979
18
Detection and Attribution
of Observed Impacts
Coordinating Lead Authors:
Wolfgang Cramer (Germany/France), Gary W. Yohe (USA)
Lead Authors:
Maximilian Auffhammer (USA), Christian Huggel (Switzerland), Ulf Molau (Sweden),
Maria Assunção Faus da Silva Dias (Brazil), Andrew Solow (USA), Dáithí A. Stone
(Canada/South Africa/USA), Lourdes Tibig (Philippines)
Contributing Authors:
Laurens Bouwer (Netherlands), Mark Carey (USA), Graham Cogley (Canada), Dim Coumou
(Germany), Yuka Otsuki Estrada (USA/Japan), Eberhard Faust (Germany), Gerrit Hansen
(Germany), Ove Hoegh-Guldberg (Australia), Joanna House (UK), Solomon Hsiang (USA),
Lesley Hughes (Australia), Sari Kovats (UK), Paul Leadley (France), David Lobell (USA),
Camille Parmesan (USA), Elvira Poloczanska (Australia), Hans Otto Pörtner (Germany),
Andy Reisinger (New Zealand)
Review Editors:
Rik Leemans (Netherlands), Bernard Seguin (France), Neville Smith (Australia)
Volunteer Chapter Scientist:
Gerrit Hansen (Germany)
This chapter should be cited as:
Cramer
, W., G.W. Yohe, M. Auffhammer, C. Huggel, U. Molau, M.A.F. da Silva Dias, A. Solow, D.A. Stone, and
L. Tibig, 2014: Detection and attribution of observed impacts. In: Climate Change 2014: Impacts, Adaptation,
and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken,
K.J. Mach, M.D. Mastrandrea, 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. 979-1037.
18
980
Executive Summary ........................................................................................................................................................... 982
18.1. Introduction ............................................................................................................................................................ 984
18.1.1. Scope and Goals of the Chapter ....................................................................................................................................................... 984
18.1.2. Summary of Findings from the Fourth Assessment Report ................................................................................................................ 984
18.2. Methodological Concepts for Detection and Attribution of Impacts of Climate Change ...................................... 984
18.2.1. Concepts and Approaches ................................................................................................................................................................ 985
18.2.1.1 Detecting and Attributing Change in the Earth System ..................................................................................................... 985
18.2.1.2 Concepts of Detection and Attribution of Climate Change Impacts Used in this Chapter .................................................. 985
Box 18-1. Quantitative Synthesis Assessment of Detection and Attribution Studies in Ecological Systems .................. 986
18.2.2. Challenges to Detection and Attribution ........................................................................................................................................... 986
18.3. Detection and Attribution of Observed Climate Change Impacts in Natural Systems ........................................... 986
18.3.1. Freshwater Resources ....................................................................................................................................................................... 986
18.3.1.1. The Cryosphere .................................................................................................................................................................. 987
18.3.1.2. The Regional Water Balance .............................................................................................................................................. 988
18.3.1.3. Erosion, Landslides, and Avalanches .................................................................................................................................. 988
18.3.2. Terrestrial and Inland Water Systems ................................................................................................................................................ 989
18.3.2.1. Phenology ......................................................................................................................................................................... 989
18.3.2.2. Productivity and Biomass .................................................................................................................................................. 989
18.3.2.3. Species Distributions and Biodiversity ............................................................................................................................... 990
18.3.2.4. Impacts on Major Systems ................................................................................................................................................ 990
18.3.3. Coastal Systems and Low-Lying Areas .............................................................................................................................................. 991
18.3.3.1. Shoreline Erosion and Other Coastal Processes ................................................................................................................. 991
18.3.3.2. Coastal Ecosystems ........................................................................................................................................................... 991
Box 18-2. Attribution of Mass Coral Bleaching Events to Climate Change ..................................................................... 992
18.3.3.3. Coastal Settlements and Infrastructure ............................................................................................................................. 993
18.3.4. Oceans .............................................................................................................................................................................................. 993
18.3.4.1. Impacts on Ocean System Properties and Marine Organisms and Ecosystems .................................................................. 994
18.3.4.2. Observed Climate Change Effects across Ocean Regions .................................................................................................. 994
Box 18-3. Differences in Detection and Attribution of Ecosystem Change on Land and in the Ocean ........................... 995
18.4. Detection and Attribution of Observed Climate Change Impacts in Human and Managed Systems ..................... 996
18.4.1. Food Production Systems .................................................................................................................................................................. 996
18.4.1.1. Agricultural Crops ............................................................................................................................................................. 996
Box 18-4. The Role of Sensitivity to Climate and Adaptation for Impact Models in Human Systems ............................. 997
18.4.1.2. Fisheries ............................................................................................................................................................................ 997
Table of Contents
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Detection and Attribution of Observed Impacts Chapter 18
18
18.4.2. Economic Impacts, Key Economic Sectors, and Services .................................................................................................................... 997
18.4.2.1. Economic Growth .............................................................................................................................................................. 997
18.4.2.2. Energy Systems ................................................................................................................................................................. 997
18.4.2.3. Tourism .............................................................................................................................................................................. 998
18.4.3. Impacts of Extreme Weather Events ................................................................................................................................................. 998
18.4.3.1. Economic Losses Due to Extreme Weather Events ............................................................................................................. 998
18.4.3.2. Detection and Attribution of the Impacts of Single Extreme Weather Events to Climate Change ...................................... 998
18.4.4. Human Health ................................................................................................................................................................................ 1000
Box 18-5. Detection, Attribution, and Traditional Ecological Knowledge ................................................................................. 1001
18.4.5. Human Security .............................................................................................................................................................................. 1001
18.4.6. Livelihoods and Poverty .................................................................................................................................................................. 1002
18.5. Detection and Attribution of Observed Climate Change Impacts across Regions ............................................... 1003
18.6. Synthesis: Emerging Patterns of Observed Impacts of Climate Change .............................................................. 1010
18.6.1. Approach ........................................................................................................................................................................................ 1010
18.6.2. The Global Pattern of Regional Impacts .......................................................................................................................................... 1010
18.6.3. Cascading Impacts .......................................................................................................................................................................... 1013
18.6.4. Reasons for Concern ....................................................................................................................................................................... 1013
18.6.5. Conclusion ...................................................................................................................................................................................... 1016
18.7. Gaps, Research Needs, and Emerging Issues ........................................................................................................ 1017
References ....................................................................................................................................................................... 1018
Frequently Asked Questions
18.1: Why are detection and attribution of climate impacts important? ................................................................................................. 1017
18.2: Why is it important to assess impacts of all climate change aspects, and not only impacts of anthropogenic climate change? .... 1017
18.3: What are the main challenges in detecting climate change impacts? ............................................................................................ 1018
18.4: What are the main challenges in attributing changes in a system to climate change? ................................................................... 1018
18.5: Is it possible to attribute a single event, such as a disease outbreak, or the extinction of a species, to climate change? ............... 1018
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Chapter 18 Detection and Attribution of Observed Impacts
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Executive Summary
Evidence has grown since the Fourth Assessment Report (AR4) that impacts of recent changes in climate on natural and human
systems occur on all continents and across the oceans. This conclusion is strengthened both by new and longer term observations and
through more extensive analyses of existing data. {18.3-6}
Reported impacts are caused by changes in climate that deviate from historical conditions, irrespective of the driver of climate
change.
Most reported impacts of climate change are attributed to warming and/or shifts in precipitation patterns. There is also emerging
evidence of impacts of ocean acidification. Only some robust attribution studies and meta-analyses link responses in physical and biological
systems to anthropogenic climate change. {18.1, 18.3-5}
For many natural systems there is new or stronger evidence for substantial and wide-ranging impacts of climate change. These
systems include the cryosphere, water resources, coastal systems, and ecosystems on land and in the ocean. {18.3}
Impacts of climate change on the hydrological cycle, and notably the availability of freshwater resources, have been observed on all continents
and many islands. Glaciers continue to shrink worldwide, as a result of climate change (high confidence), affecting runoff and water resources
downstream. Climate change is the main driver of permafrost warming and thawing in both high-latitude and high-elevation mountain regions
(high confidence). Hydrological systems have changed in many regions because of changing precipitation or melting cryosphere, affecting
water resources, water quality, and sediment transport (medium confidence). {18.3.1, 18.5, Figure 18-2}
Across all climate zones and continents, the major role of climate change and increasing atmospheric carbon dioxide (CO
2
) on terrestrial and
freshwater ecosystems has been confirmed by new and stronger evidence on phenology (high confidence), productivity (low confidence),
distribution ranges (medium confidence), and other processes, affecting an increasing number of species and ecosystems. The majority of
species extinctions and the recession of the Amazon forest cannot be attributed reliably to climate change. Major climate-driven changes occur
in the Arctic region (high confidence), the boreal forest (low confidence), and many freshwater ecosystems (low to high confidence, region-
dependent). {18.3.2, 18.5}
Despite the known sensitivity of coastal systems to sea level rise, local natural and human perturbations preclude a confident detection of sea
level-related impacts of climate change. Climate change has had a major role in observed changes in abundance and distribution of many
coastal species (medium confidence). {18.3.3}
The physical and chemical properties of oceans (including the extent of Arctic sea ice) have changed significantly over the past 6 decades, due
to anthropogenic climate change. Marine organisms have moved to higher latitudes and changed their depth distribution or their phenology,
mostly as a result of the warming (high confidence). Coral reefs have experienced increased mass bleaching and mortality, driven mainly by
warming (high confidence). {18.3.3-4, 18.5, Table 18-8, Box 18-2}
Substantial new evidence has been collected on sensitivities of human systems to climate change. Climate change-related impacts
on human systems are often dominated by effects of changing social and economic factors. {18.4}
Production of wheat and maize globally and in many regional systems has been impacted by climate change over the past several decades
(medium confidence). The impacts of climate change on rice and soybean have been small in major production regions and globally (medium
confidence). Crop production has increased in some mid-latitude regions (United Kingdom, Northeast China) (high confidence). Evidence of
observed climate change impacts on food systems other than agricultural crops and fisheries is limited. {18.4.1}
Economic losses due to extreme weather events have increased globally, mostly due to increase in wealth and exposure, with a possible
influence of climate change (low confidence). {18.4.3}
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18
Detection and Attribution of Observed Impacts Chapter 18
There has been a shift from cold- to heat-related mortality in some regions as a result of warming (medium confidence), but despite many well-
documented sensitivities of human health to other aspects of weather, clear evidence of an additional observed climate change impact on
health outcomes is lacking. {18.4.4}
Livelihoods of indigenous peoples in the Arctic have been altered by climate change, through impacts on food security and traditional and
cultural values (medium confidence). There is emerging evidence of climate change impacts on livelihoods of indigenous people in other
regions. {18.4.6, Box 18-5, Table 18-9}
There is emerging literature on the impact of climate change on poverty, working conditions, violent conflict, migration, and economic growth
from various parts of the world, but evidence for detection or attribution to climate change remains limited. {18.4}
Regional impacts of climate change have now been observed at more locations than before, on all continents and across ocean
regions. In many regions, impacts of climate change are now detected also in the presence of strong confounding factors such as pollution or
land use change. {18.6.2}
“Cascading” impacts of climate change from physical climate through ecosystems on people can now be detected along chains
of evidence. Examples include systems in the cryosphere, the oceans, and forests. In these cases, confidence in attribution to observed climate
change decreases for effects further down the impact chain. {18.6.3}
Evaluation of observed impacts of climate change supports risk assessment of climate change for four of the “Reasons for
Concern” developed by earlier IPCC assessments.
(1) Impacts related to Risks to Unique and Threatened Systems are now manifested for
several systems (Arctic, glaciers on all continents, warm-water coral systems). (2) High-temperature spells have impacted one system with high
confidence (coral reefs), indicating Risks Associated with Extreme Weather Events. Elsewhere, extreme events have caused increasing impacts
and economic losses, but there is only low confidence in attribution to climate change for these. (3) Though impacts of climate change have
now been documented globally with unprecedented coverage, observations are still insufficient to address the spatial or social disparities
underlying the Risks Associated with the Distribution of Impacts. (4) Risks Associated with Aggregated Impacts: large-scale impacts, indicated
by unified metrics, have been found for the cryosphere (ice volume, high confidence), terrestrial ecosystems (net productivity, carbon stocks,
medium-high confidence), and human systems (crop yields, disaster losses, low-medium confidence). (5) Risks Associated with Large-Scale
Singular Events: impacts that demonstrate irreversible shifts with significant feedback potential in the Earth system have yet to be observed,
but there is now robust evidence of early warning signals in observed impacts of climate change that indicate climate-driven large-scale regime
shifts for the Arctic region and the tropical coral reef systems. {18.6.4}
Though evidence is improving, there is a persistent gap in the knowledge regarding how certain parts of the world are being
affected by observed climate change.
Data collection and monitoring are in need to gain wider coverage. Research to improve the
conceptual basis, timeliness, and knowledge about detection and attribution is needed in particular for human systems. {18.2, 18.7}
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Chapter 18 Detection and Attribution of Observed Impacts
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18.1. Introduction
This chapter synthesizes the scientific literature on the detection and
attribution of observed changes in natural and human systems in response
t
o observed recent climate change. For policy makers and the public,
detection and attribution of observed impacts will be a key element to
determine the necessity and degree of mitigation and adaptation efforts.
For most natural and essentially all human systems, climate is only one
of many drivers that cause change—other factors such as technological
innovation, social and demographic changes, and environmental
degradation frequently play an important role as well. Careful accounting
of the importance of these and other confounding factors is therefore
an important part of the analysis.
At any given location, observed recent climate change has happened
as a result of a combination of natural, longer term fluctuations and
anthropogenic alteration of forcings. To inform about the sensitivity of
natural and human systems to ongoing climate change, the chapter
assesses the degree to which detected changes in such systems can be
attributed to all aspects of recent climate change. For the development
of adaptation policies, it is less important whether the observed changes
have been caused by anthropogenic climate change or by natural climate
fluctuations. Where possible, the relative importance of anthropogenic
drivers of climate change is assessed as well.
18.1.1. Scope and Goals of the Chapter
Previous assessments, notably in the IPCC Fourth Assessment Report
(AR4; Rosenzweig et al., 2007), indicated that numerous physical and
biological systems are affected by recent climate change. Owing to
a limited number of published studies, human systems received
comparatively little attention in these assessments, with the exception
of the food system, which is a coupled human-natural system. This
knowledge base is growing rapidly, for all types of impacted systems,
but the disequilibrium remains (see also Section 1.1.1, Figure 1-1). The
great majority of published studies attribute local to regional changes
in affected systems to local to regional climate change.
The objective of the assessment was to cover the growing knowledge
about detection and attribution of impacts as exhaustively as possible.
To improve coverage across sectors and regions, the work was linked
directly to the assessments made by most other chapters of the report.
This ensured that knowledge gained in the expert assessments of any
given sector, system, or region found its way into this chapter. This
chapter uses a consistent set of definitions for detection and attribution
(elaborated in Section 18.2.1—these differ from those found in some
other chapters).
This chapter first reviews methodologies and definitions for detection
and attribution, including the uncertainties that are inherent in such
assessments (Section 18.2). It then assesses the scientific knowledge
base that has developed since the AR4, focusing on the different types
of impacted systems. The assessment covers the state of knowledge
across major natural (Section 18.3) and human systems (Section 18.4),
based largely on the respective sectoral chapters of this report (Chapters
3 to 7, 10 to 13). Assessment in confidence of the existence and cause
o
f impacts is made according to the definitions elaborated in Section
18.2.1.2. Based on this material, and on regional assessments mostly
drawn from the regional chapters of this report (Chapters 22 to 30), an
assessment is made to highlight regional impacts and also to identify
the regional pattern of observed impacts around the globe (Section 18.5).
A synthesis (Section 18.6) and an analysis of research and knowledge
gaps (Section 18.7) conclude the chapter.
18.1.2. Summary of Findings
from the Fourth Assessment Report
Based on Rosenzweig et al. (2007), IPCC (2007a, p. 8) reported that
“observational evidence from all continents and most oceans shows that
many natural systems are being affected by regional climate changes,
particularly temperature increases.” In particular, they highlighted
several areas where this general conclusion was supported by specific
conclusions that were reported with high confidence:
• Changes in snow, ice, and frozen ground had increased ground
instability in mountains and other permafrost regions; these changes
had led to changes in some Arctic and Antarctic ecosystems and
produced increases in the number and size of glacial lakes.
• Some hydrological systems had been affected by increased runoff
and earlier spring peak discharges; in particular many glacier- and
snow-fed rivers and lakes had warmed, producing changes in their
thermal structures and water quality.
• Spring events had appeared earlier in the year so that some terrestrial
ecosystems had moved poleward and upward; these shifts in plant
and animal ranges were attributed to recent warming.
• Shifts in ranges and changes in algal, plankton, and fish abundance
as well as changes in ice cover, salinity, oxygen levels, and circulation
had been associated with rising water temperatures in some marine
and freshwater systems.
In terms of a global synthesis, this assessment noted “that it is likely
that anthropogenic warming over the last three decades has had a
discernible influence on many physical and biological systems” (IPCC,
2007a, p. 9). Though it was based on analyses of a very large number
of observational data sets, the assessment noted a lack of geographic
balance in data and literature on observed changes, with marked
scarcity in low- and middle-income countries.
Evidence reported for human systems was scarce. IPCC (2007a, p. 9)
concluded with medium confidence only that, “other effects of regional
climate change on […] human environments are emerging, although
many are difficult to discern due to adaptation and non-climatic drivers.”
They especially noted effects of temperature increases on agricultural
and forestry management practices in the higher latitudes of the Northern
Hemisphere (NH), various aspects of human health, and some human
activities in snow- and glacier-dominated environments.
18.2. Methodological Concepts for Detection and
Attribution of Impacts of Climate Change
There are substantial challenges to the detection and assessment of the
impacts of climate change on natural and human systems. Virtually all
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Detection and Attribution of Observed Impacts Chapter 18
18
s
uch systems are affected by factors other than climate change. Isolating
the impacts of climate change therefore requires controlling for the
effects of other factors. The problem is further complicated by the ability
of many systems to adapt to climate change. In this section we
summarize the concepts underlying the detection and attribution of
impacts of climate change and the requirements for addressing the
main challenges.
18.2.1. Concepts and Approaches
18.2.1.1. Detecting and Attributing Change in the Earth System
Detection and attribution is concerned with assessing the causal
relationship between one or more drivers and a responding system.
From an analysis perspective, the Earth system can be separated into
three coupled subsystems, referred to here as the climate system, the
natural system, and the human system (Figure 18-1). Separation of drivers
from a responding system is a crucial element of formal detection and
attribution analysis. Many external drivers may influence any system,
including the changing climate and other confounding factors (Hegerl
et al., 2010). Each of the three subsystems affects the other two directly
or indirectly. For example, the human system may directly affect the
natural system through deforestation, which in turn affects the climate
system through changes in albedo; this can alter surface temperatures,
which in turn feed back on natural and human systems. If an observed
c
hange in the human system impacts the climate system, we call this
an anthropogenic driver of climate change.
In this chapter we assess the impacts of climate change, where climate
change refers to any long-term trend in climate, irrespective of its cause
(see Glossary). The great majority of published scientific studies support
this type of assessment only. Some studies directly address the detection
of and attribution to anthropogenic climate change, relating observed
impacts, via the climate, to anthropogenic emissions of greenhouse gases
and other human activities. Because of the complexity of the causal
chain, investigation of this relationship is exceptionally challenging
(Parmesan et al., 2011). The findings from such studies are explicitly
highlighted in the chapter.
18.2.1.2. Concepts of Detection and Attribution of Climate
Change Impacts Used in this Chapter
“Detection of impacts” of climate change addresses the question of
whether a natural or human system is changing beyond a specified
baseline that characterizes its behavior in the absence of climate change
(Stone et al., 2013). The baseline may be stationary or non-stationary
(e.g., due to land use change), and needs to be clearly defined. This
definition of the detection of climate change impacts differs from that
in WGI AR5 Chapter 10 which concerns any change in a climate variable,
regardless of its cause. The definition adopted here focuses explicitly
P
F
Example of drivers
Example of Impacts
Direct impacts Subsequent impacts
Emission of CO
2
Warming Altered crop yield
Shift in species phenology
Emission of CO
2
Carbon fertilization
of plants
Increase in forestry yield
Change in humidity
Pollution of river
catchment
Fisheries collapse
Plague of crop pests Decrease in crop
yield
Forest fi re Change in humidity
El Nino event More wildfi res
El Nino event Crop Failures
D&A
WGII
D&A
WGII
D&A
WGI
E
x
t
e
r
n
a
l
N
a
t
u
r
a
l
F
o
r
c
i
n
g
Human
System
Natural
System
Climate
System
Anthropogenic climate driver
Other driver / Confounder
Working Group II
study area
Working Group II
study area
Working Group I
study area
Locations of detection
and attribution analyses
(D&A)
Direct impacts
Subsequent impacts
2
1
1
1
2
2
2
1
2b
2b
1b
1b
3
3 3
3
4
4 4
4
6
6
7
7
1a
1a
2a
2a
5
5
6
6
7
7
5
5
Figure 18-1 | Schematic of the subject covered in this chapter. The Earth system consists of three coupled and overlapping systems. Direct drivers of the human system on the
climate system are denoted with a red arrow; some of these drivers may also directly affect natural systems. These effects can in turn influence other systems (dashed red arrows).
Further influences of each of the systems on each other (confounding factors) that do not involve climate drivers are represented by blue arrows. Examples of drivers and their
impacts are given in the table. Adapted from Stone et al. (2013).
986
Chapter 18 Detection and Attribution of Observed Impacts
18
on the impact of climate change and not on trends related to other
factors. The statement of detection is binary: an impact has or has not
been detected.
“Attribution” addresses the question of the magnitude of the contribution
of climate change to a change in a system. In practice, an attribution
statement indicates how much of the observed change is due to climate
change with an associated confidence statement. Hence, attribution
requires the evaluation of the contributions of all external drivers to the
system change. In this chapter we simplify the assessment of this
relative contribution by specifying whether observed climate change
has had a “minor role” or a “major role” in the overall change in the
impacted system. A major role is assessed if the past behavior of the
system would have been grossly different in the absence of the observed
climate change.
18.2.2. Challenges to Detection and Attribution
Two broad challenges to the detection and attribution of climate change
impacts relate to observations and process understanding. On the
observational side, high-quality, long-term data relating to natural and
human systems and the multiple factors affecting them are rare. In
addition, the detection and attribution of climate change impacts requires
an understanding of the processes by which climate change, in conjunction
with other factors, may affect the system in question (see also Box 18-1).
These processes can be nonlinear—for example, involving threshold
effects (e.g., De Young and Jarre, 2009; Wassmann and Lenton, 2012)—
and non-local in both space and time, involving lagged responses and
trans-regional effects due, for example, to trade or migration.
Conclusions about the effect of climate change on natural and human
systems in this report are based on a synthesis of findings in the scientific
literature. A potential problem arises through the preferential publication
of papers reporting statistically significant findings (Parmesan and Yohe,
2003). Methods exist for detecting and correcting for publication bias in
formal quantitative synthesis analysis (Rothstein et al., 2005; Menzel et
al., 2006), but these methods cannot be applied in all situations (Kovats et
al., 2001). While the assessment in this chapter considers findings in the
context of consistency across studies, regions, and similar systems, it has
not been possible to quantitatively account for selection bias and to fully
differentiate it from the lack of monitoring for some regions and systems.
