 has reduced

wheat, maize, and barley productivity, although the impacts were small

compared with the technological yield gains over the same period

(Lobell and Field, 2007). In central Argentina, simulated potential wheat

yield—without considering technological improvements—has been

decreasing at increasing rates since 1930 (1930–2000: –28 kg ha

–1

;

1970–2000: –53 kg ha

–1

) in response to increases in minimum

temperature during October–November (1930–2000: +0.4°C per decade;

1970–2000: +0.6°C per decade) (Magrin et al., 2009). The observed

changes in the growing season temperature and precipitation between

1980 and 2008 have slowed the positive yield trends due to improved

genetics in Brazilian wheat, maize, and soy, as well as Paraguayan soy.

In contrast, rice in Brazil and soybean in Argentina have benefited from

precipitation and temperature trends (Lobell et al., 2011). In Argentina,

increases in soybean yield may be associated with weather types that

favor the entry of cold air from the south, reducing thermal stress during

flowering and pod set, and weather types that increase the probability

of dry days at harvest (Bettolli et al., 2009).

27.3.4.1.2. Projected impacts

Assessment of future climate scenarios implications to food production

and food security (see Table 27-5) shows a large range of uncertainty

across the spectrum of climate models and scenarios. One of the

uncertainties is related to the effect of CO

on plant physiology. Many

crops (such as soybean, common bean, maize, and sugarcane) can

probably respond with an increasing productivity as a result of higher

growth rates and better water use efficiency. However, food quality

could decrease as a result of higher sugar contents in grain and fruits,

and decreases in the protein content in cereals and legumes (DaMatta

et al., 2010). Uncertainties associated with climate and crop models, as

1528

Chapter 27 Central and South America

ell as with the uncertainty in human behavior, potentially lead to large

error bars on any long-term prediction of food output. However, the

trends presented here represent the current available information.

In SESA, some crops could be benefitted until mid-21st century if CO

effects are considered (see Table 27-5), although interannual and decadal

climate variability could provoke important damages. In Uruguay and

rgentina, productivity could increase or remain almost stable until the

2030s–2050s depending on the SRES scenario (ECLAC, 2010c). Warmer

and wetter conditions may benefit crops toward the southern and western

zone of the Pampas (Magrin et al., 2007c; ECLAC, 2010c). In south Brazil,

irrigated rice yield (Walter et al., 2010) and bean productivity (Costa et

al., 2009) are expected to increase. If technological improvement is

considered, the productivity of common bean and maize could increase

Continued next page

Country/region Activity Time slice

Special report

on Emissions

Scenarios

(SRES)

Changes Source

Southeastern

South

America

Uruguay

Annual crops 2030 / 2050 / 2070 / 2100 A2 +185 / –194 / – 284 / – 508 ECLAC (2010a)

030 / 2050 B2 + 9 2 / + 1 6 9

Livestock 2030 / 2050 / 2070 / 2100 A2 +174 / – 80 / –160 / – 287

2030 / 2050 B2 + 1 3 6 / + 1 8 2

orestry 2030 / 2050 / 2070 / 2100 A2 + 1 5 / + 3 9 / + 5 2 / + 1 9

2030 / 2050 / 2070 B2 + 6 / + 1 3 / + 1 8

Paraguay

assava 2020 / 2050 / 2080 A2 + 1 6 / + 2 2 / + 2 2 E C L A C ( 2 0 1 0 a )

Wheat 2020 / 2050 / 2080 A2 +4 / – 9/ –13

B2 –1/+1/ – 5

Maize 2020 / 2050 / 2080 A2 + 3 / + 3 / + 8

B2 + 3 / + 1 / + 6

Soybean 2020 / 2050 / 2080 A2 0 / –10 / –15

B2 0 / –15 / – 2

Bean 2020 / 2050 / 2080 A2 – 1 / + 1 0 / + 1 6

Argentina

Maize 2080 A2 / B2 N – 24 / –15 ECLAC (2010a)

A2 / B2 Y + 1 / 0

Soybean 2080 A2 / B2 N – 25 / –14

A2 / B2 Y + 1 4 / + 1 9

Wheat 2080 A2 / B2 N–16 / –11

A2 / B2 Y+3/+3

Soybean 2020 / 2050 / 2080 A2 Y + 2 4 / + 4 2 / + 4 8 Travasso et al. (2008)

B2 Y + 1 4 / + 3 0 / + 3 3

Maize 2020 / 2050 / 2080 A2 Y + 8 / + 1 1 / + 1 6

B2 Y + 5 / + 5 / + 9

Brazil

Rice 2CO

/ 0ºC Y+60 Walter et al. (2010)

2CO

/+5ºC Y+30

Bean 2050 / 2080 A2 N Up to – 30% Costa et al. (2009)

2020 / 2050 / 2080 A2+CO

Y Up to: +30 /+30 /+45

A2+CO

+T Y Up to: +45 /+75 /+90

Maize 2050 / 2080 A2 N Up to – 30%

A2+CO

Y Near to –15%

2020 / 2050 / 2080 A2+CO

+T Y Up to: +40 /+60 /+90

Arabica coffee +0 to +1ºC +1.5% Zullo et al. (2011)

+1 to +2ºC +15.9%

+2 to +3ºC +28.6%

+3 to +4ºC –12.9%

State of São Paulo, Brazil

Sugarcane 2040 Pessimistic +6% Marin et al. (2009)

Optimistic +2%

Table 27-5 | Impacts on agriculture.

1529

Central and South America Chapter 27

etween 40 and 90% (Costa et al., 2009). Sugarcane production could

benefit, as warming could allow the expansion of planted areas toward

the south, where low temperatures are a limiting factor (Pinto et al.,

2008). Increases in crop productivity could reach 6% in São Paulo state

toward 2040 (Marin et al., 2009). In Paraguay the yields of soybean,

maize, and wheat could have slight variations (–1.4 to +3.5%) until 2020

(ECLAC, 2010a).

In Chile and western Argentina, yields could be reduced by water limitation.

In central Chile (30ºS to 42ºS) temperature increases, reduction in chilling

hours, and water shortages may reduce productivity of winter crops, fruits,

vines, and radiata pine. Conversely, rising temperatures, more moderate

frosts, and more abundant water will very likely benefit all species toward

the south (ECLAC, 2010a; Meza and da Silva, 2009). In northern Patagonia

(Argentina) fruit and vegetable growing could be negatively affected

ecause of a reduction in rainfall and in average flows in the Neuquén

River basin. In the north of the Mendoza basin (Argentina) increases in

water demand, due to population growth, may compromise the availability

of subterranean water for irrigation, pushing up irrigation costs and

forcing many producers out of farming toward 2030. Also, water quality

could be reduced by the worsening of existing salinization processes

(ECLAC, 2010a).

In CA, NEB, and parts of the Andean region (Table 27-5) climate change

could affect crop yields, local economies, and food security. It is very likely

that growing season temperatures in parts of tropical SA, east of the

Andes, and CA exceed the extreme seasonal temperatures documented

from 1900 to 2006 at the end of this century (23 GCMs), affecting

regional agricultural productivity and human welfare (Battisti and Naylor,

2009). For NEB, declining crop yields in subsistence crops such as beans,

Country/region Activity Time slice

Special report

on Emissions

Scenarios

(SRES)

Changes Source

Northeastern Brazil

Cassava 2020 – 2040 N 0 to –10 Lobell et al. (2008)

aize 2020 – 2040 N 0 to –10

Rice 2020 – 2040 N –1 to –10

Wheat 2020 – 2040 N –1 to –14

Maize – 20 to – 30 Margulis et al. (2010)

Bean – 20 to – 30

Rice – 20 to – 30

Cowpea bean +1.5ºC – 26% Silva et al. (2010)

+3.0ºC – 44%

+5.0ºC – 63%

Central America

Maize 2030 / 2050 / 2070 / 2100 A2 0 / 0 / –10 / – 30 ECLAC (2010a)

Bean 2030 / 2050 / 2070 / 2100 A2 – 4 / –19/ – 29/ – 87

Rice 2030 / 2050 / 2070 / 2100 A2 +3 / – 3 / –14 / – 63

Rice 2020 – 2040 N 0 to –10 Lobell et al. (2008)

Wheat 2020 – 2040 N –1 to – 9

Panamá

Maize 2020 / 2050 / 2080 A2 Y – 0.5 /+2.4 /+4.5 Ruane et al. (2011)

B1 Y – 0.1/ – 0.8/+1.5

Andean Region

Wheat 2020 – 2040 N –14 to +2 Lobell et al. (2008)

Barley 2020 – 2040 N 0 to –13

Potato 2020 – 2040 N 0 to – 5

Maize 2020 – 2040 N 0 to – 5

Colombia

All main crops 2050 17 GCMs (A2) 80% of crops impacted in more than

60% of current cultivated areas

Ramirez et al. (2012)

Chile (34.6º to 38.5ºS)

Maize 2050 A1FI Y – 5% to –10% Meza and Silva (2009)

Wheat 2050 A1FI Y –10% to – 20%

Notes:

Changes are expressed as differences in relative yield (%), except for

and

N: Without considering CO

biological effects.

Y: Considering CO

biological effects.

2CO

Considering double CO

concentration (780 ppm CO

T: Considering technological improvement (genetic changes).

Gross value of production (millions of US$).

Huge spatial variability; values are approximated.

Changes in the percentage of areas with low climate risk.

Table 27-5 (continued)

1530

Chapter 27 Central and South America

orn, and cassava are projected (Lobell et al., 2008; Margulis et al.,

2010). In addition, increases in temperature could reduce the areas

currently favorable to cowpea bean (Silva et al., 2010). The highest

warming foreseen for 2100 (5.8°C, under SRES A2 scenario) could make

the coffee crop unfeasible in Minas Gerais and São Paulo (southeast

Brazil) if no adaptation action is accomplished. Thus, the coffee crop

may have to be transferred to southern regions where temperatures are

lower and the frost risk will be reduced (Camargo, 2010). With +3ºC,

Arabica coffee is expected to expand in the extreme south of Brazil,

the Uruguayan border, and northern Argentina (Zullo Jr. et al., 2011).

Brazilian potato production could be restricted to a few months in

currently warm areas, which today allow potato production year-round

(Lopes et al., 2011). Large losses of suitable environments for the “Pequi”

tree (Caryocar brasiliense, an economically important Cerrado fruit tree)

are projected by 2050, affecting mainly the poorest communities in

central Brazil (Nabout et al., 2011). In the Amazon region soybean yields

would be reduced by 44% in the worst scenario (Hadley Centre climate

prediction model 3 (HadCM3) and no CO

fertilization) by 2050 (Lapola

et al., 2011). By 2050, according to 17 GCMs under SRES A2 scenario,

80% of crops will be impacted in more than 60% of current areas of

cultivation in Colombia, with severe impacts in perennial and exportable

crops (Ramirez-Villegas et al., 2012).

Teixeira et al. (2013) identified hotspots for heat stress toward 2071–

2100 under the A1B scenario and suggest that rice in southeast Brazil,

maize in CA and SA, and soybean in central Brazil will be the crops and

zones most affected by increases in temperature.

In CA, changes projected in climate could severely affect the poorest

population and especially their food security, increasing the current rate

of chronic malnutrition. Currently, Guatemala is the most food insecure

country by percentage of the population (30.4%) and the problem has

been increasing in recent years (FAO, WFP, and IFAD, 2012). The impact

of climate variability and change is a great challenge in the region. As

an example, the recent rust problem on the coffee sector of 2012–2013

has affected nearly 600,000 ha (55% of the total area) (ICO, 2013) and

will reduce employment by 30 to 40% for the harvest 2013–2014

(FEWS NET, 2013). At least 1.4 million people in Guatemala, El Salvador,

Honduras, and Nicaragua depend on the coffee sector, which is very

susceptible to climate variations. In Panamá, the large interannual climate

variability will continue to be the dominant inﬂuence on seasonal maize

yield into the coming decades (Ruane et al., 2013). In the future, warming

conditions combined with more variable rainfall are expected to reduce

maize, bean, and rice productivity (ECLAC, 2010c); rice and wheat

yields could decrease up to 10% by 2030 (Lobell et al., 2008; medium

confidence). In CA, nearly 90% of agricultural production destined for

internal consumption is composed by maize (70%), bean (25%), and

rice (6%) (ECLAC, 2011d).

Climate change may also alter the current scenario of plant diseases

and their management, having effects on productivity (Ghini et al.,

2011). In Argentina, years with severe infection of late cycle diseases

in soybean could increase; severe outbreaks of the Mal de Rio Cuarto

virus in maize (natural vectors: Delphacodes kuscheli and Delphacodes

hayward) could be more frequent; and wheat head fusariosis will increase

slightly in the south of the Pampas region by the end of the century

(ECLAC, 2010a). In Brazil favorable areas for soybean and coffee rusts

ill move toward the south, particularly for the hottest scenario of 2080

(Alves et al., 2011). Potato late blight (Phytophtora infestans) severity

is expected to increase in Peru (Giraldo et al., 2010).

The choice of livestock species could change in the future. For example,

by 2060, under a hot and dry scenario, beef and dairy cattle, pig, and

chicken production choice could decrease between 0.9 and 3.2%, while

sheep election could increase by 7% mainly in the Andean countries

(Seo et al., 2010). Future climate could strongly affect milk production

and feed intake in dairy cattle in Brazil, where substantial modifications

in areas suitable for livestock, mainly in the Pernambuco region, are

expected (da Silva et al., 2009). Warming and drying conditions in

Nicaragua could reduce milk production, mainly among farmers who

are already seriously affected under average dry season conditions

(Lentes et al., 2010).

Climate change impact on regional welfare will depend not only on

changes in yield, but also in international trade. According to Hertel et

al. (2010), by 2030, global cereal price could change between increases

of 32% (low-productivity scenario) or decreases of 16% (optimistic yield

scenario). A rise in prices could benefit net exporting countries such as

Brazil, where gains from terms of trade shifts could outweigh the losses

due to climate change. Despite experiencing significant negative yield

shocks, some countries tend to gain from higher commodity prices.

However, most poor household are food purchasers and rising commodity

prices tend to have a negative effect on poverty (von Braun, 2007).

According to Chapter 7, increases in prices during 2007–2009 led to

rising poverty in Nicaragua.

27.3.4.2. Adaptation Practices

Genetic advances and suitable soil and technological management

may induce an increase in some crops’ yield despite unfavorable future

climate conditions. In Argentina, genetic techniques, specific scientific

knowledge, and land use planning are viewed as promising sources of

adaptation (Urcola et al., 2010). Adjustments in sowing dates and

fertilization rates could reduce negative impacts or increase yields in

maize and wheat crops in Argentina and Chile (Magrin et al., 2009;

Meza and da Silva, 2009; Travasso et al., 2009b). Furthermore, in central

Chile and southern Pampas in Argentina warmer climates could allow

performing two crops per season, increasing productivity per unit land

(Monzon et al., 2007; Meza et al., 2008). In Brazil, adaptation strategies

for coffee crops include planting at high densities, vegetated soil, accurate

irrigation and breeding programs, and shading management system

(arborization) (Camargo, 2010). Shading is also used in Costa Rica and

Colombia. In south Brazil, a good option for irrigated rice could be to

plant early cultivars (Walter et al., 2010).

Water management is another option for needed better preparedness

regarding water scarcity (see Section 27.3.1). In Chile, the adoption of

water conservation practices depends on social capital, farm size, and land

use; and the adoption of technologies that require investment depend on

the access to credit and irrigation water subsidies (Jara-Rojas et al., 2012).

Deficit irrigation could be an effective measure for water savings in dry

areas such as the Bolivian Altiplano (quinoa), central Brazil (tomatoes),

and northern Argentina (cotton) (Geerts and Raes, 2009). In rainfed

1531

Central and South America Chapter 27

rops adaptive strategies might need to look at the harvest, storage,

temporal transfer, and efficient use of rainfall water. In addition, some

agronomic practices such as fallowing, crop sequences, groundwater

management, no-till operations, cover crops, and fertilization could

improve the adaptation to water scarcity (Quiroga and Gaggioli, 2011).

One approach to adapting to future climate change is by assisting people

to cope with current climate variability (Baethgen, 2010), for which the

use of climatic forecasts in agricultural planning presents a measure.

Increased access and improvement of climate forecast information

enhances the ability of farmers in the Brazilian Amazon to cope with El

Niño impacts (Moran et al., 2006). The Southern Oscillation Index for

maize and the South Atlantic Sea Surface Temperature for soybean and

sunflower were the best indicators of annual crop yield variability in

Argentina (Travasso et al., 2009a). Another possibility to cope with extreme

events consists in transferring weather-related risks by using different

types of rural insurance (Baethgen, 2010). Index insurance is one

mechanism that has been recently introduced to overcome obstacles

to traditional agricultural and disaster insurance markets (see Chapter

15). For the support of such parametric agricultural insurance, a Central

American climate database was recently established (SICA, 2013).

Local and indigenous knowledge has the potential to bring solutions

even in the face of rapidly changing climatic conditions (Folke et al.,

2002; Altieri and Koohafkan, 2008), although migration, climate change,

and market integration are reducing indigenous capacity for dealing

with weather and climate risk (Pérez et al., 2010; Valdivia et al., 2010).

Crop diversification is used in the Peruvian Andes to suppress pest

outbreaks and dampen pathogen transmission (Lin, 2011). In Honduras,

Nicaragua, and Guatemala traditional practices have proven more

resilient to erosion and runoff and have helped retain more topsoil and

moisture (Holt-Gimenez, 2002). In El Salvador, if local sustainability

efforts continue, the future climate vulnerability index could only slightly

increase by 2015 (Aguilar et al., 2009). Studies with Indigenous farmers

in highland Bolivia and Peru indicate that constraints on access to key

resources must be addressed for reducing vulnerability over time

(McDowell and Hess, 2012; Sietz et al., 2012). In Guatemala and

Honduras adaptive response between coffees farmers is mainly related

to land availability, while participation in organized groups and access

to information contribute to adaptive decision making (Tucker et al.,

2010). Otherwise, adaptation may include an orientation toward non-

farming activities to sustain their livelihoods and be able to meet their

food requirements (Sietz, 2011). In NEB increasing vulnerability related

to degradation of natural resources (due to overuse of soil and water)

encouraged farmers toward off-farm activities; however, they could not

improve their well-being (Sietz et al., 2006, 2011). Migration is another

strategy in ecosystems and regions at high risk of climate hazards (see

Section 27.3.1.1). During 1970–2000 LA and the Caribbean has had a

great rate of net migration per population in the dryland zones (de

Sherbinin et al., 2012). In CA nearly 25% of the surveyed households

reported some type of migration during the coffee crisis (Tucker et al.,

2010). Some migrations—for example, Guatemala, 1960s–1990s; El

Salvador, 1950s–1980s; NEB, 1960s–present—have provoked conflict

in receiving areas (Reuveny, 2007).

Shifting in agricultural zoning has been an autonomous adaptation

observed in SA. In Argentina., for example, increases in precipitation

romoted the expansion of the agricultural frontier to the west and

north of the traditional agricultural area, resulting in environmental

damage that could be aggravated in the future (República Argentina,

2007; Barros, 2008b). Adjustment of production practices—like those

of farmers in the semi-arid zones of mountain regions of Bolivia, which

began as they noticed strong changes in the climate since the 1980s,

including upward migration of crops, selection of more resistant varieties,

and water capturing—presents a further adaptation measure (PNCC,

2007).

Organic systems could enhance adaptive capacity as a result of the

application of traditional skills and farmers’ knowledge, soil fertility-

building techniques, and a high degree of diversity (ITC, 2007). As

mentioned previously, crop diversity, local knowledge, soil conservation,

and economic diversity are all documented strategies for managing

risk in CA and SA. A controversial but important issue in relation to

adaptation is the use of genetically modified plants to produce food,

with biotech crops being a strategy to cope with the needed food

productivity increase considering the global population trend (see

Chapter 7). Brazil and Argentina are the second and third fastest

growing biotech crop producers in the world after the USA (Marshall,

2012). However, this option is problematic for the small farms (Mercer

et al., 2012), which are least favorable toward GMO (Soleri et al., 2008).

According to Eakin and Wehbe (2009) some practices could be an

adaptive option for specific farm enterprises, but may have maladaptive

implications at regional scales, and over time become maladaptive for

individual enterprises.

27.3.5. Human Settlements, Industry, and Infrastructure

According to the World Bank database (World Bank, 2012) CA and SA

are the geographic regions with the second highest urban population

(79%), behind North America (82%) and well above the world average

(50%). Therefore this section focuses on assessing the literature on

climate change impacts and vulnerability of urban human settlements.

The information provided should be complemented with other sections

of the chapter (see Sections 27.2.2.2, 27.3.1, 27.3.3, 27.3.7).

27.3.5.1. Observed and Projected Impacts and Vulnerabilities

Urban human settlements suffer from many of the vulnerabilities and

impacts already presented in several sections of this chapter. The

provision of critical resources and services as already discussed in the

chapter—water, health, and energy—and of adequate infrastructure and

housing remain determinants of urban vulnerability that are enhanced

by climate change (Smolka and Larangeira, 2008; Winchester, 2008;

Roberts, 2009; Romero-Lankao et al., 2012c, 2013b).

Water resource management (see Section 27.3.1) is a major concern

for many cities that need to provide both drinking water and sanitation

(Henríquez Ruiz, 2009). More than 20% of the population in the region

are concentrated in the largest city in each country (World Bank, 2012),

hence water availability for human consumption in the region’s megacities

(e.g., São Paulo, Santiago, Lima, Buenos Aires) is of great concern. In

this context, reduction in glacier and snowmelt related runoff in the

1532

Chapter 27 Central and South America

Andes poses important adaptation challenges for many cities, for

example, the metropolitan areas of Lima, La Paz/El Alto, and Santiago

de Chile (Bradley et al., 2006; Hegglin and Huggel, 2008; Melo et al.,

2010). Flooding is also a preoccupation in several cities. In São Paulo

for example, according to Marengo et al. (2009b, 2013b) the number

of days with rainfall above 50 mm were almost zero during the 1950s

and now they occur between two and five times per year (2000–2010).

The increase in precipitation is one of the expected risks affecting the

city of São Paulo as presented in Box 27-2. Increases in flood events

during 1980–2000 have been observed also in the Buenos Aires

province and Metropolitan Area (Andrade and Scarpati, 2007; Barros et

al., 2008; Hegglin and Huggel, 2008; Nabel et al., 2008). There are also

the combined effects of climate change impacts, human settlements’

features, and other stresses, such as more intense pollution events

(Moreno, 2006; Nobre, 2011; Nobre et al., 2011; Romero-Lankao et al.,

2013b) and more intense hydrological cycles from urban heat island

effects. In terms of these combined effects, peri-urban areas and

irregular settlements pose particular challenges to urban governance

and risk management given their scale, lack of infrastructure, and

socioeconomic fragility (Romero-Lankao et al., 2012a).

Changes in prevailing urban climates have led to changing patterns

of disease vectors, and water-borne disease issues linked to water

availability and subsequent quality (see Section 27.3.7). The influence

of climate change on particulate matter and other local contaminants

is another concern (Moreno, 2006; Romero-Lankao et al., 2013b). It is

important to highlight the relationship between water and health, given

the problems of water stress and intense precipitation events affecting

many urban centers. Both relate to changing disease risks, as well as wider

problems of event-related mortalities and morbidity, and infrastructure

and property damage. These risks are compounded for low-income

groups in settlements with little or no service provision, for example,

waste collection, piped drinking water, and sanitation (ECLAC, 2008).

Existing cases of flooding, air pollution, and heat waves reveal that not

only low-income groups are at risk, but also that wealthier sectors are

not spared. Factors such as high-density settlement (Barros et al., 2008)

and the characteristics of some hazards explain this—for example, poor

and wealthy alike are at risk from air pollution and temperature in

Santiago de Chile and Bogotá (Romero-Lankao et al., 2012b, 2013b).

There are also other climate change risks in terms of economic activity

location and impacts on urban manufacturing and service workers (e.g.,

thermal stress; Hsiang, 2010) and the forms of urban expansion or sprawl

into areas where ecosystem services may be compromised and risks

enhanced (e.g., floodplains). Both processes are also related to rising

motorization rates that facilitate suburban development and new

Box 27-2 | Vulnerability of South American Megacities to Climate Change:

The Case of the Metropolitan Region of São Paulo

Research in the Metropolitan Region of São Paulo (MRSP), between 2009 and 2011, represents a comprehensive and interdisciplinary

project on the impacts of climate variability and change, and vulnerability of Brazilian megacities. Studies derived from this project

(Nobre et al., 2011; Marengo et al., 2013b) identify the impacts of climate extremes on the occurrence of natural disasters and

human health. These impacts are linked to a projected increase of 38% in the extension of the urban area of the MRSP by 2030,

accompanied by a projected increase in rainfall extremes. These may induce an intensiﬁcation of urban ﬂash ﬂoods and landslides,

affecting large populated areas already vulnerable to climate extremes and variability. The urbanization process in the MRSP has

been affecting the local climate, and the intensiﬁcation of the heat island effect to a certain degree may be responsible for the 2°C

warming detected in the city during the last 50 years (Nobre et al., 2011). This warming has been further accompanied by an increase

in heavy precipitation as well as more frequent warm nights (Silva Dias et al., 2012; Marengo et al., 2013b). By 2100, climate projections

based on data from 1933–2010 show an expected warming between 2°C and 3°C in the MRSP, together with a possible doubling of

the number of days with heavy precipitation in comparison to the present (Silva Dias et al., 2012; Marengo et al., 2013b).

With the projected changes in climate and in the extension of the MRSP (Marengo et al., 2013b) more than 20% of the total area of

the city could be potentially affected by natural disasters. More frequent ﬂoods may increase the risk of leptospirosis, which, together

with increasing air pollution and worsening environmental conditions that trigger the risk of respiratory diseases, would leave the

population of the MRSP more vulnerable. Potential adaptation measures include a set of strategies that need to be developed by the

MRSP and its institutions to face these environmental changes. These include improved building controls to avoid construction in risk

areas, investment in public transportation, protection of the urban basins, and the creation of forest corridors in the collecting basins

and slope regions. The lessons learned suggest that the knowledge on the observed and projected environmental changes, as well as

on the vulnerability of populations living in risk areas, is of great importance for deﬁning adaptation policies that in turn constitute a

ﬁrst step toward building resilient cities that in turn improve urban quality of life in Brazil.

1533

Central and South America Chapter 27

egional agglomerations that bring pressure to bear on land uses that

favor infiltration, surface cooling, and biodiversity; the number of light

vehicles in LA and the Caribbean is expected to double between 2000 and

2030, and be three times the 2000 figure by 2050 (Samaniego, 2009).

While urban populations face diverse social, political, economic, and

environmental risks in daily life, climate change adds a new dimension

to these risk settings (Pielke, Jr. et al., 2003; Roberts, 2009; Romero-

Lankao and Qin, 2011). Because urban development remains fragile in

many cases, with weak planning responses, climate change can compound

existing challenges. The probabilities and magnitudes of these events

in each urban center will differ significantly according to socioeconomic,

institutional, and physical contexts.

27.3.5.2. Adaptation Practices

The direct and indirect effects of climate change such as flooding, heat

islands, and food insecurity present cities with a set of challenges and

opportunities for mainstreaming flood management, warning systems,

and other adaptation responses with sustainability goals (Bradley et al.,

2006; Hegglin and Huggel, 2008; Hardoy and Pandiella, 2009; Romero-

Lankao, 2010, 2012a; Romero-Lankao et al., 2013a).

Urban populations, economic activities, and authorities have a long

experience of responding to climate-related hazards, particularly through

disaster risk management, for example, Tucuman and San Martin,

Argentina (Plaza and Pasculi, 2007; Sayago et al., 2010), and land use

and economic development planning to a limited extent (Barton, 2009).

Climate policies can build on these. Local administrations participate in

the International Council for Local Environmental Initiatives (ICLEI),

Cities Climate Leadership Group (C40), Inter-American Development

Bank (IDB), Emerging and Sustainable Cities Initiative (ESCI) (IDB, 2013),

and other networks, demonstrating their engagement in the generation

of more climate-resilient cities. In smaller settlements, there is less

capacity for adequate responses, for example, climate change and

vulnerability information (Hardoy and Romero-Lankao, 2011). Policies,

plans, and programs are required to reduce social vulnerability, and

identify and reduce potential economic effects of climate on the local

economy. Rio de Janeiro, for example, with its coastline property and

high dependence on tourists (and their perceptions of risk), cannot

ignore these climate-related hazards (Gasper et al., 2011).

Poverty and vulnerability, as interlinked elements of the adaptation

challenge in CA and SA, remain pivotal to understanding how urban

climate policies can be streamlined with broader development issues

and not solely the capacity to respond to climate change (Hardoy and

Pandiella, 2009; Winchester and Szalachman, 2009; Hardoy and

Romero-Lankao, 2011). These broader links include addressing the

determinants of vulnerability (e.g., access to education, health care, and

infrastructure, and to emergency response systems (Romero-Lankao,

2007a; Romero-Lankao and Qin, 2011)). Among these response options,

a focus on social assets has been highlighted by Rubin and Rossing

(2012), rather than a purely physical asset focus.

Much urbanization involves in-migrating or already resident, low-

income groups and their location in risk-prone zones (da Costa Fereira

t al., 2011). The need to consider land use arrangements, particularly

urban growth on risk-prone zones, as part of climate change adaptation

highlights the role of green areas that mitigate the heat island effect

and reduce risks from landslides and flooding (Rodríguez Laredo, 2011;

Krellenberg et al., 2013).

In the case of governance frameworks, there is clear evidence that

incorporation of climate change considerations into wider city planning

is still a challenge, as are more inter-sectoral and participative processes

that have been linked to more effective policies (Barton, 2009, 2013;

de Oliveira, 2009; Romero-Lankao et al., 2013a). Several metropolitan

adaptation plans have been generated over the last 5 years, for example,

Bogotá, Buenos Aires, Esmeraldas, Quito, and São Paulo, although for

the most part they have been restricted to the largest conglomerations

and are often included as an addition to mitigation plans (Romero-

Lankao, 2007b; Carmin et al., 2009; Romero-Lankao et al., 2012b, 2013a;

Luque et al., 2013).

27.3.6. Renewable Energy

27.3.6.1. Observed and Projected Impacts and Vulnerabilities

Table 27-6 shows the relevance of renewable energy in the LA energy

matrix as compared to the world for 2009 according to IEA statistics

(IEA, 2012). Hydropower is the most representative source of renewable

energy and therefore analyzed separately (see the case study in Section

27.6.1.). Geothermal energy is not discussed, as it is assumed that there

is no impact of climate change on the effectiveness of this energy type

(Arvizu et al., 2011).

Hydro, wind energy, and biofuel production might be sensitive to

climate change in Brazil (de Lucena et al., 2009). With the vital role that

renewable energy plays in mitigating the effects of climate change,

being by far the most important sources of non-hydro renewable energy

in SA and CA, this sensitivity demands the implementation of renewable

energy projects that will increase knowledge on the crops providing

bioenergy.

For historical reasons, CA and SA developed sugarcane as bioenergy

feedstock. Brazil accounts for the most intensive renewable energy

production as bioethanol, which is used by the majority of the cars in

the country (Goldemberg, 2008) whereas biodiesel comprises 5% of

all diesel nationwide. With the continent’s long latitudinal length, the

expected impacts of climate change on plants will be complex owing

to a wide variety of climate conditions, so that different crops would

have to be used in different regions. In Brazil, most of the biodiesel

comes from soybeans, but there are promising new sources such as

palm oil (de Lucena et al., 2009). The development of palm oil as well

as soybean are important factors that induce land use change, with a

potential to influence stability of forests and biodiversity in certain key

regions in SA, such as the Amazon (Section 27.2.2.1).

Biofuels can help CA and SA to decrease emissions from energy

production and use. However, renewable energy might imply potential

problems such as those related to positive net emissions of GHGs,

threats to biodiversity, an increase in food prices, and competition for

1534

Chapter 27 Central and South America

water resources (Section 27.2.3), some of which can be reverted or

attenuated (Koh and Ghazoul, 2008). For example, the sugarcane agro-

industry in Brazil combusts bagasse to produce electricity, providing

power for the bioethanol industry and increasing sustainability. The

excess heat energy is then used to generate bioelectricity, thus allowing

the biorefinery to be self-sufficient in energy utilization (Amorim et al.,

2011; Dias et al., 2012). In 2005–2006 the production of bioelectricity

was estimated to be 9.2 kWh per tonne of sugarcane (Macedo et al.,

2008). Most bioenergy feedstocks at present in production in CA and

SA are grasses. In the case of sugarcane, the responses to the elevation

of CO

concentration up to 720 ppmv have been shown to be positive

in terms of biomass production and principally regarding water use

efficiency (de Souza et al., 2008).

The production of energy from renewable sources such as hydro- and

wind power is greatly dependent on climatic conditions and therefore

may be impacted in the future by climate change. de Lucena et al.

(2010a) suggest an increasing energy vulnerability of the poorest

regions of Brazil to climate change together with a possible negative

influence on biofuels production and electricity generation, mainly

biodiesel and hydropower respectively.

Expansion of biofuel crops in Brazil might cause both direct and indirect

land use changes (e.g., biofuel crops replacing rangelands, which

previously replaced forests) with the direct land use changes, according

to simulation performed by Lapola et al. (2010) of the effects for 2020.

The same study shows that sugarcane ethanol and biodiesel derived

from soybean each contribute, with about one-half of the indirect

deforestation projected for 2020 (121,970 km

) (Lapola et al., 2010).

Thus, indirect land use changes, especially those causing the rangeland

frontier to move further into the Amazonian forests, might potentially

offset carbon savings from biofuel production.

The increase in global ethanol demand is leading to the development

of new hydrolytic processes capable of converting cellulose into ethanol

(dos Santos et al., 2011). The expected increase in the hydrolysis

technologies is very likely to balance the requirement of land for

biomass crops. Thus, the development of these technologies has a

strong potential to diminish social (e.g., negative health effects due the

burning process, poor labor conditions) and environmental impacts (e.g.,

loss of biodiversity, water and land uses) whereas it can improve the

economic potential of sugarcane. One adaptation measure will be to

increase the productivity of bioenergy crops due to planting in high

productivity environments with highly developed technologies, in order

to use less land. As one of the main centers of biotech agriculture

application in the world (Gruskin, 2012), the region has a great potential

to achieve this goal.

As the effects previously reported on crops growing in SESA might

prevail (see Section 27.3.4.1), that is, that an increase in productivity

may happen due to increasing precipitation, future uncertainty will have

to be dealt with by preparing adapted varieties of soybean in order to

maintain food and biodiesel production, mainly in Argentina, as it is

one of the main producers of biodiesel from soybean in the world (Chum

et al., 2011).

Other renewable energy sources—such as wind power generation—

may also be vulnerable, raising the need for further research. According

to de Lucena et al. (2009, 2010b), the projections of changes in wind

power in Brazil may favor the use of this kind of energy in the future.

27.3.6.2. Adaptation Practices

Renewable energy will become increasingly more important over time,

as this is closely related to the emissions of GHGs (Fischedick et al., 2011).

Thus, renewable energy could have an important role as adaptation

means to provide sustainable energy for development in the region (see

also Section 27.6.1). However, the production of renewable energy

requires large available areas for agriculture, which is the case of

Energy resource

Latin America World

TFC

(non-electricity)

TFC

(via electricity

generation)

TFC

(total)

TFC

(non-electricity)

TFC

(via electricity

generation)

TFC

(total)

Fossil Coal and

peat

008 3% 1398 2% 10,406 3% 831,897 12% 581,248 40% 1,413,145 17%

Oil

189,313 55% 8685 13% 197,998 48% 3,462,133 52% 73,552 5% 3,535,685 44%

Natural gas

59,440 17% 9423 14% 68,863 17% 1,265,862 19% 307,956 21% 1,573,818 19%

Nuclear

0 0% 1449 2% 1449 0% 0 0% 193,075 13% 193,075 2%

Renewable Biofuels and

waste

82,997 24% 2179 3% 85,176 21% 1,080,039 16% 20,630 1% 1,100,669 14%

Hydropower

0% 45,920 66% 45,920 11% 0 0% 238,313 17% 238,313 3%

Geothermal,

solar, wind,

other

renewable

08 0% 364 1% 772 0% 18,265 0% 26,592 2% 44,857 1%

Total

41,166 100% 69,418 100% 410,584 100% 6,658,196 100% 1,441,366 100% 8,099,562 100%

Table 27-6 | Comparison of consumption of different energy sources in Latin America and the world (in thousand tonnes of oil equivalent on a net caloriﬁ c value basis).

TFC = Total ﬁ nal consumption.

Source: IEA (2012).

1535

Central and South America Chapter 27

rgentina, Bolivia, Brazil, Chile, Colombia, Peru, and Venezuela, which

together represent 90% of the total area of CA and SA. However, for

small countries it might not be possible to use bioenergy. Instead, they

could benefit in the future from other types of renewable energy, such

as geothermal, eolic, photovoltaic, and so forth, depending on policies

and investment in different technologies. This is important because

economic development is thought to be strongly correlated with an

increase in energy use (Smil, 2000), which is itself associated with an

increase in emissions (Sathaye et al., 2011).

LA is second to Africa in terms of technical potential for bioenergy

production from rainfed lignocellulosic feedstocks on unprotected

grassland and woodlands (Chum et al., 2011). Among the most important

adaptation measures regarding renewable energy are (1) management

of land use change ; and (2) development of policies for financing and

management of science and technology for all types of renewable

energy in the region.

If carefully managed, biofuel crops can be used as a means to regenerate

biodiversity as proposed by Buckeridge et al. (2012), highlighting that

the technology for tropical forest regeneration has become available

and that forests could share land with biofuel crops (such as sugarcane)

taking advantage of forests’ mitigating potential. A possible adaptation

measure could be to expand the use of reforestation technology to other

countries in CA and SA.

One of the main adaptation issues is related to food versus fuel (Valentine

et al., 2012). This is important because an increase in bioenergy feedstocks

might threaten primary food production in a scenario expected to feed

future populations with an increase of 70% in production (Gruskin,

2012; Valentine et al., 2012). This is particularly important in the region,

as it has one of the highest percentages of arable land available for

food production in the world (Nellemann et al., 2009). As CA and SA

develop new strategies to produce more renewable energy there might

be a pressure for more acreage to produce bioenergy. Because climate

change will affect bioenergy and food crops at the same time, their

effects, as well as the adaptation measures related to agriculture,

will be similar. The main risks identified by Arvizu et al. (2011) are (1)

business as usual, (2) unreconciled growth, and (3) environment and

food versus fuel. Thus, the most important adaptation measures will

be the ones related to the control of economic growth, environmental

management, and agriculture production. The choice for lignocellulosic

feedstocks (e.g., sugarcane second-generation technologies) will be an

important mitigation/adaptation measure because these feedstocks do

not compete with food (Arvizu et al., 2011). In the case of sugarcane,

for instance, an increase of approximately 40% in the production of

bioethanol is expected as a result of the implantation of second-

generation technologies coupled with the first-generation ones already

existent in Brazil (Dias et al., 2012; de Souza et al., 2013).

Biodiesel production has the lowest costs in LA (Chum et al., 2011)

owing to the high production of soybean in Brazil and Argentina. The

use of biodiesel to complement oil-derived diesel is a productive choice

for adaptation measures regarding this bioenergy source. Also, the cost

of ethanol, mainly derived from sugarcane, is the lowest in CA, SA, and

LA (Chum et al., 2011) and as an adaptation measure, such costs, as

well as the one of biodiesel, should be lowered even more by improving

echnologies related to agricultural and industrial production of both.

Indeed, it has been reported that in LA the use of agricultural budgets

by governments for investment in public goods induces faster growth,

decreasing poverty and environmental degradation (López and Galinato,

2007).The pressure of soy expansion due to biodiesel demand can lead

to land use change and consequently to economic teleconnections, as

suggested by Nepstad et al. (2006). These teleconnections may link

Amazon deforestation derived from soy expansion to economic growth

in some developing countries because of changes in the demand of soy.

