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Adaptation Opportunities,

Constraints, and Limits

Coordinating Lead Authors:

Richard J.T. Klein (Sweden), Guy F. Midgley (South Africa), Benjamin L. Preston (USA)

Lead Authors:

Mozaharul Alam (Bangladesh), Frans G.H. Berkhout (Netherlands), Kirstin Dow (USA),

M. Rebecca Shaw (USA)

Contributing Authors:

Wouter Botzen (Netherlands), Halvard Buhaug (Norway), Karl W. Butzer (USA),

E. Carina H. Keskitalo (Sweden), Yu’e Li (China), Elena Mateescu (Romania), Robert Muir-Wood

(UK), Johanna Mustelin (Finland/Australia), Hannah Reid (UK), Lauren Rickards (Australia),

Sarshen Scorgie (South Africa), Timothy F. Smith (Australia), Adelle Thomas (Bahamas),

Paul Watkiss (UK), Johanna Wolf (Germany/Canada)

Review Editors:

Habiba Gitay (Australia), James Thurlow (South Africa)

Volunteer Chapter Scientists:

Seraina Buob (Switzerland), Adelle Thomas (Bahamas)

This chapter should be cited as:

Klein

, R.J.T., G.F. Midgley, B.L. Preston, M. Alam, F.G.H. Berkhout, K. Dow, and M.R. Shaw, 2014: Adaptation

opportunities, constraints, and limits. 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. 899-943.

900

Executive Summary............................................................................................................................................................ 902

16.1. Introduction and Context ....................................................................................................................................... 904

16.1.1. Summary of Relevant AR4 Findings .................................................................................................................................................. 904

16.1.2. Summary of Relevant SREX Findings ................................................................................................................................................ 905

16.2. A Risk-Based Framework for Assessing Adaptation Opportunities, Constraints, and Limits ................................. 905

Box 16-1. Deﬁnitions of Adaptation Opportunities, Constraints, and Limits .............................................................................. 907

16.3. Adaptation Opportunities and Constraints ............................................................................................................ 908

16.3.1. Adaptation Opportunities ................................................................................................................................................................. 908

16.3.1.1. Enabling Conditions for Adaptation .................................................................................................................................. 908

Box 16-2. A Case Study of Opportunities for Adaptation and Disaster Risk Reduction .................................................. 910

16.3.1.2. Ancillary Beneﬁts of Adaptation ........................................................................................................................................ 910

16.3.2. Adaptation Constraints ..................................................................................................................................................................... 911

16.3.2.1. Knowledge, Awareness, and Technology Constraints ......................................................................................................... 911

Box 16-3. Rates of Change as a Cross-Cutting Constraint ............................................................................................... 912

16.3.2.2. Physical Constraints .......................................................................................................................................................... 913

16.3.2.3. Biological Constraints ........................................................................................................................................................ 913

16.3.2.4. Economic Constraints ........................................................................................................................................................ 914

16.3.2.5. Financial Constraints ......................................................................................................................................................... 914

16.3.2.6. Human Resource Constraints ............................................................................................................................................ 915

16.3.2.7. Social and Cultural Constraints .......................................................................................................................................... 915

16.3.2.8. Governance and Institutional Constraints ......................................................................................................................... 916

16.3.2.9. Constraints and Competing Values .................................................................................................................................... 917

16.3.2.10. Consideration of Cross-Scale Dynamics ........................................................................................................................... 918

16.4. Limits to Adaptation ............................................................................................................................................... 919

16.4.1. Hard and Soft Limits ......................................................................................................................................................................... 919

Box 16-4. Historical Perspectives on Limits to Adaptation ......................................................................................................... 920

16.4.2. Limits and Transformational Adaptation ........................................................................................................................................... 921

16.5. Sectoral and Regional Synthesis ............................................................................................................................. 922

16.5.1. Sectoral Synthesis ............................................................................................................................................................................. 922

16.5.2. Regional Synthesis ............................................................................................................................................................................ 922

Table of Contents

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Adaptation Opportunities, Constraints, and Limits Chapter 16

16.6. Effects of Mitigation on Adaptation Opportunities, Constraints, and Limits ......................................................... 924

16.7. Ethical Dimensions of Adaptation Opportunities, Constraints, and Limits ............................................................. 925

16.8. Seizing Opportunities, Overcoming Constraints, and Avoiding Limits ................................................................... 927

References ......................................................................................................................................................................... 927

Frequently Asked Questions

16.1: What is the difference between an adaptation barrier, constraint, obstacle, and limit? .................................................................... 906

16.2: What opportunities are available to facilitate adaptation? ............................................................................................................... 908

16.3: How does greenhouse gas mitigation inﬂuence the risk of exceeding adaptation limits? ................................................................ 924

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Chapter 16 Adaptation Opportunities, Constraints, and Limits

Executive Summary

Risk-based approaches to decision making provide a useful foundation for assessing the potential opportunities, constraints, and

limits associated with adaptation of human and natural systems (medium evidence, high agreement). Risk management frames the

consequences of climate change and potential adaptation responses in the context of actors’ values, objectives, and planning horizons as they

make decisions under uncertainty. Adaptation planning and implementation are therefore contingent on actors’ perceptions of risk. Some risks

may be routine and/or the consequences so minor that they are accepted. Other risks may be judged intolerable because they pose fundamental

threats to actors’ objectives or the sustainability of natural systems. A key objective of adaptation is to avoid such intolerable risks. Yet, the

capacity of societal actors and natural systems to adapt is finite, and thus there are limits to adaptation. {16.2, 16.3.2, 16.4, Box 16-1}

Understanding of how the adaptive capacity of societal actors and natural systems influences the potential for adaptation to

effectively manage climate risk has improved since the Fourth Assessment Report (AR4; very high confidence). Adaptive capacity is

influenced by actors’ abilities to capitalize on available opportunities that ease the planning and implementation of adaptation as well as

constraints that make adaptation processes more difficult for both human and natural systems. Opportunities and constraints are unevenly

distributed among global regions, communities, sectors, ecological systems, and species as well as across different time periods. Recent studies

have provided greater recognition of the role of private businesses in facilitating adaptation. However, much of the current knowledge about

adaptation opportunities and constraints is dominated by insights from public institutions and community-based case studies. {16.2-5, Box 16-1}

Opportunities exist to enable adaptation planning and implementation for actors across all sectors and geographic regions (very

high confidence). Adaptation guidance, information, and tools are increasingly available to practitioners operating in different sectoral,

regional, and organizational contexts. Enhancing the awareness of individuals, organizations, and institutions about climate change vulnerability,

impacts, and adaptation can help build individual and institutional capacity for adaptation planning and implementation. However, addressing

knowledge deficits alone is not sufficient to achieve successful adaptation. The development and provision of tools for risk and vulnerability

assessment as well as decision-support tools and early warning systems can help actors prioritize adaptation needs and identify options that

reduce vulnerability. Opportunities can also arise as actors learn from experience with climate variability and incorporate consideration for

long-term climate change into disaster risk reduction efforts. Formal policies regarding infrastructure design standards or spatial planning can

trigger adaptation action. However, many adaptation opportunities arise as ancillary benefits of actions implemented for reasons other than

climate change. {16.2, 16.3.1, 16.5; Tables 16-1, 16-3; Boxes 16-1, 16-2, CC-EA}

A range of biophysical, institutional, financial, social, and cultural factors constrain the planning and implementation of adaptation

options and potentially reduce their effectiveness (very high confidence). Adaptation of both human and natural systems is influenced

by the rate of climate change as well as rates of economic development, demographic change, ecosystem alteration, and technological innovation.

Adaptation planning and implementation may require significant inputs of knowledge as well as human, social, and financial capital. Real or

perceived deficiencies in access to such resources can and do constrain adaptation efforts in both developing and developed nations. Public

and private institutions influence the distribution of such resources as well as the development of policies, legal instruments, and other measures

that facilitate adaptation. Therefore, institutional weaknesses, lack of coordinated governance, and conflicting objectives among different actors

can constrain adaptation. Cultural characteristics including age, gender, and sense of place influence risk perception, entitlements to resources,

and choices about adaptation. Societal actors and natural systems may experience multiple constraints that interact. {16.2, 16.3.2, 16.5; Tables

16-2, 16-3; Boxes 16-1, 16-3}

Limits to adaptation can emerge as a result of the interactions among climate change and biophysical and socioeconomic con-

straints (medium evidence, high agreement).

An adaptation limit occurs owing to the inability to avoid an intolerable risk to an actor’s

objectives and/or to the sustainability of a natural system. Understanding of limits is informed by historical and recent experience where limits

to adaptation have been observed, as well as by limits that are anticipated to arise as a consequence of future global change. Recent studies

have provided valuable insights regarding global “tipping points,” “key vulnerabilities,” or “planetary boundaries” as well as evidence of climate

thresholds for agricultural crops, species of fish, forest and coral reef communities, and humans. However, for most regions and sectors, there is

a lack of empirical evidence to quantify magnitudes of climate change that would constitute a future adaptation limit. Furthermore, economic

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Adaptation Opportunities, Constraints, and Limits Chapter 16

development, technology, and cultural norms and values can change over time to enhance or reduce the capacity of systems to avoid limits. As

a consequence, some limits may be considered “soft” in that they may be alleviated over time. Nevertheless, some limits may be “hard” in that

there are no reasonable prospects for avoiding intolerable risks. Recent literature suggests that incremental adaptation may not be sufficient to

avoid intolerable risks, and therefore transformational adaptation may be required to sustain some human and natural systems. {16.2-7; Table

16-3; Boxes 16-1, 16-4}

Greenhouse gas (GHG) mitigation can reduce the rate and magnitude of future climate change and therefore the likelihood that

limits to adaptation will be exceeded (medium evidence, high agreement). Adaptation and GHG mitigation are complementary risk

management strategies. However, residual loss and damage will occur from climate change despite adaptation and mitigation action. Knowledge

about limits to adaptation can inform the level and timing of mitigation needed to avoid dangerous anthropogenic interference with the climate

system. For example, the level of effort needed to adapt to a 4°C increase in global mean temperature would be significantly greater than that

needed to adapt to lower magnitudes of temperature increase. Mitigation can reduce the likelihood of 4°C of warming and therefore the likelihood

of exceeding limits to adaptation of natural and human systems. However, the empirical evidence needed to identify limits to adaptation of

specific sectors, regions, ecosystems, or species that can be avoided with different GHG mitigation pathways is lacking. {16.3.2.2, 16.6; Box 16-3}

The selection and implementation of specific adaptation options has ethical implications (very high confidence). Adaptation decision

making involves the reconciliation of legitimate differences about how adaptation resources are distributed and the values that adaptation

seeks to protect. For example, the costs and benefits of different adaptation options, such as insurance schemes or large-scale infrastructure

projects, may be inequitably distributed among different actors and stakeholders. Such inequities may generate ethical questions regarding

who is advantaged or disadvantaged by adaptation actions. In addition, awareness that climate change may exceed the capacity of actors to

adapt may have ethical implications for decisions regarding mitigation and climate targets as well as investments in GHG mitigation policies

and measures. National and international law as well as decision making at regional and local scales among both public and private actors will

influence distributive and procedural justice in adaptation planning and implementation. {16.3.3.8, 16.6-7; Table 16-4; Box 16-4}

Successful adaptation requires not only identifying adaptation options and assessing their costs and benefits, but also exploiting

available mechanisms for expanding the adaptive capacity of human and natural systems (medium evidence, high agreement).

Since the AR4, a growing body of literature provides guidance on how enabling conditions for adaptation can be developed and how constraints

can be reduced. Continued development of this knowledge through research and practice could accelerate more widespread and successful

adaptation outcomes. However, seizing opportunities, overcoming constraints, and avoiding limits can involve complex governance challenges

and may necessitate new institutions and institutional arrangements to effectively address multi-actor, multiscale risks. {16.2-3, 16.5, 16.8;

Table 16-1; Box CC-EA}

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Chapter 16 Adaptation Opportunities, Constraints, and Limits

16.1. Introduction and Context

Since the IPCC’s Fourth Assessment Report (AR4), demand for knowledge

regarding the planning and implementation of adaptation as a strategy

or climate risk management has increased significantly (Preston et al.,

2011a; Park et al., 2012). This chapter assesses recent literature on the

opportunities that create enabling conditions for adaptation as well as

the ancillary benefits that may arise from adaptive responses. It also

assesses the literature on biophysical and socioeconomic constraints

on adaptation and the potential for such constraints to pose limits to

adaptation. Given the available evidence of observed and anticipated

limits to adaptation, the chapter also discusses the ethical implications

of adaptation limits and the literature on system transformational

adaptation as a response to adaptation limits.

To facilitate this assessment, this chapter provides an explicit framework

for conceptualizing opportunities, constraints, and limits (Section 16.2).

In this framework, the core concepts including definitions of adaptation,

vulnerability, and adaptive capacity are consistent with those used

previously in the AR4 (Adger et al., 2007). However, the material in this

chapter should be considered in conjunction with that of complementary

WGII AR5 chapters. These include Chapter 14 (Adaptation Needs and

Options), Chapter 15 (Adaptation Planning and Implementation), and

Chapter 17 (Economics of Adaptation). Material from other WGII AR5

chapters is also relevant to informing adaptation opportunities, constraints,

and limits, particularly Chapter 2 (Foundations for Decision Making) and

Chapter 19 (Emergent Risks and Key Vulnerabilities). This chapter also

synthesizes relevant material from each of the sectoral and regional

chapters (Section 16.5).

To enhance its policy relevance, this chapter takes as its entry point the

perspective of actors as they consider adaptation response strategies

over near, medium, and longer terms (Eisenack and Stecker, 2012; Dow

et al., 2013a,b). Actors may be individuals, communities, organizations,

corporations, non-governmental organizations (NGOs), governmental

agencies, or other entities responding to real or perceived climate-

related stresses or opportunities as they pursue their objectives (Patt

and Schröter, 2008; Blennow and Persson, 2009; Frank et al., 2011).

These actors may seek to navigate near-term constraints to implement

adaptation while simultaneously working to alleviate those constraints

to enable greater flexibility and adaptive capacity in the future.

Therefore, it is necessary to consider diverse time frames for possible

social, institutional, technological, and environmental changes. These

time frames also differ in the types of uncertainties that are relevant,

ranging from those of climate scenarios and models, possible system

thresholds, nonlinear responses or irreversible changes in social or

environmental systems, and the anticipated magnitude of impacts

associated with higher or lower levels of climate change (Meze-Hausken,

2008; Hallegatte, 2009; Briske et al., 2010).

To provide further background and context, this chapter proceeds by

revisiting relevant findings on adaptation opportunities, constraints, and

limits within the AR4 and the more recent IPCC Special Report on

Managing the Risks of Extreme Events and Disasters to Advance Climate

Change Adaptation (SREX) (IPCC, 2012). The chapter then presents a

framework for adaptation, opportunities, and limits with an emphasis

on explicit definitions of these concepts to facilitate assessment. Key

omponents of this framework are assessed in subsequent chapters,

including the synthesis of how these components are treated among

the different sectoral and regional chapters of the WGII AR5 report. The

chapter subsequently assesses relationships between mitigation and

adaptation opportunities, constraints, and limits as well as their ethical

implications. The chapter concludes with discussion of key pathways

forward for research and practice to seize opportunities, overcome

constraints, and avoid limits.

16.1.1. Summary of Relevant AR4 Findings

The AR4 Summary for Policymakers of Working Group II concluded that

there are “formidable environmental, economic, informational, social,

attitudinal and behavioural barriers to the implementation of adaptation”

and that “availability of resources and building adaptive capacity are

particularly important” (IPCC, 2007a, p. 19). These findings were based

primarily on Chapter 17, Assessment of Adaptation Practices, Options,

Constraints and Capacity (Adger et al., 2007). The key conclusion from

Adger et al. (2007, p. 719), as relevant to this chapter, was as follows:

“There are substantial limits and barriers to adaptation (very high

confidence).” The authors go on to discuss biophysical and technological

limits to adaptation as well as barriers arising from technological,

financial, cognitive and behavioral, and social and cultural factors. The

authors also noted both significant knowledge gaps and impediments

to the sharing of relevant information to alleviate those gaps.

These findings were further evidenced by the sectoral, and particularly

regional, chapters of the WGII AR4 report. For example, the chapters

assessing impacts and adaptation in Africa, Asia, and Latin America

collectively emphasized the significant constraints on adaptation in

developing nations. Meanwhile, the chapter on Small Islands by Mimura

et al. (2007) identified several constraints to adaptation including

limited natural resources and relative isolation. Finally, in the chapter

on Polar Regions, Anisimov et al. (2007) noted that indigenous groups

have developed resilience through sharing resources in kinship networks

that link hunters with office workers, and even in the cash sector of

the economy. However, they concluded that such responses may be

constrained by social, cultural, economic, and political factors. For all of

these regions, adaptation constraints are linked to governance systems

and the quality of national institutions as well as limited scientific

capacity and ongoing development challenges (e.g., poverty, literacy,

and civil and political rights).

The AR4 also provided evidence that constraints on adaptation are not

limited to the developing world. For example, Hennessy et al. (2007)

reported that while adaptive capacity in Australia and New Zealand has

strengthened over time, a number of constraints remain including

access to tools and methods for impact assessment as well as appraisal

and evaluation of adaptation options. They also note weak linkages

among the various strata of government regarding adaptation policy

and skepticism among some populations toward climate change science.

For North America, Field et al. (2007) identify a range of social and cultural

barriers, informational and technological barriers, and financial and

market barriers. The chapter on Europe mentions the limits faced by

species and ecosystems due to lack of migration space, low soil fertility,

and human alterations of the landscape (Alcamo et al., 2007).

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Adaptation Opportunities, Constraints, and Limits Chapter 16

everal other AR4 chapters assessed literature relevant to this chapter.

