cultural barriers to climate change adaptation a case study from northern burkina faso

• DOI: 10.1016/J.GLOENVCHA.2009.10.002
• Corpus ID: 154667178

Cultural barriers to climate change adaptation: A case study from Northern Burkina Faso

• J. Nielsen , A. Reenberg
• Published 1 February 2010
• Environmental Science, Sociology, Geography
• Global Environmental Change-human and Policy Dimensions

417 Citations

The role of culture in adaptive responses to climate and environmental change in a fijian village, climate change response at the farm level: a review of farmers’ awareness and adaptation strategies in developing countries, framing the application of adaptation pathways for rural livelihoods and global change in eastern indonesian islands, sociocultural dimension in agriculture adaptation to climate change, the role of gender and caste in climate adaptation strategies in nepal, effects of socio-cultural norms on smallholder adaptation to climate change in nkoranza south municipality, ghana.

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Adaptation to climate change as a development project: A case study from Northern Burkina Faso

Cultural values and climate change economic valuation of ecosystem services exemplary transdisciplinary projects, cultural dimension and adaptation to floods in a coastal settlement and a savannah community in ghana, 68 references, roots in the african dust, farmer adaptation, change and ‘crisis’ in the sahel, adapting to environmental change in artisanal fisheries—insights from a south indian lagoon, increasing the resilience of hillside communities in bolivia, temporality and the problem with singling out climate as a current driver of change in a small west african village, institutional adaptation to climate change: flood responses at the municipal level in norway, migration in west africa: a savanna village prespective, planning for climate change in small islands: insights from national hurricane preparedness in the cayman islands, the african sahel 25 years after the great drought: assessing progress and moving towards new agendas and approaches, the scramble in africa: reorienting rural livelihoods, related papers.

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Cultural barriers to climate change adaptation: A case study from Northern Burkina Faso

• Nielsen, Jonas Østergaard
• Reenberg, Anette

Human adaptation to climate change is a heterogeneous process influenced by more than economic and technological development. It is increasingly acknowledged in the adaptation to climate change literature that factors such as class, gender and culture play a large role when adaptation strategies are either chosen or rejected at the local scale. This paper explores adaptation strategies by focusing on livelihood diversification in the face of the most recent of recurrent droughts in the Sahel. It is shown that for Fulbe, one of the two main ethnic groups in the small village in Northern Burkina Faso studied, culture acts as a major barrier to embracing four of the most successful livelihood strategies: labour migration, working for development projects, gardening, and the engagement of women in economic activities.

• Climate change;
• Adaptation;
• Cultural barriers;

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• Proc Natl Acad Sci U S A
• v.107(51); 2010 Dec 21

A framework to diagnose barriers to climate change adaptation

Susanne c. moser.

a Susanne Moser Research and Consulting, Santa Cruz, CA 95060;

b Institute for Marine Sciences, University of California, Santa Cruz, CA 95064; and

Julia A. Ekstrom

c Climate and Energy Policy Institute, University of California, Berkeley, CA 94705

Author contributions: S.C.M. designed research; S.C.M. and J.A.E. performed research; and S.C.M. and J.A.E. wrote the paper.

Associated Data

This article presents a systematic framework to identify barriers that may impede the process of adaptation to climate change. The framework targets the process of planned adaptation and focuses on potentially challenging but malleable barriers. Three key sets of components create the architecture for the framework. First, a staged depiction of an idealized, rational approach to adaptation decision-making makes up the process component. Second, a set of interconnected structural elements includes the actors, the larger context in which they function (e.g., governance), and the object on which they act (the system of concern that is exposed to climate change). At each of these stages, we ask ( i ) what could impede the adaptation process and ( ii ) how do the actors, context, and system of concern contribute to the barrier. To facilitate the identification of barriers, we provide a series of diagnostic questions. Third, the framework is completed by a simple matrix to help locate points of intervention to overcome a given barrier. It provides a systematic starting point for answering critical questions about how to support climate change adaptation at all levels of decision-making.

In the first decade of the 21st century, adaptation to climate change has risen sharply as a topic of scientific inquiry, in local to international policy and planning, in the media, and in public awareness ( 1 – 3 ). Adaptation researchers have generally assumed lower vulnerability and greater adaptive capacity in developed countries than in developing countries and thus have focused more research in the latter ( 1 , 4 ). Yet climatic events in Europe, the United States, and Australia in recent years have also led to critical questioning of richer nations’ ability to adapt to climate change ( 3 , 5 , 6 ).

The examination of developed nations’ adaptive capacity, and the persistent “adaptation deficit” in developing nations ( 7 ), has led to focused research on barriers and limits to adaptation. This research develops a systematic framework to identify barriers to adaptation, which impact society's ability to deal with climate change impacts, an area of growing interest in the past few years ( 6 , 8 – 13 ). Our primary goal is to advance the discussion and examination of these barriers by presenting a systematic framework to identify and organize barriers that can arise in the adaptation process in different contexts. Systematically identifying barriers to adaptation can serve to advance our understanding of the process and assist in decision-making. As such, we aim to be comprehensive but do not assume every real-world process will touch on all steps or barriers.