18.3. Detection and Attribution of Observed
Climate Change Impacts in Natural Systems
The following section provides a synthesis of findings with regard to
freshwater resources, terrestrial and inland water systems, coastal systems,
and oceans, which are documented in greater detail in Chapters 3, 4,
5, 6, and 30, respectively. It also incorporates evidence from regional
chapters and further available literature.
18.3.1. Freshwater Resources
Impacts of climate change on the hydrological cycle, and notably the
availability of freshwater resources, have been observed on all continents
and many islands, with different characteristics of change in different
regions (Chapters 3, 22 to 29; WGI AR5 Chapters 2 and 10). Figure 18-2
presents a synthesis of confidence in detection of global scale changes
in freshwater resources and related systems (notably slope stability and
erosion), and their attribution to climate change. Frozen components of
freshwater systems tend to show higher confidence in detection and
attribution, while components that are strongly influenced by non-
climatic drivers, such as river flow, have lower confidence.
Box 18-1 | Quantitative Synthesis Assessment of Detection and Attribution Studies in Ecological Systems
The wealth of observations in ecological systems now permits the application of quantitative tools for synthesis assessment of
detection and attribution (Root et al., 2005). These tools include associative pattern analyses (e.g., Rosenzweig et al., 2008) and
regression analyses (Chen, I.C. et al., 2011), which compare expected changes due to anthropogenic climate change across multiple
studies against observed changes.
Quantitative synthesis assessments have been particularly prominent in ecology, where measures of phenology (timing of seasonal
events) and geographical range can be assembled across species into standardized indices (Parmesan and Yohe, 2003; Rosenzweig et
al., 2008; Chen, I.C. et al., 2011; Poloczanska et al., 2013; Rosenzweig and Neofotis, 2013). Confidence in the detection of general
patterns of change in these indices can increase with the number of species/ecosystems observed, the number of independent studies,
the geographical distribution of these observations, the temporal depth and resolution of the data, and the representativeness of
species/ecosystems and locations studied. However, increasing spatial coverage, numbers of species, and so forth does not a priori
increase confidence that climate change is a more credible explanation for biological change than alternative hypotheses. Additional
data can contribute to increased confidence in causal relationships, that is, attribution, in a synthesis assessment when it provides
new evidence for explicit testing against a credible range of alternative hypotheses.
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Detection and Attribution of Observed Impacts Chapter 18
18
18.3.1.1. The Cryosphere
Most components of the cryosphere (glaciers, ice sheets, and floating ice
shelves; sea, lake, and river ice; permafrost and snow) have undergone
significant changes during recent decades (high confidence), related to
climatic forcing (high confidence; WGI AR5 Chapter 4). It is likely that
there is an anthropogenic component in the changes observed in Arctic
sea ice, Greenland’s surface melt, glaciers, and snow cover (WGI AR5
Section 10.5). Glaciers continue to shrink worldwide, with regional
variations. It is likely that a substantial part of the glacier mass loss is
due to anthropogenic warming (WGI AR5 Section 10.5.2.2). Climate
change has a major role in the absolute contribution of ice loss from
glaciers and ice caps to sea level rise, which has increased since the
early 20th century and has now been close to 1 mm yr
–
1
for the past
2 decades (WGI AR5 Sections 4.3.3, 4.4.3), around a third of total
observed sea level rise. Recent mass loss of ice sheets and glaciers has
accelerated isostatic land uplift in the North Atlantic Region (Jiang et al.,
2010). In several high-mountain regions, slope instabilities have occurred
as a consequence of recent glacier downwasting (high confidence;
Vilímek et al., 2005; Haeberli and Hohmann, 2008; Huggel et al., 2011).
The role of climate in changes in runoff decreases from major to minor
as the distance from glaciers increases and other non-climatic factors
become more important. Runoff from glacier areas has increased for
catchments in western and southwestern China over the past several
decades, and in western Canada and Europe (Collins, 2006; Zhang, Y. et
al., 2008; Moore et al., 2009; Li et al., 2010; Pellicciotti et al., 2010; Stahl
et al., 2010). Glacier runoff has decreased in the European Alps (Collins,
2006; Huss, 2011), in the central Andes of Chile (Casassa et al., 2009),
and in the Cordillera Blanca (Baraer et al., 2012; medium confidence), a
trend that has also been confirmed by qualitative observations made
by local people (Bury et al., 2010; Carey et al., 2012a). For lake and river
i
ce, there is generally high confidence in detection of, and a major role
of climate change in, later freeze-up and earlier break-up over the past
100+ years for several sites in the NH, yet with regional differences and
warmer regions showing higher sensitivities in interannual variability
(Livingstone et al., 2010; Voigt et al., 2011; Weyhenmeyer et al., 2011;
Benson et al., 2012). Changes in lake and river ice can have effects on
freshwater ecosystems, transport and traffic over frozen lakes and rivers,
and ice-induced floods during freeze-up and break-up events (Voigt et
al., 2011). Some evidence exists in Europe that ice-jam floods were
reduced during the last century due to reduced freshwater freezing
(Svensson et al., 2006).
The rate of Arctic sea ice decline has increased significantly during the
first decade of the 21st century, due to warming (WGI AR5 Section
4.2.2). It is very likely that at least some of the decline in Arctic sea ice
extent can be attributed to anthropogenic climate forcing (WGI AR5
Section 10.5.1). Observations by Inuit people in the Canadian Arctic
confirm with high confidence the instrumental observations on the
various changes of sea ice (see Box 18-5). Antarctic sea ice has slightly
increased over the past 30 years, yet with strong regional differences
(WGI AR5 Section 4.2.3).
Combined in situ and satellite observations indicate a decline of 8% in
NH spring snow cover extent since 1922 (WGI AR5 Section 4.5.2). A
limited number of studies indicate an anthropogenic influence on snow
cover reduction (high confidence; WGI AR5 Section 10.5.3), including a
significant contribution of anthropogenic climate forcing on changes in
snow pack and runoff timing between 1950 and 1999 in the western
USA (Table 18-6; Barnett et al., 2008).
Climate change generally exerts a major role on permafrost changes.
Widespread permafrost warming and thawing, and active layer thickening
10
9
3
1
2
4
8
6
5
7
11
Very low Low Medium
Confidence in attribution
High
Very high
Very low Low Medium
Confidence in detection
High Very high
1. Shrinking glaciers (Section 3.2.2)
2. Changes in glacier lakes
3. Erosion and degradation of Arctic coastal permafrost
4. Degradation and thaw of lowland and mountain permafrost
5. Groundwater storage change (Section 3.2.4)
6. Changing river flow (Section 3.2.3)
7. Changing flood frequency or intensity (Section 3.2.7)
8. Reduction in lake and river ice duration or thickness in the Northern
Hemisphere
9. Increasing erosion (Section 3.2.6)
10. Changes in shallow landslides (Section 3.2.6)
11. Increasing frequency of high-mountain rock failures
Cryosphere (Section 18.3.1.1)
Rivers, lakes, and groundwater (Section 18.3.1.2)
Erosion and landslides (Section 18.3.1.3)
Figure 18-2 | Assessment of confidence in detection of observed climate change impacts in global freshwater systems over the past several decades, with confidence in
attribution of a major role of climate change, based on expert assessment contained in Section 18.3.1 and augmented by subsections of Chapter 3 as indicated.
988
Chapter 18 Detection and Attribution of Observed Impacts
18
i
n both high-latitude lowlands and high-elevation mountain regions,
have been observed over the past decades (high confidence; WGI AR5
Section 4.7.2). Climate change impacts have been related to permafrost
changes, including an increase of flow speed of rock glaciers and debris
lobes in the European Alps and Alaska (high confidence), resulting in
rockfall, debris flows, and potential hazards to transport and energy
systems (Kääb et al., 2007; Delaloye et al., 2010; Daanen et al., 2012),
expansion, deepening and higher dynamics of thermokarst lakes and
ponds in the Arctic (Rowland et al., 2010), and a doubled erosion rate
of Alaska’s northern coastline over the past 50 years (high confidence;
Section 18.3.3.1, Table 18-8; Mars and Houseknecht, 2007; Karl et al.,
2009; Forbes, 2011). Expansion of channel networks (Toniolo et al.,
2009), increased river bank erosion (Costard et al., 2007), and an increase
in hillslope erosion and landsliding in northern Alaska since the 1980s
(Gooseff et al., 2009) have all been related to climate. Warming and
thawing of permafrost in Alaska has adversely affected transport and
energy structures and their operation (Karl et al., 2009). Feedbacks and
interactions complicate detection of drivers and effects. For example,
drying of land surface due to permafrost degradation may cause an
increase in wildfires, in turn resulting in a loss of ground surface
insulation and change in surface albedo that accelerates permafrost
thawing (Rowland et al., 2010; Forkel et al., 2012).
18.3.1.2. The Regional Water Balance
The regional water balance is the net result of gains (precipitation, ice
and snow melt, river inflow, and groundwater recharge) and losses
(evapotranspiration, water use and river outflow, and groundwater
discharge). Impacts of climate change include reduced availability of
freshwater for use (one of the variables defining drought) or excess water
(floods). Evapotranspiration, being a function of solar radiation, surface
temperature, vegetation cover, soil moisture, and wind, is affected by the
changing climate, but also by changing vegetation processes and land
cover. At the global scale, human influence has contributed to large-
scale changes in precipitation patterns over land and, since the mid-
20th century, in extreme precipitation (medium confidence; WGI AR5
Section 10.6.1.2; Min et al., 2011). More locations worldwide have
experienced an increase than a decrease in heavy rainfall events, yet
with significant regional and seasonal variations (Seneviratne et al.,
2012; Westra et al., 2013). In some regions, however, there is medium
confidence that anthropogenic climate change has affected streamflow
and evapotranspiration (WGI AR5 Section 10.3.2.3).
Change in river flow is a direct indicator of a changing regional water
balance. Globally, about one-third of the top 200 rivers (ranked by river
flow) show statistically significant trends during 1948–2004, with more
rivers having reduced flow (45) than rivers with increased flow (Dai et
al., 2009). Regional reductions in precipitation in southwestern South
America are primarily due to internal variability (Dai, 2011; see also
Section 27.2.1.1). River floods, defined as impacts caused by the over-
topping of river banks and levées, have shown statistically significant
increasing and decreasing trends in some regions. The role of climate
change in these changes is uncertain, as they may reflect decadal
climate variability and be affected by other confounding factors such
as human alteration of river channels and land use (Section 3.2.7). In
regions with detected increases in heavy rainfall events (North America,
E
urope), both increases and decreases in floods have been found
(medium confidence in detection; Petrow and Merz, 2009; Villarini et
al., 2009). In the UK, flood risk has increased due to anthropogenic
forcing for events comparable to the 2000 floods (Kay et al., 2011; Pall
et al., 2011; see also Section 18.4.3).
Expanding or new lakes as a result of ice melt at the margin of many
shrinking glaciers in the Alps of Europe, Himalayas, Andes, and other
mountain regions have altered the risk of glacier lake outburst floods
(GLOFs) and required substantial risk reduction measures in the 21st
century (Huggel et al., 2011; Carey et al., 2012b). Though there is no
evidence for a change in frequency or magnitude of GLOFs (Seneviratne
et al., 2012), climate change has had a major role in the substantial
increase in glacial lake area in the eastern Himalaya region between
1990 and 2009 (Gardelle et al., 2011), and the similarly strong increase
in lake numbers in the Andes of Peru in the second half of the 20th
century (Carey, 2005), and in northern Patagonia from 1945 to 2011
(Loriaux and Casassa, 2013; high confidence in detection). New
glacier lakes are not only an additional source of floods but also
have become a tourist attraction, led to additional infrastructure, and
stimulated assessment of potential for hydropower generation (Terrier
et al., 2011).
Since the 1950s some regions of the world have experienced more
intense and longer droughts, although a global trend currently cannot
be established (Seneviratne et al., 2012; see also Section 3.2.2 and
WGI AR5 Section 2.6.2.3). Longer drought periods have affected
groundwater recharge (Leblanc et al., 2009; Taylor et al., 2013), but
changes in groundwater storage are generally difficult to attribute to
climate change, due to confounding factors from human activities (Table
3-1; Rodell et al., 2009; Taylor et al., 2013). Likewise, confounding factors
do not permit attribution of observed changes in water quality to climate
change (Kundzewicz and Krysanova, 2010; see also Section 3.2.5).
18.3.1.3. Erosion, Landslides, and Avalanches
Erosion and landsliding typically increase in phase with deglaciation in
mountain areas (Ballantyne, 2002; Korup et al., 2012), and there is
emerging evidence for this to occur during contemporary deglaciation
(Schneider et al., 2011; Uhlmann et al., 2013). In the western Himalaya,
sediment flux has increased (medium confidence; Wulf et al., 2012)
and been related to hydrologic extreme events over the past 60 years
(low confidence; Malik et al., 2011), with important consequences for
hydropower schemes. In China, a drastic decrease of sediment load in
the Yangtze River was observed since the 1980s. There have been local
variations in precipitation and runoff since 1950, but changes in
sediment load are attributed primarily to more than 50,000 dams and
vegetation changes (medium confidence; Xu et al., 2008). There is clear
evidence for decline in sediment load in the Zhujiang (Pearl River) basin
since the early 1990s (Zhang, S. et al., 2008).
In the European Alps, no clear evidence exists so far for any change in
frequency of shallow landslides and debris flows from recently
deglaciated mountain areas (Jomelli et al., 2004; Stoffel and Huggel,
2012). In some cases climate change has had a major role in influencing
frequency and magnitude of alpine shallow landslides and debris flows
989
Detection and Attribution of Observed Impacts Chapter 18
18
b
y altering sediment yield, for example, from rockfall or disintegration
of rock glaciers (low confidence; Lugon and Stoffel, 2010).
Glacier shrinkage, permafrost degradation, and high-temperature events
have contributed to many high-mountain rock slope failures since the
1990s (medium confidence in major role of climate change; Allen et al.,
2010; Ravanel and Deline, 2011; Schneider et al., 2011; Fischer et al.,
2012; Huggel et al., 2012a). Rock slope failures have increased over this
period in the Western Alps of Europe (high confidence), the New Zealand
Alps (medium confidence), and globally (low confidence). Cascading
processes of permafrost and ice-related landslides impacting lakes and
downstream areas have been observed in many high-mountain regions,
causing major damages and risk reduction measures (high confidence),
with climate change exerting a major role (medium confidence; e.g.,
Xin et al., 2008; Bajracharya and Mool, 2009; Künzler et al., 2010; Carey
et al., 2012a; Huggel et al., 2012b). For landslide types other than the
above, there is no clear evidence that their frequency or magnitude has
changed over the past decades (Huggel et al., 2012b). In general,
detection of changes in the occurrence of landslides is complicated by
incomplete inventories, both in time and space, and inconsistency in
terminology.
Physical understanding suggests that climate change has a major role
in changes of snow avalanche activity but no such changes have been
reported so far (medium confidence; Laternser and Schneebeli, 2002;
Voigt et al., 2011), except for the French Alps (Eckert et al., 2013;
medium confidence in detection). The detection of changes in snow
avalanche impacts, such as fatalities and property loss, is difficult over
the past decades because of changes in snow sport activities and
avalanche defense measures.
18.3.2. Terrestrial and Inland Water Systems
As documented by previous IPCC reports (notably Rosenzweig et al.,
2007), climate-driven changes in terrestrial and inland water systems
are widespread and numerous. Confidence in such detection of change
is often very high, reflecting high agreement among many independent
sources of evidence of change, and robust evidence that changes in
ecosystems or species are outside of their natural variation. Confidence
in attribution to climate change is also often high, due to process
understanding of responses to climate change, or strong correlations
with climate trends and where confounding factors are understood to
have limited importance (Sections 4.3.2, 4.3.3, Figure 4-4). The scientific
literature in this field is growing quickly; detailed traceability is provided
in Chapter 4.
Organisms respond to changing climate in a multitude of ways, including
through their phenology (the timing of key life history events such as
flowering in plants or migration of birds), productivity (the assimilation
of carbon and nutrients in biomass), spatial distribution, mortality/
extinction, or by invading new territory. Noticeable changes may occur
at the level of individual organisms, ecosystems, landscapes, or by
modification of entire biomes. Organisms and ecosystems are adapted
to a variable environment, and they are capable of adapting to gradual
change to some degree. Assessing confidence in the detection of such
change therefore involves assumptions about natural variability in these
e
cosystems, while assessment of confidence in the attribution of
detected change to climate drivers (or carbon dioxide (CO
2
)) implies the
assessment of confounding drivers such as pollution or land use change.
18.3.2.1. Phenology
Since the AR4 there has been a further substantial increase in observations,
showing that hundreds of (but not all) species of plants and animals
have changed functioning to some degree over the last decades to
centuries on all continents (high confidence due to robust evidence but
only medium agreement across all species; Section 4.3.2.1; Menzel et
al., 2006; Cook et al., 2012b; Peñuelas et al., 2013). New satellite-based
analyses confirm earlier trends, showing, for example, that the onset of
the growing season in the NH has advanced by 5.4 days from 1982 to
2008 and its end has been delayed by 6.6 days (Jeong et al., 2011).
Significant changes have been detected, by direct observation, for many
different species, for example, for amphibians (e.g., Phillimore et al., 2010),
birds (e.g., Pulido, 2007; Devictor et al., 2008), mammals (e.g., Adamík
and Král, 2008), vascular plants (e.g., Cook et al., 2012a), freshwater
plankton (Adrian et al., 2009), and others (Section 4.3.2.1); a number
of new meta-analyses have been carried out summarizing this literature
(e.g., Cook et al., 2012a). Attribution of these changes to climate change
is supported by more refined analyses that consider also the regional
changes in several variables such as temperature, growing season
length, precipitation, snow cover duration, and others, as well as
experimental evidence (Xu et al., 2013). The high confidence in attributing
many observed changes in phenology to changing climate is a result of
these analyses, as well as of improved knowledge of confounding factors
such as land use and land management (see also Section 4.3.2.1).
18.3.2.2. Productivity and Biomass
Many terrestrial ecosystems are now net sinks for carbon over much of
the NH and also in parts of the Southern Hemisphere (high confidence;
see also Sections 4.3.2.2-3). This is shown, for example, by inference
from atmospheric chemistry, but also by direct observations of increased
tree growth in many regions including Europe, the USA, tropical Africa,
and the Amazon. During the decade 2000 to 2009, global land net
primary productivity was approximately 5% above the preindustrial
level, contributing to a net carbon sink on land of 2.6±1.2PgC yr
–1
(Section 4.3.2.2; WGI AR5 6.3.2.6; for primary literature, see also Raupach
et al., 2008; Le Quéré et al., 2009), despite ongoing deforestation.
Forests have increased in biomass for several decades in Europe
(Luyssaert et al., 2010) and the USA (Birdsey et al., 2006). These trends
are in part due to nitrogen deposition, afforestation, and altered land
management which makes direct attribution of the increase to climate
change difficult. The degree to which rising atmospheric CO
2
concentrations contribute to this trend remains a particularly important
source of uncertainty (Raupach et al., 2008). Canadian managed forests
increased in biomass only slightly during 1998-2008, because growth
was offset by significant losses due to fires and beetle outbreaks (Stinson
et al., 2011). In the Amazon forest biomass has generally increased in
recent decades, dropping temporarily after a drought in 2005 (Phillips
et al., 2009). A global analysis of long-term measurements suggests that
soil respiration has increased over the past 2 decades by approximately
990
Chapter 18 Detection and Attribution of Observed Impacts
18
0
.1PgCyr
–1
,
some of which may be due to increased productivity (Bond-
Lamberty and Thomson, 2010). Man-made impoundments in freshwater
ecosystems represent an increasing and short-lived additional carbon
store with conservative annual estimates of 0.16 to 0.2PgCyr
–
1
(Cole
et al., 2007).
1
8.3.2.3. Species Distributions and Biodiversity
Each species responds differently to a changing environment; therefore
the composition of species, genotypes, communities, and even ecosystems
varies in different ways from place to place, in response to climate
change. The consequences are changing ranges of species, changing
composition of the local species pool, invasions, mortality, and ultimately
extinctions. For different species and species groups, detected range
shifts vary, and so do the confidence of detection and the degree of
attribution to climate change. The number of species studied has
considerably increased since the AR4. Overall, many terrestrial species
have recently moved, on a global average, 17 km poleward and 11 m
up in altitude per decade (e.g., Europe, North America, Chile, Malaysia),
which corresponds to predicted range shifts due to warming (Chen, I.C.
et al., 2011) and is two to three times faster than previous estimates
(Parmesan and Yohe, 2003; Fischlin et al., 2007), with high confidence
in detection. Europe forest species are moving up in altitude, probably
due to climate warming at the end of the 20th century (Gehrig-Fasel et
al., 2007; Lenoir et al., 2008). Species with short life cycles and high
dispersal capacity—such as butterflies (high confidence in a major
role of climate change)—are generally tracking climate more closely
than longer-lived species or those with more limited dispersal such as
trees (Devictor et al., 2012; medium confidence in a major role of
climate change). There are many less well-studied species for which
detection of change and its attribution to climate change are more
uncertain.
Changes in abundance, as measured by changes in the population size
of individual species or shifts in community structure within existing
range limits, have occurred in response to recent global warming (Thaxter
et al., 2010; Bertrand et al., 2011; Naito and Cairns, 2011; Rubidge et
al., 2011; Devictor et al., 2012; Tingley et al., 2012; Vadadi-Fülöp et al.,
2012; Cahill et al., 2013; Ruiz-Labourdette et al., 2013), but owing to
confounders, confidence in a major role of climate change is often low.
Across the world, species extinctions are at or above the highest rates
of species extinction in the fossil record (high confidence; Barnosky et
al., 2011). However, only a small fraction of observed species extinctions
have been attributed to climate change—most have been ascribed to
non-climatic factors such as invasive species, overexploitation, or habitat
loss (Cahill et al., 2013). For those species where climate change has been
invoked as a causal factor in extinction (such as for the case of Central
American amphibians), there is low agreement among investigators
concerning the importance of climate variation in driving extinction and
even less agreement that extinctions were caused by climate change
(Pounds et al., 2006; Kiesecker, 2011). Confidence in the suggested
attribution of extinctions across all species to climate change is very
low (see also Section 4.3.2.5).
Species invasions have increased over the last several decades
worldwide, notably in freshwater ecosystems (very high confidence),
o
ften causing biodiversity loss or other negative impacts. There is only
low confidence that species invasions have generally been assisted by
recent climatic trends because of the overwhelming importance of
human facilitated (intentional or non-intentional) dispersal in the transfer
from the area of origin. Once established in a new environment, many
introduced species have recently become invasive due to climate change
(medium to high confidence, depending on the taxon; see also Section
4.2.4.6).
18.3.2.4. Impacts on Major Systems
Field and satellite measurements indicate substantial changes in
freshwater and terrestrial ecosystems (often linked to permafrost
thawing) in many areas of the Arctic tundra (high confidence; Hinzman
et al., 2005; Axford et al., 2009; Jia et al., 2009; Post et al., 2009; Prowse
and Brown, 2010; Myers-Smith et al., 2011; Walker et al., 2012).
Vegetation productivity has systematically increased over the past few
decades in both North America and northern Eurasia (Goetz et al., 2007;
Jia et al., 2009; Elmendorf et al., 2012). Most subpopulations of the
polar bear are declining in number (Vongraven and Richardson, 2011).