These effects may possibly mean a decrease in jobs related to small to big

farms in agriculture in Argentina (Tomei and Upham, 2009) on the one

hand, and deforestation in the Amazon due to the advance of soybean

cropping in the region on the other (Nepstad and Stickler, 2008).

27.3.7. Human Health

27.3.7.1. Observed and Projected Impacts and Vulnerabilities

Changes in weather extremes and climatic patterns are affecting human

health (high confidence), by increasing morbidity, mortality, and disabilities,

and through the emergence of diseases in previously non-endemic

regions (high confidence; Winchester and Szalachman, 2009; Rodríguez-

Morales, 2011). Heat waves and cold spells have increased urban

mortality rates (McMichael et al., 2006; Bell et al., 2008; Hardoy and

Pandiella, 2009; Muggeo and Hajat, 2009; Hajat et al., 2010). Outbreaks

of vector- and water-borne diseases were triggered in CA by Hurricane

Mitch in 1998 (Costello et al., 2009; Rodríguez-Morales et al., 2010),

while the 2010–2012 Colombian floods caused hundreds of deaths and

displaced thousands of people (Hoyos et al., 2012).

The number of cases of malaria have increased in Colombia during the

last 5 decades alongside air temperatures (Poveda et al., 2011; Arevalo-

Herrera et al., 2012), but also in urban and rural Amazonian regions

undergoing large environmental changes (Gil et al., 2007; Tada et al., 2007;

Cabral et al., 2010; da Silva-Nunes et al., 2012). Malaria transmission

has reached 2300 m in the Bolivian Andes, and vectors are found at

higher altitudes from Venezuela to Bolivia (Benítez and Rodríguez-

Morales, 2004; Lardeux et al., 2007; Pinault and Hunter, 2011).

Although the incidence of malaria has decreased in Argentina, its vector

density has increased in the northwest along with climate variables

(Dantur Juri et al., 2010, 2011). El Niño drives malaria outbreaks in

Colombia (Mantilla et al., 2009; Poveda et al., 2011), amidst other

factors (Rodríguez-Morales et al., 2006; Osorio et al., 2007; Restrepo-

Pineda et al., 2008). Linkages between ENSO and malaria are also

reported in Ecuador and Peru (Anyamba et al., 2006; Kelly-Hope and

Thomson, 2010), French Guiana (Hanf et al., 2011), Amazonia (Olson et

al., 2009), and Venezuela (Moreno et al., 2007).

Unlike malaria, dengue fever and its hemorrhagic variant are mostly

urban diseases whose vector is affected by climate conditions. Their

incidence have risen in tropical America in the last 25 years, causing

annual economic losses of US$2.1+ (1 to 4) billion (Torres and Castro,

2007; Tapia-Conyer et al., 2009; Shepard et al., 2011). Environmental

and climatic variability affect their incidence in CA (Fuller et al.,

2009; Rodríguez-Morales et al., 2010; Mena et al., 2011), in Colombia

1536

Chapter 27 Central and South America

(

Arboleda et al., 2009), and in French Guiana alongside malaria (Carme

et al., 2009; Gharbi et al., 2011). In Venezuela, dengue fever increases

during La Niña (Rodríguez-Morales and Herrera-Martinez, 2009; Herrera-

Martinez and Rodríguez-Morales, 2010). Weather and climate variability

are also associated with dengue fever in southern SA (Honório et al.,

2009; Costa et al., 2010; de Carvalho-Leandro et al., 2010; Degallier et

al., 2010; Lowe et al., 2011), involving also demographic and geographic

factors in Argentina (Carbajo et al., 2012). In Rio de Janeiro a 1°C increase

in monthly minimum temperature led to a 45% increase of dengue fever

in the next month, and 10 mm increase in rainfall to a 6% increase

(Gomes et al., 2012). Despite large vaccination campaigns, the risk of

yellow fever outbreaks has increased mostly in tropical America’s

densely populated poor urban settings (Gardner and Ryman, 2010),

alongside climate conditions (Jentes et al., 2011).

Schistosomiasis is endemic in rural areas of Suriname, Venezuela, the

Andean highlands, and rural and peripheral urbanized regions of Brazil

(Barbosa et al., 2010; Kelly-Hope and Thomson, 2010; Igreja, 2011). It

is highly likely that schistosomiasis will increase in a warmer climate

(Mangal et al., 2008; Mas-Coma et al., 2009; Lopes et al., 2010).

Vegetation indices are associated with human fascioliasis in the Andes

(Fuentes, 2004).

Hantaviruses have been recently reported throughout the region

(Jonsson et al., 2010; MacNeil et al., 2011), and El Niño and climate

change augment their prevalence (Dearing and Dizney, 2010). Variation

in hantavirus reservoirs in Patagonia is strongly dependent on climate

and environmental conditions (Andreo et al., 2012; Carbajo et al., 2009).

In Venezuela, rotavirus is more frequent and more severe in cities with

minimal seasonality (Kane et al., 2004). The peak of rotavirus in

Guatemala occurs in the dry season, causing 60% of total diarrhea cases

(Cortes et al., 2012).

In spite of its rapid decline, climate-sensitive Chagas disease is still a

major public health issue (Tourre et al., 2008; Moncayo and Silveira,

2009; Abad-Franch et al., 2009; Araújo et al., 2009; Gottdenker et al.,

2011). Climate also affects the most prevalent mycosis (Barrozo et al.,

2009), and ENSO is associated with outbreaks of bartonellosis in Peru

(Payne and Fitchett, 2010).

he high incidence of cutaneous leishmaniasis in Bolivia is exacerbated

during La Niña (Gomez et al., 2006; García et al., 2009). Cutaneous

leishmaniasis is affected in Costa Rica by temperature, forest cover, and

ENSO (Chaves et al., 2008), and in Colombia by land cover, altitude,

climatic variables, and El Niño (Cárdenas et al., 2006, 2007, 2008;

Valderrama-Ardila et al., 2010), and decreases during La Niña in

Venezuela (Cabaniel et al., 2005). Cutaneous leishmaniasis in Suriname

peaks during the March dry season (35%; van der Meide et al., 2008),

and in French Guiana is intensified after the October-December dry

season (Rotureau et al., 2007). The incidence of visceral leishmaniasis

has increased in Brazil (highest in LA) in association with El Niño and

deforestation (Ready, 2008; Cascio et al., 2011; Sortino-Rachou et al.,

2011), as in Argentina, Paraguay, and Uruguay (Bern et al., 2008;

Dupnik et al., 2011; Salomón et al., 2011; Fernández et al., 2012).

Visceral leishmaniasis transmission in Venezuela is associated with

rainfall seasonality (Feliciangeli et al., 2006; Rodríguez-Morales et al.,

2007). The incidence of skin cancer in Chile has increased in recent years,

concomitantly with climate and geographic variables (Salinas et al., 2006).

Onchocerciasis (river blindness) vector exhibits seasonal biting rates

(Botto et al., 2005; Rodríguez-Pérez et al., 2011), and leptospirosis is

prevalent in CA’s warm-humid tropical regions (Valverde et al., 2008).

Other climate-driven infectious diseases are ascariasis and gram-

positive cocci in Venezuela (Benítez et al., 2004; Rodríguez-Morales et

al., 2010) and Carrion’s disease in Peru (Huarcaya et al., 2004).

Seawater temperature affects the abundance of cholera bacteria (Koelle,

2009; Jutla et al., 2010; Marcheggiani et al., 2010; Hofstra, 2011), which

explains the outbreaks during El Niño in Peru, Ecuador, Colombia, and

Venezuela (Cerda Lorca et al., 2008; Martínez-Urtaza et al., 2008;

Salazar-Lindo et al., 2008; Holmner et al., 2010; Gavilán and Martínez-

Urtaza, 2011; Murugaiah, 2011).

The worsening of air quality and higher temperatures in urban settings

are increasing chronic respiratory and cardiovascular diseases, and

morbidity from asthma and rhinitis (Grass and Cane, 2008; Martins and

Andrade, 2008; Gurjar et al., 2010; Jasinski et al., 2011; Rodriguez et

al., 2011), but also atherosclerosis, pregnancy-related outcomes, cancer,

cognitive deficit, otitis, and diabetes (Olmo et al., 2011). Dehydration

Frequently Asked Questions

FAQ 27.3 | Are there emerging and reemerging human diseases

as a consequence of climate variability and change in the region?

Human health impacts have been exacerbated by variations and changes in climate extremes. Climate-related

diseases have appeared in previously non-endemic regions (e.g., malaria in the Andes, dengue in CA and southern

SA) (high conﬁdence). Climate variability and air pollution have also contributed to increase the incidence of

respiratory and cardiovascular, vector- and water-borne and chronic kidney diseases, hantaviruses and rotaviruses,

pregnancy-related outcomes, and psychological trauma (very high conﬁdence). Health vulnerabilities vary with

geography, age, gender, ethnicity, and socioeconomic status, and are rising in large cities. Without adaptation

measures (e.g., extending basic public health services), climate change will exacerbate future health risks, owing

to population growth rates and existing vulnerabilities in health, water, sanitation and waste collection systems,

nutrition, pollution, and food production in poor regions (medium conﬁdence).

1537

Central and South America Chapter 27

rom heat waves increases hospitalizations for chronic kidney diseases

(Kjellstrom et al., 2010), affecting construction, sugarcane, and cotton

workers in CA (Crowe et al., 2009, 2010; Kjellstrom and Crowe, 2011;

Peraza et al., 2012).

Extreme weather/climate events affect mental health in Brazil (depression,

psychological distress, anxiety, mania, and bipolar disorder), in particular

in drought-prone areas of NEB (Coêlho et al., 2004; Volpe et al., 2010).

Extreme weather, meager crop yields, and low GDP are also associated

with increased violence (McMichael et al., 2006).

Multiple factors increase the region’s vulnerability to climate change:

precarious health systems; malnutrition; inadequate water and sanitation

services; poor waste collection and treatment systems; air, soil, and

water pollution; lack of social participation; and inadequate governance

(Luber and Prudent, 2009; Rodríguez-Morales, 2011; Sverdlik, 2011).

Human health vulnerabilities in the region depend on geography, age

(Perera, 2008; Martiello and Giacchi, 2010; Åstrom et al., 2011; Graham

et al., 2011), gender (de Oliveira et al., 2011), race, ethnicity, and

socioeconomic status (Diez Roux et al., 2007; Martiello and Giacchi,

2010). Neglected tropical diseases in LA cause 1.5 to 5.0 million

disability-adjusted life years (DALYs) (Hotez et al., 2008).

Vulnerability of megacities (see Section 27.3.5) is aggravated by access

to clean water, rapid spread of diseases (Borsdorf and Coy, 2009), and

migration from rural areas forced by disasters (Campbell-Lendrum and

Corvalán, 2007; Borsdorf and Coy, 2009; Hardoy and Pandiella, 2009).

Human health vulnerabilitieshave been assessed in Brazil through

composite indicators involving epidemiological variables, downscaled

climate scenarios,and socioeconomic projections (Confalonieri et al.,

2009; Barata et al., 2011; Barbieri and Confalonieri, 2011). The Andes and

CA are among the regions of highest predicted losses (1 to 27%) in

labor productivity from future climate scenarios (Kjellstrom et al., 2009).

27.3.7.2. Adaptation Strategies and Practices

Adaptation efforts in the region (Blashki et al., 2007; Costello et al.,

2011) are hampered by lack of political commitment, gaps in scientific

knowledge, and institutional weaknesses (Keim, 2008; Lesnikowski et

al., 2011; Olmo et al., 2011; see Section 27.4.3). Research priorities and

current strategies must be reviewed (Halsnæs and Verhagen, 2007;

Romero and Boelaert, 2010; Karanja et al., 2011), and preventive/

responsive systems must be put in place (Bell, 2011) to foster adaptive

capacity (Campbell-Lendrum and Bertollini, 2010; Huang et al., 2011).

Colombia established a pilot adaptation program to cope with changes

in malaria transmission and exposure (Poveda et al., 2011). The city of

São Paulo has implemented local pollution control measures, with the

co-benefit of reducing GHG emissions (de Oliveira, 2009; Nath and

Behera, 2011).

Human well-being indices must be explicitly stated as adaptation

policies in LA (e.g., Millennium Development Goals; Franco-Paredes et

al., 2007; Halsnæs and Verhagen, 2007; Mitra and Rodriguez-Fernandez,

2010). South–south cooperation and multidisciplinary research are

required to design relevant adaptation and mitigation strategies (Tirado

et al., 2010; Team and Manderson, 2011).

27.4. Adaptation Opportunities,

Constraints, and Limits

27.4.1. Adaptation Needs and Gaps

During the last few years, the study of adaptation to climate change

has progressively switched from an impact-focused approach (mainly

climate-driven) to include a vulnerability-focused vision (Boulanger et

al., 2011). As a consequence, the development and implementation of

systemic adaptation strategies, involving institutional, social, ecosystem,

environmental, financial, and capacity components (see Chapter 14) to

cope with present climate extreme events is a key step toward climate

change adaptation, especially in SA and CA countries. Although different

frameworks and definitions of vulnerability exist, a general tendency

aims at studying vulnerability to climate change, especially in SA and

CA, focusing on the following aspects: urban vulnerability (e.g., Hardoy

and Pandiella, 2009; Heinrichs and Krellenberg, 2011), rural community

(McSweeney and Coomes, 2011; Ravera et al., 2011), rural farmer

vulnerability (Oft, 2010), and sectoral vulnerability (see Section 27.3). The

approach used can be holistic or systemic (Ison, 2010; Carey et al., 2012b),

where climate drivers are actually few with respect to all other drivers

related to human and environment interactions including physical,

economic, political, and social context, as well as local characteristics

such as occupations, resource uses, accessibility to water, and so forth

(Manuel-Navarrete et al., 2007; Young et al., 2010).

In developing and emergent countries, there exists a general consensus

that the adaptive capacity is low, strengthened by the fact that poverty

is the key determinant of vulnerability in LA (to climate-related natural

hazards; see Rubin and Rossing, 2012) and thus a limit to resilience

(Pettengell, 2010) leading to a “low human development trap” (UNDP,

2007). However, Magnan (2009, p. 1) suggests that this analysis is biased

by a “relative immaturity of the science of adaptation to explain what

are the processes and the determinants of adaptive capacity.” Increasing

research efforts on the study of adaptation is therefore of great

importance to improve understanding of the actual societal, economical,

community, and individual drivers defining the adaptive capacity.

Especially, a major focus on traditions and their transmission (Young

and Lipton, 2006) may actually indicate potential adaption potentials

in remote and economically poor regions of SA and CA. Such a potential

does not dismiss the fact that the nature of future challenges may

actually not be compared to past climate variability (e.g., glacier retreat

in the Andes).

Coping with new situations may require new approaches such as a multi-

level risk governance (Corfee-Morlot et al., 2011; Young and Lipton, 2006)

associated with decentralization in decision making and responsibility.

Although the multi-level risk governance and the local participatory

approach are interesting frameworks for strengthening adaptation

capacity, perception of local and national needs is diverging, challenging

the implementation of adaptation strategies in CA/SA (Salzmann et al.,

2009). At present, despite an important improvement during the last

few years, there still exists a certain lack of awareness of environmental

changes and their implications for livelihoods and businesses (Young

et al., 2010). Moreover, considering the limited financial resources of

some states in CA and SA, long-term planning and the related human

and financial resource needs may be seen as conflicting with present

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Chapter 27 Central and South America

ocial deficit in the welfare of the population. This situation weakens

the importance of adaptation planning to climate change in the political

agenda (Carey et al., 2012b), and therefore requires international

involvement as one facilitating factor in natural hazard management

and climate change adaptation, with respect to sovereignty according

to international conventions including the United Nations Framework

Convention on Climate Change (UNFCCC). In addition, as pointed out

by McGray et al. (2007), development, adaptation, and mitigation are

not separate issues. Development and adaptation strategies especially

should be tackled together in developing countries such as SA and CA,

focusing on strategies to reduce vulnerability. The poor level of adaptation

of present-day climate in SA and CA countries is characterized by the

fact that responses to disasters are mainly reactive rather than preventive.

Some early warning systems are being implemented, but the capacity

of responding to a warning is often limited, particularly among poor

populations. Finally, actions combining public communication (and

education), public decision-maker capacity-building, and a synergetic

development-adaptation funding will be key to sustain the adaptation

process that CA and SA require to face future climate change challenges.

27.4.2. Practical Experiences of Autonomous and

Planned Adaptation, Including Lessons Learned

Adaptation processes in many cases have been initiated a few years

ago, and there is still a lack of literature to evaluate their efficiency in

reducing vulnerability and building resilience of the society against

climate change. However, experiences of effective adaptation and

maladaptation are slowly being documented (see also Section 27.4.3);

some lessons have already been learned from these first experiences

(see Section 27.3); and tools, such as the Index of Usefulness of Practices

for Adaptation (IUPA) to evaluate adaptation practices, have been

developed for the region (Debels et al., 2009). Evidenced by these

practical experiences, there is a wide range of options to foster adaptation

and thus adaptive capacity in CA and SA. In CA and SA, many societal

issues are strongly connected to development goals and are often

considered a priority in comparison to adaptation efforts to climate

change. However, according to the 135 case studies analyzed by McGray

et al. (2007), 21 of which were in CA and SA, the synergy between

development and adaptation actions makes it possible to ensure a

sustainable result of the development projects.

Vulnerability and disaster risk reduction may not always lead to long-

term adaptive capacity (Tompkins et al., 2008; Nelson and Finan, 2009),

except when structural reforms based on good governance (Tompkins

et al., 2008) and negotiations (de Souza Filho and Brown, 2009) are

implemented. While multi-level governance can help to create resilience

and reduce vulnerability (Roncoli, 2006; Young and Lipton, 2006;

Corfee-Morlot et al., 2011), capacity-building (Eakin and Lemos, 2006),

good governance, and enforcement (Lemos et al., 2010; Pittock, 2011)

are key components.

Autonomous adaptation experience is mainly realized at local levels

(individual or communitarian) with examples found, for instance, for rural

communities in Honduras (McSweeney and Coomes, 2011), Indigenous

communities in Bolivia (Valdivia et al., 2010), and coffee agroforestry

systems in Brazil (de Souza et al., 2012). However, such adaptation

rocesses do not always respond specifically to climate forcing. For

instance, the agricultural sector adapts rapidly to economic stressors,

although, despite a clear perception of climate risks, it may last longer

before responding to climate changes (Tucker et al., 2010). In certain

regions or communities, such as Anchioreta in Brazil (Schlindwein et al.,

2011), adaptation is part of a permanent process and is actually tackled

through a clear objective of vulnerability reduction, maintaining and

diversifying a large set of natural varieties of corn, allowing the farmers

to diversify their planting. Another kind of autonomous adaptation is

the southward displacement of agriculture activities (e.g., wine, coffee)

through the purchase of lands, which will become favorable for such

agriculture activities in a warmer climate. In Argentina, the increase of

precipitation observed during the last 30 years contributed to a

westward displacement of the annual crop frontier.

However, local adaptation to climate and non-climate drivers may

undermine long-term resilience of socio-ecological systems when local,

short-term strategies designed to deal with specific threats or challenges

do not integrate a more holistic and long-term vision of the system at

threat (Adger et al., 2011). Thus, policy should identify the sources of

and conditions for local resilience and strengthen their capacities to

adapt and learn (Borsdorf and Coy, 2009; Adger et al., 2011; Eakin et

al., 2011), as well as to integrate new adapted tools (Oft, 2010). This

sets the question of convergence between the local-scale/short-term

and broad-scale/long-term visions in terms of perceptions of risks, needs

to adapt, and appropriate policies to be implemented (Eakin and Wehbe,

2009; Salzmann et al., 2009). Even if funding for adaptation is available,

the overarching problem is the lack of capacity and/or willingness to

address the risks, especially those threatening lower income groups

(Satterthwaite, 2011a). Adaptation to climate change cannot eliminate

the extreme weather risks, and thus efforts should focus on disaster

preparedness and post-disaster response (Sverdlik, 2011). Migration is

the last resort for rural communities facing water stress problems in CA

and SA (Acosta-Michlik et al., 2008).

In natural hazard management contributing to climate change adaptation,

specific cases such as the one in Lake 513 in Peru (Carey et al., 2012b)

clearly allowed identification of facilitating factors for a successful

adaptation process (technical capacity, disaster events with visible

hazards, institutional support, committed individuals, and international

involvement) as well as impediments (divergent risk perceptions, imposed

government policies, institutional instability, knowledge disparities, and

invisible hazards). In certain cases, forward-looking learning (anticipatory

process), as a contrast to learning by shock (reactive process), has been

found as a key element for adaptation and resilience (Tschakert and

Dietrich, 2010) and should be promoted as a tool for capacity-

building at all levels (stakeholders, local and national governments). Its

combination with role-playing game and agent-based models (Rebaudo

et al., 2011) can strengthen and accelerate the learning process.

Planned adaptation policies promoted by governments have been

strengthened by participation in international networks, where experience

and knowledge can be exchanged. As an example, the C40 Cities-Climate

Leadership Group or ICLEI include Bogotá (Colombia), Buenos Aires

(Argentina), Caracas (Venezuela), Curitiba, Rio de Janeiro, and São Paulo

(Brazil), Lima (Peru), and Santiago de Chile (Chile). Most of these cities

have come up with related action and strategy plans (e.g., Action Plan

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Central and South America Chapter 27

uenos Aires 2030, Plan of Caracas 2020, or the Metropolitan Strategy

to CCA of Lima) (C40 Cities, 2011).

At a regional policy level, an example of intergovernmental initiatives

in SA and CA is the Ibero-American Programme on Adaptation to Climate

Change (PIACC), developed by the Ibero-American Network of Climate

Change Offices (RIOCC) (Keller et al., 2011b). For CA specifically, the

Central American Commission for Environment and Development (CCAD)

brings together the environmental ministries of the Central American

Integration System (Sistema de la Integración Centroamericana (SICA))

that released its climate change strategy in 2010 (CCAD and SICA, 2010;

Keller et al., 2011a).

These initiatives demonstrate that there has been a growing awareness

of CA and SA governments on the need to integrate climate change

and future climate risks in their policies. To date, in total, 18 regional

Non-Annex countries, including Argentina, Belize, Bolivia, Brazil, Chile,

Colombia, Costa Rica, Ecuador, El Salvador, Guatemala, Honduras,

Nicaragua, Guyana, Panama, Paraguay, Peru, Suriname, Uruguay, and

Venezuela, have already published their first and/or second National

Communication to the UNFCCC (see UNFCCC, 2012), making it possible

to measure the country’s emissions and to assess its present and future

vulnerability.

27.4.3. Observed and Expected Barriers to Adaptation

Adaptation is a dynamic process, which to be efficient requires a

permanent evolution and even transformation of the vulnerable system.

Such a transformation process can be affected by several constraints,

including constraints affecting the context of adaptation as well as the

implementation of policies and measures (see Section 16.3.2).

Major constraints related to the capacity and resources needed to

support the implementation of adaptation policies and processes include:

access to (Lemos et al., 2010) and exchange of knowledge (e.g., adaptive

capacity can be enhanced by linking indigenous and scientific knowledge;

Valdivia, 2010); access to and quality of natural resources (López-

Marrero, 2010); access to financial resources, especially for poor

households (Satterthwaite, 2011b; Hickey and Weis, 2012; Rubin and

Rossing, 2012), as well as for institutions (Pereira et al., 2009); access to

technological resources (López-Marrero, 2010) and technical assistance

(Guariguata, 2009; Eakin et al., 2011), as well as the fostering of public-

private technology transfer (La Rovere et al., 2009; Ramirez-Villegas et

al., 2012) and promotion of technical skills (Hickey and Weis, 2012); and

social asset-based formation at the local level (Rubin and Rossing,

2012).

In terms of framing adaptation, as a constraint to affect the adaptation

context, it is usually considered that a major barrier to adaptation is

the perception of risks, and many studies focused on such an issue (e.g.,

Schlindwein et al., 2011). New studies (Adger et al., 2009) identified

social limits to possible adaptation to climate change in relation with

issues of values and ethics, risk, knowledge, and culture, even though

such limits can evolve in time. Indeed, while being a necessary condition,

perception may not be the main driver for initiating an adaptation

process. As pointed out by Tucker et al. (2010) with a specific focus on

A, exogenous factors (economic, land tenure, cost, etc.) may actually

strongly constrain the decision-making process involved in a possible

adaptation process. In that sense, efficient governance and management

are key components in the use of climate and non-climate information

in the decision-making and adaptation process. As a consequence, it is

difficult to describe adaptation without defining at which level it is

thought. Indeed, though much effort is invested in national and regional

policy initiatives, most of the final adaptation efforts will be local.

National and international (transborder) governance is key to build

adaptive capacity (Engle and Lemos, 2010) and therefore to strengthen

(or weaken) local adaptation through efficient policies and delivery of

resources. At a smaller scale (Agrawal, 2008), local institutions can

strongly contribute to vulnerability reduction and adaptation. However,

at all levels, the efficiency in national and local adaptation activities

strongly depend on the capacity-building and information transmission

to decision makers (Eakin and Lemos, 2006).

27.5 Interactions between

Adaptation and Mitigation

Synergies between adaptation and mitigation strategies on the local

level can be reached as a result of self-organization of communities in

cooperatives (see, e.g., “The SouthSouthNorth Capacity Building Module

on Poverty Reduction” (SSN Capacity Building Team, 2006), which

manages recycling or renewable energy production, leading to an

increase in energy availability, thus production capacity, and therefore

new financial resources). Moreover, Venema and Cisse (2004) also

support the development of decentralized renewable energy solutions

for the growth of renewable energy in CA and SA (see also Section

27.3.6) next to a large infrastructure project (see their case studies for

Argentina and Brazil).

In spite of their smaller size (individual or communitarian), these solutions

offer adaptation and mitigation benefits. On one hand, fossil-based

energy consumption is reduced, while energy availability is increased.

On the other hand, reduction of energy precariousness is key in any

development strategy. Thus, it allows local community and individuals

to grow socially and economically, and therefore to reduce vulnerability,

avoiding the poverty trap (UNDP, 2007), and to initiate an adaptation

process based on non-fossil fuel energy sources. Such initiatives also

depend on local and organizational leaderships (UN-HABITAT, 2011).

Such integrated strategies of income generation as adaptation measures

as well as production of renewable energy are also identified for

vulnerable, small farmers diversifying their crops toward crops for

vegetable oil and biodiesel production in Brazil. Barriers identified

concern capacity-building and logistical requirements, making policy tools,

credit mechanism, and organization into cooperatives, and fostering

necessary research (La Rovere et al., 2009). Other promising interactions

of mitigation and adaptation are identified, for example, for the

management of Brazilian tropical natural and planted forest (Guariguata,

2009).

At national and regional scales, CA and SA countries will require the

allocation of human and financial resources to adapt to climate change.

While resources are limited, too large an economic dependence of these

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Chapter 27 Central and South America

ountries to fossil fuels will reduce their adaptive capacity. The reduction

in energy consumption and the integration of renewable energies in

their energetic matrix is therefore a key issue for all these countries to

sustain their development and growth and therefore increase their

adaptive capacity (see also Section 27.3.6).

Reforestation and avoided deforestation are important practices that

contribute to both mitigation and adaptation efforts in the region as

in other parts of the world. Maintaining forest cover can provide a

suite of environmental services including local climate regulation, water

regulation, and reduced soil erosion—all of which can reduce the

vulnerability of communities to variable climate (see Section 27.3.2.2;

Vignola et al., 2009).

27.6. Case Studies

27.6.1. Hydropower

Hydropower is the main source of renewable energy in CA and SA (see

Section 27.3.6). The region is second only to Asia in terms of hydropower

energy generation in the world, displaying a 20% share of total annual

generation and an average regional capacity factor of greater than 50%

(SRREN Table 5-1; IPCC, 2011). As a result, the region has by far the

largest proportion of electricity generated through hydropower facilities

(Table 27-6). The hydropower proportion of total electricity production

is greater than 40% in the region, and in some cases is near or close to

80%, as in the case of Brazil, Colombia, and Costa Rica (IEA, 2012).

Although there is debate, especially in tropical environments, about GHG

emissions from hydropower reservoirs (Fearnside and Pueyo, 2012), this

form of electricity generation is often seen as a major contributor to

mitigating GHG emissions worldwide (see IPCC, 2011; Kumar et al., 2011).

But, on the other hand, hydropower is a climate-related sector, thus

making it prone to the potential effects of changing climate conditions

(see Section 27.3.1.1). In this regard the CA and SA region constitutes

a unique example to study these relations between climate change

mitigation and adaptation in relation to hydropower generation.

Diverse studies have analyzed the potential impacts of climate change

on hydropower generation (Table 27-4). Maurer et al. (2009) studied

future conditions for the Lempa River (El Salvador, Honduras, and

Guatemala), showing a potential reduction in hydropower capacity of

33 to 53% by 2070–2099. A similar loss is expected for the Sinú-Caribe

basin in Colombia where, despite a general projection of increased

precipitation, losses due to evaporation enhancement reduce inflows

to hydroelectric systems, thus reducing electricity generation up to 35%

(Ospina Noreña et al., 2009a). Further studies (Ospina Noreña et al.,

2011a,b) have estimated vulnerability indices for the hydropower sector

in the same basin, and identified reservoir operation strategies to reduce

this vulnerability. Overall reductions in hydropower generation capacity

are also expected in Chile for the main hydropower generation river

basins (Maule, Laja, and Biobio (ECLAC, 2009a; McPhee et al., 2010; Stehr

et al., 2010)), and also in the Argentinean Limay River basin (Seoane and

López, 2007). Ecuador, on the other hand, faces an increase in generation

capacity associated with an increment in precipitation on its largest

hydroelectric generator, the Paute River basin (Buytaert et al., 2010).

Brazil, although being the country with the largest installed hydroelectric

apacity in the region, still has unused generation capacity in sub-basins

of the Amazon River (Soito and Freitas, 2011). However, future climate

conditions plus environmental concerns pose an important challenge

for the expansion of the system (Freitas and Soito, 2009; Andrade et al.,

2012; Finer and Jenkins, 2012). According to de Lucena et al. (2009),

hydropower systems in southern Brazil (most significantly the Parana

River system) could face a slight increase in energy production under

an A2 scenario. However, the rest of the country’s hydropower system,

especially those in NEB, could face a reduction in power generation,

thus reducing the reliability of the whole system (de Lucena et al., 2009).

An obvious implication of the mentioned impacts is the need to replace

the energy lost through alternative (see Section 27.3.6.2) or traditional

sources. Adaptation measures have been studied for Brazil (de Lucena

et al., 2010a), with results implying an increase in natural gas and

sugarcane bagasse electricity generation on the order of 300 TWh,

increase in operation costs on the order of US$7 billion annually, and

US$50 billion in terms of investment costs by 2035. In Chile, the study

by ECLAC (2009a) assumed that the loss in hydropower generation, on

the order of 18 TWh for the 2011–2040 period (a little over 10% of

actual total hydropower generation capacity) would be compensated by

the least operating cost source available, coal-fired power plant, implying

an increase of 2 MT CO

-eq of total GHG emissions (emissions for the

electricity sector in Chile totaled 25 MT CO

-eq in 2009). Ospina Noreña

(2011a,b) studied some adaptation options, such as changes in water

use efficiency or demand growth that could mitigate the expected

impacts on hydropower systems in the Colombian Sinú-Caribe River

basin. Changes in seasonality and total availability could also increase

complexities in the management of multiple-use dedicated basins in

Peru (Juen et al., 2007; Condom et al., 2012), Chile (ECLAC, 2009a), and

Argentina (Seoane and López, 2007), that could affect the relationship

between different water users within a basin. It is worth noting that

those regions that are projected to face an increase in streamflow and

associated generation capacity, such as Ecuador or Costa Rica, also

share difficulties in managing deforestation, erosion, and sedimentation

which limits the useful life of reservoirs (see Section 27.3.1.1). In these

cases it is important to consider these effects in future infrastructure

operation (Ferreira and Teegavarapu, 2012) and planning, and also to

enhance the ongoing process of recognizing the value of the relation

between ecosystem services and hydropower system operations (Leguía

et al., 2008) (see more on PES in Sections 27.3.2.2, 27.6.2).

27.6.2. Payment for Ecosystem Services

Payment for ecosystem services (PES) is commonly described as a set of

transparent schemes for securing a well-defined ecosystem service (or a

land use capable to secure that service) through conditional payments

or compensations to voluntary providers (Engel et al., 2008; Tacconi,

2012). Van Noordwijk et al. (2012) provides a broader definition to PES

by arguing that it encompasses three complementary approaches: (1)

the one above, that is, commodification of predefined ecosystem services

so that prices can be negotiated between buyers and sellers; plus (2)

compensation for opportunities forgone voluntarily or by command and

control decisions; and (3) coinvestment in environmental stewardships.

Therefore, the terms conservation agreements, conservation incentives,

and community conservation are often used as synonyms or as something

1541

Central and South America Chapter 27

different or broader than PES (Milne and Niesten, 2009; Cranford and

Mourato, 2011). For simplicity, we refer to PES in its broadest sense

(van Noordwijk et al., 2012).

Services subjected to such types of agreements often include regulation

of freshwater flows, carbon storage, provision of habitat for biodiversity,

and scenic beauty (de Koning et al., 2011; Montagnini and Finney, 2011).

Because the ecosystems that provide the services are mostly privately

owned, policies often aim at supporting landowners to maintain the

provision of services over time (Kemkes et al., 2010). Irrespective of the

debate as to whether payments or compensations should be designed

to focus on actions or results (Gibbons et al., 2011), experiences in

Colombia, Costa Rica, and Nicaragua show that PES can finance

conservation, ecosystem restoration, and better land use practices

(Montagnini and Finney, 2011; see also Table 27-5). However, based on

examples from Ecuador and Guatemala, Southgate et al. (2010) argue

that uniformity of payment for beneficiaries can be inefficient if recipients

accept less compensation in return for conservation measures, or if

recipients that promote greater environmental gains receive only the

prevailing payment. Other setbacks to PES schemes might include cases

where there is a perception of commoditization of nature and its

intangible values (e.g., Bolivia, Cuba, Ecuador, and Venezuela); other

cases where mechanisms are inefficient to reduce poverty; and slowness

to build trust between buyers and sellers, as well as gender and land

tenure issues that might arise (Asquith et al., 2008; Peterson et al., 2010;

Balvanera et al., 2012; van Noordwijk et al., 2012). Table 27-7 lists

select examples of PES schemes in Latin America, with a more complete

and detailed list given in Balvanera et al. (2012).

The PES concept (or “fishing agreements”) also applies to coastal and

marine areas, although only a few cases have been reported. Begossi

(2011) argues that this is due to three factors: origin (the mechanism

was originally designed for forests), monitoring (marine resources such

as fish are more difficult to monitor than terrestrial resources), and

definition of resource boundaries in offshore water. One example of a

compensation mechanism in the region is the so-called defeso, in Brazil.

It consists of a period (reproductive season) when fishing is forbidden

by the government and fishermen receive a financial compensation. It

applies to shrimp, lobster, and both marine and freshwater fisheries

(Begossi et al., 2011).

27.7. Data and Research Gaps

The scarcity of and difficulty in obtaining high-resolution, high quality,

and continuous climate, oceanic, and hydrological data, together with

availability of only very few complete regional studies, pose challenges

for the region to address changes in climate variability and the

identification of trends in extremes, in particular for CA. This situation

hampers studies on frequency and variability of extremes, as well as

impacts and vulnerability analyses of the present and future climates,

and the development of vulnerability assessments and adaptation

actions.

Related to observed impacts in most sectors, there is an imbalance in

information availability among countries. While more studies have been

performed for Brazil, southern SA, and SESA region, much less are

available for CA and for some regions of tropical SA. An additional

problem is poor dissemination of results in peer-reviewed publications

because most information is available only as grey literature. There is a

need for studies focused on current impacts and vulnerabilities across

sectors throughout CA and SA, with emphasis on extremes to improve

risk management assessments.

The complex interactions between climate and non-climate drivers make

the assessment of impacts and projections difficult, as is the case for

water availability and streamflows owing to current and potential

deforestation, overfishing and pollution regarding the impacts on fisheries,

or impacts on hydroenergy production. The lack of interdisciplinary

integrated studies limits our understanding of the complex interactions

between natural and socioeconomic systems. In addition, accelerating

deforestation and land use changes, as well as changes in economic

conditions, impose a continuous need for updated and available data

sets that feed basic and applied studies.

To address the global challenge of food security and food quality, both

important issues in CA and SA, investment in scientific agricultural

knowledge needs to be reinforced, mainly with regard to the integration

of agriculture with organic production, and the integration of food and

bioenergy production. It is necessary to consider ethical aspects when

the competition for food and bioenergy production is analyzed to

identify which activity is most important at a given location and time

and whether bioenergy production would affect food security for a

particular population.

SLR and coastal erosion are also relevant issues; the lack of comparable

measurements of SLR in CA and SA make the present and future

integrated assessment of the impacts of SLR in the region difficult. Of

local and global importance will be improving our understanding of the

physical oceanic processes, in particular of the Humboldt Current system

flowing along the west coast of SA, which is one of the most productive

systems worldwide.

Countries Level Start Name Beneﬁ ts References

Brazil Sub-national

(

Amazonas state)

2007 Bolsa Floresta By 2008, 2700 traditional and indigenous families already beneﬁ tted: ﬁ nancial

ompensation and health assistance in exchange for zero deforestation in primary forests.

Viana (2008)

Costa Rica National 1997 Fondo Nacional de

inanciamiento Forestal

PES is a strong incentive for reforestation and, for agroforestry ecosystems alone, more than

000 contracts have been set since 2003 and nearly 2 million trees planted.

Montagnini and Finney

(

2011)

cuador National 2008 Socio-Bosque By 2010, the program already included more than half a million hectares of natural

ecosystems protected and has more than 60,000 beneﬁ ciaries.

e Koning et al. (2011)

uatemala National 1997 Programa de Incentivos

Forestales

y 2009, the program included 4174 beneﬁ ciaries, who planted 94,151 hectares of forest. In

addition, 155,790 hectares of natural forest were under protection with monetary incentives.

NE (2011)

Countries Level Start Name Beneﬁ ts References

razil Sub-national

(Amazonas state)

007 Bolsa Floresta By 2008, 2700 traditional and indigenous families already beneﬁ tted: ﬁ nancial

compensation and health assistance in exchange for zero deforestation in primary forests.

iana (2008)

osta Rica National 1997 Fondo Nacional de

Financiamiento Forestal

ES is a strong incentive for reforestation and, for agroforestry ecosystems alone, more than

7000 contracts have been set since 2003 and nearly 2 million trees planted.

ontagnini and Finney

(2011)

cuador National 2008 Socio-Bosque By 2010, the program already included more than half a million hectares of natural

ecosystems protected and has more than 60,000 beneﬁ ciaries.

e Koning et al. (2011)

Guatemala National 1997 Programa de Incentivos

orestales

By 2009, the program included 4174 beneﬁ ciaries, who planted 94,151 hectares of forest. In

ddition, 155,790 hectares of natural forest were under protection with monetary incentives.

INE (2011)

Countries Level Start Name Beneﬁ ts References

razil Sub-national

(Amazonas state)

007 Bolsa Floresta By 2008, 2700 traditional and indigenous families already beneﬁ tted: ﬁ nancial

compensation and health assistance in exchange for zero deforestation in primary forests.

iana (2008)

osta Rica National 1997 Fondo Nacional de

Financiamiento Forestal

ES is a strong incentive for reforestation and, for agroforestry ecosystems alone, more than

7000 contracts have been set since 2003 and nearly 2 million trees planted.

ontagnini and Finney

(2011)

cuador National 2008 Socio-Bosque By 2010, the program already included more than half a million hectares of natural

ecosystems protected and has more than 60,000 beneﬁ ciaries.

e Koning et al. (2011)

Guatemala National 1997 Programa de Incentivos

orestales

By 2009, the program included 4174 beneﬁ ciaries, who planted 94,151 hectares of forest. In

ddition, 155,790 hectares of natural forest were under protection with monetary incentives.