Defining Adaptation

Adaptation has a long and multidisciplinary history of investigation. As a result, meanings of the term differ by field and in practice ( 14 ). For the purposes of this article, we select a generic, but inclusive, definition reflecting common usage in the climate change field. We deviate from the Intergovernmental Panel on Climate Change (IPCC) definition of adaptation in recognizing that adaptation must consider, but may not be justified by, climate change alone and may be initiated or undertaken in the context of nonclimatic windows of opportunity (e.g., land-use plan updates, infrastructure replacement, renovating a building). The IPCC definition also implicitly assumes effectiveness in outcome that we believe is premature. Whether harm will be moderated and beneficial opportunities exploited is contingent on many factors, not just on the adaptive action itself. Some adaptive actions may turn out maladaptive later. Finally, the IPCC distinguishes natural and human systems whereas we are most interested in social-ecological systems. Thus, we define adaption as follows:

Adaptation involves changes in social-ecological systems in response to actual and expected impacts of climate change in the context of interacting nonclimatic changes. Adaptation strategies and actions can range from short-term coping to longer-term, deeper transformations, aim to meet more than climate change goals alone, and may or may not succeed in moderating harm or exploiting beneficial opportunities.

Our primary focus here is on the intentional , planned adaptation process without presuming a particular set of actors, level of planning, or involvement of government; rather, we attempt to account for the complexity of a deliberate and more involved process. We are also not a priori normative about what the right scale or scope of adaptation should be, i.e., assuming that actions taken in pursuit of shorter-term and maybe shallower goals are necessarily less worthy. Success in the near term may well turn out to be maladaptive in the long run, and vice versa. We do suggest, however, that choosing a particular scope and scale of adaptation has significant implications for the number and types of barriers activated and encountered by choosing different adaptation actions or pathways. System transformations will require different and likely more challenging barriers to be overcome than planning or implementing immediate measures to cope with a climate-driven disaster ( Fig. 1 ).

Scope and scale of adaptation to climate change [based on an extensive literature review (ref. 14 , especially refs. 15 – 18 )].

Defining Barriers to Adaptation

Researchers often use the concepts of barriers and limits together, even interchangeably, whereas others distinguish between them. Here, as is consistent with the IPCC ( 1 ), we refer to limits as obstacles that tend to be absolute in a real sense: they constitute thresholds beyond which existing activities, land uses, ecosystems, species, sustenance, or system states cannot be maintained, not even in a modified fashion ( 19 – 21 ). Beyond such limits looms irreversible loss (and the adjustment to living with that loss) and/or radical system shifts, including innovation and novelty ( 22 , 23 ). Limits are common in physical and ecological systems in their natural state, but, in some instances, physical and ecological limits have been stretched or overcome with technological innovations (e.g., genetic modification of crops to increase heat tolerance). Those seeming limits that can be overcome, we would view as barriers.

Barriers are defined here as obstacles that can be overcome with concerted effort, creative management, change of thinking, prioritization, and related shifts in resources, land uses, institutions, etc. As Adger et al. ( 8 ) argue, many seeming limits, especially social ones, are in fact malleable barriers; they can be overcome with sufficient political will, social support, resources, and effort. However, many barriers will make adaptation less efficient or less effective or may require costly changes that lead to missed opportunities or higher costs. In many instances, the barrier may appear as de facto limits (e.g., a law). Not questioning the changeability of such barriers (however difficult to overcome) may itself be an obstacle to progressing in the adaptation process.

Importantly, we take a descriptive rather than a normative approach in which barriers are simply impediments that can stop, delay, or divert the adaptation process. Overcoming all barriers does not necessarily lead to a successful outcome (however defined and by whom). Thus, a hypothetical smooth, barrier-free process is not a sufficient condition to guarantee adaptation success. In turn, not even the best-run process should be expected to be free of barriers, and its outcomes may still require adjustments in the next iteration. However, ignoring certain best practices throughout the process (such as effective stakeholder involvement, consensus or broad agreement if and when it is required, adequate information, considering both biophysical and social dimensions of the problem, or adequate funding) could lead to maladaptation.

Given the pervasive influence of climate change and the many climate-sensitive systems and decisions that will be made in regard to it, a diagnostic framework that is applicable to a wide range of adaptation cases must be principled but not overly confining. The “architecture” of our framework is guided by four principles. It aims to be ( i ) socially focused but ecologically constrained; ( ii ) actor-centric but context-aware; ( iii ) process-focused but action/outcome-oriented; and ( iv ) iterative and messy but linear for convenience ( 14 ).

Three key components underlie the diagnostic framework. First, an idealized depiction of a rational approach to adaptation decision-making makes up the process component. Second, a set of interconnected structural elements include the actors, the larger context in which they act (e.g., governance), and the object on which they act (the system of concern that is exposed to climate change). Third, to overcome identified barriers, a simple matrix helps map the source of the barrier relative to the actor's influence over it.

Process of Adaptation.