These changes correspond to expectations, based on experiments,
models, and paleoecological responses to past warming, of broad-scale
boreal forest encroachment into tundra, a process that takes decades
and that would have very large impacts on ecosystem structure and
function. The particular strength of warming over the last 50 years for
most of the Arctic further facilitates attribution of a major role of climate
change (high confidence). The change affects a significant area of the
tundra biome and can be considered an early warning for an ongoing
regime shift (Section 4.3.3.4, Figure 4-4).
For the boreal forest, increases in tree mortality are observed in many
regions, including widespread dieback related to insect infestations
and/or fire disturbances in North America (Fauria and Johnson, 2008;
Girardin and Mudelsee, 2008; Kasischke et al., 2010; Turetsky et al.,
2010; Wolken et al., 2011) and in Siberia (Soja et al., 2007), but there is
low confidence in detection of a global trend. Many areas of boreal
forest have experienced productivity declines (high confidence; Goetz
et al., 2007; Parent and Verbyla, 2010; Beck and Goetz, 2011), related
to warming-induced drought, specifically the greater drying power of
air (Williams et al., 2012), inducing photosynthetic down-regulation of
boreal tree species not adapted to the warmer conditions (Welp et al.,
2007; Bonan, 2008). Conversely, productivity has increased along the
boreal-tundra ecotone where more mesic (moist) conditions may be
generating the expected warming-induced positive growth response
(McGuire et al., 2007; Goldblum and Rigg, 2010; Beck and Goetz, 2011).
Overall, these multiple impacts in the boreal forest biome can be
considered an early warning for an ongoing regime shift only with low
confidence (Section 4.3.3.1.1, Figure 4-4). Many of the aforementioned
changes take place in the tundra-boreal ecotone, affecting both biomes
significantly (Box 4-4, Figure 4-10).
In tropical forests, climate change effects are difficult to identify against
the confounding effects of direct human influence as is well illustrated
for the Amazon forest (Davidson et al., 2012) but also applies elsewhere.
Since AR4, there is new evidence of more frequent severe drought
episodes in the Amazon region that are associated with observed sea
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Detection and Attribution of Observed Impacts Chapter 18
18
s
urface temperature increases in the tropical North Atlantic (medium
confidence; Marengo et al., 2011a). There is low confidence, however,
that these changes can be attributed to climate change (Section
4.3.3.1.3). There is medium confidence that tree mortality in the Amazon
region has increased due to severe drought and increased forest fire
occurrence and low confidence that this can be attributed to warming
(Section 4.3.3.1.3, Figures 4-4, 4-8).
In freshwater ecosystems of most continents and climate zones, rising
temperatures have been linked to shifts in invertebrate and fish
community composition, especially in headwater streams where species
are more sensitive to warming (Brown et al., 2007; Durance and Ormerod,
2007; Chessman, 2009; see also Section 4.3.3.3; high confidence in
detection, low confidence in a major role of climate change due to
numerous confounding factors). Long-term shifts in macroinvertebrate
communities have been observed in European lakes where temperatures
have increased (Burgmer et al., 2007).
18.3.3. Coastal Systems and Low-Lying Areas
Coastal systems are influenced by many anthropogenic and natural
processes. Important climate-related drivers include changes in ocean
temperature, salinity, and pH; and sea level (see Table 5-2). In coastal
waters, both annual and seasonal changes in temperature tend to be
larger than the average rate for the open ocean (Section 5.3.3). Sea
surface temperatures have increased significantly during the past 30
years along more than 70% of the world’s coastlines, with large spatial
and seasonal variation, and the frequency of extreme temperature
events in coastal waters has changed in many areas (Lima and Wethey,
2012). Seawater pH spans larger ranges and exhibits higher variability
near coastlines, and anthropogenic ocean acidification can be enhanced
or reduced by coastal geochemical processes (Borges and Gypens, 2010;
Feely et al., 2010; Duarte et al., 2013, see also Box CC-OA).
While it is likely that extreme sea levels have increased globally since
the 1970s, mainly as a result of mean sea level rise due in part to
anthropogenic warming (WGI AR5 Sections 3.7.5-6, 10.4.3), local sea
level trends are also influenced by factors such as regional variability
in ocean and atmospheric circulation, subsidence, isostatic adjustment,
coastal erosion, and coastal modification (see also Section 5.3.2). As a
consequence, the detection of the impact of climate change in observed
changes in relative sea level remains challenging (Nicholls et al., 2007,
2009; Menéndez and Woodworth, 2010). An exception is lower sea level
in regions of isostatic rebound in response to reduced ice cover due to
climate change (Kopp et al., 2010; Tamisiea and Mitrovica, 2011). In
these regions, climate change has played a major role in the lowering
sea level (medium confidence).
18.3.3.1. Shoreline Erosion and Other Coastal Processes
Throughout the world, the rate of shoreline erosion is increasing
(Section 5.4.2.1). While processes related to climate change, such as
rising mean sea levels (Leatherman et al., 2000; Ranasinghe and Stive,
2009), more frequent extreme sea levels (Woodworth et al., 2011), or
permafrost degradation and sea ice retreat (Forbes, 2011) can be
e
xpected to enhance global erosion, there are multiple drivers involved
in shoreline erosion that are unrelated to climate change including long
shore sediment transport; the diversion of sediments by dams; and
subsidence due to resource extraction, mining, and coastal engineering
and development (see also Table 5-3). Owing to the fragmentary nature
of the information available, and to the multiple natural and anthropogenic
stressors contributing to coastal erosion, confidence in detection of a
climate change contribution to observed shoreline changes is very low,
with the exception of polar regions (Table 18-8; Mars and Houseknecht,
2007; Forbes, 2011).
Coastal lagoons and estuaries, as well as deltas, are highly susceptible
to alterations of sediment input and accumulation (Syvitski et al., 2005;
Ravens et al., 2009), processes that can be influenced by climate change
via changes in mean and extreme sea levels, storminess, and precipitation.
However, the primary drivers of widespread observed changes in those
systems are human drivers other than climate change so that there is
very low confidence in the detection of impacts related to climate change
(Section 5.4.2).
Coastal aquifers are crucial for the water supply of densely populated
coastal areas, in particular in small island environments and dry
climates. Aquifer recharge is sensitive to changes in temperature and
precipitation, and rising sea levels and saltwater overwash from storm
surges can contribute to saline intrusion into groundwater (Post and
Abarca, 2010; Terry and Falkland, 2010; White and Falkland, 2010; see
also Section 29.3.2, Table 18-8). However, groundwater extraction for
coastal settlements and agriculture is the main cause for widely
observed groundwater degradation in coastal aquifers (e.g., White et
al., 2007a; Barlow and Reichard, 2010). It is not yet possible to detect
the impact of climate change on coastal aquifers with any degree of
confidence (Rozell and Wong, 2010; White and Falkland, 2010).
Changes in water column mixing have combined with other factors such
as nutrient loading to drive down oxygen concentrations and increase
the number and extent of hypoxic zones (Vaquer-Sunyer and Duarte,
2011). These zones are characterized by very low oxygen and high CO
2
levels and, in some cases, exert strong local and regional effects on
marine biota such as distribution shifts, habitat contraction or loss, and
fish kills (Diaz and Rosenberg, 2008). The operation of other factors
makes the detection of a climate change impact on the frequency,
distribution, and intensity of hypoxia possible with only medium
confidence and it is difficult to assess the relative magnitude of this
impact (see Table 18-1).
18.3.3.2. Coastal Ecosystems
Coastal habitats and ecosystems experience cumulative impacts of
land- and ocean-based anthropogenic stressors (Halpern et al., 2008).
Most coral reefs, seagrass beds, mangroves, rocky reefs, and shelves
have undergone substantial changes over the course of the last century.
Fishing and other extractive activities, land use changes, and pollution
have been responsible for a large proportion of these historical changes
(Lotze et al., 2006). Biological responses to changes in the temperature,
chemistry, and circulation of the ocean are complex and often interact
with other anthropogenic factors.
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Chapter 18 Detection and Attribution of Observed Impacts
18
Coral reefs have been degraded due both to local anthropogenic factors
such as fishing, land use changes, and pollution and to ocean warming
related to climate change and also possibly to acidification (see Box
CC-CR). Over the past 30 years, mass coral bleaching has been detected
with very high confidence on all coasts, and warming is a major
contributor (high confidence; for further discussion see Boxes 18-2,
CC-OA).
Changes in abundance and distribution of rocky shore species have
been observed since the late 1940s in the Northeast Atlantic (Hawkins
et al., 2008), and the role of temperature has been demonstrated by
experiments and modelling (Poloczanska et al., 2008; Wethey and
Woodin, 2008; Peck et al., 2009; Somero, 2012; see also Section 5.4.2.2).
Globally, the ranges of many rocky shore species have shifted up to
50 km per decade, much faster than most recorded shifts of terrestrial
species (Helmuth et al., 2006; Poloczanska et al., 2013; see also Box
18-3). However, distinguishing the response of these communities to
climate change from those due to other natural and anthropogenic
causes is challenging. Weak warming, overriding effects of confounding
factors, or biogeographic barriers can explain the fact that geographical
distribution of some species did not change over the past decades
(Helmuth et al., 2002, 2006; Rivadeneira and Fernández, 2005; Poloczanska
et al., 2011).
Ocean warming has contributed to observed range shifts in vegetated
coastal habitats such as coastal wetlands, mangrove forests and seagrass
meadows (Section 5.4.2.3). Poleward expansion of mangrove forests,
consistent with expected behavior under climate change, has been
observed in the Gulf of Mexico (Perry and Mendelssohn, 2009; Comeaux
et al., 2012; Raabe et al., 2012) and New Zealand (Stokes et al., 2010).
High temperatures have impacted seagrass biomass in the Atlantic
Ocean (Reusch et al., 2005; Díez et al., 2012; Lamela-Silvarrey et al.,
2012), the Mediterranean Sea (Marbà and Duarte, 2010), and Australian
waters (Rasheed and Unsworth, 2011). Extreme weather events also
contributed to the overall degradation of seagrass meadows in a
Portuguese estuary (Cardoso et al., 2008).
Decline in kelp populations attributed to ocean warming has occurred
off the north coast of Spain (Fernández, 2011), as well as in southern
Australia, where the poleward range expansion of some herbivores have
also contributed to observed kelp decline (Ling, 2008; Ling et al.,
2009a,b; Johnson et al., 2011; Wernberg et al., 2011a). The spread of
subtropical invasive macroalgal species (e.g., Lima et al., 2007) may be
adding to the stresses temperate seagrass meadows experience from
ocean warming. Extreme temperature events can alter marine and
coastal communities, as shown, for example, for the European 2003
heat wave (Garrabou et al., 2009), and the early 2011 heat wave off
the Australian west coast (Wernberg et al., 2012).
In summary, there is high confidence in the detection of the impact of
climate change on the abundance and distribution of a range of coastal
species and medium confidence that climate change has played a major
role in many cases. In specific cases, such as the decline of salt marshes
and mangroves, the impact of climate change has been detected with
very low confidence owing to the overriding effect of land use changes,
pollution, and other factors unrelated to climate change.
Box 18-2 | Attribution of Mass Coral Bleaching Events to Climate Change
A critical source of energy for the maintenance and growth of coral is provided by symbiotic brown algae. Coral bleaching occurs
when these symbionts leave their host. Bleaching events have deleterious impacts on corals and, depending on their severity and
duration, can cause death. It is known that thermal stress can trigger coral bleaching (Muscatine, 1986; Hoegh-Guldberg and Smith,
1989; Jones et al., 1998). Mass bleaching events that affect entire reefs or coastal regions can occur when local or regional temperatures
exceed the typical summer maximum for a period of a few weeks (Hoegh-Guldberg, 1999; Baker et al., 2008; Strong et al., 2011). The
effect of elevated temperature is exacerbated by strong solar irradiance (Hoegh-Guldberg, 1999).
Since 1980, mass coral bleaching events have occurred throughout the tropics and subtropics at a rate without precedent in the
literature (see also Boxes CC-CR and CC-OA, and Section 5.4.2.4). These events have often been followed by mass mortality (Hoegh-
Guldberg, 1999; Baker et al., 2008). In the very warm year of 1998, for example, mass bleaching occurred in almost every part of the
tropics and subtropics and resulted in the loss of a substantial fraction of the world's corals (Wilkinson et al., 1999). A large-scale
bleaching event also occurred in the Caribbean during 2005 (Eakin et al., 2010).
Declining water quality, coastal development, increased fishing, and even tourism have also been implicated in the decline of coral
communities over the past 50 years (Bryant et al., 1998; Gardner et al., 2003; Bruno and Selig, 2007; Sheppard et al., 2010; Burke et al.,
2011; De'ath et al., 2012). However, given the scope of recent mass bleaching events, their co-occurrence with elevated temperatures,
and a physiological understanding of the role of temperature in bleaching, there is very high confidence in the detection of the
impact of climate change and high confidence in the finding that climate change has played a major role.
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Detection and Attribution of Observed Impacts Chapter 18
18
18.3.3.3. Coastal Settlements and Infrastructure
Total damages from coastal flooding have increased globally over the
last decades (high confidence); however, with exposure and subsidence
constituting the major drivers, confidence in detection of a climate change
impact is very low (Seneviratne et al., 2012, see also Sections 5.4.3.2,
5.4.4).
Recent global (e.g., Menéndez and Woodworth, 2010; Woodworth et
al., 2011) and regional (e.g., Marcos et al., 2009; Haigh et al., 2010,
2011) studies have found increases in extreme sea levels consistent
with mean sea level trends (see also Table 5-2), indicating that the
increasing frequency of extreme water levels affecting coastal
infrastructures observed so far is related to rising mean sea level rather
than to changes in the behavior of severe storms. While vulnerability
of coastal settlements and infrastructure to future climate change, in
particular sea level rise and coastal flooding, is widely accepted and
well documented (see Section 5.5), there is a shortage of studies
discussing the role of climate change in observed impacts on coastal
systems.
Increases in saltwater intrusion and flooding have been observed in
low-lying agricultural areas of deltaic regions and small islands, but the
contribution of climate change to this is not clear (e.g., Rahman et al.,
2011; see also Sections 5.4.2.5, 5.4.3.3). While both climate change
impacts on physiological and ecological properties of fish (e.g., Barange
and Perry, 2009; see also Section 18.3.4) and vulnerability of coastal
communities and fisherfolks to climate fluctuations and change (Badjeck
et al., 2010; Cinner et al., 2012) are well established in the literature,
there is limited evidence for observed effects of climate change on
coastal fishery operations (see also Section 18.4.1.2).
18.3.4. Oceans
Since 1970, ocean temperatures have increased by around 0.1°C per
decade in the upper 75 m and approximately 0.015°Cper decade at
700 m (see Section 30.3.1.1). It is very likely that the increase in global
ocean heat content observed in the upper 700 m since the 1970s has a
substantial contribution from anthropogenic forcing (WGI AR5 Section
10.4.1).
The increased flux of CO
2
from the atmosphere to the ocean has reduced
the average pH of sea water by about 0.1 pH units over the past century,
with the greatest reduction occurring at high latitudes (see also Box CC-
OA). These changes have been attributed to increases in the atmospheric
concentration of greenhouse gases as result of human activities (very
high confidence; WGI AR5 Section 10.4.4). Changes in wind speed,
upwelling, water column stratification, surface salinity, ocean currents,
and oxygen depth profile have also been been detected with at least
medium confidence (WGI AR5 Chapter 3; Figures 30-5, 30-6).
Changes in the physical and chemical nature of ocean environments
are predicted to have impacts on marine organisms and ecosystems,
with many already having been observed across most ocean regions
(Sections 6.2-3, 30.4-5). However, the detection of these predicted
changes and the assessment of the role of climate change in them are
complicated by the influence of long-term variability such as the Pacific
Decadal Oscillation (PDO) and the Atlantic Multi-decadal Oscillation
(AMO). The fragmentary nature of ocean observations and the influence
of confounding factors such as fishing, habitat alteration, and pollution
also represent significant challenges to detection and attribution
(Hoegh-Guldberg et al., 2011; Parmesan et al., 2011; see also Box
18-3).
Process
Confi dence in
Role Context Reference
Detection Attribution
Impacts of ocean acidifi cation
on pelagic marine biota
Low Very low Minor For example, reduction in foraminiferan, coccolithophores, and pteropod shell
weight. Attribution supported by experimental evidence and physiological
knowledge.
1
Expansion of midwater
hypoxic zones
Medium Low Minor Oxygen minimum zones caused by enhanced stratifi cation and bacterial
respiration due to effects of warming
2
Regional and local impacts of
expanding hypoxic zones
Medium Low Minor Reduction of biodiversity, compression of oxygenated habitat for intolerant
species, range expansion for tolerant taxa
3
Direct temperature effects on
marine biota related to limited
physiological tolerance ranges
Very high High Major For example, large-scale latitudinal shifts of species distribution, changes in
community composition; attribution supported by experimental and statistical
evidence as well as physiological knowledge
4
Increase in net primary
production at high latitudes
Medium Medium Major At higher latitudes, net primary production is increasing owing to sea ice
decline and warming. At the global scale, estimates vary regionally, and there is
a discrepancy between satellite observations and open ocean time series sites.
5
Changes in microbial
processes
Low Very low Minor Limited understanding of microbial processes, drivers, and interactions, and
subsequently of large-scale shifts in biogeochemical pathways such as oxygen
production, carbon sequestration, and export production and nitrogen fi xation
6
Table 18-1 | Observed changes in ocean system properties and their effects, with confi dence levels for the detection of the effect of climate change and an assessment of the
magnitude of its role.
Key references and further related information for the assessment in this table:
1
Wootton et al. (2008); De Moel et al. (2009); Moy et al. (2009); Bednaršek et al. (2012); Section 6.3.2; Box CC-OA
2
Stramma et al. (2008); Stolper et al. (2010); Sections 6.1.1.3 and 6.3.3
3
Levin et al. (2009); Ekau et al. (2010); Stramma et al. (2010, 2012); Sections 6.3.3, 6.3.5, and 30.5
4
Merico et al. (2004); Perry et al. (2005); Pörtner and Farrell (2008); Beaugrand et al. (2010); Alheit et al. (2012); Section 6.3.1
5
Behrenfeld et al. (2006); Saba et al. (2010); Arrigo and Van Dijken (2011); Section 6.3.4; Box CC-PP
6
Sections 6.3.1.2, 6.3.2.2, 6.3.3.2, and 6.3.5.2
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Chapter 18 Detection and Attribution of Observed Impacts
18
18.3.4.1. Impacts on Ocean System Properties
and Marine Organisms and Ecosystems
Greater thermal stratification in many regions has reduced ocean
ventilation and mixing depth. As this reduces the availability of inorganic
nutrients, it can reduce primary productivity in surface layers. However,
trends in primary production from different observational methods
disagree (Sections 6.1.1, 6.3.4; Box CC-PP). Coastal upwelling has
increased in some regions bringing greater concentrations of nutrients
to surface waters, boosting productivity and enhancing fisheries output
(see Section 30.5.5). Increases in productivity also occurred with
warming and sea ice loss at high latitude (medium confidence; Table
18-1).
Poleward shifts in the distributions of zooplankton, fish, seabirds, and
benthic invertebrates related to climate change have been detected
with high confidence in the well-studied Northeast Atlantic. There is
also high confidence that climate change has played a major role in
these shifts (Box 6-1; Sections 6.3, 30.5.1). In many regions, temperature
exerts the strongest influence on ecosystems and the responses of
ecological systems to changing temperature are well studied. However,
it is often difficult to clearly identify the interaction of temperature with
other factors (Section 6.3.5). Some studies have found changes in the
abundance of fish species that are consistent with regional warming,
with differences in response between species, in line with differential
specializations of coexisting species (Sections 6.2, 6.3.1; see also Pörtner,
2012). Anthropogenic influences modulate responses to climate, for
example, due to exploitation status (Tasker, 2008; Belkin, 2009; Overland
et al., 2010; Schwing et al., 2010), with more heavily exploited species
being more sensitive to environmental variability in general, including
temperature trends and extremes (Hsieh et al., 2005, 2008; Stige et al.,
2006).
Laboratory experiments have shown that a broad range of marine
organisms (e.g., corals, fish, pteropods, coccolithophores, and macroalgae),
physiological processes (e.g., skeleton formation, gas exchange,
r
eproduction, growth, and neural function), and ecosystems processes
(e.g., productivity, reef building, and erosion) are sensitive to changes
in pH and carbonate chemistry of seawater (Section 6.2, Box CC-OA).
However, few field studies have been able to detect specific changes in
marine ecosystems to ocean acidification owing to the inability to
identify the effect of ocean acidification from ocean warming or local
factors (Wootton et al., 2008; De Moel et al., 2009; Moy et al., 2009;
Bednaršek et al., 2012; see also Section 6.3.2).
There has been a substantial increase in the number of studies
documenting significant changes in marine species and processes
since the AR4. A new meta-analysis using a database of long-term
observations from peer-reviewed studies of biological systems, with
nearly half of the time series extending prior to 1960, shows that more
than 80% of observed responses are consistent with regional climate
change (see Section 30.4, Box CC-MB). Poloczanska et al. (2013) argue
that the high consistency of marine species’ responses across geographic
regions (coastal to open ocean, polar to tropical), taxonomic groups
(phytoplankton to top predators), and types of responses (distribution,
phenology, abundance) reported in their analysis support the detection
of a widespread impact of climate change on marine populations and
ecosystems (see Sections 30.4 and 30.5 for more detail). Table 18-2
gives examples of the manifestation of climate change on marine
species and ecosystems.
18.3.4.2. Observed Climate Change Effects across Ocean Regions
Climate change has affected physical properties across the ocean, with
regional variations (Table 30-1; Figures 30-2 to 30-5; WGI AR5 Chapter
3). Confidence in the detection and attribution of these impacts also
varies regionally, reflecting differences in system understanding, data
availability, influence of long-term natural variability, and the impact
of factors unrelated to climate change. The attribution of changes in
heat content to climate change is less certain regionally than globally,
but warming has been detected with high confidence in all basins except
Table 18-2 | Observed changes in marine species and ecosystems, with confi dence levels for the detection of the effect of climate change and an assessment of the magnitude
of its role (see also Sections 6.2, 6.3, and 30.4; Box CC-MB).
Process
Confi dence in
Role Context Reference
Detection Attribution
Range shifts of fi sh and macroalgae High High Major Changes in species biogeographical ranges to higher latitudes or greater depths 1
Changes in community composition High High Major Due to effects of warming, hypoxia, and sea ice retreat 1
Changes in abundance High Medium Major Observed in fi sh, corals, and intertidal species 1
Impacts on large non-fi sh species,
e.g., walruses, penguins, and other
sea birds
High High Major Observed effects include changing abundance, phenology, species distribution
and turtle sex ratios, and are mediated mostly through changes in resource
availability, including prey.