INE (2011)

Table 27-7 | Cases of government-funded physiological-ecological simulation (PES) schemes in Central America and South America.

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Chapter 27 Central and South America

ore information and research about the impacts of climate variability

and change on human health is needed. One problem is the difficulty

in accessing health data that are not always archived and ready to be

used in integrated studies. Another need refers to building the necessary

critical mass of transdisciplinary scientists to tackle the climate change-

human health problems in the region. The prevailing gaps in scientific

knowledge hamper the implementation of adaptation strategies, thus

demanding a review of research priorities toward better disease control.

With the aim of further studying the health impacts of climate change

and identifying resilience, mitigation, and adaptation strategies, South-

South cooperation and multidisciplinary research are considered to be

relevant priorities.

In spite of the uncertainty that stems from global and regional climatic

projections, the region needs to act in preparation for a possible increase

in climate variability and in extremes. It is necessary to undertake research

activities leading to public policies to assist societies in coping with

current climate variability, such as, for example, risk assessment and risk

management. Another important aspect since AR4 is the improvement

of climate modeling and the generation of high-resolution climate

scenarios, which in countries in CA and SA resulted in the first integrated

regional studies on impacts and vulnerability assessments of climate

change focusing on sectors such as agriculture, energy, and human

health.

Research on adaptation and the scientific understanding of the various

processes and determinants of adaptive capacity is also mandatory for

the region, with particular emphasis on increasing adaptation capacity

involving the traditional knowledge of ancestral cultures and how this

knowledge is transmitted. Linking indigenous knowledge with scientific

knowledge is important. The concept of “mother earth” (madre tierra

in Spanish) as a living system has been mentioned in recent years, as a

key sacred entity on the view of indigenous nations and as a system

that may be affected and also resilient to climate change. Although

some adaptation processes have been initiated in recent years dealing

with this and other indigenous knowledge, there is only very limited

scientific literature discussing these subjects so far.

The research agenda needs to address vulnerability and foster adaptation

in the region, encompassing an inclusion of the regions’ researchers and

focusing also on governance structures and action-oriented research

that addresses resource distribution inequities.

Regional and international partnerships, and research networks and

programs, have allowed linking those programs with local strategies

for adaptation and mitigation, also providing opportunities to address

research gaps and exchange among researchers. Examples are the

European Union funded projects CLARIS LPB (La Plata Basin) in SESA,

and AMAZALERT in Amazonia. Other important initiatives come from

the Interamerican Institute for Global Change Research (IAI), World

Health Organization (WHO), Global Environment Facility (GEF), Inter-

American Development Bank (IDB), Economic Commission for Latin

America and the Caribbean (ECLAC, CEPAL), La Red, and BirdLife

International, among others. The same holds for local international

networks such as the International Council for Local Environmental

Initiatives (ICLEI) or C40, of which CA and SA cities form part. The

weADAPT initiative is a good example on how CA and SA practitioners,

esearchers, and policy makers can have access to credible, high-quality

information and to share experiences and lessons learned in other

regions of the world.

27.8. Conclusions

CA and SA harbor unique ecosystems and maximum biodiversity, with

a variety of eco-climatic gradients rapidly changing from development

initiatives. Agricultural and beef production as well as bioenergy crops

are on the rise, mostly by expanding agricultural frontiers. Poverty and

inequality are decreasing, but at a slow pace. Socioeconomic development

shows a high level of heterogeneity and a very unequal income

distribution, resulting in high vulnerability to climatic conditions. There

is still a high and persistent level of poverty in most countries (45% for

CA and 30% for SA for year 2010) in spite of the sustained economic

growth observed in the last decade.

The IPCC AR4 and SREX reports contain ample evidence of increase in

extreme climate events in CA and SA. During 2000–2013, 613 weather

and climate extreme events led to 13,883 fatalities and 53.8 million

people affected, with estimated losses of US$52.3 billion. During 2000–

2009, 39 hurricanes occurred in the CA-Caribbean basin compared to

15 and 9 in the decade of 1980 and 1990, respectively. In SESA, more

frequent and intense rainfall extremes have favored an increase in the

occurrence of flash floods and landslides. In Amazonia extreme droughts

were reported in 2005 and 2010, and record floods were observed in

2009 and 2012. In 2012–2013 an extreme drought affected NEB.

While warming occurred in most of CA and SA, cooling was detected

off the coast of southern Peru and Chile. There is growing evidence that

Andean glaciers (both tropical and extratropical) are retreating in

response to warming trends. Increases in precipitation were registered

in SESA, CA, and the NAMS regions, while decreases were observed in

southern Chile, and a slight decrease in NEB after the middle 1970s.

In CA a gradual delay of the beginning of the rainfall season has been

observed. SLR varied from 2 to 7 mm yr

–1

between 1950 and 2008 in

CA and SA, which is a reason for concern because a large proportion of

the population of the region lives by the coast.

Land use and land cover change are key drivers of regional environmental

change in SA and CA. Natural ecosystems are affected by climate

variability/change and land use change. Deforestation, land degradation,

and biodiversity loss are attributed mainly to increased extensive

agriculture for traditional export activities and bioenergy crops.

Agricultural expansion has affected fragile ecosystems, causing severe

environmental degradation and reducing the environmental services

provided by these ecosystems. Deforestation has intensified the process

of land degradation, increasing the vulnerability of communities exposed

to floods, landslides, and droughts. Plant species are rapidly declining

in CA and SA, with a high percentage of rapidly declining amphibian

species. However, the region has still large extensions of natural

vegetation cover, with the Amazon being the main example. Ecosystem-

based adaptation practices, such as the establishment of protected

areas and their effective management, conservation agreements,

community management of natural areas, and payment for ecosystem

services are increasingly more common across the region.

1543

Central and South America Chapter 27

Figure 27-7 summarizes of some of the main observed trends in global

environmental change drivers across different representative regions of

CA and SA. Changes in climate and non-climate drivers have to be

compounded with other socioeconomic related trends, such as the rapid

urbanization experienced in the region.

Some observed impacts on human and natural systems can be directly

or indirectly attributed to human influences (see also Figure 27-8):

• Changes in river flow variability in the Amazon River during the last

2 decades, robust positive trends in streamflow in sub-basins of the

La Plata River basin, and increased dryness for most of the river

basins in west coast of South America during the last 50 years

• Reduction in tropical glaciers and ice fields in extratropical and

tropical Andes over the second half of the 20th century that can be

attributed to an increase in temperature

• Coastal erosion, bleaching of coral reefs in the coast of CA, and

reduction in fisheries stock

• Increase in agricultural yield in SESA, and shift in agricultural zoning

(significant expansion of agricultural areas, mainly in climatically

marginal regions)

• Increase in frequency and extension of dengue fever, yellow fever,

and malaria.

However, for some impacts the number of concluding studies is still

insufficient, leading to low levels of confidence for attribution to human

influences.

By the end of the century, the CMIP5-derived projections for RCP8.5

yielded: CA – mean annual warming of 2.5ºC (range: 1.5°C to 5.0°C),

mean rainfall reduction of 10% (range: –25% to +10%), and reduction

in summertime precipitation; SA – mean warming of 4ºC (range: 2.0°C

to 5.0°C), with rainfall reduction up to 15% in tropical SA east of the

Andes, and an increase of about 15 to 20% in SESA and in other regions

of the continent, and increases in warm days and nights very likely to

occur in most of SA; SESA – increases in heavy precipitation, and

increases in dry spell in northeastern SA. However, there is some degree

of uncertainty in climate change projections for regions, particularly for

rainfall in CA and tropical SA.

Current vulnerability in terms of water supply in the semi-arid zones and

the tropical Andes is expected to increase even further due to climate

change. This would be exacerbated by the expected glacier retreat,

precipitation reduction, and increased evapotranspiration demands as

expected in the semi-arid regions of CA and SA. These scenarios would

affect water supply for large cities, small communities, food production,

and hydropower generation. There is a need for reassessing current

practices to reduce the mismatch between water supply and demand

to reduce future vulnerability, and to implement constitutional and legal

reforms toward more efficient and effective water resources management.

SLR due to climate change and human activities on coastal and marine

ecosystems pose threats to fish stocks, corals, mangroves, recreation

1. CA-NSA: Central America, northern South

America

2. AMA: Amazonia

7. SESA: Southeastern South America

6. NE: Northeast Brazil

4. CAnd: Central Andes

5. PAT: Patagonia

3. TAnd: Tropical Andes

Seasonality ChangeIncrease

Decrease

Vector

range

Agriculture

land use

Forest

cover

Glacier

Precipitation

RunoffTemperature

Figure 27-7 | Summary of observed changes in climate and other environmental factors in representative regions of Central and South America. The boundaries of the regions in

the map are conceptual (neither geographic nor political precision). Information and references to changes provided are presented in different sections of the chapter.

1544

Chapter 27 Central and South America

and tourism, and diseases control in CA and SA.Coral reefs, mangroves,

fisheries, and other benthic marine invertebrates that provide key

ecosystem services, such as nutrient cycling, water quality regulation,

and herbivory, are also threatened by climate change.It is possible that

the Mesoamerican coral reef will collapse by mid-century (between

2050 and 2070), causing major economic and environmental losses.In

the southwestern Atlantic coast,eastern Brazilian reefs might suffer a

massive coral cover decline in the next 50 years.In the Rio de La Plata

area extreme flooding events may become more frequent because

return periods are decreasing,and urban coastalareasin the eastern

coast will be particularly affected. Beach erosion is expected to increase

in southern Brazil and in scattered areas at the Pacific coast.

Urban populations in CA and SA face diverse social, political, economic,

and environmental risks in daily life, and climate change will add a new

dimension to these risks. Because urban development remains fragile

in many cases, with weak planning responses, climate change can

compound existing challenges, for example, water supply in cities from

glacier, snowmelt, and paramos related runoff in the Andes (Lima, La

Paz/El Alto, Santiago de Chile, Bogotá), flooding in several cities such

as São Paulo and Buenos Aires, and health-related challenges in many

cities of the region.

Climate change will affectindividual species and biotic interactions.

Vertebrate fauna will suffer major species losses especially in high-altitude

areas; elevational specialists might be particularly vulnerable because

of their small geographic ranges and high energetic requirements.

Freshwater fisheries can suffer alterations in physiology and life histories.

In addition,modifications in phenology, structure of ecological networks,

predator-prey interactions, and non-trophic interactions among organisms

will affect biotic interactions. Shifts in biotic interactions are expected to

have negative consequences on biodiversity and ecosystem services in

High Andean ecosystems.Although in the region biodiversity conservation

is largely confined to protected areas, it is expected that many species

and vegetational types will lose representativeness inside such protected

areas.

Changes in food production and food security are expected to have

great spatial variability, with a wide range of uncertainty mainly related

to climate and crop models. In SESA average productivity could be

sustained or increased until the mid-century, although interannual and

decadal climate variability is likely to impose important damages. In

other regions such as NEB, CA, and some Andean countries agricultural

productivity could decrease in the short term, threatening the food

security of the poorest population. The expansion of pastures and

croplands is expected to continue in the coming years, particularly from

an increasing global demand for food and biofuels. The great challenge

for CA and SA will be to increase the food and bioenergy production

and at the same time sustain the environmental quality in a scenario

of climate change.

Renewable energy provides great potential for adaptation and mitigation.

Hydropower is currently the main source of renewable energy in CA and

SA, followed by biofuels. SESA is one of the main sources of production

of the feedstocks for biofuel production, mainly with sugarcane and

soybean, and future climate conditions may lead to an increase in

ontinental scale

Very low

Very low Low Medium

Degree of conﬁdence in detection of a trend in climate-sensitive systems

High Very high

Low Medium

Degree of conﬁdence in attribution

High Very high

1. Glacier retreat in the Andes in South America (Section 27.3.1.1)

. Streamﬂow increase La Plata Basin (Section 27.3.1.1)

3. Increase in heavy precipitation and in risk of land slides and

ﬂ

ooding in southeastern South America, and in Central America

and northern South America (Section 27.3.1.1)

. Changes in extreme ﬂows in Amazon River (Section 27.3.1.1)

. Coastal erosion and other physical sea level impacts (Section

7.3.2.1)

6. Bleaching of coral reefs in western Caribbean and coast of Central

America (Section 27.3.2.1)

. Degrading and receding rainforest in Amazonia and in Central

merica and northern South America (Section 27.3.2.1)

8. Reduction in ﬁsheries stock (Section 27.3.4.1)

. Increase in frequency and extension of dengue fever and malaria

(

Section 27.3.7.1)

10. Increases in agricultural yield in southeastern South America (Section

27.3.4.1)

11. Shifting in agricultural zoning (Section 27.3.4.1)

hysical systems

Biological systems

Human and managed systems

Figure 27-8 | Observed impacts of climate variations and attribution of causes to climate change in Central and South America.

1545

Central and South America Chapter 27

roductivity and production. Advances in second-generation biofuels

will be important as a measure of adaptation, as they have the potential

to increase biofuel productivity. In spite of the large amount of arable

land available, the expansion of biofuels might have some direct and

indirect land use change effects, producing teleconnections that could

lead to deforestation of native tropical forests and loss of employment

in some countries. This might also affect food security.

Changes in weather and climatic patterns are negatively affecting human

health in CA and SA, by increasing morbidity, mortality, and disabilities,

and through the emergence of diseases in previously non-endemic

regions. Multiple factors increase the region’s vulnerability to climate

change: precarious health systems; malnutrition; inadequate water

and sanitation services; population growth; poor waste collection and

treatment systems; air, soil, and water pollution; food in poor regions;

lack of social participation; and inadequate governance. Vulnerabilities

vary with geography, age, gender, race, ethnicity, and socioeconomic

status, and are rising in large cities. Climate change and variability may

exacerbate current and future risks to health.

Climate change will bring modifications to environmental conditions in

space and time, and the frequency and intensity of weather and climate

processes.In many CA and SA countries, a first step toward adaptation

o climate change is to reduce the vulnerability to present climate,

taking into account future potential impacts, particularly of weather

and climate extremes. Long-term planning and the related human and

financial resource needs may be seen as conflicting with present social

deficit in the welfare of the CA and SA population. Such conditions

weaken the importance of adaptation planning to climate change on

the political agenda. Currently, there are few experiences on synergies

between development, adaptation, and mitigation planning, which can

help local communities and governments to allocate available resources

in the design of strategies to reduce vulnerability and develop adaptation

measures. Facing a new climate system and, in particular, the exacerbation

of extreme events, will call for new ways to manage human and natural

systems for achieving sustainable development.

References

Abad-Franch, F., F.A. Monteiro, N. Jaramillo O., R. Gurgel-Gonçalves, F.B.S. Dias, and

L. Diotaiuti, 2009: Ecology, evolution, and the long-term surveillance of vector-

borne Chagas disease: a multi-scale appraisal of the tribe Rhodniini (Triatominae).

Acta Tropica, 110(2-3), 159-177.

Abell, R., M.L. Thieme, C. Revenga, M. Bryer, M. Kottelat, N. Bogutskaya, B. Coad, N.

Mandrak, S. Contreras-Balderas, W. Bussing, M.L.J. Stiassny, P. Skelton, G.R. Allen,

P. Unmack, A. Naseka, R. Ng, N. Sindorf, J. Robertson, E. Armijo, J.V. Higgins, T.J.

Near term

(2030–2040)

Present

Long term

(2080–2100)

2°C

4°C

Very

low

Very

high

Medium

CA coral reef bleaching (high conﬁdence)

[27.3.3]

Limited evidence for autonomous genetic adaptation of corals; other adaptation

options are limited to reducing other stresses, mainly enhancing water quality

and limiting pressures from tourism and ﬁshing.

Table 27-8 | Key risks from climate change and the potential for risk reduction through mitigation and adaptation.

Key risk Adaptation issues & prospects

Climatic

drivers

Risk & potential for

adaptation

Timeframe

Carbon dioxide

fertilization

Ocean

acidiﬁcation

Precipitation

Climate-related drivers of impacts

Warming

trend

Extreme

precipitation

Extreme

temperature

Level of risk & potential for adaptation

Potential for additional adaptation

to reduce risk

Risk level with

current adaptation

Risk level with

high adaptation

Drying

trend

Snow

cover

not available

Near term

(2030–2040)

Present

Long term

(2080–2100)

2°C

4°C

Very

low

Very

high

Medium

Spread of vector-borne diseases in altitude

and latitude (high conﬁdence)

[27.3]

• Development of early warning systems for disease control and mitigation

based on climatic and other relevant inputs. Many factors augment

vulnerability.

• Establishing programs to extend basic public health services

Near term

(2030–2040)

Present

Long term

(2080–2100)

2°C

4°C

Very

low

Very

high

Medium

Decreased food production and food quality

(medium conﬁdence)

[27.3]

• Development of new crop varieties more adapted to climate change

(temperature and drought)

• Offsetting of human and animal health impacts of reduced food quality

• Offsetting of economic impacts of land-use change

• Strengthening traditional indigenous knowledge systems and practices

Near term

(2030–2040)

Present

Long term

(2080–2100)

2°C

4°C

Very

low

Very

high

Medium

Water availability in semi-arid and

glacier-melt-dependent regions and Central

America; ﬂooding and landslides in urban

and rural areas due to extreme precipitation

(high conﬁdence)

[27.3]

• Integrated water resource management

• Urban and rural ﬂood management (including infrastructure), early warning

systems, better weather and runoff forecasts, and infectious disease control

1546

Chapter 27 Central and South America

Heibel, E. Wikramanayake, D. Olson, H.L. López, R.E. Reis, J.G. Lundberg, M.H.S.

Pérez, and P. Petry, 2008: Freshwater ecoregions of the world: a new map of

biogeographic units for freshwater biodiversity conservation. BioScience, 58(5),

403-414.

Abers, R.N., 2007: Organizing for governance: building collaboration in Brazilian

river basins. World Development, 35(8), 1450-1463.

Abson, D.J. and M. Termansen, 2011: Valuing ecosystem services in terms of ecological

risks and returns. Conservation Biology, 25(2), 250-258.

Acosta-Michlik, L., U. Kelkar, and U. Sharma, 2008: A critical overview: local evidence

on vulnerabilities and adaptations to global environmental change in developing

countries. Global Environmental Change, 18(4), 539-542.

Adger, W.N., S. Dessai, M. Goulden, M. Hulme, I. Lorenzoni, D.R. Nelson, L.O. Naess,

J. Wolf, and A. Wreford, 2009: Are there social limits to adaptation to climate

change? Climatic Change, 93(3-4), 335-354.

Adger, W.N., K. Brown, D.R. Nelson, F. Berkes, H. Eakin, C. Folke, K. Galvin, L.

Gunderson, M. Goulden, K. O’Brien, J. Ruitenbeek, and E.L. Tompkins, 2011:

Resilience implications of policy responses to climate change. Wiley

Interdisciplinary Reviews: Climate Change, 2(5), 757-766.

Aerts, J.C.J.H., H. Renssen, P.J. Ward, H. de Moel, E. Odada, L.M. Bouwer, and H.

Goosse, 2006: Sensitivity of global river discharges under Holocene and future

climate conditions. Geophysical Research Letters, 33(19), L19401, doi:10.1029/

2006GL027493.

Agrawal, A., 2008: The Role of Local Institutions in Adaptation to Climate Change.

IFRI Working Paper W08I-3, Paper prepared for the Social Dimensions of Climate

Change, Social Development Department, The World Bank, Washington, DC,

March 5-6, 2008, International Forestry Resources and Institutions Program

(IFRI), School of Natural Resources and Environment, University of Michigan,

Ann Arbor, MI, USA, 47 pp.

Aguayo, M., A. Pauchard, G. Azócar, and O. Parra, 2009: Cambio del uso del suelo en

el centro sur de Chile a fines del siglo XX. Entendiendo la dinámica espacial y

temporal del paisaje [Land use change in the south central Chile at the end of

the 20

century. Understanding the spatio-temporal dynamics of the landscape].

Revista Chilena de Historia Natural, 82, 361-374 (in Spanish).

Aguilar, M.Y., T.R. Pacheco, J.M. Tobar, and J.C. Quiñonez, 2009: Vulnerability and

adaptation to climate change of rural inhabitants in the central coastal plain

of El Salvador. Climate Research, 40(2-3), 187-198.

Aide, T.M., M.L. Clark, H.R. Grau, D. López-Carr, M.A. Levy, D. Redo, M. Bonilla-

Moheno, G. Riner, M.J. Andrade-Núñez, and M. Muñiz, 2013: Deforestation and

reforestation of Latin America and the Caribbean (2001-2010). Biotropica,

45(2), 262-271.

Allison, E.H., A.L. Perry, M.-C. Badjeck, W.N. Adger, K. Brown, D. Conway, A.S. Halls,

G.M. Pilling, J.D. Reynolds, N.L. Andrew, and N.K. Dulvy, 2009: Vulnerability of

national economies to the impacts of climate change on fisheries. Fish and

Fisheries, 10(2), 173-196.

Alongi, D.M., 2008: Mangrove forests: resilience, protection from tsunamis, and

responses to global climate change. Estuarine Coastal and Shelf Science, 76(1),

1-13.

Altieri, M. and P. Koohafkan, 2008: Enduring Farms: Climate Change, Smallholders

and Traditional Farming Communities. TWN Environment and Development

Series 6, Third World Network (TWN), Penang, Malaysia, 63 pp.

Alves, M.d.C., L.G. de Carvalho, E.A. Pozza, L. Sanches, and J.C.d.S. Maia, 2011:

Ecological zoning of soybean rust, coffee rust and banana black Sigatoka based

on Brazilian climate changes. Earth System Science 2010: Global Change,

Climate and People, 6, 35-49.

Amorim, H.V., M.L. Lopes, J.V. de Castro Oliveira, M.S. Buckeridge, and G.H. Goldman,

2011: Scientific challenges of bioethanol production in Brazil. Applied

Microbiology and Biotechnology, 91(5), 1267-1275.

Amsler, M.L. and E.C. Drago, 2009: A review of the suspended sediment budget at

the confluence of the Paraná and Paraguay Rivers. Hydrological Processes,

23(22), 3230-3235.

Anciães, M. and A.T. Peterson, 2006: Climate change effects on neotropical manakin

diversity based on ecological niche modeling. The Condor, 108(4), 778-791.

Anderson, B.T., J. Wang, G. Salvucci, S. Gopal, and S. Islam, 2010: Observed trends in

summertime precipitation over the southwestern United States. Journal of

Climate, 23(7), 1937-1944.

Andrade, E.M., J.P. Cosenza, L.P. Rosa, and G. Lacerda, 2012: The vulnerability of

hydroelectric generation in the northeast of Brazil: the environmental and

business risks for CHESF. Renewable & Sustainable Energy Reviews, 16(8),

5760-5769.

Andrade, M.I. and O.E. Scarpati, 2007: Recent changes in flood risk in the Gran La

Plata, Buenos Aires Province, Argentina: causes and management strategy.

GeoJournal, 70(4), 245-250.

Andreo, V., C. Provensal, S. Levis, N. Pini, D. Enria, and J. Polop, 2012: Summer-

autumn distribution and abundance of the hantavirus host, Oligoryzomys

longicaudatus, in northwestern Chubut, Argentina. Journal of Mammalogy,

93(6), 1559-1568.

Anthelme, F., B. Buendia, C. Mazoyer, and O. Dangles, 2012: Unexpected mechanisms

sustain the stress gradient hypothesis in a tropical alpine environment. Journal

of Vegetation Science, 23(1), 62-72.

Anyamba, A., J.-P. Chretien, J. Small, C.J. Tucker, and K.J. Linthicum, 2006: Developing

global climate anomalies suggest potential disease risks for 2006-2007.

International Journal of Health Geographics, 5, 60, doi:10.1186/1476-072X-5-60.

Araújo, C.A.C., P.J. Waniek, and A.M. Jansen, 2009: An overview of chagas disease

and the role of triatomines on its distribution in Brazil. Vector-Borne and

Zoonotic Diseases, 9(3), 227-234.

Arboleda, S., N. Jaramillo-O., and A.T. Peterson, 2009: Mapping environmental

dimensions of dengue fever transmission risk in the Aburrá Valley, Colombia.

International Journal of Environmental Research and Public Health, 6(12),

3040-3055.

Arevalo-Herrera, M., M.L. Quiñones, C. Guerra, N. Céspedes, S. Giron, M. Ahumada,

J.G. Piñeros, N. Padilla, Z. Terrientes, A. Rosas, J.C. Padilla, A.A. Escalante, J.C.

Beier, and S. Herrera, 2012: Malaria in selected non-Amazonian countries of

Latin America. Acta Tropica, 121(3), 303-314.

Arias, P.A., R. Fu, C.D. Hoyos, W. Li, and L. Zhou, 2011: Changes in cloudiness over

the Amazon rainforests during the last two decades: diagnostic and potential

causes. Climate Dynamics, 37(5-6), 1151-1164.

Arias, P.A., R. Fu, and K.C. Mo, 2012: Decadal variation of rainfall seasonality in the

North American monsoon region and its potential causes. Journal of Climate,

25(12), 4258-4274.

Armenteras, D., E. Cabrera, N. Rodríguez, and J. Retana, 2013: National and regional

determinants of tropical deforestation in Colombia. Regional Environmental

Change, 13(6), 1181-1193.

Arnell, N.W. and S.N. Gosling, 2013: The impacts of climate change on river flow

regimes at the global scale. Journal of Hydrology, 486, 351-364.

Arvizu, D., T. Bruckner, H. Chum, O. Edenhofer, S. Estefen, A. Faaij, M. Fischedick, G.

Hansen, G. Hiriart, O. Hohmeyer, K.G.T. Hollands, J. Huckerby, S. Kadner, Å.

Killingtveit, A. Kumar, A. Lewis, O. Lucon, P. Matschoss, L. Maurice, M. Mirza, C.

Mitchell, W. Moomaw, J. Moreira, L.J. Nilsson, J. Nyboer, R. Pichs-Madruga, J.

Sathaye, J.L. Sawin, R. Schaeffer, T. Schei, S. Schlömer, K. Seyboth, R. Sims, G.

Sinden, Y. Sokona, C. von Stechow, J. Steckel, A. Verbruggen, R. Wiser, F. Yamba,

and T. Zwickel, 2011: Technical Summary. In: IPCC Special Report on Renewable

Energy Sources and Climate Change Mitigation. Special Report of Working

Group III of the Intergovernmental Panel on Climate Change [Edenhofer, O., R.

Pichs-Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner, T. Zwickel, P.

Eickemeier, G. Hansen, S. Schlömer, and C. von Stechow (eds.)]. Cambridge

University Press, Cambridge, UK and New York, NY, USA, pp. 27-158.

Asquith, N.M., M.T. Vargas, and S. Wunder, 2008: Selling two environmental services:

in-kind payments for bird habitat and watershed protection in Los Negros,

Bolivia. Ecological Economics, 65(4), 675-684.

Åstrom, D.O., B. Forsberg, and J. Rocklov, 2011: Heat wave impact on morbidity and

mortality in the elderly population: a review of recent studies. Maturitas, 69(2),

99-105.

Ayoo, C., 2008: Economic instruments and the conservation of biodiversity.

Management of Environmental Quality, 19(5), 550-564.

Baethgen, W.E., 2010: Climate risk management for adaptation to climate variability

and change. Crop Science, 50(1 Suppl.), 70-76.

Baker, A.C., P.W. Glynn, and B. Riegl, 2008: Climate change and coral reef bleaching:

an ecological assessment of long-term impacts, recovery trends and future

outlook. Estuarine, Coastal and Shelf Science, 80(4), 435-471.

Baldi, G. and J.M. Paruelo, 2008: Land-use and land cover dynamics in South

American temperate grasslands. Ecology and Society, 13(2), 6, www.ecology

andsociety.org/vol13/iss2/art6/.

Balvanera, P., M. Uriarte, L. Almeida-Leñero, A. Altesor, F. DeClerck, T. Gardner, J. Hall,

A. Lara, P. Laterra, M. Peña-Claros, D.M. Silva Matos, A.L. Vogl, L.P. Romero-

Duque, L.F. Arreola, Á.P. Caro-Borrero, F. Gallego, M. Jain, C. Little, R. de Oliveira

Xavier, J.M. Paruelo, J.E. Peinado, L. Poorter, N. Ascarrunz, F. Correa, M.B. Cunha-

Santino, A.P. Hernández-Sánchez, and M. Vallejos, 2012: Ecosystem services

research in Latin America: the state of the art. Ecosystem Services, 2, 56-70.

1547

Central and South America Chapter 27

Baraer, M., B. Mark, J. McKenzie, T. Condom, J. Bury, K. Huh, C. Portocarrero, J. Gomez,

and S. Rathay, 2012: Glacier recession and water resources in Peru’s Cordillera

Blanca. Journal of Glaciology, 58(207), 134-150.

Barata, M.M.d.L., U.E.C. Confalonieri, A.C.L. de Lima, D.P. Marinho, G. Luigi, G.C. De

Simone, I.d.B. Ferreira, I.V. Pinto, F.d.O. Tosta, H.V.d.O. Silva, and A.S. Valadares,

2011: Mapa de Vulnerabilidade da População do Estado do Rio de Janeiro aos

Impactos das Mudanças Climáticas nas Áreas Social, Saúde e Ambiente. Relatório

4, Versão Final. Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, Brazil, 162

pp. (in Portuguese).

Barbieri, A. and U.E.C. Confalonieri, 2011: Climate change, migration and health in

Brazil. In: Migration and Climate Change [Piguet, E., A. Pécoud, and P. de

Guchteneire (eds.)]. Cambridge University Press, Cambridge, UK and United

Nations Educational, Scientific and Cultural Organization (UNESCO) Publishing,

Paris, France, pp. 49-73.

Barbosa, C.S., K.C. Araújo, M.A.A. Sevilla, F. Melo, E.C.S. Gomes, and R. Souza-Santos,

2010: Current epidemiological status of schistosomiasis in the state of

Pernambuco, Brazil. Memórias do Instituto Oswaldo Cruz, 105(4), 549-554.

Barcaza, G., M. Aniya, T. Matsumoto, and T. Aoki, 2009: Satellite-derived equilibrium

lines in northern Patagonia icefield, Chile, and their implications to glacier

variations. Arctic, Antarctic, and Alpine Research, 41(2), 174-182.

Bárcena, A., 2010: Structural constraints on development in Latin America and the

Caribbean: a post-crisis reflection. Cepal Review, 100, 7-27.

Barros, V., 2008a: Adaptation to climate trends: lessons from the Argentine experience.

In: Climate Change and Adaptation [Leary, N., J. Adejuwon, V. Barros, I. Burton,

J. Kulkarm, and R. Lasco (eds.)]. Earthscan, London, UK and New York, NY, USA,

pp. 296-314.

Barros, V.R., 2008b: El cambio climático en Argentina. In: Agro y Ambiente:

Una Agenda Compartida para el Desarrollo Sustentable. Foro de la Cadena

Agroindustrial Argentina, Buenos Aires, Argentina, 35 pp. (in Spanish).

Barros, V., A. Menéndez, C. Natenzon, R. Kokot, J. Codignotto, M. Re, P. Bronstein, I.

Camilloni, S. Ludueña, D. Riós, and S. González, 2008: Storm surges, rising seas

and flood risks in metropolitan Buenos Aires. In: Climate Change and Vulnerability

[Leary, N., C. Conde, J. Kulkarni, A. Nyong, and J. Pulhin (eds.)]. Earthscan, London,

UK, pp. 117-133.

Barrozo, L.V., R.P. Mendes, S.A. Marques, G. Benard, M.E. Siqueira Silva, and E.

Bagagli, 2009: Climate and acute/subacute paracoccidioidomycosis in a hyper-

endemic area in Brazil. International Journal of Epidemiology, 38(6), 1642-

1649.

Barrucand, M.G., W.M. Vargas, and M.M. Rusticucci, 2007: Dry conditions over

Argentina and the related monthly circulation patterns. Meteorology and

Atmospheric Physics, 98(1-2), 99-114.

Barton, J.R., 2009: Adaptación al cambio climático en la planificación de ciudades-

regiones. Revista de Geografía Norte Grande, 43, 5-30 (in Spanish).

Barton, J.R., 2013: Climate change adaptive capacity in Santiago de Chile: creating

a governance regime for sustainability planning. International Journal of Urban

and Regional Research, 37(6), 1916-1933.

Bathurst, J.C., J. Amezaga, F. Cisneros, M. Gaviño Novillo, A. Iroumé, M.A. Lenzi, J.

Mintegui Aguirre, M. Miranda, and A. Urciuolo, 2010: Forests and floods in Latin

America: science, management, policy and the EPIC FORCE project. Water

International, 35(2), 114-131.

Bathurst, J.C., S.J. Birkinshaw, F. Cisneros, J. Fallas, A. Iroumé, R. Iturraspe, M.G.

Novillo, A. Urciuolo, A. Alvarado, C. Coello, A. Huber, M. Miranda, M. Ramirez,

and R. Sarandón, 2011: Forest impact on floods due to extreme rainfall and

snowmelt in four Latin American environments 2: model analysis. Journal of

Hydrology, 400(3-4), 292-304.

Battisti, D.S. and R.L. Naylor, 2009: Historical warnings of future food insecurity with

unprecedented seasonal heat. Science, 323(5911), 240-244.

Begossi, A., P.H. May, P.F. Lopes, L.E.C. Oliveira, V. da Vinha, and R.A.M. Silvano, 2011:

Compensation for environmental services from artisanal fisheries in SE Brazil:

policy and technical strategies. Ecological Economics, 71, 25-32.

Bell, A.R., N.L. Engle, and M.C. Lemos, 2011: How does diversity matter? The case of

Brazilian river basin councils. Ecology and Society, 16(1), 42, www.ecologyand

society.org/vol16/iss1/art42/.

Bell, E., 2011: Readying health services for climate change: a policy framework for

regional development. American Journal of Public Health, 101(5), 804-813.

Bell, M.L., M.S. O’Neill, N. Ranjit, V.H. Borja-Aburto, L.A. Cifuentes, and N.C. Gouveia,

2008: Vulnerability to heat-related mortality in Latin America: a case-crossover

study in São Paulo, Brazil, Santiago, Chile and Mexico City, Mexico. International

Journal of Epidemiology, 37(4), 796-804.

Benayas, J.M.R., A.C. Newton, A. Diaz, and J.M. Bullock, 2009: Enhancement of

biodiversity and ecosystem services by ecological restoration: a meta-analysis.

Science, 325(5944), 1121-1124.

Benegas, L., F. Jiménez, B. Locatelli, J. Faustino, and M. Campos, 2009: A

methodological proposal for the evaluation of farmer’s adaptation to climate

variability, mainly due to drought in watersheds in Central America. Mitigation

and Adaptation Strategies for Global Change, 14(2), 169-183.

Benhin, J.K.A., 2006: Agriculture and deforestation in the tropics: a critical theoretical

and empirical review. Ambio, 35(1), 9-16.

Benítez, J.A. and A.J. Rodríguez Morales, 2004: Malaria de altura en Venezuela

¿Consecuencia de las variaciones climáticas? Ciencia e Investigación Médica

Estudiantil Latinoamericana(CIMEL), 9(1), 27-30.

Benítez, J.A., A. Rodríguez, M. Sojo, H. Lobo, C. Villegas, L. Oviedo, and E. Brown,

2004: Descripción de un brote epidémico de malaria de altura en un área

originalmente sin malaria del estado Trujillo, Venezuela. Boletín de Malariología

y Salud Ambiental, 44(2), 93-100.

Bern, C., J.H. Maguire, and J. Alvar, 2008: Complexities of assessing the disease

burden attributable to leishmaniasis. PLoS Neglected Tropical Diseases, 2(10),

e313, doi:10.1371/journal.pntd.0000313.

Berthrong, S.T., E.G. Jobbágy, and R.B. Jackson, 2009: A global meta-analysis of soil

exchangeable cations, pH, carbon, and nitrogen with afforestation. Ecological

Applications, 19(8), 2228-2241.

Bettolli, M.L., W.M. Vargas, and O.C. Penalba, 2009: Soya bean yield variability in

the Argentine Pampas in relation to synoptic weather types: monitoring

implications. Meteorological Applications, 16(4), 501-511.

Betts, R.A., P.M. Cox, M. Collins, P.P. Harris, C. Huntingford, and C.D. Jones, 2004: The

role of ecosystem-atmosphere interactions in simulated Amazonian precipitation

decrease and forest dieback under global climate warming. Theoretical and

Applied Climatology, 78(1-3), 157-175.

Betts, R.A., Y. Malhi, and J.T. Roberts, 2008: The future of the Amazon: new perspectives

from climate, ecosystem and social sciences. Philosophical Transactions of the

Royal Society B, 363(1498), 1729-1735.

Blashki, G., T. McMichael, and D.J. Karoly, 2007: Climate change and primary health

care. Australian Family Physician, 36(12), 986-989.

Blázquez, J. and M.N. Nuñez, 2013: Analysis of uncertainties in future climate

projections for South America: comparison of WCRP-CMIP3 and WCRP-CMIP5

models. Climate Dynamics, 41(3-4), 1039-1056.

Bodin, X., F. Rojas, and A. Brenning, 2010: Status and evolution of the cryosphere in

the Andes of Santiago (Chile, 33.5°S.). Geomorphology, 118(3-4), 453-464.

Bombardi, R.J. and L.M.V. Carvalho, 2009: IPCC global coupled model simulations

of the South America monsoon system. Climate Dynamics, 33(7-8), 893-916.

Borsdorf, A. and M. Coy, 2009: Megacities and global change: case studies from

Latin America. Erde, 140(4), 341-353.

Botto, C., E. Escalona, S. Vivas-Martinez, V. Behm, L. Delgado, and P. Coronel, 2005:

Geographical patterns of onchocerciasis in southern Venezuela: relationships

between environment and infection prevalence. Parassitologia, 47(1), 145-150.

Boulanger, J.-P., S. Schlindwein, and E. Gentile, 2011: CLARIS LPB WP1: Metamorphosis

of the CLARIS LPB European project: from a mechanistic to a systemic approach.

CLIVAR Exchanges, No. 57, 16(3), 7-10.

Bown, F. and A. Rivera, 2007: Climate changes and recent glacier behaviour in the

Chilean Lake District. Global and Planetary Change, 59(1-4), 79-86.

Bown, F., A. Rivera, and C. Acuna, 2008: Recent glacier variations at the Aconcagua

basin, central Chilean Andes. Annals of Glaciology, 48(1), 43-48.

Bradley, R.S., M. Vuille, H.F. Diaz, and W. Vergara, 2006: Threats to water supplies in

the tropical Andes. Science, 312(5781), 1755-1756.

Bradley, R.S., F.T. Keimig, H.F. Diaz, and D.R. Hardy, 2009: Recent changes in freezing

level heights in the Tropics with implications for the deglacierization of high

mountain regions. Geophysical Research Letters, 36(17), L17701, doi:10.1029/

2009GL037712.

Bradshaw, C.J.A., N.S. Sodhi, and B.W. Brook, 2009: Tropical turmoil: a biodiversity

tragedy in progress. Frontiers in Ecology and the Environment, 7(2), 79-87.

Broad, K., A. Pfaff, R. Taddei, A. Sankarasubramanian, U. Lall, and F.d.A. de Souza

Filho, 2007: Climate, stream flow prediction and water management in northeast

Brazil: societal trends and forecast value. Climatic Change, 84(2), 217-239.

Brook, B.W., N.S. Sodhi, and C.J.A. Bradshaw, 2008: Synergies among extinction drivers

under global change. Trends in Ecology & Evolution, 23(8), 453-460.