The process of adaptation provides the foundation for identifying and organizing the barriers. We use common phases of a rational decision-making process, including understanding the problem, planning adaptation actions, and managing the implementation of the selected option(s). Each of these process phases includes a series of stages (for a total of nine stages) ( Fig. 2 ). We systematically identify potential barriers in each stage. The barriers may impede progress from one stage to another or—if stages and the issues that arise in each are skipped (as can be the case in real-world decision-making)—result in problems or unintended consequences later. Understanding involves the stages of ( i ) problem detection and awareness raising (resulting in an initial problem framing); ( ii ) information gathering and use to deepen problem understanding; and ( iii ) problem (re)definition (resulting in a framing that does or does not warrant further attention to the issue). Planning involves ( iv ) development of adaptation options; ( v ) assessment of options; and ( vi ) selection of option(s). Finally, the management phase involves ( vii ) implementation of the selected option(s); ( viii ) monitoring the environment and outcome of the realized option(s); and ( ix ) evaluation. Monitoring and evaluation stages are critical to an adaptive management approach because they help support institutional and social learning ( 24 ), which is commonly considered necessary to deal with complex and uncertain problems ( 25 ). The decision process typically is less linear and neat in practice. Several authors convincingly show ( 26 – 28 ) how reality typically differs from such ideal normative models of decision-making. For the purposes here, however, the process stages provide a useful ordering heuristic.

Phases and subprocesses throughout the adaptation process.

Structural Elements of Adaptation.

To understand why a given barrier arises in the adaptation process, we build on a framework proposed for the analysis of social-ecological systems ( 29 , 30 ). We consider three interconnected pieces of the puzzle: the actors (not a static but often wide-ranging and dynamic set over time), the larger context in which they act, and the object upon which they act (i.e., the specific coupled human–natural system to be managed or altered). For example, we are interested not just in a coastal waterfront (the system of concern) that has to be better managed in light of sea-level rise. Rather, we also consider how the actors themselves who manage that waterfront have to change (e.g., their perceptions of or thinking about the environment, use of information, decisions, and interactions with other levels of government). In turn, they may only make these changes if the governance context in which they act also changes (e.g., shaping what is legal or politically feasible, which decision protocols to use, or the timing of certain opportunities to make changes in budgeting, planning, or infrastructure replacement schedules). Finally, the greater context in which both the actor and the system of interest are embedded provides the enabling and constraining contextual conditions that shape adaptive actions ( Fig. 3 ). Barriers may arise from all three components. Sample diagnostic questions are provided in Table S1 to identify how each structural component contributes to the occurrence of a barrier.

The structural elements of the diagnostic framework: interacting actors, the governance and larger socio-economic context, and the system of concern that is to be managed for climate change.

What can stop, delay, or divert the adaptation decision-making process? This question, applied to every stage in the process, identifies the stage-specific barriers. The structural model establishes the source of the barriers by asking: What causes the impediments? How do the actors, context, and the system of concern contribute to the barriers? We discuss the third step of the framework after the initial diagnosis as it addresses how to overcome the barriers.

Identifying Barriers Throughout the Adaptation Process.

Based on our reading of the adaptation literature, certain barriers are repeatedly encountered during the Understanding phase. We have organized them in Table 1 according to the stages in which they arise.

Common barriers in the stages of the Understanding phase

Although the system of concern may produce signals of change, the actors, governance system, and larger context affect whether they are noticed and how they are interpreted. In terms of detecting the problem (the first stage of the Understanding phase), the existence of the signal may not be detected if, for example, the actor's mental model filters out the signal, if the individual is too busy or distracted to notice it or if the actor is too distant from the signal to take note. In turn, the governance system or media may fail to transmit a signal or prevent it from reaching individuals. A study on the needs of coastal managers revealed that a lack of high-level leadership and guidance (governance) can undermine the capacity and willingness to make adaptation decisions ( 31 ). Transmission could also fail because of the absence of social or professional networks or because of the presence of dysfunctional ones ( 32 – 34 ). Similarly, the nature of the system of concern and its interaction with climate change may involve so much uncertainty or variability that a signal does not clearly emerge from the background noise.

In the same way, other barriers can arise from one or all three sources in our framework. If the actors do not reach a minimum threshold of concern over the detected issue or do not see a need for, or a feasible, response (at least in principle), the adaptation process will not enter stage ii . (Alternatively, if actors have a solution in search of a problem, as is often the case in practical decision-making ( 28 ), the climate problem must have registered sufficiently on the actors’ radar to fit the bill.) Actors may not proceed carefully through each of the subsequent stages (and thus encounter the associated barriers), but those who do may encounter the barriers listed in Table 1 . Systematic discussion of each barrier, its sources, and examples from the published literature are provided in Ekstrom, Moser, and Torn ( 14 ).

In the rational decision-making model, actors next go through the adaptation planning phase. Research on existing adaptation processes reveals that they commonly encounter the barriers listed in Table 2 .