2
Impacts on reef-building corals Very high High Major Effects attributed mostly to warming and rising extreme temperatures, though
ocean acidifi cation may contribute
3
Changes in fi sh species richness in
temperate and high-latitude zones
High Medium Major Effect associated with loss of sea ice and latitudinal species shifts due to
warming trends
4
Key references and further related information for the assessment in this table:
1
Müller et al. (2009); Stige et al. (2010); Sections 6.3.1 and 30.4; Box CC-MB
2
Grémillet and Boulinier (2009); McIntyre et al. (2011); Section 6.3.7
3
Hoegh-Guldberg (1999); Hoegh-Guldberg et al. (2007); Baker et al. (2008); Veron et al. (2009); Sections 6.3.1.4 and 6.3.1.5; Box CC-CR
4
Hiddink and ter Hofstede, (2008); Beaugrand et al. (2010); Box 6-1; Section 6.3.1.5
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Detection and Attribution of Observed Impacts Chapter 18
18
Eastern boundary upwelling systems (Table 30-1, Figure 30-2). Recent
research shows declining oxygen levels (medium confidence; Section
30.3.2.3) and deep penetration of warming in some regions. Regional
estimates of CO
2
uptake are in line with global estimates, and ocean
acidification has been detected with high confidence in most regions
(Section 30.3.2.2; WGI AR5 Section 3.8.2).
The high latitude spring bloom systems of the NH show strong warming
and associated effects (see above). In the North Pacific, the Bering Sea
has undergone major changes in recent decades as a result of climate
variability, climate change, and fishing impacts (Litzow et al., 2008;
Mueter and Litzow, 2008; Jin et al., 2009; Hunt et al., 2010). Loss of sea
ice has led to the retreat of the cold pool in parts of the Bering Sea, and
northward expansion of productivity (Wang et al., 2006; Mueter and
Lizow, 2008; Brown and Arrigo 2012; see also Section 30.5.1.1.2).
Marginal seas such as the East China Sea are also warming rapidly,
with subsequent impacts such as declining primary productivity and
fisheries yields as well as other ecological changes (Section 30.5.4.1).
However, other human pressures including over-fishing, habitat
alteration, and nutrient loading are important contributing factors
and it is difficult to disentangle these from the impacts of climate
change.
Semi-enclosed seas such as the Black and Baltic Seas and the Arabian/
Persian Gulf show differing patterns of change over the past decades
(Section 30.5.3.1). Expansions of hypoxic zones in the Baltic and Black
Seas have been detected. Although there is high confidence that climate
change has had a role, its magnitude is difficult to assess in light of
other contributing factors. Coral reefs in the Arabian/Persian Gulf and
Red Sea have experienced widespread bleaching in 1996 and 1998
associated with elevated temperature with high confidence that climate
change has played a major role.
Warming of the Mediterranean has been associated with mass mortality
events as well as invasions and spread of new warm water species,
Box 18-3 | Differences in Detection and Attribution of Ecosystem Change on Land and in the Ocean
Marine and terrestrial ecosystems differ in fundamental ways. Gradients in turbulence, light, pressure, and nutrients uniquely drive
fundamental characteristics of organisms and ecosystems in the ocean. While the critical factor for transporting nutrients to marine
primary producers is ocean mixing driven by wind, water is the primary mode for transporting nutrients to land plants. In addition to
these characteristics, marine ecosystems are often more technically difficult and costly to explore than terrestrial equivalents, which
explains the low number and shorter scientific studies of marine ecosystems (Hoegh-Guldberg and Bruno, 2010). The latter has
restricted the extent to which changes within the ocean can be detected and attributed.
Impacts of climate change in terrestrial and marine systems differ significantly for the same types of measures, for example, species
phenology and range shifts, leading to differences in experts’ interpretations of the data and possibly divergent levels of confidence
in detection and attribution. There are also fundamental differences in exposure of organisms to recent warming, their biological
responses, and our ability to detect change through observations. Changes in temperature of ocean systems have generally been less
than those of terrestrial ecosystems over the last 4 decades (Burrows et al., 2011). Furthermore, despite higher variability the horizontal
spatial gradient of temperature change (°C km
–
1
) is generally much higher in terrestrial ecosystems than in marine ecosystems. All
else being equal, the net result is that species have generally needed to move much shorter distances in terrestrial ecosystems to stay
within their preferred climates, also due to the influence of the topography such as mountain ranges (Burrows et al., 2011), although
many marine species can potentially exploit strong vertical thermal gradients to attenuate the need for range shifts in response to
warming.
Species and ecosystems may respond very differently to these climate signals in ways that influence the ability to detect change. For
example, a comparison of ectotherm species (i.e., species that do not actively regulate their body temperatures, such as reptiles and
fish) indicates that marine species' ranges have tracked recent warming at both their poleward and equatorial range limits, while
many terrestrial species’ ranges have tracked warming only at their poleward range limits (Sunday et al., 2012). Biological processes
influencing phenological shifts may also differ substantially between systems. For example, the effect of climate on the timing of
flowering of terrestrial plants at high latitudes is only moderately influenced by confounding effects, whereas the timing of
phytoplankton blooms in high-latitude marine systems is highly dependent on ocean temperature and associated stratification and
changes in nutrient availability.
996
Chapter 18 Detection and Attribution of Observed Impacts
18
r
esulting in the “tropicalization” of fauna with high confidence in a
major role for climate change (Section 30.5.3.1.5). In many tropical
regions and the subtropical gyres of the Pacific, Indian, and Atlantic,
periodic heat stress related to climate change has combined with other
local stresses to cause mass coral bleaching and mortality (see also Box
CC-CR, Section 30.5).
In other regions, such as the California Current upwelling system, there
is very high confidence in both the detection and attribution of ecological
changes associated with climate change, but separating the effects
of El Niño-Southern Oscillation (ENSO) and the PDO from those of
anthropogenic climate change is not possible.
In overall terms, attributing observed local and regional changes in
marine species and ecosystems to climate change remains an important
question for ongoing research (Stock et al., 2010).
18.4. Detection and Attribution of
Observed Climate Change Impacts in
Human and Managed Systems
Observed impacts on human systems have received considerably less
attention in previous IPCC reports and the scientific literature, compared
to observed impacts on natural systems. Human systems’ “normal
state in the absence of climate change” is almost never stationary.
Confounders other than climate change have been and continue to
drive the normal evolution of these systems, with climate often playing
a relatively minor role. Further, monitoring in many of the systems has
been and continues to be inadequate. It is therefore difficult to detect
and attribute the signal of climate change in the majority of human
systems, food production systems constituting one noteworthy
exception. There is emerging literature estimating the sensitivity to
climate of many sectors within the human system (see Box 18-4), yet
climate impacts are often not detectable over the impacts from non-
climate confounders.
For some human systems, the clearest situations where a climate signal
had a detectable and sometimes attributable impact are during extreme
weather events. Impacts of extreme events and single event attribution
are therefore discussed in Section 18.4.3, and the discussion is expanded
to include responses to extreme weather for some sectors. Overall, the
literature has made significant progress for certain sectors, such as food
systems, since AR4. The following sections provide a synthesis of findings
with regard to food systems, economic systems, human health, human
security, and human livelihoods and poverty, which are documented in
greater detail in Chapters 7, 9, 10, 11, 12, and 13. They also incorporate
evidence from regional chapters and further available literature,
especially for the discussion of extreme events, human security, and
observed changes in indigenous communities.
18.4.1. Food Production Systems
Detection and attribution of climate change impacts in food systems is
challenging, given that the behavior of the system in the absence of
climate change is driven by a large number of other factors (Section 7.2.1).
F
or cropping systems, these confounders include, but are not limited to,
cultivar improvement and increased use of synthetic fertilizers, herbicides,
and irrigation. These confounders are often not well measured in terms
of their distribution across space and time. Further, it is difficult to
quantify or model the exact relationship between these confounders
and outcomes of interest (e.g., crop yield or pasture productivity). In
addition, the role of farmers’ behavior in response to climate change
requires significant assumptions and has been shown to change over
time (Section 7.2.1). The discussion below is limited to crop systems
and fisheries, as literature is scarce on observed impacts for other
important sources of food.
18.4.1.1. Agricultural Crops
A significant number of studies have provided impact estimates of
observed changes in climate on cropping systems over the past few
decades (e.g., Auffhammer et al., 2006; Kucharik and Serbin, 2008;
Ludwig et al., 2009; Lobell et al., 2011; Tao et al., 2012; see also Figure
7-2). Over the past several decades, observed climate trends have
adversely affected wheat and maize production for many regions, as
well as the total global production of these crops (medium confidence
in a minor role of climate change in overall production). Climate change
impacts on rice and soybean yields over this time period have been
small in major production regions and globally (medium confidence;
Figure 7-2). In some high-latitude regions, such as the UK and northeast
China, warming has benefitted crop production during recent decades
(high confidence in a minor role of climate change; Section 7.2.1.1;
Jaggard et al., 2007; Chen. C. et al., 2011). At the continental or global
scale, observed trends in some climatic variables, including mean summer
temperatures, attributed to anthropogenic activity (see Section 7.2.1.1;
WGI AR5 Section 10.3.1 and Table 10-1) have had significant negative
impacts on trends in yields for certain crops (Lobell and Field, 2007; You
et al., 2009; Lobell et al., 2011).
Attributable trends have been found not only in the seasonal averages
of climate variables, but also for extremes (WGI AR5 Section 10.6).
Extreme rainfall events are widely recognized as important to cropping
systems (Rosenzweig et al., 2002), and global scale changes in the
patterns of rainfall extremes have been attributed to anthropogenic
activity (Min et al., 2011). High nighttime temperatures are harmful to
most crops, particularly for rice yield (Peng et al., 2004; Wassmann et
al., 2009; Welch et al., 2010) and quality (Okada et al., 2009). Daytime
extreme heat is also damaging and sometimes lethal to crops (Porter
and Gawith, 1999; Schlenker and Roberts, 2009). At the global scale,
trends in annual maximum daytime temperatures have been attributed
to greenhouse gas emissions (Christidis et al., 2011; Zwiers et al., 2011),
and similar observations have been made for the occurrence of very hot
nights (WGI AR5 Section 10.6.1.1; Seneviratne et al., 2012).
Changing atmospheric conditions are affecting crops both positively
and negatively. It is virtually certain that the increase in atmospheric
CO
2
concentrations since preindustrial times has improved water use
efficiency and yields most notably in C
3
crops. These effects are however
of relatively minor importance when explaining total yield trends
(Amthor, 2001; McGrath and Lobell, 2011). Emissions of CO
2
have been
associated with tropospheric ozone (O
3
) precursors (Morgan et al., 2006;
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Detection and Attribution of Observed Impacts Chapter 18
18
Mills et al., 2007; see also Section 7.3.2.1.2). O
3
suppresses global
output of major crops, with reductions estimated at roughly 10% for
wheat and soy and 3 to 5% for maize and rice (Van Dingenen et al.,
2009). Detected impacts are most significant for India and China, but
can also be found for soybean and maize production in the USA in
recent decades (Fishman et al., 2010).
18.4.1.2. Fisheries
Many new studies focus on the relationship between the dynamics of
marine fish stocks and climate, suggesting a sensitivity to climate of
these stocks and on the fisheries that exploit them (Hollowed et al.,
2001; Roessig et al., 2004; Shriver et al., 2006; Brander, 2007). Some
fisheries and aquaculture do not show evidence of climate change
impacts (e.g., aquaculture in the UK and Ireland; Callaway et al., 2012),
while many others do with both positive and negative changes (see
also Sections 7.2.1.1, 18.3.4, 30.6.2.1).
There is high confidence in the detection of a climate change impact
on the spatial distributions of marine fishes (Perry et al., 2005) and in
the timing of events like spawning and migration (Sydeman and Bograd,
2009), with high confidence of a major role of climate change (see
Sections 18.3.4, 30.4; Box CC-MB). This distributional shift is reflected
in the species composition of harvest, with the relative share of warm
water species increasing (Cheung et al., 2013). The impacts of ocean
warming and acidification on fish stocks vary from region to region
(Section 30.6.2.1). To date, the role of climate change in change in fish
stocks and fishery yields is, in most cases, minor (high confidence) in
relation to other factors such as harvesting, habitat modification,
technological development, and pollution (Brander, 2010).
18.4.2. Economic Impacts,
Key Economic Sectors, and Services
18.4.2.1. Economic Growth
In low-income countries, careful tracking of incomes and temperatures
over an extended period, taking into account important confounders,
shows that higher annual temperatures as well as higher temperatures
averaged over 15-year periods result in substantially lower economic
growth (Dell et al., 2012). This effect is not limited to the level of per
capita income, but also to its rate of growth. Declining rainfall over the
20th century partly explains the slower growth of sub-Saharan economies
relative to those of other developing regions (Barrios et al., 2006; Brown
et al., 2011). Dell et al. (2009) find that 1°C of warming reduces income
by 1.2% in the short run and by 0.5% in the long run. The difference is
argued to be due to adaptation. Horowitz (2009) finds a much larger
effect: a 3.8% drop in income in the long run for 1°C of warming.
One proposed mechanism for this is the impact of heat stress on
workers in the workplace (Dash and Kjellström, 2011; Dunne et al.,
2013). Temperature shocks have negatively affected the growth of
developing countries’ exports, for which 1°C of warming in a given
year reduced the growth rate of its exports by 2.0 to 5.7 percentage
points (Jones and Olken, 2010). The export sectors most affected are
agricultural and light manufacturing exports.
18.4.2.2. Energy Systems
Energy production and consumption is growing rapidly globally, with
much of the growth taking place in low-income and emerging
economies. Various parts of the energy sector are known to be sensitive
Box 18-4 | The Role of Sensitivity to Climate and Adaptation for Impact Models in Human Systems
Impacts of climate change on a measurable attribute of a human system occur only if (1) the attribute is sensitive to climate and (2)
a change in climate has occurred. Many studies now attempt to quantify both climate sensitivity of various systems and observed
changes in climate.
Assessment of the sensitivity of an outcome such as crop yields, heat-related mortality, or migration to climate relies on observed
climate variability either across space (e.g., Schlenker et al., 2005), time (e.g., Mann and Emanuel, 2012), or space and time (e.g., Dell
et al., 2012). Though there are many studies using climate variability across space, the lack of long observational weather time series
required for exploring climate variability across space and time have limited the opportunities for study. A number of studies have
instead estimated the sensitivity of outcomes to short-run fluctuations (e.g., weather) in order to project the future impacts of climate
change (Deschênes and Greenstone, 2007, 2011), or attribute impacts for the past (Auffhammer et al., 2006). The issue with impact
studies using a weather-based sensitivity measure is that they cannot provide estimates of impacts based on the sensitivity to climate.
For example, farmers may respond to an unusually hot summer, which is a weather event, by applying more irrigation water. However,
in the long run farmers may respond to a warmer climate by switching crops, changing irrigation technology, or abandoning farming
altogether. The two sensitivities and resulting magnitudes of attributable impacts due to a change in weather versus a change in
climate are therefore different. To detect and attribute a change in a system to climate change, one needs to combine a measure of
sensitivity of the outcome to climate with climate observations under climate change.
998
Chapter 18 Detection and Attribution of Observed Impacts
18
t
o climate change (cf. Ebinger and Vegara, 2011). Higher temperatures
raise the demand for cooling and lower the demand for heating. Cooling
demand is largest in the summer and in some areas peak loads during
the summer months have increased, this peak being highly correlated
with summer maximum temperatures (Franco and Sanstad, 2008). There
are also opposing effects of warmer winters and summers on electricity
and gas demand. Statistical studies have confirmed this U-shaped
relationship of energy and electricity demand in temperature for the
USA and elsewhere (Isaac and van Vuuren, 2009; Akpinar-Ferrand and
Singh, 2010; Deschênes and Greenstone, 2011).
On the supply side, sensitivity to climatic factors such as ambient
temperature, wind speeds, or snow and ice is well known for many
energy technologies and part of the transmission infrastructure (see
Sections 10.2.2-3); however, there are no studies available that discuss
observed effects of climate change on the energy sector.
18.4.2.3. Tourism
Tourism is a climate sensitive economic sector and ample research has
been performed to understand its sensitivity to climate change and
impacts of (future) climate change on tourism, yet few studies have
focused on detection and attribution of observed impacts (cf. Scott et
al., 2008; see also Section 10.6).
A comparatively well-studied area is the sensitivity of the winter sports
industry in lower lying areas to climate. For example, the increase in
investment in artificial snow machines in the European Alps can be
attributed with high confidence to a general decrease of snow depth,
snow cover duration, and snowfall days since the end of the 1980s for
low-elevation mountain stations (Durand et al., 2009; Valt and Cianfarra,
2010; Voigt et al., 2011), which in turn has been attributed to anomalous
higher winter temperatures over the past 20 years (Marty, 2008).
Variability in precipitation, shrinking glaciers, and milder winters has
been shown to negatively affect visitor numbers in winter sports areas
in Europe and North America (Becken and Hay, 2007). Another indirect
effect of climate change that has been reported is a rise in popularity
of destinations that are perceived to be at risk from climate change
(e.g., Eijgelaar et al. (2010) for Antarctic glaciers, or Farbotko (2010) for
Tuvalu).
18.4.3. Impacts of Extreme Weather Events
The impacts of extreme weather events depend on the frequency and
intensity of the events, as well as exposure and vulnerability of society
and assets. The last several decades have seen changes in the frequency
and intensity of extreme weather events including extreme temperature,
droughts, heavy rainfall, and tropical and extratropical cyclones with
low to very high confidence, depending on the type of extreme event
(IPCC, 2012; WGI AR5 Chapter 2). However, the impacts of extreme
weather events also depend on the vulnerability and exposure of
systems. It is possible that climate change can affect vulnerability and
exposure, but typically both are influenced primarily by non-climate
confounders, most notably economic development.
18.4.3.1. Economic Losses Due to Extreme Weather Events
Extreme weather events can result in economic impacts related to
damage to private and public assets as well as the temporary disruption
of economic and social activities, long-term impacts, and impacts beyond
the areas affected. Some economic and especially social impacts are
not readily monetizable and are thus excluded from most economic
assessments (Handmer et al., 2012, their Sections 4.5.1, 4.5.3).
Economic costs of extreme weather events have increased over the
period 1960–2000 (high confidence), with insured losses increasing more
rapidly than overall losses (Section 10.7.3; Handmer et al., 2012, their
Sections 4.5.3.3, 4.5.4.1). This is also reflected by an increase in the
frequency of extreme weather-related disasters over the same period
(Neumayer and Barthel, 2011). Recent studies from Mexico and Colombia
highlight both variability and positive trends in disaster frequency
(unadjusted) losses and other damage metrics (Saldaña-Zorrilla and
Sandberg, 2009; Marulanda et al., 2010; Rodriguez-Oreggia et al., 2013).
However, the greatest contributor to increased cost is rising exposure
associated with population growth and growing value of assets (high
confidence; Bouwer et al., 2007; Bouwer, 2011; Barthel and Neumayer,
2012; Handmer et al., 2012, their Sections 4.2.2, 4.5.3.3, Box 4-2). To
account for changes over time in the value of exposed assets, many
studies attempt to normalize monetary losses by an overall measure of
changes in asset value. A majority of studies have found no detectable
trend in normalized losses (Bouwer, 2011). Studies on insured losses
that in general meet higher data quality standards than data on overall
losses due to thoroughly monitored payouts have focused on developed
countries including Australia, Germany, Spain, the USA (Changnon, 2007,
2008, 2009a,b; Barredo et al., 2012; Barthel and Neumayer, 2012; Sander
et al., 2013; see also Section 10.7.3). Studies of normalized losses from
extreme winds associated with hurricanes in the USA (Miller et al., 2008;
Pielke Jr. et al., 2008; Schmidt et al., 2010; Bouwer and Botzen, 2011)
and the Caribbean (Pielke Jr. et al., 2003), tornadoes in the USA (Brooks
and Doswell, 2002; Boruff et al., 2003; Simmons et al., 2013), and wind
storms in Europe (Barredo, 2010) have failed to detect trends consistent
with anthropogenic climate change, although some studies were able
to find signals in loss records related to climate variability, such as
damage and loss of life due to wildfires in Australia related to ENSO and
Indian Ocean dipole phenomena (Crompton et al., 2010), or typhoon loss
variability in the western North Pacific (Welker and Faust, 2013). Effects
of adaptation measures (disaster risk prevention) on disaster loss
changes over time cannot be excluded as research is currently not able
to control for this factor (Neumayer and Barthel, 2011).
In conclusion, although there is limited evidence of a trend in the
economic impacts of extreme weather events that is consistent with a
change driven by observed climate change, climate change cannot be
excluded as at least one of the drivers involved in changes of normalized
losses over time in some regions and for some hazards.
18.4.3.2. Detection and Attribution of the Impacts of
Single Extreme Weather Events to Climate Change
Although most studies on the relationship between climate change and
extreme weather events have focused on changes over time in their
999
Detection and Attribution of Observed Impacts Chapter 18
18
Date
and locale
Impact event Associated climate hazard
Trends relating to likelihood
of climate hazard
Trends relating to consequence
of climate hazard
France, summer
2
003
Approximately 15,000 excess
d
eaths (Hémon and Jougla,
2003; Fouillet et al., 2006)
Record hot days / heat wave (Hémon
a
nd Jougla, 2003; Fouillet et al., 2006)
Increasingly frequent hot days and
h
eat waves in recent decades (Perkins
et al., 2012; Seneviratne et al., 2012)
(
high confi dence)
• Aging population, increasing population, trends in
m
arital status (Hémon and Jougla, 2003; Prioux,
2005; Fouillet et al., 2006; Rey et al., 2007)
•
D
iffi culties staffi ng health services, undeveloped
early warning system (Lalande et al., 2003; Fouillet
e
t al., 2008)
Atlantic and
G
ulf coasts
of the United
S
tates, 2005
More than 1,000 deaths and
m
ore than US$100 billion in
damage (Beven et al., 2008)
Record number of tropical storms,
h
urricanes, and category 5 hurricanes
(Bell et al., 2006)
Recent increase in frequency but
n
o clear century-scale trends in
USA landfalling tropical storms or
h
urricanes (WGI AR5 Section 2.6.3,
Knutson et al., 2010) ( high confi dence)
• More population, settlement, and wealth in coastal
a
reas (Pielke Jr. et al., 2008; Schmidt et al., 2010)
•
S
trengthening of building codes (IntraRisk, 2002)
Mozambique,
e
arly 2007
More than 100,000 people
d
isplaced by fl ooding (Foley,
2007; Artur and Hilhorst,
2
012)
High rainfall in upper Zambezi Basin in
p
receding months; passage of Cyclone
Favio (Thiaw et al., 2008)
Warming and decreasing rainfall
l
eading to lower discharge of the
Zambezi (Dai et al., 2009) ( low
c
onfi dence)
Decreasing frequency of tropical
c
yclones in the Mozambique Channel
during past 50 years (Mavume et al.,
2
009) ( medium confi dence)
• Increased settlement of Zambezi fl ood plain
f
ollowing dam construction (Foley, 2007)
•
D
evelopment of emergency response plans
(Cosgrave et al., 2007; Foley, 2007)
Colombia,
O c t o b e r –
D
ecember 2010
Floods affecting 4 million
people; US$7.8 billion total
d
amage (Hoyos, N. et al.,
2013)
Wettest year since records began 40
years ago (Martinez et al., 2011)
No clear trend in discharge of rivers in
fl ood-affected areas since 1940 (Hoyos,
N
. et al., 2013) ( low confi dence)
• Rapid urbanization, with high concentration of
residential areas in fl ood-prone areas (OSSO, 2013;
Á
lvarez-Berríos et al., 2013)
•
I
ncreasing vulnerability of rural population over the
past decades and highly fragile urban systems (e.g.,
water and gas) (OSSO, 2013)
Pakistan,
July – September
2010
Flooding leading to 2,000
deaths; 20 million affected;
total loss US$10 billion
(NDMA, 2011)
Exceptionally high monsoon rainfall
over northern Pakistan during July and
August (Houze Jr. et al., 2011; Rajeevan
et al., 2011; Webster et al., 2011)
No substantial trend in heavy rainfall
event frequency in northern Pakistan
in past several decades (Wang, S.-Y.
et al., 2011; Webster et al., 2011) ( low
confi dence)
• Rapid population growth and expansion of formal
and informal human settlements (Oxley, 2011)
• Decreased risk through development of fl ood and
disease warning systems and disaster planning
(NDMA, 2011)
• Increased risk from deforestation on mountainous
slopes (Ali et al., 2006)
• Recent unrest in north constrains ability of
institutions to deliver basic services (World Bank
and ADB, 2010)
European
Russia, July –
August 2010
Burned area >12,500 km
(Müller, 2011)
Record hot days (Barriopedro et al.,
2011; Müller, 2011)
Unusually dry June – August (Bulygina
et al., 2011)
Trends in temperature, precipitation,
humidity, soil moisture, and snow
cover toward less conducive climatic
conditions for fi re (Groisman et al.,
2007) ( medium confi dence)
• Increased risk from draining of peat bogs in 1960s
and earlier (Global Fire Monitoring Center, 2010;
Müller, 2011)
• Increased risk from poorly implemented devolution
of forest management and forest fi re protection
in 2007 to regional administrations (Global Fire
Monitoring Center, 2010)
Russia, summer
2010
Grain harvest 30% lower
than forecast (Wegren, 2011)
Hottest June – August in at least 130
years, unusually dry June – August
(Bulygina et al., 2011)
~1°C summer warming trend over last
70 years (Gruza and Mescherskaya,
2008; Bulygina et al., 2011) (very high
confi dence)
• Increase in grain production partially due to
government support programs (Wegren, 2011)
Southeast
Queensland,
Australia,
January 2011
Floods affecting >200,000
people; >30,000 homes
fl ooded; damages and cost
to economy of US$2.5 –10
billion (Hayes and
Goonetilleke, 2012)
2010 was the wettest year since 1974,
with landfall of tropical cyclone in
December and wet start to January
resulting in highest fl ood since 1974
(Van den Honert and McAneney, 2011;
Hayes and Goonetilleke, 2012).