Brooker, R.W., F.T. Maestre, R.M. Callaway, C.L. Lortie, L.A. Cavieres, G. Kunstler, P.

Liancourt, K. Tielboerger, J.M.J. Travis, F. Anthelme, C. Armas, L. Coll, E. Corcket,

S. Delzon, E. Forey, Z. Kikvidze, J. Olofsson, F. Pugnaire, C.L. Quiroz, P. Saccone,

1548

Chapter 27 Central and South America

K. Schiffers, M. Seifan, B. Touzard, and R. Michalet, 2008: Facilitation in plant

communities: the past, the present, and the future. Journal of Ecology, 96(1),

18-34.

Bucher, E.H. and E. Curto, 2012: Influence of long-term climatic changes on breeding

of the Chilean flamingo in Mar Chiquita, Córdoba, Argentina. Hydrobiologia,

697(1), 127-137.

Buckeridge, M.S., A.P. De Souza, R.A. Arundale, K.J. Anderson-Teixeira, and E. DeLucia,

2012: Ethanol from sugarcane in Brazil: a ‘midway’ strategy for increasing

ethanol production while maximizing environmental benefits. Global Change

Biology Bioenergy, 4(2), 119-126.

Bulte, E.H., R. Damania, and R. Lopez, 2007: On the gains of committing to inefficiency:

corruption, deforestation and low land productivity in Latin America. Journal

of Environmental Economics and Management, 54(3), 277-295.

Burte, J.D.P., A. Coudrain, and S. Marlet, 2011: Use of water from small alluvial

aquifers for irrigation in semi-arid regions. Revista Ciência Agronômica, 42(3),

635-643.

Bury, J.T., B.G. Mark, J.M. McKenzie, A. French, M. Baraer, K.I. Huh, M.A.Z. Luyo, and

R.J.G. Lopez, 2011: Glacier recession and human vulnerability in the Yanamarey

watershed of the Cordillera Blanca, Peru. Climatic Change, 105(1-2), 179-206.

Bury, J., B.G. Mark, M. Carey, K.R. Young, J.M. McKenzie, M. Baraer, A. French, and

M.H. Polk, 2013: New geographies of water and climate change in Peru:

coupled natural and social transformations in the Santa River watershed.

Annals of the Association of American Geographers, 103(2), 363-374.

Butler, R. and W.F. Laurance, 2009: Is oil palm the next emerging threat to the

Amazon? Tropical Conservation Science, 2(1), 1-10.

Butt, N., P.A. de Oliveira, and M.H. Costa, 2011: Evidence that deforestation affects

the onset of the rainy season in Rondonia, Brazil. Journal of Geophysical

Research: Atmospheres, 116, D11120, doi:10.1029/2010JD015174.

Buytaert, W. and B. De Bièvre, 2012: Water for cities: the impact of climate change

and demographic growth in the tropical Andes. Water Resources Research,

48(8), W08503, doi:10.1029/2011WR011755.

Buytaert, W., M. Vuille, A. Dewulf, R. Urrutia, A. Karmalkar, and R. Célleri, 2010:

Uncertainties in climate change projections and regional downscaling in the

tropical Andes: implications for water resources management. Hydrology and

Earth System Sciences Discussion, 14(7), 1821-1848.

Buytaert, W., F. Cuesta-Camacho, and C. Tobón, 2011: Potential impacts of climate

change on the environmental services of humid tropical alpine regions. Global

Ecology and Biogeography, 20(1), 19-33.

C40 Cities, 2011: C40 Cities. C40 Cities, Climate Leadership Group, London, UK,

www.c40.org.

Cabaniel, G., L. Rada, J.J. Blanco, A.J. Rodríguez-Morales, and J.P. Escalera, 2005:

Impacto de los eventos de El Niño Southern Oscillation (ENSO) sobre la

leishmaniosis cutánea en Sucre, Venezuela, a través del uso de información

satelital, 1994-2003. Revista Peruana de Medicina Experimental y Salud

Publica, 22(1), 32-37.

Cabral, A.C., N.F. Fé, M.C. Suárez-Mutis, M.N. Bóia, and F.A. Carvalho-Costa, 2010:

Increasing incidence of malaria in the Negro River basin, Brazilian Amazon.

Transactions of the Royal Society of Tropical Medicine and Hygiene, 104(8),

556-562.

Cabré, M., S. Solman, and M. Nuñez, 2010: Creating regional climate change

scenarios over southern South America for the 2020’s and 2050’s using the

pattern scaling technique: validity and limitations. Climatic Change, 98(3-4),

449-469.

Cáceres, B., 2010: Actualización del Inventario de Tres Casquetes Glaciares del

Ecuador. Dissertation for Master of Science, Université Nice Sophia Antipolis,

Nice, France, 78 pp. (in Spanish).

Callaway, R.M., 2007: Positive Interactions and Interdependence in Plant Communities.

Springer, Dordrecht, Netherlands, 415 pp.

Calmon, M., P.H.S. Brancalion, A. Paese, J. Aronson, P. Castro, S.C. da Silva, and R.R.

Rodrigues, 2011: Emerging threats and opportunities for large-scale ecological

restoration in the Atlantic Forest of Brazil. Restoration Ecology, 19(2), 154-158.

Camargo, M.B.P., 2010: The impact of climatic variability and climate change on

arabic coffee crop in Brazil. Bragantia, 69(1), 239-247.

Campbell, J.D., M.A. Taylor, T.S. Stephenson, R.A. Watson, and F.S. Whyte, 2011: Future

climate of the Caribbean from a regional climate model. International Journal

of Climatology, 31(12), 1866-1878.

Campbell-Lendrum, D. and R. Bertollini, 2010: Science, media and public perception:

implications for climate and health policies. Bulletin of the World Health

Organization, 88(4), 242, doi: 10.2471/BLT.10.077362.

Campbell-Lendrum, D. and C. Corvalán, 2007: Climate change and developing-

country cities: implications for environmental health and equity. Journal of

Urban Health, 84(1 Suppl.), i109-i117.

Campos, J.N.B. and T.M. de Carvalho Studart, 2008: Drought and water policies in

Northeast Brazil: backgrounds and rationale. Water Policy, 10(5), 425-438.

Carbajo, A.E., C. Vera, and P.L.M. González, 2009: Hantavirus reservoir Oligoryzomys

longicaudatus spatial distribution sensitivity to climate change scenarios in

Argentine Patagonia. International Journal of Health Geographics, 8, 44,

doi:10.1186/1476-072X-8-44.

Carbajo, A.E., M.V. Cardo, and D. Vezzani, 2012: Is temperature the main cause of

dengue rise in non-endemic countries? The case of Argentina. International

Journal of Health Geographics, 11, 26, doi:10.1186/1476-072X-11-26.

Cárdenas, R., C.M. Sandoval, A.J. Rodríguez-Morales, and C. Franco-Paredes, 2006:

Impact of climate variability in the occurrence of leishmaniasis in Northeastern

Colombia. American Journal of Tropical Medicine and Hygiene, 75(2), 273-277.

Cárdenas, R., C.M. Sandoval, A.J. Rodriguez-Morales, and C. Franco-Paredes, 2007:

Climate variability and leishmaniasis in Colombia. American Journal of Tropical

Medicine and Hygiene, 77(5 Suppl.), 286, www.ajtmh.org/content/77/5_Suppl/

258.full.pdf+html.

Cárdenas, R., C.M. Sandoval, A.J. Rodriguez-Morales, and P. Vivas, 2008: Zoonoses

and climate variability: the example of leishmaniasis in southern departments

of Colombia. Animal Biodiversity and Emerging Diseases: Annals of the New

York Academy of Science, 1149(1), pp. 326-330.

Carey, M., 2005: Living and dying with glaciers: people’s historical vulnerability to

avalanches and outburst floods in Peru. Global and Planetary Change, 47(2-4),

122-134.

Carey, M., A. French, and E. O’Brien, 2012a: Unintended effects of technology on

climate change adaptation: an historical analysis of water conflicts below

Andean Glaciers. Journal of Historical Geography, 38(2), 181-191.

Carey, M., C. Huggel, J. Bury, C. Portocarrero, and W. Haeberli, 2012b: An integrated

socio-environmental framework for glacier hazard management and climate

change adaptation: lessons from Lake 513, Cordillera Blanca, Peru. Climatic

Change, 112(3-4), 733-767.

Carilli, J.E., R.D. Norris, B.A. Black, S.M. Walsh, and M. McField, 2009: Local stressors

reduce coral resilience to bleaching. PLoS ONE, 4(7), e6324, doi:10.1371/

journal.pone.0006324.

Carme, B., S. Matheus, G. Donutil, O. Raulin, M. Nacher, and J. Morvan, 2009:

Concurrent dengue and malaria in Cayenne Hospital, French Guiana. Emerging

Infectious Diseases, 15(4), 668-671.

Carmin, J.A., D. Roberts, and I. Anguelovski, 2009: Planning Climate Resilient Cities:

Early Lessons from Early Adapters. Presented at the World Bank 5

Urban

Research Symposium, Cities and Climate Change, 28-30 June 2009, Marseille,

France, World Bank, Washington, DC, USA, 27 pp., siteresources.worldbank.org/

INTURBANDEVELOPMENT/Resources/336387-1256566800920/6505269-

1268260567624/Carmin.pdf.

Carmona, A. and G. Poveda, 2011: Identificación de Modos Principales de Variabilidad

Hidroclimática en Colombia Mediante la Transformada de Hilbert-Huang.

Presented at the IX Congreso Colombiano de Meteorología 23-25 March 2011,

Bogotá, DC, Colombia, Executive Secretariat: Research Group “Weather, Climate

and Society”, Department of Geography, National University of Colombia,

Bogotá, DC, Columbia, 14 pp., www.bdigital.unal.edu.co/4216/1/DD956.PDF

(in Spanish).

Carpenter, K.E., M. Abrar, G. Aeby, R.B. Aronson, S. Banks, A. Bruckner, A. Chiriboga,

J. Cortés, J.C. Delbeek, L. DeVantier, G.J. Edgar, A.J. Edwards, D. Fenner, H.M.

Guzmán, B.W. Hoeksema, G. Hodgson, O. Johan, W.Y. Licuanan, S.R. Livingstone,

E.R. Lovell, J.A. Moore, D.O. Obura, D. Ochavillo, B.A. Polidoro, W.F. Precht, M.C.

Quibilan, C. Reboton, Z.T. Richards, A.D. Rogers, J. Sanciangco, A. Sheppard, C.

Sheppard, J. Smith, S. Stuart, E. Turak, J.E.N. Veron, C. Wallace, E. Weil, and E.

Wood, 2008: One-third of reef-building corals face elevated extinction risk from

climate change and local impacts. Science, 321(5888), 560-563.

Carr, D.L., A.C. Lopez, and R.E. Bilsborrow, 2009: The population, agriculture, and

environment nexus in Latin America: country-level evidence from the latter half

of the twentieth century. Population and Environment, 30(6), 222-246.

Carrasco, J.F., G. Casassa, and J. Quintana, 2005: Changes of the 0°C isotherm and

the equilibrium line altitude in central Chile during the last quarter of the 20

century. Hydrological Sciences Journal, 50(6), 933-948.

Carvalho, L.M.V., C. Jones, A.E. Silva, B. Liebmann, and P.L. Silva Dias, 2011: The South

American Monsoon System and the 1970s climate transition. International

Journal of Climatology, 31(8), 1248-1256.

1549

Central and South America Chapter 27

Casassa, G., W. Haeberli, G. Jones, G. Kaser, P. Ribstein, A. Rivera, and C. Schneider,

2007: Current status of Andean glaciers. Global and Planetary Change, 59(1-4),

1-9.

Casassa, G., P. López, B. Pouyaud, and F. Escobar, 2009: Detection of changes in glacial

run-off in alpine basins: examples from North America, the Alps, central Asia

and the Andes. Hydrological Processes, 23(1), 31-41.

Cascio, A., M. Bosilkovski, A.J. Rodriguez-Morales, and G. Pappas, 2011: The socio-

ecology of zoonotic infections. Clinical Microbiology and Infection, 17(3), 336-

342.

Casco, S.L., C.E. Natenzon, N.I. Basterra, and J.J. Neiff, 2011: Inundaciones en el Bajo

Paraná ¿Se puede articular la gestión social a partir del comportamiento

hidrológico previo? Interciencia, 36(6), 423-430 (in Spanish).

Castellanos, E.J., C. Tucker, H. Eakin, H. Morales, J.F. Barrera, and R. Díaz, 2013:

Assessing the adaptation strategies of farmers facing multiple stressors: lessons

from the Coffee and Global Changes project in Mesoamerica. Environmental

Science & Policy, 26, 19-28.

Cavazos, T., C. Turrent, and D.P. Lettenmaier, 2008: Extreme precipitation trends

associated with tropical cyclones in the core of the North American monsoon.

Geophysical Research Letters, 35(21), L21703, doi:10.1029/2008GL035832.

CCAD and SICA, 2010: Estrategia Regional de Cambio Climático: Documento Ejecutivo.

Comisión Centroamericana de Ambiente y Desarrollo (CCAD) and Sistema de

la Integración Centroamericana (SICA), Antiguo Cuscatlán, El Salvador, 93 pp.

(in Spanish).

Ceballos, J.L., C. Euscátegui, J. Ramírez, M. Cañon, C. Huggel, W. Haeberli, and H.

Machguth, 2006: Fast shrinkage of tropical glaciers in Colombia. Annals of

Glaciology, 43(1), 194-201.

Cerda Lorca, J., G. Valdivia C., M.T. Valenzuela B., and J. Venegas L., 2008: Cambio

climático y enfermedades infecciosas. Un nuevo escenario epidemiológico

[Climate change and infectious diseases. A novel epidemiological scenario].

Revista Chilena de Infectologia, 25(6), 447-452 (in Spanish).

Chaves, L.F., J.M. Cohen, M. Pascual, and M.L. Wilson, 2008: Social exclusion modifies

climate and deforestation impacts on a vector-borne disease. PLoS Neglected

Tropical Diseases, 2(2), e176, doi:10.1371/journal.pntd.0000176.

Chazdon, R.L., 2008: Beyond deforestation: restoring forests and ecosystem services

on degraded lands. Science, 320(5882), 1458-1460.

Chazdon, R.L., C.A. Harvey, O. Komar, D.M. Griffith, B.G. Ferguson, M. Martínez-

Ramos, H. Morales, R. Nigh, L. Soto-Pinto, M. van Breugel, and S.M. Philpott,

2009: Beyond reserves: a research agenda for conserving biodiversity in human-

modified tropical landscapes. Biotropica, 41(2), 142-153.

Chen, J.L., C.R. Wilson, B.D. Tapley, D.D. Blankenship, and E.R. Ivins, 2007: Patagonia

icefield melting observed by gravity recovery and climate experiment (GRACE).

Geophysical Research Letters, 34(22), L22501, doi:10.1029/2007GL031871.

Chevallier, P., B. Pouyaud, W. Suarez, and T. Condom, 2011: Climate change threats

to environment in the tropical Andes: glaciers and water resources. Regional

Environmental Change, 11(S1), 179-187.

Christie, D.A., J.A. Boninsegna, M.K. Cleaveland, A. Lara, C. Le Quesne, M.S. Morales,

M. Mudelsee, D.W. Stahle, and R. Villalba, 2011: Aridity changes in the Temperate-

Mediterranean transition of the Andes since AD 1346 reconstructed from tree-

rings. Climate Dynamics, 36(7-8), 1505-1521.

Chum, H., A. Faaij, J. Moreira, G. Berndes, P. Dhamija, H. Dong, B. Gabrielle, A. Goss

Eng, W. Lucht, M. Mapako, O. Masera Cerutti, T. McIntyre, T. Minowa, and K.

Pingoud, 2011: Bioenergy. In: IPCC Special Report on Renewable Energy

Sources and Climate Change Mitigation. Special Report of Working Group III

of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-

Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner, T. Zwickel, P. Eickenmeier,

G. Hansen, S.Schlömer, and C. von Stechow (eds.)]. Cambridge University Press,

Cambridge, UK and New York, NY, USA, pp. 209-332.

Chuvieco, E., S. Opazo, W. Sione, H. Del Valle, J. Anaya, C. Di Bella, I. Cruz, L. Manzo,

G. Lopez, N. Mari, F. Gonzalez-Alonso, F. Morelli, A. Setzer, I. Csiszar, J. Ander

Kanpandegi, A. Bastarrika, and R. Libonati, 2008: Global burned-land estimation

in Latin America using MODIS composite data. Ecological Applications, 18(1),

64-79.

Coe, M.T., M.H. Costa, and B.S. Soares-Filho, 2009: The influence of historical and

potential future deforestation on the stream flow of the Amazon River – land

surface processes and atmospheric feedbacks. Journal of Hydrology, 369(1-2),

165-174.

Coe, M.T., E.M. Latrubesse, M.E. Ferreira, and M.L. Amsler, 2011: The effects of

deforestation and climate variability on the streamflow of the Araguaia River,

Brazil. Biogeochemistry, 105(1-3), 119-131.

Coêlho, A.E.L., J.G. Adair, and J.S.P. Mocellin, 2004: Psycological responses to drought

in Northeastern Brazil. Interamerican Journal of Psychology, 38(1), 95-103.

Collini, E.A., E.H. Berbery, V.R. Barros, and M.E. Pyle, 2008: How does soil moisture

influence the early stages of the South American monsoon? Journal of Climate,

21(2), 195-213.

Condom, T., M. Escobar, D. Purkey, J.C. Pouget, W. Suarez, C. Ramos, J. Apaestegui, A.

Tacsi, and J. Gomez, 2012: Simulating the implications of glaciers’ retreat for

water management: a case study in the Rio Santa basin, Peru. Water

International, 37(4), 442-459.

Confalonieri, U.E.C., D.P. Marinho, and R.E. Rodriguez, 2009: Public health

vulnerability to climate change in Brazil. Climate Research, 40(2-3), 175-186.

Confalonieri, U.E.C., A.C.L. Lima, I. Brito, and A.F. Quintão, 2013: Social, environmental

and health vulnerability to climate change in the Brazilian Northeastern region.

Climatic Change, doi:10.1007/s10584-013-0811-7.

Conway, D. and G. Mahé, 2009: River flow modelling in two large river basins with

non-stationary behaviour: the Paraná and the Niger. Hydrological Processes,

23(22), 3186-3192.

Cooper, E., L. Burke, and N. Bood, 2008: Coastal Capital: Belize. The Economic

Contribution of Belize’s Coral Reefs and Mangroves. WRI Working Paper, World

Resources Institute (WRI), Washington, DC, USA, 53 pp.

Corfee-Morlot, J., I. Cochran, S. Hallegatte, and P. Teasdale, 2011: Multilevel risk

governance and urban adaptation policy. Climatic Change, 104(1), 169-197.

Cortés, G., X. Vargas, and J. McPhee, 2011: Climatic sensitivity of streamflow timing

in the extratropical western Andes Cordillera. Journal of Hydrology, 405(1-2),

93-109.

Cortes, J., W. Arvelo, B. Lopez, L. Reyes, T. Kerin, R. Gautam, M. Patel, U. Parashar, and

K.A. Lindblade, 2012: Rotavirus disease burden among children <5years of age

– Santa Rosa, Guatemala, 2007-2009. Tropical Medicine and International

Health, 17(2), 254-259.

Costa, E.A.P.d.A., E.M.d.M. Santos, J.C. Correia, and C.M.R. de Albuquerque, 2010:

Impact of small variations in temperature and humidity on the reproductive

activity and survival of Aedes aegypti (Diptera, Culicidae). Revista Brasileira de

Entomologia, 54(3), 488-493.

Costa, L.C., F. Justino, L.J.C. Oliveira, G.C. Sediyama, W.P.M. Ferreira, and C.F. Lemos,

2009: Potential forcing of CO

, technology and climate changes in maize (Zea

mays) and bean (Phaseolus vulgaris) yield in southeast Brazil. Environmental

Research Letters, 4(1), 014013, doi:10.1088/1748-9326/4/1/014013.

Costa, M.H. and G.F. Pires, 2010: Effects of Amazon and Central Brazil deforestation

scenarios on the duration of the dry season in the arc of deforestation.

International Journal of Climatology, 30(13), 1970-1979.

Costa, M.H., S.N.M. Yanagi, P.J.O.P. Souza, A. Ribeiro, and E.J.P. Rocha, 2007: Climate

change in Amazonia caused by soybean cropland expansion, as compared to

caused by pastureland expansion. Geophysical Research Letters, 34(7), L07706,

doi:10.1029/2007GL029271.

Costello, A., M. Abbas, A. Allen, S. Ball, S. Bell, R. Bellamy, S. Friel, N. Groce, A. Johnson,

M. Kett, M. Lee, C. Levy, M. Maslin, D. McCoy, B. McGuire, H. Montgomery, D.

Napier, C. Pagel, J. Patel, J.A.P. de Oliveira, N. Redclift, H. Rees, D. Rogger, J. Scott,

J. Stephenson, J. Twigg, J. Wolff, and C. Patterson, 2009: Managing the health

effects of climate change. The Lancet, 373(9676), 1693-1733.

Costello, A., M. Maslin, H. Montgomery, A.M. Johnson, and P. Ekins, 2011: Global

health and climate change: moving from denial and catastrophic fatalism to

positive action. Philosophical Transactions of the Royal Society A, 369(1942),

1866-1882.

Cox, P.M., R.A. Betts, C.D. Jones, S.A. Spall, and I.J. Totterdell, 2000: Acceleration of

global warming due to carbon-cycle feedbacks in a coupled climate model.

Nature, 408(6809), 184-187.

Cox, P.M., R.A. Betts, M. Collins, P.P. Harris, C. Huntingford, and C.D. Jones, 2004:

Amazonian forest dieback under climate-carbon cycle projections for the 21

century. Theoretical and Applied Climatology, 78(1-3), 137-156.

Cranford, M. and S. Mourato, 2011: Community conservation and a two-stage

approach to payments for ecosystem services. Ecological Economics, 71, 89-

98.

CRED, 2011: Emergency Events Database (EM-DAT). The International Disaster

Database. Centre for Research on the Epidemiology of Disasters (CRED), School

of Public Health, Université catholique de Louvain, Brussels, Belgium,

www.emdat.be/.

Cronkleton, P., M.R. Guariguata, and M.A. Albornoz, 2012: Multiple use forestry

planning: timber and Brazil nut management in the community forests of

Northern Bolivia. Forest Ecology and Management, 268, 49-56.

1550

Chapter 27 Central and South America

Crowe, J., B. van Wendel de Joode, and C. Wesseling, 2009: A pilot field evaluation

on heat stress in sugarcane workers in Costa Rica: what to do next? Global

Health Action, 2, doi:10.3402/gha.v2i0.2062.

Crowe, J., J. Manuel Moya-Bonilla, B. Roman-Solano, and A. Robles-Ramirez, 2010:

Heat exposure in sugarcane workers in Costa Rica during the non-harvest

season. Global Health Action, 3, 5619, doi:10.3402/gha.v3i0.5619.

da Costa Fereira, Leila, R. D’Almeida Martins, F. Barbi, Lúcia da Costa Ferreira, L.F.

de Mello, A.M. Urbinatti, F.O. de Souza, and T.H.N. de Andrade, 2011: Governing

climate change in Brazilian coastal cities: risks and strategies. Journal of US-

China Public Administration, 8(1), 51-65.

da Silva, T.G.F., M.S.B. de Moura, I.I.S. Sá, S. Zolnier, S.H.N. Turco, F. Justino, J.F.A. do

Carmo, and L.S.B. de Souza, 2009: Impactos das mudanças climáticas na

produção leiteira do estado de Pernambuco: análise para os cenários B2 e A2

do IPCC [Impacts of climate change on regional variation of milk production

in the Pernambuco State, Brazil: analysis for the A2 and B2 IPCC scenarios].

Revista Brasileira de Meteorologia, 24(4), 489-501.

da Silva-Nunes, M., M. Moreno, J.E. Conn, D. Gamboa, S. Abeles, J.M. Vinetz, and M.U.

Ferreira, 2012: Amazonian malaria: asymptomatic human reservoirs, diagnostic

challenges, environmentally driven changes in mosquito vector populations, and

the mandate for sustainable control strategies. Acta Tropica, 121(3), 281-291.

Dai, A., 2011: Drought under global warming: a review. Wiley Interdisciplinary

Reviews: Climate Change, 2(1), 45-65.

Dai, A., T. Qian, K.E. Trenberth, and J.D. Milliman, 2009: Changes in continental freshwater

discharge from 1948 to 2004. Journal of Climate, 22(10), 2773-2792.

DaMatta, F.M., A. Grandis, B.C. Arenque, and M.S. Buckeridge, 2010: Impacts of climate

changes on crop physiology and food quality. Food Research International,

43(7), 1814-1823.

Dantur Juri, M.J., G.L. Claps, M. Santana, M. Zaidenberg, and W.R. Almirón, 2010:

Abundance patterns of Anopheles pseudopunctipennis and Anopheles

argyritarsis in northwestern Argentina. Acta Tropica, 115(3), 234-241.

Dantur Juri, M.J., M. Stein, and M.A. Mureb Sallum, 2011: Occurrence of Anopheles

(Anopheles) neomaculipalpus Curry in north-western Argentina. Journal of

Vector Borne Diseases, 48(1), 64-66.

de Carvalho-Leandro, D., A.L.M. Ribeiro, J.S.V. Rodrigues, C.M.R. de Albuquerque,

A.M. Acel, F.A. Leal-Santos, D.P. Leite Jr., and R.D. Miyazaki, 2010: Temporal

distribution of Aedes aegypti Linnaeus (Diptera, Culicidae), in a Hospital in

Cuiabá, State of Mato Grosso, Brazil. Revista Brasileira de Entomologia, 54(4),

701-706.

de Koning, F., M. Aguiñaga, M. Bravo, M. Chiu, M. Lascano, T. Lozada, and L. Suarez,

2011: Bridging the gap between forest conservation and poverty alleviation:

the Ecuadorian Socio Bosque program. Environmental Science & Policy, 14(5),

531-542.

de Lucena, A.F.P., A.S. Szklo, R. Schaeffer, R.R. de Souza, B.S.M.C. Borba, I.V.L. da

Costa, A.O. Pereira Jr., and S.H.F. da Cunha, 2009: The vulnerability of renewable

energy to climate change in Brazil. Energy Policy, 37(3), 879-889.

de Lucena, A.F.P., R. Schaeffer, and A.S. Szklo, 2010a: Least-cost adaptation options

for global climate change impacts on the Brazilian electric power system.

Global Environmental Change: Human and Policy Dimensions, 20(2), 342-350.

de Lucena, A.F.P., A.S. Szklo, R. Schaeffer, and R.M. Dutra, 2010b: The vulnerability

of wind power to climate change in Brazil. Renewable Energy, 35(5), 904-912.

de Mello, E.L., F.A. Oliveira, F.F. Pruski, and J.C. Figueiredo, 2008: Efeito das mudanças

climáticas na disponibilidade hídrica da bacia hidrográfica do Rio Paracatu

[Effect of the climate change on the water availability in the Paracatu river

basin]. Engenharia Agrícola, 28(4), 635-644 (in Portuguese).

de Moura, R.L.d., C.V. Minte-Vera, I.B. Curado, R.B. Francini Filho, H.d.C.L. Rodrigues,

G.F. Dutra, D.C. Alves, and F.J.B. Souto, 2009: Challenges and prospects of

fisheries co-management under a marine extractive reserve framework in

northeastern Brazil. Coastal Management, 37(6), 617-632.

de Oliveira, B.F.A., E. Ignotti, and S.S. Hacon, 2011: A systematic review of the

physical and chemical characteristics of pollutants from biomass burning and

combustion of fossil fuels and health effects in Brazil. Cadernos de Saúde

Pública, 27(9), 1678-1698.

de Oliveira, J.A.P., 2009: The implementation of climate change related policies at

the subnational level: an analysis of three countries. Habitat International,

33(3), 253-259.

de Sherbinin, A., M. Levy, S. Adamo, K. MacManus, G. Yetman, V. Mara, L. Razafindrazay,

B. Goodrich, T. Srebotnjak, C. Aichele, and L. Pistolesi, 2012: Migration and risk:

net migration in marginal ecosystems and hazardous areas. Environmental

Research Letters, 7(4), 045602, doi:10.1088/1748-9326/7/4/045602.

de Siqueira, M.F and A.T. Peterson, 2003: Consequences of global climate change

for geographic distributions of Cerrado species. Biota Neotropica, 3(2), 1-14.

de Souza, A.P., M. Gaspar, E.A. da Silva, E.C. Ulian, A.J. Waclawovsky, M.Y. Nishiyama

Jr., R.V. dos Santos, M.M. Teixeira, G.M. Souza, and M.S. Buckeridge, 2008:

Elevated CO

increases photosynthesis, biomass and productivity, and modifies

gene expression in sugarcane. Plant Cell and Environment, 31(8), 1116-1127.

de Souza, A.P., A. Grandis, D.C.C. Leite, and M.S. Buckeridge, 2013: Sugarcane as a

bioenergy source: history, performance, and perspectives for second-generation

bioethanol. Bioenergy Research (in press), doi:10.1007/s12155-013-9366-8.

de Souza, H.N., R.G.M. de Goede, L. Brussaard, I.M. Cardoso, E.M.G. Duarte, R.B.A.

Fernandes, L.C. Gomes, and M.M. Pulleman, 2012: Protective shade, tree

diversity and soil properties in coffee agroforestry systems in the Atlantic

Rainforest biome. Agriculture Ecosystems & Environment, 146(1), 179-196.

de Souza Filho, F.d.A. and C.M. Brown, 2009: Performance of water policy reforms

under scarcity conditions: a case study in northeast Brazil. Water Policy, 11(5),

553-568.

dos Santos, W.D., E.O. Gomez, and M.S. Buckeridge, 2011: Bioenergy and the

sustainable revolution. In: Routes to Cellulosic Ethanol [Buckeridge, M.S. and

G.H. Goldmann (eds.)]. Springer, New York, NY, USA, pp. 15-26.

Dearing, M.D. and L. Dizney, 2010: Ecology of hantavirus in a changing world. Annals

of the New York Academy of Sciences, 1195(1), 99-112.

Debels, P., C. Szlafsztein, P. Aldunce, C. Neri, Y. Carvajal, M. Quintero-Angel, A. Celis,

A. Bezanilla, and D. Martínez, 2009: IUPA: a tool for the evaluation of the

general usefulness of practices for adaptation to climate change and variability.

Natural Hazards, 50(2), 211-233.

Degallier, N., C. Favier, C. Menkes, M. Lengaigne, W.M. Ramalho, R. Souza, J. Servain,

and J.-P. Boulanger, 2010: Toward an early warning system for dengue

prevention: modeling climate impact on dengue transmission. Climatic Change,

98(3), 581-592.

Demaria, E.M.C., E.P. Maurer, B. Thrasher, S. Vicuña, and F.J. Meza, 2013: Climate

change impacts on an alpine watershed in Chile: do new model projections

change the story? Journal of Hydrology, 502, 128-138.

Dias, M.O.S., T.L. Junqueira, O. Cavalett, M.P. Cunha, C.D.F. Jesus, C.E.V. Rossell, R.

Maciel Filho, and A. Bonomi, 2012: Integrated versus stand-alone second

generation ethanol production from sugarcane bagasse and trash. Bioresource

Technology, 103(1), 152-161.

Diez Roux, A.V., T. Green Franklin, M. Alazraqui, and H. Spinelli, 2007: Intraurban

variations in adult mortality in a large Latin American city. Journal of Urban

Health, 84(3), 319-333.

Diffenbaugh, N.S. and F. Giorgi, 2012: Climate change hotspots in the CMIP5 global

climate model ensemble. Climatic Change, 114(3-4), 813-822.

Diffenbaugh, N.S., F. Giorgi, and J.S. Pal, 2008: Climate change hotspots in the United

States. Geophysical Research Letters, 35(16), L16709, doi:10.1029/

2008GL035075.

Döll, P., 2009: Vulnerability to the impact of climate change on renewable groundwater

resources: a global-scale assessment. Environmental Research Letters, 4(3),

035006, doi:10.1088/1748-9326/4/3/035006.

Donat, M.G., L.V. Alexander, H. Yang, I. Durre, R. Vose, R.J.H. Dunn, K.M. Willett, E.

Aguilar, M. Brunet, J. Caesar, B. Hewitson, C. Jack, A.M.G. Klein Tank, A.C. Kruger,

J.A. Marengo, T.C. Peterson, M. Renom, C. Oria Rojas, M. Rusticucci, J. Salinger,

A. Sanhouri Elrayah, S.S. Sekele, A.K. Srivastava, B. Trewin, C. Villarroel, L.A.

Vincent, P. Zhai, X. Zhang, and S. Kitching, 2013: Updated analyses of

temperature and precipitation extreme indices since the beginning of the

twentieth century: the HadEX2 dataset. Journal of Geophysical Research:

Atmospheres, 118(5), 2098-2118.

Doyle, M.E. and V.R. Barros, 2011: Attribution of the river flow growth in the Plata

Basin. International Journal of Climatology, 31(15), 2234-2248.

Doyle, M.E., R.I. Saurral, and V.R. Barros, 2012: Trends in the distributions of

aggregated monthly precipitation over the La Plata Basin. International Journal

of Climatology, 32(14), 2149-2162.

Dufek, A.S. and T. Ambrizzi, 2008: Precipitation variability in São Paulo State, Brazil.

Theoretical and Applied Climatology, 93(3-4), 167-178.

Dufek, A.S., T. Ambrizzi, and R.P. da Rocha, 2008: Are reanalysis data useful for

calculating climate indices over South America? Trends and Directions in Climate

Research: Annals of the New York Academy of Sciences, 1146, 87-104.

Duke, N.C., J.-O. Meynecke, S. Dittmann, A.M. Ellison, K. Anger, U. Berger, S. Cannicci,

K. Diele, K.C. Ewel, C.D. Field, N. Koedam, S.Y. Lee, C. Marchand, I. Nordhaus,

and F. Dahdouh-Guebas, 2007: A world without mangroves? Science,

317(5834), 41-42.

1551

Central and South America Chapter 27

Dupnik, K.M., E.L. Nascimento, J.F. Rodrigues-Neto, T. Keesen, M. Zélia Fernandes, I.

Duarte, and S.M.B. Jeronimo, 2011: New challenges in the epidemiology and

treatment of visceral leishmaniasis in periurban areas. Drug Development

Research, 72(6), 451-462.

Dussaillant, A., G. Benito, W. Buytaert, P. Carling, C. Meier, and F. Espinoza, 2010:

Repeated glacial-lake outburst floods in Patagonia: an increasing hazard?

Natural Hazards, 54(2), 469-481.

Eakin, C.M., J.A. Morgan, S.F. Heron, T.B. Smith, G. Liu, L. Alvarez-Filip, B. Baca, E.

Bartels, C. Bastidas, C. Bouchon, M. Brandt, A.W. Bruckner, L. Bunkley-Williams,

A. Cameron, B.D. Causey, M. Chiappone, T.R.L. Christensen, M.J.C. Crabbe, O.

Day, E. de la Guardia, G. Díaz-Pulido, D. DiResta, D.L. Gil-Agudelo, D.S. Gilliam,

R.N. Ginsburg, S. Gore, H.M. Guzmán, J.C. Hendee, E.A. Hernández-Delgado, E.

Husain, C.F.G. Jeffrey, R.J. Jones, E. Jordán-Dahlgren, L.S. Kaufman, D.I. Kline,

P.A. Kramer, J.C. Lang, D. Lirman, J. Mallela, C. Manfrino, J.-P. Maréchal, K. Marks,

J. Mihaly, W.J. Miller, E.M. Mueller, E.M. Muller, C.A. Orozco Toro, H.A. Oxenford,

D. Ponce-Taylor, N. Quinn, K.B. Ritchie, S. Rodríguez, A. Rodríguez Ramírez, S.

Romano, J.F. Samhouri, J.A. Sánchez, G.P. Schmahl, B.V. Shank, W.J. Skirving,

S.C.C. Steiner, E. Villamizar, S.M. Walsh, C. Walter, E. Weil, E.H. Williams, K.W.

Roberson, and Y. Yusuf, 2010: Caribbean corals in crisis: record thermal stress,

bleaching, and mortality in 2005. PLoS ONE, 5(11), e13969, doi:10.1371/

journal.pone.0013969.

Eakin, H. and M.C. Lemos, 2006: Adaptation and the state: Latin America and the

challenge of capacity-building under globalization. Global Environmental

Change, 16(1), 7-18.

Eakin, H.C. and M.B. Wehbe, 2009: Linking local vulnerability to system sustainability

in a resilience framework: two cases from Latin America. Climatic Change,

93(3-4), 355-377.

Eakin, H., L.A. Bojórquez-Tapia, R. Monterde Diaz, E. Castellanos, and J. Haggar, 2011:

Adaptive capacity and social-environmental change: theoretical and operational

modeling of smallholder coffee systems response in Mesoamerican Pacific Rim.

Environmental Management, 47(3), 352-367.

Eakin, H., C. Tucker, E. Castellanos, R. Diaz-Porras, J. Barrera, and H. Morales, 2013:

Adaptation in a multi-stressor environment: perceptions and responses to

climatic and economic risks by coffee growers in Mesoamerica. Environment,

Development and Sustainability (in press), doi:10.1007/s10668-013-9466-9.

Echeverría, C., D. Coomes, J. Salas, J.M. Rey-Benayas, A. Lara, and A. Newton, 2006:

Rapid deforestation and fragmentation of Chilean temperate forests. Biological

Conservation, 130(4), 481-494.

ECLAC, 2008: Structural Change and Productivity Growth – 20 Years Later: Old

Problems, New Opportunities. LC/G.2367(SES.32/3), 32nd session of ECLAC,

Santo Domingo, Dominican Republic, 9-13 June 2008, Economic Commission

for Latin America and the Caribbean (ECLAC), Santiago de Chile, Chile, 330 pp.

ECLAC, 2009a: La Economia del Cambio Climatico en Chile: Sintesis. LC/W.288,

Economic Commission for Latin America and the Caribbean (ECLAC), Santiago

de Chile, Chile, 88 pp.

ECLAC, 2009b: Social Panorama of Latin America 2009: Briefing Paper. Economic

Commission for Latin America and the Caribbean (ECLAC), Santiago de Chile,

Chile, 64 pp.

ECLAC, 2010a: Economics of Climate Change in Latin America and the Caribbean:

Summary 2010. LC/G.2474, Economic Commission for Latin America and the

Caribbean (ECLAC), Santiago de Chile, Chile, 107 pp.

ECLAC, 2010b: Objetivos de Desarrollo del Milenio: El Progreso de América Latina y

el Caribe Hacia los Objetivos de Desarrollo del Milenio. Desafíos para Lograrlos

con Igualdad. LC/G 2460, Economic Commission for Latin America and the

Caribbean (ECLAC), Santiago de Chile, Chile, 25 pp.

ECLAC, 2010c: The Economics of Climate Change in Central America: Summary 2010.

LC/MEX/L.978, Economic Commission for Latin America and the Caribbean

(ECLAC), Santiago de Chile, Chile, 144 pp.

ECLAC, 2010d: Economics of Climate Change in Latin America and the Caribbean:

Summary 2010. United Nations, Economic Commission for Latin America and

the Caribbean (ECLAC), Santiago de Chile, Chile, 107 pp.

ECLAC, 2010e: Latin America and the Caribbean in the World Economy. 2009-2010.

A Crisis Generated in the Centre and a Recovery Driven by the Emerging

Economies. Economic Commission for Latin America and the Caribbean

(ECLAC), Santiago de Chile, Chile, 164 pp.

ECLAC, 2010f: The Reactions of the Governments of the Americas to the International

Crisis: An Overview of Policy Measures up to 31 December 2009.

LC/L.3025/Rev.6, Economic Commission for Latin America and the Caribbean

(ECLAC), Santiago de Chile, Chile, 69 pp.