Common barriers in the stages of the Planning phase

In an ideal-case process, the initial stage of the Planning phase produces a larger set of potential options that are then assessed according to agreed-upon criteria and goals; one or several options that meet the goals and are deemed feasible are selected in the end. During the first stage in this phase, where adaptation options are being brainstormed and developed, leadership, authority, and skill to guide the process can be critical. Actor(s) may focus their deliberations only on options they perceive to be under their control or may be open to generating options beyond their immediate control ( 32 , 35 , 36 ). The inability to identify and agree upon goals and criteria can become a significant barrier at this point. A survey of U.S. government officials showed that >55% of respondents indicated the challenge of defining adaptation goals as very to extremely challenging ( 37 ). Because the brainstorm is rarely cleanly separated from the careful evaluation, many of the barriers identified in the option development stage reemerge, as do those encountered in stage ii (information gathering) given the potential reliance on science, information, and existing knowledge to assess options.

Barriers in the Planning phase that arise from traits of the governance system often have to do with who has control over the process. For example, if a nongovernmental organization and a government agency (both focused on public health) are developing adaptation plans, their respective options will likely differ because of these organizations’ different missions, jurisdictions, political interests, funding, etc. ( 38 ). The system of concern has its own influence on the range of options. For example, to be effective, the level of intervention and the boundary of the system of concern may inherently limit the range of options ( 39 ). If the system of concern extends across multiple jurisdictions, the problem requires coordination and collaboration across jurisdictions to implement options. Failing to develop such cross-level relationships may result in barriers in the Planning and Management phases ( 36 , 40 ).

Whether or not actors have proceeded through a sequential process of generating, assessing, and selecting options [and overcoming the associated barriers ( Table S1 )], once an option has been selected, the process moves into the Management phase. Table 3 lists common barriers encountered in that phase.

Common barriers in the stages of the Managing phase

Research on climate adaptation to date suggests that few adaptation processes have reached this phase ( 1 , 9 , 15 , 37 , 41 ), partly because the barriers before and in the implementation stage are so significant and partly because climate change adaptation has emerged as a concern only recently. Thus, we draw more heavily on experience with other management and change processes.

The first stage here, implementation, can involve multiple subprocesses, often many different actors (including some not involved in the process so far), and require varying amounts of time, resources, skills, and effort to fully accomplish. Actors critically influence whether and how a selected option is implemented. The actual intent to implement is a first barrier ( 42 , 43 ). Grothmann and Patt ( 10 ) found farmers in Zimbabwe hesitant or even resistant to take adaptive actions because they had not learned how to correctly interpret climate-related probabilities and they preferred to plant (and eat) maize over millet (the proposed strategy for drought years). The same is often true in bigger interventions. Further, actors must have gathered and aligned knowledge, skill, and financial resources. As the “policy windows” literature has found repeatedly, preparations must be made before the opening of a policy window to be able to take advantage of it when it opens ( 44 ).

Moving from option selection to implementation also is influenced in important ways by the governance and larger social context, in part through its impact on the actor's perception, freedom, and capacity to do so, in part through its impact on the available resources, authorization, permits, political climate, or social norms. For example, implementation of an option must be legal and feasible within existing policies, laws, rules, regulations, programs, and mandates unless the selected strategy is to change a law or process. For example, hardening shorelines to protect them against the encroaching sea may not be permissible under existing law. Past practices of the implementer can present another powerful barrier. The nature of the system of concern also plays a significant role in that it will be physically changed in the course of implementation. Flexible and/or robust strategies may garner easier political will or behavioral intent than strategies that may have big or irreversible consequences ( 40 ). For example, building a dam or massive levee system may require a higher degree of public acceptance and stakeholder support and confidence in the science for implementation than those strategies that are more easily reversed.

For adaptive management, mechanisms have to be put in place to allow monitoring and periodic evaluation of the changing environment and the outcomes of the implemented option. A range of barriers have arisen in the past in various adaptive management experiments ( 45 , 46 ). Lack of (agreement on) indicators, relevant data, methods, and expertise can undermine assessing outcomes and success as well as involve varying degrees of reception (i.e., legitimacy and credibility) by decision-makers and their constituents. The diagnostic questions in Table S1 suggest the actor-, context-, and system-specific reasons why this step so often is not taken.

Crosscutting Issues.

Research on climate change adaptation suggests that some barriers appear to be of repeated and cross-cutting importance throughout the process. We describe each of these briefly below but suggest that more systematic empirical research must be undertaken to verify our observations.

Leadership can be critical at any stage in the adaptation process but maybe most important in initiating the process and sustaining momentum over time. When there is no mandate, law, job description, or public demand yet for adaptation planning, leaders are required to initiate the process. Importantly, we do not restrict this function to formal leadership and certainly not to just one individual, because some adaptation processes will go on for a long period; rather, we view it as a role that can be taken on by individuals in any position. Leadership can help overcome barriers, but lack of or ineffective leadership can also create some.

Leaders vary in the quality of guidance, motivation, and vision they provide. Those who demonstrate high skill levels (e.g., in communication, facilitation, and elicitation) and strong qualities of integrity (e.g., dedication and openness to the issue, the process and the solution options, self-reflexivity, humility, creativity, transparency, honesty) tend to be trusted more by participants and perceived as legitimate ( 47 , 48 ).