Chapter 18, Inter-Relationships between Adaptation and Mitigation (Klein

et al., 2007), discussed the possible effect of mitigation on adaptation

(an issue also considered by WGIII AR4, in particular by Fisher et al.

(2007) and Sathaye et al. (2007)). Finally, Chapter 19, Assessing Key

Vulnerabilities and the Risk from Climate Change (Schneider et al.,

2007), outlined how the presence of adaptation constraints and limits

is a contributing factor to vulnerability. Chapters that address similar

themes also appear in the AR5, and cross-references are provided in

this chapter to this more recent material.

16.1.2. Summary of Relevant SREX Findings

The IPCC Special Report on Managing the Risks of Extreme Events and

Disasters to Advance Climate Change Adaptation (SREX) assesses a

broad array of literature on climate change, extreme events, adaptation,

and disaster risk reduction. A central framing concept for the SREX was

the assertion that (Lavell et al., 2012, p. 37), “ . .while there is a long-

standing awareness of the role of development policy and practice in

shaping disaster risk, advances in the reduction of the underlying causes

– the social, political, economic, and environmental drivers of disaster

risk – remain insufficient to reduce hazard, exposure, and vulnerability

in many regions (UNISDR, 2009, 2011) (high confidence).”

This summary of relevant SREX material focuses on how the key findings

of the SREX provide insights relevant to the treatment of opportunities,

constraints, and limits in this chapter.

With respect to opportunities, the linkages between development and

disaster risk reduction provide a number of avenues for enhancing

societal resilience to natural disasters and climate change. For example,

the SREX highlights the benefits of considering disaster risk in national

development planning if strategies to adapt to climate change are

adopted (Lal et al., 2012). The observed dependence of disasters on

underlying patterns of development is indicative of the opportunities

for increasing societal resilience through sustainable development. In

addition, incorporating adaptation into multi-hazard risk management

may be an effective strategy for the efficient integrated management

of natural hazards and future climate risk (O’Brien et al., 2012).

The SREX report also discussed the constraints associated with enhancing

disaster risk reduction and climate adaptation. In particular, ongoing

development deficits as well as inequality in coping and adaptive

capacities pose fundamental constraints (Cardona et al., 2012). The

SREX noted that national systems and institutions are critical for

generating the capacity needed to manage the risks associated with

climate variability and change (Lal et al., 2012). Yet capacity at one level

of governance does not necessarily convey capacity to other levels

(Burton et al., 2012). Even in the presence of robust institutions, rates

of socioeconomic and climate change can interact to constrain adaptation.

For example, O’Brien et al. (2012) note that rapid socioeconomic

development in vulnerable urban areas can increase societal exposure

to natural hazards while simultaneously constraining the capacity of

actors to implement policies and measures to reduce vulnerability.

Overcoming these constraints to achieve development objectives is

constrained by a paucity of disaster data at the local level as well as

ersistent uncertainties regarding the manifestation of extreme events

in future decades (Cutter et al., 2012; Seneviratne et al., 2012).

The SREX report cautioned that natural hazards, climate change, and

societal vulnerability can pose fundamental limits to sustainable

development. Such limits can arise from the exceedance of natural

and/or societal thresholds or tipping points (Lal et al., 2012; O’Brien et

al., 2012; Seneviratne et al., 2012). Accordingly, the SREX concludes that

adaptation options should include not only incremental adjustments to

climate variability and climate change, but also transformational

changes that alter the fundamental attributes of systems. Though

challenging to implement, such transformation may be aided by actors

questioning prevailing assumptions, paradigms, and management

objectives toward the development of new ways of managing risk and

identifying opportunities (O’Brien et al., 2012).

16.2. A Risk-Based Framework for

Assessing Adaptation Opportunities,

Constraints, and Limits

Risk is an intrinsic element of any understanding of “dangerous

anthropogenic interference with the climate system” (UNFCCC, 1992)

and associated assumptions about the capacity of human and natural

systems to adapt to climatic change. The United Nations Framework

Convention on Climate Change (UNFCCC) refers specifically to adaptation

of ecosystems, threats to food production, and sustainable economic

development. While there is evidence of opportunities in natural and

human systems to adapt to climate changes, there is also evidence that

the potential to adapt is constrained, or more difficult, in some situations,

and faces limits in others (very high confidence; e.g., Adger et al., 2009;

Dow et al., 2013a,b; see also Sections 16.3-5).

This chapter applies a risk-based framework and a set of linked definitions

to the assessment of adaptation opportunities, constraints, and limits.

This approach is consistent with other risk management approaches to

guiding adaptation responses to climate change (IPCC, 2012; see also

Sections 1.3.4, 2.1.2, 14.4, 15.3). The adaptation literature ascribes a

number of different meanings to the terms opportunities, constraints,

and limits, which may have added confusion to an important scientific

and policy debate. The AR4, for example, provided a specific definition

of adaptation limits, but used the terms barriers and constraints

interchangeably to describe general impediments to adaptation (Adger et

al., 2007). Similar ambiguities are apparent within the rapidly expanding

literature focused on adaptation constraints (Biesbroek et al., 2013a).

The framework and definitions employed here draw on a number of

literatures (Dow et al., 2013a,b), in particular vulnerability assessment

(Füssel, 2006; Füssel and Klein, 2006) and risk assessment (Jones, 2001;

Klinke and Renn, 2002; Renn, 2008; National Research Council, 2010)

as well as climate adaptation (Hulme et al., 2007; Adger et al., 2009;

Hall et al., 2012). Moving from such general definitions to applications

requires specifying who or what is adapting, what they are adapting

to, and the process of adaptation (Smit et al., 1999). Hence, this chapter

explores adaptation opportunities, constraints, and limits from the context

of social actors, which includes individuals, businesses, government

agencies, or informal social groups.

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Chapter 16 Adaptation Opportunities, Constraints, and Limits

An explicit focus on risk is particularly useful to understanding climate

adaptation (Jones and Preston, 2011; Dow et al., 2012b). Adaptation is

intended to reduce the risk to assets or systems of value (Adger et al.,

2012b). The concept of risk integrates the dimensions of probability and

uncertainty with the material and normative dimensions that shape

societal responses to threats (Renn, 2008). Figure 16-1 relates judgments

about risk and the ability to maintain risks at a tolerable level to the

concept of adaptation and adaptation opportunities, constraints, and

limits (Box 16-1). Drawing on the work of Klinke and Renn (2002),

actors evaluate risks based on one of three categories: acceptable,

tolerable, and intolerable. Acceptable risks are those deemed so low that

additional efforts at risk reduction, in this case climate adaptation efforts,

are not justified. Tolerable risks relate to situations where adaptive risk

management efforts are required and effective for risks to be kept

within reasonable levels. The scope of risks that fall within the tolerable

area is influenced by adaptation opportunities and constraints.

Therefore, the categorization of risks varies across spatial, jurisdictional,

and temporal. As discussed later in this chapter, opportunities and

constraints may be physical, technological, economic, institutional, legal,

cultural, or environmental in nature (Sections 16.3, 16.5-7). Constraints

may limit the range of available adaptation options creating the potential

for residual damages for actors, species, or ecosystems associated with

specific regions or sectors. Under some circumstances, the risk of residual

damage may be viewed as an acceptable or tolerable trade-off (Stern

et al., 2006; de Bruin et al., 2009a).

Intolerable risks may be related to threats to core social objectives

associated with health, welfare, security, or sustainability (Klinke and

Renn, 2002; Renn, 2008; Dow et al., 2013a,b). Risks become intolerable

when practicable or affordable adaptation options to avoid escalating

risks to such valued objectives or biophysical needs become unavailable.

Therefore, a limit is a point when an intolerable risk must be accepted;

the objective itself must be relinquished; or some adaptive transformation

must take place to avoid intolerable risk. Such a discontinuity may take

several forms such as individual’s decision to relocate, an insurance

company’s decision to withdraw coverage, or a species’ extinction. The

alternative to such discontinuities is an escalating and unmediated risk

of losses (Moser and Ekstrom, 2010; see also Section 16.4.2). While

individuals have their own perspectives about what are acceptable,

tolerable, or intolerable risks, collective judgments about risk are also

codified through mechanisms such as engineering design standards, air

and water quality standards, and legislation that establishes goals for

regulatory action. There are also international agreements that establish

norms and rights relevant to climate change risks (Knox, 2009; OHCHR,

2009; Crowley, 2011), such as the Universal Declaration of Human

Rights, the International Covenant on Civil and Political Rights, and the

International Covenant on Economic, Social and Cultural Rights. Further,

these high level responses often shape the constraints and opportunities

to adaptation and responses to risk at lower levels through the distribution

Frequently Asked Questions

FAQ 16.1 | What is the difference between an adaptation barrier,

constraint, obstacle, and limit?

An adaptation constraint represents a factor or process that makes adaptation planning and implementation more

difﬁcult. This could include reductions in the range of adaptation options that can be implemented, increases in

the costs of implementation, or reduced efﬁcacy of selected options with respect to achieving adaptation objectives.

In this context, a constraint is synonymous with the terms adaptation barrier or obstacle that also appear in the

adaptation literature. However, the existence of a constraint alone does not mean that adaptation is not possible

or that one’s objectives cannot be achieved. In contrast, an adaptation limit is more restrictive in that it means

there are no adaptation options that can be implemented over a given time horizon to achieve one or more

management objectives, maintain values, or sustain natural systems. This implies that certain objectives, practices,

or livelihoods as well as natural systems may not be sustainable in a changing climate, resulting in deliberate or

involuntary system transformations.

Intensity of adverse impact

Catastrophic Negligible

Very frequentVery rare

Acceptable

risks

Tolerable risks

Intolerable

risks

Frequency of adverse impact

Figure 16-1 | Conceptual model of the determinants of acceptable, tolerable, and

intolerable risks and their implications for limits to adaptation (Dow et al., 2013b,

based on Klinke and Renn, 2002; see also Renn and Klinke, 2013). In this conceptual

diagram, adaptation efforts are seen as keeping risks to objectives within the tolerable

risk space. Opportunities and constraints inﬂuence the capacity of actors to maintain

risks within a tolerable range. The dotted lines indicate that individual or collective

views on risk tolerance with respect to the frequency and intensity of climate-related

risks are not ﬁxed, but may vary and change over time. In addition, the shape or angle

of the lines and the relative area in each section of the diagram are illustrative and

may themselves change as capacities and attitudes change. The shaded areas

represent the potential differences in perspective among actors.

907

Adaptation Opportunities, Constraints, and Limits Chapter 16

of resources, institutional design, and support of capacity development

(Sections 16.2-3, 16.4.1). If these risks and discontinuities have global-

scale consequences, they can be linked to “key vulnerabilities” to climate

change (Section 19.6). Consistent with our framing of adaptation limits,

such key vulnerabilities would need to be assessed in terms of the limits

they imply for specific social actors, species, and ecosystems.

It is essential to evaluate opportunities, constraints, and limits with respect

to both the rate and magnitude of climate change and the relevant time

horizon for an actor, a species, or an ecosystem. Opportunities, constraints,

and limits to adaptation develop along a dynamic continuum (i.e., the

dotted lines in Figure 16-1 can shift), together conditioning the capacity

of natural and human systems to adapt to climate change. New

opportunities for adaptation may emerge through time; constraints may

be loosened; and some, although not all, limits that arise in the present

may eventually be shifted or removed altogether. For a given social

actor, the time horizon for adaptation decisions usefully bounds an

analysis of opportunities, constraints, and limits. For natural systems,

Box 16-1 | Deﬁnitions of Adaptation Opportunities, Constraints, and Limits

Adaptation Opportunities: Factors that make it easier to plan and implement adaptation actions, that expand adaptation options,

or that provide ancillary co-beneﬁts. These factors enhance the ability of an actor(s) to secure their existing objectives, or for a natu-

ral system to retain productivity or functioning. For instance, increased public awareness and support for adaptation, availability of

additional resources from actors at other levels of governance to overcome constraints and soft limits, and interest in acquiring co-

beneﬁts arising from adaptation strategies can all facilitate adaptation planning and implementation. Private sector efforts in research

and development that can improve affordability, ﬂexibility, or ease of implementation could also create opportunities (Section 14.2.4).

Such adaptation opportunities, sometimes also referred to as adaptation enablers, are distinct from opportunities arising from climate

change (e.g., longer growing seasons), which are commonly referred to as potential beneﬁts of climate change or adaptation options.

Adaptation Constraints: Factors that make it harder to plan and implement adaptation actions. Adaptation constraints restrict the

variety and effectiveness of options for actors to secure their existing objectives, or for a natural system to change in ways that

maintain productivity or functioning. These constraints commonly include lack of resources (e.g., funding, technology, or knowledge)

(Section 16.3.2), institutional characteristics that impede action (Section 16.3.2.8), or lack of connectivity and environmental quality

for ecosystems (Section 4.4). The terms “barriers” and “obstacles” are frequently used as synonyms. Constraints—alone or in

combination—can drive an actor or natural system to an adaptation limit.

Adaptation Limit: The point at which an actor’s objectives or system’s needs cannot be secured from intolerable risks through

adaptive actions (Adger et al., 2009; Moser and Ekstrom, 2010; Dow et al., 2013a,b; Islam et al., 2014).

Hard Adaptation Limit: No adaptive actions are possible to avoid intolerable risks.

Soft Adaptation Limit: Options are currently not available to avoid intolerable risks through adaptive action.

A limit to adaptation means that, for a particular actor, system, and planning horizon of interest, no adaptation options exist, or an

unacceptable measure of adaptive effort is required, to maintain societal objectives or the sustainability of a natural system. Objectives

include, for example, maintaining safety standards such as those codiﬁed in laws, regulations, or engineering design standards (e.g.,

1-in-500 year levees); security of air or water quality; as well as equity, cultural cohesion, and preservation of livelihoods. Requirements

for sustaining natural systems might include temperature ranges or moisture availability. In the case of hard limits, no adaptation

options are foreseeable, even when looking beyond the current planning horizon. For soft limits, however, adaptation options could

become available in the future owing to changing attitudes or values or as a result of innovation or other resources becoming available

to an actor. For example, 31 Native Alaskan villages are facing “imminent threats” due to coastal erosion and at least 12 of the 31

have begun to explore relocation or have decided to partially or totally relocate (US GAO, 2009). In the case of these communities

with minimum local revenue, the ability to relocate depends on the political and ﬁnancial support of the U.S. federal government

(Huntingon et al., 2012). Therefore, limits are strongly inﬂuenced by relationships among public and private actors and institutions

across different spatial, temporal, and jurisdictional scales (Cash et al., 2006; see also Section 16.4.1).

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Chapter 16 Adaptation Opportunities, Constraints, and Limits

he rate of species responses relative to changes in environmental

conditions is a limit to the capacity to adapt (Sections 4.3.2.5, 4.4,

16.3.2.3, 16.4.1). The observed rate of evolutionary and other species

responses ranges from rapid to inadequate to allow persistence

(Hoffmann and Sgro, 2011).

Because adaptation limits relate to adaptation resources and attitudes

to risk that may change over time, some limits may be viewed as “soft”

or time sensitive (Section 16.4.1). While a given adaptation option may

not be available today or require impracticable levels of effort, it may

become available through innovation or changes in attitudes in time.

Soft limits may be shifted by investments in research and development,

changes in regulatory rules or funding arrangements, or by changing

social or political attitudes (Park et al., 2012; Adger et al., 2013). Other

limits are “hard” or time insensitive in that there is no known process

to change them (Section 16.4.1). Examples of hard limits include water

supply in fossil aquifers, limits to retreat on islands, and loss of genetic

diversity.

16.3. Adaptation Opportunities and Constraints

Different actors, sectors, and geographic regions have differential capacities

to adapt to climate variability and change (very high confidence; Adger

et al., 2007; IPCC, 2012), although those capacities can be difficult to

measure (Tol et al., 2008; Hinkel, 2011). Since the AR4 (Adger et al., 2007),

the literature on the factors that contribute to adaptive capacity has

deepened (Adger et al., 2009; Moser and Ekstrom, 2010). This literature

has evolved along two different pathways. One focuses on the range

of opportunities that exist to facilitate adaptation planning and

implementation. The other, which is also more extensive, focuses on

describing the constraints that inhibit adaptation. Although they are

sometimes treated in the literature as distinct, opportunities and

constraints are complementary in that adaptive capacity is influenced

jointly by the extent to which actors take advantage of available

opportunities to pursue adaptation responses and the extent to which

those actors or natural, unmanaged systems experience constraints. In

ddition, factors that are identified as constraints may also reveal valuable

opportunities for adaptation interventions to build adaptive capacity.

While some level of generalization regarding opportunities and

constraints that are common to different regions, sectors, communities,

and actors is possible, the manner in which they manifest is context

dependent (very high confidence; Adger et al., 2007; Orlove, 2009;

Kasperson and Berberian, 2011; Weichselgartner and Breviere, 2011;

IPCC, 2012). For example, actors that frame adaptation as a process of

capacity building or sustainable development may pursue different

adaptation options with different opportunities and constraints compared

with those that frame adaptation as largely addressing climate change

impacts (McGray et al., 2007; Fünfgeld and McEvoy, 2011). Adaptation

researchers apply their own frameworks and heuristics that influence

understanding of adaptation processes (Biesbroek et al., 2013b; Preston

et al., 2013b). Therefore, one must be cautious in applying generic

assumptions regarding adaptation opportunities and constraints in

assessments of vulnerability and adaptive capacity or in the identification

of appropriate adaptation responses (Adger and Barnett, 2009; Barnett

and Campbell, 2009; Mortreux and Barnett, 2009). The recent adaptation

literature suggests significant work remains in understanding such

context-specific determinants of vulnerability and adaptive capacity and

in effectively using the knowledge gained from available case studies

to facilitate adaptation more broadly (Tol and Yohe, 2007; Klein, 2009;

Smith et al., 2010; Hinkel, 2011; Preston et al., 2011b; Biesbroek et al.,

2013a). Therefore, the discussion of opportunities and constraints here

should be considered in the context of the sectoral and regional

synthesis (Section 16.5) as well as the sector- and region-specific

material on constraints and opportunities in other WGII AR5 chapters.