Decreasing frequency of intense fl oods
since 1840 (Van den Honert and
McAneney, 2011) ( medium confi dence)
• Increased development in fl ood-prone urban areas
(Van den Honert and McAneney, 2011)
• Lack of development of riverine fl ood insurance
(Van den Honert and McAneney, 2011; Ma et al.,
2012)
Thailand, 2011 Prolonged inundation of
urban and industrialized
areas; manufacturing losses
of about US$32 billion (World
Bank, 2012)
One of the wettest monsoon seasons
on record in middle and upper Chao
Phraya Basin, resulting in fl ooding
(Komori et al., 2012; Van Oldenborgh
et al., 2012)
No detectable change in precipitation
over the basin (Van Oldenborgh et al.,
2012) ( low confi dence)
• Economic development focused on large industrial
estates built in fl ood plains (Chongvilaivan, 2012;
Courbage et al., 2012)
• Recent spell of political instability (Courbage et
al., 2012)
• Subsidence from groundwater pumping (Phien-Wej
et al., 2006)
Contiguous
United States,
summer 2012
Agricultural drought, with
57% of cropland and 43% of
farms experiencing at least
severe drought (Crutchfi eld,
2013)
Second warmest summer and warmest
month (July) in the contiguous USA,
and one of the driest March – July
periods in the central USA in the 118-
year record (Crouch et al., 2013; Kumar
et al., 2013)
~0.5ºC warming in summer over the
last century (Menne et al., 2009) (very
high confi dence)
No substantial long-term trend in
drought occurrence (Peterson et al.,
2013) ( medium confi dence)
Signifi cant growth in area dedicated to soy and
maize (FAOSTAT, 2013)
Table 18-3 | Illustrative selection of recent disasters related to extreme weather events, with description of the impact event, the associated climate hazard, recent climate trends
relating to the weather event, and recent trends relating to the consequences of such a weather event.
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Chapter 18 Detection and Attribution of Observed Impacts
18
f
requency and intensity, a few studies have focused on the contribution
of climate change to specific events (WGI AR5 Section 10.6.2). Assessing
the contribution of climate change to a specific event poses particular
challenges, both in terms of methodology and communication of results
(Allen, 2011; Curry, 2011; Hulme et al., 2011; Trenberth, 2011). Only a
few studies have attempted to evaluate the role of climate change in
the impacts of individual extreme weather events. For instance, Pall et
al. (2011) and Kay et al. (2011), using observational constraints on climate
and hydrologic model simulations, concluded that greenhouse gas
emissions have increased the probability of occurrence of a comparable
flooding event in autumn 2000 over the UK.
In highly temperature-sensitive regions, such as high mountains, several
extreme impact events of recent decades can be qualitatively attributed
to effects of long-term warming (high confidence), namely glacier lake
outburst floods due to glacier recession and subsequent formation of
unstable lakes (Evans and Clague, 1994; Carey, 2005; Bajracharya and
Mool, 2009), debris flows from recently deglaciated areas, and rock fall
and avalanches following the loss of mechanical support accompanying
glacier retreat (Haeberli and Beniston, 1998; Oppikofer et al., 2008;
Huggel et al., 2012b; Stoffel and Huggel, 2012; see also Section 18.3.1.3).
Multi-step approaches can be used to evaluate the contributions of
anthropogenic emissions to recent damaging extreme events (Hegerl
et al., 2010).
Irrespective of whether a specific event can be attributed in part to climate
change, there is ample evidence of the severity of related impacts on
people and various assets. Both low- and high-income countries have
been strongly impacted by extreme weather events in recent years, but
the impacts relative to economic strength have been higher in low-income
countries (Handmer et al., 2012). Similarly, at the national scale, poor
or elderly people have been disproportionately affected, as documented
for Hurricane Katrina in the USA in 2005 (Elliott and Pais, 2006; Bullard
and Wright, 2010) or the 2003 European heat wave (Fouillet et al.,
2008). Exacerbating effects of extreme weather events are mostly of
non-climatic nature, including increasing exposure and urbanization,
land use changes including deforestation, or vulnerable infrastructure.
Table 18-3 lists a selection of recent weather-related disasters, and lists
various factors contributing to long-term changes in the risk of damage,
including recent climate change.
18.4.4. Human Health
IPCC AR4 (Confalonieri et al., 2007) concluded that there was weak to
moderate evidence of effects of recent observed climate change on
three main categories of health exposure (ranging from low to medium
confidence): vectors of human infectious diseases (changes in distribution),
allergenic pollen (changes in phenology), and extreme heat exposures
(trend in increased frequency of very hot days and heat wave events).
Overall, there was a lack of evidence for observed effects of climate
change on human health outcomes, and this generally remains the case
(see Chapter 11). Evaluation of the detection and attribution of impacts
on health outcomes requires disentangling the roles of changes in
exposures (e.g. patterns), control measures (e.g., vaccination, drug
resistance), population structures (e.g., population aging), and reporting
practices.
T
he most direct potential health impact of climate change is through
exposure to higher temperatures, as the association between very hot
days and increases in mortality is very robust (Section 11.4.1). Recent
decades have seen a shift toward more frequent hot extremes and less
frequent cold extremes (high confidence; Seneviratne et al., 2012; WGI
AR5 Table 2.13). However, the translation of this trend in hazard to a
trend in exposure is complicated by changes in social, environmental,
and behavioral factors (e.g., Carson et al., 2006; see also Table 18-3)
and interseasonal mortality relationships (Rocklöv et al., 2009; Ha et
al., 2011). Climate change has contributed to a shift from cold-related
mortality to heat-related mortality during recent decades in Australia
(medium confidence; Bennett et al., 2013). In a similar shift in England
and Wales, a contribution from anthropogenic climate change has been
detected (medium confidence; Christidis et al., 2010).
For pollen production, changes in phenology have been consistently
observed in mid- to high latitudes with, for example, earlier onset in
Finland (e.g., Yli-Panula et al., 2009) and Spain (D’Amato et al., 2007;
García-Mozo et al., 2010; see also Section 4.3) over the past few
decades. In North America, the pollen season of ragweed (Ambrosia
spp.) has been extended by 13 to 27 days since 1995 at latitudes above
44°N (Ziska et al., 2011). Allergic sensitization of humans has changed
over a 25-year period in Italy, but the attribution to observed warming
remains unclear (Ariano et al., 2010).
There is limited evidence regarding the role of observed warming in
changes in tick-borne disease in mid- to high latitudes. While patterns
of changes in tick-borne encephalitis (TBE) incidence in the Czech
Republic match those expected from observed warming (Kriz et al.,
2012), the upsurge of TBE in the 1980–1990s in Central and Eastern
Europe generally has been attributed to socioeconomic factors (human
behavior) rather than temperature (Šumilo et al., 2008, 2009).
Changes in the latitudinal and altitudinal distribution of ticks in Europe
and North America are consistent with observed warming trends (e.g.,
Gray et al., 2009; Ogden et al., 2010), but there is no evidence so far of
any associated changes in the distribution of human cases of tick-borne
diseases. There is limited evidence of a change in the distribution of
rodent-borne infections in the USA (plague and tularemia) consistent
with observed warming (Nakazawa et al., 2007). Specifically, a
northward shift of the southern edge of the distributions of the diseases
(based on human case data for period 1965–2003) was observed.
There was no change detected in the northern edge of the distributions,
however.
Globally, the dominant trend concerning malaria has been a contraction
of the geographical range and a decrease in endemicity over the past
century due to changes in land cover, behavior, and health care (Gething
et al., 2010). Given that the mosquito vector is climate sensitive,
however, there may be specific locations where climate change matches
the influence of these other factors. In the Kericho region of Kenya, both
increasing incidence and warming have been observed over several
decades (Omumbo et al., 2011). Modelling suggests that the gradual
warming is inducing an amplified nonlinear response in malaria
incidence (Alonso et al., 2011). A detailed review concluded that
decadal temperature changes have played at least a minor role in these
malaria trends in the East African highlands (low confidence; Chaves
and Koenraadt, 2010).
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Detection and Attribution of Observed Impacts Chapter 18
18
18.4.5. Human Security
A small number of studies have examined the connection between the
collapse of civilizations and large-scale climate disruptions such as
severe or prolonged drought. However, both the detection of a climate
change effect and an assessment of the importance of its role can be
made only with low confidence owing to limitations on both historical
understanding and data. Some studies have suggested that levels of
warfare in Europe and Asia were relatively high during the Little Ice Age
(Parker, 2008; Brook, 2010; Tol and Wagner, 2010; White, 2011; Zhang
et al., 2011), but for the same reasons the detection of the effect of
climate change and an assessment of its importance can be made only
with low confidence. There is no evidence of a climate change effect on
interstate conflict in the post-World War II period.
Most recent research in this area has focused on the relationship
between interannual climate variability in temperature, precipitation,
and other climate variables and civil conflict, with most studies focusing
on Africa (Hsiang et al., 2013; see also Section 12.5). A number of
studies have identified statistical relationships (Miguel et al., 2004;
Hendrix and Glaser, 2007; Hsiang et al., 2011), but the results have been
challenged (Buhaug et al., 2010; Theisen et al., 2011; Buhaug and
Theisen, 2012; Slettebak, 2012) on both technical and substantive
grounds. The issue is further complicated by the focus on interannual
variability—rather than climate change—and civil conflict. Though a
plausible argument could be made that climate change has increased
interannual variability and has, therefore, contributed positively to the
rate of civil conflict, this argument has not been tested in the literature.
For these reasons, neither the detection of an effect of climate change
on civil conflict nor an assessment of the magnitude of such an effect
can currently be made with a degree of confidence.
Several studies have examined links between climate variability and
small-scale communal violence (Adano et al., 2012; Butler and Gates,
2012; Hendrix and Salehyan, 2012; Raleigh and Kniveton, 2012; Theisen,
2012). As with larger-scale civil conflict, this work has focused on climate
Box 18-5 | Detection, Attribution, and Traditional Ecological Knowledge
Indigenous and local peoples often possess detailed knowledge of climate change that is derived from observations of environmental
conditions over many generations. Consequently, there is increasing interest in merging this traditional ecological knowledge
(TEK)—also referred to as indigenous knowledge—with the natural and social sciences in order to better understand and detect
climate change impacts (Huntington et al., 2004; Parry et al., 2007; Salick and Ross, 2009; Green and Raygorodetsky, 2010; Ford et
al., 2011; Diemberger et al., 2012). TEK, however, does not simply augment the sciences, but rather stands on its own as a valued
knowledge system that can, together with or independently of the natural sciences, produce useful knowledge for climate change
detection or adaptation (Agrawal, 1995; Cruikshank, 2001; Hulme, 2008; Berkes, 2009; Byg and Salick, 2009; Maclean and Cullen,
2009; Wohling, 2009; Ziervogel and Opere, 2010; Ford et al., 2011; Herman-Mercer et al., 2011).
Cases in which TEK and scientific studies both detect the same phenomenon offer a higher level of confidence about climate change
impacts and environmental change (Huntington et al., 2004; Laidler, 2006; Krupnik and Ray, 2007; Salick and Ross, 2009; Gamble et
al., 2010; Green and Raygorodetsky, 2010; Alexander et al., 2011; Cullen-Unsworth et al., 2012). Evidence is available in particular
from Nordic and Mountain peoples, for example, from Peru’s Cordillera Blanca mountains (Bury et al., 2010; Carey, 2010; Baraer et
al., 2012; Carey et al., 2012b), Tibet (Byg and Salick, 2009), and Canada (Nichols et al., 2004; Laidler, 2006; Krupnik and Ray, 2007;
Ford et al., 2009; Aporta et al., 2011). TEK can also inspire scientists to study new issues in the detection of climate change impacts.
In one case, experienced Inuit weather forecasters in Baker Lake, Nunavut, Canada, reported that it had become increasingly difficult
for them to predict weather, suggesting an increase of weather variability and anomalies in recent years. To test Inuit observations,
scientists analyzing hourly temperature data over a 50-year period confirmed that afternoon temperatures fluctuated much more
during springtime during the last 20 years—precisely when Inuit forecasters noted unpredictability—than they had during the
previous 30 years (Weatherhead et al., 2010).
Despite frequent confluence between TEK and scientific observations, there are sometimes discrepancies between them, indicating
uncertainty in the identification of climate change impacts. They can arise because TEK and scientific studies frequently focus on
different and distinct scales that make comparison difficult. Local knowledge may fail to detect regional environmental changes
while scientific regional or global scale analyses may miss local variation (Wohling, 2009; Gamble et al., 2010). Furthermore, TEK-
based observations and related interpretations necessarily need to be viewed within the context of the respective cultural, social, and
political backgrounds (Agrawal, 1995). Therefore, a direct translation of TEK into a natural science perspective is often not feasible.
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Chapter 18 Detection and Attribution of Observed Impacts
18
variability rather than on climate change, so neither the detection of
the effect of climate change nor an assessment of its magnitude can
currently made with a degree of confidence.
Finally, efforts have been made to establish a link between high
temperatures and violent crime (Anderson, 1987; Field, 1992; Anderson,
2001; Rotton and Cohn, 2001; Butke and Sheridan, 2010; Breetzke and
Cohn, 2012; Gamble and Hess, 2012). However, the findings remain
controversial with other studies identifying non-climate factors as
explaining variations in the rate of violent crime (Kawachi et al., 1999;
Fajnzylber et al., 2002; Neumayer, 2003; Cole and Gramajo, 2009).
Again, the focus in this work has been on weather rather than climate
and, in light of this and the equivocal nature of the results, neither the
detection of a climate change effect nor an assessment of its magnitude
can currently be made with a degree of confidence.
The impact of future climate change on human displacement and
migration has been identified as an emerging risk (Section 19.4.2.1).
The social, economic, and environmental factors underlying migration
are complex and varied (see, e.g., Black et al., 2011) and it has not been
possible to detect the effect of observed climate change nor assess its
magnitude with any degree of confidence (see also Section 12.4.1.1).
Migration in response to climate-related events has been identified in
sub-Saharan Africa (Marchiori et al., 2012), with evidence from North
America a subject of disagreement (Auffhammer and Vincent, 2012;
Feng et al., 2012; Feng and Oppenheimer, 2012).
18.4.6. Livelihoods and Poverty
The vulnerability of the world’s poor to climate change, and more
generally the sensitivity of many livelihood aspects to climate variability,
has been shown in this and earlier IPCC reports (see Chapter 13).
However, available research about climate-related effects on livelihood
and poverty has focused on impacts of climate extremes or year to year
climate variability rather than long-term climatic trends, resulting in a
paucity of evidence on observed impacts of climate change on livelihoods
and poverty. Moreover, detection of changes in livelihood aspects is often
difficult due to a lack of observations (Section 13.2.1), while multiple
confounding factors and lack of both adequate climate data and system
understanding preclude attribution (Nielsen and Reenberg, 2010).
Table 18-4 summarizes examples of impacts on livelihoods related to
climatic trends, climate variability, and extreme weather events.
Impacted natural assets include land, water, fish stocks, and livestock
(Osbahr et al., 2008; Bunce et al., 2010). There is growing concern about
negative effects of climate change and ocean acidification on marine
and coastal fisheries, and the livelihoods of fisherfolks (Cooley and
Doney, 2009; Badjeck et al., 2010); however, there are no studies
evaluating observed impacts.
Climate-related impacts disproportionately affect poor populations, thus
increasing social and economic inequalities, both in urban and rural areas,
and in low-, middle-, and high-income countries (Sections 13.1.4, 13.2.1).
Evidence for poor people in high-income nations being disproportionately
affected by extreme weather events comes, for instance, from 2005 U.S.
Hurricane Katrina (Elliott and Pais, 2006; Bullard and Wright, 2010; see
also Section 13.2.1.5) or severe drought in Australia (Alston, 2011).
Glacial lake outburst floods in the Peruvian Andes also affected different
populations depending on their degree of exposure, level of vulnerability,
race, ethnicity, and socioeconomic class (Carey, 2010; Carey et al., 2012b).
Owing to gender-specific roles within the household, communities, and
wider sociopolitical and institutional networks, a gender bias has been
found in observations of impacts of extreme weather events and climate
variability (Carr, 2008; Arora-Jonsson, 2011; Nightingale, 2011; see also
Box 13-1).
Impacted population Climate-related driver Impact on livelihood Reference
S
mall-scale farmers, Ghana Drought (past 20 – 30 years) Landscape transformation causing emotional distress, sense of loss
of belonging
T
schakert et al. (2013)
M
iddle-class farmers, Australia Drought (2000s) Landscape transformation, income loss from agriculture, social
confl ict, poverty
A
lston (2011)
A
rctic indigenous peoples Warming (past decades) Changing ice and snow conditions, dwindling access to hunting
g
rounds
S
ection 28.2.4; Table 18-9; Hovelsrud et
a
l. (2008); Ford (2009a); Brubaker et al.
(2011); Arctic Council (2013); Crate (2013)
U
rban populations in Maputo,
A
ccra, Nairobi, Lagos, Kampala
F
lood frequency and severity increase
(
1990s and 2000s)
D
irect impacts on people and loss of physical assets (e.g., housing) Douglas et al. (2008); Adelekan (2010)
Industry workers in India Temperature variability and heat waves
(
1960s to present)
Decrease of fully workable days since 1960; limited ability to carry
o
ut physical work; health impacts
Ayyappan et al. (2009); Balakrishnan et al.
(
2010); Dash and Kjellström (2011)
Farmers in Subarnabad,
B
angladesh
Sea level rise (~1980s to present) Salt water intrusion; shift from agriculture to shrimp farming; loss of
a
gricultural livelihoods
Pouliotte et al. (2009)
Women farmers, Ghana Rainfall-related climate variability
(~1990s and 2000s)
Adaptation practices in agriculture produce gender inequalities. Carr (2008)
C
ambodian rice farmers Warming, rainfall-related climate
variability (1980s to present)
S
hift in income generation patterns between men and women Resurreccion (2011)
Poor children in Africa and
L
atin America
Weather- and climate-related events
(
1980s to present)
Food price shocks, reduced caloric intake, physical stunting, long-
t
erm effects such as reduced lifetime earnings
Alderman (2010)
Smallholder farmers in
highlands of Bolivia
Locally perceived changes in
temperature means and extremes, and
r
ainfall seasonality (~1990s and 2000s)
Stress on household resources due to need to respond to increasing
plant pests; switching to other crop types or livestock
McDowell and Hess (2012)
Table 18-4 | Cases of regional livelihood impacts associated with weather- and climate-related events, inter-annual climate variability, or climate change (see also Table 18-3;
Section 13.2.1.1).
1003
Detection and Attribution of Observed Impacts Chapter 18
18
P
oor people living in hazard exposed areas in Africa and Latin America
were increasingly affected by floods and landslides in the 1990s and
2000s (high confidence; Handmer et al., 2012); however, most of this trend
was due to increased urbanization in such areas (Douglas et al., 2008;
Hardoy and Pandiella, 2009). There is evidence of a decline in average
precipitation in West Africa since 1960 (Lacombe et al., 2012), including
repeated droughts (Dietz et al., 2004; Armah et al., 2011), which in some
cases has been partly attributed to anthropogenic climate forcing (Held
et al., 2005; Jenkins et al., 2005; Biasutti and Giannini, 2006). However,
there is only limited evidence of changes in poverty among affected
small-holder and subsistence farmers that can be attributed to climate
drivers such as rainfall decline and droughts (Section 13.2.1).
Livelihoods of indigenous people in the Arctic have been identified as
among the most severely affected by climate change, including food
s
ecurity aspects, traditional travel and hunting, and cultural values and
references (Hovelsrud et al., 2008; Ford et al., 2009; Ford, 2009a,b;
Beaumier and Ford, 2010; Pearce et al., 2010; Olsen et al., 2011; Eira,
2012; Crate, 2013; see also Box 18-5, Table 18-9). Impacts of rising
temperatures, increased variability, and weather extremes on crops and
livestock of indigenous people in highlands were reported from Tibet
Autonomous Region, China (Byg and Salick, 2009), and the Andes of
Bolivia (McDowell and Hess, 2012).
18.5. Detection and Attribution of Observed
Climate Impacts across Regions
Since the AR4, significant new knowledge about detected impacts of
recent climate change has been gained from all continents and oceans
Mountains, snow and ice References
Confi dence
in
detection
Role of
climate
Climate
driver
Reference
behavior
Confi dence
in
attribution
Africa
Retreat of tropical highland glaciers in
East Africa
Mölg et al. (2008, 2012); Taylor et al. (2009) Very high Major Warming,
drying
No change High
Europe
Retreat of Alpine, Scandinavian, and
Icelandic glaciers
WGI AR5 Section 4.3.3; Bauder et al. (2007); Björnsson
and Pálsson (2008); Paul and Haeberli (2008); WGMS
(2008); Zemp et al. (2009); Andreassen et al. (2012);
Marzeion et al. (2012); Gardner et al. (2013)
Very high Major Warming No change High
Increase in rock slope failures in western
Alps
Sections 18.3.1.3 and 23.3.1.4; Fischer et al. (2012);
Huggel et al. (2012a)
High Major Warming No change Medium
Asia
Permafrost degradation in Siberia,
Central Asia, and the Tibetan Plateau
WGI AR5 Section 4.7.2; Section 24.4.2.2; Romanovsky
et al. (2010); Yang et al. (2013)
High Major Warming No change High
Shrinking mountain glaciers across most
of Asia
WGI AR5 Section 4.3.3; Section 24.4.1.2; Box 3-1;
Bolch et al. (2012); Cogley (2012); Gardelle et al.