Resources also prove to be important in almost every stage, but certainly in the science-heavy planning and management (especially implementation and monitoring) phases of adaptation. Resources include financial means but also technical/information resources, technology, staff expertise, and time. Inadequate resources are often the first response practitioners give when asked why they have not yet begun adaptation planning ( 31 , 49 ).

Throughout the adaptation process, communication and information —about the problem, solutions, and their implications—are perpetually needed aspects of the adaptation process. A growing body of literature highlights the importance of effective communication of climate change information to increase awareness and understanding, provide continuity, and constructively engage policy-makers, stakeholders, and the public ( 50 – 55 ). Information-related barriers have to do with whether, which, and how information is created, how it is communicated, and who delivers and receives it. Misunderstood information, unintended interpretation of conveyed information, complete lack or insufficient frequency or content of communication can severely interrupt or derail social interactions among those involved in the adaptation process ( 56 – 58 ).

Finally, there is the issue of deeply held values and beliefs that influence how people perceive, interpret, and think about risks and their management, what information and knowledge they value, what concerns have standing and so on—in short, a foundational influence on the decisions and choices made during the adaptation process. Individuals look at new problems, tasks, and solutions through the lens of their preexisting values, preferences, beliefs, norms, and experiences. In northern Burkina Faso, different cultural values allowed one and prevented another cultural group from adopting new livelihood strategies to reduce vulnerability to climate change ( 12 ). As research in risk perception, cognitive psychology, and people's values and beliefs suggests, this “cultural” lens colors our general beliefs about society and the environment ( 51 , 59 ). In addition, certain heuristics, mental shortcuts, lead to the tendency to underestimate risks arising from climate change ( 60 – 63 ). Cognitive filters shape our perceptions, constrain our attitudes about options (and others involved in the process), and influence our decision-making processes ( 11 , 38 ). For example, Blennow and Persson ( 64 ) found that the strength of belief in climate change was a crucial factor for explaining differences in adaptation actions among Swedish forest owners. Ideologies based on the dominating pattern of values thus can act as barriers or drivers to the process ( 59 ).

These crosscutting issues take on specific “flavors” in each stage, and context features may make them rise to greater or lesser significance, yet there is probably not a single case of adaptation to date where they have not posed significant barriers to the process.

Overcoming Barriers: Scales of Influence.

The third and final step in our diagnostic framework provides a simple matrix to help locate possible points of intervention to overcome a given barrier. Although we do not view overcoming barriers as a normative “must,” actors involved in the adaptation process may be interested in overcoming them. In fact, we hypothesize that working through barriers, rather than skipping entire phases of the decision process, may prove beneficial for the decision outcome. At any rate, an actor's ability to overcome a barrier depends not just on his or her capabilities but also on the source or origin of the barrier. The spatial/jurisdictional and temporal origins of the barrier relative to the location of the actor are important. The temporal dimension includes contemporary versus legacy barriers, and along the spatial/jurisdictional dimensions (which sometimes coincide, other times differ in scale), proximate versus remote barriers.

Each barrier varies along both dimensions ( Fig. 4 ), and, although there may be overlap between legacy/remote barriers and contemporary/proximate barriers, respectively, they are not necessarily identical. For example, a local official may want to find scientific information on vulnerability but cannot locate any relevant research to her community. The fact that federal agencies in years past have not provided funding to conduct such research has created a barrier that is a legacy of past science-policy decisions by remote actors (D in Fig. 4 ). The local official cannot easily overcome this barrier by addressing it at its source (i.e., through changes in federal research and development funding) and closer to home only with significant resources, time, and expertise (i.e., by hiring someone to do this research). By contrast, a barrier that is both proximate and contemporary (A in Fig. 4 ) is one over which the actor has direct control here and now. For example, the official finds that not all participants are at the table that should be and decides to extend invitations to those additional people for the next meeting. The same official may find that a local law prevents taking a certain adaptation action—a proximate legacy barrier (C in Fig. 4 ). Although the situation is still challenging, she has control over initiating changes in this regulation. She may also be faced with a remote contemporary barrier, i.e., one that occurs now but is beyond the official's direct control (B in Fig. 4 ). For example, a budget crisis results in an agency, charged with providing technical assistance to the local process, now having insufficient staff to do so.

Opportunities for influence and intervention to overcome barriers.

The purpose of our diagnostic framework is to systematize the identification of barriers that may impede the adaptation process. In Results , we answered two fundamental questions: ( i ) what could thwart the process and ( ii ) how do the actor, context, and the system of concern contribute to the barrier. We also noted how the sources of these barriers vary across temporal and spatial/jurisdictional scales, and thus identified the locus of control over them.

Together, the nature of the barrier, its source, and the location of influence over the barrier provide a “road map” to design strategies to circumvent, remove, or lower the barriers. Leadership, strategic thinking, resourcefulness, creativity, collaboration, and effective communication will all be required in overcoming them. Frequently, this effort of overcoming barriers is in fact the primary target and focus of the initial adaptation effort ( 3 , 37 ).