ECLAC, 2010g: Time for Equality: Closing Gaps, Opening Trails. 33rd session of ECLAC,

Brasilia, Brazil, 30 May to 1 June 2010, Economic Commission for Latin America

and the Caribbean (ECLAC), Santiago de Chile, Chile, 269 pp.

ECLAC, 2010h: Millennium Development Goals: Advances in Environmentally

Sustainable Development in Latin America and the Caribbean. United Nations

publication LC/G.2428-P, Prepared by the Economic Commission for Latin America

and the Caribbean (ECLAC) in close collaboration with the regional offices of

other specialized agencies, programmes and funds in the United Nations system,

United Nations (UN), Santiago, Chile, 218 pp.

ECLAC, 2011a: Efectos del Cambio Climático en la Costa de América Latina y el

Caribe: Dinámicas, Tendencias y Variabilidad Climática [Effects of Climate

Change on the Coast of Latin America and the Caribbean: Dynamics, Trends

and Climate Variability]. LC/W.447, the Economic Commission for Latin America

and the Caribbean (ECLAC), the Spanish Climate Change Office under the

Ministry of Agriculture, Food and Environment of the Government of Spain,

and the Environmental Hydraulics Institute of Cantabria University, ECLAC,

Santiago de Chile, Chile, 263 pp.

ECLAC, 2011b: Social Panorama of Latin America 2010. Economic Commission for

Latin America and the Caribbean (ECLAC), Santiago, Chile, 252 pp.

ECLAC, 2011c: Social Panorama of Latin America 2011. Briefing Paper, Economic

Commission for Latin America and the Caribbean (ECLAC), Santiago, Chile, 49 pp.

ECLAC, 2011d: Subregión Norte de América Latina y el Caribe: Información del Sector

Agropecuario: Las Tendencias Alimentarias 2000-2010. Economic Commission

for Latin America and the Caribbean (ECLAC), México DF, Mexico, 69 pp. (in

Spanish).

ECLAC, 2012a: CEPALSTAT: Database and Statistical Publications of the Economic

Comission for Latin America and the Caribbean. Economic Comission for Latin

America and the Caribbean (ECLAC)/Comisión Económica para América Latina

(CEPAL), Santiago de Chile, Chile, estadisticas.cepal.org/cepalstat/WEB_

CEPALSTAT/Portada.asp?idioma=i.

ECLAC, 2012b: Sustainable Development 20 years on from the Earth Summit:

Progress, Gaps and Strategic Guidelines for Latin America and the Caribbean

– Summary. LC/G.3363/Rev.1, Report prepared by the Economic Commission

for Latin America and the Caribbean (ECLAC) in its capacity as Coordinator of

the Regional Coordination Mechanism, in close collaboration with technical

teams from other specialized United Nations (UN) agencies, funds and programs,

UN, Santiago de Chile, Chile, 55 pp.

Engel, S., S. Pagiola, and S. Wunder, 2008: Designing payments for environmental

services in theory and practice: an overview of the issues. Ecological Economics,

65(4), 663-674.

Engle, N.L. and M.C. Lemos, 2010: Unpacking governance: building adaptive capacity

to climate change of river basins in Brazil. Global Environmental Change:

Human and Policy Dimensions, 20(1), 4-13.

Engle, N.L., O.R. Johns, M.C. Lemos, and D.R. Nelson, 2011: Integrated and adaptive

management of water resources: tensions, legacies, and the next best thing.

Ecology and Society, 16(1), 19, www.ecologyandsociety.org/vol16/iss1/art19/

main.html.

Englehart, P.J. and A.V. Douglas, 2006: Defining intraseasonal rainfall variability

within the North American monsoon. Journal of Climate, 19(17), 4243-4253.

Espinoza, J.C., J.L. Guyot, J. Ronchail, G. Cochonneau, N. Filizola, P. Fraizy, D. Labat,

E. de Oliveira, J. Julio Ordonez, and P. Vauchel, 2009a: Contrasting regional

discharge evolutions in the Amazon basin (1974-2004). Journal of Hydrology,

375(3-4), 297-311.

Espinoza, J.C., J. Ronchail, J.L. Guyot, G. Cochonneau, F. Naziano, W. Lavado, E. De

Oliveira, R. Pombosa, and P. Vauchel, 2009b: Spatio-temporal rainfall variability

in the Amazon basin countries (Brazil, Peru, Bolivia, Colombia, and Ecuador).

International Journal of Climatology, 29(11), 1574-1594.

Espinoza, J.C., J. Ronchail, J.L. Guyot, C. Junquas, P. Vauchel, W. Lavado, G. Drapeau,

and R. Pombosa, 2011: Climate variability and extreme drought in the upper

Solimões River (western Amazon Basin): understanding the exceptional 2010

drought. Geophysical Research Letters, 38(13), L13406, doi:10.1029/

2011GL047862.

Espinoza, J.C., M. Lengaigne, J. Ronchail, and S. Janicot, 2012: Large-scale circulation

patterns and related rainfall in the Amazon Basin: a neuronal networks approach.

Climate Dynamics, 38(1-2), 121-140.

Espinoza, J.C., J. Ronchail, F. Frappart, W. Lavado, W. Santini, and J.L. Guyot, 2013:

The major floods in the Amazonas River and tributaries (Western Amazon Basin)

during the 1970-2012 period: a focus on the 2012 flood. Journal of

Hydrometeorology, 14(3), 1000-1008.

1552

Chapter 27 Central and South America

Fábrega, J., T. Nakaegawa, R. Pinzón, K. Nakayama, O. Arakawa, and SOUSEI Theme-

C Modeling Group, 2013: Hydroclimate projections for Panama in the late 21

Century. Hydrological Research Letters, 7(2), 23-29.

Falvey, M. and R.D. Garreaud, 2009: Regional cooling in a warming world: recent

temperature trends in the southeast Pacific and along the west coast of

subtropical South America (1979-2006). Journal of Geophysical Research:

Atmospheres, 114(D4), D04102, doi:10.1029/2008JD010519.

FAO, 2009: Global Forest Resources Assessment 2010: Brazil Country Report. Food

and Agriculture Organization of the United Nations (FAO), Rome, Italy, 111 pp.

FAO, 2010: Global Forest Resources Assessment 2010. FAO Forestry Paper No. 163,

Food and Agriculture Organization of the United Nations (FAO), Rome, Italy,

340 pp.

FAO, WFP, and IFAD, 2012: The State of Food Insecurity in the World 2012. Economic

Growth is Necessary but not Sufficient to Accelerate Reduction of Hunger and

Malnutrition. Report by the Food and Agricultural Organization of the United

Nations (FAO), World Food Programme (WFP), and the International Fund for

Agricultural Development (IFAD), FAO, Rome, Italy, 62 pp.

Farley, K.A., G. Piñeiro, S.M. Palmer, E.G. Jobbágy, and R.B. Jackson, 2009: Stream

acidification and base cation losses with grassland afforestation. Water

Resources Research, 45(7), W00A03, doi:10.1029/2007WR006659.

Fearnside, P.M., 2008: The roles and movements of actors in the deforestation of

Brazilian Amazonia. Ecology and Society, 13(1), 23, www.ecologyand

society.org/vol13/iss1/art23/.

Fearnside, P.M. and S. Pueyo, 2012: Greenhouse-gas emissions from tropical dams.

Nature Climate Change, 2(6), 382-384.

Feeley, K.J. and M.R. Silman, 2009: Extinction risks of Amazonian plant species.

Proceedings of the National Academy of Sciences of the United States of

America, 106(30), 12382-12387.

Feliciangeli, M.D., O. Delgado, B. Suarez, and A. Bravo, 2006: Leishmania and sand

flies: proximity to woodland as a risk factor for infection in a rural focus of visceral

leishmaniasis in west central Venezuela. Tropical Medicine & International Health,

11(12), 1785-1791.

Fernández, M.S., E.A. Lestani, R. Cavia, and O.D. Salomón, 2012: Phlebotominae

fauna in a recent deforested area with American Tegumentary Leishmaniasis

transmission (Puerto Iguazú, Misiones, Argentina): seasonal distribution in

domestic and peridomestic environments. Acta Tropica, 122(1), 16-23.

Ferreira, A.R. and R.S.V. Teegavarapu, 2012: Optimal and adaptive operation of a

hydropower system with unit commitment and water quality constraints. Water

Resources Management, 26(3), 707-732.

FEWS NET, 2013: Special Report Central America: Coffee Sector Shocks and Projected

Food Security Impacts in Central America. Famine Early Warning Systems

Network (FEWS NET), Washington, DC, USA, 3 pp.

Ficke, A.D., C.A. Myrick, and L.J. Hansen, 2007: Potential impacts of global climate

change on freshwater fisheries. Reviews in Fish Biology and Fisheries, 17(4),

581-613.

Fiebig-Wittmaack, M., O. Astudillo, E. Wheaton, V. Wittrock, C. Perez, and A.

Ibacache, 2012: Climatic trends and impact of climate change on agriculture

in an arid Andean valley. Climatic Change, 111(3-4), 819-833.

Finer, M. and C.N. Jenkins, 2012: Proliferation of hydroelectric dams in the Andean

Amazon and implications for Andes-Amazon connectivity. PLoS ONE, 7(4),

e35126, doi:10.1371/journal.pone.0035126.

Fischedick, M., R. Schaeffer, A. Adedoyin, M. Akai, T. Bruckner, L. Clarke, V. Krey, I.

Savolainen, S. Teske, D. Ürge-Vorsatz, and R. Wright, 2011: Mitigation potential

and costs. In: IPCC Special Report on Renewable Energy Sources and Climate

Change Mitigation. Special Report of Working Group III of the Intergovernmental

Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, K. Seyboth,

P. Matschoss, S. Kadner, T. Zwickel, P. Eickemeier, G. Hansen, S. Schlömer, and C.

von Stechow (eds.)]. Cambridge University Press, Cambridge, UK and New York,

NY, USA, pp. 791-864.

Fitzherbert, E., M. Struebig, A. Morel, F. Danielsen, C. Brühl, P. Donald, and B. Phalan,

2008: How will oil palm expansion affect biodiversity? Trends in Ecology and

Evolution, 23(10), 538-545.

Folke, C., S. Carpenter, T. Elmqvist, L. Gunderson, C.S. Holling, and B. Walker, 2002:

Resilience and sustainable development: building adaptive capacity in a world

of transformations. Ambio, 31(5), 437-440.

Fortner, S.K., B.G. Mark, J.M. McKenzie, J. Bury, A. Trierweiler, M. Baraer, P.J. Burns,

and L. Munk, 2011: Elevated stream trace and minor element concentrations

in the foreland of receding tropical glaciers. Applied Geochemistry, 26(11),

1792-1801.

Foster, J.L., D.K. Hall, R.E.J. Kelly, and L. Chiu, 2009: Seasonal snow extent and snow

mass in South America using SMMR and SSM/I passive microwave data (1979-

2006). Remote Sensing of Environment, 113(2), 291-305.

Francini-Filho, R.B. and R.L. Moura, 2008: Dynamics of fish assemblages on coral reefs

subjected to different management regimes in the Abrolhos Bank, eastern Brazil.

Aquatic Conservation: Marine and Freshwater Ecosystems, 18(7), 1166-1179.

Francini-Filho, R.B., R.L. Moura, F.L. Thompson, R.M. Reis, L. Kaufman, R.K.P. Kikuchi,

and Z.M. Leão, 2008: Diseases leading to accelerated decline of reef corals in

the largest South Atlantic reef complex (Abrolhos Bank, eastern Brazil). Marine

Pollution Bulletin, 56(5), 1008-1014.

Franco-Paredes, C., D. Jones, A.J. Rodriguez-Morales, and J. Ignacio Santos-Preciado,

2007: Commentary: improving the health of neglected populations in Latin

America. BMC Public Health, 7, 11, doi:10.1186/1471-2458-7-11.

Francou, B., B. Cáceres, J. Gomez, and A. Soruco, 2007: Coherence of the glacier

signal throughout the tropical Andes over the last decades. Proceedings of the

First International Conference on the Impact of Climate Change on High-

Mountain Systems, Institute of Hydrology, Meteorology, and Environmental

Studies (IDEAM), the Colombian Ministry of the Environment, Housing and

Regional Development, November 2005, Bogotá, DC, Colombia. National

Printing Office of Colombia, Bogotá, DC, Columbia, pp. 87-97.

Francou, B., D. Fabre, B. Pouyaud, V. Jomelli, and Y. Arnaud, 1999: Symptoms of

degradation in a tropical rock glacier, Bolivian Andes. Permafrost and Periglacial

Processes, 10(1), 91-100.

Fraser, B., 2012: Melting in the Andes: goodbye glaciers. Nature, 491(7423), 180-182.

Freire, K.M.F. and D. Pauly, 2010: Fishing down Brazilian marine food webs, emphasis

on the east Brazil large marine ecosystem. Fisheries Research, 105(1), 57-62.

Freitas, M.A.V. and J.L.S. Soito, 2009: Vulnerability to climate change and water

management: hydropower generation in Brazil. River Basin Management V,

124, 217-226.

Fry, L., D. Watkins, J. Mihelcic, and N. Reents, 2010: Sustainability of gravity fed water

systems in Alto Beni, Bolivia: preparing for change. In: World Environmental

and Water Resources Congress 2010: Challenges of Change [Palmer, R.N. (ed.)].

Proceedings of World Environmental and Water Resources Congress 2010:

Challenges of Change in Providence, Rhode Island,16-20 May, 2010, American

Society of Civil Engineers (ASCE), Reston, VA, USA, pp. 744-751.

Fry, L.M., D.W. Watkins, N. Reents, M.D. Rowe, and J.R. Mihelcic, 2012: Climate change

and development impacts on the sustainability of spring-fed water supply

systems in the Alto Beni region of Bolivia. Journal of Hydrology, 468, 120-129.

Fuentes, M.V., 2004: Proposal of a Geographic Information System for modeling

zoonotic fasciolosis transmission in the Andes. Parasitologia Latinoamericana,

59(1-2), 51-55.

Fuller, D.O., A. Troyo, and J.C. Beier, 2009: El Niño Southern Oscillation and vegetation

dynamics as predictors of dengue fever cases in Costa Rica. Environmental

Research Letters, 4(1), 014011,doi:10.1088/1748-9326/4/1/014011.

García, A.L., R. Parrado, E. Rojas, R. Delgado, J.-C. Dujardin, and R. Reithinger, 2009:

Leishmaniases in Bolivia: comprehensive review and current status. American

Journal of Tropical Medicine and Hygiene, 80(5), 704-711.

Gardner, C.L. and K.D. Ryman, 2010: Yellow fever: a reemerging threat. Clinics in

Laboratory Medicine, 30(1), 237-260.

Garreaud, R.D. and M. Falvey, 2009: The coastal winds off western subtropical South

America in future climate scenarios. International Journal of Climatology, 29(4),

543-554.

Gascoin, S., C. Kinnard, R. Ponce, S. Lhermitte, S. MacDonell, and A. Rabatel, 2011:

Glacier contribution to streamflow in two headwaters of the Huasco River, Dry

Andes of Chile. The Cryosphere, 5(4), 1099-1113.

Gasparri, N.I. and H.R. Grau, 2009: Deforestation and fragmentation of Chaco dry

forest in NW Argentina (1972-2007). Forest Ecology and Management, 258(6),

913-921.

Gasparri, N.I., H.R. Grau, and E. Manghi, 2008: Carbon pools and emissions from

deforestation in extra-tropical forests of Northern Argentina between 1900 and

2005. Ecosystems, 11(8), 1247-1261.

Gasper, R., A. Blohm, and M. Ruth, 2011: Social and economic impacts of climate

change on the urban environment. Current Opinion in Environmental

Sustainability, 3(3), 150-157.

Gavilán, R.G. and J. Martínez-Urtaza, 2011: Factores ambientales vinculados con la

aparición y dispersión de las epidemias de Vibrio en América del Sur

[Environmental drivers of emergence and spreading of vibrio epidemics in

South America]. Revista Peruana de Medicina de Experimental y Salud Publica,

28(1), 109-115 (in Spanish).

1553

Central and South America Chapter 27

Geerts, S. and D. Raes, 2009: Deficit irrigation as an on-farm strategy to maximize

crop water productivity in dry areas. Agricultural Water Management, 96(9),

1275-1284.

Geerts, S., D. Raes, and M. Garcia, 2010: Using AquaCrop to derive deficit irrigation

schedules. Agricultural Water Management, 98(1), 213-216.

Georgescu, M., D.B. Lobell, C.B. Field, and A. Mahalov, 2013: Simulated hydroclimatic

impacts of projected Brazilian sugarcane expansion. Geophysical Research

Letters, 40(5), 972-977.

Gharbi, M., P. Quenel, J. Gustave, S. Cassadou, G. La Ruche, L. Girdary, and L.

Marrama, 2011: Time series analysis of dengue incidence in Guadeloupe, French

West Indies: forecasting models using climate variables as predictors. BMC

Infectious Diseases, 11, 166, doi:10.1186/1471-2334-11-166.

Ghini, R., W. Bettiol, and E. Hamada, 2011: Diseases in tropical and plantation crops

as affected by climate changes: current knowledge and perspectives. Plant

Pathology, 60(1), 122-132.

Gibbons, J.M., E. Nicholson, E.J. Milner-Gulland, and J.P.G. Jones, 2011: Should

payments for biodiversity conservation be based on action or results? Journal

of Applied Ecology, 48(5), 1218-1226.

Gil, L.H.S., M.S. Tada, T.H. Katsuragawa, P.E.M. Ribolla, and L.H.P. Da Silva, 2007:

Urban and suburban malaria in Rondônia (Brazilian Western Amazon) II.

Perennial transmissions with high anopheline densities are associated with

human environmental changes. Memórias do Instituto Oswaldo Cruz, 102(3),

271-276.

Gilbert, A., P. Wagnon, C. Vincent, P. Ginot, and M. Funk, 2010: Atmospheric warming

at a high-elevation tropical site revealed by englacial temperatures at Illimani,

Bolivia (6340 m above sea level, 16°S, 67°W). Journal of Geophysical Research,

115(D10), D10109, doi:10.1029/2009JD012961.

Gilman, E.L., J. Ellison, N.C. Duke, and C. Field, 2008: Threats to mangroves from climate

change and adaptation options: a review. Aquatic Botany, 89(2), 237-250.

Giorgi, F., 2002: Variability and trends of sub-continental scale surface climate in the

twentieth century. Part I: observations. Climate Dynamics, 18(8), 675-691.

Giorgi, F., 2006: Climate change hot-spots. Geophysical Research Letters, 33(8),

L08707, doi:10.1029/2006GL025734.

Giorgi, F. and N. Diffenbaugh, 2008: Developing regional climate change scenarios

for use in assessment of effects on human health and disease. Climate

Research, 36(2), 141-151.

Giraldo, D., H. Juarez, W. Pérez, I. Trebejo, W. Yzarra, and G. Forbes, 2010: Severidad

del tizón tardío de la papa (Phytophthora infestans) en zonas agrícolas del

Perú asociado con el cambio climático [Severity of the potato late blight

(Phytophthora infestans) in agricultural areas of Peru associated with climate

change]. Revista Peruana Geo-Atmosférica (RPGA), 2, 56-67 (in Spanish).

Giri, C., E. Ochieng, L.L. Tieszen, Z. Zhu, A. Singh, T. Loveland, J. Masek, and N. Duke,

2011: Status and distribution of mangrove forests of the world using earth

observation satellite data. Global Ecology and Biogeography, 20(1), 154-159.

Gloor, M., R.J.W. Brienen, D. Galbraith, T.R. Feldpausch, J. Schöngart, J.-L. Guyot, J.C.

Espinoza, J. Lloyd, and O.L. Phillips, 2013: Intensification of the Amazon

hydrological cycle over the last two decades. Geophysical Research Letters,

40(9), 1729-1733.

Goldemberg, J., 2008: The Brazilian biofuels industry. Biotechnology for Biofuels,

1(1), 6, doi:10.1186/1754-6834-1-6.

Gomes, A.F., A.A. Nobre, and O.G. Cruz, 2012: Temporal analysis of the relationship

between dengue and meteorological variables in the city of Rio de Janeiro,

Brazil, 2001-2009. Cadernos de Saúde Pública, 28(11), 2189-2197.

Gomez, C., A.J. Rodriguez-Morales, and C. Franco-Paredes, 2006: Impact of climate

variability in the occurrence of leishmaniasis in Bolivia. American Journal of

Tropical Medicine and Hygiene, 75(5 Suppl.), 42, www.ajtmh.org/content/

75/5_suppl/26.full.pdf+html.

Gondim, R.S., M.A.H. de Castro, A.d.H.N. Maia, S.R.M. Evangelista, and S.C.d.F. Fuck

Jr., 2012: Climate change impacts on irrigation water needs in the Jaguaribe River

Basin. Journal of the American Water Resources Association, 48(2), 355-365.

Gondim, R.S., M.A.H. de Castro, S.R.d.M. Evangelista, A.d.S. Teixeira, and S.C.d.F. Fuck

Jr., 2008: Mudanças climáticas e impactos na necessidade hídrica das culturas

perenes na Bacia do Jaguaribe, no Estado do Ceará [Climate change and impacts

on water requirement of permanent crops in the Jaguaribe Basin, Ceará, Brazil].

Pesquisa Agropecuária Brasileira, 43(12), 1657-1664 (in Portuguese).

Gosling, S.N., R.G. Taylor, N.W. Arnell, and M.C. Todd, 2011: A comparative analysis

of projected impacts of climate change on river runoff from global and

catchment-scale hydrological models. Hydrology and Earth System Sciences,

15(1), 279-294.

Gottdenker, N.L., J.E. Calzada, A. Saldaña, and C.R. Carroll, 2011: Association of

anthropogenic land use change and increased abundance of the Chagas

disease vector Rhodnius pallescens in a rural landscape of Panama. American

Journal of Tropical Medicine and Hygiene, 84(1), 70-77.

Graham, C., L. Higuera, and E. Lora, 2011: Which health conditions cause the most

unhappiness? Health Economics, 20(12), 1431-1447.

Grantz, K., B. Rajagopalan, M. Clark, and E. Zagona, 2007: Seasonal shifts in the

North American monsoon. Journal of Climate, 20(9), 1923-1935.

Grass, D. and M. Cane, 2008: The effects of weather and air pollution on cardiovascular

and respiratory mortality in Santiago, Chile, during the winters of 1988-1996.

International Journal of Climatology, 28(8), 1113-1126.

Gratiot, N., E.J. Anthony, A. Gardel, C. Gaucherel, C. Proisy, and J.T. Wells, 2008:

Significant contribution of the 18.6 year tidal cycle to regional coastal changes.

Nature Geoscience, 1(3), 169-172.

Grau, H.R. and M. Aide, 2008: Globalization and land-use transitions in Latin

America. Ecology and Society, 13(2), 16, www.ecologyandsociety.org/

vol13/iss2/art16/.

Gray, C.L., R.E. Bilsborrow, J.L. Bremner, and F. Lu, 2008: Indigenous land use in the

Ecuadorian Amazon: a cross-cultural and multilevel analysis. Human Ecology,

36(1), 97-109.

Gregg, J.S. and S.J. Smith, 2010: Global and regional potential for bioenergy from

agricultural and forestry residue biomass. Mitigation and Adaptation Strategies

for Global Change, 15(3), 241-262.

Gruskin, D., 2012: Agbiotech 2.0. Nature Biotechnology, 30(3), 211-214.

Guarderas, A.P., S.D. Hacker, and J. Lubchenco, 2008: Current status of marine

protected areas in Latin America and the Caribbean. Conservation Biology,

22(6), 1630-1640.

Guariguata, M.R., 2009: El manejo forestal en el contexto de la adaptación al cambio

climático [Tropical forest management and climate change adaptation]. Revista

de Estudios Sociales, 32, 98-113 (in Spanish).

Guariguata, M.R., P. Sist, and R. Nasi, 2012: Reprint of: multiple use management

of tropical production forests: how can we move from concept to reality? Forest

Ecology and Management, 268, 1-5.

Guevara, S. and J. Laborde, 2008: The landscape approach: designing new reserves

for protection of biological and cultural diversity in Latin America. Environmental

Ethics, 30(3), 251-262.

Guimberteau, M., J. Ronchail, J.C. Espinoza, M. Lengaigne, B. Sultan, J. Polcher, G.

Drapeau, J.-L. Guyot, A. Ducharne, and P. Ciais, 2013: Future changes in

precipitation and impacts on extreme streamflow over Amazonian sub-basins.

Environmental Research Letters, 8(1), 014035, doi:10.1088/1748-9326/8/1/

014035.

Gullison, R.E., P.C. Frumhoff, J.G. Canadell, C.B. Field, D.C. Nepstad, K. Hayhoe, R.

Avissar, L.M. Curran, P. Friedlingstein, C.D. Jones, and C. Nobre, 2007: Tropical

forests and climate policy. Science, 316(5827), 985-986.

Gurjar, B.R., A. Jain, A. Sharma, A. Agarwal, P. Gupta, A.S. Nagpure, and J. Lelieveld,

2010: Human health risks in megacities due to air pollution. Atmospheric

Environment, 44(36), 4606-4613.

Gutiérrez, D., A. Bertrand, C. Wosnitza-Mendo, B. Dewitte, S. Purca, C. Peña, A.

Chaigneau, J. Tam, M. Graco, V. Echevin, C. Grados, P. Fréon, and R. Guevara-

Carrasco, 2011a: Sensibilidad del sistema de afloramiento costero del Perú al

cambio climático e implicancias ecológicas [Climate change sensitivity of the

Peruvian upwelling system and ecological implications]. Revista Peruana Geo-

Atmosférica (RPGA), 3, 1-24 (in Spanish).

Gutiérrez, D., I. Bouloubassi, A. Sifeddine, S. Purca, K. Goubanova, M. Graco, D. Field,

L. Mejanelle, F. Velazco, A. Lorre, R. Salvatteci, D. Quispe, G. Vargas, B. Dewitte,

and L. Ortlieb, 2011b: Coastal cooling and increased productivity in the main

upwelling zone off Peru since the mid-twentieth century. Geophysical Research

Letters, 38, L07603, doi:10.1029/2010GL046324.

Gutiérrez-Vélez, V., R.S. DeFries, M. Pinedo-Vásquez, M. Uriarte, C. Padoch, W.E.

Baethgen, K. Fernandes, and Y. Lim, 2011: High-yield oil palm expansion spares

land at the expense of forests in the Peruvian Amazon. Environmental Research

Letters, 6(4), 044029, doi:10.1088/1748-9326/6/4/044029.

Hajat, S., M. O’Connor, and T. Kosatsky, 2010: Health effects of hot weather: from

awareness of risk factors to effective health protection. The Lancet, 375(9717),

856-863.

Hall, T.C., A.M. Sealy, T.S. Stephenson, S. Kusunoki, M.A. Taylor, A.A. Chen, and A.

Kitoh, 2013: Future climate of the Caribbean from a super-high-resolution

atmospheric general circulation model. Theoretical and Applied Climatology,

113(1-2), 271-287.

1554

Chapter 27 Central and South America

Halpern, B.S., S. Walbridge, K.A. Selkoe, C.V. Kappel, F. Micheli, C. D’Agrosa, J.F. Bruno,

K.S. Casey, C. Ebert, H.E. Fox, R. Fujita, D. Heinemann, H.S. Lenihan, E.M.P. Madin,

M.T. Perry, E.R. Selig, M. Spalding, R. Steneck, and R. Watson, 2008: A global

map of human impact on marine ecosystems. Science, 319(5865), 948-952.

Halpern, B.S., C. Longo, D. Hardy, K.L. McLeod, J.F. Samhouri, S.K. Katona, K. Kleisner,

S.E. Lester, J. O’Leary, M. Ranelletti, A.A. Rosenberg, C. Scarborough, E.R. Selig,

B.D. Best, D.R. Brumbaugh, F.S. Chapin, L.B. Crowder, K.L. Daly, S.C. Doney, C.

Elfes, M.J. Fogarty, S.D. Gaines, K.I. Jacobsen, L.B. Karrer, H.M. Leslie, E. Neeley,

D. Pauly, S. Polasky, B. Ris, K. St. Martin, G.S. Stone, U.R. Sumaila, and D. Zeller,

2012: An index to assess the health and benefits of the global ocean. Nature,

488(7413), 615-620.

Halsnæs, K. and J. Verhagen, 2007: Development based climate change adaptation

and mitigation – conceptual issues and lessons learned in studies in developing

countries. Mitigation and Adaptation Strategies for Global Change, 12(5), 665-

684.

Hanf, M., A. Adenis, M. Nacher, and B. Carme, 2011: The role of El Niño Southern

Oscillation (ENSO) on variations of monthly Plasmodium falciparum malaria

cases at the Cayenne General Hospital, 1996-2009, French Guiana. Malaria

Journal, 10, 100, doi:10.1186/1475-2875-10-100.

Hantke-Domas, M., 2011: Avances Legislativos en Gestión Sostenible y Descentralizada

del Agua en América Latina. LC/W.44, Economic Commission for Latin America

and the Caribbean (ECLAC), Santiago de Chile, Chile, 70 pp. (in Spanish).

Hardoy, J. and G. Pandiella, 2009: Urban poverty and vulnerability to climate change

in Latin America. Environment and Urbanization, 21(1), 203-224.

Hardoy, J. and P. Romero-Lankao, 2011: Latin American cities and climate change:

challenges and options to mitigation and adaptation responses. Current

Opinion in Environmental Sustainability, 3(3), 158-163.

Harrison, S., N. Glasser, V. Winchester, E. Haresign, C. Warren, and K. Jansson, 2006:

A glacial lake outburst flood associated with recent mountain glacier retreat,

Patagonian Andes. The Holocene, 16(4), 611-620.

Harvey, C.A., O. Komar, R. Chazdon, B.G. Ferguson, B. Finegan, D.M. Griffith, M.

Martínez-Ramos, H. Morales, R. Nigh, L. Soto-Pinto, M. Van Breugel, and M.

Wishnie, 2008: Integrating agricultural landscapes with biodiversity conservation

in the Mesoamerican hotspot. Conservation Biology, 22(1), 8-15.

Hastenrath, S., 2012: Exploring the climate problems of Brazil’s Nordeste: a review.

Climatic Change, 112(2), 243-251.

Hastings, J.G., 2011: International environmental NGOs and conservation science

and policy: a case from Brazil. Coastal Management, 39(3), 317-335.

Hayhoe, S.J., C. Neill, S. Porder, R. McHorney, P. Lefebvre, M.T. Coe, H. Elsenbeer, and

A.V. Krusche, 2011: Conversion to soy on the Amazonian agricultural frontier

increases streamflow without affecting stormflow dynamics. Global Change

Biology, 17(5), 1821-1833.

Hecht, S.B. and S.S. Saatchi, 2007: Globalization and forest resurgence: changes in

forest cover in El Salvador. BioScience, 57(8), 663-672.

Hegglin, E. and C. Huggel, 2008: An integrated assessment of vulnerability to glacial

hazards: a case study in the Cordillera Blanca, Peru. Mountain Research and

Development, 28(3-4), 299-309.

Heinrichs, D. and K. Krellenberg, 2011: Chapter 23: Climate adaptation strategies:

evidence from Latin American city-regions. In: Resilient Cities: Cities and

Adaptation to Climate Change. Proceedings of the Global Forum 2010 [Otto-

Zimmermann, K. (ed.)]. Local Sustainability Vol. 1, Springer, New York, NY, USA,

pp. 223-230.

Heller, N.E. and E.S. Zavaleta, 2009: Biodiversity management in the face of climate

change: a review of 22 years of recommendations. Biological Conservation,

142(1), 14-32.

Henríquez Ruiz, C., 2009: El proceso de urbanización en la cuenca del Río Chillán y

su capacidad adaptativa ante precipitaciones extremas [The process of

urbanization in the Chillán River basin and its adaptive capacity to stormwater].

Revista Estudios Geográficos, 70(266), 155-179 (in Spanish).

Herrera-Martinez, A.D. and A.J. Rodríguez-Morales, 2010: Potential influence of

climate variability on dengue incidence registered in a western pediatric

hospital of Venezuela. Tropical Biomedicine, 27(2), 280-286.

Hertel, T.W., M.B. Burke, and D.B. Lobell, 2010: The poverty implications of climate-

induced crop yield changes by 2030. Global Environmental Change, 20(4), 577-

585.

Hickey, C. and T. Weis, 2012: The challenge of climate change adaptation in Guyana.

Climate and Development, 4(1), 66-74.

Hidalgo, H.G., J.A. Amador, E.J. Alfaro, and B. Quesada, 2013: Hydrological climate

change projections for Central America. Journal of Hydrology, 495, 94-112.

Hirata, R. and B.P. Conicelli, 2012: Groundwater resources in Brazil: a review of

possible impacts caused by climate change. Anais da Academia Brasileira

Ciências, 84(2), 297-312.

Hoegh-Guldberg, O. and J.F. Bruno, 2010: The impact of climate change on the

world’s marine ecosystems. Science, 328(5985), 1523-1528.

Hoffmann, D., I. Oetting, C.A. Arnillas, and R. Ulloa, 2011: Climate change and

protected areas in the Tropical Andes. In: Climate Change and Biodiversity in

the Tropical Andes [Herzog, S.K., R. Martínez, P.M. Jørgensen, and H. Tiessen

(eds.)]. Inter-American Institute for Global Change Research (IAI) and Scientific

Committee on Problems of the Envrionment (SCOPE), IAI, São José dos Campos,

SP, Brazil and SCOPE, Paris, France, pp. 311-325.

Hofstra, N., 2011: Quantifying the impact of climate change on enteric waterborne

pathogen concentrations in surface water. Current Opinion in Environmental

Sustainability, 3(6), 471-479.

Holder, C.D., 2006: The hydrological significance of cloud forests in the Sierra de las

Minas Biosphere Reserve, Guatemala. Geoforum, 37(1), 82-93.

Holmner, Å., A. Mackenzie, and U. Krengel, 2010: Molecular basis of cholera blood-

group dependence and implications for a world characterized by climate

change. Federation of European Biochemical Societies (FEBS) Letters, 584(12),

2548-2555.

Holt-Gimenez, E., 2002: Measuring farmers’ agroecological resistance after Hurricane

Mitch in Nicaragua: a case study in participatory, sustainable land management

impact monitoring. Agriculture Ecosystems & Environment, 93(1-3), 87-105.

Honório, N.A., C.T. Codeço, F.C. Alves, M.A.F.M. Magalhes, and R. Lourenço-De-

Oliveira, 2009: Temporal distribution of Aedes aegypti in different districts of

Rio De Janeiro, Brazil, measured by two types of traps. Journal of Medical

Entomology, 46(5), 1001-1014.

Hotez, P.J., M.E. Bottazzi, C. Franco-Paredes, S.K. Ault, and M.R. Periago, 2008: The

neglected tropical diseases of Latin America and the Caribbean: a review of

disease burden and distribution and a roadmap for control and elimination.

PLoS Neglected Tropical Diseases, 2(9), e300, doi:10.1371/journal.pntd.

0000300.

Hoyos, L.E., A.M. Cingolani, M.R. Zak, M.V. Vaieretti, D.E. Gorla, and M.R. Cabido,

2012: Deforestation and precipitation patterns in the arid Chaco forests of

central Argentina. Applied Vegetation Science, 16(2), 260-271 (published online

9 July 2012).

Hoyos, N., J. Escobar, J.C. Restrepo, A.M. Arango, and J.C. Ortiz, 2013: Impact of the

2010-2011 La Nina phenomenon in Colombia, South America: the human toll

of an extreme weather event. Applied Geography, 39, 16-25.

Hsiang, S.M., 2010: Temperatures and cyclones strongly associated with economic

production in the Caribbean and Central America. Proceedings of the National

Academy of Sciences of the United States of America, 107(35), 15367-15372.

Huang, C., A.G. Barnett, X. Wang, P. Vaneckova, G. Fitzgerald, and S. Tong, 2011:

Projecting future heat-related mortality under climate change scenarios: a

systematic review. Environmental Health Perspectives, 119(12), 1681-1690.

Huarcaya, E., C. Maguiña, R. Torres, J. Rupay, and L. Fuentes, 2004: Bartonelosis

(Carrion’s Disease) in the pediatric population of Peru: an overview and update.

The Brazilian Journal of Infectious Diseases, 8(5), 331-339.

Hubbell, S.P., F. He, R. Condit, L. Borda-de-Agua, J. Kellner, and H. ter Steege, 2008:

How many tree species are there in the Amazon and how many of them will

go extinct? Proceedings of the National Academy of Sciences of the United

States of America, 105(1 Suppl.), 11498-11504.

ICO, 2013: Report on the Outbreak of Coffee Leaf Rust in Central America and Action

Plan to Combat the Pest. ED 2157/13, International Coffee Organization (ICO),

London, UK, 6 pp.

IDB, 2013: Emerging and Sustainable Cities Initiative (ESCI). Inter-American

Development Bank, New York, NY, USA, www.iadb.org/en/topics/emerging-

and-sustainable-cities/emerging-and-sustainable-cities-initiative,6656.html.

IDEAM, 2012: Glaciares de Colombia, más que Montañas con Hielo. Instituto de

Hidrología, Meteorología y Estudios Ambientales (IDEAM), Bogotá, DC, Colombia,

344 pp.

IEA, 2012: Statistics & balances. In: IAE Statistics. International Energy Agency (IEA),

Paris, France, www.iea.org/stats/index.asp.

Igreja, R.P., 2011: Infectious disease control in Brazil. The Lancet, 378(9797), 1135,

doi:10.1016/S0140-6736(11)61497-9.

Imbach, P., L. Molina, B. Locatelli, O. Roupsard, G. Mahé, R. Neilson, L. Corrales, M.

Scholze, and P. Ciais, 2012: Modeling potential equilibrium states of vegetation

and terrestrial water cycle of Mesoamerica under climate change scenarios.

Journal of Hydrometeorology, 13(2), 665-680.

1555

Central and South America Chapter 27

INE, 2011: Compendio Estadístico Ambiental de Guatemala 2010. Instituto Nacional

de Estadística (INE), Sección de Estadísticas Ambientales, Oficina Coordinadora

Sectorial de Estadísticas de Ambiente y Recursos Naturales, OCSE/Ambiente,

Ciudad de Guatemala, Guatemala, 357 pp. (in Spanish).

INPE, 2011: Projeto PRODES. Monitoramente da Floresta Amazônica Brasileira por

Satélite. Instituto Nacional de Pesquisas Espaciais (INPE), São José dos Campos,

SP, Brazil, www.obt.inpe.br/prodes/.

IPCC, 2011: IPCC Special Report on Renewable Energy Sources and Climate Change

Mitigation. Special Report of Working Group III of the Intergovernmental Panel

on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, K. Seyboth, P.

Matschoss, S. Kadner, T. Zwickel, P. Eickemeier, G. Hansen, S. Schlömer, and C.

von Stechow (eds.)]. Cambridge University Press, Cambridge, UK and New York,

NY, USA, 1075 pp.

IPCC, 2012a: Summary for Policymakers. In: Managing the Risks of Extreme Events

and Disasters to Advance Climate Change Adaptation. A Special Report of

Working Groups I and II of the Intergovernmental Panel on Climate Change

[Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea,

K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor, and P.M. Midgley (eds.)].

Cambridge University Press, Cambridge, UK and New York, NY, USA, pp. 1-19.

IPCC, 2012b: Managing the Risks of Extreme Events and Disasters to Advance

Climate Change Adaptation. A Special Report of Working Groups I and II of the

Intergovernmental Panel on Climate Change [Field, C.B., V. Barros, T.F. Stocker,

D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K. Plattner, S.K.

Allen, M. Tignor, and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge,

UK and New York, NY, USA, 582 pp.

Ison, R., 2010: Systems Practice: How to Act in a Climate-Change World. Springer,

London, UK, 340 pp.