(2012); Kääb et al. (2012); Yao et al. (2012); Gardner et
al. (2013); Stokes et al. (2013)
High Major Warming No change Medium
Australasia
Substantial reduction in ice and glacier
ice volume in New Zealand
WGI AR5 Section 4.3.3; Table 25-1; Chinn et al. (2012) High Major Warming No change Medium
Signifi cant decline in late-season snow
depth at three out of four alpine sites in
Australia 1957–2002
Table 25-1; Nicholls (2006); Hennessy et al. (2008) High Major Warming No change Medium
North
America
Shrinkage of glaciers across western and
northern North America
WGI AR5 Section 4.3.3; Gardner et al. (2013) High Major Warming No change High
Decreasing amount of water in spring
snowpack in western North America
1960–2002
Stewart et al. (2005); Mote (2006); Barnett et al. (2008) High Major Warming No change High
South and
Central
America
Shrinkage of Andean glaciers WGI AR5 Section 4.3.3; Section 27.3.1.1; Table 27-3;
Vuille et al. (2008); Bradley et al. (2009); Jomelli et
al. (2009); Poveda and Pineda (2009); Marzeion et al.
(2012); Gardner et al. (2013); Rabatel et al. (2013)
High Major Warming No change High
Polar
regions
Decreasing Arctic sea ice cover in
summer
WGI AR5 Section 4.2.2.1; ACIA (2005); AMAP (2011) Very high Major Air and
ocean
warming,
change
in ocean
circulation
No change High
Reduction in ice volume in Arctic glaciers WGI AR5 Section 4.3.3; ACIA (2005); Nuth et al. (2010);
AMAP (2011); Gardner et al. (2011, 2013); Moholdt
et al. (2012)
Very high Major Warming No change High
Decreasing snow cover across the Arctic Section 28.2.3.1; AMAP (2011); Callaghan et al. (2011) High Major Warming No change Medium
Widespread permafrost degradation,
especially in the southern Arctic
Section 28.2.1.1; AMAP (2011); Olsen et al. (2011) High Major Warming No change High
Ice mass loss along coastal Antarctica WGI AR5 Sections 4.3.3, 4.4, and 10.5.2.1; Gardner et
al. (2013); Miles et al. (2013)
Medium Major Warming No change Medium
Table 18-5 | Observed impacts of climate change reported since AR4 on mountains, snow, and ice, over the past several decades, across major world regions, with descriptors
for (1) the confi dence in detection of a climate change impact; (2) the relative contribution of climate change to the observed change, compared to that of non-climatic drivers;
(3) the main climatic driver(s) causing the impacts; (4) the reference behavior of the system in the absence of climate change; and (5) the confi dence in attribution of the impacts
to climate change. References to related chapters in this report are given as well as key references to other IPCC reports and the scientifi c literature. Absence of climate change
impacts from this table does not imply that such impacts have not occurred.
1004
Chapter 18 Detection and Attribution of Observed Impacts
18
Rivers, lakes, and soil moisture References
Confi dence
in
detection
Role of
climate
Climate driver
Reference
behavior
Confi dence
in
attribution
Africa
Reduced discharge in West African
r
ivers
d’Orgeval and Polcher (2008); Dai et al.
(
2009); Di Baldassarre et al. (2010)
Medium Major Reduced
p
recipitation
No change Low
Lake surface warming and water
c
olumn stratifi cation increases in the
G
reat Lakes and Lake Kariba
Section 22.3.2.2; Tierney et al. (2010);
N
debele-Murisa et al. (2011); Powers et al.
(
2011)
High Major Warming No change High
Increased soil moisture drought in
t
he Sahel since 1970, partially wetter
conditions since 1990
Section 22.2.2.1; Hoerling et al. (2006);
G
iannini et al. (2008); Greene et al. (2009);
Seneviratne et al. (2012)
Medium Major Change in
p
recipitation
No change Medium
Europe
C
hanges in the occurrence of extreme
river discharges and fl oods
S
ection 23.2.3; Schmocker-Fackel and Naef
(2010); Beniston et al. (2011); Cutter et
al. (2012); Vorogushyn and Merz (2012);
K
undzewicz et al. (2013)
L
ow Minor Change in
precipitation;
change in extreme
p
recipitation
N
o change Very low
Asia
Changes in water availability in many
C
hinese rivers
Table SM24-4; Zhang et al. (2007); Zhang, S.
e
t al. (2008)
High Minor Change in
p
recipitation
Changes due
t
o land use
Low
Increased fl ow in several rivers in China
d
ue to shrinking glaciers
Casassa et al. (2009); Li et al. (2010);
Z
hang, Y. et al. (2008)
High Major Warming No change High
Earlier timing of maximum spring fl ood
in Russian rivers
Section 28.2.1.1; Shiklomanov et al. (2007);
Tan et al. (2011)
High Major Warming No change Medium
R
educed soil moisture in North Central
and Northeast China 1950 – 2006
S
ections 24.3.1 and 24.4.1.2; Sheffi eld
and Wood (2007); Wang, A. et al. (2011);
Seneviratne et al. (2012)
M
edium Major Warming; change in
precipitation
N
o change Medium
Surface water degradation in parts
of Asia
Section 24.4.1.2; Prathumratana et al. (2008);
Delpla et al. (2009); Huang et al. (2009)
Medium Minor Warming; change in
precipitation
Changes due
to land use
Medium
Australasia
Intensifi cation of hydrological drought
due to regional warming in Southeast
Australia
Table 25-1; Nicholls (2006); Cai et al. (2009) Low Minor Warming No change Low
Reduced infl ow in river systems in
southwestern Australia (since the
mid-1970s)
Table 25-1; Section 25.5.1; Cai and Cowan
(2006); Nicholls (2010)
High Major Change in
precipitation;
warming
No change High
North
America
Shift to earlier peak fl ow in snow
dominated rivers in western North
America
Barnett et al. (2008) High Major Warming; change
in snow
No change High
Runoff increases in the midwestern and
northeastern USA
Georgakakos et al. (2013) High Minor Change in
precipitation;
warming
No change Medium
South and
Central
America
Changes in extreme fl ows in Amazon
River
Section 27.3.1.1; Butt et al. (2011); Wang, G.
et al. (2011); Espinoza et al. (2013)
High Major Change in
precipitation;
change in extreme
precipitation
No change Medium
Changing discharge patterns in rivers
in the Western Andes; for major river
basins in Colombia discharge has
decreased during the last 30 – 40 years
Section 27.3.1.1; Table 27-3; Vuille et al.
(2008); Casassa et al. (2009); Poveda and
Pineda (2009); Baraer et al. (2012); Rabatel
et al. (2013)
Medium Major Warming No change Medium
Increased streamfl ow in sub-basins of
the La Plata River
Section 27.3.1.1; Pasquini and Depetris
(2007); Krepper et al. (2008); Saurral et al.
(2008); Conway and Mahé (2009); Krepper
and Zucarelli (2010); Doyle and Barros (2011)
High Major Change in
precipitation
Increase due
to land use
High
Polar
regions
Increased river discharge for large
circumpolar rivers (1997 – 2007)
Section 28.2.1.1; Overeem and Syvitsky,
(2010)
High Major Warming; change in
precipitation; change
in snow cover
No change Low
Winter minimum river fl ow increase in
most sectors of the Arctic
Section 28.2.1.1; Tan et al. (2011) High Major Warming; change in
snow cover
No change Medium
Increasing lake water temperatures
1985 – 2009, prolonged ice-free seasons
Section 28.2.1.1; Callaghan et al. (2010);
Schneider and Hook (2010)
Medium Major Warming No change Medium
Thermokarst lakes disappear due to
permafrost degradation in the low
Arctic, new ones created in areas of
formerly frozen peat
Section 28.2.1.1; Riordan et al. (2006); Marsh
et al. (2008); Prowse and Brown (2010)
High Major Warming No change High
Small
islands
Increased water scarcity in Jamaica Gamble et al. (2010); Jury and Winter (2010) Low Minor Change in
precipitation
Increase due
to water use
Very low
Table 18-6 | Observed impacts of climate change reported since AR4 on rivers, lakes, and soil moisture, over the past several decades, across major world regions, with
descriptors for (1) the confi dence in detection of a climate change impact; (2) the relative contribution of climate change to the observed change, compared to that of
non-climatic drivers; (3) the main climatic driver(s) causing the impacts; (4) the reference behavior of the system in the absence of climate change; and (5) the confi dence in
attribution of the impacts to climate change. References to related chapters in this report are given as well as key references to other IPCC reports and the scientifi c literature.
Absence of climate change impacts from this table does not imply that such impacts have not occurred.
1005
Detection and Attribution of Observed Impacts Chapter 18
18
of the world, as assessed in Chapters 22 to 30 of this report. Tables
18-5 to 18-9 summarize impacts in major natural and human systems,
at the local to continental scale, for which assessment of the role of
climate as one driver has been possible. The following paragraphs
provide a summary of recent climate changes in these regions along
with notes about particular challenges in the regional assessments.
For much of Africa, knowledge about recent climate change is limited,
owing to weak climate monitoring and gaps in coverage that continue
to exist. On the other hand, the low natural temperature variability
over the continent allows earlier detection of warming signals. Thus
there is medium to high confidence in regional warming, with low to
high confidence in attribution to anthropogenic emissions. A main
regional feature has been the drying of the Sahel during the decades
following 1970, but that trend has halted during the most recent decade
(Hoerling et al., 2006; Giannini et al., 2008; Greene et al., 2009;
Seneviratne et al., 2012). African natural and human systems present
challenges for the potential detection and attribution of responses to
climate change. Given the weak spatial and temporal variations in
temperature, there is smaller scope for migrational and phenological
Continued next page
Terrestrial ecosystems References
Confi dence
in
detection
Role of
climate
Climate
driver
Reference
behavior
Confi dence
in
attribution
Africa
T
ree density decreases in Western Sahel
and semi-arid Morocco
S
ection 22.3.2.1; Gonzalez et al. (2012); Le
Polain de Waroux and Lambin (2012)
M
edium Major Change in
precipitation
C
hanges due to
land use
M
edium
R
ange shifts of several southern plants
and animals: South African bird species
p
olewards; Madagascan reptiles and
amphibians upwards; Namib aloe
contracting ranges
T
able 22-3; Foden et al. (2007); Raxworthy et
al. (2008); Hockey and Midgley (2009); Hockey
e
t al. (2011)
H
igh Major Warming Changes due to
land use
M
edium
W
ildfi res increase on Mt. Kilimanjaro Table 22-3; Hemp (2005) Medium Major Warming;
drying
N
o change Low
Europe
E
arlier greening, earlier leaf emergence
and fruiting in temperate and boreal trees
S
ection 4.3.2.1; Menzel et al. (2006) High Major Warming No change High
I
ncreased colonization of alien plant
species in Europe
S
ection 4.2.4.6; Table 23-6; Walther et al.
(2009)
M
edium Major Warming Some invasion Medium
Earlier arrival of migratory birds in Europe
s
ince 1970
Section 4.2.4.6; Table 23-6; Møller et al.
(
2008)
Medium Major Warming No change Medium
Upward shift in tree line in Europe Section 18.3.2.3; Table 23-6; Gehrig-Fasel et
al. (2007); Lenoir et al. (2008)
Medium Major Warming Changes due to
land use
Low
I
ncreasing burnt forest areas during
recent decades in Portugal and Greece
T
able 23-6; Camia and Amatulli (2009);
Hoinka et al. (2009); Costa et al. (2011);
Koutsias et al. (2012)
H
igh Major Warming;
change in
precipitation
S
ome increase
due to land use
H
igh
Asia
Changes in plant phenology and growth
in many parts of Asia (earlier greening),
particularly in the north and the east
Sections 4.3.2.1 and 24.4.2.2; Figure 4-4; Ma
and Zhou (2012); Panday and Ghimire (2012);
Shrestha et al. (2012); Ogawa-Onishi and
Berry (2013)
High Major Warming No change Medium
Distribution shifts in many plant and
animal species, particularly in the north of
Asia, upwards in elevation or polewards
Sections 4.3.2.5 and 24.4.2.2; Figure 4-4;
Moiseev et al. (2010); Chen et al. (2011); Jump
et al. (2012); Ogawa-Onishi and Berry (2013)
High Major Warming No change Medium
Invasion of Siberian larch forests by pine
and spruce during recent decades
Section 24.4.2.2; Kharuk et al. (2010); Lloyd
et al. (2011)
Medium Major Warming No change Low
Advance of shrubs into the Siberian
tundra
Sections 4.3.3.4, 24.4.2.2, and 28.2.3.1; Henry
and Elmendorf (2010); Blok et al. (2011)
High Major Warming No change High
Australasia
Changes in genetics, growth, distribution,
and phenology of many species, in
particular birds, butterfl ies and plants in
Australia
Table 25-3; Chambers (2008); Chessman
(2009); Green (2010); Kearney et al. (2010);
Keatley and Hudson (2012); Chambers et al.
(2013b)
High Major Warming Fluctuations due
to variable local
climates, land
use, pollution,
invasive species
High
Expansion of some wetlands and
contraction of adjacent woodlands in
southeast Australia
Table 25-3; Keith et al. (2010) Medium Major Change in
precipitation;
warming
No change Low
Expansion of monsoon rainforest at
expense of savannah and grasslands in
north Australia
Table 25-3; Banfai and Bowman (2007);
Bowman et al. (2010)
Medium Major Change in
precipitation;
increased CO
2
No change Medium
Migration of glass eels advanced by
several weeks in Waikato River, New
Zealand
Table 25-3; Jellyman et al. (2009) Medium Major Warming No change Low
Table 18-7 | Observed impacts of climate change reported since AR4 on terrestrial ecosystems, over the past several decades, across major world regions, with descriptors for:
(1) the confi dence in detection of a climate change impact; (2) the relative contribution of climate change to the observed change, compared to that of non-climatic drivers; (3)
the main climatic driver(s) causing the impacts; (4) the reference behavior of the system in the absence of climate change; and (5) the confi dence in attribution of the impacts
to climate change. References to related chapters in this report are given as well as key references to other IPCC reports and the scientifi c literature. Absence of climate change
impacts from this table does not imply that such impacts have not occurred.
1006
Chapter 18 Detection and Attribution of Observed Impacts
18
responses to anthropogenic climate change than in other parts of the
world. High-quality monitoring is relatively sparse in time and space, and
is often unsuitable for detecting changes across margins and borders
where responses to climate change are most expected. The dearth of
studies examining attribution questions means it is currently difficult
to estimate the degree to which studies are selectively published based
on results, and thus to determine whether each attribution study is
indicative only of local reasons for concern or if it is more generally
representative of a broader domain.
Amongst all continents, Europe has the longest tradition in climate
monitoring. Warming has been occurring across the continent in all
seasons, with an associated decreasing frequency of cold extremes and
increasing frequency of hot extremes (Seneviratne et al., 2012). The
Mediterranean basin has been getting drier, while northern areas have
been getting wetter (Section 23.2.2.1), with a general increase in the
frequency of extreme wet events everywhere (Seneviratne et al., 2012).
Asia spans a particularly wide range of climate types. Warming has been
observed throughout the continent, with northern areas among the fastest
warming on the planet. Precipitation trends vary geographically, with
a weaker Indian monsoon (WGI AR5 Section 14.2.2.1) and contrasting
increasing and drying trends over coastal and inland China (Section 24.3).
Warming has occurred in Australasia during the past century, with hot
extremes becoming more frequent and cold extremes becoming less
Terrestrial ecosystems References
Confi dence
in
detection
Role of
climate
Climate
driver
Reference
behavior
Confi dence
in
attribution
North
America
P
henology changes and species
distribution shifts upward in elevation and
n
orthward across multiple taxa
S
ection 26.4.1; Parmesan and Galbraith
(2004); Parmesan (2006); Kelly and Goulden
(
2008); Moritz et al. (2008); Tingley et al.
(
2009)
H
igh Major Warming No change Medium
Increased wildfi re frequency in subarctic
conifer forests and tundra
Section 28.2.3.1; Mack et al. (2011); Mann et
al. (2012)
High Major Warming No change Medium
R
egional increases in tree mortality and
insect infestations in forests
S
ection 26.4.2.1; Van Mantgem et al. (2009);
Peng et al. (2011)
M
edium Minor Warming No change Low
I
ncrease in wildfi re activity, fi re frequency
and duration, and burnt area in forests
of the western US and boreal forests in
C
anada
B
ox 26-2; Gillett et al. (2004); Westerling et al.
(2006); Girardin et al. (2013)
H
igh Minor Warming;
change in
precipitation
C
hanges due to
land use and fi re
management
M
edium
South and
Central
America
Increased tree mortality and forest fi re in
t
he Amazon
Section 4.3.3.1.3; Phillips et al. (2009) Medium Minor Warming No change Low
Degrading and receding rainforest in the
A
mazon
Sections 18.3.2.4, 27.2.2.1, and 27.3.2.1; Etter
e
t al. (2006); Nepstad et al. (2006); Oliveira et
al. (2007); Wassenaar et al. (2007); Killeen et
al. (2008); Nepstad and Stickler (2008)
Low Minor Warming Deforestation
a
nd land
degradation
Low
Polar
regions
I
ncrease in shrub cover in tundra in North
America and Eurasia
S
ection 28.2.3.1.2; Tape et al. (2006); Walker
et al. (2006); Henry and Elmendorf (2010);
B
lok et al. (2011); Elmendorf et al. (2012);
T
ape et al. (2012)
H
igh Major Warming No change High
Advance of Arctic tree-line in latitude and
altitude
Section 28.2.3.1.2; AMAP (2011); Hedenås et
al. (2011); Van Bogaert et al. (2011)
High Major Warming No change Medium
Loss of snow-bed ecosystems and tussock
tundra
Section 28.2.3.1.2; Björk and Molau (2007);
Molau (2010a); Hedenås et al. (2011);
Callaghan et al. (2013)
High Major Warming;
change in
precipitation
No change High
Impacts on tundra animals from increased
ice layers in snow pack, following rain-on-
snow events
Section 28.2.3.1.3; Callaghan et al. (2011);
Hansen et al. (2013)
Medium Major Change in
precipitation;
warming
No change Medium
Changes in breeding area and
population size of subarctic birds, due to
snowbed reduction and/or tundra shrub
encroachment
Molau (2010b); Callaghan et al. (2013) High Major Warming No change Medium
Increase in plant species ranges in the
West Antarctic Peninsula and nearby
islands over the past 50 years
Section 28.2.3.2; Fowbert and Smith (1994);
Parnikoza et al. (2009)
High Major Warming No change High
Increasing phytoplankton productivity in
Signy Island lake waters
Quayle et al. (2002); Laybourn-Parry (2003) High Major Warming No change High
Small
islands
Changes in tropical bird populations in
Mauritius
Section 29.3.2; Senapathi et al. (2011) Medium Major Change in
precipitation
No change Medium
Decline of an endemic plant in Hawai’i Krushelnycky et al. (2013) Medium Major Warming;
change in
precipitation
No change Medium
Upward trend in tree lines and associated
fauna on high-elevation islands
Section 29.3.2; Benning et al. (2002); Jump
et al. (2006)
Low Minor Warming No change Low
Table 18-7 (continued)
1007
Detection and Attribution of Observed Impacts Chapter 18
18
Continued next page
Coastal and marine
ecosystems
References
Confi dence
in
detection
Role of
climate
Climate driver
Reference
behavior
Confi dence
in
attribution
Africa
D
ecline in coral reefs in tropical
African waters
S
ections 30.5.3.1.2 and 30.5.4.1.5; Baker et al.
(2008); Carpenter et al. (2008); Ateweberhan et
a
l. (2011)
H
igh Major Ocean warming Decline due to
human impacts
H
igh
Europe
N
orthward shifts in the
distributions of zooplankton,
fi
sh, seabirds, and benthic
invertebrates in the northeast
A
tlantic
B
ox 6-1; Table 6-2; Sections 6.3.1, 23.6.5, and
30.5.1.1; Beaugrand et al. (2009); Philippart et
a
l. (2011)
H
igh Major Ocean warming No change High
Northward and depth shift in
distribution of many fi sh species
a
cross European seas
Sections 6.3.1, 23.6.4, 23.6.5, and 30.5.3.1;
Table 6-2; Perry et al. (2005); Pörtner et
a
l. (2008); Beaugrand et al. (2009, 2010);
Beaugrand and Kirby (2010); Hermant et al.
(
2010); Philippart et al. (2011)
High Major Ocean warming No change Medium
Phenology changes in plankton
i
n the northeast Atlantic
Box 6-1; Sections 6.3.1, 23.6.5, and 30.5.1.1;
B
eaugrand et al. (2002, 2009); Edwards and
Richardson (2004); Philippart et al. (2011)
Medium Major Ocean warming No change Medium
Spread of warm water species
i
nto the Mediterranean
Sections 23.6.5 and 30.5.3.1.5; Boero et al.
(
2008); Lasram and Mouillot (2009); Raitsos et
al. (2010)
High Major Ocean warming Changes due to
i
nvasive species
and human
i
mpacts
Medium
Asia
Decline in coral reefs in tropical
Asian waters
Sections 24.4.3.2 and 30.5.1.4.3; McLeod et al.
(2010); Krishnan et al. (2011); Coles and Riegl
(2012)
High Major Ocean warming Decline due to
human impacts
High
Northward range extension of
coral in the East China Sea and
western Pacifi c, and a predatory
fi sh in the Sea of Japan
Section 24.4.3.2; Yamano et al. (2011); Tian et al.
(2012); Ogawa-Onishi and Berry (2013)
Medium Major Ocean warming No change Medium
Shift from sardines to anchovies
in the western North Pacifi c
Sections 6.3.1 and 6.3.6; Table 6-2; Takasuka et
al. (2007, 2008)
Medium Major Ocean warming Fluctuations due
to fi sheries
Low
Increased coastal erosion in
Arctic Asia
Section 24.4.3.2; Razumov (2010); Forbes
(2011); Lantuit et al. (2011)
Medium Major Permafrost
degradation, ocean
warming, change in
sea ice
No change Low
Australasia
Southward shifts in the
distribution of marine species
near Australia
Table 25-3; Ling et al. (2009b); Pitt et al. (2010);
Neuheimer et al. (2011); Wernberg et al. (2011b)
High Major Ocean warming Changes due
to short-term
environmental
fl uctuations;
fi shing and
pollution
Medium
Change in timing of migration of
seabirds in Australia
Section 25.6.2.1; Chambers et al. (2011, 2013a) Medium Major Air and ocean
warming
No change Low
Increase in coral bleaching in the
Great Barrier Reef and Western
Australian Reefs
Sections 6.3.1.4, 6.3.1.5, and 25.6.2.1; Table
25-3; Cooper et al. (2008); De’ath et al. (2009,
2012); Moore et al. (2012)
High Major Ocean warming Pollution;
physical
disturbance
High
Changes in coral disease patterns
at Great Barrier Reef
Section 25.6.2.1; Table 25-3; Bruno et al. (2007);
Sato et al. (2009); Dalton et al. (2010)
Medium Major Ocean warming Pollution Medium
North
America
Northward shifts in the
distributions of northwest
Atlantic fi sh species
Section 30.5.1.1; Nye et al. (2009, 2011); Lucey
and Nye (2010)
High Major Ocean warming No change High
Changes in mussel beds along
the west coast of the USA
Smith et al. (2006); Menge et al. (2008); Harley
(2011)
High Major Ocean warming No change High
Changes in migration and
survival of salmon in the
northeast Pacifi c
Table 6-2; Eliason et al. (2011); Kovach et al.