16.3.1. Adaptation Opportunities

16.3.1.1. Enabling Conditions for Adaptation

Adaptation opportunities represent enabling factors that enhance the

potential for actors to plan and implement actions to achieve their

Frequently Asked Questions

FAQ 16.2 | What opportunities are available to facilitate adaptation?

Although an extensive literature now exists regarding factors that can constrain adaptation, there is very high

conﬁdence that a broad range of opportunities exist for actors in different regions and sectors that can ease

adaptation planning and implementation. Generally, sustainable economic development is an overarching process

that can facilitate adaptation, and therefore represents a key opportunity to reduce adaptation constraints and

limits. More speciﬁcally, those actions or processes that enhance the awareness of adaptation actors and relevant

stakeholders and/or enhance their entitlements to resources can expand the range of adaptation options that can

be implemented and help overcome constraints. The development and application of tools to support assessment,

planning, and implementation can aid actors in weighing different options and their costs and beneﬁts. Policies,

whether formal policies of government institutions, initiatives of informal actors, or corporate policies and standards,

can direct resources to adaptation and/or reduce vulnerability to current and future climate. Finally, the ability for

humans to learn from experience and to develop new practices and technologies through innovation can signiﬁcantly

expand adaptive capacity in the future.

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Adaptation Opportunities, Constraints, and Limits Chapter 16

adaptation objective(s) or facilitate adaptive responses by natural systems

to climate risk (Box 16-1). Therefore, an opportunity is distinct from an

adaptation option, which is a specific means of achieving an adaptation

objective (such as an early warning system as a means of reducing

vulnerability to tropical cyclones) or a strategy for the conservation of

an ecological system (Section 14.3; Table 14-1). Adaptation opportunities

described here also do not consider the potential beneficial consequences

of climate change (Box 16-1), an issue addressed to varying degrees

among the various sectoral and regional chapters.

Opportunities for adaptation range from increasing awareness of

climate change, its consequences, and the potential costs and benefits

of adaptation options to the implementation of specific policies that

create conditions that are conducive to adaptation implementation. For

example, rice is a key food crop, particularly in Asia, in which 90% of rice

is produced and subsequently consumed (Timmer, 2010). Multiple studies

have identified rice as being particularly vulnerable to the effects of climate

change, including both temperature and water availability impacts

(Papademetriou et al., 2000). Therefore, planning and implementation

of adaptive responses will be an important component of managing

the risk of climate change to rice production (Howden et al., 2007;

Lobell et al., 2008; Tilman et al., 2011; Anwar et al., 2013). A range of

opportunities are available to support adaptation (Tables 16-1, 16-3)

(very high confidence). Hypothetically, these could include the use of

analysis tools to better understand vulnerabilities and thresholds in rice

and develop scenarios of future consequences. That information could then

be communicated to farmers, national governments, and international

agencies to increase awareness of potential risks. Policies can be used

to incentivize adaptation including investments in biotechnology

research to breed more resistant strains as well as field studies to identify

potential new regions that might be appropriate for rice cultivation in

the future.

Such opportunities exist for other agricultural commodities as well as

other sectors and regions at risk from climate change (Box 16-2). For

example, there is growing recognition of the potential for using disaster

response and recovery processes as a means of increasing resilience to

future extreme events (Lavell et al., 2012). Meanwhile, case studies of

Australian local governments as well as Inuit communities in the Arctic

have identified a range of opportunities for building adaptive capacity

and overcoming constraints (Smith et al., 2008; Ford, 2009; Ford et al.,

2010). These include risk assessment, partnerships, establishment of

monitoring and evaluation frameworks, developing finance mechanisms,

and formal adaptation policy development.

Sustainable economic development is a critical foundation for the

creation of adaptation opportunities (Sections 20.2, 20.6), because it

has the potential to build the capacity of individuals and organizations

to adapt (very high confidence). Sustainable development is associated

with increasing opportunities for research, training, and education as

Opportunity Examples References

Awareness

raising

ositive stakeholder engagement O’Neill and Chicholson-Cole (2009); Kahan (2010)

Communication of risk and uncertainty Berry et al. (2011); Pidgeon and FIschhoff (2011); Pidgeon (2012); Lieske et al. (2013)

articipatory research Pearce et al. (2009); McNamara and McNamara (2011); Sheppard et al. (2011); Duru et al. (2012); Faysse et al. (2012)

Capacity

building

Research, data, education, and training PCAST (2011); WMO (2011); Bangay and Blum (2012); Lemos et al. (2013)

xtensions services for agriculture Deressa et al. (2009); Fosu-Mensah et al. (2012)

Resource provision Ayers (2009); Ayers and Huq (2009); Grasso (2010); Klein (2010); Rübbelke (2011)

evelopment of human capital Bowen et al. (2012); Lemos et al. (2013)

evelopment of social capital Deressa et al. (2009); Adger et al. (2010); Engle and Lemos (2010); Huang et al. (2011)

Tools

Risk analysis van Aalst et al. (2008); Pidgeon and Butler (2009); Chin et al. (2010); Zhou et al. (2012); Wade et al. (2013)

ulnerability assessment Allison et al. (2009); Moreno and Becken (2009); Nelson et al. (2010b); Romieu et al. (2010); Koh (2011); Preston et al. (2011b)

Multi-criteria analysis de Bruin et al. (2009b); Garﬁ et al. (2011); Yang et al. (2012); Kyung-Soo et al. (2013)

ost / beneﬁ t analysis Tol et al. (2008); Hallegatte (2009); Weitzman (2009); Mechler and Islam (2013)

Decision support systems Norman et al. (2010); Wenkel et al. (2013)

Early warning systems Lowe et al. (2011); Lenton (2013); Marvin et al. (2013)

Policy

ntegrated resource and infrastructure

planning

osenberg et al. (2010); Becker et al. (2012); Heeres et al. (2012)

patial planning Brown (2011); Wheeler (2012); Pinto et al. (2013)

Design / planning standards Hamin and Gurran (2009); Mailhot and Duchesn (2009); Kwok and Rajkovich (2010); Ren et al. (2011); Nassopoulos et al. (2012)

Learning

xperience with climate vulnerability and

disaster risk

iksel (2006); Crespo Cuaresma et al. (2008); Cutter et al. (2012)

Learning-by-doing Berkhout et al. (2006); Bulkeley and Castán Broto (2012); Roberts et al. (2012)

Monitoring and evaluation GIZ (2011a,b); Preston et al. (2011a); Adaptation Sub-Committee (2012)

Innovation

Technological change Hanjra and Qureshi (2010); Chhetri et al. (2012); Lybbert and Sumner (2012); Rodima-Taylor et al. (2012); Vermeulen et al. (2012)

Infrastructure efﬁ ciencies Beard et al. (2009); Newton (2013)

Digital / mobile telecommunications Ospina and Heeks (2010a,b); Meera et al. (2012)

Table 16-1 | Identiﬁ cation of key adaptation opportunities. Each type of opportunity is represented by multiple illustrative examples as well as supporting references.

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Chapter 16 Adaptation Opportunities, Constraints, and Limits

well as for enhancing access to expertise and tools for assessment

activities and decision support. It also increases access to technologies

that can enhance efficiencies. For example, water use in the USA has

remained relatively constant since the mid-1980s, despite population

growth, increases in agricultural yields, and expansion of electricity

generation (Kenny et al., 2009). Improvements in technology and

management practice stimulated by innovation, education, and learning

have increased water use efficiency. This phenomenon may increase the

resilience of U.S. water resources to climate change. Yet, these advances

are a function of broader national and regional economic development

trends. Therefore, future development pathways may have a significant

influence on the opportunities for adaptation and therefore the adaptive

capacity of adaptation actors (Sections 16.3.2.10, 20.6; Box 16-3).

16.3.1.2. Ancillary Benefits of Adaptation

Some adaptation options may offer ancillary benefits (or co-benefits)

independent of their direct benefits with respect to reducing vulnerability

to climate change (very high confidence; Section 17.2.3). The potential

for ancillary benefits has two important implications for adaptation

planning and implementation. First, their consideration may result in a

more favorable assessment of the cost-effectiveness of a specific

adaptation option (Hallegatte, 2009). Second, consideration of the

ancillary benefits of adaptation may help in efficiently integrating

adaptation into existing management and decision-making processes

(Ahmed and Fajber, 2009; Dovers, 2010).

Such ancillary benefits may arise from adaptation responses in three

ways:

• Stimulating adaptation to current climate variability: Although it is

generally assumed that physical, ecological, and social systems are

well adapted to current climatic conditions, this is frequently not

the case (Dugmore et al., 2009; Heyd and Brooks, 2009). Increased

awareness of the potential impacts of future climate change may,

in some instances, lead to the implementation of adaptation options

to reduce vulnerability or capitalize on opportunities (medium

evidence, high agreement; Section 16.3.2.1).These options may have

near-term ancillary benefits with respect to reducing vulnerability

to current climate variability and extreme weather events (Füssel,

2008; Hallegatte, 2009; Ford et al., 2010). On the other hand, future

reductions in vulnerability to climate change can be perceived as

Box 16-2 | A Case Study of Opportunities for Adaptation and Disaster Risk Reduction

Bangladesh has been identiﬁed as a region of South Asia that is particularly vulnerable to tropical cyclones (Ali, 1999; Mallick and

Rahman, 2013), and this vulnerability is projected to increase due to climate change (Karim and Mimura, 2008; Dasgupta et al.,

2010). The nation’s response to this vulnerability illustrates the manner in which multiple opportunities can converge to facilitate

adaptation and disaster risk reduction. The Cyclone Preparedness Program (CPP) was launched in the 1960s to establish a warning

system in coastal regions (Habib et al., 2012). The CPP has been continually improved in subsequent years with assistance from the

International Federation of Red Cross and Red Crescent Societies and the International Foundation (Mallick and Rahman, 2013). A

coastal reforestation program was also established in the 1960s to enhance natural buffers to storm surge (Mallick and Rahman,

2013; Box CC-EA). The Bangladesh Government initiated construction of cyclone shelters in the late 1980s, yet a cyclone in 1991

revealed that too few shelters were available (Bern et al., 1991; Chowdhury et al., 1993). This prompted collaboration between the

government of Bangladesh, the United Nations Development Programme, and the World Bank to launch the Multipurpose Cyclone

Shelter Program. That program characterized shelter needs along the coast and provided resources for their construction. In addition,

shelter construction, which was concentrated around primary and secondary schools, coincided with national legislation requiring

compulsory attendance in primary school, which required the construction of new schools. This created the opportunity for multi-

purpose construction of buildings, reﬂecting the potential ancillary beneﬁts that can arise from integrated planning (Section

16.3.1.2).

More recently, Bangladesh has begun to focus on increasing the resilience of the built environment. This effort has focused on the

development of disaster-resilient habitat (Mallick and Rahman, 2007), where communities participate in the design and construction

of resilient housing with support from international donors (Mallick et al., 2008; Mallick and Rahman, 2013). This may be a more

cost-effective strategy for both reducing mortality and property damage (Mallick et al., 2008). The observed progress in reducing

vulnerability to tropical cyclones is a function of various opportunities (awareness, assessment, policies, innovation, and capacity

building) that have emerged over the past several decades that created conditions that enabled the implementation of speciﬁc policies,

projects, and programs. Nevertheless, the additional risk posed by future climate change may necessitate further future investments

(Dasgupta et al., 2010).

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Adaptation Opportunities, Constraints, and Limits Chapter 16

ncillary benefits of near-term responses to current climate variability

and natural disasters (Ziervogel et al., 2010a,b). Hence, there may

be some ambiguity with respect to what actors perceive as the

primary versus ancillary benefit of a particular policy or measure.

• Generation of climate adaptation goods and services: Adaptation

planning and implementation often may require additional knowledge

and investment of resources. Adaptation therefore represents a

potential economic opportunity for producers of goods and

services used to satisfy adaptation needs (limited evidence, medium

agreement; EBI, 2013). Such services range from vulnerability

assessment and risk analysis to the implementation of technology

and engineering solutions. The Stern Review indicated that the

market opportunities for new infrastructure and buildings resilient

to climate change in Organisation for Economic Co-operation and

Development (OECD) countries could be quite significant (Stern et

al., 2006). For example, the market for snow machines will be

influenced by growing concerns about snow cover in more marginal

ski resorts (Scott et al., 2006). Higher elevation regions may see

new opportunities as a result of snow resort shifts (Bark et al.,

2010). Likewise, increased risks associated with track buckling

caused by higher summer temperatures may trigger innovation and

investment in new railway track and drainage systems (Bark et al.,

2010). Rising damage caused by climate change could provide new

markets for innovative insurance products and other risk-based

financial services (limited evidence, medium agreement; Botzen et

al., 2009, 2010). However, these ancillary benefits must be weighed

against the adverse impacts that create the market for such services.

• Advancing sustainable development: As part of a larger portfolio of

policies and measures, adaptation can assist in addressing existing

development deficits while also meeting long-term sustainable

development objectives (very high confidence; Sections 20.2, 20.6).

For example, policy options related to management of water and

natural resources under a changing climate; the development of

water, transportation, and communication infrastructure; and the

promotion of credit and insurance services can promote economic

development, increase adaptive capacity, and reduce the impacts

of climate change on the poor (Hertel and Rosch, 2010). Therefore,

effective adaptation and climate risk management may be important

enablers of sustainable economic development.

16.3.2. Adaptation Constraints

As discussed in the AR4 (Adger et al., 2007), a number of factors constrain

planning and implementation of adaptation options (very high confidence).

More recent studies have documented an expanded range of constraints

in a diverse array of contexts, but Biesbroek et al. (2013a) note that there

is no consensus definition of constraints or a consistent framework for

their assessment. Although constraints are often discussed in the

literature as discrete determinants of adaptive capacity, they rarely act

in isolation (Dryden-Cripton et al., 2007; Smith et al., 2008; Moser and

Ekstrom, 2010; Shen et al., 2011). Rather actors are challenged to

navigate multiple, interacting constraints in order to achieve a given

adaptation objective (very high confidence; Adger et al., 2007, 2009;

Dryden-Cripton et al., 2007; Shen et al., 2008, 2011; Smith et al., 2008;

Jantarasami et al., 2010; Moser and Ekstrom, 2010; see also Section

16.3.2.10). Multiple constraints can significantly reduce the range of

daptation options and opportunities available to actors and therefore

may pose fundamental limits to adaptation (very high confidence; Section

16.4) and/or drive actors toward responses that may be maladaptive

(limited evidence, medium agreement; Barnett and O’Neill, 2010; Eriksen

et al., 2011).

6.3.2.1. Knowledge, Awareness, and Technology Constraints

The AR4 concluded that there are significant knowledge gaps and

impediments to flows of information that can constrain adaptation, but

knowledge in itself is not sufficient to drive adaptive responses (Adger

et al., 2007). These conclusions are echoed by more recent literature.

Adaptation practitioners and stakeholders in both developed (Tribbia

and Moser, 2008; Gardner et al., 2010; Jantarasami et al., 2010; Ford et

al., 2011; Milfont, 2012) and developing nations (Bryan et al., 2009;

Deressa et al., 2009; Begum and Pereira, 2013; Pasquini et al., 2013)

continue to identify knowledge deficits as an adaptation constraint (very

high confidence). Often this demand for more information is linked to

concerns regarding decision making under uncertainty about the future

(medium evidence, medium agreement; Tribbia and Moser, 2008; Moser,

2010a; Whitmarsh, 2011; Stoutenborough and Vedlitz, 2013). A broad

range of guidance on adaptation planning and implementation continues

to emerge as a means of empowering actors to pursue adaptation efforts

(Clar et al., 2013; EC, 2013; FAO, 2013; USCTI, 2013; Webb and Beh,

2013), and the World Meteorological Organization has emphasized the

importance of climate services for vulnerability and disaster risk reduction

(WMO, 2011).

A number of recent studies have investigated the extent to which

education and knowledge about climate change influences perceptions

of risk (Hamilton, 2011; McCright and Dunlap, 2011; Milfont, 2012). For

example, studies suggest overconfidence in the ability of actors to manage

risk (Wolf et al., 2010; Kuruppu and Liverman, 2011) or differences in

the perception of climate risk between actors and governing institutions

(Patt and Schröter, 2008a) can constrain adaptation (medium evidence,

medium agreement). Therefore, capacity building through education,

training, and information access represents a valuable opportunity for

adaptation (Section 16.3.1.1).

Nevertheless, numerous recent studies caution that addressing

knowledge deficits may not necessarily lead to adaptive responses

(very high confidence; Kellstedt et al., 2008; Tribbia and Moser, 2008;

Adger et al., 2009; Malka and Krosnick, 2009; Moser, 2010b; Preston et

al., 2011b; Kahan et al., 2012; Lemos et al., 2012). Research from the

USA indicates that those most informed about science and climate

change are not necessarily the most concerned about its potential

consequences (Kellstedt et al., 2008; Kahan et al., 2012), although these

findings run counter to research from New Zealand, where increased

knowledge translated into increased public concern and efficacy

(Milfont, 2012). Recent research also indicates that multiple factors

influence how knowledge is perceived including political affiliation

(Hamilton, 2011; McCright and Dunlap, 2011), educational attainment

(McCright and Dunlap, 2011), and the confidence placed on different

information sources (Sundblad et al., 2009). Various studies have

questioned a common assumption in the climate change literature that

improvements in climate information are needed to facilitate adaptation

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Chapter 16 Adaptation Opportunities, Constraints, and Limits

(Dessai et al., 2009; Hulme et al., 2009; Wilby and Dessai, 2010; Verdon-

Kidd et al., 2012; see also Section 2.4). Similarly, multiple authors have

questioned the utility and robustness of vulnerability metrics and indices

for informing adaptation decision making (Barnett et al., 2009; Klein,

2009; Hinkel, 2011; Preston et al., 2011b).