ITC, 2007: Organic Farming and Climate Change. International Trade Centre (ITC) of

the United Nations Conference on Trade and Development (UNCTAD) and the

World Trade Organization (WTO) and the Research Institute of Organic

Agriculture (FiBL), ITC, Geneva, Switzerland, 29 pp.

Izaguirre, C., F. Méndez, A. Espejo, I.J. Losada, and B.G. Reguero, 2013: Extreme wave

climate changes in Central-South America. Climatic Change, 119(2), 277-290.

Izquierdo, A.E., C.D. De Angelo, and T.M. Aide, 2008: Thirty years of human demography

and land-use change in the Atlantic forest of Misiones, Argentina: an evaluation

of the forest transition model. Ecology and Society, 13(2), 3, www.ecologyand

society.org/vol13/iss2/art3/.

Jara-Rojas, R., B.E. Bravo-Ureta, and J. Díaz, 2012: Adoption of water conservation

practices: a socioeconomic analysis of small-scale farmers in Central Chile.

Agricultural Systems, 110, 54-62.

Jarvis, A., J.L. Touval, M.C. Schmitz, L. Sotomayor, and G.G. Hyman, 2010: Assessment

of threats to ecosystems in South America. Journal for Nature Conservation,

18(3), 180-188.

Jasinski, R., L.A.A. Pereira, and A.L.F. Braga, 2011: Poluição atmosférica e internações

hospitalares por doenças respiratórias em crianças e adolescentes em Cubatão,

São Paulo, Brasil, entre 1997 e 2004 [Air pollution and pediatric hospital

admissions due to respiratory diseases in Cubatão, São Paulo State, Brazil, from

1997 to 2004]. Cadernos de Saúde Pública, 27(11), 2242-2252 (in Portuguese).

Jentes, E.S., G. Poumerol, M.D. Gershman, D.R. Hill, J. Lemarchand, R.F. Lewis, J.E.

Staples, O. Tomori, A. Wilder-Smith, and T.P. Monath, 2011: The revised global

yellow fever risk map and recommendations for vaccination, 2010: consensus

of the Informal WHO Working Group on Geographic Risk for Yellow Fever. The

Lancet Infectious Diseases, 11(8), 622-632.

Jomelli, V., V. Favier, A. Rabatel, D. Brunstein, G. Hoffmann, and B. Francou, 2009:

Fluctuations of glaciers in the tropical Andes over the last millennium and

palaeoclimatic implications: a review. Palaeogeography, Palaeoclimatology,

Palaeoecology, 281(3-4), 269-282.

Jomelli, V., M. Khodri, V. Favier, D. Brunstein, M.-P. Ledru, P. Wagnon, P.-H. Blard, J.-E.

Sicart, R. Braucher, D. Grancher, D.L. Bourles, P. Braconnot, and M. Vuille, 2011:

Irregular tropical glacier retreat over the Holocene epoch driven by progressive

warming. Nature, 474(7350), 196-199.

Jones, C. and L.V. Carvalho, 2013: Climate change in South American monsoon system:

present climate and CMIP5 projections. Journal of Climate, 26(17), 6660-6678.

Jonsson, C.B., L.T.M. Figueiredo, and O. Vapalahti, 2010: A global perspective on

hantavirus ecology, epidemiology, and disease. Clinical Microbiology Reviews,

23(2), 412-441.

Juen, I., G. Kaser, and C. Georges, 2007: Modelling observed and future runoff from

a glacierized tropical catchment (Cordillera Blanca, Perú). Global and Planetary

Change, 59(1-4), 37-48.

Jutla, A.S., A.S. Akanda, and S. Islam, 2010: Tracking cholera in coastal regions using

satellite observations. Journal of the American Water Resources Association,

46(4), 651-662.

Kacef, O. and R. López-Monti, 2010: Latin America, from boom to crisis: macroeconomic

policy challenges. Cepal Review, 100, 41-67.

Kaimowitz, D., 2008: The prospects for Reduced Emissions from Deforestation and

Degradation (REDD) in Mesoamerica. International Forestry Review, 10(3), 485-

495.

Kaimowitz, D. and A. Angelsen, 2008: Will livestock intensification help save Latin

America’s tropical forests? Journal of Sustainable Forestry, 27(1-2), 6-24.

Kamiguchi, K., A. Kitoh, T. Uchiyama, R. Mizuta, and A. Noda, 2006: Changes in

precipitation-based extremes indices due to global warming projected by a

global 20-km-mesh atmospheric model. Scientific Online Letters on the

Atmosphere (SOLA), 2, 64-67.

Kane, E.M., R.M. Turcios, M.L. Arvay, S. Garcia, J.S. Bresee, and R.I. Glass, 2004: The

epidemiology of rotavirus diarrhea in Latin America. Anticipating rotavirus

vaccines. Revista Panamericana de Salud Publica/Pan American Journal of

Public Health, 16(6), 371-377.

Karanja, D., S.J. Elliott, and S. Gabizon, 2011: Community level research on water

health and global change: where have we been? Where are we going? Current

Opinion in Environmental Sustainability, 3(6), 467-470.

Karmalkar, A.V., R.S. Bradley, and H.F. Diaz, 2011: Climate change in Central America

and Mexico: regional climate model validation and climate change projections.

Climate Dynamics, 37(3-4), 605-629.

Kaser, G., M. Großhauser, and B. Marzeion, 2010: Contribution potential of glaciers

to water availability in different climate regimes. Proceedings of the National

Academy of Sciences of the United States of America, 107(47), 20223-20227.

Keim, M.E., 2008: Building human resilience: the role of public health preparedness

and response as an adaptation to climate change. American Journal of Preventive

Medicine, 35(5), 508-516.

Keller, M., D. Echeverría, and J.-E. Parry, 2011a: Review of Current and Planned

Adaptation Action: Central America and Mexico. Belize, Costa Rica, El Salvador,

Guatemala, Honduras, Nicaragua, Mexico and Panama.Adaptation Partnership

and International Institute for Sustainable Development (IISD), Adaptation

Partnership, Washington, DC, USA and IISD, Winnipeg, MB, Canada 143 pp.

Keller, M., D. Medeiros, D. Echeverría, and J.-E. Parry, 2011b: Review of Current and

Planned Adaptation Action: South America. Argentina, Bolivia, Brazil, Chile,

Colombia, Ecuador, Guyana, Paraguay, Peru, Suriname, Uruguay and Venezuela.

Adaptation Partnership and International Institute for Sustainable Development

(IISD), Adaptation Partnership, Washington, DC, USA and IISD, Winnipeg, MB,

Canada,190 pp.

Kelly-Hope, L.A. and M. Thomson, 2010: Chapter 4: Climate and infectious diseases.

In: Seasonal Forecasts, Climate Change and Human Health [Thomson, M.C., R.

Garcia-Herrera, and M. Beniston (eds.)]. Springer Health and Climate Series:

Advances in Global Change Research, Vol. 30, Springer, London, UK, pp. 31-70.

Kemkes, R.J., J. Farley, and C.J. Koliba, 2010: Determining when payments are an

effective policy approach to ecosystem service provision. Ecological Economics,

69(11), 2069-2074.

Khalil, A.F., H. Kwon, U. Lall, M.J. Miranda, and J. Skees, 2007: El Niño-Southern

Oscillation-based index insurance for floods: statistical risk analyses and

application to Peru. Water Resources Research, 43(10), W10416, doi:10.1029/

2006WR005281.

Killeen, T.J., A. Guerra, M. Calzada, L. Correa, V. Calderon, L. Soria, B. Quezada, and

M.K. Steininger, 2008: Total historical land-use change in eastern Bolivia: who,

where, when, and how much? Ecology and Society, 13(1), 36, www.ecology

andsociety.org/vol13/iss1/art36/.

Kirchhoff, C.J., M.C. Lemos, and N.L. Engle, 2013: What influences climate

information use in water management? The role of boundary organizations

and governance regimes in Brazil and the U.S. Environmental Science & Policy,

26, 6-18.

Kitoh, A., H. Endo, K. Krishna Kumar, I.F.A. Cavalcanti, P. Goswami, and T. Zhou, 2013:

Monsoons in a changing world: a regional perspective in a global context.

Journal of Geophysical Research: Atmospheres, 118(8), 3053-3065.

Kjellstrom, T. and J. Crowe, 2011: Climate change, workplace heat exposure, and

occupational health and productivity in Central America. International Journal

of Occupational and Environmental Health, 17(3), 270-281.

Kjellstrom, T., R.S. Kovats, S.J. Lloyd, T. Holt, and R.S.J. Tol, 2009: The direct impact of

climate change on regional labor productivity. Archives of Environmental &

Occupational Health, 64(4), 217-227.

1556

Chapter 27 Central and South America

Kjellstrom, T., A.J. Butler, R.M. Lucas, and R. Bonita, 2010: Public health impact of

global heating due to climate change: potential effects on chronic non-

communicable diseases. International Journal of Public Health, 55(2), 97-103.

Klemm, O., R.S. Schemenauer, A. Lummerich, P. Cereceda, V. Marzol, D. Corell, J. van

Heerden, D. Reinhard, T. Gherezghiher, J. Olivier, P. Osses, J. Sarsour, E. Frost, M.J.

Estrela, J.A. Valiente, and G.M. Fessehaye, 2012: Fog as a fresh-water resource:

overview and perspectives. AMBIO, 41(3), 221-234.

Klimas, C.A., K.A. Kainer, and L.H.d.O. Wadt, 2012: The economic value of sustainable

seed and timber harvests of multi-use species: an example using Carapa

guianensis. Forest Ecology and Management, 268, 81-91.

Koelle, K., 2009: The impact of climate on the disease dynamics of cholera. Clinical

Microbiology and Infection, 15(1 Suppl.), 29-31.

Koh, L.P. and J. Ghazoul, 2008: Biofuels, biodiversity, and people: understanding the

conflicts and finding opportunities. Biological Conservation, 141(10), 2450-

2460.

Kosaka, Y. and S. Xie, 2013: Recent global-warming hiatus tied to equatorial Pacific

surface cooling. Nature, 501, 403-407, doi:10.1038/nature12534.

Krellenberg, K., A. Mueller, A. Schwarz, R. Hoefer, and J. Welz, 2013: Flood and heat

hazards in the Metropolitan Region of Santiago de Chile and the socio-

economics of exposure. Applied Geography, 38, 86-95.

Krepper, C.M. and G.V. Zucarelli, 2010: Climatology of water excesses and shortages

in the La Plata Basin. Theoretical and Applied Climatology, 102(1-2), 13-27.

Krepper, C.M., N.O. García, and P.D. Jones, 2008: Low-frequency response of the

upper Paraná basin. International Journal of Climatology, 28(3), 351-360.

Krol, M.S. and A. Bronstert, 2007: Regional integrated modelling of climate change

impacts on natural resources and resource usage in semi-arid Northeast Brazil.

Environmental Modelling & Software, 22(2), 259-268.

Krol, M., A. Jaeger, A. Bronstert, and A. Guentner, 2006: Integrated modelling of

climate, water, soil, agricultural and socio-economic processes: a general

introduction of the methodology and some exemplary results from the semi-

arid north-east of Brazil. Journal of Hydrology, 328(3-4), 417-431.

Krol, M.S., M.J. Vries, P.R. Oel, and J.C. Araújo, 2011: Sustainability of small reservoirs

and large scale water availability under current conditions and climate change.

Water Resources Management, 25(12), 3017-3026.

Kumar, A., T. Schei, A. Ahenkorah, R. Caceres Rodriguez, J.-M. Devernay, M. Freitas,

D. Hall, Å. Killingtveit, and Z. Liu, 2011: Hydropower. In: IPCC Special Report on

Renewable Energy Sources and Climate Change Mitigation. Special Report of

Working Group III of the Intergovernmental Panel on Climate Change [Edenhofer,

O., R. Pichs-Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner, T. Zwickel,

P. Eickemeier, G. Hansen, S. Schlömer, and C. von Stechow (eds.)]. Cambridge

University Press, Cambridge, UK and New York, NY, USA, pp. 437-496.

Kumler, L.M. and M.C. Lemos, 2008: Managing waters of the Paraíba do Sul River

basin, Brazil: a case study in institutional change and social learning. Ecology

and Society, 13(2), 22, www.ecologyandsociety.org/vol13/iss2/art22/.

Kundzewicz, Z.W. and P. Döll, 2009: Will groundwater ease freshwater stress under

climate change? Hydrological Sciences Journal, 54(4), 665-675.

La Rovere, E.L., A.C. Avzaradel, and J.M.G. Monteiro, 2009: Potential synergy

between adaptation and mitigation strategies: production of vegetable oils

and biodiesel in northeastern Brazil. Climate Research, 40(2-3), 233-239.

Lacambra, C. and K. Zahedi, 2011: Climate change, natural hazards and coastal

ecosystems in Latin-America: a framework for analysis. In: Coping with Global

Environmental Change, Disasters and Security [Brauch, H.G., Ú. Oswald Spring,

C. Mesjasz, J. Grin, P. Kameri-Mbote, B. Chourou, P. Dunay, and J. Birkmann

(eds.)]. Hexagon Series on Human and Environmental Security and Peace Vol.

5, Springer, Berlin, Germany, pp. 585-601.

Lampis, A., 2010: Challenges to adaptation for risk-prone coastal livelihoods in

Tumaco, Pacific Coast (Colombia). Urbanization and Global Environmental

Change (UGEC) Viewpoints, March, 2010, No. 3, 18-22.

Langerwisch, F., S. Rost, D. Gerten, B. Poulter, A. Rammig, and W. Cramer, 2013:

Potential effects of climate change on inundation patterns in the Amazon Basin.

Hydrology and Earth System Sciences, 17(6), 2247-2262.

Lapola, D.M., R. Schaldach, J. Alcamo, A. Bondeau, J. Koch, C. Koelking, and J.A. Priess,

2010: Indirect land-use changes can overcome carbon savings from biofuels

in Brazil. Proceedings of the National Academy of Sciences of the United States

of America, 107(8), 3388-3393.

Lapola, D.M., R. Schaldach, J. Alcamo, A. Bondeau, S. Msangi, J.A. Priess, R. Silvestrini,

and B.S. Soares, 2011: Impacts of climate change and the end of deforestation

on land use in the Brazilian legal Amazon. Earth Interactions, 15(16),

doi:10.1175/2010EI333.1.

Lara, A., R. Villalba, and R. Urrutia, 2007: A 400-year tree-ring record of the Puelo

River summer–fall streamflow in the Valdivian Rainforest eco-region, Chile.

Climatic Change, 86(3-4), 331-356.

Lardeux, F., P. Loayza, B. Bouchite, and T. Chavez, 2007: Host choice and human blood

index of Anopheles pseudopunctipennis in a village of the Andean valleys of

Bolivia. Malaria Journal, 6, 8, doi:10.1186/1475-2875-6-8.

Larson, A.M., 2010: Making the ‘rules of the game’: constituting territory and

authority in Nicaragua’s indigenous communities. Land Use Policy, 27(4), 1143-

1152.

Laurance, W.F., D.C. Useche, L.P. Shoo, S.K. Herzog, M. Kessler, F. Escobar, G. Brehm,

J.C. Axmacher, I.-C. Chen, L. Arellano Gámez, P. Hietz, K. Fiedler, T. Pyrcz, J. Wolf,

C.L. Merkord, C. Cardelus, A.R. Marshall, C. Ah-Peng, G.H. Aplet, M. del Coro

Arizmendi, W.J. Baker, J. Barone, C.A. Brühl, R.W. Bussmann, D. Cicuzza, G. Eilu,

M.E. Favila, A. Hemp, C. Hemp, J. Homeier, J. Hurtado, J. Jankowski, G. Kattán, J.

Kluge, T. Krömer, D.C. Lees, M. Lehnert, J.T. Longino, J. Lovett, P.H. Martin, B.D.

Patterson, R.G. Pearson, K.S.-H. Peh, B. Richardson, M. Richardson, M.J.

Samways, F. Senbeta, T.B. Smith, T.M.A. Utteridge, J.E. Watkins, R. Wilson, S.E.

Williams, and C.D. Thomas, 2011: Global warming, elevational ranges and the

vulnerability of tropical biota. Biological Conservation, 144(1), 548-557.

Lavado, C.W.S., D. Labat, J.L. Guyot, and S. Ardoin-Bardin, 2011: Assessment of

climate change impacts on the hydrology of the Peruvian Amazon–Andes basin.

Hydrological Processes, 25(24), 3721-3734.

Lavado, C.W.S., J. Ronchail, D. Labat, J.C. Espinoza, and J.L. Guyot, 2012: Basin-scale

analysis of rainfall and runoff in Peru (1969-2004): Pacific, Titicaca and

Amazonas drainages. Hydrological Sciences Journal/Journal des Sciences

Hydrologiques, 57(4), 625-642.

Lawler, J.J., S.L. Shafer, D. White, P. Kareiva, E.P. Maurer, A.R. Blaustein, and P.J.

Bartlein, 2009: Projected climate-induced faunal change in the Western

Hemisphere. Ecology, 90(3), 588-597.

Le Quesne, C., C. Acuña, J.A. Boninsegna, A. Rivera, and J. Barichivich, 2009: Long-

term glacier variations in the Central Andes of Argentina and Chile, inferred from

historical records and tree-ring reconstructed precipitation. Palaeogeography,

Palaeoclimatology, Palaeoecology, 281(3-4), 334-344.

Leguía, E.J., B. Locatelli, P. Imbach, C.J. Pérez, and R. Vignola, 2008: Servicios

ecosistémicos e hidroenergía en Costa Rica. Ecosistemas, 17(1), 16-23 (in

Spanish).

Leiva, J.C., G.A. Cabrera, and L.E. Lenzano, 2007: 20 years of mass balances on the

Piloto Glacier, Las Cuevas River basin, Mendoza, Argentina. Global and

Planetary Change, 59(1-4), 10-16.

Lemos, M.C., A.R. Bell, N.L. Engle, R.M. Formiga-Johnsson, and D.R. Nelson, 2010:

Technical knowledge and water resources management: a comparative study

of river basin councils, Brazil. Water Resources Research, 46(6), W06523,

doi:10.1029/2009WR007949.

Lentes, P., M. Peters, and F. Holmann, 2010: Regionalization of climatic factors and

income indicators for milk production in Honduras. Ecological Economics, 69(3),

539-552.

Lenton, T.M., H. Held, E. Kriegler, J.W. Hall, W. Lucht, S. Rahmstorf, and H.J. Schellnhuber,

2008: Tipping elements in the Earth’s climate system. Proceedings of the

National Academy of Sciences of the United States of America, 105(6), 1786-

1793.

Lesnikowski, A.C., J.D. Ford, L. Berrang-Ford, J.A. Paterson, M. Barrera, and S.J.

Heymann, 2011: Adapting to health impacts of climate change: a study of

UNFCCC Annex I parties. Environmental Research Letters, 6(4), 044009,

doi:10.1088/1748-9326/6/4/044009.

Lewis, S.L., P.M. Brando, O.L. Phillips, G.M.F. van der Heijden, and D. Nepstad, 2011:

The 2010 Amazon drought. Science, 331(6017), 554, doi:10.1126/science.

1200807.

Lin, B.B., 2011: Resilience in agriculture through crop diversification: adaptive

management for environmental change. BioScience, 61(3), 183-193.

Loarie, S., D.B. Lobell, G. Asner, Q. Mu, and C. Field, 2011: Direct impacts on local climate

of sugar-cane expansion in Brazil. Nature Climate Change, 1, 105-109.

Lobell, D.B. and C.B. Field, 2007: Global scale climate – crop yield relationships and

the impacts of recent warming. Environmental Research Letters, 2(1), 014002,

doi:10.1088/1748-9326/2/1/014002.

Lobell, D.B., M.B. Burke, C. Tebaldi, M.D. Mastrandrea, W.P. Falcon, and R.L. Naylor,

2008: Prioritizing climate change adaptation needs for food security in 2030.

Science, 319(5863), 607-610.

Lobell, D.B., W. Schlenker, and J. Costa-Roberts, 2011: Climate trends and global crop

production since 1980. Science, 333(6042), 616-620.

1557

Central and South America Chapter 27

Locatelli, B., V. Evans, A. Wardell, A. Andrade, and R. Vignola, 2011: Forests and

climate change in Latin America: linking adaptation and mitigation. Forests,

2(1), 431-450.

Lopes, A.A., A.P. Bandeira, P.C. Flores, and M.V.T. Santana, 2010: Pulmonary

hypertension in Latin America: pulmonary vascular disease: the global

perspective. Chest, 137(6 Suppl.), 78-84.

Lopes, C.A., G.O. da Silva, E.M. Cruz, E.D. Assad, and A.d.S. Pereira, 2011: Uma análise

do efeito do aquecimento global na produção de batata no Brasil [An analysis

of the potato production in Brazil upon global warming]. Horticultura Brasileira,

29(1), 7-15 (in Portuguese).

Lopez, P., P. Chevallier, V. Favier, B. Pouyaud, F. Ordenes, and J. Oerlemans, 2010: A

regional view of fluctuations in glacier length in southern South America.

Global and Planetary Change, 71(1-2), 85-108.

López, R. and G.I. Galinato, 2007: Should governments stop subsidies to private

goods? Evidence from rural Latin America. Journal of Public Economics, 91(5-6),

1071-1094.

López-Marrero, T., 2010: An integrative approach to study and promote natural

hazards adaptive capacity: a case study of two flood-prone communities in

Puerto Rico. Geographical Journal, 176(2), 150-163.

Lopez-Rodriguez, S.R. and J.F. Blanco-Libreros, 2008: Illicit crops tropical America:

deforestation, landslides, and the terrestrial carbon stocks. Ambio, 37(2), 141-

143.

Lorz, C., G. Abbt-Braun, F. Bakker, P. Borges, H. Börnick, L. Fortes, F.H. Frimmel, A.

Gaffron, N. Hebben, R. Höfer, F. Makeschin, K. Neder, L.H. Roig, B. Steiniger, M.

Strauch, D. Walde, H. Weiß, E. Worch, and J. Wummel, 2012: Challenges of an

integrated water resource management for the Distrito Federal, Western Central

Brazil: climate, land-use and water resources. Environmental Earth Sciences,

65(5), 1575-1586.

Losada, I.J., B.G. Reguero, F.J. Méndez, S. Castanedo, A.J. Abascal, and R. Mínguez,

2013: Long-term changes in sea-level components in Latin America and the

Caribbean. Global and Planetary Change, 104, 34-50.

Lowe, R., T.C. Bailey, D.B. Stephenson, R.J. Graham, C.A.S. Coelho, M. Sá Carvalho,

and C. Barcellos, 2011: Spatio-temporal modelling of climate-sensitive disease

risk: towards an early warning system for dengue in Brazil. Computers and

Geosciences, 37(3), 371-381.

Luber, G. and N. Prudent, 2009: Climate change and human health. Transactions of

the American Clinical and Climatological Association, 120, 113-117.

Luque, A., E. Gareth, and C. Lalande, 2013: Climate change governance at the local

level: new tools to respond to old deficiencies in Esmeraldas, Ecuador. Local

Environment: The International Journal of Justice and Sustainability, 18(6), 738-

751.

Luzar, J.B., K.M. Silvius, H. Overman, S.T. Giery, J.M. Read, and J.M.V. Fragoso, 2011:

Large-scale environmental monitoring by indigenous peoples. BioScience,

61(10), 771-781.

Lynch, B.D., 2012: Vulnerabilities, competition and rights in a context of climate

change toward equitable water governance in Peru’s Rio Santa Valley. Global

Environmental Change: Human and Policy Dimensions, 22(2), 364-373.

Macedo, I.C., J.E.A. Seabra, and J.E.A.R. Silva, 2008: Green house gases emissions

in the production and use of ethanol from sugarcane in Brazil: the 2005/2006

averages and a prediction for 2020. Biomass & Bioenergy, 32(7), 582-595.

MacNeil, A., S.T. Nichol, and C.F. Spiropoulou, 2011: Hantavirus pulmonary syndrome.

Virus Research, 162(1-2), 138-147.

Magnan, A., 2009: Proposition d’une trame de recherche pour appréhender la capacité

d’adaptation au changement climatique. VertigO – La Revue Électronique en

Sciences de l’Environnement, 9(3), doi:10.4000/vertigo.9189 (in French).

Magrin, G., C. Gay García, D. Cruz Choque, J.C. Giménez, A.R. Moreno, G.J. Nagy, C.

Nobre, and A. Villamizar, 2007a: Latin America. In: Climate Change 2007:

Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the

Fourth Assessment Report of the Intergovernmental Panel on Climate Change

[Parry, M.L., O.F. Canziani, J.P. Palutikof, P.J. van der Linden, and C.E. Hanson

(eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA, pp.

581-615.

Magrin, G.O., M.I. Travasso, W.E. Baethgen, M.O. Grondona, A. Giménez, G. Cunha,

J.P. Castaño, and G.R. Rodriguez, 2007b: Past and future changes in climate

and their impacts on annual crops yield in South East South America. In: IPCC

Task Group on Data Scenario Support for Impact and Climate Analysis (TGICA)

Expert Meeting: Integrating Analysis of Regional Climate Change and Response

Options. Meeting Report, Intergovernmental Panel on Climate Change (IPCC),

Nadi, Fiji, pp. 121-124.

Magrin, G.O., M.I. Travasso, G.M. López, G.R. Rodríguez, and A.R. Lloveras, 2007c:

Vulnerabilidad de la Producción Agrícola en la Región Pampeana Argentina:

Informe Final. 2da Comunicación Nacional Sobre el Cambio Climático,

Componente B3, Gobierno Argentina, Secretaría de Ambiente y Desarrollo

Sustentable, Buenos Aires, Argentina, 84 pp. (in Spanish).

Magrin, G.O., M.I. Travasso, G.R. Rodríguez, S. Solman, and M. Núñez, 2009: Climate

change and wheat production in Argentina. International Journal of Global

Warming, 1(1), 214-226.

Malhi, Y., J.T. Roberts, R.A. Betts, T.J. Killeen, W. Li, and C.A. Nobre, 2008: Climate

change, deforestation, and the fate of the Amazon. Science, 319(5860), 169-

172.

Malhi, Y., L.E.O.C. Aragão, D. Galbraith, C. Huntingford, R. Fisher, P. Zelazowski, S.

Sitch, C. McSweeney, and P. Meir, 2009: Exploring the likelihood and mechanism

of a climate-change-induced dieback of the Amazon rainforest. Proceedings of

the National Academy of Sciences of the United States of America, 106(49),

20610-20615.

Mangal, T.D., S. Paterson, and A. Fenton, 2008: Predicting the impact of long-term

temperature changes on the epidemiology and control of Schistosomiasis: a

mechanistic model. PLoS ONE, 3(1), e1438, doi:10.1371/journal.pone.0001438.

Mantilla, G., H. Oliveros, and A.G. Barnston, 2009: The role of ENSO in understanding

changes in Colombia’s annual malaria burden by region, 1960-2006. Malaria

Journal, 8, 6, doi:10.1186/1475-2875-8-6.

Manuel-Navarrete, D., J.J. Gómez, and G. Gallopín, 2007: Syndromes of sustainability

of development for assessing the vulnerability of coupled human-environmental

systems. The case of hydrometeorological disasters in Central America and the

Caribbean. Global Environmental Change: Human and Policy Dimensions,

17(2), 207-217.

Manzello, D.P., J.A. Kleypas, D.A. Budd, C.M. Eakin, P.W. Glynn, and C. Langdon, 2008:

Poorly cemented coral reefs of the eastern tropical Pacific: possible insights into

reef development in a high-CO

world. Proceedings of the National Academy

of Sciences of the United States of America, 105(30), 10450-10455.

Marcheggiani, S., C. Puccinelli, S. Ciadamidaro, V.D. Bella, M. Carere, M.F. Blasi, N.

Pacini, E. Funari, and L. Mancini, 2010: Risks of water-borne disease outbreaks

after extreme events. Toxicological and Environmental Chemistry, 92(3), 593-

599.

Marengo, J.A., 2004: Interdecadal variability and trends of rainfall across the Amazon

basin. Theoretical and Applied Climatology, 78(1-3), 79-96.

Marengo, J.A., C.A. Nobre, J. Tomasella, M.D. Oyama, G.S. de Oliveira, R. de Oliveira,

H. Camargo, L.M. Alves, and I.F. Brown, 2008: The drought of Amazonia in 2005.

Journal of Climate, 21(3), 495-516.

Marengo, J.A., R. Jones, L.M. Alves, and M.C. Valverde, 2009a: Future change of

temperature and precipitation extremes in South America as derived from the

PRECIS regional climate modeling system. International Journal of Climatology,

29(15), 2241-2255.

Marengo, J.A., M. Rusticucci, O. Penalba, and M. Renom, 2009b: An intercomparison

of observed and simulated extreme rainfall and temperature events during the

last half of the twentieth century: Part 2: historical trends. Climatic Change,

98(3-4), 509-529.

Marengo, J.A., T. Ambrizzi, R. da Rocha, L. Alves, S. Cuadra, M. Valverde, R. Torres, D.

Santos, and S. Ferraz, 2010: Future change of climate in South America in the

late twenty-first century: intercomparison of scenarios from three regional

climate models. Climate Dynamics, 35(6), 1073-1097.

Marengo, J.A., S.C. Chou, G. Kay, L.M. Alves, J.F. Pesquero, W.R. Soares, D.C. Santos,

A.A. Lyra, G. Sueiro, R. Betts, D.J. Chagas, J.L. Gomes, J.F. Bustamante, and P.

Tavares, 2011a: Development of regional future climate change scenarios in

South America using the Eta CPTEC/HadCM3 climate change projections:

climatology and regional analyses for the Amazon, São Francisco and the

Paraná river basins. Climate Dynamics, 38(9-10), 1829-1848.

Marengo, J.A., J.D. Pabón, A. Díaz, G. Rosas, G. Ávalos, E. Montealegre, M. Villacis, S.

Solman, and M. Rojas, 2011b: Chapter 7: Climate change: evidence and future

scenarios for the Andean region. In: Climate Change and Biodiversity in the

Tropical Andes [Herzog, K., R. Martínez, P.M. Jørgensen, and H. Tiessen (eds.)].

Inter-American Institute for Global Change Research (IAI) and Scientific

Committee on Problems of the Environment (SCOPE), funded by the John D.

and Catherine T. MacArthur Foundation, IAI Directorate, São Jose dos Campos,

São Paulo, Brazil, pp. 110-127.

Marengo, J.A., J. Tomasella, L.M. Alves, W.R. Soares, and D.A. Rodriguez, 2011c: The

drought of 2010 in the context of historical droughts in the Amazon region.

Geophysical Research Letters, 38(12), L12703, doi:10.1029/2011GL047436.

1558

Chapter 27 Central and South America

Marengo, J.A., J. Tomasella, W.R. Soares, L.M. Alves, and C.A. Nobre, 2012: Extreme

climatic events in the Amazon basin: climatological and hydrological context

of recent floods. Theoretical and Applied Climatology, 107(1-2), 73-85.

Marengo, J.A., L.M. Alves, W.R. Soares, D.A. Rodriguez, H. Camargo, M. Paredes

Riveros, and A. Diaz Pabló, 2013a: Two contrasting severe seasonal extremes

in tropical South America in 2012: flood in Amazonia and drought in northeast

Brazil. Journal of Climate, 26(22), 9137-9154.

Marengo, J.A., M.C. Valverde, and G.O. Obregon, 2013b: Assessments of observed

and projected changes in rainfall extremes in the Metropolitan Area of São

Paulo (MASP). Climate Research, 57, 61-72.

Margulis, S., C.B.S. Dubeux, and J. Marcovitch (eds.), 2010: Economia da Mudança

do Clima no Brasil: Custos e Oportunidades. IBEP Gráfica, São Paulo, Brazil, 82

pp. (in Portuguese).

Marin, F.R., G.Q. Pellegrino, E.D. Assad, D.S.P. Nassif, M.S. Viana, F.A. Soares, L.L.

Cabral, and D. Guiatto, 2009: Cenários Futuros para Cana-De-Açúcar no Estado

de São Paulo Baseados em Projeções Regionalizadas de Mudanças Climáticas.

Apresentado no XVI Congresso Brasileiro de Agrometeorologia, 22-25 September

2009, Gran Darrell Minas Hotel, Eventos e Convenções – Belo Horizonte, MG,

Brazil, 5 pp.

Marín, V.H., A. Tironi, M. Alejandra Paredes, and M. Contreras, 2013: Modeling suspended

solids in a Northern Chilean Patagonia glacier-fed fjord: GLOF scenarios under

climate change conditions. Ecological Modelling, 264, 7-16.

Marini, M.A., M. Barbet-Massin, L.E. Lopes, and F. Jiguet, 2009: Predicted climate-

driven bird distribution changes and forecasted conservation conflicts in a

neotropical savanna. Conservation Biology, 23(6), 1558-1567.

Mark, B.G., J. Bury, J.M. McKenzie, A. French, and M. Baraer, 2010: Climate change

and tropical Andean glacier recession: evaluating hydrologic changes and

livelihood vulnerability in the Cordillera Blanca, Peru. Annals of the Association

of American Geographers, 100(4), 794-805.

Marques, W.C., 2012: The temporal variability of the freshwater discharge and water

levels at the Patos Lagoon, Brazil. International Journal of Geosciences, 3(4),

758-766.

Marshall, A., 2012: Existing agbiotech traits continue global march. Nature

Biotechnology, 30(3), 207, doi:10.1038/nbt.2154.

Martiello, M.A. and M.V. Giacchi, 2010: Review article: high temperatures and health

outcomes: a review of the literature. Scandinavian Journal of Public Health,

38(8), 826-837.

Martínez-Urtaza, J., B. Huapaya, R.G. Gavilan, V. Blanco-Abad, J. Ansede-Bermejo,

C. Cadarso-Suarez, A. Figueiras, and J. Trinanes, 2008: Emergence of Asiatic

Vibrio diseases in South America in phase with El Niño. Epidemiology, 19(6),

829-837.

Martins, L.D. and M.D.F. Andrade, 2008: Ozone formation potentials of volatile

organic compounds and ozone sensitivity to their emission in the megacity of

São Paulo, Brazil. Water, Air, and Soil Pollution, 195(1-4), 201-213.

Mas-Coma, S., M.A. Valero, and M.D. Bargues, 2009: Climate change effects on

trematodiases, with emphasis on zoonotic fascioliasis and schistosomiasis.

Veterinary Parasitology, 163(4), 264-280.

Masiokas, M.H., R. Villalba, B.H. Luckman, C. Le Quesne, and J.C. Aravena, 2006:

Snowpack variations in the central Andes of Argentina and Chile, 1951-2005:

large-scale atmospheric influences and implications for water resources in the

region. Journal of Climate, 19(24), 6334-6352.

Masiokas, M.H., R. Villalba, B.H. Luckman, M.E. Lascano, S. Delgado, and P. Stepanek,

2008: 20

-century glacier recession and regional hydroclimatic changes in

northwestern Patagonia. Global and Planetary Change, 60(1-2), 85-100.

Masiokas, M.H., A. Rivera, L.E. Espizua, R. Villalba, S. Delgado, and J.C. Aravena,

2009: Glacier fluctuations in extratropical South America during the past 1000

years. Palaeogeography, Palaeoclimatology, Palaeoecology, 281(3-4), 242-268.

Maurer, E., J. Adam, and A. Wood, 2009: Climate model based consensus on the

hydrologic impacts of climate change to the Rio Lempa basin of Central

America. Hydrology and Earth System Sciences, 13(2), 183-194.

McDowell, J.Z. and J.J. Hess, 2012: Accessing adaptation: multiple stressors on

livelihoods in the Bolivian highlands under a changing climate. Global

Environmental Change: Human and Policy Dimensions, 22(2), 342-352.

McGranahan, G., D. Balk, and B. Anderson, 2007: The rising tide: assessing the risks

of climate change and human settlements in low elevation coastal zones.

Environment and Urbanization, 19(1), 17-37.

McGray, H., A. Hammill, and R. Bradley, 2007: Weathering the Storm Options for

Framing Adaptation and Development. WRI Report, World Resources Institute

(WRI), Washington, DC, USA, 57 pp.

McLeod, E., R. Salm, A. Green, and J. Almany, 2009: Designing marine protected area

networks to address the impacts of climate change. Frontiers in Ecology and

the Environment, 7(7), 362-370.

McMichael, A.J., R.E. Woodruff, and S. Hales, 2006: Climate change and human

health: present and future risks. Lancet, 367(9513), 859-869.

McPhee, J., E. Rubio-Alvarez, R. Meza, A. Ayala, X. Vargas, and S. Vicuña, 2010: An

approach to estimating hydropower impacts of climate change from a regional

perspective. In: Watershed Management 2010: Innovations in Watershed

Management under Land Use and Climate Change [Potter, K.W. and D.K. Frevert

(eds.)]. Proceedings of the Watershed Management Conference 2010, Madison,

Wisconsin, 23-27 August, 2010, American Society of Civil Engineers (ASCE),

Reston, VA, USA, pp. 13-24.

McSweeney, K. and O.T. Coomes, 2011: Climate-related disaster opens a window

of opportunity for rural poor in northeastern Honduras. Proceedings of the

National Academy of Sciences of the United States of America, 108(13), 5203-

5208.

Medema, W., B.S. McIntosh, and P.J. Jeffrey, 2008: From premise to practice: a

critical assessment of integrated water resources management and adaptive

management approaches in the water sector. Ecology and Society, 13(2), 29,

www.ecologyandsociety.org/vol13/iss2/art29/.

Melo, O., X. Vargas, S. Vicuña, F. Meza, and J. McPhee, 2010: Climate change economic

impacts on supply of water for the M & I Sector in the Metropolitan Region of

Chile. In: Watershed Management 2010: Innovations in Watershed

Management under Land Use and Climate Change [Potter, K.W. and D.K. Frevert

(eds.)]. Proceedings of the Watershed Management Conference 2010, Madison,

Wisconsin, 23-27 August, 2010, American Society of Civil Engineers (ASCE),

Reston, VA, USA, pp. 159-170.

Mena, N., A. Troyo, R. Bonilla-Carrión, and Ó. Calderón-Arguedas, 2011: Factores

asociados con la incidencia de dengue en Costa Rica [Factors associated with

incidence of dengue in Costa Rica]. Revista Panamericana de Salud Pública/Pan

American Journal of Public Health, 29(4), 234-242 (in Spanish).

Mendes, D. and J.A. Marengo, 2010: Temporal downscaling: a comparison between

artificial neural network and autocorrelation techniques over the Amazon Basin

in present and future climate change scenarios. Theoretical and Applied

Climatology, 100(3-4), 413-421.

Menendez, C.G. and A.F. Carril, 2010: Potential changes in extremes and links with

the Southern Annular Mode as simulated by a multi-model ensemble. Climatic

Change, 98(3-4), 359-377.

Mercer, K.L., H.R. Perales, and J.D. Wainwright, 2012: Climate change and the

transgenic adaptation strategy: smallholder livelihoods, climate justice, and

maize landraces in Mexico. Global Environmental Change, 22(2), 495-504.

Meza, F.J. and D. Silva, 2009: Dynamic adaptation of maize and wheat production to

climate change. Climatic Change, 94(1-2), 143-156.

Meza, F.J., D. Silva, and H. Vigil, 2008: Climate change impacts on irrigated maize in

Mediterranean climates: evaluation of double cropping as an emerging

adaptation alternative. Agricultural Systems, 98(1), 21-30.

Meza, F.J., D.S. Wilks, L. Gurovich, and N. Bambach, 2012: Impacts of climate change

on irrigated agriculture in the Maipo Basin, Chile: reliability of water rights and

changes in the demand for irrigation. Journal of Water Resources Planning and

Management, 138(5), 421-430.

Milne, S. and E. Niesten, 2009: Direct payments for biodiversity conservation in

developing countries: practical insights for design and implementation. Oryx,

43(4), 530-541.