(2012)
High Major Ocean warming No change High
Increased coastal erosion in
Alaska and Canada
Sections 18.3.1.1 and 18.3.3.1; Mars and
Houseknecht (2007); Forbes (2011); Lantuit et
al. (2011)
High Major Permafrost
degradation; ocean
warming, change in
sea ice
No change Medium
Table 18-8 | Observed impacts of climate change reported since AR4 on coastal and marine ecosystems, over the past several decades, across major world regions, with
descriptors for (1) the confi dence in detection of a climate change impact; (2) the relative contribution of climate change to the observed change, compared to that of
non-climatic drivers; (3) the main climatic driver(s) causing the impacts; (4) the reference behavior of the system in the absence of climate change; and (5) the confi dence in
attribution of the impacts to climate change. References to related chapters in this report are given as well as key references to other IPCC reports and the scientifi c literature.
Absence of climate change impacts from this table does not imply that such impacts have not occurred.
1008
Chapter 18 Detection and Attribution of Observed Impacts
18
frequent (Section 25.2, Table 25-1). Winters in southern areas of
Australia have become drier in the past few decades and the northwest
has become wetter, and precipitation increased over the south and west
of both islands of New Zealand. Though there have been no significant
trends in drought frequency over Australia, regional warming may have
increased their hydrological intensity, and fire weather increased since
1973 in Australia (Table 25-1; Clarke et al., 2012).
North America spans a wide range of climate types and observed climate
changes. While the northwest has been among the fastest warming
regions on the planet, the southeast of the USA has experienced slight
cooling (Section 26.2.2.1). Hot extremes have been becoming more
frequent while cold extremes and frost days have been becoming less
frequent over the past several decades. Trends in precipitation over
western parts of the continent are strongly influenced by the variability
of the ENSO, with a matching drying and decreasing snowpack. The
intensity of precipitation events has been increasing over most of the
continent, but trends in dryness are spatially heterogeneous (Section
26.2.2.1). Intense tropical storms have increased in the North Atlantic
over the past several decades (WGI AR5 Section 2.6.3).
Most of Central and South America has warmed over the past half
century, except for a slight cooling over a western coastal strip (Section
27.2.1). Precipitation over much of Central and South America is strongly
influenced by the ENSO, with accompanying long-term variability.
There has been a reduction in the number of dry summer months in the
southern half of the continent, while trends over the Amazon are
sensitive to the selection of time period (Section 27.2.1). More frequent
and severe droughts in the Amazon have been linked to warming
(Marengo et al., 2011a).
The areas of largest observed warming are all polar: the northwest of
North America, northern Asia, and the Antarctic Peninsula. The nature
of polar regions means that warming can lead to large changes in other
Coastal and marine
ecosystems
References
Confi dence
in
detection
Role of
climate
Climate driver
Reference
behavior
Confi dence
in
attribution
South and
Central
America
Increase in coral bleaching in the
w
estern Caribbean
Section 27.3.3.1; Guzman et al. (2008); Manzello
e
t al. (2008); Carilli et al. (2009); Eakin et al.
(
2010)
High Major Ocean warming Pollution;
p
hysical
d
isturbance
High
Mangrove degradation on north
c
oast of South America
Section 27.3.3.1; Alongi (2008); Lampis (2010);
P
olidoro et al. (2010); Giri et al. (2011)
Low Minor Ocean warming Degradation due
t
o pollution and
land use
Low
Polar
regions
I
ncreased coastal erosion across
the Arctic
S
ections 18.3.1.1, 18.3.3.1, 28.2.4.2, and 28.3.4;
Mars and Houseknecht (2007); Razumov (2010);
F
orbes (2011); Lantuit et al. (2011)
M
edium Major Permafrost
degradation; ocean
w
arming, change in
s
ea ice
N
o change Medium
Negative effects on non-
m
igratory Arctic species
Section 28.2.2.1; Laidre et al. (2008); Amstrup et
a
l. (2010); McIntyre et al. (2011)
High Major Atmospheric and
o
cean warming;
circulation change;
c
hange in sea ice
No change High
Decreased reproductive success
in Arctic seabirds
Section 28.2.2.1.2; Gaston et al. (2009);
Grémillet and Boulinier (2009)
Medium Major Air and ocean
warming; change in
o
cean circulation;
change in sea ice
No change Medium
D
ecline in Southern Ocean seals
and seabirds
S
ection 28.2.2.2; Croxall et al. (2002); Patterson
et al. (2003); Jenouvrier et al. (2005); Véran et
a
l. (2007); Forcada et al. (2008); Trathan et al.
(2011); Chambers et al. (2013a)
H
igh Major Ocean warming No change Medium
Reduced thickness of
f
oraminiferal shells in the
Southern Ocean
Sections 6.3.2 and 28.2.2.2; Moy et al. (2009) Medium Major Ocean acidifi cation No change Medium
Reduced density of krill in the
Scotia Sea
Atkinson et al. (2004); Trivelpiece et al. (2011) Medium Major Ocean warming;
change in ocean
circulation; change
in sea ice
No change Medium
Small
islands
Increased coral bleaching near
many tropical small islands
Section 29.3.1.2; Alling et al. (2007); Bruno and
Selig (2007); Oxenford et al. (2008); Sandin et
al. (2008)
High Major Ocean warming Degradation due
to fi shing and
pollution
High
Degradation of mangroves,
wetlands, and seagrass around
small islands
Section 29.3.1.2; McKee et al. (2007); Gilman
et al. (2008); Schleupner (2008); Krauss et al.
(2010); Marbà and Duarte (2010); Rankey (2011)
Low Minor Sea level rise;
atmospheric and
ocean warming
Degradation
due to other
disturbances
Very low
Increasing fl ooding and erosion Section 29.3.1.1; Webb (2006); Webb (2007);
Yamano et al. (2007); Cambers (2009); Novelo-
Casanova and Suarez (2010); Storey and Hunter
(2010); Ballu et al. (2011); Rankey (2011); Ford
(2012); Romine et al. (2013)
Low Minor Sea level rise Erosion due to
human activities,
natural erosion,
and accretion
Low
Degradation of groundwater and
freshwater ecosystems due to
saline intrusion
Section 29.3.2; White et al. (2007a,b); Ross et al.
(2009); Carreira et al. (2010); Terry and Falkland
(2010); White and Falkland (2010); Goodman
et al. (2012)
Low Minor Sea level rise Degradation due
to pollution and
groundwater
pumping
Low
Table 18-8 (continued)
1009
Detection and Attribution of Observed Impacts Chapter 18
18
Continued next page
Human and managed
systems
References
Confi dence
in
detection
Role of
climate
Climate
driver
Reference
behavior
Confi dence
in
attribution
Africa
A
daptative responses to changing
rainfall by South African farmers
S
ection 13.2.1.2; Thomas et al. (2007) Low Major Change in
precipitation
C
hanges due
to economic
c
onditions
V
ery low
Decline in fruit-bearing trees in Sahel Wezel and Lykke (2006); Maranz (2009) Medium Major Change in
p
recipitation
No change Low
Malaria increases in Kenyan
highlands
Section 11.5.1.1; O’Meara et al. (2010); Alonso et
al. (2011); Stern et al. (2011)
Low Minor Warming Changes due
to vaccination,
d
rug resistance,
demography,
a
nd livelihoods
Low
Reduced fi sheries productivity of
G
reat Lakes and Lake Kariba
Sections 7.2.1.2, 13.2.1.1, and 22.3.2.2; Descy
a
nd Sarmento (2008); Hecky et al. (2010);
Ndebele-Murisa et al. (2011); Marshall (2012)
Low Minor Warming Changes due
t
o fi sheries
management
and land use
Low
Europe
S
hift from cold-related mortality to
heat-related mortality in England
a
nd Wales
S
ections 18.4.4 and 23.5.1; Christidis et al.
(2010)
M
edium Major Warming Changes due to
exposure and
h
ealth care
L
ow
Impacts on livelihoods of Sámi
p
eople in northern Europe
Eira (2012); Mathiesen et al. (2013) Medium Major Warming Economic and
s
ociopolitical
changes
Medium
Stagnation of wheat yields in some
countries in recent decades
Section 23.4.1; Brisson et al. (2010); Kristensen
et al. (2011)
High Minor Warming Increase due
to improved
technology
Medium
Positive yield impacts for some crops,
mainly in northern Europe
Figure 7-2; Section 23.4.1; Jaggard et al. (2007);
Supit et al. (2010); Gregory and Marshall (2012)
High Minor Warming Increase due
to improved
technology
Medium
Spread of bluetongue virus in sheep,
and of ticks across parts of Europe
Section 23.4.2; Arzt et al. (2010); Randolph and
Rogers (2010); Van Dijk et al. (2010); Guis et al.
(2012); Petney et al. (2012)
High Minor Warming No change Medium
Asia
Impacts on livelihoods of indigenous
groups in Arctic Russia
Sections 13.2.1.2, 18.4.6, and 28.2.4.2; Table
18-4; Crate (2013)
Medium Major Warming; change
in snow cover;
change in sea ice
Economic and
sociopolitical
changes
Low
Negative impacts on aggregate
wheat yields in South Asia
Section 7.2.1; Figure 7-2; Pathak et al. (2003) Medium Minor Warming; change
in precipitation
Increase due
to improved
technology
Medium
Negative impacts on aggregate
wheat and maize yields in China
Section 7.2.1; Figure 7-2; Tao et al. (2006, 2008,
2012); You et al. (2009); Chen et al. (2010)
Low Minor Warming Increase due
to improved
technology
Low
Increases in a water-borne disease
in Israel
Paz et al. (2007) Low Minor Warming No change Low
Australasia
Advance timing of wine-grape
maturation in recent decades
Table 25-3; Webb et al. (2012) High Major Warming Advance due
to improved
management
Medium
Shift in winter versus summer human
mortality in Australia
Sections 11.4.1, 18.4.4, and 25.8.1.1; Bennett
et al. (2013)
Medium Major Warming Changes due to
exposure and
health care
Low
Relocation or diversifi cation of
agricultural activities in Australia
Section 25.7.2; Box 25-5; Gaydon et al. (2010);
Howden et al. (2010); Park et al. (2012); Thorburn
et al. (2012)
Medium Minor Warming Changes due to
policy, markets,
and short-
term climate
variability
Low
Central
and South
America
More vulnerable livelihood
trajectories for indigenous Aymara
farmers in Bolivia, due to water
shortage
Section 13.1.4; McDowell and Hess (2012) Medium Major Warming Increasing
social and
economic
stress
Medium
Increase in agricultural yields and
expansion of agricultural areas in
southeastern South America
Section 27.3.4.1; Magrin et al. (2007); Barros
(2010); Hoyos et al. (2013)
Medium Major Precipitation
increase
Increase due
to improved
technology
Medium
Table 18-9 | Observed impacts of climate change reported since AR4 on human and managed systems, over the past several decades, across major world regions, with
descriptors for (1) the confi dence in detection of a climate change impact; (2) the relative contribution of climate change to the observed change, compared to that of
non-climatic drivers; (3) the main climatic driver(s) causing the impacts; (4) the reference behavior of the system in the absence of climate change; and (5) the confi dence in
attribution of the impacts to climate change. References to related chapters in this report are given as well as key references to other IPCC reports and the scientifi c literature.
Absence of climate change impacts from this table does not imply that such impacts have not occurred.
1010
Chapter 18 Detection and Attribution of Observed Impacts
18
aspects of the climate system, in particular the observed decrease in
summer sea ice cover, earlier thaw, earlier spring runoff, and thawing
of permafrost (Section 28.2).
Despite the widely accepted high vulnerability of many small islands to
climate change, there are only few formal studies on observed impacts.
Detection of climate change impacts in small islands is challenging due to
the strong presence of other anthropogenic drivers of local environmental
change. Attribution is further challenged by the strong influence of
natural variability compared to incremental changes of climate drivers
and by the lack of long-term monitoring and high-quality data.
18.6. Synthesis: Emerging Patterns of
Observed Impacts of Climate Change
18.6.1. Approach
The AR4 precursor of the current chapter (Rosenzweig et al., 2007)
provided a geographically distributed empirical analysis of correlations
across numerous detailed and localized studies of changing systems
(elaborated more later in Rosenzweig et al., 2008). Rather than expand
that approach, this synthesis organizes the findings on detection and
attribution of observed impacts of climate change aiming at covering
the full disciplinary, sectoral, and geographic diversity of impacts, drawn
directly from sectoral and regional assessments in this report.
A key motivation for the effort in assessing these observed changes is
the possibility that observed impacts could constitute indications of future
expected changes. Observed losses in glacial volume, for example, lend
important additional plausibility to model-based expectations that
sustained warming could result in additional ice loss. Such extrapolation
faces important limitations, however. First, owing to the complex
nonlinear behavior of most natural and human systems, it cannot always
be assumed that past impacts scale linearly to future impacts. Likewise,
absence of past impacts cannot constitute evidence against the
possibility of future impacts. Nonetheless, detection and attribution of
observed impacts may serve as part of the foundation for a climatic risk
analysis. To do so, the total body of observed impacts needs to undergo
a synthetic assessment pointing toward any conceivable risks.
Virtually all observed impacts of climate change are of regional nature
(Section 18.5); however, the occurrence of similar impacts in many
regions of the world emerges more strongly with every IPCC assessment.
The global pattern emerging from the sum of observed regional impacts
is therefore analyzed in Section 18.6.2. The current body of observations
provides improved evidence of major impacts in natural and human
systems that have “cascading” consequences for other systems—key
examples for these are synthesized in Section 18.6.3. Finally, Section
18.6.4 aims to establish current conditions concerning the risk analysis
model formulated earlier by the IPCC through the establishment of a
limited number of “Reasons for Concern” (RFC)—the risk analysis itself
is part of Chapter 19 of this report.
18.6.2. The Global Pattern of Regional Impacts
The global pattern of observed climate change differs strongly for the
different climate variables. Broadly, more warming has occurred at
higher latitudes than in the Tropics, while the pattern of rainfall changes
is highly complex (WGI AR5 Chapter 2). Taken together, this provides a
heterogeneous pattern of climate change across the globe. In addition,
some natural and human systems (and the regions in which they
occur) are more vulnerable to changing climate than others. Crucially,
observational records are of highly heterogeneous nature: not only do
low-income countries report fewer impacts than high-income countries,
but there is also a significant shortage of observations from remote
areas such as the deep sea or sparsely populated mountains and
deserts. Taken together, it is therefore natural to expect an uneven
distribution of detected impacts (Figure 18-3).
The outstanding finding about the global pattern of observed impacts
is that, on all continents and across major ocean regions, significant
impacts have now been observed. Many of these concern systems which
are affected directly by warming (the cryosphere, marine systems), but
a growing number of observed impacts have been shown to be the
result of a combination of changing temperature and precipitation
(agricultural and hydrological systems).
The global distribution of observed impacts shown in Figure 18-3
demonstrates that analyses can now detect impacts in systems strongly
Human and managed
systems
References
Confi dence
in
detection
Role of
climate
Climate
driver
Reference
behavior
Confi dence
in
attribution
North
America
I
mpacts on livelihoods of indigenous
groups in the Canadian Arctic
S
ections 18.4.6 and 28.2.4.2; Table 18-4;
Hovelsrud et al. (2008); Ford et al. (2009);
B
eaumier and Ford (2010); Pearce et al. (2010);
Brubaker et al. (2011)
M
edium Major Warming; change
in snow cover;
c
hange in sea ice
E
conomic and
sociopolitical
c
hanges
M
edium
Polar
regions
I
mpact on livelihoods of Arctic
i
ndigenous peoples
S
ections 18.4.6 and 28.2.4.2; Table 18-4;
H
ovelsrud et al. (2008); Ford et al. (2009);
B
eaumier and Ford (2010); Pearce et al. (2010);
Eira (2012); Crate (2013); Mathiesen et al. (2013)
M
edium Major Warming; change
i
n snow cover;
c
hange in sea ice
E
conomic and
s
ociopolitical
c
hanges
M
edium
I
ncrease of shipping traffi c across the
Bering Strait
S
ection 28.2.6.1.3; Figure 28-4; Robards (2013) Medium Major Warming; change
in sea ice
N
o change Medium
Small
islands
I
ncreased degradation of coastal
fi sheries due to direct effects and
effects of increased coral reef
b
leaching
B
ox CC-CR; Sections 18.3.3.3, 18.4.1.2, 29.3.1.2,
and 30.6.2.1
L
ow Minor Ocean warming Coastal
fi sheries
degraded by
o
verfi shing and
pollution
L
ow
Table 18-9 (continued)
1011
Detection and Attribution of Observed Impacts Chapter 18
18
medlow
very
high
very
low
high
Glaciers, snow, ice
and/or permafrost
indicates
confidence range
Rivers, lakes, floods,
and/or drought
Terrestrial ecosystems
Regional-scale
impacts
Marine ecosystems
Coastal erosion
and/or sea level effects
Wildfire
Livelihoods, health,
and/or economics
Food production
Physical systems Biological systems Human and managed systems
Filled symbols / bars = Major contribution of climate change
Outlined symbols / bars = Minor contribution of climate change
Confidence in attribution to
climate change
Observed impacts attributed to climate change for
ANTARCTIC
CENTRAL & SOUTH
AMERICA
SMALL ISLANDS
SMALL ISLANDS
AFRICA AUSTRALASIA
AUSTRALASIA
EUROPE
EUROPE
ASIA
ASIA
ARCTICNORTH AMERICA
NORTH
AMERICA
Figure 18-3 | Global patterns of observed climate change impacts reported since AR4. Each filled symbol in the top panels indicates a class of systems for which climate change has played a major role in observed changes in at least one
system within that class across the respective region, with the range of confidence in attribution for those region-wide impacts indicated by the bars. Regional-scale impacts where climate change has played a minor role are shown by
outlined symbols in a box in the respective region. Sub-regional impacts are indicated with symbols on the map, placed in the approximate area of their occurrence. The impacted area can vary from specific locations to broad areas such as
a major river basin. Impacts on physical (blue), biological (green), and human (red) systems are differentiated by color. This map represents a graphical synthesis of Tables 18-5, 18-6, 18-7, 18-8, and 18-9. Absence of climate change impacts
from this figure does not imply that such impacts have not occurred.
1012
Chapter 18 Detection and Attribution of Observed Impacts
18
Land surface
warming
Ocean surface and
atmospheric warming
Wind and ocean
circulation changes
Ocean and
atmosphere
circulation changes
Atmospheric warming
Precipitation changes
G
lacial shrinkage
(
very high/high)
Sea ice recession, earlier
breakup (very high/high)
C
hanges in river discharge
p
atterns (medium/medium)
I
ncreased runoff in
g
lacial-fed rivers (high/high)
Cryosphere
Impacts on livelihoods of indigenous
peoples (medium/medium)
Effects on non-migratory
marine animals (high/high)
I
ncreased coastal erosion
(
medium/medium)
C
hanges in locations of
t
hermokarst lakes (high/high)
D
ecreasing spring
s
nowpack (high/high)
Western North America Western Andes Asia Arctic
Increased coral mortality and
bleaching (very high/high)
Range shifts of fish and
m
acroalgae (high/high)
Changes in
fishery yields
(low/low)
I
mpacts on large non-fish
species (high/high)
Regional changes in
species abundance
(high/medium)
Ocean
Physical impacts Biological impacts Impacts on managed systems
Forests
High elevation islands
Western North America
Western Sahel
Upward shift in treelines
(low/low)
Increase in insect pests
(medium/low)
Increased soil moisture drought
(medium/medium)
Upward shift in fauna
(low/low)
Increased tree mortality
(medium/low)
Decreased tree density
(medium/medium)
Description of impact
(confidence in detection/confidence in attribution)
Attribution of climate change role
Major role Minor role
Expansion of hypoxic
z
ones (medium/low)
Arctic sea ice retreat
(very high/high)
Ocean
surface
warming
Increased thermal
stratification (very
high/very high)
Increased primary production at
high latitudes (medium/medium)
E
arly spring peak
fl
ow (high/high)
P
ermafrost degradation
(
high/high)
Changes in species
richness (high/medium)
Figure 18-4 | Major systems where new evidence indicates interconnected, “cascading” impacts from recent climate change through several natural and human subsystems.
Text in parentheses indicates confidence in the detection of a climate change effect and the attribution of observed impacts to climate change. The role of climate change can be
major (solid arrow) or minor (dashed arrow). Confidence is assessed in Sections 18.3, 18.4, 18.5, and 18.6.
1013
Detection and Attribution of Observed Impacts Chapter 18
18
i
nfluenced by confounding factors and hence where climate change
plays only a minor role. The most outstanding examples for this are
agricultural systems where impacts now emerge in a number of places.
An identified minor role of climate for some impact does not imply that
this role is less important. New studies now identify more clearly such
roles even when they are masked by stronger confounding factors such
as environmental degradation or improved technology. Examples for such
studies include assessments of mangrove degradation, caused by both
warming and pollution (Giri et al., 2011), or changes in Inuit livelihoods,
influenced by both warming and social changes (Ford et al., 2009).
Enhanced research efforts would probably add additional observations
of impacts with a minor, but important, role of climate to the global map.
18.6.3. Cascading Impacts
Many impacts of climate change are direct cause-effect relationships,
such as reduction of glacier volume following higher temperatures.
Others may be mediated through impacts on intermediary systems (e.g.,
Johnson et al., 2011). Enhanced evidence of observed impacts of climate
change, and improved research methodologies now allow attribution
of effects at various stages along the causal impact chain (Figure 18-4).
Within the cryosphere, changes in atmospheric and ocean properties of
the climate have driven changes in the cryosphere on the land surface,
the land subsurface, and the ocean surface. These changes have in turn
led to changes in multiple aspects of hydrology and ecosystems, and in
some regions (e.g., the Arctic) changes in these systems have impacted
human livelihoods (Xu et al., 2009). Within most ocean regions,
warming has led to a number of observed impacts on biota, some of
w
hich are mediated through the effect of warming on the ocean’s thermal
stratification or on sea ice. Impacts tend to propagate up the food chain,
eventually affecting large mammals, birds, reptiles, and humans. In
forests and woodlands, climate change impacts on trees have been
transmitted through pests, fire, and drought, while impacts on forests
have also been observed to affect the forest fauna. In all these cases,
confidence in detection and attribution to observed climate change
decreases for effects further down each impact chain.
18.6.4. Reasons for Concern
To synthesize its findings in support of a risk analysis the IPCC in its
Third Assessment Report (TAR) developed the “Reasons for Concern”
(RFC) concept (Smith et al., 2001), which was adopted for a second time
in IPCC AR4 (IPCC, 2007b), and elaborated in Smith et al. (2009). It is
further developed in Chapter 1 of this report and employed extensively
in Chapter 19 for the risk framing approach of WGII AR5. In this chapter,
the goal is to establish, qualitatively, the evidence of impacts already
observed that are relevant to these categories (names of categories have
been adapted for consistency across Chapters 1, 18, and 19; see below).