Similar tensions arise with respect to the role of traditional knowledge

in adaptation. For example, cultural preferences regarding the value of

traditional versus more formal scientific forms of knowledge influence

what types of knowledge, and therefore adaptation options, are considered

legitimate (Jones and Boyd, 2011). In the Arctic, Inuit traditional knowledge

(Inuit Qaujimajatuqangit, IQ) encompasses all aspects of traditional Inuit

culture including values, world-view, language, life skills, perceptions,

and expectations (Nunavut Social Development Council, 1999; Wenzel,

2004). IQ includes, for example, weather forecasting, sea ice safety,

navigation, and hunting and animal preparation skills that may have

value for managing climate risk. Yet, as noted in the AR4 and more

recent studies, these skills are declining among youth (medium evidence,

medium agreement; Adger et al., 2007; Pearce et al., 2011). Increasing

reliance on non-traditional forecasting (national weather office forecasts)

and other technologies (GPS) in Arctic communities is in part responsible

for increased risk taking when traveling on the land and sea ice (medium

evidence, medium agreement; Aporta and Higgs, 2005; Ford et al., 2006;

Pearce et al., 2011). Collectively, the recent literature suggests the

extent to which knowledge acts to constrain or enable adaptation is

dependent on how that knowledge is generated, shared, and used to

achieve desired adaptation objectives (very high confidence; Patt et al.,

2007; Nelson et al., 2008; Tribbia and Moser, 2008; Moser, 2010a,b).

Individual, institutional, and societal knowledge influences the capacity

to develop and use technologies to achieve adaptation objectives (very

high confidence; UNFCCC, 2006; Adger et al., 2007). The AR4 noted the

role of technology in contributing to spatial and temporal heterogeneity

in adaptive capacity and the potential for technology to constrain

Box 16-3 | Rates of Change as a Cross-Cutting Constraint

Future rates of global change will have a signiﬁcant inﬂuence on the demand for, and costs of, adaptation (very high conﬁdence).

Since the AR4, new research has conﬁrmed the commitment of the Earth system to future warming (Lowe et al., 2009; Armour and

Roe, 2011; WGI AR5 Section 12.5) and elucidated a broad range of tipping points or “key vulnerabilities” that would result in signiﬁcant

adverse consequences should they be exceeded (Lenton et al., 2008; Rockstrom et al., 2009; see also Chapter 19). While the speciﬁc

rate of climate change to which different ecological communities or individual species can adapt remains uncertain (Sections

16.3.2.3, 16.4.1), more rapid rates of change can constrain adaptation of natural systems (Hoegh-Guldberg, 2008; Gilman et al.,

2008; Maynard et al., 2008; CCSP, 2009; Hallegatte, 2009; Malhi et al., 2009a,b; Thackeray et al., 2010; Lemieux et al., 2011;

Fankhauser and Soare, 2013; see also Sections 4.3.2.5, 5.5.6), particularly in the presence of other environmental pressures (very high

conﬁdence; Brook et al., 2008). Literature suggests that the near-term economic costs of societal adaptation may be substantial, and

those costs increase incrementally over time as the climate changes (Section 17.4.4). Therefore, higher rates or magnitudes of climate

change may reduce the effectiveness of some adaptation options, and higher costs for adaptation may be incurred (New et al., 2011;

Stafford Smith et al., 2011; Peters et al., 2013; see also Section 16.6). However, more rapid rates of change may also create greater

incentives for adaptation, resulting in a faster pace of implementation (Travis and Huisenga, 2013).

Although rapid socioeconomic change, including economic development and technological innovation and diffusion, can enhance

adaptive capacity (Section 16.3.1), it can also pose constraints (very high conﬁdence; Section 20.3.2). Globally, economic losses from

climate extremes are doubling approximately every 1 to 2 decades owing to increasing economic exposure (Pielke Jr. et al., 2008;

Baldassarre et al., 2010; Bouwer, 2011; Gall et al., 2011; Munich Re, 2011; IPCC, 2012; Preston, 2013). Such losses are associated

with high interannual variability (Preston, 2013), but current trends are projected to continue in future decades (Pielke Jr., 2007;

Montgomery, 2008; O'Neill et al., 2010; UN DESA Population Division, 2011; Preston, 2013; see also Section 10.7.3), although losses

may decline relative to growth in gross domestic product (GDP; IPCC, 2012). In addition, population growth and economic development

can lead to greater resource consumption and ecological degradation (Alberti, 2010; Chen et al., 2010; Raudsepp-Hearne et al., 2010;

Liu et al., 2012), which can constrain adaptation in regions where livelihoods are closely linked to ecosystem goods and services (very

high conﬁdence; Badjeck et al., 2010; Marshall, 2010; Warner et al., 2010; see also Section 16.3.2.3 and Box CC-EA). The adaptation

literature also suggests that successful adaptation will be dependent in part on the rate at which institutions can learn to adjust to

the challenges and risks posed by climate change and implement effective responses (very high conﬁdence; Adger et al., 2009; Moser

and Ekstrom, 2010; Stafford Smith et al., 2011).

913

Adaptation Opportunities, Constraints, and Limits Chapter 16

daptation or create opportunities (Adger et al., 2007). Key considerations

with respect to technology as an adaptation constraint include (1)

availability; (2) access (including the capacity to finance, operate, and

maintain); (3) acceptability to users and affected stakeholders; and (4)

effectiveness in managing climate risk (Adger et al., 2007; Dryden-Cripton

et al., 2007; van Aalst et al., 2008; see also Sections 9.4.4, 11.7, 14.2.4,

15.4.3). Although technology has implications for regional adaptive

capacity (e.g., Sections 22.4.5.7, 27.3.6.2, 29.6.2), in-depth exploration

of technology in the adaptation literature is often associated with specific

sectors (Howden et al., 2007; Bates et al., 2008; van Koningsveld et al.,

2008; EPA, 2009; Parry et al., 2009; Zhu et al., 2010). For example, Howden

et al. (2007) note the importance of technology options for facilitating

adaptation including applications of existing management strategies

as well as introduction of innovative solutions such as bio- and

nanotechnology (see also Hillie and Hlophe, 2007; Bates et al., 2008;

Fleischer et al., 2011). Several studies from Africa have explored how

different factors drive awareness, uptake, and use of adaptation

technologies for agriculture (Nhemachena and Hassan, 2007; Hassan and

Nhemachena, 2008; Deressa et al., 2009, 2011). While such literature

identifies specific adaptation technology options, and in some cases the

costs associated with their implementation, quantitative understanding of

the extent to which improving technology will enhance adaptive capacity

or reduce climate change impacts remains limited (Piao et al., 2010).

16.3.2.2. Physical Constraints

The capacity of human and natural systems to adapt to a changing climate

is linked to characteristics of the physical environment including the climate

itself. Recent studies have suggested that the effort required to adapt

to an increase in global mean temperature of 4°C by 2100 may be

significantly greater than adapting to lower magnitudes of change (very

high confidence; Fung et al., 2011; Gemenne, 2011; New et al., 2011;

Nicholls et al., 2011; Stafford Smith et al., 2011; Thornton et al., 2011;

Zelazowski et al., 2011; see also Section 19.5.1). This challenge arises

from the magnitude of climate change, as well as the rate (Box 16-3).

A variety of non-climatic physical factors also can constrain adaptation

efforts of natural systems (very high confidence). For example, migration

can be constrained by geographical features such as lack of sufficient

altitude to migrate vertically or barriers posed by coastlines or rivers

(Clark et al., 2011). Alternatively, Lafleur et al. (2010) identify soil

conditions as a factor that may influence the migration of North American

forests in response to climate change. Such physical barriers to migration

can also arise from human activities. Feeley and Silman (2010) note that

anthropogenic land use change can constrain the migration of Andean

plant species to higher altitudes. Meanwhile, Titus et al. (2009) analyze

state and local land use plans along the U.S. Atlantic coast and conclude

that approximately 60% of coastal land below 1meter in elevation is

anticipated to be developed in the future, posing a physical barrier to

inland migration of wetlands (see also Bulleri and Chapman, 2010;

Jackson and McIlvenny, 2011). Collectively, such physical constraints

can reduce available migration corridors and the distances over which

migration is a feasible adaptive response.

Physical constraints have important implications for human adaptation

as well (medium evidence, high agreement). For example, the distribution

nd abundance of water is a feature of the physical environment that

is influenced by climate. Human consumption of freshwater increasingly

is approaching the sustainable yield of surface and groundwater systems

in a number of global regions (Shah, 2009; Pfister et al., 2009, 2011a,b;

see also Sections 3.3.2, 3.5). Water-dependent enterprises in such regions

may therefore have reduced flexibility to cope with transient or long-

term reductions in water supply. This in turn influences the portfolio of

adaptation actions that can be implemented effectively to manage risk

to water security and, subsequently, agriculture and food security (Hanjra

and Qureshi, 2010) as well as energy security (Voinov and Cardwell,

2009; Dale et al., 2011). Similarly, water quality and soil quality can

constrain agricultural activities and therefore the capacity of agricultural

systems to adapt to a changing climate (Delgado et al., 2011; Kato et

al., 2011; Lobell et al., 2011; Olesen et al., 2011).

It is important to note, however, that these physical characteristics of the

environment are often amenable to management (very high confidence).

The AR4 presented case studies where adaptive capacity was linked to

the ability of human populations or communities to access physical capital

(Adger et al., 2007), such as machinery or infrastructure, to manage the

environment and associated risks. Similar findings have appeared in

more recent studies (Paavola, 2008; Thornton et al., 2008; Iwasaki et al.,

2009; Badjeck et al., 2010; Nelson et al., 2010a,b). Human modification

of the physical environment is particularly apparent in urban areas,

where the location and design of buildings and infrastructure influence

vulnerability to climate variability and change (Section 8.2.2.2). However,

past decisions regarding the built environment and its need for continual

maintenance can constrain future adaptation options and/or their costs

of implementation (Section 16.3.2.10).

16.3.2.3. Biological Constraints

Since the AR4, the literature on biological (including behavioral,

physiological, and genetic) tolerances of individuals, populations, and

communities to climate change and extremes has continued to expand

(Sections 4.4, 5.5.6, 6.2). This has resulted in a significant increase in

the number of studies describing mechanisms by which biological factors

can constrain the adaptation options for humans, nonhuman species, and

ecological systems more broadly. In particular, biological characteristics

influence the capacity of organisms to cope with increasing climate

stress in situ through acclimation, adaptation, or behavior (Jensen et

al., 2008; Somero, 2010; Tomanek, 2010; Aitken et al., 2011; Donelson

et al., 2011; Gale et al., 2011; Sorte et al., 2011) as well as the rate at

which organisms can migrate to occupy suitable bioclimatic regions

(very high confidence; Morin and Thuiller, 2009; Hill et al., 2011; Feeley

et al., 2012). Studies of humans also find age and geographic variation

among populations with respect to perceptions of thermal comfort in

indoor and outdoor space, which in turn influences the use of technologies

(e.g., air conditioning, vegetation) and behavior to adjust to the thermal

environment (Indraganti, 2010; Chen and Chang, 2012; Yang et al.,

2012; Fuller and Bulkeley, 2013; Müller et al., 2013).

The biological capacity for migration among nonhuman species is linked

to characteristics such as fecundity, phenotypic and genotypic variation,

dispersal rates, and interspecific interactions (Aitken et al., 2008; Engler

et al., 2009; Hellmann et al., 2012). For example, Aitken et al. (2008)

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Chapter 16 Adaptation Opportunities, Constraints, and Limits

rgue that migration rates of tree species necessary to track a changing

climate are higher than what has been observed since the last glaciation.

However, Kremer et al. (2012) note that long-distance gene flow of tree

species can span distances in one generation that are greater than habitat

shifts predicted under climate change. Additional research is needed to

clarify the capacity of species and communities to migrate in response

to a changing climate.

The degradation of environmental quality is another source of constraints

(very high confidence; Côté and Darling, 2010), with multiple studies

including natural capital as a foundation for sustainable livelihoods

(Paavola, 2008; Thornton et al., 2008; Iwasaki et al., 2009; Badjeck et

al., 2010; Nelson et al., 2010a,b). Non-climatic stresses to ecological

systems can reduce their resilience to climate change as evidenced by

studies on coral reefs and marine ecosystems, tropical forests, and

coastal wetlands (very high confidence; Diaz and Rosenberg, 2008;

Kapos and Miles, 2008; Malhi et al., 2009a,b; Afreen et al., 2011; see

also Section 4.2.4 and Box CC-CR). For example, several studies have

noted interactions between anthropogenic land use change and species

migration rates on the risk of extirpation (Feeley et al., 2010; Yates et

al., 2010; Cabral et al., 2013; Svenning and Sandel, 2013).

Ecological degradation also reduces the availability of ecosystem goods

and services for human populations (very high confidence; Nkem et al.,

2010; Tobey et al., 2010; see also Sections 4.4.3, 6.4.1). For example,

degradation of coastal wetlands and coral reef systems may reduce their

capacity to buffer coastal systems from the effects of tropical cyclones

(Das and Vincent, 2009; Tobey et al., 2010; Gedan et al., 2011; Keryn et

al., 2011; Box CC-EA). Similarly, soil degradation and desertification can

reduce crop yields and the resilience of agricultural and pastoral

livelihoods to climate stress (Iglesias et al., 2011; Lal, 2011).

Ecosystem constraints can also arise from non-native species, including

pests and disease, that compete with endemic species (Hellman et al.,

2008; Dukes et al., 2009; Moser et al., 2011; Ziska et al., 2011; Pautasso

et al., 2012; Svobodová et al., 2013; see also Section 4.2.4.6). Climate

change could reduce the effectiveness of current control mechanisms for

invasive species (very low confidence; Hellmann et al., 2008). However,

studies also indicate that uncertainty associated with predictions of future

pests, disease, and invasive species remains high (Dukes et al., 2009).

16.3.2.4. Economic Constraints

The AR4 concluded that adaptive capacity is influenced by the entitlements

of actors to economic resources and by larger macro-level driving forces

such as economic development and trends in globalization (Adger et al.,

2007). More recent literature continues to identify economic constraints

associated with adaptation. However, such constraints often involve the

financing of discrete adaptation options (e.g., Matasci et al., 2013; Islam

et al., 2014). This chapter draws a distinction between such financial

constraints (Section 16.3.2.5) and economic constraints, which are

associated with broader macroeconomic considerations.

Long-term trends in economic development as well as short-term

dynamics in economic systems can have a significant influence on the

capacity of actors to adapt to climate change (very high confidence;

ection 16.3.1.1). Multiple authors, for example, discuss the concept of

“double exposure” where actors are subjected to stresses associated with

climate change as well as those associated with economic disruptions

such as the recent global financial crisis or other stresses (Leichenko et

al., 2010; Silva et al., 2010; Leichenko, 2012; Jeffers, 2013; McKune and

Silva, 2013). Similarly, Kiem and Austin (2013) argue that prevailing

economic conditions have an important influence on the capacity of

Australian farmers to cope with drought.

The implications of economic constraints vary among different sectors

that have differential vulnerability to climate change. Economies that

are disproportionately composed of climate-sensitive sectors such as

agriculture, forestry, and fisheries may be particularly vulnerable to the

effects of climate change and may encounter greater constraints on

their capacity to adapt (very high confidence). Such economies occur

disproportionately in the developing world (Thornton et al., 2008; Allison

et al., 2009; Feng et al., 2010; Füssel, 2010), although multiple studies

have explored climate-sensitive regional economies in developed nations

as well (Edwards et al., 2009; Leichenko et al., 2010; Aaheim et al., 2012;

Kiem and Austin, 2013). Poverty and development deficits that are

linked to economic conditions also exist in urban areas (Sections 8.1.3,

8.3.2.1).

While economic development and diversification are generally seen as

factors that can ameliorate resource deficits (Sections 20.2.1.2, 20.3.2),

certain economic enterprises can constrain adaptation. For example, the

AR4 noted that activities such as shrimp farming and conversion of coastal

mangroves, though profitable in an economic sense, can exacerbate

vulnerability to sea level rise (Agrawala et al., 2005; Adger et al., 2007).

More recent studies have demonstrated that economic development

and urbanization of hazardous landscapes may increase human exposure

to extreme weather events and climate change, resulting in greater

economic losses and risks to public health and safety (Baldassare et al.,

2010; IPCC, 2012; Preston, 2013). Economic development also can put

pressure on natural resources and ecosystems that can constrain their

capacity to adapt (Titus et al., 2009; Sydneysmith et al., 2010; see also

Sections 16.3.2.3, 20.3.2). The extent to which economic development

creates opportunities or constrains adaptation is dependent on the

development pathway (Section 20.6). Low resource-intensive economic

growth can enhance adaptive capacity while minimizing externalities

of development that can increase vulnerability of human and natural

systems (Section 20.6).

16.3.2.5. Financial Constraints

In addition to broader macroeconomic constraints on adaptation (Section

16.3.2.4), the implementation of specific adaptation strategies and options

can be constrained by access to financial capital (very high confidence).

Financial capital can manifest in a variety of forms including credit,

insurance, and tax revenues, as well as earnings of individual households

or private entities. The AR4 concluded that the global costs of adaptation

could be quite substantial over the next several decades (Adger et al.,

2007). More recent studies suggest costs on the order of US$75 to

US$100 billion per year by 2050 (Section 17.4; Table 17-2). In the context

of the UNFCCC, mechanisms have been established to help meet these

costs. The Least Developed Country Fund was established to assist

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Adaptation Opportunities, Constraints, and Limits Chapter 16

eveloping nations in generating National Adaptation Plans of Action

(Sections 14.4.4, 15.2.3). The Adaptation Fund was established within

the context of the UNFCCC to finance adaptation in developing nations

through the sale of certified emissions reductions (CERs) credits under the

Clean Development Mechanism (Sections 14.3.2, 15.2.2.1). Nevertheless,

declines in CER credit prices since early 2011 have reduced the flow of

revenue to the Adaptation Fund (Adaptation Fund Board, 2013), and

the demand for adaptation finance in general is larger than the current

availability of resources represented through these funds (Bouwer and

Aerts, 2006; Flåm and Skjærseth, 2009; Hof et al., 2009). Furthermore,

developing a framework for the equitable and effective allocation of

adaptation funds to developing nations is a non-trivial challenge (Smith

et al., 2009a; Barr et al., 2010).