Minvielle, M. and R.D. Garreaud, 2011: Projecting rainfall changes over the South

American Altiplano. Journal of Climate, 24(17), 4577-4583.

Miteva, D.A., S.K. Pattanayak, and P.J. Ferraro, 2012: Evaluation of biodiversity policy

instruments: what works and what doesn’t? Oxford Review of Economic Policy,

28(1), 69-92.

Mitra, A.K. and G. Rodriguez-Fernandez, 2010: Latin America and the Caribbean:

assessment of the advances in public health for the achievement of the

millennium development goals. International Journal of Environmental Research

and Public Health, 7(5), 2238-2255.

Mittermeier, R.A., P. Robles Gil, and C.G. Mittermeier (eds.), 1997: Megadiversity:

Earth’s Biologically Wealthiest Nations. CEMEX Conservation Book Series 5,

Monterrey, Mexico, 501 pp.

Mittermeier, R.A., P.R. Gil, M. Hoffmann, J. Pilgrim, T. Brooks, C.G. Mittermeier, J.

Lamoreux, and G.A.B. Fonseca, 2005: Hotspots Revisited: Earth’s Biologically

Richest and Most Endangered Terrestrial Ecoregions. 2

ed., Conservation

International, Arlington, VA, USA, 392 pp.

1559

Central and South America Chapter 27

Moncayo, Á. and A.C. Silveira, 2009: Current epidemiological trends for Chagas

disease in Latin America and future challenges in epidemiology, surveillance

and health policy. Memórias do Instituto Oswaldo Cruz, 104(1 Suppl.), 17-30.

Montagnini, F. and C. Finney, 2011: Payments for environmental services in Latin

America as a tool for restoration and rural development. Ambio, 40(3), 285-297.

Montenegro, A. and R. Ragab, 2010: Hydrological response of a Brazilian semi-arid

catchment to different land use and climate change scenarios: a modelling

study. Hydrological Processes, 24(19), 2705-2723.

Montenegro, S. and R. Ragab, 2012: Impact of possible climate and land use changes

in the semi arid regions: a case study from north eastern Brazil. Journal of

Hydrology, 434-435, 55-68.

Monzon, J.P., V.O. Sadras, P.A. Abbate, and O.P. Caviglia, 2007: Modelling management

strategies for wheat-soybean double crops in the south-eastern Pampas. Field

Crops Research, 101(1), 44-52.

Moore, N., E. Arima, R. Walker, and R. Ramos da Silva, 2007: Uncertainty and the

changing hydroclimatology of the Amazon. Geophysical Research Letters,

34(14), L14707, doi:10.1029/2007GL030157.

Mora, C., 2008: A clear human footprint in the coral reefs of the Caribbean.

Proceedings of the Royal Society B, 275(1636), 767-773.

Moran, E.F., R. Adams, B. Bakoyéma, S.T. Fiorni, and B. Boucek, 2006: Human strategies

for coping with drought in Amazônia. Climatic Change, 77(3-4), 343-361.

Moreno, A.R., 2006: Climate change and human health in Latin America: drivers,

effects, and policies. Regional Environmental Change, 6(3), 157-164.

Moreno, J.E., Y. Rubio-Palis, E. Páez, E. Pérez, and V. Sánchez, 2007: Abundance, biting

behaviour and parous rate of anopheline mosquito species in relation to

malaria incidence in gold-mining areas of southern Venezuela. Medical and

Veterinary Entomology, 21(4), 339-349.

Morris, J.N., A.J. Poole, and A.G. Klein, 2006: Retreat of Tropical Glaciers in Colombia

and Venezuela from 1984 to 2004 as measured from ASTER and Landsat

Images. In: Proceedings of 63

Annual Eastern Snow Conference, 7-9 June

2006, Newark, Delaware [Hellström, R. and S. Frankenstein (eds.)]. University

of Delaware, Newark, DE, USA, pp. 181-191.

Mosquera-Machado, S. and S. Ahmad, 2006: Flood hazard assessment of Atrato

River in Colombia. Water Resources Management, 21(3), 591-609.

Müller, A., J. Schmidhuber, J. Hoogeveen, and P. Steduto, 2008: Some insights in the

effect of growing bio-energy demand on global food security and natural

resources. Water Policy, 10(1 Suppl.), 83-94.

Muggeo, V.M. and S. Hajat, 2009: Modelling the non-linear multiple-lag effects of

ambient temperature on mortality in Santiago and Palermo: a constrained

segmented distributed lag approach. Occupational and Environmental Medicine,

66(9), 584-591.

Mulligan, M., J. Rubiano, G. Hyman, D. White, J. Garcia, M. Saravia, J. Gabriel Leon,

J.J. Selvaraj, T. Guttierez, and L. Leonardo Saenz-Cruz, 2010: The Andes

basins: biophysical and developmental diversity in a climate of change. Water

International, 35(5), 472-492.

Murugaiah, C., 2011: The burden of cholera. Critical Reviews in Microbiology, 37(4),

337-348.

Nabel, P.E., M. Caretti, and R. Becerra Serial, 2008: Incidencia de aspectos naturales

y antrópicos en los anegamientos de la ciudad de Buenos Aires [Incidence of

natural and anthropic aspects in the floods of Buenos Aires City]. Revista del

Museo Argentino de Ciencias Naturales, 10(1), 37-53 (in Spanish).

Nabout, J.C., G. Oliveira, M.R. Magalhães, L.C. Terribile, and F.A. Severo de Almeida,

2011: Global climate change and the production of “pequi” fruits (Caryocar

brasiliense) in the Brazilian Cerrado. Natureza & Conservação, 9(1), 55-60.

Nadal, G.H., G. Bravo, L.O. Girardin, and S. Gortari, 2013: Can renewable energy

technologies improve the management of stressed water resources threatened

by climate change? Argentine drylands case study. Environment Development

and Sustainability, 15(4), 1079-1097.

Nakaegawa, T. and W. Vergara, 2010: First projection of climatological mean river

discharges in the Magdalena River basin, Colombia, in a changing climate

during the 21

century. Hydrological Research Letters, 4, 50-54.

Nakaegawa, T., A. Kitoh, and M. Hosaka, 2013a: Discharge of major global rivers in

the late 21

century climate projected with the high horizontal resolution MRI-

AGCMs. Hydrological Processes, 27(23), 3301-3318.

Nakaegawa, T., A. Kitoh, H. Murakami, and S. Kusunoki, 2013b: Annual maximum 5-

day rainfall total and maximum number of consecutive dry days over Central

America and the Caribbean in the late twenty-first century projected by an

atmospheric general circulation model with three different horizontal resolutions.

Theoretical Applied Climatology (in press), doi:10.1007/s00704-013-0934-9.

Narayan, N., A. Paul, S. Mulitza, and M. Schulz, 2010: Trends in coastal upwelling

intensity during the late 20

century. Ocean Science, 6(3), 815-823.

Nath, P.K. and B. Behera, 2011: A critical review of impact of and adaptation to climate

change in developed and developing economies. Environment, Development

and Sustainability, 13(1), 141-162.

Nellemann, C., M. MacDevette, T. Manders, B. Eickhout, B. Svihus, A.G. Prins, and B.P.

Kaltenborn (eds.), 2009: The Environmental Food Crisis – The Environment’s

Role in Averting Future Food Crises. A UNEP rapid response assessment, United

Nations Environment Programme (UNEP), Global Resource Information Database

(GRID), Arendal, Norway, 101 pp.

Nelson, A. and K.M. Chomitz, 2011: Effectiveness of strict vs. multiple use protected

areas in reducing tropical forest fires: a global analysis using matching methods.

PLoS ONE, 6(8), e22722, doi:10.1371/journal.pone.0022722.

Nelson, D.R. and T.J. Finan, 2009: Praying for drought: persistent vulnerability and

the politics of patronage in Ceará, northeast Brazil. American Anthropologist,

111(3), 302-316.

Nepstad, D.C. and C.M. Stickler, 2008: Managing the tropical agriculture revolution.

Journal of Sustainable Forestry, 27(1-2), 43-56.

Nepstad, D.C., C.M. Stickler, and O.T. Almeida, 2006: Globalization of the Amazon

soy and beef industries: opportunities for conservation. Conservation Biology,

20(6), 1595-1603.

Nepstad, D., B.S. Soares-Filho, F. Merry, A. Lima, P. Moutinho, J. Carter, M. Bowman, A.

Cattaneo, H. Rodrigues, S. Schwartzman, D.G. McGrath, C.M. Stickler, R. Lubowski,

P. Piris-Cabezas, S. Rivero, A. Alencar, O. Almeida, and O. Stella, 2009: The end of

deforestation in the Brazilian Amazon. Science, 326(5958), 1350-1351.

Nicholson, L., J. Marin, D. Lopez, A. Rabatel, F. Bown, and A. Rivera, 2009: Glacier

inventory of the upper Huasco valley, Norte Chico, Chile: glacier characteristics,

glacier change and comparison with central Chile. Annals of Glaciology, 50(53),

111-118.

Nobre, C.A., 2011: Global climate change modeling: the Brazilian Model of the

Global Climate System (MBSCG). In: Research to Advance the Knowledge on

Climate Change. FAPESP Research Program on Global Climate Change

(FRPGCC), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP),

São Paulo, Brazil, pp. 8-9.

Nobre, C.A. and L.d.S. Borma, 2009: ‘Tipping points’ for the Amazon forest. Current

Opinion in Environmental Sustainability, 1(1), 28-36.

Nobre, C.A., A.D. Young, P.H.N. Salvida, J.A. Marengo Orsini, A.D. Nobre, A. Ogura, O.

Thomaz, G.O. Obregon Párraga, G.C.M. da Silva, M. Valverde, A.C. Silveira, and

G.d.O. Rodrigues, 2011: Vulnerabilidades das Megacidades Brasileiras às

Mudanças Climáticas: Região Metropolitana de São Paulo, Relatório Final. Centro

de Ciência do Sistema Terrestre (CCST), Instituto Nacional de Pesquisas Espaciais

(INPE), São José dos Campos, Brazil and Núcleo de Estudos de População (NEPO),

Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil, 179 pp.

Nóbrega, M.T., W. Collischonn, C.E.M. Tucci, and A.R. Paz, 2011: Uncertainty in climate

change impacts on water resources in the Rio Grande basin, Brazil. Hydrology

and Earth System Sciences, 15(2), 585-595.

Nogueira, C., P.A. Buckup, N.A. Menezes, O.T. Oyakawa, T.P. Kasecker, M.B. Ramos Neto,

and J.M.C. da Silva, 2010: Restricted-range fishes and conservation of Brazilian

freshwaters. PLoS ONE, 5(6), e11390, doi:10.1371/journal.pone.0011390.

Nohara, D., A. Kitoh, M. Hosaka, and T. Oki, 2006: Impact of climate change on river

discharge projected by multimodel ensemble. Journal of Hydrometeorology,

7(5), 1076-1089.

Nosetto, M.D., E.G. Jobbágy, T. Tóth, and R.B. Jackson, 2008: Regional patterns and

controls of ecosystem salinization with grassland afforestation along a rainfall

gradient. Global Biogeochemical Cycles, 22(2), GB2015, doi:10.1029/

2007GB003000.

Nuñez, M.N., S.A. Solman, and M. Fernanda Cabré, 2009: Regional climate change

experiments over southern South America. II: climate change scenarios in the

late twenty-first century. Climate Dynamics, 32(7-8), 1081-1095.

Oestreicher, J.S., K. Benessaiah, M.C. Ruiz-Jaen, S. Sloan, K. Turner, J. Pelletier, B.

Guay, K.E. Clark, D.G. Roche, M. Meiners, and C. Potvin, 2009: Avoiding

deforestation in Panamanian protected areas: an analysis of protection

effectiveness and implications for reducing emissions from deforestation and

forest degradation. Global Environmental Change, 19(2), 279-291.

Oft, P., 2010: Micro-Finance Instruments Can Contribute to Build Resilience: A Case

Study of Coping and Adaptation Strategies to Climate-Related Shocks in Piura,

Peru. Graduate Research Series: PhD Dissertation, Publication Series of UNU-

EHS Vol. 2, United Nations University Institute for Environment and Human

Security (UNU-EHS), Bonn, Germany, 157 pp.

1560

Chapter 27 Central and South America

Oliveira, P.J.C., G.P. Asner, D.E. Knapp, A. Almeyda, R. Galvan-Gildemeister, S. Keene,

R.F. Raybin, and R.C. Smith, 2007: Land-use allocation protects the Peruvian

Amazon. Science, 317(5842), 1233-1236.

Olmo, N.R.S., P.H.N. Saldiva, A.L.F. Braga, C.A. Lin, U.P. Santos, and L.A.A. Pereirai,

2011: A review of low-level air pollution and adverse effects on human health:

implications for epidemiological studies and public policy. Clinics, 66(4), 681-

690.

Olson, S.H., R. Gangnon, E. Elguero, L. Durieux, J.-F. Guégan, J.A. Foley, and J.A. Patz,

2009: Links between climate, malaria, and wetlands in the Amazon basin.

Emerging Infectious Diseases, 15(4), 659-662.

Oltremari, J.V. and R.G. Jackson, 2006: Conflicts, perceptions, and expectations of

indigenous communities associated with natural areas in Chile. Natural Areas

Journal, 26(2), 215-220.

Osorio, L., J. Todd, R. Pearce, and D.J. Bradley, 2007: The role of imported cases in the

epidemiology of urban Plasmodium falciparum malaria in Quibdó, Colombia.

Tropical Medicine and International Health, 12(3), 331-341.

Ospina Noreña, J.E., C. Gay García, A.C. Conde, V.O. Magaña Rueda, and G. Sánchez

Torres Esqueda, 2009a: Vulnerability of water resources in the face of potential

climate change: generation of hydroelectric power in Colombia. Atmósfera,

22(3), 229-252.

Ospina Noreña, J.E., C. Gay García, A.C. Conde, and G. Sánchez Torres Esqueda,

2009b: Analysis of the water supply-demand relationship in the Sinú-Caribe

Basin, Colombia, under different climate change scenarios. Atmósfera, 22(4),

399-412.

Ospina Noreña, J.E., C. Gay García, A.C. Conde, and G. Sánchez Torres Esqueda,

2011a: Water availability as a limiting factor and optimization of hydropower

generation as an adaptation strategy to climate change in the Sinú-Caribe River

basin. Atmósfera, 24(2), 203-220.

Ospina Noreña, J.E., C. Gay García, A.C. Conde, and G. Sánchez Torres Esqueda,

2011b: A proposal for a vulnerability index for hydroelectricity generation in

the face of potential climate change in Colombia. Atmósfera, 24(3), 329-346.

Palmer, M.A., C.A. Reidy Liermann, C. Nilsson, M. Flörke, J. Alcamo, P.S. Lake, and N.

Bond, 2008: Climate change and the world’s river basins: anticipating

management options. Frontiers in Ecology and the Environment, 6(2), 81-89.

Pasquini, A.I. and P.J. Depetris, 2007: Discharge trends and flow dynamics of South

American rivers draining the southern Atlantic seaboard: an overview. Journal

of Hydrology, 333(2-4), 385-399.

Pasquini, A.I., K.L. Lecomte, E.L. Piovano, and P.J. Depetris, 2006: Recent rainfall and

runoff variability in central Argentina. Quaternary International, 158(1), 127-139.

Pasquini, A.I., K.L. Lecomte, and P.J. Depetris, 2008: Climate change and recent water

level variability in Patagonian proglacial lakes, Argentina. Global and Planetary

Change, 63(4), 290-298.

Pasquini, A.I., K.L. Lecomte, and P.J. Depetris, 2013: The Manso Glacier drainage

system in the northern Patagonian Andes: an overview of its main hydrological

characteristics. Hydrological Processes, 27(2), 217-224.

Payne, L. and J.R. Fitchett, 2010: Bringing neglected tropical diseases into the

spotlight. Trends in Parasitology, 26(9), 421-423.

Pellicciotti, F., P. Burlando, and K. van Vliet, 2007: Recent trends in precipitation and

streamflow in the Aconcagua River basin, central Chile. In: Glacier Mass

Balance Changes and Meltwater Discharge [Ginot, P. and J.-E. Sicart (eds.)].

Selected Papers from sessions at the IAHS Assembly in Foz do Iguaçu, Brazil,

2005, IAHS Publication 318, International Association of Hydrological Sciences

(IAHS) Press, Wallingford, UK, pp. 17-38.

Penalba, O.C. and J.A. Rivera, 2013: Future changes in drought characteristics over

southern South America projected by a CMIP5 multi-model ensemble. American

Journal of Climate Change, 2(3), 173-182.

Penalba, O.C. and F.A. Robledo, 2010: Spatial and temporal variability of the

frequency of extreme daily rainfall regime in the La Plata Basin during the 20

century. Climatic Change, 98(3-4), 531-550.

Peraza, S., C. Wesseling, A. Aragon, R. Leiva, R.A. García-Trabanino, C. Torres, K.

Jakobsson, C.G. Elinder, and C. Hogstedt, 2012: Decreased kidney function

among agricultural workers in El Salvador. American Journal of Kidney Diseases,

59(4), 531-540.

Perazzoli, M., A. Pinheiro, and V. Kaufmann, 2013: Assessing the impact of climate

change scenarios on water resources in southern Brazil. Hydrological Sciences

Journal, 58(1), 77-87.

Pereira, L.F.M., S. Barreto, and J. Pittock, 2009: Participatory river basin management

in the São João River, Brazil: a basis for climate change adaptation? Climate

and Development, 1(3), 261-268.

Perera, F.P., 2008: Children are likely to suffer most from our fossil fuel addiction.

Environmental Health Perspectives, 116(8), 987-990.

Pérez, C., C. Nicklin, O. Dangles, S. Vanek, S. Sherwood, S. Halloy, K. Garrett, and G.

Forbes, 2010: Climate change in the high Andes: implications and adaptation

strategies for small-scale farmers. The International Journal of Environmental,

Cultural, Economic and Social Sustainability, 6(5), 71-88.

Peterson, M.J., D.M. Hall, A.M. Feldpausch-Parker, and T.R. Peterson, 2010: Obscuring

ecosystem function with application of the ecosystem services concept.

Conservation Biology, 24(1), 113-119.

Pettengell, C., 2010: Adaptación al Cambio Climático: Capacitar a las Personas que

Viven en la Pobreza para que Puedan Adaptarse. Informe de Investigación de

Oxfam, Oxfam Internacional, Oxford, UK, 56 pp. (in Spanish).

Pielke Jr., R.A., J. Rubiera, C. Landsea, M.L. Fernández, and R. Klein, 2003: Hurricane

vulnerability in Latin America and the Caribbean: normalized damage and loss

potentials. Natural Hazards Review, 4(3), 101-114.

Pinault, L.L. and F.F. Hunter, 2011: New highland distribution records of multiple

Anopheles species in the Ecuadorian Andes. Malaria Journal, 10, 236,

doi:10.1186/1475-2875-10-236.

Pinto, H.S., E.D. Assad, J. Zullo Jr., S.R.M. Evangelista, A.F. Otavian, A.M.H. de Ávila, B.A.

Evangelista, F.R. Marin, C. Macedo Jr., G.Q. Pellegrino, P.P. Coltri, and G. Coral, 2008:

Aquecimento Global e a Nova Geografia da Produção Agrícola no Brasil. Empresa

Brasileira de Pesquisa Agropecuária (EMBRAPA) and Universidade Estadual de

Campinas (UNICAMP), EMBRAPA, São Paulo, Brazil, 83 pp. (in Portuguese).

Pittock, J., 2011: National climate change policies and sustainable water management:

conflicts and synergies. Ecology and Society, 16(2), 25, www.ecologyand

society.org/vol16/iss2/art25/.

Pizarro, R., F. Balocchi, M. Vera, A. Aguilera, C. Morales, R. Valdés, C. Sangüesa, C.

Vallejos, R. Fuentes, A. Abarza, and C. Olivares, 2013: Influencia del cambio

climático en el comportamiento de los caudales máximos en la zona Mediterránea

de Chile. Tecnología y Ciencias del Agua, 4(2), 5-19 (in Spanish).

Plaza, G. and M. Pasculi, 2007: Estrategias de adaptación al cambio climático: caso

de estudio de la localidad de Aguaray Salta [Adaptation strategies to climate

change: case study of the town of Salta Aguaray]. Avances en Energías

Renovables y Medio Ambiente, 11, 129-136 (in Spanish).

PNCC, 2007: Vulnerabilidad y Adaptación al Cambio Climático en Bolivia: Resultados

de un Proceso de Investigación Participativa en las Regiones del Lago Titicaca y

los Valles Cruceños. PNUD BOL/39564, Programa de las Naciones Unidas para el

Desarrollo (PNUD) [United Nations Development Programme (UNDP)] and

República de Bolivia, Viceministro de Planificación Territorial y Ambiental, Programa

Nacional de Cambios Climáticos (PNCC), La Paz, Bolivia, 141 pp. (in Spanish).

Podestá, G., F. Bert, B. Rajagopalan, S. Apipattanavis, C. Laciana, E. Weber, W.

Easterling, R. Katz, D. Letson, and A. Menendez, 2009: Decadal climate variability

in the Argentine Pampas: regional impacts of plausible climate scenarios on

agricultural systems. Climate Research, 40(2-3), 199-210.

Polidoro, B.A., K.E. Carpenter, L. Collins, N.C. Duke, A.M. Ellison, J.C. Ellison, E.J.

Farnsworth, E.S. Fernando, K. Kathiresan, N.E. Koedam, S.R. Livingstone, T.

Miyagi, G.E. Moore, V.N. Nam, J.E. Ong, J.H. Primavera, S.G. Salmo III, J.C.

Sanciangco, S. Sukardjo, Y. Wang, and J.W.H. Yong, 2010: The loss of species:

mangrove extinction risk and geographic areas of global concern. PLoS ONE,

5(4), e10095, doi:10.1371/journal.pone.0010095.

Polissar, P.J., M.B. Abbott, A.P. Wolfe, M. Bezada, V. Rull, and R.S. Bradley, 2006: Solar

modulation of Little Ice Age climate in the tropical Andes. Proceedings of the

National Academy of Sciences of the United States of America, 103(24), 8937-

8942.

Porter-Bolland, L., E.A. Ellis, M.R. Guariguata, I. Ruiz-Mallén, S. Negrete-Yankelevich,

and V. Reyes-García, 2012: Community managed forests and forest protected

areas: an assessment of their conservation effectiveness across the tropics.

Forest Ecology and Management, 268, 6-17.

Poveda, G. and K. Pineda, 2009: Reassessment of Colombia’s tropical glaciers retreat

rates: are they bound to disappear during the 2010-2020 decade? Advances

in Geosciences, 22, 107-116.

Poveda, G., Ó.A. Estrada-Restrepo, J.E. Morales, Ó.O. Hernández, A. Galeano, and S.

Osorio, 2011: Integrating knowledge and management regarding the climate-

malaria linkages in Colombia. Current Opinion in Environmental Sustainability,

3(6), 449-460.

Programa Estado de la Nación-Región, 2011: Cuarto Informe Estado de la Región

en Desarrollo Humano Sostenible. Un informe desde Centroamérica y para

Centroamérica, Programa Estado de la Nación – Región, Pavas, Costa Rica, 550

pp., www.estadonacion.or.cr/estado-de-la-region/region-informe-actual2011.

1561

Central and South America Chapter 27

Przeslawski, R., S. Ahyong, M. Byrne, G. Woerheide, and P. Hutchings, 2008: Beyond

corals and fish: the effects of climate change on noncoral benthic invertebrates

of tropical reefs. Global Change Biology, 14(12), 2773-2795.

Quintana, J.M. and P. Aceituno, 2012: Changes in the rainfall regime along the

extratropical west coast of South America (Chile): 30-43°S. Atmósfera, 25(1),

1-12.

Quiroga, A. and C. Gaggioli, 2011: Gestión del agua y viabilidad de los sistemas

productivos. In: Condiciones para el Desarrollo de Producciones Agrícola–

Ganaderas en el SO Bonaerense. Academia Nacional de Agronomía y Veterinaria

de la República Argentina, Tomo LXIV, 12 de Noviembre de 2010, Buenos Aires,

Argentina, pp. 233-249 (in Spanish).

Rabatel, A., A. Machaca, B. Francou, and V. Jomelli, 2006: Glacier recession on Cerro

Charquini (16°S), Bolivia, since the maximum of the Little Ice Age (17

century).

Journal of Glaciology, 52(176), 110-118.

Rabatel, A., B. Francou, V. Jomelli, P. Naveau, and D. Grancher, 2008: A chronology of

the Little Ice Age in the tropical Andes of Bolivia (16°S) and its implications for

climate reconstruction. Quaternary Research, 70(2), 198-212.

Rabatel, A., H. Castebrunet, V. Favier, L. Nicholson, and C. Kinnard, 2011: Glacier

changes in the Pascua-Lama region, Chilean Andes (29°S): recent mass balance

and 50 yr surface area variations. The Cryosphere, 5(4), 1029-1041.

Rabatel, A., B. Francou, A. Soruco, J. Gomez, B. Cáceres, J.L. Ceballos, R. Basantes, M.

Vuille, J.-E. Sicart, C. Huggel, M. Scheel, Y. Lejeune, Y. Arnaud, M. Collet, T. Condom,

G. Consoli, V. Favier, V. Jomelli, R. Galarraga, P. Ginot, L. Maisincho, J. Mendoza,

M. Ménégoz, E. Ramirez, P. Ribstein, W. Suarez, M. Villacis, and P. Wagnon, 2013:

Current state of glaciers in the tropical Andes: a multi-century perspective on

glacier evolution and climate change. The Cryosphere Discussions, 7, 81-102.

Racoviteanu, A.E., W.F. Manley, Y. Arnaud, and M.W. Williams, 2007: Evaluating

digital elevation models for glaciologic applications: an example from Nevado

Coropuna, Peruvian Andes. Global and Planetary Change, 59(1-4), 110-125.

Radachowsky, J., V.H. Ramos, R. McNab, E.H. Baur, and N. Kazakov, 2012: Forest

concessions in the Maya Biosphere Reserve, Guatemala: a decade later. Forest

Ecology and Management, 268, 18-28.

Ramankutty, N., H.K. Gibbs, F. Achard, R. Defriess, J.A. Foley, and R.A. Houghton,

2007: Challenges to estimating carbon emissions from tropical deforestation.

Global Change Biology, 13(1), 51-66.

Ramirez-Villegas, J., M. Salazar, A. Jarvis, and C.E. Navarro-Racines, 2012: A way

forward on adaptation to climate change in Colombian agriculture: perspectives

towards 2050. Climatic Change, 115(3-4), 611-628.

Rammig, A., T. Jupp, K. Thonicke, B. Tietjen, J. Heinke, S. Ostberg, W. Lucht, W. Cramer,

and P. Cox, 2010: Estimating the risk of Amazonian forest dieback. New

Phytologist, 187(3), 694-706.

Raup, B., A. Racoviteanu, S.J.S. Khalsa, C. Helm, R. Armstrong, and Y. Arnaud, 2007:

The GLIMS geospatial glacier database: a new tool for studying glacier change.

Global and Planetary Change, 56(1-2), 101-110.

Ravera, F., D. Tarrason, and E. Simelton, 2011: Envisioning adaptive strategies to

change: participatory scenarios for agropastoral semiarid systems in Nicaragua.

Ecology and Society, 16(1), 20, www.ecologyandsociety.org/vol16/iss1/art20/.

Re, M. and V.R. Barros, 2009: Extreme rainfalls in SE South America. Climatic Change,

96(1-2), 119-136.

Ready, P.D., 2008: Leishmaniasis emergence and climate change. OIE Revue

Scientifique et Technique, 27(2), 399-412.

Rebaudo, F., V. Crespo-Pérez, J. Silvain, and O. Dangles, 2011: Agent-based modeling

of human-induced spread of invasive species in agricultural landscapes: insights

from the potato moth in Ecuador. Journal of Artificial Societies and Social

Simulation, 14(3), 7, http://jasss.soc.surrey.ac.uk/14/3/7.html.

República Argentina, 2007: 2da Comunicación Nacional de la República Argentina

a la Convención Marco de las Naciones Unidas sobre Cambio Climático.

República Argentina, Buenos Aires, Argentina, 199 pp. (in Spanish).

Restrepo, C. and N. Alvarez, 2006: Landslides and their contribution to land-cover

change in the mountains of Mexico and Central America. Biotropica, 38(4),

446-457.

Restrepo-Pineda, E., E. Arango, A. Maestre, V.E.D. Rosário, and P. Cravo, 2008: Studies

on antimalarial drug susceptibility in Colombia, in relation to Pfmdr1 and Pfcrt.

Parasitology, 135(5), 547-553.

Reuveny, R., 2007: Climate change-induced migration and violent conflict. Political

Geography, 26(6), 656-673.

Rivarola Sosa, J.M., G. Brandani, C. Dibari, M. Moriondo, R. Ferrise, G. Trombi, and

M. Bindi, 2011: Climate change impact on the hydrological balance of the Itaipu

basin. Meteorological Applications, 18(2), 163-170.

Rivera, J.A., O.C. Penalba, and M.L. Betolli, 2013: Inter-annual and inter-decadal

variability of dry days in Argentina. International Journal of Climatology, 33(4),

834-842.

Roberts, N., 2009: Culture and landslide risk in the Central Andes of Bolivia and

Peru. Studia Universitatis Babeş-Bolyai, Geologia, 54(1), 55-59.

Rodrigues, R.R., S. Gandolfi, A.G. Nave, J. Aronson, T.E. Barreto, C.Y. Vidal, and P.H.S.

Brancalion, 2011: Large-scale ecological restoration of high-diversity tropical

forests in SE Brazil. Forest Ecology and Management, 261(10), 1605-1613.

Rodrigues Capítulo, A., N. Gómez, A. Giorgi, and C. Feijoó, 2010: Global changes in

Pampean lowland streams (Argentina): implications for biodiversity and

functioning. Hydrobiologia, 657(1), 53-70.

Rodriguez, A., M. Vaca, G. Oviedo, S. Erazo, M.E. Chico, C. Teles, M.L. Barreto, L.C.

Rodrigues, and P.J. Cooper, 2011: Urbanisation is associated with prevalence

of childhood asthma in diverse, small rural communities in Ecuador. Thorax,

66(12), 1043-1050.

Rodriguez, D.A., J. Tomasella, and C. Linhares, 2010: Is the forest conversion to

pasture affecting the hydrological response of Amazonian catchments? Signals

in the Ji-Paraná Basin. Hydrological Processes, 24(10), 1254-1269.

Rodríguez, J.P., F. Rojas-Suárez, and D. Hernández (eds.), 2010: Libro Rojo de los

Ecosistemas Terrestres de Venezuela. Provita Caracas (Venezuela), Shell Venezuela,

and Lenovo (Venezuela), Provita, Caracas, Venezuela, 324 pp. (in Spanish).

Rodríguez Laredo, D.M., 2011: La gestión del verde urbano como un criterio de

mitigación y adaptación al cambio climatico. Revista de la Asociación Argentina

de Ecología de Paisajes, 2(2), 123-130 (in Spanish).

Rodríguez-Morales, A.J., 2011: Cambio climático, precipitaciones, sociedad y

desastres en América Latina: relaciones y necesidades [Climate change, rainfall,

society and disasters in Latin America: relations and needs]. Revista Peruana

de Medicina Experimental y Salud Pública, 28(1), 165-166.

Rodríguez-Morales, A. and A. Herrera-Martinez, 2009: Potential influence of climate

variability on dengue incidence in a western pediatric hospital of Venezuela,

2001-2008. Tropical Medicine & International Health, 14(2 Suppl.), 164-165.

Rodríguez-Morales, A.J., L. Delgado, N. Martinez, and C. Franco-Paredes, 2006:

Impact of imported malaria on the burden of disease in northeastern Venezuela.

Journal of Travel Medicine, 13(1), 15-20.

Rodríguez-Morales, A.J., L. Rada, J. Benitez, and C. Franco-Paredes, 2007: Impact

of climate variability on cutaneous leishmaniasis in Venezuela. American

Journal of Tropical Medicine and Hygiene, 77(5), 228-229.

Rodríguez-Morales, A.J., A. Risquez, and L. Echezuria, 2010: Impact of climate

change on health and disease in Latin America. In: Climate Change and

Variability [Simard, S. (ed.)]. Sciyo, Rijeka, Croatia, pp. 464-486.

Rodríguez-Pérez, M.A., T.R. Unnasch, and O. Real-Najarro, 2011: Chapter 4:

Assessment and monitoring of Onchocerciasis in Latin America. In: Advances

in Parasitology, Vol. 77 [Rollinson, D. and S.I. Hay (eds.)]. Elsevier Science and

Technology/Academic Press, Waltham, MA, USA, pp. 175-226.

Roebeling, P.C. and E.M.T. Hendrix, 2010: Land speculation and interest rate

subsidies as a cause of deforestation: the role of cattle ranching in Costa Rica.

Land Use Policy, 27(2), 489-496.

Romero, G.A.S. and M. Boelaert, 2010: Control of visceral leishmaniasis in Latin

America – a systematic review. PLoS Neglected Tropical Diseases, 4(1), e584,

doi:10.1371/journal.pntd.0000584.

Romero-Lankao, P., 2007a: Are we missing the point? Particularities of urbanization,

sustainability and carbon emissions in Latin American cities. Environment and

Urbanization, 19(1), 159-175.

Romero-Lankao, P., 2007b: How do local governments in Mexico City manage global

warming? Local Environment, 12(5), 519-535.

Romero-Lankao, P., 2010: Water in Mexico City: what will climate change bring to

its history of water-related hazards and vulnerabilities? Environment and

Urbanization, 22(1), 157-178.

Romero-Lankao, P., 2012: Governing carbon and climate in the cities: an overview

of policy and planning challenges and options. European Planning Studies,

20(1), 7-26.

Romero-Lankao, P. and H. Qin, 2011: Conceptualizing urban vulnerability to global

climate and environmental change. Current Opinion in Environmental

Sustainability, 3(3), 142-149.

Romero-Lankao, P., H. Qin, S. Hughes, M. Haeffner, and M. Borbor-Cordova, 2012a:

Chapter 10: Urban vulnerability and adaptation to the health impacts of air

pollution and climate extremes in Latin American cities. In: Research in Urban

Sociology [Holt, W.G. (ed.)]. Volume 12, Emerald Group Publishing Ltd., Bingley,

UK, pp. 247-275.

1562

Chapter 27 Central and South America

Romero-Lankao, P., M. Borbor-Cordova, R. Abrutsky, G. Günther, E. Behrenz, and L.

Dawidowsky, 2012b: ADAPTE: a tale of diverse teams coming together to do

issue-driven interdisciplinary research. Environmental Science & Policy, 26, 29-

39.

Romero-Lankao, P., H. Qin, and K. Dickinson, 2012c: Urban vulnerability to

temperature-related hazards: a meta-analysis and meta-knowledge approach.

Global Environmental Change, 22(3), 670-683.

Romero-Lankao, P., S. Hughes, A. Rosas-Huerta, R. Borquez, and D.M. Gnatz, 2013a:

Urban institutional response capacity for climate change: an examination of

construction and pathways in Mexico City and Santiago. Environment and

Planning C: Government and Policy, 31(5), 785-805.

Romero-Lankao, P., H. Qin, and M. Borbor-Cordova, 2013b: Exploration of health

risks related to air pollution and temperature in three Latin American cities

Social Sciences and Medicine, 83, 110-118.

Roncoli, C., 2006: Ethnographic and participatory approaches to research on farmers’

responses to climate predictions. Climate Research, 33(1), 81-99.

Rotureau, B., P. Couppié, M. Nacher, J.-P. Dedet, and B. Carme, 2007: Les leishmanioses

cutanées en Guyane française [Cutaneous leishmaniases in French Guiana].

Bulletin de la Societe de Pathologie Exotique, 100(4), 251-260 (in French).

Ruane, A.C., L.D. Cecil, R.M. Horton, R. Gordón, R. McCollum, D. Brown, B. Killough,

R. Goldberg, A.P. Greeley, and C. Rosenzweig, 2013: Climate change impact

uncertainties for maize in Panama: farm information, climate projections, and

yield sensitivities. Agricultural and Forest Meteorology, 170, 132-145.

Rubin, O. and T. Rossing, 2012: National and local vulnerability to climate-related

disasters in Latin America: the role of social asset-based adaptation. Bulletin

of Latin American Research, 31(1), 19-35.

Rubio-Álvarez, E. and J. McPhee, 2010: Patterns of spatial and temporal variability

in streamflow records in south central Chile in the period 1952-2003. Water

Resources Research, 46(5), W05514, doi:10.1029/2009WR007982.

Ruiz, D., H.A. Moreno, M.E. Gutiérrez, and P.A. Zapata, 2008: Changing climate and

endangered high mountain ecosystems in Colombia. Science of the Total

Environment, 398(1-3), 122-132.

Rusticucci, M., 2012: Observed and simulated variability of extreme temperature

events over South America. Atmospheric Research, 106, 1-17.

Rusticucci, M. and M. Renom, 2008: Variability and trends in indices of quality-

controlled daily temperature extremes in Uruguay. International Journal of

Climatology, 28(8), 1083-1095.

Rusticucci, M. and B. Tencer, 2008: Observed changes in return values of annual

temperature extremes over Argentina. Journal of Climate, 21(21), 5455-5467.

Salazar, L.F., C.A. Nobre, and M.D. Oyama, 2007: Climate change consequences on

the biome distribution in tropical South America. Geophysical Research Letters,

34(9), L09708, doi:10.1029/2007GL029695.

Salazar-Lindo, E., C. Seas, and D. Gutierrez, 2008: ENSO and cholera in South America:

what can we learn about it from the 1991 cholera outbreak? International Journal

of Environment and Health, 2(1), 30-36.

Saldaña-Zorrilla, S.O., 2008: Stakeholders’ views in reducing rural vulnerability to

natural disasters in southern Mexico: hazard exposure and coping and adaptive

capacity. Global Environmental Change, 18(4), 583-597.

Salinas, H., J. Almenara, Á. Reyes, P. Silva, M. Erazo, and M.J. Abellán, 2006: Estudio

de variables asociadas al cáncer de piel en Chile mediante análisis de

componentes principales [Study of variables associated with skin cancer in

Chile using principal component analysis]. Actas Dermo-Sifiliográficas, 97(4),

241-246 (in Spanish).

Salomón, O.D., Y. Basmajdian, M.S. Fernández, and M.S. Santini, 2011: Lutzomyia

longipalpis in Uruguay: the first report and the potential of visceral leishmaniasis

transmission. Memórias do Instituto Oswaldo Cruz, 106(3), 381-382.

Salzmann, N., C. Huggel, P. Calanca, A. Dí az, T. Jonas, C. Jurt, T. Konzelmann, P. Lagos,

M. Rohrer, W. Silverio, and M. Zappa, 2009: Integrated assessment and

adaptation to climate change impacts in the Peruvian Andes. Advances in

Geosciences, 22, 35-39.

Salzmann, N., C. Huggel, M. Rohrer, W. Silverio, B.G. Mark, P. Burns, and C. Portocarrero,

2013: Glacier changes and climate trends derived from multiple sources in the

data scarce Cordillera Vilcanota region, southern Peruvian Andes. Cryosphere,

7(1), 103-118.

Samaniego, J., 2009: Cambio Climático y Desarrollo en América Latina y el Caribe:

Una Reseña. LC/W.232, Economic Commission for Latin America and the

Caribbean (ECLAC)/Comisión Económica para América Latina (CEPAL) and the

German Agency for Technical Cooperation (GTZ), ECLAC/CEPAL, Santiago de

Chile, Chile, 148 pp.

Sampaio, G., C. Nobre, M.H. Costa, P. Satyamurty, B.S. Soares-Filho, and M. Cardoso,

2007: Regional climate change over eastern Amazonia caused by pasture and

soybean cropland expansion. Geophysical Research Letters, 34(17), L17709,

doi:10.1029/2007GL030612.