The broad definitions of the RFC continue to imply significant overlap;
hence some observed impacts are referred to under more than one RFC.
The RFC Risks to Unique and Threatened Systems is concerned with the
potential for increased damage to, or irreversible loss of, systems such
as physical systems, ecosystems, and human livelihoods, all of which are
known to be highly sensitive to temporal and/or spatial variations in
climate. Figure 18-5 displays confidence levels in the current evidence
Very low
Low
Medium
Confidence in attribution
High
Very high
Very low Low Medium
Confidence in detection
High Very high
Livelihood impacts on indigenous Arctic peoples
Shrinking/receding glaciers
Mountain and lowland permafrost degradation
Increased bleaching of warm-water corals
Changes in Arctic marine ecosystems
Shrub increase in Arctic tundra
Degrading and receding rainforest in the Amazon
Increased tree mortality in boreal forests
Human systems
Terrestrial ecosystems
Physical systems
Marine ecosystems
Global
assessment
Attribution of major role
Attribution of minor role
Regional
assessment
Figure 18-5 | Confidence in detection and attribution of observed impacts on “Unique and Threatened Systems” as a result of recent climate change. Global assessments (large
circles) and regional assessments (small circles) are discussed in Sections 18.3.1.1 and 18.3.2.4, Box 18-2, and Tables 18-2 and 18-5 through 18-9. Attribution assessments are
for a minor (outlined circles) or major (filled circles) role of climate change, as indicated.
1014
Chapter 18 Detection and Attribution of Observed Impacts
18
derived from detection and attribution studies of such observed impacts.
Changes in the three indicated main natural systems (physical systems,
marine and terrestrial ecosystems) have at least high confidence in
attribution of a major role of climate change, with regional assessments
also tending to have similar confidence. There is at least medium
confidence in attribution of a major role for at least one each of
ecosystems, physical systems, and human systems.
The unique and threatened systems with strongest detection and
attribution evidence cover the Arctic, warm-water coral reefs, and
mountains. In the Arctic, climate change has played a major role in
observed impacts on glaciers, permafrost, the tundra, marine ecosystems,
and livelihoods of indigenous peoples (at least medium confidence),
reflecting large-scale changes across both natural and human systems
and across the physical and ecological sub-regions. Evidence for the
detection and attribution of shrinkage and recession of glaciers comes
from all continents, while evidence for attribution of coral bleaching
spans a similarly broad area of the tropical oceans (see Figure 18-5).
The RFC Risks Associated with Extreme Weather Events“tracks increases
in extreme events with substantial consequences for societies and
natural systems” (Smith et al., 2009, p. 4134). Besides episodic (e.g.,
coral bleaching) and chronic (e.g., erosion) impacts of extreme weather
events, this RFC also considers increased frequency of extreme impact
events (e.g., floods), even if their climate drivers are not wholly episodic
in nature. A change in the risk of impacts of extreme weather events
could be caused by a change in the probability, intensity, or sequencing
of the weather event itself (which are manifestations of recent climate
change), or by a change in exposure, vulnerability, or the resilience of
t
he impacted system. Trends have been noted for extreme weather
hazards. Temperature extremes have changed in most regions over the
past half century, with more frequent hot events and less frequent cold
events (high confidence; Hansen et al., 2012; Seneviratne et al., 2012;
Coumou et al., 2013; see WGI AR5 Section 2.6.1). Some regions have
also experienced increasingly frequent periods of heavy precipitation
events (medium confidence; Min et al., 2011), while other regions have
experienced positive or negative trends in measures of dry spells
(Seneviratne et al., 2012). Current evidence does not, however, indicate
sustained global trends in tropical cyclone or extratropical cyclone
activity (Seneviratne et al., 2012; see WGI AR5 Section 2.6.3).
Table 18-10 summarizes new evidence concerning this RFC. Generally,
the strongest evidence of detected impacts related to extremes concerns
warm-water corals where bleaching has been linked directly to high-
temperature spells (Box 18-2; Baker et al., 2008; Strong et al., 2011).
Outside of these coral reef systems, however, evidence for extreme
event impacts is limited and mostly local. Overall, a number of trends
in observed impacts on natural systems have been documented that
indicate changing risks driven by changes in extreme weather
(medium confidence), but any similar trends in human systems have
not been detected against large shifts in exposure, vulnerability, and
resilience.
Impacts and impact events Climate/ weather drivers
Reference
Observed trend
Confi dence
in
detection
Reference behavior
Confi dence
in
attribution
Role of
climate
change
Observed trend
Confi dence
in existence
of trend
Earlier timing
and decreasing
magnitude of
snowmelt fl oods
Medium
No change Medium Major Decreasing snow pack High Section 3.2.7; Tables 18-5 and 18-6; WGI
AR5 Section 4.5; Seneviratne et al. (2012)
Increasing heavy
precipitation amounts
Medium
Changes in fl ood
frequency and
magnitude in non-
snowmelt–fed rivers
Low Changes due to land use Low Minor Trends in extreme rainfall
amounts
Medium Min et al. (2011); WGI AR5 Sections 2.5.2
and 2.6.2
Increased evapotranspiration
and decreased soil moisture
Medium
Increased coastal
erosion in low and
mid latitudes
Very low Erosion due to shoreline
modifi cation and natural
processes
Very low Minor Increasingly frequent high
storm waves and surges
High Sections 5.4.2 and 18.3.3.1; WGI AR5
Section 3.7.5
Increased erosion of
Arctic coasts
Medium No change Medium Major Lack of sea ice protection
from wind storms
Very high Table 18-8; Sections 18.3.1.1, 24.4.3.2,
28.2.4.2, and 28.3.4; Forbes (2011); WGI
AR5 Section 4.2.2
Increase in high-
mountain rock slope
failures
Low No change Low Major Increasingly frequent and
intense heat waves
Medium Figure 18-2; Huggel et al. (2012a);
Seneviratne et al. (2012); Allen and
Huggel (2013); WGI AR5 Section 2.6.1
Increased coral
bleaching
Very high Changes due to pollution,
physical disturbance, and
fi shing
High Major Increasingly frequent
extreme hot surface waters
Very high Tables 18-2 and 18-8; Sections 5.2.4.2,
6.3.1, 24.4.3.2, 27.3.3.1, 29.3.1.2,
30.3.1.1, and 30.5; Box 18-2
Increased monetary
losses
Low Changes due to exposure
and wealth
Low Minor Increased frequency of
storms
Low Sections 10.7.3 and 18.4.3.1; Seneviratne
et al. (2012); WGI AR5 Section 2.6
Increased frequency of fl oods Low
Increased heat
related mortality
Low Changes due to exposure
and health care
Very low Minor Increased frequency of heat
waves
Medium Section 11.4.1; Seneviratne et al.
(2012);WGI AR5 Section 2.6.1
Table 18-10 | Confi dence in detection and attribution of observed trends in impacts related to extreme weather. The assessment, for the impacts on various systems, is of
attribution of those trends to climate change and of the confi dence in existence of observed trends in that extreme weather. The assessment of confi dence in detection is against
the specifi ed reference behavior, while the assessment of attribution is for the indicated minor or major role of observed climate trends. The confi dence statements refer to a
globally balanced assessment.
1015
Detection and Attribution of Observed Impacts Chapter 18
18
The RFC Risks Associated with the Distribution of Impacts focuses on
the disparities of impacts between regions, countries, and populations.
The survey of recent studies presented in Section 18.5 indicates that,
while evidence for detected impacts is still more exhaustive from Europe
and North America, considerable confidence in conclusions has been
developed elsewhere since the AR4, particularly in Central and South
America and Australasia (Figure 18-3). It is no longer the case that
higher confidence levels of detected impacts are restricted to any
particular region (Figure 18-6).
The qualitative conclusion that observed impacts on human and managed
systems have now been detected with at least medium confidence on all
inhabited continents is new and noteworthy. However, the number of
systems with detectable impacts is only an indicative metric of coverage,
because many options exist for aggregation and disaggregation of
evidence. Thus this synthesis of detection and attribution studies does not,
at this time, provide evidence of differing severity of impacts between
continents. Throughout its assessments, the IPCC has repeatedly noted
the significant disparity between the vulnerability of countries, regions,
and social groups, related to differences in adaptive capacity (e.g.,
Wilbanks et al., 2007). Nevertheless, additional coverage of detection and
attribution studies is required for broad evaluation of social disparities in
impacts.
The original intent of the category now labeled as Risks Associated with
Aggregate Impacts was to assess those economic impacts, damages,
and risks that are specifically driven by climate change at a globally
aggregated level, using unified monetary metrics. Recognizing the limits
of calibrated monetarization of impacts, the scope of this RFC has been
expanded over time to also include non-monetary metrics (Smith et al.,
2009). Table 18-11 lists various aggregate systems of near-global extent
for which the following two conditions apply: there is some form of
calibrated metric for comparison of impacts across space and subsystems,
and the evidence for detection and attribution of the impacts has
sufficient geographical coverage to count as spatially representative
sample.
Confidence in such large-scale detection is, again, highest in cryospheric
systems (expressed in glacier volume or permafrost active layer thickness),
but climate change has also affected ecosystems (expressed as net
productivity or carbon stocks, ranging from medium to high confidence)
and some human systems (crop yields, losses due to extreme events,
ranging from low to medium confidence) according to the listed
aggregate measures. Thus, several globally aggregated impacts of
recent climate change have now been identified.
The RFC Risks Associated with Large-Scale Singular Events “represents
the likelihood that certain phenomena (sometimes called singularities
or tipping points) would occur, any of which may be accompanied by
very large impacts” (Smith et al., 2009). Several studies have identified
“tipping elements” in the Earth system that exhibit nonlinear behavior
with potentially strong feedbacks on the Earth system (Lenton et al.,
2008; Leadley et al., 2010). For observed impacts, the concern translates
into a question of the possible presence of “early warning signals” for
discontinuities that may be derived from monitoring changes in some
climate or natural systems (Collie et al., 2004; deYoung et al., 2008;
Andersen et al., 2009; Lenton, 2011).
For the Arctic region, new evidence indicates a biophysical regime shift
is taking place, with cascading impacts on physical systems, ecosystems,
and human livelihoods. For Arctic marine biota, the rapid reduction
of summer ice cover causes a tipping element that is now severely
A
ntarctic
Arctic
Very low
Low
Medium
Confidence in attribution
High
Very high
V
ery low Low Medium
C
onfidence in detection
H
igh Very highVery low Low Medium
C
onfidence in detection
H
igh Very highVery low Low Medium
C
onfidence in detection
H
igh Very high
Attribution of major role
A
ttribution of minor role
(a) Physical systems (b) Biological systems
(c) Human and
managed systems
A
frica
Central and South America
A
ustralasia
Small Islands
North America
E
urope
A
sia
Figure 18-6 | Confidence in detection of observed climate change impacts in physical natural systems, biological systems, and human and managed systems across regions, and
confidence in attribution of such trends to observed climate change as a major or minor driver (based on assessments developed in Tables 18-5 to 18-9). (a) Physical systems
include the cryosphere, hydrology, and coastal processes; (b) biological systems refer to changes in marine and terrestrial ecosystems, including wildfires; and (c) human and
managed systems summarize impacts on food production, health, human livelihoods, and economics.
1016
Chapter 18 Detection and Attribution of Observed Impacts
18
affecting pelagic ecosystems as well as ice-dependent mammals such
as seals and polar bears (high confidence; Duarte et al., 2012a; see also
Tables 18-2, 18-8; Section 28.2.2.1). On land, thawing of Arctic
permafrost and shrub encroachment on the tundra have been driven
by warming and prolongation of the growing season (high confidence;
Sections 4.3.3.4, 18.3.2.4, 24.4.2.2; Tables 18-5, 18-7; Figure 4-4).
Permafrost degradation has contributed to widespread hydrological
changes including lake formation or disappearance within a few years’
time (high confidence; Prowse and Brown, 2010; Callaghan et al., 2013;
Table 18-6), while increasing winter rains have had consequences for
the tundra food webs (medium confidence; Post et al., 2009; Callaghan
et al., 2013; Hansen et al., 2013). Indigenous people throughout the
Arctic are impacted by these changes (Eira, 2012; Crate, 2013; see also
Section 18.4.6). In summary, several indicators of the ongoing regime shift
in the entire Arctic land-sea socio-ecological system can be interpreted
as a warning sign for a large-scale singular event (Post et al., 2009;
CAFF, 2010; Callaghan et al., 2010; AMAP, 2011; Duarte et al., 2012b;
Figure 18-3; Tables 18-5, 18-7 to 18-9; Section 28.2).
Reef building corals are in rapid decline in many regions, and climate
change is one of the major drivers (high confidence; Box 18-2). This
irreversible loss of biodiversity has significant feedbacks within the
marine biosphere, and significant consequences for regional marine
ecosystems as well as the human livelihoods that depend on them
(Hoegh-Guldberg and Bruno, 2010; Richardson et al., 2012). The growing
evidence for presently ongoing change and its attribution to warming
gained since the AR4 strengthens the conclusion that increased mass
bleaching of corals constitutes a strong warning signal for the singular
event that would constitute the irreversible loss of an entire biome.
Dieback and degradation in the boreal forests as well as the Amazonian
rainforest have also been identified as potential tipping elements in the
Earth system, due to their large extent and the possible feedbacks with
the carbon cycle (Lenton et al., 2008; Leadley et al., 2010; Marengo et
al., 2011b; see also Section 4.3.3.1). For the boreal forest, increases in
tree mortality have been observed in many regions, including widespread
dieback related to insect infestations and fire in North America (Sections
4.3.3.1, 26.4.2.1). Taken together, these may be seen as indicators of
an ongoing regime shift in the boreal forest, but there is only low
confidence in attribution to climate change (Section 18.3.2.4; Figure
4-4). In the humid tropical forests of the Amazon basin, increased tree
turnover (both mortality and growth) and enhanced drought risks have
been observed during recent decades. However, the main reason for
concern is the interaction between climate change, deforestation, and
the high susceptibility of forests to fire, which together could produce
positive feedbacks leading to degradation of forests in large areas of
the Amazon (Malhi et al., 2009). Currently, there is only low confidence
in attribution of observed ecosystem changes in the Amazon to climate
change. In conclusion, there is insufficient evidence from observed climate
change impacts to support a climate-related warning sign of possible
large-scale singular events in the boreal and Amazonian forest.
18.6.5. Conclusion
Detection and attribution studies evaluate the agreement between
observations of change in a system and process understanding of its
causes, whether these are due to climate change or other forces. This
sets a higher bar for establishing confidence in the assessment of past
changes than is generally applied to the projections of future changes,
because observational evidence has important gaps, while plausibility
of future changes is established on the basis of process knowledge only.
Despite this constraint, the body of evidence on observed impacts of
recent climate change demonstrates increasing coverage of the Earth
and its various subsystems, including human livelihoods. Increasingly,
there is also evidence for complex changes in interconnected systems.
This analysis lends new qualitative support to four out of the five RFCs
established by earlier IPCC assessments. Specifically, evidence is notable
for risks to unique and threatened systems, risks stemming from
extreme weather events, risks associated with globally aggregated
impacts, and—in terms of early warnings—risks associated with large-
scale discontinuities. Only the spatial or social disparities covered under
“Risks Associated with the Distribution of Impacts” are still insufficiently
studied to permit a synthesis of available observations for the
characterization of a global concern. While the Arctic stands out as a
region with robust evidence of impacts across numerous systems,
current detection and attribution literature does not address whether
the severity of those impacts differs from other regions. The Arctic
region, warm-water coral reef systems, and mountain glaciers feature
strongly in the observational evidence discussed for all the RFCs, but
there are also important observations from impacted hydrological
systems and human systems, including agriculture.
The evidence gathered since the AR4 on detection and attribution of
observed impacts from climate change has reached a level at which it
can inform evaluation of many of the aspects of present-day climate
change risk as described by the RFCs. In particular, the geographical
Global aggregated impact
Confi dence
in detection
Reference behavior
Confi dence
in attribution
Role of climate
change
Reference
G
lacier ice volume reduction Very high No change High Major Sections 3.2.2 and 18.3.1.1
P
ermafrost degradation and increase of active layer
thickness
H
igh No change High Major Section 18.3.1.1
I
ncrease in terrestrial net primary production and carbon
stocks
H
igh Changes due to nitrogen deposition,
afforestation, and land management
L
ow Major Section 18.3.2.2
N
egative yield impacts on global wheat and maize yields Medium Changes due to technology, practice,
and coverage
M
edium Minor Section 18.4.1.1; Figure 7-2
I
ncrease in monetary losses due to extreme weather Low Changes due to exposure and wealth Low Minor Sections 10.7.3 and 18.4.3.1
Table 18-11 | Confi dence in detection of impacts on aggregate impact measures against the specifi ed reference behavior and confi dence in attribution of the specifi ed role of
climate change in those observed changes.
1017
Detection and Attribution of Observed Impacts Chapter 18
18
d
istribution of studies is reaching the point where assessment of the
global nature of impacts is possible:
• There is now robust evidence of observed changes in natural
systems in all of the regional groupings used in this report. Climate
change has played a major role in observed changes in various
components of the cryosphere on all continents (high confidence).
Climate change has also driven observed changes in terrestrial
ecosystems on six continents (high confidence, the exception being
low confidence in Central and South America) and on some small
islands (medium confidence), and for marine ecosystems surrounding
six continents and some small islands (high confidence, with evidence
lacking for Africa).
• There is new and stronger evidence of the detection of impacts in
human systems on the inhabited continents. There is at least
medium confidence in detection of impacts on food production in
all the inhabited continents except North America.
• While the current detection and attribution literature does not
reveal observational evidence of geographical differences in the
severity of climate change impacts between continents, it does
indicate that the unique systems of the Arctic region and warm
water coral reefs are undergoing rapid changes in response to
observed warming in ways that are potentially irreversible.
18.7. Gaps, Research Needs, and Emerging Issues
There are three broad areas relating to the detection and attribution of
the impacts of climate change on natural and human systems that
require more research. The first concerns the formulation of the relevant
issues and further development of rigorous scientific methods for
addressing them. At present, the terms detection and attribution are
used in numerous different ways, and, while there is no need for a single
definition, more clarity about usage is important. Methods in this area
a
re closely linked to specific formulations of these terms and there is a
parallel need to develop, refine, and evaluate them in light of this. For
example, statistical methods are commonly used to detect the impact
of variations in climate on human and natural systems while controlling
for the effect of other factors. Such detection can be valuable in helping
to predict the response of systems to projections of future climate
change but a positive correlation does not necessarily imply that the
system has already changed in response to historical climate change. A
second example is the growing use of methods that combine information
from multiple systems— for example, different locations or species—
to draw a conclusion about systems in general. More conceptual work
is needed to develop the basis for such ecological meta-analysis and
the interpretation of its results.
A second area in which more work is needed is data collection and
monitoring. Globally, environmental data are still insufficient for
monitoring the impacts of climate change. In addition, developed
countries are typically over-represented in impact studies because of
their comparable wealth in socioeconomic data. Because the level of
economic development is extremely important in determining the
impacts of climate change, this over-representation probably gives rise
to a distorted picture of the global impacts of climate change.
Finally, this chapter stresses the need to base detection and attribution
studies on a scientific understanding of the system in question and the
way in which climate change (and other factors) might affect it rather
than on relatively simple correlational analysis. This is particularly
important for human systems and at least some natural systems in which
the combined effect of climate change and other factors is complex and
historical adaptation to climate change must be expected. Further
development, refinement, and evaluation of both conceptual and process-
based models of the human-environment system will be essential for
improved conclusions about detection and attribution.
Frequently Asked Questions
FAQ 18.1 | Why are detection and attribution of climate impacts important?
To respond to climate change, it is necessary to predict what its impacts on natural and human systems will be. As
some of these predicted impacts are expected to already have occurred, detection and attribution provides a way
of validating and refining predictions about the future. For example, one of the clearest predicted ecological
impacts of climate is a poleward shift in the ranges of plant and animal species. The detection in historical data of
a climate-related shift in species ranges would lend credence to this prediction, and the assessment of its magnitude
would provide information about the likely magnitude of future shifts.
Freque
ntly Ask
ed Questions
FAQ 18.2 |
Why is it important to assess impacts of all climate change aspects,
and not only impacts of anthropogenic climate change?
Natural and human systems are affected by both natural and anthropogenic climate change, operating locally,
regionally, and/or globally. To understand the sensitivity of natural and human systems to expected future climate
change, and to anticipate the outcome of adaptation policies, it is less important whether the observed changes
have been caused by anthropogenic climate change or by natural climate fluctuations. In the context of this chapter,
all known impacts of climate change are assessed.
1018
Chapter 18 Detection and Attribution of Observed Impacts
18
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Fr
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Q
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ons
FAQ 18.4 |
What ar
e the main challenges in attributing changes in a system
to climate change?
W
h
er
eas
t
h
e
d
et
ec
t
io
n
o
f
c
limat
e
c
h
an
g
e
imp
ac
t
s
ad
d
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es
s
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io
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ly
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et
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er
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r
n
o
t
a
s
ys
t
em
h
as
changed
as
a
resul
t
of
cl
i
m
ate
change,
attri
buti
on
addresses
the
m
agni
tude
of
the
contri
buti
on
of
cl
i
m
ate
change
t
o
s
u
ch
ch
a
n
g
e
s
. E
ve
n
wh
e
n
it
is
p
o
s
s
ib
le
t
o
d
e
t
e
ct
t
h
e
imp
a
ct
o
f
clima
t
e
ch
a
n
g
e
o
n
a
s
ys
t
e
m, mo
r
e
d
e
t
a
ile
d
unde
rsta
nding ma
y
be
ne
e
de
d to a
sse
ss the
ma
gnitude
of this impa
ct in re
la
tion to the
influe
nce
s of othe
r e
x
te
rna
l
factors
and
natural
v
ari
abi
l
i
ty
.
Fr
equent
l
y
As
ked
Ques
t
i
ons
FAQ 18.5 | Is it possible to attribute a single event, like a disease outbreak
or the extinction of a species, to climate change?
It
is
p
o
s
s
ib
le
t
o
d
e
t
e
ct
t
r
e
n
d
s
in
t
h
e
f
r
e
q
u
e
n
cy
o
r
ch
a
r
a
ct
e
r
is
t
ics
o
f
a
cla
s
s
o
f
we
a
t
h
e
r
e
ve
n
t
s
lik
e
h
e
a
t
wa
ve
s
.
S
i
m
i
l
arl
y
,
trends
i
n
a
certai
n
ki
nd
of
i
m
pact
of
that
cl
ass
of
ev
ents
can
al
so
be
detected
and
attri
buted,
al
though
the
i
nfl
uence
of
other
dri
v
ers
of
change,
such
as
pol
i
cy
deci
si
ons
and
i
ncreasi
ng
weal
th,
can
m
ake
thi
s
chal
l
engi
ng.
H
owe
v
er
,
a
ny
si
ngle
i
m
pa
ct e
v
e
nt a
lso re
sul
ts from
the
a
nte
ce
de
nt condi
ti
ons of the
i
m
pa
cte
d sy
ste
m
.
T
hus though
dam
age from
a si
ngl
e ex
trem
e weather ev
ent m
ay
occur agai
nst the background of trends i
n m
any
i
nfl
uenci
ng
factors,
i
ncl
udi
ng
cl
i
m
ate
change,
there
i
s
al
way
s
a
contri
buti
on
from
random
chance.
1019
Detection and Attribution of Observed Impacts Chapter 18
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