899
16
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.
16
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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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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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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
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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 ofC 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
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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
f
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
c
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
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S
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
p
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
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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.
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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.
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Adaptation Opportunities, Constraints, and Limits Chapter 16
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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
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t
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
a
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
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
P
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)
P
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)
E
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)
D
evelopment of human capital Bowen et al. (2012); Lemos et al. (2013)
D
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)
V
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)
C
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
I
ntegrated resource and infrastructure
planning
R
osenberg et al. (2010); Becker et al. (2012); Heeres et al. (2012)
S
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
E
xperience with climate vulnerability and
disaster risk
F
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
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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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a
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
a
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).
1
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
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(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).
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a
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 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
a
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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a
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;
S
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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16
d
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
d
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
16
f
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
b
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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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
w
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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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
E
nhance drought and pest resistance;
enhance yields
B
iotechnology and genetically modifi ed
crops
P
erceived risk to public health and
safety; ecological risks associated with
i
ntroduction of new genetic variants to
n
atural environments
H
owden et al. (2007); Nisbet and
Scheufele (2009); Fedoroff et al. (2010)
Provide fi nancial safety net for farmers
t
o ensure continuation of farming
enterprises
Subsidized drought assistance; crop
i
nsurance
Creates moral hazard and distributional
i
nequalities if not appropriately
administered
Productivity Commission (2009); Pray et
a
l. (2011); Trærup (2011); O’Hara (2012);
Vermeulen et al. (2012)
M
aintain or enhance crop yields;
suppress opportunistic agricultural pests
a
nd invasive species
I
ncreased use of chemical fertilizer and
pesticides
I
ncreased discharge of nutrients and
chemical pollution to the environment;
a
dverse impacts of pesticide use on
n
on-target species; increased emissions
of greenhouse gases; increased human
e
xposure to pollutants
G
regory et al. (2005); Howden et al.
(2007); Boxall et al. (2009)
Biodiversity
Enhance capacity for natural adaptation
a
nd migration to changing climatic
conditions
Migration corridors; expansion of
c
onservation areas
Unknown effi cacy; concerns over
p
roperty rights regarding land
acquisition; governance challenges
Hodgson et al. (2009); West et al. (2009);
K
rosby et al. (2010); Levin and Petersen
(2011)
Enhance regulatory protections for
s
pecies potentially at risk due to climate
and non-climatic changes
Protection of critical habitat for
v
ulnerable species
Addresses secondary rather than primary
p
ressures on species; concerns over
property rights; regulatory barriers to
r
egional economic development
Clark et al. (2008); Ragen et al. (2008);
B
ernanzzani et al. (2012)
Facilitate conservation of valued species
b
y shifting populations to alternative
areas as the climate changes
Assisted migration Diffi cult to predict ultimate success of
a
ssisted migration; possible adverse
impacts on indigenous fl ora and fauna
from introduction of species into new
e
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
16
G
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
16
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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a
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
o
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
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2
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
16
F
reshwater (3)
S
ectors (chapter) Opportunities Constraints Limits
Terrestrial (4)
C
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
O
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 dened as the point at which an actor’s objectives or systems 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.
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Chapter 16 Adaptation Opportunities, Constraints, and Limits
16
2
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
c
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
2
) 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 C represents an adaptation limit or, subsequently, “dangerous anthropogenic
interference” as defined by the UNFCCC’s Article II.
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Adaptation Opportunities, Constraints, and Limits Chapter 16
16
N
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 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
i
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
16
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 termedsolastalgia
(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
A
ccess to opportunities Inequitable access to the factors
that make it easier to adapt and
a
chieve adaptation objectives
W
hether national or international
policy should support more
e
quitable access to adaptation
opportunities
T
homas and Twyman (2005);
Paavola and Adger (2006); Paavola
(
2008); Füssel (2010); Rübbelke
(2011); Klinsky et al. (2012)
Adaptation constraints
D
istribution of constraints Inequitable distribution of factors
t
hat make it harder to plan and
implement adaptation actions
W
hether national or international
p
olicy should reduce or remove
constraints to adaptation
P
aavola and Adger (2006); Klein
a
nd Möhner (2009); Grasso (2010)
Adaptation limits
D
iffering attitudes to risk What is deemed an acceptable,
tolerable, and intolerable risk will
v
ary across cultures, social groups,
and individuals.
R
isk governance is concerned
with balancing differentiated
a
nd dynamic attitudes to risk in
allocating resources to managing
r
isks.
B
isaro et al. (2010); Juhola et al.
(2011); Lata and Nunn (2012);
S
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
b
etween individuals and collectives.
Risk governance related to
adaptation limits is concerned with
s
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)
D
iffering rates at which limits are
reached
L
imits will be reached earlier by
some groups and regions (Arctic,
u
nprotected coastal zones) than
others.
R
isk governance at different scales
will be confronted with choices
a
bout adaptation limits emerging
through time.
B
aum and Easterling (2010);
Edvardsson-Bjornberg and Hansson
(
2011); Dow et al. (2013a)
T
rade-offs in securing valued
objectives
A
daptive responses will involve
choices between valued objectives
a
t adaptation limits (i.e., between
river water quality and water
d
emand from irrigation).
A
s adaptation limits that affect
multiple valued objectives are
r
eached, private and public choices
will be made about which values
h
ave priority over others.
S
teenberg et al. (2011); Towler et
al. (2012); Pittock (2013); Seidl and
L
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
16
p
. 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
a
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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