Sankarasubramanian, A., U. Lall, F.A. Souza Filho, and A. Sharma, 2009: Improved

water allocation utilizing probabilistic climate forecasts: short-term water

contracts in a risk management framework. Water Resources Research, 45(11),

W11409, doi:10.1029/2009WR007821.

Sansigolo, C.A. and M.T. Kayano, 2010: Trends of seasonal maximum and minimum

temperatures and precipitation in southern Brazil for the 1913-2006 period.

Theoretical and Applied Climatology, 101(1-2), 209-216.

Sathaye, J., O. Lucon, A. Rahman, J. Christensen, F. Denton, J. Fujino, G. Heath, M.

Mirza, H. Rudnick, A. Schlaepfer, and A. Shmakin, 2011: Renewable energy

in the context of sustainable development. In: IPCC Special Report on

Renewable Energy Sources and Climate change Mitigation. Special Report

of Working Group III of the Intergovernmental Panel on Climate Change

[Edenhofer, O., R. Pichs-Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S.

Kadner, T. Zwickel, P. Eickemeier, G. Hansen, S. Schlömer, and C. von Stechow

(eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA,

pp. 707-790.

Satterthwaite, D., 2011a: How urban societies can adapt to resource shortage and

climate change. Philosophical Transactions of the Royal Society A, 369(1942),

1762-1783.

Satterthwaite, D., 2011b: How can urban centers adapt to climate change with

ineffective or unrepresentative local governments? Wiley Interdisciplinary

Reviews: Climate Change, 2(5), 767-776.

Satyamurty, P., A.A. de Castro, J. Tota, L.E. da Silva Gularte, and A.O. Manzi, 2010:

Rainfall trends in the Brazilian Amazon Basin in the past eight decades.

Theoretical and Applied Climatology, 99(1-2), 139-148.

Satyamurty, P., C.P.W. da Costa, A.O. Manzi, and L.A. Candido, 2013: A quick look at

the 2012 record flood in the Amazon Basin. Geophysical Research Letters,

40(7), 1396-1401.

Saulo, C., L. Ferreira, J. Nogués-Paegle, M. Seluchi, and J. Ruiz, 2010: Land-atmosphere

interactions during a northwestern Argentina low event. Monthly Weather

Review, 138(7), 2481-2498.

Saurral, R.I., V.R. Barros, and D.P. Lettenmaier, 2008: Land use impact on the Uruguay

River discharge. Geophysical Research Letters, 35(12), L12401, doi:10.1029/

2008GL033707.

Sayago, J.M., M.M. Collantes, L.d.V. Neder, and J. Busnelli, 2010: Cambio climático y

amenazas ambientales en el Área Metropolitana de Tucumán [Climate change

and environmental hazard at the Metropolitan Area of Tucumán]. Revista de

la Asociación Geológica Argentina, 66(4), 544-554 (in Spanish).

Schlindwein, S., S. Sieber, C. Albaladejo, H. Bazzani, M. Bonatti, J.P. Boulanger, M.

Calandra, L.R. D’Agostini, J.P. Delfino Barbosa, J. Elverdin, A.C. Fantini, E. Gentile,

E. Guevara, V. Hernandez, P, La Nasa, M. Lana, S.R. Martins, S. Meira, M.M.

Mosciaro, F. Mouillot, E. Muzi, F.F. Riglos, A. Rolla, R. Terra, H. Urcola, and A.C.F.

Vasconcelos, 2011: CLARIS LPB WP8: Land-use change, agriculture and socio-

economic implications. CLIVAR Exchanges No. 57, 16(3), 28-31.

Schneider, C., M. Schnirch, C. Acuña, G. Casassa, and R. Kilian, 2007: Glacier

inventory of the Gran Campo Nevado Ice Cap in the Southern Andes and

glacier changes observed during recent decades. Global and Planetary Change,

59(1-4), 87-100.

Schulz, N., J.P. Boisier, and P. Aceituno, 2012: Climate change along the arid coast of

northern Chile. International Journal of Climatology, 32(12), 1803-1814.

Scott, C.A., R.G. Varady, F. Meza, E. Montaña, G.B. de Raga, B. Luckman, and C.

Martius, 2012: Science-policy dialogues for water security: addressing

vulnerability and adaptation to global change in the arid Americas. Environment,

54(3), 30-42.

Scott, C.A., F.J. Meza, R.G. Varady, H. Tiessen, J. McEvoy, G.M. Garfin, M. Wilder, L.M.

Farfan, N. Pineda Pablos, and E. Montaña, 2013: Water security and adaptive

management in the arid Americas. Annals of the Association of American

Geographers, 103(2), 280-289.

Seiler, C., R.W.A. Hutjes, and P. Kabat, 2013: Likely ranges of climate change in

Bolivia. Journal of Applied Meteorology and Climatology, 52(6), 1303-1317.

SENAMHI, 2005: Escenarios del Cambio Climático en el Perú al 2050: Cuenca del

Río Piura [Climate Change Scenarios in Peru for 2050: The Piura River Basin].

Programa de Cambio Climático y Calidad de Aire (PROCLIM) and Servicio

Nacional de Meteorología e Hidrología (SENAMHI), Lima, Peru,182 pp. (in

Spanish).

1563

Central and South America Chapter 27

SENAMHI, 2007: Escenarios de Cambio Climático en la Cuenca del Río Urubamba

para el Año 2100 [Climate Change Scenarios in the Urubamba River Basin

by 2100] [Rosas, G., G. Avalos, A. Díaz, C. Oria, L. Metzger, D. Acuña, and

R.M. San Martin (eds.)]. Parte del Proyecto Regional Andino de Adaptación

(PRAA), como línea de base del proyecto “Adaptación al Retroceso Acelerado

de Glaciares en los Andes Tropicales (Bolivia, Ecuador, Perú)”, auspiciado

por el GEF a través del Banco Mundial, y coordinado por el CONAM,

Ministerio de Ambiente (MINAM), Centro de Predicción Numérica (CPN),

Servicio Nacional de Meteorología e Hidrología (SENAMHI), Lima, Perú, 120

pp. (in Spanish).

SENAMHI, 2009a: Escenarios Climáticos en la Cuenca del Rio Mayo para el Año

2030 [Climate Scenarios in the Mayo River Basin by the Year 2030][Obregón,

G., A. Díaz, G. Rosas, G. Avalos, D. Acuña, C. Oria, A. Llacza, and R. Miguel (eds.)].

Parte del componente de Vulnerabilidad y Adaptación en el marco de la

Segunda Comunicación Nacional de Cambio Climático a la CMNUCC, financiado

por el GEF y coordinado por el Ministerio de Ambiente del Perú (MINAM),

Centro de Predicción Numérica (CPN), Servicio Nacional de Meteorología e

Hidrología (SENAMHI), Lima, Peru, 133 pp. (in Spanish).

SENAMHI, 2009b: Escenarios Climáticos en la Cuenca del Rio Santa para el Año

2030 [Climate Scenarios in the Santa River Basin by 2030]. [Obregón, G., A.

Díaz, G. Rosas, G. Avalos, D. Acuña, C. Oria, A. Llacza, and R. Miguel (eds.)].

Parte del componente de Vulnerabilidad y Adaptación en el marco de la

Segunda Comunicación Nacional de Cambio Climático a la CMNUCC, financiado

por el GEF y coordinado por el Ministerio de Ambiente del Perú (MINAM),

Centro de Predicción Numérica (CPN), Servicio Nacional de Meteorología e

Hidrología (SENAMHI), Lima, Peru, 139 pp. (in Spanish).

SENAMHI, 2009c: Escenarios de Cambio Climático en la Cuenca del Río Mantaro

para 2100: Resumen Técnico [Climate Change Scenarios in the Mantaro river

Basin by 2100: Technical Summary][Avalos, G., A. Díaz, C. Oria, L. Metzger, and

D. Acuña (eds.)]. Parte de la fase de preparación del Proyecto de Adaptación al

Impacto del Retroceso Acelerado de Glaciares en los Andes Tropicales (PRAA),

el cual es implementado en Bolivia, Ecuador y Perú con financiamiento del Fondo

Mundial del Medio Ambiente (GEF) a través del Banco Mundial, coordinado

por la Secretaría General de la Comunidad Andina e implementado en el Perú

por el Ministerio del Ambiente (MINAM), Centro de Predicción Numérica (CPN),

Servicio Nacional de Meteorología e Hidrología (SENAMHI), Lima, Peru, 56 pp.

(in Spanish).

SENAMHI, 2009d: Climate Scenarios for Peru to 2030 [Obregón, G., A. Díaz, G. Rosas,

G. Avalos, D. Acuña, C. Oria, A. Llacza, and R. Miguel (eds.)]. Part of the

Vulnerability and Adaptation Component within the framework of the Second

National Communication on Climate Change to the UNFCCC, financed by the

GEF and Coordinated by the Ministry of Environment of Peru (MINAM),

National Meteorology and Hydrology Service (SENAMHI), Numerical Prediction

Center (CPN), Lima, Peru, 134 pp.

Seneviratne, S.I., N. Nicholls, D. Easterling, C.M. Goodess, S. Kanae, J. Kossin, Y. Luo,

J.A. Marengo, K. McInnes, M. Rahimi, M. Reichstein, A. Sorteberg, C. Vera, and

X. Zhang, 2012: Changes in climate extremes and their impacts on the natural

physical environment. In: Managing the Risks of Extreme Events and Disasters

to Advance Climate Change Adaptation. A Special Report of Working Groups I

and II of the Intergovernmental Panel on Climate Change [Field, C.B., V. Barros,

T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K.

Plattner, S.K. Allen, M. Tignor, and P.M. Midgley (eds.)]. Cambridge University

Press, Cambridge, UK and New York, NY, USA, pp. 109-230.

Seo, S.N., B.A. McCarl, and R. Mendelsohn, 2010: From beef cattle to sheep under

global warming? An analysis of adaptation by livestock species choice in South

America. Ecological Economics, 69(12), 2486-2494.

Seoane, R. and P. López, 2007: Assessing the effects of climate change on the

hydrological regime of the Limay River basin. GeoJournal, 70(4), 251-256.

Seth, A., M. Rojas, and S.A. Rauscher, 2010: CMIP3 projected changes in the annual

cycle of the South American monsoon. Climatic Change, 98(3-4), 331-357.

Shepard, D.S., L. Coudeville, Y.A. Halasa, B. Zambrano, and G.H. Dayan, 2011:

Economic impact of dengue illness in the Americas. American Journal of Tropical

Medicine and Hygiene, 84(2), 200-207.

Shiogama, H., S. Emori, N. Hanasaki, M. Abe, Y. Masutomi, K. Takahashi, and T.

Nozawa, 2011: Observational constraints indicate risk of drying in the Amazon

basin. Nature Communications, 2, 253, doi:10.1038/ncomms1252.

SICA, 2013: CRRH – Comité Regional de Recursos Hidráulicos [Regional Committee

of Hydraulic Resources]. Sistema de la Integración Centroamericana (SICA),

Antiguo Cuscatlán, La Libertad, El Salvador, www.recursoshidricos.org/.

Sietz, D., 2011: Dryland Vulnerability – Typical Patterns and Dynamics in Support of

Vulnerability Reduction Efforts. Dissertation for Doctor rerum naturalium in

Global Ecology, University of Potsdam and the Potsdam Institute for Climate

Impact Research Research, Potsdam, Germany, 135 pp.

Sietz, D., B. Untied, O. Walkenhorst, M.K.B. Lüdeke, G. Mertins, G. Petschel-Held, and

H.J. Schellnhuber, 2006: Smallholder agriculture in Northeast Brazil: assessing

heterogeneous human-environmental dynamics. Regional Environmental

Change, 6(3), 132-146.

Sietz, D., M.K.B. Luedeke, and C. Walther, 2011: Categorisation of typical vulnerability

patterns in global drylands. Global Environmental Change, 21(2), 431-440.

Sietz, D., S.E. Mamani Choque, and M.K.B. Lüdeke, 2012: Typical patterns of

smallholder vulnerability to weather extremes with regard to food security in

the Peruvian Altiplano. Regional Environmental Change, 12(3), 489-505.

Silva, G.B. and P.V. de Azevedo, 2008: Índices de tendências de mudanças climáticas

no Estado da Bahia [Indices of climate change trends in the State of Bahia].

Engenheiria Ambiental, 5(3), 141-151.

Silva, V.d.P.R., J.H.B.C. Campos, M.T. Silva, and P.V. Azevedo, 2010: Impact of global

warming on cowpea bean cultivation in northeastern Brazil. Agricultural Water

Management, 97(11), 1760-1768.

Silva Dias, M.A.F., J. Dias, L. Carvalho, E. Freitas, and P.L. Silva Dias, 2012: Changes

in extreme daily rainfall for São Paulo, Brazil. Climatic Change, 116(3-4), 705-

722.

Sitch, S., C. Huntingford, N. Gedney, P.E. Levy, M. Lomas, S.L. Piao, R. Betts, P. Ciais,

P. Cox, P. Friedlingstein, C.D. Jones, I.C. Prentice, and F.I. Woodward, 2008:

Evaluation of the terrestrial carbon cycle, future plant geography and climate-

carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs).

Global Change Biology, 14(9), 2015-2039.

Smil, V., 2000: Energy in the twentieth century: resources, conversions, costs, uses,

and consequences. Annual Review of Energy and the Environment, 25, 21-51.

Smolka, M.O. and A.A. Larangeira, 2008: Chapter 5: Informality and poverty in Latin

American urban policies. In: The New Global Frontier: Urbanization, Poverty

and Environment in the 21

Century [Martine, G., G. McGranahan, M.

Montgomery, and R. Fernández-Castilla (eds.)]. Earthscan, London, UK, pp.

99-114.

Soares, W.R. and J.A. Marengo, 2009: Assessments of moisture fluxes east of the

Andes in South America in a global warming scenario. International Journal of

Climatology, 29(10), 1395-1414.

Soares-Filho, B., P. Moutinho, D. Nepstad, A. Anderson, H. Rodrigues, R. Garcia, L.

Dietzsch, F. Merry, M. Bowman, L. Hissa, R. Silvestrini, and C. Maretti, 2010:

Role of Brazilian Amazon protected areas in climate change mitigation.

Proceedings of the National Academy of Sciences of the United States of

America, 107(24), 10821-10826.

Soito, J.L.d.S. and M.A.V. Freitas, 2011: Amazon and the expansion of hydropower

in Brazil: vulnerability, impacts and possibilities for adaptation to global climate

change. Renewable and Sustainable Energy Reviews, 15(6), 3165-3177.

Soleri, D., D.A. Cleveland, G. Glasgow, S.H. Sweeney, F. Aragón Cuevas, M.R. Fuentes,

and H. Ríos L., 2008: Testing assumptions underlying economic research on

transgenic food crops for Third World farmers: evidence from Cuba, Guatemala

and Mexico. Ecological Economics, 67(4), 667-682.

Sörensson, A.A., C.G. Menéndez, R. Ruscica, P. Alexander, P. Samuelsson, and U.

Willén, 2010: Projected precipitation changes in South America: a dynamical

downscaling within CLARIS. Meteorologische Zeitschrift, 19(4), 347-355.

Soriano, M., K.A. Kainer, C.L. Staudhammer, and E. Soriano, 2012: Implementing

multiple forest management in Brazil nut-rich community forests: effects of

logging on natural regeneration and forest disturbance. Forest Ecology and

Management, 268, 92-102.

Sortino-Rachou, A.M., M.P. Curado, and M.d.C. Cancela, 2011: Cutaneous

melanoma in Latin America: a population-based descriptive study. Cadernos

de Saúde Pública, 27(3), 565-572.

Soruco, A., C. Vincent, B. Francou, and J.F. Gonzalez, 2009: Glacier decline between

1963 and 2006 in the Cordillera Real, Bolivia. Geophysical Research Letters,

36, L03502, doi:10.1029/2008GL036238.

Southgate, D., T. Haab, J. Lundine, and F. Rodríguez, 2010: Payments for environmental

services and rural livelihood strategies in Ecuador and Guatemala. Environment

and Development Economics, 15(1), 21-37.

Souvignet, M., H. Gaese, L. Ribbe, N. Kretschmer, and R. Oyarzún, 2010: Statistical

downscaling of precipitation and temperature in north-central Chile: an

assessment of possible climate change impacts in an arid Andean watershed.

Hydrological Sciences Journal/Journal des Sciences Hydrologiques, 55(1), 41-57.

1564

Chapter 27 Central and South America

Souvignet, M., R. Oyarzún, K.M.J. Verbist, H. Gaese, and J. Heinrich, 2012: Hydro-

meteorological trends in semi-arid north-central Chile (29-32 °S): water

resources implications for a fragile Andean region. Hydrological Sciences Journal/

Journal des Sciences Hydrologiques, 57(3), 479-495.

Souza, M.N., E.C. Mantovani, A.G. da Silva Jr., J.J. Griffith, and R.C. Delgado, 2010:

Avaliação do comportamento hidrológico na Bacia do Ribeirão entre Ribeiros,

Afluente do Rio Paracatu, em Cenário de Mudança Climática com o Uso do

Software STELLA [Evaluation of hydrologic behavior of the entre Ribeiros River

Basin, an affluent of Paracatu River, in climatic change scenario, with the

use of the STELLA software]. Engenharia na Agricultura, 18(4), 339-351 (in

Portuguese).

SSN Capacity Building Team, 2006: The SouthSouthNorth Capacity Building Module

on Poverty Reduction: Approaches for Achieving Sustainable Development and

Poverty Reduction. SouthSouthNorth (SSN), Cape Town, South Africa, 63 pp.

Stehr, A., P. Debels, J.L. Arumí, H. Alcayaga, and F. Romero, 2010: Modelación de la

respuesta hidrológica al cambio climático: experiencias de dos cuencas de la

zona centro-sur de Chile [Modeling the hydrological response to climate

change: experiences from two south-central Chilean watersheds]. Tecnología

y Ciencias del Agua, 1(4), 37-58 (in Spanish).

Strassburg, B.B.N., A. Kelly, A. Balmford, R.G. Davies, H.K. Gibbs, A. Lovett, L. Miles,

C.D.L. Orme, J. Price, R.K. Turner, and A.S.L. Rodrigues, 2010: Global congruence

of carbon storage and biodiversity in terrestrial ecosystems. Conservation

Letters, 3(2), 98-105.

Strelin, J. and R. Iturraspe, 2007: Recent evolution and mass balance of Cordón

Martial glaciers, Cordillera Fueguina Oriental. Global and Planetary Change,

59(1-4), 17-26.

Sverdlik, A., 2011: Ill-health and poverty: a literature review on health in informal

settlements. Environment and Urbanization, 23(1), 123-155.

Tacconi, L., 2012: Redefining payments for environmental services. Ecological

Economics, 73, 29-36.

Tada, M.S., R.P. Marques, E. Mesquita, R.C. Dalla Martha, J.A. Rodrigues, J.D. Costa,

R.R. Pepelascov, T.H. Katsuragawa, and L.H. Pereira-da-Silva, 2007: Urban malaria

in the Brazilian Western Amazon Region I: high prevalence of asymptomatic

carriers in an urban riverside district is associated with a high level of clinical

malaria. Memórias do Instituto Oswaldo Cruz, 102(3), 263-269.

Takasaki, Y., 2007: Dynamic household models of forest clearing under distinct

land and labor market institutions: can agricultural policies reduce tropical

deforestation? Environment and Development Economics, 12(3), 423-443.

Tapia-Conyer, R., J.F. Méndez-Galván, and H. Gallardo-Rincón, 2009: The growing

burden of dengue in Latin America. Journal of Clinical Virology, 46(2 Suppl.),

3-6.

Team, V. and L. Manderson, 2011: Social and public health effects of climate change

in the ‘40 South’. Wiley Interdisciplinary Reviews: Climate Change, 2(6), 902-

918.

Teixeira, E.I., G. Fischer, H. van Velthuizen, C. Walter, and F. Ewert, 2013: Global hot-

spots of heat stress on agricultural crops due to climate change. Agricultural

and Forest Meteorology, 170, 206-215.

Thompson, L.G., E. Mosley-Thompson, H. Brecher, M. Davis, B. Leon, D. Les, P.N. Lin,

T. Mashiotta, and K. Mountain, 2006: Abrupt tropical climate change: past and

present. Proceedings of the National Academy of Sciences of the United States

of America, 103(28), 10536-10543.

Thompson, L.G., E. Mosley-Thompson, M.E. Davis, and H.H. Brecher, 2011: Tropical

glaciers, recorders and indicators of climate change, are disappearing globally.

Annals of Glaciology, 52(59), 23-34.

Tirado, M.C., R. Clarke, L.A. Jaykus, A. McQuatters-Gollop, and J.M. Frank, 2010:

Climate change and food safety: a review. Food Research International, 43(7),

1745-1765.

Todd, M.C., R.G. Taylor, T.J. Osborn, D.G. Kingston, N.W. Arnell, and S.N. Gosling, 2011:

Uncertainty in climate change impacts on basin-scale freshwater resources –

preface to the special issue: the QUEST-GSI methodology and synthesis of

results. Hydrology and Earth System Sciences, 15(3), 1035-1046.

Tomei, J. and P. Upham, 2009: Argentinean soy-based biodiesel: an introduction to

production and impacts. Energy Policy, 37(10), 3890-3898.

Tompkins, E.L., M.C. Lemos, and E. Boyd, 2008: A less disastrous disaster: managing

response to climate-driven hazards in the Cayman Islands and NE Brazil. Global

Environmental Change: Human and Policy Dimensions, 18(4), 736-745.

Tormey, D., 2010: Managing the effects of accelerated glacial melting on volcanic

collapse and debris flows: Planchon-Peteroa Volcano, Southern Andes. Global

and Planetary Change, 74(2), 82-90.

Torres, J.R. and J. Castro, 2007: The health and economic impact of dengue in Latin

America. Cadernos de Saúde Pública, 23(1 Suppl.), 23-31.

Tourre, Y.M., L. Jarlan, J.-P. Lacaux, C.H. Rotela, and M. Lafaye, 2008: Spatio-temporal

variability of NDVI-precipitation over southernmost South America: possible

linkages between climate signals and epidemics. Environmental Research

Letters, 3(4), 044008, doi:10.1088/1748-9326/3/4/044008.

Travasso, M.I., G.O. Magrin, W.E. Baethgen, J.P. Castaño, G.I.R. Rodriguez, J.L. Pires,

A. Gimenez, G. Cunha, and M. Fernández, 2008: Chapter 19: Maize and soybean

cultivation in southeastern South America: adapting to climate change. In:

Climate Change and Adaptation [Leary, N., J. Adejuwon, V. Barros, I. Burton, J.

Kulkarni, and R. Lasco (eds.)]. Earthscan, London, UK, pp. 332-352.

Travasso, M.I., G.O. Magrin, M.O. Grondona, and G.R. Rodriguez, 2009a: The use of

SST and SOI anomalies as indicators of crop yield variability. International Journal

of Climatology, 29(1), 23-29.

Travasso, M.I., G.O. Magrin, G.R. Rodríguez, S. Solman, and M. Núñez, 2009b: Climate

change impacts on regional maize yields and possible adaptation measures in

Argentina. International Journal of Global Warming, 1(1-3), 201-213.

Troin, M., C. Vallet-Coulomb, F. Sylvestre, and E. Piovano, 2010: Hydrological modelling

of a closed lake (Laguna Mar Chiquita, Argentina) in the context of 20

century

climatic changes. Journal of Hydrology, 393(3-4), 233-244.

Trombotto, D. and E. Borzotta, 2009: Indicators of present global warming through

changes in active layer-thickness, estimation of thermal diffusivity and geo-

morphological observations in the Morenas Coloradas rockglacier, Central Andes

of Mendoza, Argentina. Cold Regions Science and Technology, 55(3), 321-330.

Tschakert, P. and K.A. Dietrich, 2010: Anticipatory learning for climate change

adaptation and resilience. Ecology and Society, 15(2), 11, www.ecologyand

society.org/vol15/iss2/art11/.

Tucker, C.M., H. Eakin, and E.J. Castellanos, 2010: Perceptions of risk and adaptation:

coffee producers, market shocks, and extreme weather in Central America and

Mexico. Global Environmental Change, 20(1), 23-32.

UGHR, 2010: Inventario de Glaciares Cordillera Blanca. Ministerio de Agricultura del

Perú, Autoridad Nacional del Agua, Direccion de conservación y Planeamiento

de Recursos Hidricos and Unidad de Glaciologia y Recursos Hidricos (UGHR),

Huaraz, Peru, 74 pp.

UNDP, 2007: Chapter 2: Climate shocks: risk and vulnerability in an unequal world.

In: Human Development Report 2007/2008. Fighting Climate Change: Human

Solidarity in a Divided World. United Nations Development Programme (UNDP),

New York, NY, USA, pp. 71-108.

UNDP, 2010: Regional Human Development Report for Latin America and Caribbean

2010. Acting on the Future: Breaking the Intergenerational Transmission of

Inequality. United Nations Development Programme (UNDP), San José, Costa

Rica, 206 pp.

UNEP and ECLAC, 2010: Vital Climate Change Graphics for Latin America and the

Caribbean. United Nations Environment Programme (UNEP)-Regional Office

for Latin America and the Caribbean, Sustainable Development and Human

Settlements Division of the Economic Commission for Latin America and the

Caribbean (ECLAC), and UNEP/GRID-Arendal, UNEP Regional Office for Latin

America and the Caribbean, Panama City, Panama and ECLAC, Santiago, Chile,

42 pp.

UNFCCC, 2012: Non-Annex I National Communications. United Nations Framework

Convention on Climate Change (UNFCCC), Bonn, Germany, unfccc.int/national_

reports/non-annex_i_natcom/items/2979.php (accessed on 4 November 2012).

UN-HABITAT, 2011: Climate change mitigation responses in urban areas. In: Cities

and Climate Change: Global Report on Human Settlements 2011. United Na-

tions Human Settlements Programme (UN-HABITAT), Earthscan, London, UK

and Washington, DC, USA, pp. 91-128.

Urcola, H.A., J.H. Elverdin, M.A. Mosciaro, C. Albaladejo, J.C. Manchado, and J.F.

Giussepucci, 2010: Climate change impacts on rural societies: stakeholders per-

ceptions and adaptation strategies in Buenos Aires, Argentina. In: International

Symposium, “Innovation and Societies: What kinds of agriculture? What kinds

of innovation?” Proceedings of Innovation and Sustainable Development in

Agriculture and Food (ISDA): 2010, June 28-July 1, 2010, Montpellier, France

[Coudel, E., H. Devautour, C. Soulard, and B. Hubert (eds.)]. Organised by the

Centre de Coopération Internationale en Recherche Agronomique pour le

Développement (CIRAD), The French National Institute for Agricultural Research

(INRA) and Office de la Recherche Scientifique et Technique Outre-Mer

(ORSTOM), CIRAD, Montpellier, France, hal.archives-ouvertes.fr/view_by_

stamp.php?&halsid=u34r94cgmdir369ehfh2f84o16&label=ISDA2010&langue=

en&action_todo=home.

1565

Central and South America Chapter 27

Urrutia, R.B., A. Lara, R. Villalba, D.A. Christie, C. Le Quesne, and A. Cuq, 2011:

Multicentury tree ring reconstruction of annual streamflow for the Maule River

watershed in south central Chile. Water Resources Research, 47(6), W06527,

doi:10.1029/2010WR009562.

Valderrama-Ardila, C., N. Alexander, C. Ferro, H. Cadena, D. Marín, T.R. Holford, L.E.

Munstermann, and C.B. Ocampo, 2010: Environmental risk factors for the

incidence of American cutaneous leishmaniasis in a Sub-Andean zone of

Colombia (Chaparral, Tolima). American Journal of Tropical Medicine and

Hygiene, 82(2), 243-250.

Valdivia, C., A. Seth, J.L. Gilles, M. Garcia, E. Jimenez, J. Cusicanqui, F. Navia, and E.

Yucra, 2010: Adapting to climate change in Andean ecosystems: landscapes,

capitals, and perceptions shaping rural livelihood strategies and linking

knowledge systems. Annals of the Association of American Geographers,

100(4), 818-834.

Valentine, J., J. Clifton-Brown, A. Hastings, P. Robson, G. Allison, and P. Smith, 2012:

Food vs. fuel: the use of land for lignocellulosic ‘next generation’ energy crops

that minimize competition with primary food production. Global Change

Biology Bioenergy, 4(1), 1-19.

Valverde, M.d.l.A., J.M. Ramírez, L.G.M.d. Oca, M.G.A. Goris, N. Ahmed, and R.A.

Hartskeerl, 2008: Arenal, a new Leptospira serovar of serogroup Javanica, isolated

from a patient in Costa Rica. Infection, Genetics and Evolution, 8(5), 529-533.

van der Meide, W.F., A.J. Jensema, R.A.E. Akrum, L.O.A. Sabajo, R.F.M. Lai A Fat,

L. Lambregts, H.D.F.H. Schallig, M. van der Paardt, and W.R. Faber, 2008:

Epidemiology of cutaneous leishmaniasis in Suriname: a study performed in

2006. American Journal of Tropical Medicine and Hygiene, 79(2), 192-197.

van Noordwijk, M., B. Leimona, R. Jindal, G.B. Villamor, M. Vardhan, S. Namirembe, D.

Catacutan, J. Kerr, P.A. Minang, and T.P. Tomich, 2012: Payments for environmental

services: evolution toward efficient and fair incentives for multifunctional

landscapes. Annual Review of Environment and Resources, 37, 389-420.

van Oel, P.R., M.S. Krol, A.Y. Hoekstra, and R.R. Taddei, 2010: Feedback mechanisms

between water availability and water use in a semi-arid river basin: a spatially

explicit multi-agent simulation approach. Environmental Modelling & Software,

25(4), 433-443.

Vargas, W.M., G. Naumann, and J.L. Minetti, 2011: Dry spells in the River Plata Basin:

an approximation of the diagnosis of droughts using daily data. Theoretical

and Applied Climatology, 104(1-2), 159-173.

Venema, H.D. and M. Cisse (eds.), 2004: Seeing the Light: Adapting to Climate Change

with Decentralized Renewable Energy in Developing Countries. International

Institute for Sustainable Development (IISD), Winnipeg, MB, Canada, 174 pp.

Venencio, M.d.V. and N.O. García, 2011: Interannual variability and predictability of

water table levels at Santa Fe Province (Argentina) within the climatic change

context. Journal of Hydrology, 409(1-2), 62-70.

Vergara, W. (ed.), 2009: Assessing the Potential Consequences of Climate

Destabilization in Latin America. Latin America and Caribbean Region

Sustainable Development Working Paper No. 32, The World Bank, Latin America

and the Caribbean Region, Sustainable Development Department (LCSSD),

Washington, DC, USA, 119 pp.

Vergara, W., A. Deeb, A. Valencia, R. Bradley, B. Francou, A. Zarzar, A. Grünwaldt, and

S. Haeussling, 2007: Economic impacts of rapid glacier retreat in the Andes.

Eos, Transactions of the America Geophysical Union, 88(25), 261-264.

Viana, V.M., 2008: Bolsa Floresta (Forest Conservation Allowance): an innovative

mechanism to promote health in traditional communities in the Amazon.

Estudos Avançados, 22(64), 143-153.

Vich, A.I.J., P.M. López, and M.C. Schumacher, 2007: Trend detection in the water

regime of the main rivers of the Province of Mendoza, Argentina. GeoJournal,

70(4), 233-243.

Vicuña, S., R. Garreaud, J. McPhee, F. Meza, and G. Donoso, 2010: Vulnerability and

adaptation to climate change in an irrigated agricultural basin in semi arid Chile.

In: Watershed Management 2010: Innovations in Watershed Management under

Land Use and Climate Change [Potter, K.W. and D.K. Frevert (eds.)]. Proceedings

of the Watershed Management Conference 2010, Madison, Wisconsin, 23-27

August, 2010, American Society of Civil Engineers (ASCE), Reston, VA, USA, pp.

135-146.

Vicuña, S., R.D. Garreaud, and J. McPhee, 2011: Climate change impacts on the

hydrology of a snowmelt driven basin in semiarid Chile. Climatic Change,

105(3-4), 469-488.

Vicuña, S., J. McPhee, and R.D. Garreaud, 2012: Agriculture vulnerability to climate

change in a snowmelt driven basin in semiarid Chile. Journal of Water

Resources Planning and Management, 138(5), 431-441.

Vicuña, S., J. Gironás, F.J. Meza, M.L. Cruzat, M. Jelinek, E. Bustos, D. Poblete, and N.

Bambach, 2013: Exploring possible connections between hydrological extreme

events and climate change in central south Chile. Hydrological Sciences Journal,

58(8), 1598-1619.

Viglizzo, E.F. and F.C. Frank, 2006: Ecological interactions, feedbacks, thresholds and

collapses in the Argentine Pampas in response to climate and farming during

the last century. Quaternary International, 158(1), 122-126.

Viglizzo, E.F., E.G. Jobbagy, L. Carreno, F.C. Frank, R. Aragon, L. De Oro, and V.

Salvador, 2009: The dynamics of cultivation and floods in arable lands of Central

Argentina. Hydrology and Earth System Sciences, 13(4), 491-502.

Viglizzo, E.F., F.C. Frank, L.V. Carreño, E.G. Jobbágy, H. Pereyra, J. Clatt, D. Pincén, and

M.F. Ricard, 2011: Ecological and environmental footprint of 50 years of

agricultural expansion in Argentina. Global Change Biology, 17(2), 959-973.

Vignola, R., B. Locatelli, C. Martinez, and P. Imbach, 2009: Ecosystem-based adaptation

to climate change: what role for policy-makers, society and scientists? Mitigation

and Adaptation Strategies for Global Change, 14(8), 691-696.

Villacís, M., 2008: Ressources en Eau Glaciaire dans les Andes d’Equateur en Relation

avec les Variations du Climat: Le Cas du Volcan Antisana [Resources of Water

Ice in the Andes of Ecuador in Relation to Climate Variations: The Case of

Antisana Volcano]. PhD Dissertation, Université Montpellier, Montpellier, France,

231 pp. (in French).

Volpe, F.M., E.M. da Silva, T.N. dos Santos, and D.E.G. de Freitas, 2010: Further

evidence of seasonality of mania in the tropics. Journal of Affective Disorders,

124(1-2), 178-182.

von Braun, J., 2007: The World Food Situation: New Driving Forces and Required

Actions. International Food Policy Research Institute (IFPRI), Washington, DC,

USA, 18 pp.

Vuille, M., B. Francou, P. Wagnon, I. Juen, G. Kaser, B.G. Mark, and R.S. Bradley, 2008a:

Climate change and tropical Andean glaciers: past, present and future. Earth-

Science Reviews, 89(3-4), 79-96.

Vuille, M., G. Kaser, and I. Juen, 2008b: Glacier mass balance variability in the

Cordillera Blanca, Peru and its relationship with climate and the large-scale

circulation. Global and Planetary Change, 62(1-2), 14-28.

Walter, L.C., H.T. Rosa, and N.A. Streck, 2010: Simulação do rendimento de grãos de

arroz irrigado em cenários de mudanças climáticas [Simulating grain yield of

irrigated rice in climate change scenarios]. Pesquisa Agropecuaria Brasileira,

45(11), 1237-1245 (in Portuguese).

Walther, G., 2010: Community and ecosystem responses to recent climate change.

Philosophical Transactions of the Royal Society B, 365(1549), 2019-2024.

Wang, B., J. Liu, H. Kim, P.J. Webster, and S. Yim, 2012: Recent change of the global

monsoon precipitation (1979-2008). Climate Dynamics, 39(5 SI), 1123-1135.

Wang, G., S. Sun, and R. Mei, 2011: Vegetation dynamics contributes to the multi-

decadal variability of precipitation in the Amazon region. Geophysical Research

Letters, 38, L19703, doi:10.1029/2011GL049017.

Warner, J. and M.T. Oré, 2006: El Niño platforms: participatory disaster response in

Peru. Disasters, 30(1), 102-117.

Wassenaar, T., P. Gerber, P.H. Verburg, M. Rosales, M. Ibrahim, and H. Steinfeld, 2007:

Projecting land use changes in the Neotropics: the geography of pasture

expansion into forest. Global Environmental Change: Human and Policy

Dimensions, 17(1), 86-104.

Waycott, M., C.M. Duarte, T.J.B. Carruthers, R.J. Orth, W.C. Dennison, S. Olyarnik, A.

Calladine, J.W. Fourqurean, K.L. Heck Jr., A.R. Hughes, G.A. Kendrick, W.J.

Kenworthy, F.T. Short, and S.L. Williams, 2009: Accelerating loss of seagrasses

across the globe threatens coastal ecosystems. Proceedings of the National

Academy of Sciences of the United States of America, 106(30), 12377-12381.

Winchester, L., 2008: Harmony and Dissonance between Human Settlements and the

Environment in Latin America and the Caribbean. LC/W.204, Economic Commission

for Latin America and the Caribbean (ECLAC), Santiago de Chile, Chile, 91 pp.

World Bank, 2012: The World Bank Data. In: World Development Indicators, Urban

Development, Urban Population (% of Total) and Population in the Largest City

(% of Urban Population). The World Bank, Washington, DC, USA, data.

worldbank.org/topic/urban-development (accessed on 6 May 2012).

Winchester, L. and R. Szalachman, 2009: The Urban Poor’s Vulnerability to the Impacts

of Climate Change in Latin America and the Caribbean. A Policy Agenda.

Presented at the 5

Urban Research Symposium “Cities and Climate Change:

Responding to the Urgent Agenda” June 28-30, 2009, Marseille, France, The

World Bank, Washington, DC, USA, 31 pp. http://siteresources.worldbank.org/

INTURBANDEVELOPMENT/Resources/336387-1256566800920/6505269-

1268260567624/Winchester.pdf.

1566

Chapter 27 Central and South America

Wright, S.J. and M.J. Samaniego, 2008: Historical, demographic, and economic

correlates of land-use change in the Republic of Panama. Ecology and Society,

13(2), 17, www.ecologyandsociety.org/vol13/iss2/art17/.

Xu, Y., X. Gao, and F. Giorgi, 2009: Regional variability of climate change hot-spots in

East Asia. Advances in Atmospheric Sciences, 26(4), 783-792.

Young, G., H. Zavala, J. Wandel, B. Smit, S. Salas, E. Jimenez, M. Fiebig, R. Espinoza,

H. Diaz, and J. Cepeda, 2010: Vulnerability and adaptation in a dryland

community of the Elqui Valley, Chile. Climatic Change, 98(1-2), 245-276.

Young, K.R. and J.K. Lipton, 2006: Adaptive governance and climate change in the

tropical highlands of western South America. Climatic Change, 78(1), 63-102.

Zagonari, F., 2010: Sustainable, just, equal, and optimal groundwater management

strategies to cope with climate change: insights from Brazil. Water Resources

Management, 24(13), 3731-3756.

Zak, M.R., M. Cabido, D. Caceres, and S. Diaz, 2008: What drives accelerated land

cover change in central Argentina? Synergistic consequences of climatic,

socioeconomic, and technological factors. Environmental Management, 42(2),

181-189.

Zhang, X. and X. Cai, 2011: Climate change impacts on global agricultural land

availability. Environmental Research Letters, 6(1), 014014doi:10.1088/1748-

9326/6/1/014014.

Zhang, Y., R. Fu, H. Yu, Y. Qian, R. Dickinson, M.A.F. Silva Dias, P.L. da Silva Dias, and

K. Fernandes, 2009: Impact of biomass burning aerosol on the monsoon

circulation transition over Amazonia. Geophysical Research Letters, 36, L10814,

doi:10.1029/2009GL037180.

Zullo Jr., J., H.S. Pinto, E.D. Assad, and A.M. Heuminski de Ávila, 2011: Potential for

growing Arabica coffee in the extreme south of Brazil in a warmer world.

Climatic Change, 109(3-4), 535-548.