As adaptation initiatives progress, accruing experience may reveal that understanding adaptation and its associated barriers will not lead to a fixed prescription for how to adapt or to a one-size-fits-all way to overcome barriers. Rather, we expect feasible strategies to be highly context-sensitive (i.e., actor-, governance-, and system-specific), which is why a systematic diagnostic framework may be more useful than a prescriptive list of necessary conditions, capacities, or steps to overcome barriers. We do, however, suggest that the generalized call for “building adaptive capacity” may be too simplistic an answer to deal with the range of adaptation barriers. Although the list we developed here may be viewed as an elaboration on the inverse qualities of adaptive capacity, overcoming barriers is not as straightforward as building adaptive capacity. To truly understand the relevance of, say, “more resources” is to ask when these resources are needed, by whom, and for what aspects of the adaptation process. Differently put, more resources just for science but not for implementation or for monitoring does not result in a greater likelihood of adaptation actions being implemented on the ground. Thus, one question for future research is whether “performance” at each of the stages could become a more useful and tangible measure of adaptive capacity. Different dimensions of adaptive capacity may also partially compensate for each other. For example, a good leader may be able to compensate to some extent for inadequate time and money because she has great connections or can facilitate potentially difficult processes efficiently and find creative financing solutions without additional resources. Future research must explore the range of pathways actors have found to overcome the specific adaptation barriers they encountered.

Conclusions

In this article, we have introduced a framework for identifying and organizing barriers to adaptation. Rather than propose a normative approach to making “good” adaptation decisions, we offer a comprehensive, systematic approach to detecting barriers in each stage of an idealized adaptation process, along with diagnostic questions that help ascertain how actors, context, and the system of concern contribute to the existence of the barriers.

Our diagnostic framework requires testing and refinement if it is to aid decision-making. For example, the framework could be used as a foundation to examine whether and how barriers differ by the type of system of concern, sector, scale of governance, problem definition, and the depth of the adaptation or transformation sought. Patterns may emerge from such comparative investigations showing where the biggest barriers lie.

A refined ability to identify where the most challenging barriers might lie affords the opportunity to better allocate resources and strategically design processes to overcome them. Similarly, we may learn much about adaptive capacity and ultimate adaptation success by exploring the implications of actors’ skipping certain stages—and the associated barriers—in real-world decision-making. Thus, the framework presented here provides a starting point for answering critical questions that can ultimately inform and benefit climate change adaptation at all levels of decision-making.

Supplementary Material

Acknowledgments.

We thank Margaret Torn for comments on a longer version of this paper, Oran Young and two anonymous reviewers for criticism of an earlier draft of this paper, and the California Energy Commission for financial support (to J.A.E.) through CEC Contract 500-07-043.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1007887107/-/DCSupplemental .

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Climate Change, Health Risks, and Vulnerabilities in Burkina Faso: A Qualitative Study on the Perceptions of National Policymakers

Affiliations.

• 1 Heidelberg Institute of Global Health (HIGH), Heidelberg University Hospital, Heidelberg University, Im Neuenheimer Feld 324, 69120 Heidelberg, Germany.
• 2 Heidelberg Center for the Environment (HCE), Heidelberg University, Im Neuenheimer Feld 404, 69120 Heidelberg, Germany.
• PMID: 34067050
• PMCID: PMC8125418
• DOI: 10.3390/ijerph18094972

Climate change (CC) constitutes one of the greatest threats to human health, and requires political awareness for effective and efficient adaptation planning. This study identified the perceptions of climate change and health adaptation (CC&H) among relevant stakeholders, decision-makers, and policymakers (SDPs) in Burkina Faso (BF) by determining their perceptions of CC, of related health risks and vulnerabilities, and of CC impacts on agriculture and food security. We carried out 35 semi-structured, qualitative in-depth interviews with SDPs, representing national governmental institutions, international organizations, and civil society organizations. The interviews were analyzed using content analysis. SDPs shared similar perceptions of CC and concurred with three ideas (1) CC is a real and lived experience in BF; (2) the population is aware of climatic changes in their environment; (3) CC is intertwined with the agricultural and economic development of the country. SDPs identified biodiversity loss, floods, droughts, and extreme heat as posing the highest risk to health. They elaborated five exposure pathways that are and will be affected by CC: water quality and quantity, heat stress, food supply and safety, vector borne diseases, and air quality. In conclusion, SDPs in Burkina Faso are highly aware of CC hazards, relevant health exposure pathways, and their corresponding health outcomes. Mental health and the interplay between social factors and complex health risks constitute perception gaps. SDPs perceived CC&H risks and vulnerabilities align with current evidence.

Keywords: West Africa; adaptation; agriculture; climate change; food security; health; policymakers.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Composition of the participant sample.