Overseas development assistance (ODA) represents another mechanism

for channeling financial capital into adaptation programs and projects.

However, multiple authors have identified potential constraints associated

with the use of ODA for financing adaptation, including concerns among

donors for the effectiveness of ODA (Kalirajan et al., 2011), lack of

incentives among donors to allocate ODA to adaptation (Buob and

Stephan, 2013), and potential for allocation of ODA to adaptation to

reduce the availability of funds for achieving development goals (Ayers

and Huq, 2009).

The potential for finance to constrain adaptation also emerges from a

broad range of recent case studies exploring adaptive capacity in

different sector and regional contexts, although finance is often identified

as just one of a broad range of resource constraints (Paavola, 2008;

Jantarasami et al., 2010; Moser and Ekstrom, 2010; Osbahr et al., 2010;

Biesbroek et al., 2013a). Investigations of farming communities in Africa

have identified finance as a key determinant of vulnerability and adaptive

capacity of farmers to climate variability and change (Nhemachena and

Hassan, 2007; Hassan and Nhemachena, 2008; Deressa et al., 2009,

2011). Islam et al. (2014) cite access to credit as a key constraint on

adaptation among fishing communities in Bangladesh, and financial

constraints have also been documented in municipal governments in

South Africa (Pasquini et al., 2013). Huntington et al. (2012) question

whether relocating the 184 Alaskan Native villages threatened by

coastal erosion and inundation is politically feasible given the high

costs, estimated at up to US$1 million per person or US$100 million per

village on average.

Institutions in developed nations face constraints in funding adaptation

options despite their comparatively high adaptive capacity. For example,

Jantarasami et al. (2010) report that staff from U.S. federal land

management agencies identified resource constraints as a key barrier

to adaptation. Similarly, surveys and interviews with state and local

government representatives in Australia indicate that the costs of

investigating and responding to climate change are perceived to be

significant constraints on adaptation at these levels of governance

(Smith et al., 2008b; Gardner et al., 2010; Measham et al., 2011). However,

Burch (2010) argues that financial constraints on adaptation reported

by local governments in Canada are secondary to other institutional

practices and cultures (Section 16.3.2.8).

Insurance represents a cross-cutting financial instrument that is relevant

to a range of public and private institutions in both developing and

eveloped nations. While insurance can represent an opportunity to

influence decision making regarding climate risk management (Næss

et al., 2005; Herweijer et al., 2009; see also Section 10.7), reduced

accessibility and/or increased costs of insurance can constrain the utility

of insurance as an adaptation option (Herwijer et al., 2009; Islam et al.,

2014; see also Section 10.7).

16.3.2.6. Human Resource Constraints

The effectiveness of societal efforts to adapt to climate change is

dependent on humans who are the primary agents of change (very high

confidence). Human resources provide the foundation for intelligence

gathering, the uptake and use of technology, as well as leadership

regarding the prioritization of adaptation policies and measures and

their implementation. Although the AR4 and subsequent adaptation

literature identify human resources as one of the factors influencing

adaptive capacity (Adger et al., 2007), there has been little attention

given specifically to human resources as a constraint on adaptation by

adaptation researchers. Rather the literature mentions human resources

in two principal contexts. First, it highlights the linkages between the

development of human resources and adaptive capacity more broadly.

For example, Ebi and Semenza (2008) treat human resources as part of

the portfolio of resources that can be harnessed to facilitate adaptation

in the public health arena. Similarly, Nelson et al. (2010a,b) use human

capital as one indicator of the capacity of rural communities to cope with

climate impacts. In addition, a number of recent studies call attention

to the role of leadership in enabling or constraining organizational

adaptation (Gupta et al., 2010; Tompkins et al., 2010; van der Berg et al.,

2010; Termeer et al., 2012). Murphy et al. (2009) discuss the emergence

of institutions to build human resources in the climate change arena,

including expanded higher education opportunities to build climate

expertise as well as professional societies. Second, the literature

highlights the finite nature of human resources as a need to prioritize

adaptation efforts including the extent of engagement in participatory

processes (van Aalst et al., 2008) as well as the selection of adaptation

actions for implementation (Millar et al., 2007).

16.3.2.7. Social and Cultural Constraints

Adaptation can be constrained by social and cultural factors that are

linked to societal values, world views, and cultural norms and behaviors

(very high confidence; O’Brien, 2009; Moser and Ekstrom, 2010; O’Brien

and Wolf, 2010; Hartzell-Nichols, 2011). These social and cultural factors

can influence perceptions of risk, what adaptation options are considered

useful and by whom, as well as the distribution of vulnerability and

adaptive capacity among different elements of society (Grothmann and

Patt, 2005; Weber, 2006; Patt and Schröter, 2008; Adger et al., 2009;

Kuruppu, 2009; O’Brien, 2009; Nielsen and Reenberg, 2010; Wolf and

Moser, 2011; Wolf et al., 2013). Although the AR4 noted that social and

cultural constraints on adaptation have not been well researched, more

recent literature has significantly expanded their understanding. As a

case in point, the erosion of traditional knowledge among the Arctic

Inuit is the consequence of a long-term process of changing livelihoods,

technology, and sources of knowledge (Pearce et al., 2011; see also

Section 16.3.2.1). Studies from the USA indicate that increasing demand

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Chapter 16 Adaptation Opportunities, Constraints, and Limits

or amenity lifestyles is resulting in the settlement of individuals in

locations where there is little experience or oral history regarding natural

hazards—a phenomenon that subsequently influences risk perception

and engagement in risk management (Heyd and Brooks, 2009; Gordon

et al., 2013).

Different actors within and among societies experience different

constraints, which result in differential adaptive capacities and preferences

for adaptation options (Wolf et al., 2013). As discussed in the AR4, for

example, gender can be a factor that constrains adaptation. Recent

studies from Nepal and India report that adaptation decisions among

women, in particular, can be constrained by cultural and institutional

pressures that favor male land ownership (Jones and Boyd, 2011) and

constrain access to hazard information (Ahmed and Fajber, 2009),

respectively. Studies of evacuation during Hurricane Katrina suggest

that females were more likely to evacuate New Orleans than males

(Brunsma et al., 2010), as were individuals without sufficient resources

and access to transportation (Cutter and Emrich, 2006). Studies from

both the USA and UK find that the elderly do not necessarily perceive

themselves as vulnerable to extreme heat events (Sheridan, 2007; Wolf

et al., 2009), which may create disincentives to react to such events

(Chapter 11).

Barriers to taking action have also been attributed to sense of place,

which shapes individual identity (Adger et al., 2011, 2012; Fresque-

Baxter and Armitage, 2012). Foresight (2011) notes that processes that

constrain migration could be maladaptive, resulting in the abandonment

of livelihoods or geographic locations. For example, Park et al. (2012)

find that sense of place attachment among some wine grape growers

in Australia precludes consideration for migration to other growing

areas in response to a changing climate.

Case studies from multiple developing countries report that some actors

view natural phenomena as being controlled by God, supernatural

forces, or ancestral spirits that are not amenable to human management

(Sehring, 2007; Schipper, 2008; Byg and Salick, 2009; Mustelin et al.,

2010; Kuruppu and Liverman, 2011; Artur and Hilhorst, 2012). Such

perspectives are not confined to the developing world. Surveys

conducted after Hurricane Katrina also indicated that religious beliefs

were a factor influencing the decision to remain rather than evacuate

(Brunsma et al., 2010).Yet, religion was also identified as a factor that

enabled affected individuals to cope with the stress of the event.

16.3.2.8. Governance and Institutional Constraints

Research conducted since the AR4 has expanded understanding of

adaptation constraints associated with governance, institutional

arrangements, and legal and regulatory issues. Adaptation to climate

change will necessitate the mobilization of resources, decision making,

and the implementation of specific policies by societal institutions

(Huang et al., 2011). Yet, these processes may be most effective when

they are aligned to the given context and group of actors (Berkhout,

2012; Garschagen, 2013). The adaptation literature provides extensive

evidence that institutional capacity is a key factor that can potentially

constrain the adaptation process (very high confidence; Berkhout, 2012).

Lesnikowski et al. (2013), for example, find that planned adaptation

y the public health sector among different nations is significantly

associated with national GDP. Similarly, it has been argued that U.S.

institutions across different levels of governance lack the mandate,

information, and/or professional capacity to select and implement

adaptation options (National Research Council, 2009). Institutional

capacity may be linked to the level of priority assigned to adaptation

(Keskitalo et al., 2010; Westerhoff et al., 2010; Maibach et al., 2011;

Measham et al., 2011; Sowers et al., 2011). For example, Ebi et al. (2009)

argue that U.S. public health agencies allocate less than US$3 million

per year to address climate change, yet a budget greater than US$200

million is needed to adequately address the problem. Keskitalo (2010)

and Lesnikowski et al. (2013) find that adaptation efforts are associated

with the extent to which institutions prioritize environmental management

more broadly. Corruption within institutions may also undermine

adaptation efforts, as evidenced by empirical studies among multiple

nations (Lesnikowski et al., 2013), as well as case studies within nations

(Schilling et al., 2012).

A key role that institutions play in facilitating adaptation is through legal

and regulatory responsibilities and authorities (very high confidence).

Multiple studies have documented the adaptation constraints affecting

institutions in Australia engaged in the development of local and regional

planning policy (Pini et al., 2007; Measham et al., 2011; Matthews,

2013). Similar capacity constraints have been observed within

institutions governing Canada’s Inuit population (Ford et al., 2010). Li

and Huntsinger (2011) observe how increasing land privatization and

the institutionalization of rigid land tenure in the Inner Mongolia region

of China have reduced the resilience of pastoralists to cope with

drought, although the lack of secure land tenure has been found to

constrain adaptation in other contexts (Almansi, 2009; Ebi et al., 2011;

Hisali et al., 2011; Larson, 2011; see also Sections 8.4.2.2, 9.3.5.1.3). In

addition to such capacity issues, multiple studies from both developed

and developing nations suggest that the current structure of institutions

and regulatory policies may be poorly aligned to achieve adaptation

objectives (Craig, 2010; Spies, 2010; Stillwell et al., 2010; Stuart-Hill and

Schulze, 2011; Eisenack and Stecker; 2012; Huntjens et al., 2012;

Herrfahrdt-Pähle, 2013). Changing legal principles to accommodate

more forward-looking adaptation responses as opposed to basing them

on historical precedent and practice may be a difficult process (Craig,

2010; McDonald, 2011).

Adaptation can also be constrained owing to the complexities of

governance networks that are often composed of multiple actors and

institutions such as government agencies, market actors, NGOs, as

well as informal community organizations and social networks (very

high confidence; Rosenau, 2005; Adger et al., 2009; Juhola and

Westerhoff, 2011; Carlsson-Kanyama et al., 2013; Sosa-Rodriguez,

2013). Coordination among these different actors is important for

facilitating adaptation decision making and implementation (Young,

2006; van Nieuwaal et al., 2009; Grothmann, 2011). Yet, different actors

may have different objectives, jurisdictional authority, as well as levels of

power or resources. Adaptation efforts may recognize these constraints,

but do not necessarily articulate institutional arrangements that

facilitate their coordination and reconciliation to achieve common

adaptation objectives (Zinn, 2007; Preston, 2009; Birkmann et al., 2010;

see also Section 15.5.1). This may arise, in part, from the dominant focus

of the adaptation discourse on formal, public institutions of governance

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Adaptation Opportunities, Constraints, and Limits Chapter 16

(

Eisenack et al., 2012), although work examining the role of private

institutions has emerged recently (Tompkins et al., 2010; CDP, 2012;

Mees et al., 2012; Taylor et al., 2012; Tompkins and Eakin, 2012; EBI,

2013; see also Section 14.2.4).

Actors and institutions associated with different scales may have

different perceptions of the need for adaptation as well as the factors that

constrain or enable adaptation (very high confidence; Biesbroek et al.,

2011). In this context, scale refers to analytical dimensions used to study

adaptation (including spatial, temporal, institutional, or jurisdictional),

and each scale can be comprised of multiple levels (e.g., local to global

in the context of spatial scales or household to central government in

the context of jurisdictions of governance) (Cash et al., 2006; Adger et

al., 2009). A large number of studies have emerged since the AR4 that

focus on how local adaptation efforts are constrained by higher levels

of governance, such as state or federal governments or private companies

(Urwin and Jordan, 2008; Huntjens et al., 2010; Abel et al., 2011;

Measham et al., 2011; Pittock, 2011; Westerhoff et al., 2011; Amaru and

Chhetri, 2013; Carlsson-Kanyama et al., 2013; Mukheibir et al., 2013;

Sosa-Rodriguez, 2013). This has led some to question whether it is

appropriate to consider adaptation as an exclusively local process (Burton

et al., 2008; Preston et al., 2013b). For example, a study of adaptation

policy initiatives in EU member countries concluded that central

governments can play a significant role in supporting local adaptation

policies. However, in cases where there is weak top-down leadership

on adaptation, it may be useful to have less centralized mechanisms

for supporting local adaptation efforts (Keskitalo, 2010). In addition, EU

funding has enabled local adaptation even in the absence of funding

from the relevant EU member state (Keskitalo, 2010), suggesting

opportunities exist for transnational governance to overcome adaptation

constraints.

Other authors have also noted that informal social institutions may help

to extend the reach of formal government actors (Wolf et al., 2010;

Juhola and Westerhoff, 2011) or drive adaptation processes when formal

actors are unable to do so (Measham and Preston, 2012). Adaptation

planning and implementation thus creates new governance challenges,

and new institutions and bridging organizations may be needed to

facilitate integration of complex planning processes across scales (medium

evidence, high agreement; Preston, 2009; National Research Council,

2010; UKCIP, 2011).

16.3.2.9. Constraints and Competing Values

A number of the aforementioned types of adaptation constraints arise

from a common cause—the differential values of societal actors and

the trade-offs associated with prioritizing and implementing adaptation

options (very high confidence; Haddad, 2005; UNEP, 2011; see also

Section 2.3.3 and Table 16-2). At the international level, for example,

agreements such as the Bali Action Plan (UNFCCC, 2007a) and Cancun

Adaptation Framework (UNFCCC, 2011) indicate that deliberation over

how the adaptation needs of least developed countries will be financed

has become central to the UNFCCC policy agenda (see also UNFCCC,

2007b; Ayers and Huq, 2009; Dellink et al., 2009; Flåm and Skjærseth,

2009; Denton, 2010; Patt et al., 2010a). Yet the extent to which the

developed world bears responsibility for compensating the developing

orld for climate impacts has been a contentious issue (Hartzell-Nichols,

2011). Rayner and Jordan (2010) and Brouwer et al. (2013) report

concern among EU water policy makers that adaptation may undermine

efforts to maintain water quality. For example, technological solutions

to enhance water supply in a changing climate may occur at the

expense of water quality. Alternatively, placing adaptation on the policy

agenda may create the perception that climate change will eventually

necessitate the acceptance of reduced water quality. At the local level,

Measham et al. (2011) report that some local governments in Australia

find it difficult to pursue adaptation efforts owing to perceived conflicts

between potential adaptation options and the values and preferences

of individuals and stakeholder groups within the community.

Such potential differences among stakeholders regarding adaptation

options may result in some actions being simultaneously perceived as

adaptive and maladaptive (limited evidence, medium agreement; Bardsley

and Hugo, 2010). Maladaptation arises from the implementation of

adaptation options that increase the vulnerability of individuals,

institutions, sectors, or regions (Barnett and O’Neill, 2010). Individuals

or institutions may have specific management objectives or values that

they seek to achieve or maintain through adaptation (Section 16.2, Table

16-2). For every objective, however, there may be multiple adaptation

options, each of which is associated with a particular set of costs,

benefits, and externalities. For example, biotechnology may contribute

to the development of drought- and pest-resistant cultivars that can

maintain or enhance yields despite more challenging climate conditions.

Yet, ecological and public health concerns over the use of biotechnology

and genetically modified crops, in particular, can constrain the use of

such technologies (Table 16-2). Agricultural producers may view

biotechnology as an adaptive response, while some consumers may

view it as a maladaptation that increases risks to ecosystems and food

security. Similar types of trade-offs can be identified across different

sectors (Table 16-2), and thus a challenge in adaptation planning and

implementation is determining who decides what options are adaptive

or maladaptive and successful or unsuccessful. The potential for

maladaptation or for some adaptation options to undermine sustainability

(Eriksen et al., 2011) suggests that actors may choose to regulate

adaptation and deliberately constrain possible options to avoid adverse

externalities (very low confidence).

Recognizing the potential for values conflicts to constrain adaptation,

researchers and practitioners have advocated for so-called “no regrets”

or “low regrets” adaptation strategies that create net benefits under

the current climate as well as a range of future potential climates

(Hallegatte, 2009; Heltberg et al., 2009). Such strategies can focus

adaptation efforts on options where there are fewer perceived trade-

offs (Preston et al., 2013b). However, identifying options that are

perceived as having no regrets across all potential stakeholders may be

quite difficult (Merz et al., 2010; Preston et al., 2013b), and it has been

suggested such strategies may reduce the perceived need for more

substantive adaptations necessary to protect highly vulnerable systems

or avoid irreversible consequences (Preston et al., 2013b). Reconciling

such trade-offs may necessitate deliberation among decision makers

and other stakeholders regarding adaptation objectives and the manner

in which competing or conflicting values can be reconciled to achieve

outcomes (de Bruin et al., 2009b; McNamara and Gibson, 2009;

McNamara et al., 2011; UNEP, 2011).

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Chapter 16 Adaptation Opportunities, Constraints, and Limits

16.3.2.10. Consideration of Cross-Scale Dynamics

The AR4 noted that adaptation processes can be constrained by

interactions and dynamics within or among different scales (Adger et

al., 2007). Recent literature since the AR4 has expanded understanding

of vulnerability and adaptive capacity as a cross-scale and multilevel

process. The vulnerabilities of different communities, regions, and

sectors are linked through processes and feedbacks that span multiple

scales and levels (medium evidence, high agreement). Adger et al.

(2008) and Eakin et al. (2009) refer to this phenomenon as “nested and

teleconnected vulnerability.”

A number of recent studies focused on agriculture and global commodities

provide evidence of this phenomenon. Adger et al. (2008) and Eakin et

al. (2009) illustrate such teleconnected vulnerability with case studies of

coffee production. Although coffee is a global commodity, the majority

of production occurs in developing nations among small-scale farmers.

As such, household vulnerability and adaptive capacity among coffee

farmers is linked to global markets and coffee prices as well as local

environmental conditions and policies. Such interactions were also

apparent in 2006–2008 and again in 2010–2011 when global food

commodity prices increased sharply in part due to the impacts of extreme

weather events on food-producing regions (FAO, 2011). The resulting

increase in food prices benefited producers that were unaffected by the

drought and were able to capitalize on higher prices, but higher prices

adversely affected consumer welfare and food security (Abbott and de

Battisti, 2009; Woden and Zaman, 2009; FAO, 2011).

Similar constraints on adaptation arise in the context of transboundary

water resources where river management is influenced by processes

occurring at different jurisdictional levels (i.e., local, regional, national,

and international water policies and management practice) as well as

different spatial levels (e.g., linkages between global climate change

and climate trends at more regional or local levels) (Iglesias et al., 2007;

Sector Actor’s adaptation objective Adaptation option Real or perceived trade-off References

Agriculture

nhance drought and pest resistance;

enhance yields

iotechnology and genetically modiﬁ ed

crops

erceived risk to public health and

safety; ecological risks associated with

ntroduction of new genetic variants to

atural environments

owden et al. (2007); Nisbet and

Scheufele (2009); Fedoroff et al. (2010)

Provide ﬁ nancial safety net for farmers

o ensure continuation of farming

enterprises

Subsidized drought assistance; crop

nsurance

Creates moral hazard and distributional

nequalities if not appropriately

administered

Productivity Commission (2009); Pray et

l. (2011); Trærup (2011); O’Hara (2012);

Vermeulen et al. (2012)

aintain or enhance crop yields;

suppress opportunistic agricultural pests

nd invasive species

ncreased use of chemical fertilizer and

pesticides

ncreased discharge of nutrients and

chemical pollution to the environment;

dverse impacts of pesticide use on

on-target species; increased emissions

of greenhouse gases; increased human

xposure to pollutants

regory et al. (2005); Howden et al.

(2007); Boxall et al. (2009)

Biodiversity

Enhance capacity for natural adaptation

nd migration to changing climatic

conditions

Migration corridors; expansion of

onservation areas

Unknown efﬁ cacy; concerns over

roperty rights regarding land

acquisition; governance challenges

Hodgson et al. (2009); West et al. (2009);

rosby et al. (2010); Levin and Petersen

(2011)

Enhance regulatory protections for

pecies potentially at risk due to climate

and non-climatic changes

Protection of critical habitat for

ulnerable species

Addresses secondary rather than primary

ressures on species; concerns over

property rights; regulatory barriers to

egional economic development

Clark et al. (2008); Ragen et al. (2008);

ernanzzani et al. (2012)

Facilitate conservation of valued species

y shifting populations to alternative

areas as the climate changes

Assisted migration Difﬁ cult to predict ultimate success of

ssisted migration; possible adverse

impacts on indigenous ﬂ ora and fauna

from introduction of species into new

cological regions

Lovejoy (2005, 2006); McLachlan et al.

(

2007); Dunlop and Brown (2008)

Coasts

Provide near-term protection to ﬁ nancial

assets from inundation and / or erosion

Sea walls High direct and opportunity costs; equity

concerns; ecological impacts to coastal

wetlands

Nicholls (2007); Hayward (2008);

Hallegatte (2009); Zhu et al. (2010)

Allow natural coastal and ecological

processes to proceed; reduce long-term

risk to property and assets

Managed retreat Undermines private property rights;

signiﬁ cant governance challenges

associated with implementation

Rupp-Armstrong and Nicholls (2007);

Hayward (2008); Abel et al. (2011); Titus

(2011)

Preserve public health and safety;

minimize property damage and risk of

stranded assets

Migration out of low-lying areas Loss of sense of place and cultural

identify; erosion of kinship and familial

ties; impacts to receiving communities

Hess et al. (2008); Heltberg et al. (2009);

McNamara and Gibson (2009); Adger et

al. (2011)

Water

resources

management

Increase water resource reliability and

drought resilience

Desalination Ecological risk of saline discharge; high

energy demand and associated carbon

emissions; creates disincentives for

conservation

Adger and Barnett (2009); Barnett and

O’Neill (2010); Becker et al. (2010, 2012);

Rygaard et al. (2011); Tal et al. (2011)

Maximize efﬁ ciency of water

management and use; increase ﬂ exibility

Water trading Undermines public good / social aspects

of water

Alston and Mason (2008); Bourgeon et

al. (2008); Donohew (2008); Mooney and

Tan (2012); Tan et al. (2012)

Enhance efﬁ ciency of available water

resources

Water recycling / reuse Perceived risk to public health and safety Hartley (2006); Dolcinar et al. (2011)

Table 16-2 | Examples of potential trade-offs associated with an illustrative set of adaptation options that could be implemented by actors to achieve speciﬁ c management

objectives.

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Adaptation Opportunities, Constraints, and Limits Chapter 16

oulden et al., 2009; Huntjens et al., 2010; Krysanova et al., 2010;

Timmerman et al., 2011; Wilby and Keenan, 2012; Milman et al., 2013).

Constraints on adaptation are also associated with temporal scaling. A

key factor constraining future adaptation options and costs is path

dependence (very high confidence), which Preston (2013, p. 719) defines

as “the dependence of future societal decision processes and/or socio-

ecological outcomes on those that have occurred in the past.” Libecap

(2010) suggests that water infrastructure developed in the U.S. West in

the late-19th and early 20th centuries has constrained management

choice regarding water allocation in the present. Chhetri et al. (2010)

suggest similar constraints may exist for the U.S. agricultural industry

in the future owing to constraints on farmers’ capacity to alter

management practices and technology in response to a changing climate.

Major development of water management and allocation systems in

watersheds of Australia and the U.S. Southeast over the latter half of

the 20th century occurred during periods of favorable rainfall relative

to long-term instrumental and paleo records (Jones and Pittock, 2002;

Jones, 2010; Chiew et al., 2011; Pederson et al., 2012), and thus those

systems were adapted to conditions that were not representative of the

long-term risk of extensive drought (Jones and Pittock, 2002; Jones,

2010; Connell and Grafton, 2011; Pederson et al., 2012).

Adjusting large-scale, complex systems and institutional behavior

established by past decision making can be costly. The Australian

government, for example, has engaged in a water management reform

process since the 1980s (Connell and Grafton, 2011), and in recent years

has committed more than AUS$12.9 billion for a number of initiatives to

address historical resource over-allocation and support sustainable water

management practices in the Murray-Darling Basin (Commonwealth of

Australia, 2010).

To avoid adverse outcomes associated with path dependence, literature

on flexible adaptation pathways emphasizes the implementation of

reversible and flexible options that allow for ongoing adjustment

(Stafford Smith et al., 2011; Haasnoot et al., 2013). In addition, the

literature on “real options” suggests that, under certain circumstances,

there may be value in such flexible adaptation strategies or in delaying

investments in certain adaptation options until new information or

management options are available (Hertzler, 2007; Dobes, 2008; Jeuland

and Whittington, 2013).

16.4. Limits to Adaptation

The various constraints discussed previously (Section 16.3.2) can, if

sufficiently severe, pose limits to the ability of actors to adapt to climate

change (medium evidence, high agreement; Meze-Hausken, 2008;

Adger et al., 2009; O’Brien, 2009; Moser and Ekstrom, 2010; Dow et al.,

2013a,b). A limit is reached when adaptation efforts are unable to

provide an acceptable level of security from risks to the existing objectives

and values and prevent the loss of the key attributes, components, or

services of ecosystems (Box 16-1). For example, one of the key messages

from the WGII AR5 chapter on Africa (Chapter 22) is, “Progress is being

achieved on managing risks to food production from current climate

variability but these will likely not be sufficient to address long-term

risks from climate change (high confidence).”

There are a variety of circumstances and terminology in the literature

that imply adaptation limits including “thresholds” (Meze-Hausken,

2008; Briske et al., 2010; Washington-Allen et al., 2010); “regime shifts”

(Washington-Allen et al., 2010); “tipping points” (Lenton et al., 2008;

Kriegler et al., 2009); “dangerous climate change” (Mastrandrea and

Schneider, 2004; Ford, 2009a); “reasons for concern” (Smith et al.,

2009a); “planetary boundaries” (Rockström et al., 2009); or “key

vulnerabilities” (Schneider et al., 2007; Hare et al., 2011; Johannessen

and Miles, 2011; see also Section 19.6). In addition, terms such as

barriers, constraints, and limits are sometimes used interchangeably.

Owing to this diversity in language, this discussion builds on recent

efforts to develop a common lexicon to facilitate research and practice

(Hulme et al., 2007; Adger et al., 2009; Dow et al., 2013a,b; see also

Section 16.2 and Box 16-1).

16.4.1. Hard and Soft Limits

Although limits to adaptation are at times described in the literature

as fixed thresholds (Adger et al., 2009), recent studies have emphasized

the need to consider the perspective of actors in defining adaptation

limits (Adger et al., 2009; Dow et al., 2013 a,b; see also Sections 16.1-2)

as well as the dynamic nature of both biophysical and socioeconomic

processes that influence adaptation decision making and implementation

(Park et al., 2012; Preston et al., 2013a; Islam et al., 2014). Informed by

the distinctions drawn in the work of Meze-Hausken (2008), Adger et

al. (2009), and Moser and Ekstrom (2010), one can distinguish between

“hard” limits, those that will not change, and “soft” limits, which could

change over time. For human actors, whether a limit is hard or soft is

usefully evaluated at a given point in time by asking whether an

adaptation response to manage an intolerable risk could emerge in the

future. For example, projected climate change impacts in Europe indicate

that increasing irrigation needs will be constrained by reduced runoff,

demand from other sectors, and economic costs. As a consequence, by

the 2050s, farmers will be limited by their inability to use irrigation to

prevent damage from heat waves to crops (Sections 23.4.1, 23.4.3). For

natural systems, whether a limit is hard or soft is defined by the rate and

capacity of species and ecosystem responses relative to environmental

changes (Shaw and Etterson, 2012).

Discussions of hard limits in the literature are often associated with

thresholds in physical systems that, if exceeded, would lead to irreversible

changes or the loss of critical structure or function (Lenton et al., 2008;

Adger et al., 2009; IPCC, 2012). Such limits arise from the magnitude

and/or rate of climate change (Box 16-3). For example, a number of

physical thresholds in the Earth system have been proposed as posing

potential limits to adaptation, particularly large-scale events such as

irreversible melting of the Greenland or Antarctic ice sheets (Schneider

and Lane, 2006a; Sheehan et al., 2008; Travis, 2010). Such physical

thresholds, however, though relevant to understanding adaptation limits,

are not necessarily limits in themselves as they neglect consideration

for the adaptive capacity of natural and human systems (Adger et al.,

2009; Leary et al., 2009; Dow et al., 2013a,b; Klein and Juhola, 2013;

Preston et al., 2013a).

For species and ecosystems, hard limits to adaptation are often associated

with exceedance of the physiological capacity of individual organisms

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Chapter 16 Adaptation Opportunities, Constraints, and Limits

or communities to adapt to changes in the climate (i.e., temperature,

rainfall, and/or disturbance regimes; Peck et al., 2009), or to climate-

induced changes in the abiotic environment (e.g., ocean circulation and

stratification; Harley et al., 2006; Doney et al., 2012; see also Sections

16.3.2.2-3). Such systems tend to be those that persist at the upper

limit of their climate tolerances (Sheehan et al., 2008; Benito et al., 2011;

Dirnböck et al., 2011); those for which sustainability is closely tied to

vulnerable physical systems (Johannessen and Miles, 2011); or those

that are under significant pressure from non-climatic forces (Jenkins et

al., 2011). For example, many species, including humans (Section 11.8.1)

Box 16-4 | Historical Perspectives on Limits to Adaptation

Does human history provide insights into societal resilience and vulnerability under conditions of environmental change? Archeological

and environmental reconstruction provides useful perspectives on the role of environmental change in cases of signiﬁcant societal

change, sometimes termed “collapse” (Diamond, 2005). These may help to illuminate how adaptation limits were either exceeded, or

where collapse was avoided to a greater or lesser degree. Great care is necessary to avoid oversimplifying cause and effect, or

overemphasizing the role of environmental change, in triggering signiﬁcant societal change, and the societal response itself.

Coincidence does not demonstrate causality, such as in the instance of matching climatic events with social crises through the use of

simple statistical tests (Zhang et al., 2011), or through derivative compilations of historical data (deMenocal, 2001; Thompson et al.,

2002; Drysdale et al., 2006; Butzer, 2012). Application of social theories may not explain speciﬁc cases of human behavior and

community decision making, especially because of the singular importance of the roles of leaders, elites, and ideology (Hunt, 2007;

McAnany and Yoffee, 2010; Butzer, 2012; Butzer and Endﬁeld, 2012).

There are now roughly a dozen case studies of historical societies under stress, from different time ranges and several parts of the

world, that are sufﬁciently detailed (based on ﬁeld, archival, or other primary sources) for relevant analysis (Butzer and Endﬁeld,

2012). These include Medieval Greenland and Iceland (Dugmore et al., 2012; Streeter et al., 2012), Ancient Egypt (Butzer, 2012),

Colonial Cyprus (Harris, 2012), the prehistoric Levant (Rosen and Rivera-Collazo, 2012), Islamic Mesopotamia and Ethiopia (Butzer,

2012), the Classic Maya (Dunning et al., 2012; Luzzadder-Beach et al., 2012), and Colonial Mexico (Endﬁeld, 2012). Seven such

civilizations underwent drastic transformation in the wake of multiple inputs, triggers, and feedbacks, with unpredictable outcomes.

These can be seen to have exceeded adaptation limits. Five other examples showed successful adaptation through the interplay of

environmental, political, and socio-cultural resilience, which responded to multiple stressors (e.g., insecurity, environmental or

economic crises, epidemics, famine). In these cases, climatic perturbations are identiﬁed as only one of many “triggers” of potential

crisis, with preconditions necessary for such triggers to stimulate transformational change. These preconditions include human-

induced environmental decline mainly through overexploitation.

Avoidance of limits to adaptation requires buffering feedbacks that encompass social and environmental resilience. Exceedance of

limits occurred through cascading feedbacks that were characterized by social polarization and conﬂict that ultimately result in societal

disruption. Political simpliﬁcation undermined traditional structures of authority to favor militarism, while breakdown was accompanied

or followed by demographic decline. Although climatic perturbations and environmental degradation did contribute to triggering

many cases of breakdown, the most prominent driver at an early stage was institutional failure, which refers to the inability of societal

institutions to address collective-action problems (Acheson, 2006). In these cases, collapse was neither abrupt nor inevitable, often

playing out over centuries. Lessons from the implementation of adaptation responses over historical time periods in Mexico City

suggest that some responses may create new and even more signiﬁcant risks (Sosa-Rodriguez, 2010).

Recent work on resilience and adaptation synthesizes lessons from extreme event impacts and responses in Australia (Kiem et al.,

2010). This further emphasizes an institutional basis for resilience, ﬁnding that government intervention through the provision of

frameworks to enable adaptation is beneﬁcial. Furthermore, it was found that a strong government role may be necessary to absorb

a portion of the costs associated with natural disasters. On the other hand, community awareness and recognition of novel conditions

were also found to be critical elements of effective responses. It would be useful to consider how lessons learned from historical

experience may relate to the perceived multiple environmental changes characterized by the “Anthropocene” era (Crutzen, 2002).

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Adaptation Opportunities, Constraints, and Limits Chapter 16

nd key food crops (e.g., wheat, maize, and rice; Sections 7.3.2, 11.8.2),

are known to have thermal limits to survival. Similarly, increased ocean

acidity is expected to reduce the ability of some marine organisms such

as corals to grow, posing threats of significant ecosystem damage

(Boxes CC-OA and CC-CR). Nevertheless, defining those limits remains

challenging owing to system complexity and lack of information regarding

responses across different levels of biological organization (Steffen et

al., 2009; Wookey et al., 2009; Lavergne et al., 2010; Preston et al.,

2013a). Furthermore, species have mechanisms for coping with climate

change including phenotypic plasticity (Charmantier et al., 2008;

Matesanz et al., 2010), genetic (evolutionary) responses (Bradshaw and

Holzapfel, 2006; Gienapp et al., 2008; Visser, 2008; Wang et al., 2013),

and range shifts (Colwell et al., 2008; Thomas, 2010; Chen et al., 2011;

see also Section 16.3.2.3). Such mechanisms influence adaptation limits

by extending the range of climate conditions with which individual

organisms can cope in situ and/or enabling species to migrate over time

to more suitable climates. Yet, more comprehensive assessments of such

adaptive mechanisms are needed to develop robust understanding of

ecological limits.

While human systems may also experience hard limits, such systems

are influenced by exogenous climate change as well as endogenous

processes such as societal choices and preferences (Adger et al., 2009).

This creates the potential for limits encountered by actors to be soft.