Illustrates how SDPs perceive the…

Illustrates how SDPs perceive the overlap between CC events and health exposure pathways…

Illustrates and compares results of…

Illustrates and compares results of SDPs’ perceptions (Section 3.1) and published literature (Section…

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Cultural barriers to climate change adaptation: A case study from Northern Burkina Faso

2010, Global Environmental Change

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Climate Change, Gendered Vulnerabilities and Adaptation Strategies: A Participatory Research in West Africa

• First Online: 28 August 2024

Cite this chapter

• Balikisu Osman   ORCID: orcid.org/0000-0002-8935-2875 4 &
• Ayansina Ayanlade   ORCID: orcid.org/0000-0001-5419-5980 5 , 6  

This study examines gender-related vulnerability and adaptation responses among rural farmers in the West African region. A comparative analysis was performed relating to sensitivities, perceptions of climate change impacts, and adaptation methods used by smallholder farmers in Ghana and Nigeria. The study sites are located in the foremost agricultural zone in both Nigeria and Ghana. Mixed methods and multi-disciplinary approaches were used in this study. Climate change impacts and multi-risk were assessed using a multiplying vulnerability indices approach by employing both quantitative and qualitative data from questionnaires and focused group discussion (FGD) in both study countries. Over 70% confirmed that temperatures are increasingly rising in all the study sites, while nearly 80% agreed that drought/dryness is becoming common. The results further show that women are much more vulnerable to climate change than men, and female farmers are less likely to adopt climate resilience practices than their male counterparts due to variations in their access to the asset. The study concludes that the overall social impacts of climate change in West Africa are overwhelming among rural farmers, but there is gender variation in terms of vulnerability and risk.

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Acknowledgements

Ayansina Ayanlade received financial support from the Tertiary Education Trust Fund, TETFund NRF 2020 Nigeria (GrantAward -TETF/DR&D-CE/NRF2020/CC/17/VOL.1). This work was supported through a project on ecological economics, commons governance, and climate justice based at York University in Canada (qesclimatejustice.info.yorku.ca), with funding from the Canadian Queen Elizabeth II Diamond Jubilee Scholarships Advanced Scholars Program (QES-AS), supported by the Social Sciences and Humanities Research Council of Canada and the International Development Research Centre.

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Osman, B., Ayanlade, A. (2024). Climate Change, Gendered Vulnerabilities and Adaptation Strategies: A Participatory Research in West Africa. In: Mishra, M., de Lucena, A.J., Maharaj, B. (eds) Climate Change and Regional Socio-Economic Systems in the Global South. Springer, Singapore. https://doi.org/10.1007/978-981-97-3870-0_11

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Burkina Faso’s National Adaptation Plan: A Long-Term Planning Effort

In 2012, Burkina Faso launched a comprehensive effort to develop a National Adaptation Plan (NAP). This case study explores Burkina Faso’s national process to formulate a medium- and long-term strategy for climate change adaptation, which in turn enabled the development of climate projections for Burkina Faso for 2021, 2050, and 2100, as well as the assessment of different sectors’ vulnerability to climate change. It made Burkina Faso one of the first five Least Developed Countries (LDCs) to have a NAP.

The formation of Burkina Faso’s NAP is a good practice because it is an appropriate framework enabling the joining of efforts to help the country reduce its structural vulnerability, increase its resilience, and better manage its socioeconomic and cultural development. It was developed through a consultative process mobilizing actors at different levels and is based on sectoral plans developed from analyses performed with actors from each sector. The vision held by the NAP also has a merit of seeking to promote the integration of climate change adaptation into development goals.

Key findings from the case study include:

• The participative and inclusive nature of the process helped ensure the relevance of adaptation strategies in different sectors.
• The monitoring and evaluation mechanism must be made effective by setting up data collection systems through agreements between institutions.
• Adaptation must not be approached in an isolated manner but should always be intersectoral.
• A greater availability of financial resources for the implementation, monitoring, and evaluation of NAPs, as well as their development, will be essential.

Further Information

Rigobert Bayala, National Observatory for the Environment and Sustainable Development (Burkina Faso)

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• Open access
• Published: 26 August 2024

Progress and gaps in climate change adaptation in coastal cities across the globe

• Mia Wannewitz   ORCID: orcid.org/0000-0003-1769-9877 1 ,
• Idowu Ajibade 2 ,
• Katharine J. Mach   ORCID: orcid.org/0000-0002-5591-8148 3 , 4 ,
• Alexandre Magnan 5 , 6 , 7 ,
• Jan Petzold   ORCID: orcid.org/0000-0003-0508-3362 1 ,
• Diana Reckien   ORCID: orcid.org/0000-0002-1145-9509 8 ,
• Nicola Ulibarri   ORCID: orcid.org/0000-0001-6238-9056 9 ,
• Armen Agopian 3 , 4 ,
• Vasiliki I. Chalastani 10 ,
• Tom Hawxwell   ORCID: orcid.org/0000-0003-1073-983X 11 ,
• Lam T. M. Huynh   ORCID: orcid.org/0000-0002-2801-8240 12 ,
• Christine J. Kirchhoff   ORCID: orcid.org/0000-0002-2686-6764 13 ,
• Rebecca Miller 14 , 15 ,
• Justice Issah Musah-Surugu 16 ,
• Gabriela Nagle Alverio   ORCID: orcid.org/0000-0001-7050-3381 17 ,
• Miriam Nielsen   ORCID: orcid.org/0000-0003-0037-294X 18 ,
• Abraham Marshall Nunbogu 19 ,
• Brian Pentz 20 ,
• Andrea Reimuth   ORCID: orcid.org/0000-0001-9347-849X 1 ,
• Giulia Scarpa 21 ,
• Nadia Seeteram   ORCID: orcid.org/0000-0002-2266-7573 22 ,
• Ivan Villaverde Canosa   ORCID: orcid.org/0000-0002-9344-6452 23 ,
• Jingyao Zhou   ORCID: orcid.org/0009-0004-6882-6797 1 ,
• The Global Adaptation Mapping Initiative Team &
• Matthias Garschagen   ORCID: orcid.org/0000-0001-9492-4463 1  