Although they may limit adaptation for the current planning horizon, they

may be ameliorated in the future by changing circumstances. Various

authors have noted that adaptation limits are socially constructed by

human agency in that economics, technology, infrastructure, laws and

regulations, or broader social and cultural considerations can limit

adaptation (medium evidence; high agreement; Adger et al., 2009; de

Bruin et al., 2009b; Flåm and Skjærseth, 2009; O’Brien, 2009; Wilbanks

and Kates, 2010; McNamara et al., 2011; Morrison and Pickering, 2012;

see also Section 16.3). Cost-benefit analyses and associated discount

rates, for example, reflect a social value on investment returns (Section

17.4.1). Yet, Morgan (2011) notes that adaptation planning based on

cost-benefit analysis can pose limits to adaptation by discounting the

future economic benefits of adaptation actions and excluding non-

market benefits. Meanwhile, increasing loss and damage from societal

exposure and climate change may pose financial limits to the

insurability of disaster risks (Section 10.7.3), which ultimately influences

what activities can occur in certain locations. All of these factors are

dynamic and can change over time. The Shared Socioeconomic Pathways,

which have been designed to facilitate comparison of findings across

modeling teams, reflect different perspectives on future changes in the

capacity of actors to adapt (Kriegler et al., 2012; Ebi et al., 2013;

Schweizer and O’Neill, 2013; van Ruijven et al., 2013). Given rising

incomes and advances in knowledge and technology, a greater number

of adaptation options may become available to a greater number of

actors over time. In contrast, impediments to development, constraints

on investments in adaptation, or rapid escalations in risk may increase

the likelihood of experiencing a limit.

Societal assessments of risk and willingness to invest in risk management

are subject to many influences (Renn, 2008; IPCC, 2012; see also Section

14.5), such as experience of a recent disaster, some of which can result

in rapid changes (Ho et al., 2008; Breakwell, 2010; Renn, 2011). Adger

et al. (2009, p. 338) argue that many limits to adaptation are dependent

n the changing goals, values, risk tolerances, and social choices of

society which make them “mutable, subjective, and socially constructed.”

Similarly, Meze-Hausken (2008) views adaptation as being triggered in

part by subjective thresholds including perceptions of change; choices,

needs, and values; and expectations about the future (see also O’Brien,

2009). For instance, the distribution of grape suitability will change in

response to climate change, but the potential for relocation as an

adaptation is limited by the concept of “terroir,” which reflects biophysical

traits and local knowledge and wine making traditions to a cultural

landscape (Box 23-1). However, terroir could become a soft limit if the

rigid, regionally defined regulatory frameworks and concepts of regional

identity that prescribe what grapes can be grown where were to

become more geographically flexible and tied to the culture and history

of the winemakers rather than regional climate and grape suitability

(Box 23-1).

Limits also have scale-dependent properties (see also Section 16.3.2.10)

(limited evidence, high agreement). Adaptation finance and capacity

building activities more broadly, for example, enable resources for

adaptation to be transferred from a variety of governmental and non-

governmental entities to developing nations in order to overcome soft

limits to adaptation (Section 16.3.2.5). For example, a local community

may not have the necessary resources to adapt, but these constraints

may be overcome by drawing in resources, such as technical expertise,

from regional, national, or international authorities as well as from

NGOs, other civil society organizations, or the private sector (Section

16.3.2.5). Scale dependence also manifests among different actors

within sectoral supply chains. For example, climate change that poses

limits to the sustainability of an individual farm enterprise may have less

impact on a national or international agribusiness (Park et al., 2012).

16.4.2. Limits and Transformational Adaptation

Adaptation has traditionally been viewed as a process of incremental

adjustments to climate variability and change to maintain existing

objectives and values despite changes in climate conditions (Smit et al.,

2001). As evidenced by the examples in Section 16.4.1, however, future

changes in climate could exceed the capacity of human actors and/or

natural systems to successfully adapt using incremental adjustments

(medium evidence, high agreement). Since the AR4, the adaptation and

resilience literature has suggested that climate change or other factors

may drive actors toward the deliberate pursuit of transformational

adaptation as a mechanism for managing the discontinuities associated

with experiencing an adaptation limit (Pelling, 2010; Kates et al., 2012;

O’Brien, 2012; O’Brien et al., 2012; O’Neill and Handmer, 2012; Dow et

al., 2013a,b; see also Section 20.3). In addition, some studies have

discussed the interactions between incremental and transformational

adaptation and the pathways by which actors can transition from one

to the other (Pelling, 2010; Park et al., 2012).

As a relatively new concept in the adaptation literature, clear operational

definitions of what constitutes transformational adaptation remain

elusive. Several authors have offered criteria that include a significant

increase in the magnitude of a management effort; introduction of new

technologies or practices; formation of new structures or systems of

governance; or geographic shifts in the location of activities (Pelling,

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Chapter 16 Adaptation Opportunities, Constraints, and Limits

010; Stafford Smith et al., 2011; Kates et al., 2012; O’Neill and Handmer,

2012; Park et al., 2012; see also Sections 20.1, 20.5). However, the

concept has also been identified as having normative elements involving

changes in desired values, objectives, and perceptions of problems

(Pelling, 2010; O’Neill and Handmer, 2012; O’Brien et al., 2012; Park et

al., 2012). The current complexity and ambiguity in the definition of

transformational adaptation may constrain its effective operationalization

in policy environments (very low confidence). However, this matter has

not been investigated.

In the context of limits to adaptation, transformational adaptation

represents options and strategies that human actors can exploit to

reorganize systems when incremental adaptation has reached its limits.

As with incremental adaptation, these changes can be reactions to what

has been experienced in the past or decisions made in anticipation of

the future (Kates et al., 2012). As a fundamental change in a system,

transformation may involve changes in actors’ objectives and associated

values. Therefore, transformational adaptation is not without risks or

costs (Orlove, 2009; Kates et al., 2012; O’Brien, 2012). For example, the

level of investment needed to relocate a community or economic

enterprise to reduce the risk of system failure (Kates et al., 2012; O’Neill

et al., 2012) and/or to take advantage of changing climatic conditions

(Park et al., 2012) may be quite substantial. Furthermore, transformational

adaptation may be associated with various externalities. Strategies such

as migration, for example, may involve the loss of sense of place and

cultural identity, particularly if migration is involuntary (Adger et al.,

2009). The feasibility of transformational adaptation may therefore be

dependent in part on whether it results in outcomes that are perceived

to be positive versus negative (Preston and Stafford Smith, 2009). This

suggests that the factors that constrain incremental adaptation (e.g.,

Section 16.3.2) also can constrain transformation, but the greater level

of investment and/or shift in fundamental values and expectations

required for transformational change may create greater resistance

(limited evidence, medium agreement; Pelling, 2010; O’Brien, 2012;

O’Neill and Handmer, 2012; Park et al., 2012).

16.5. Sectoral and Regional Synthesis

The adaptation literature since the AR4 indicates that despite a range

of opportunities to enable adaptation, multiple factors will constrain

adaptation planning and implementation (very high confidence; see

Section 16.3), and, in some cases, such constraints may limit adaptation

(medium evidence, high agreement; see Section 16.4). However,

adaptation opportunities, constraints, and limits for adaptation vary

significantly among different sectors and regional contexts (very high

confidence; Adger et al., 2007; see also Sections 16.3-4; Table 16-3). This

heterogeneity arises from a range of sources including regional

differences with respect to the rate and magnitude of climate change

that is experienced, differential exposure and sensitivity of sectors or

ecological systems, and differential capacity to adapt. Given this diversity,

it is important that opportunities, constraints, and limits are evaluated

in the specific context in which they arise. Therefore, this section draws

on the various assessments of adaptation presented in the sectoral

(Chapters 3 to 13) and regional (Chapters 22 to 30) chapters of the

WGII AR5 to synthesize knowledge regarding opportunities, constraints,

and limits across these contexts.

16.5.1. Sectoral Synthesis

Each of the sectoral chapters in the WGII AR5 addresses the opportunities

for, and constraints associated with, the pursuit of adaptation (Table

16-3). Collectively, this represents a rich body of knowledge regarding

how adaptation processes are evolving among different human and

natural systems. Although each sectoral chapter assesses the relevant

literature on adaptation independently, common themes emerge (Table

16-3). Opportunities most often cited include building awareness,

strengthening adaptive capacity, developing tools for improving

vulnerability and risk assessments, and adopting favorable policies to

improve governance. Likewise, common constraints arise among different

sectors, but the bulk of the evidence for adaptation constraints is

focused on inadequate governance and institutional structures at the

scale of the challenge, lack of access to financial resources or relevant

information for adaptation, and social and cultural norms that prevent

adoption of viable adaptation options.

There are a number of emerging, integrated approaches to adaptation

planning, governance, and implementation identified by many sectoral

and regional chapters. For example, Integrated Water Resource

Management (IWRM), Integrated Coastal Zone Management (ICZM),

Community-Based Adaptation, and Ecosystem-Based Adaptation (EBA)

are identified as cross-sectoral adaptation options, which are viewed

as more effective than standalone efforts to reduce climate-related risks

(Bijlsma et al., 1996; see also Sections 5.5.4, 14.3.2; Box CC-EA). Such

integration is important, as many sectors experience threats not only

from climate change, but also from a range of existing or emerging

threats. The sectoral chapters also reflect on the distinction between

autonomous adaptation, which is particularly important for natural

systems such as freshwater, coastal, terrestrial, and ocean ecosystems

(e.g., WGII AR5 Chapters 3 to 6), and planned adaptation, which features

strongly in the literature associated with human-managed systems

(WGII AR5 Chapters 5, 7 to 13).

Though the sectoral chapters offer few explicit definitions of adaptation

limits, they reflect the potential for hard limits to be reached and the

potential for them to be persistent due to interactions among multiple

constraints (Section 16.3.2). For example, the sustainability of individual

species or ecosystems may experience hard limits in a changing climate,

as may ecosystem services for humans such as food crop and fisheries

production. Though significantly more attention is given to sectoral

adaptation opportunities, constraints, and limits than in the AR4, the

AR5 chapters suggest that literature relevant to the coastal (Chapter 5),

food systems (Chapter 7), and urban sectors (Chapter 8) has expanded

more rapidly, perhaps because of the experience within these sectors

with risk reduction planning associated with extreme weather events.

16.5.2. Regional Synthesis

While the regional chapters assess the relevant literature on key sectors

affected by climate change, those discussions are specific to the various

regional contexts (Table 16-3). Mainstreaming adaptation to climate

change into national development policies, regional and local planning,

and economic development has emerged as an opportunity across all

regions for addressing multiple, interacting stresses (Dovers and Hezri,

923

Adaptation Opportunities, Constraints, and Limits Chapter 16

reshwater (3)

ectors (chapter) Opportunities Constraints Limits

Terrestrial (4)

oastal (5)

Ocean systems (6)

Food systems (7)

Urban areas (8)

Rural areas (9)

Human health (11)

Human security (12)

Awareness Capacity Tools Policy Learning Innovation Economic Social/

cultural

Human

capacity

Governance Financial Information Physical Biological Biophysical

Sectors

Africa (22)

Regions (chapter) Opportunities Constraints Limits

Icon legend

Europe (23)

Asia (24)

Australasia (25)

North America (26)

Cental & South

America (27)

Polar regions (28)

Small islands (29)

Open oceans (30)

Regions

pportunities

are deﬁned as factors that make it easier to plan and implement adaptation actions, that expand adaptation options, or that provide ancillary co-beneﬁts. Types of

opportunities include (1) Awareness: communication, education, and awareness raising; (2) Capacity: human and institutional capacity building including preparedness, resource provision,

and development of human and social capital; (3) Tools: decision making, vulnerability and risk analysis, decision support, and early warning tools; (4) Policy: integration and mainstreaming

of policy, governance, and planning processes including sustainable development, resource and infrastructure planning, and design standards; (5) Learning: mutual experiential learning and

knowledge management of climate vulnerability, adaptation options, disaster risk response, monitoring, and evaluation; and (6) Innovation: development and dissemination of new

information, technology development, and technology application.

Constraints are deﬁned as factors that make it harder to plan and implement adaptation actions. Types of constraints include (1) Economic: existing livelihoods, economic structures, and

economic mobility; (2) Social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support; (3) Human capacity:

individual, organizational, and societal capabilities to set and achieve adaptation objectives over time including training, education, and skill development; (4) Governance, Institutions &

Policy: existing laws, regulations, procedural requirements, governance scope, effectiveness, institutional arrangements, adaptive capacity, and absorption capacity; (5) Financial: lack of

ﬁnancial resources; (6) Information/Awareness/Technology: lack of awareness or access to information or technology; (7) Physical: presence of physical barriers; and (8) Biological:

temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind.

A L

imit

is deﬁned as the point at which an actor’s objectives or system’s needs cannot be secured from intolerable risks through adaptive actions. Types of limits include (1) Biophysical:

temperature, precipitation, salinity, acidity, and intensity and frequency of extreme events including storms, drought, and wind; (2) Economic: existing livelihoods, economic structures and

economic mobility; and (3) Social/cultural: social norms, identity, place attachment, beliefs, worldviews, values, awareness, education, social justice, and social support.

Table 16-3 | Sectoral and regional synthesis of adaptation opportunities, constraints, and limits. Each icon represents types of opportunities, constraints, and limits (described below). The size

of the icon represents when there is relatively little (small icon) or relatively ample (large icon) information in the sectoral and regional chapters to describe each type of opportunity, constraint,

or limit. If no information was presented, the table cell is blank.

924

Chapter 16 Adaptation Opportunities, Constraints, and Limits

010; Tompkins et al., 2010; Table 16-3). Most regional chapters reveal

there are significant spatial and temporal mismatches between national

adaptation planning on adaptation and local implementation to achieve

substantive reductions in vulnerability. Adaptation interventions largely

emphasize short-term risk management over long-term transformative

strategic planning to reduce long-term risk, which potentially increases

vulnerability and therefore the costs associated with future adaption

efforts. Such short-sighted decision making can also create the potential

for maladaptation (Barnett and O’Neill, 2010; Berrang-Ford et al., 2011;

Preston et al., 2013b).

Effective governance and institutions for facilitating adaptation planning

and implementation across multiple sectors within regions was by far

the dominant opportunity and constraint. Both a shift to risk-based

approaches to adaptation and to the multi-sector planning for adaptation

mentioned previously (EBA, IRWM, and ICZM) offers opportunities for

the development of approaches, tools, and guidelines for the construction

of adaptation plans at a regional scale with a long-term focus. Developing

and developed nations alike identified opportunities for building adaptive

capacity and access to better information at the scale of decision making

as important to making this happen. Compared with sectoral chapters,

the regional chapters identified limits to adaptation less frequently

(Table 16-3). This reflects the tendency for the literature to focus on limits

for specific sectors, species, or ecosystems.

16.6. Effects of Mitigation on Adaptation

Opportunities, Constraints, and Limits

The AR4 identified four ways in which adaptation and mitigation can

interrelate, one of which is mitigation actions that have consequences

for adaptation (Klein et al., 2007). It follows that mitigation actions

could have consequences for adaptation constraints and limits. Klein et

al. (2007) concluded that without mitigation, a magnitude of climate

change could be reached that makes adaptation impossible for some

natural systems, while for most human systems such high magnitudes

of change would involve very high social and economic costs. Adaptation

onstraints and limits therefore have implications for the definition of

dangerous anthropogenic interference under Article II of the UNFCCC

(UNFCCC, 1992; see also Travis, 2010; Hoegh-Guldberg, 2011; Tao et al.,

2011; Preston et al., 2013a). A number of studies published since the

AR4, for example, demonstrate that constraining future greenhouse gas

emissions would lower the magnitude of climate change experienced

over the 20th century and constrain the magnitude of future adverse

impacts or the likelihood of exceeding system thresholds (very high

confidence; Stern et al., 2006; Preston and Jones, 2008; Sheehan et al.,

2008; Meinshausen et al., 2009; O’Neill et al., 2010; Garnaut, 2011;

Arnell et al., 2011; Rogelj et al., 2011; Webster et al., 2011; see also

discussion of mitigation in the AR5 WGII sectoral and regional chapters).

Therefore, mitigation can potentially reduce the magnitude of climate

change to which human and natural systems must adapt.

Understanding the relationship between damages avoided by mitigation

and adaptation limits requires information regarding what magnitude of

climate change and associated damages would constitute an intolerable

risk. The WGI contribution to AR5 quantifies the cumulative carbon

dioxide (CO

) emissions below which—with probabilities of >33%,

>50%, and >66%—global mean warming would be limited to less than

2°C since the period 1861–1880 (see WGI AR5 Section12.5.4). Warming

beyond 2°C is considered to give rise to “reasons for concern” (Smith

et al., 2009a; see also Section 19.6), in part because adaptation to

impacts associated with such warming would be constrained or limited

(Sections 16.3.2, 16.4.1; Box 16-3). Uncertainty about the location of both

hard and soft limits is due to the fact that these limits are determined

not only by the degree and rate of climate change (as a function of

mitigation pathways), but also by the degree and rate of non-climatic

stresses affecting the resilience or adaptive capacity of natural and

human systems (Section 16.4). Little empirical information is available

on the functional relationships between climate change, non-climatic

stresses, and the emergence of limits to adaptation. The literature

aiming to establish at which degree and rate of climate change, or at

which levels of mitigation, such adaptation constraints and limits emerge

is sparse and refers primarily to natural systems (limited evidence,

medium agreement; Section 16.4).

Frequently Asked Questions

FAQ 16.3 | How does greenhouse gas mitigation inﬂuence

the risk of exceeding adaptation limits?

There is very high conﬁdence that higher rates and/or magnitudes of climate change contribute to higher adaptation

costs and/or the reduced effectiveness of certain adaptation options. For example, increases in global mean

temperature of 4°C or more would necessitate greater investment in adaptation than a temperature increase of

2°C or less. As future climate change is dependent on emissions of greenhouse gases, efforts to mitigate those

emissions can reduce the likelihood that human or natural systems will experience a limit to adaptation. However,

uncertainties regarding how future emissions translate into climate change at global and regional levels remain

signiﬁcant, and therefore it is difﬁcult to draw robust conclusions regarding whether a particular greenhouse gas

stabilization pathway would or would not allow residual risk to be successfully managed through adaptation. For

example, evidence regarding limits to adaptation does not substantiate or refute the idea that an increase in global

mean temperature beyond 2°C represents an adaptation limit or, subsequently, “dangerous anthropogenic

interference” as deﬁned by the UNFCCC’s Article II.

925

Adaptation Opportunities, Constraints, and Limits Chapter 16

evertheless, studies indicating that limits to adaptation have already

been reached for some systems suggest the climate change observed

to date has been sufficient to threaten the sustainability of human

communities, ecosystem services, or ecological systems (limited evidence,

medium agreement; Section 16.4). For many valued human and natural

systems, the complex spatial and temporal dynamics of impacts, adaptive

capacity, and adaptation make it difficult to quantitatively project with

any degree of accuracy and confidence when and where limits to

adaptation will be encountered. Furthermore, although constraints and

limits have been demonstrated to have cross-scale and cross-level

interactions (Sections 16.3.2.10, 16.4.1), there is little evidence that

indicates how limits to adaptation experienced by actors, species, or

ecosystems in individual regions or sectors scale to a global aggregate

limit. Therefore, there is little evidence to either substantiate or refute

the idea that global mean warming beyond 2°C represents a global

adaptation limit.

Analysis by Christensen et al. (2011) (see also WGI AR5 Section 12.4.1)

shows that all emission scenarios—whether aggressive mitigation

scenarios consistent with a 2°C stabilization pathway or medium-high

emission scenarios such as Special Report on Emission Scenarios (SRES)

A1B and A1Fi, or Representative Concentration Pathway 6.0 (RCP6.0)

and RCP8.5—are very similar in terms of projected climate up to 2040

(i.e., the “era of climate responsibility”). The effects of mitigation on

overall adaptation potential will therefore arise in the medium to long

term, during the “era of climate options.” Integrated Assessment

Models (IAMs) can assess the relative damage-reducing effect of

mitigation and adaptation, based on the assumption that the two

strategies are substitutes. In reality, however, mitigation and adaptation

are hardly substitutable: they create benefits on different spatial,

institutional and temporal scales and involve different actors with

different interests. Substitutability of mitigation and adaptation in IAMs

requires the reconciliation of welfare impacts on people living in different

places and at different points in time into an aggregate measure of

well-being (Klein et al., 2007). Moreover, defining the costs and benefits

of adaptation is particularly difficult, limited by data, and depends on

value judgments (Chapter 17).

Since AR4 the literature on tipping elements (Lenton et al., 2008;

Kriegler et al., 2009; Levermann et al., 2012) has provided a greater

separation of mitigation and adaptation, because only mitigation can

avoid these discontinuities. While there could be potential for mitigation

and adaptation substitutability under scenarios where catastrophic

climate change is avoided, the thresholds for the onset of any tipping

elements (anticipated to drive some systems to the limits of adaptation)

are not known. These concerns have been picked up in the economic

literature, in relation to the plausible, if unknown, probability of

catastrophic climate change as well as “fat tails,” where uncertainty is

so large that the tails of the probability distribution tend to dominate

(Weitzman, 2009). Against this background, mitigation can prevent or

delay catastrophic climate change and the reaching of adaptation limits.

Several studies using IAMs have investigated tradeoffs between

mitigation and adaptation (de Bruin et al., 2009a; Bosello et al., 2010),

treating the two strategies as substitutes in order to find a balance or

even an optimal mix. De Bruin et al. (2009a) report that short-term

optimal policies need to consist of a mixture of substantial investments

n adaptation measures, coupled with investments in mitigation, even

though the latter will decrease damages only in the longer term. They

also find that the relative mix of the two depends critically on the

assumptions, notably in relation to discount rate and the parameterization

of damages. Felgenhauer and de Bruin (2009) examine the role that

uncertainty over climate sensitivity has on optimal mitigation and

adaptation policy levels over time. They find that optimal levels of both

mitigation and adaptation are lower under uncertainty than under

certainty, and that the optimal mitigation level is more dependent on

adaptation costs than vice versa.

Such findings are all preliminary, because the current representation of

adaptation in IAMs is generally very simple (Ackerman et al., 2009; Patt

et al., 2010b). The models adopt a highly aggregated and theoretical

approach without considering any real-world constraints on adaptation

(Ackerman et al., 2009; Patt et al., 2010b). They also often assume perfect

foresight, no uncertainty, and no maladaptation (see also Watkiss, 2011;

Berkhout, 2012). More recent models have attempted to address some

of these issues. De Bruin and Dellink (2011), for example, model different

types of constraints of adaptation over time. Also the PAGE09 model

assumes adaptation to be about half as effective as it was in PAGE02

(Hope, 2011). Along with other factors, the reduced effectiveness of

adaptation in the model leads to a strong increase in the economic costs

of climate change (Hope, 2011).

16.7. Ethical Dimensions of Adaptation

Opportunities, Constraints, and Limits

Hartzell-Nichols (2011, p. 690) argues that, in general terms, “Adaptation

is fundamentally an ethical issue because the aim of adaptation is to

protect that which we value.” More specifically, ethical issues concern the

distribution of costs and benefits of prevention measures and adaptation

activities, compensation for residual damages, and participation in

the related decision processes (Grasso, 2009). These distributive and

procedural justice-related issues can be diverse and contextually specific

(Paavola, 2011). Brisley et al. (2012) argue that ensuring social justice

in adaptation requires both an understanding of which groups are most

vulnerable to climate change impacts, as well as social choice processes

about adaptation responses that are seen to meet the needs of the

vulnerable fairly. The key ethical issues raised by adaptation opportunities,

constraints, and limits as they are discussed here are summarized in

Table 16-4, together with the public policy questions they raise.

Defining general moral principles to clarify how to handle risks to

objectives, values, and needs, including where they are unavoidable and

catastrophic, is difficult. According to Gardiner (2006, p. 407), “Even

our best theories face basic and often severe difficulties addressing

basic issues … such as scientific uncertainty, intergenerational equity,

contingent persons, nonhuman animals, and nature. But climate change

involves all of these matters and more.”

Complicating this picture further is the observation that social and

personal values are not universal or static (O’Brien, 2009; O’Brien and

Wolf, 2010). There may be different, but equally legitimate, values that

are fostered or put at risk by climate change (Adger et al., 2012). These

are not limited to instrumental or economic values, but include cultural

926

Chapter 16 Adaptation Opportunities, Constraints, and Limits

values as well. Berkes (2008, p. 163), for instance, documents that in

Inuit culture, the loss of sea ice in summer months leaves some people

“lonely for the ice.” Whether the risk of irreversible cultural losses would

be seen as intolerable remains a complicated question, but has been

noted to manifest in a psychological response termed “solastalgia”

(Albrecht et al., 2007). The loss of traditional ways of experiencing and

seeing the world is a common occurrence throughout human history.

The ethical question is whether such losses should be acknowledged in

considering adaptation opportunities, constraints, and limits (as well as

in human responses to climate change more generally).

One ethical principle that is widely applied in ethical discussions of

climate is “equity” (Gardiner, 2010). It is now well established that

nations, peoples, and ecosystems are differentially vulnerable to current

and future projected climate change impacts, which themselves are

unequally distributed across world regions (very high confidence; IPCC,

2007b; Füssel, 2009, 2010). This inequity is exacerbated by the fact that

exposure to adverse impacts is involuntary for many societies (Paavola

and Adger, 2006; Patz et al., 2007; Dellink et al., 2009; Füssel, 2010).

Thus, adaptation constraints have the potential to create or exacerbate

inequitable consequences due to climate change (very high confidence).

Where limits to adaptation lead to catastrophic losses there is often a

need for humanitarian responses, as well as more structural adaptations

at the societal level (medium evidence, high agreement; Bardsley and

Hugo, 2010). Linked to this is the complex question of the attribution

of risks to anthropogenic forcing of climate change and whether there

could be grounds for redress or compensation (Verheyen, 2005). In this

regard, different ethical positions taken by countries such as through

“equity weighting” would result in very different compensation outcomes

(Anthoff and Tol, 2010).

Inequity resulting from adaptation constraints and limits emerge across

several dimensions: inter-country equity, inter-generational equity, inter-

species equity (Schneider and Lane, 2006b), and intra-country or sub-

national equity (Thomas and Twyman, 2005). Climate change, and the

need for adaptation, unfairly shifts burdens onto future generations,

contradicting the principle of intergenerational equity. This raises ethical

and justice questions because benefits are extracted from the global

environment by those who do not bear the burden of that extraction

(UNEP, 2007). Policy debates about intergenerational equity considerations

have been dominated by the need to treat the time discount rate

consistently across cases (Nordhaus, 2001; Stern et al., 2006; Beckerman

and Hepburn, 2007). But this debate largely ignores the challenge of

irreversible damages associated with limits to adaptation, especially

those that may result from nonlinear damage functions (Hanemann,

2008). Inter-species equity is the subject of an evolving ethics debate (e.g.,

Jolibert et al., 2011), but adaptation interventions involving ecosystems

and wild species increasingly invoke human and societal benefits as a

primary motivation (CBD, 2009; Box CC-EA).

Law codifies the social values and objectives influenced by opportunities,

constraints, and limits to adaptation, and sets norms and procedures

for dealing with problems of risk and loss, including the intolerable

losses experienced at adaptation limits (Section 16.3.2.8). Changing

such values and objectives, including the shifting and sharing of risks

this may involve, will often involve complex and time-consuming

governance effort. National and international law will play a role in

managing and sharing climate-related risks. The Cancun Adaptation

Framework (UNFCCC, 2011) adopted at COP16 of the UNFCCC sets

out principles for international cooperation on adaptation “…to enable

and support the implementation of adaptation actions” (UNFCCC, 2010,

Ethical dimensions Commentary Public policy issues References

Adaptation opportunities

ccess to opportunities Inequitable access to the factors

that make it easier to adapt and

chieve adaptation objectives

hether national or international

policy should support more

quitable access to adaptation

opportunities

homas and Twyman (2005);

Paavola and Adger (2006); Paavola

(

2008); Füssel (2010); Rübbelke

(2011); Klinsky et al. (2012)

Adaptation constraints

istribution of constraints Inequitable distribution of factors

hat make it harder to plan and

implement adaptation actions

hether national or international

olicy should reduce or remove

constraints to adaptation

aavola and Adger (2006); Klein

nd Möhner (2009); Grasso (2010)

Adaptation limits

iffering attitudes to risk What is deemed an acceptable,

tolerable, and intolerable risk will

ary across cultures, social groups,

and individuals.

isk governance is concerned

with balancing differentiated

nd dynamic attitudes to risk in

allocating resources to managing

isks.

isaro et al. (2010); Juhola et al.

(2011); Lata and Nunn (2012);

ovacool (2012); Fatti and Patel

(2013); Ward et al. (2013)

Rights and potentials of people to

secure particular valued objectives

Limits are related to given valued

objectives, but such objectives vary

etween individuals and collectives.

Risk governance related to

adaptation limits is concerned with

etting priorities between different

(and conﬂ icting) valued objectives.

Foale (2008); Devine-Wright (2009);

Gorman-Murray (2010); Jacob et al.

(

2010); Brown et al. (2011); Adger

et al. (2012)

iffering rates at which limits are

reached

imits will be reached earlier by

some groups and regions (Arctic,

nprotected coastal zones) than

others.

isk governance at different scales

will be confronted with choices

bout adaptation limits emerging

through time.

aum and Easterling (2010);

Edvardsson-Bjornberg and Hansson

(

2011); Dow et al. (2013a)

rade-offs in securing valued

objectives

daptive responses will involve

choices between valued objectives

t adaptation limits (i.e., between

river water quality and water

emand from irrigation).

s adaptation limits that affect

multiple valued objectives are

eached, private and public choices

will be made about which values

ave priority over others.

teenberg et al. (2011); Towler et

al. (2012); Pittock (2013); Seidl and

exer (2013)

Intergenerational and interspecies

equity and adaptation limits

Valued objectives may be

irrecoverably lost at adaptation

limits, denying them to future

generations.

Species extinctions and loss of

cultural heritage, place, or identity

may call for extraordinary public

policy interventions.

Albrecht et al. (2013)

Table 16-4 | Ethical dimensions of adaptation opportunities, constraints, and limits and their policy implications.

927

Adaptation Opportunities, Constraints, and Limits Chapter 16

. 4). Nevertheless, the complexity of international law comprises a

significant constraint to making the case for addressing the breaching

of adaptation limits (Koivurova, 2007). At national and subnational

levels, cultural attitudes can contribute to stakeholder marginalization

from adaptation processes (Section 16.3.2.7), thus preventing some

constraints and limits from being identified (such as gender issues and

patriarchal conventions).

16.8. Seizing Opportunities, Overcoming

Constraints, and Avoiding Limits

As discussed in this chapter, researchers and practitioners now have a

richer understanding of how constraints and limits influence adaptation

(Sections 16.3-7). Based on the available literature, however, less

attention has been paid to understanding the range of opportunities that

exist and how they create enabling conditions for adaptation (Section

16.3.1; Table 16-1). Focused research on facilitating such enabling

conditions and how these lead to the minimization or avoidance of

adaptation constraints would support capacity building of individuals

and institutions (very high confidence; Smith et al., 2008; Ford, 2009;

Burch, 2010; Ford et al., 2010; Eisenack, 2012; Biesbroek et al., 2013a).

Translating knowledge of potential opportunities into adaptation

responses requires that they be recognized and then exploited by actors.

Such opportunities are being created through policies, tools, and

guidelines that are emerging throughout the developed and developing

world (Sections 15.2, 16.3.2.1). It is not yet clear if these efforts are

translating into effective adaptation actions for the benefit of human

and natural systems including the avoidance of limits. As adaptation

practice has focused on what adaptation efforts can achieve in terms

of avoided damages rather than on the residual damages that adaptation

cannot avoid (Jenkins et al., 2011; McNamara et al., 2011), this question

remains largely unexplored.

Adaptation constraints have contributed to uneven adaptation planning

and implementation, with some sectoral and regional actors progressing

more rapidly than others (very high confidence; Urwin et al., 2008;

Biesbroek et al., 2010; Tompkins et al., 2010; Bichard and Kazmierczak,

2012; Bierbaum et al., 2012; Carmin et al., 2012). Multiple studies have

concluded that adaptation is largely proceeding autonomously and

incrementally, often in response to perceived climate change trends and

impacts that have been experienced (medium evidence, high agreement;

Ford, 2009; Ford et al., 2010, 2011; Berrang-Ford et al., 2011; Preston

et al., 2011a; Lesnikowski et al., 2013). In so doing, however, actors may

not adequately invest in adaptation responses that will address future

long-term risks associated with higher levels of climate change (limited

evidence, medium agreement; Preston et al., 2013b; see also Section

16.3.2.2). The suggestion that incremental approaches to mitigation

and adaptation may be inadequate to avoid intolerable risks has led to

a growing discourse regarding transformational adaptation (Pelling,

2010; Kates et al., 2012; O’Brien, 2012; O’Neill and Handmer, 2012; Park

et al., 2012). While various practical examples of transformational

adaptation appear in the literature (Kates et al., 2012; O’Neill and

Handmer, 2012; Park et al., 2012; see also Section 16.4.2), the extent

to which transformational adaptation can be operationalized within

adaptation policy remains unclear. Unresolved issues including which

actors, sectors, and regions should be considering transformational

daptations, when, and what constitutes appropriate adaptation actions

under such circumstances would benefit from focused investigation.

Better understanding and quantification of how future GHG emissions

trajectories and climate change translates into impacts would improve

understanding of limits to adaptation. Fundamental understanding of

the vulnerability of different regions and sectors to climate change

suggest that adaptive capacity is finite and thus, in general, limits to

adaptation can be anticipated to arise as a consequence of future global

change (medium evidence, high agreement; Sections 16.3.2, 16.4-6).

Yet, at present, understanding of limits to adaptation is largely qualitative,

and it is unclear whether current approaches to assessing climate change

impacts and adaptation sufficiently explore the range of potential future

climates and adaptive capacities of human and natural systems in a

manner that is sufficient to identify limits. The parallel process for

scenario development may provide a coherent framework for internally

consistent analyses of climate change impacts that address uncertainty

among climate models, emissions scenarios, and socioeconomic scenarios

(Moss et al., 2010; van Vuuren et al., 2012; Ebi et al., 2013). Such

knowledge could subsequently provide early warning of systems at risk of

experiencing intolerable risks (Dow et al., 2013a,b) while also providing

guidance regarding GHG mitigation targets.

Finally, recent literature questions whether existing institutions and

systems of governance are adequate to effectively manage climate

change risk. This includes not only institutions engaging in adaptation

planning and implementation (Berkes and Armitage, 2010; Chapin et al.,

2010; National Research Council, 2010; UKCIP, 2011; Kates et al., 2012;

Biesbroek et al., 2013a), but also those associated with adaptation re-

search (Meyer, 2011; Kates et al., 2012). New institutions and institutional

arrangements have in fact emerged including adaptation research

institutions with boundary spanning functions (Preston et al., 2013c;

see also Section14.2.3), as well as those designed to facilitate adaptation

and improve environmental and risk management (medium evidence,

high agreement; National Research Council, 2009; Biesbroek et al.,

2011; Jäger and Moll, 2011; Lemos et al., 2013). However, others have

cautioned that the complexity of modern governance systems poses

significant constraints on institutional change (Adger et al., 2009; see

also Section 16.3.2.8), and new institutions do not necessarily resolve

complex governance challenges (Lebel et al., 2013). Additional research

is therefore needed regarding the extent to which new institutions will

be required to effectively govern adaptation.

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