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• Climate-change adaptation

Coastal cities are at the frontlines of climate change impacts, resulting in an urgent need for substantial adaptation. To understand whether, and to what extent, cities are on track to prepare for climate risks, this paper systematically assesses the academic literature to evaluate evidence on climate change adaptation in 199 coastal cities worldwide. Results show that adaptation in coastal cities is rather slow, of narrow scope and not transformative. Adaptation measures are predominantly designed based on past and current—rather than future—patterns in hazards, exposure and vulnerability. City governments, particularly in high-income countries, are more likely to implement institutional and infrastructural responses, whereas coastal cities in lower-middle-income countries often rely on households to implement behavioral adaptation. There is comparatively little published knowledge on coastal urban adaptation in low- and middle-income countries, and regarding particular adaptation types such as ecosystem-based adaptation. These insights make an important contribution for tracking adaptation progress globally and help to identify entry points for improving adaptation of coastal cities in the future.

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Status of global coastal adaptation

Developing countries can adapt to climate change effectively using nature-based solutions

Quality of urban climate adaptation plans over time

Coastal cities are engines of economic growth and innovation, yet they are also hotspots of disasters and climate risk 1 , 2 , 3 . These cities face increasing environmental changes such as record-breaking sea-surface temperatures 4 and in turn an increase in hazards such as tropical cyclones, floods, storms, erosion and heatwaves 5 , 6 , 7 . Such changes dynamically interact with urban vulnerabilities driven by, for example, inequality, poverty and inadequate infrastructure 8 . Yet, coastal urban risk is not uniform, as climate change impacts and risks vary across coastal cities depending on geomorphological conditions, climatic and human drivers of coastal change, urban development, and other factors 6 , 9 , 10 . In the face of future increases in urbanization and climate change impacts, coastal cities are under pressure to adapt to, and reduce, current and future risks to ensure sustainable and equitable urban development 11 , 12 . As centers of economic activities and key players in the global political economy with substantial capacities, coastal cities have the potential to shape and advance the future of climate adaptation in meaningful and innovative ways 13 . Although the need for transformative adaptation in coastal cities—that is, adaptation that changes the fundamental attributes of a social-ecological system in anticipation of climate change and its impacts 14 —has been stressed in principle 2 , 15 , little is known about the actual progress of adaptation in coastal cities across the globe.

Given the unique challenges and opportunities in coastal cities as hotspots of risk and centers of economic activity, we argue that assessing their current state of adaptation is important, not least as a knowledge base for tracking countries’ progress in climate action within the Global Stocktake under the Paris Agreement 16 . Understanding how coastal cities are responding to climate impacts is crucial for identifying successes and gaps, and for advancing adaptation efforts at large. Studies have assessed different types of urban adaptation, for example, institutional 17 or ecosystem-based 18 , certain actor types involved in urban adaptation (for example, ref. 20 ), urban adaptation in particular regions (for example, refs. 19 , 21 , 22 , 23 ) or coastal adaptation planning 24 , 25 . However, a systematic global assessment of the literature on empirical evidence for implemented coastal urban adaptation—including its response types, actors and level of transformation—does not yet exist. Such an assessment is particularly relevant in the face of the latest Intergovernmental Panel on Climate Change’s (IPCC) report’s finding that coastal cities tend to implement adaptation interventions reactively in response to high-impact events such as floods and storms 26 , and that many gaps remain in urban adaptation to climate change induced hazards across regions 13 .

This study therefore aims to provide a global analysis of empirical evidence of adaptation in coastal cities, including gaps and shortcomings. It also aims to inform policy and practice to advance effective adaptation strategies in response to current and projected climate impacts. To address these objectives, the study is guided by four questions that also serve to structure the results section: (1) How is evidence for coastal urban adaptation spread across the globe? (2) Which hazards and trends of exposure and vulnerability are reported? (3) Which actors are reported to be involved in which types of responses? And (4) what is the speed, scope and depth of reported coastal urban adaptation?

By answering these four questions, this study extends earlier assessments of the state of adaptation more generally 27 by systematically analyzing the empirical evidence of coastal urban responses to climate change, as published in the peer-reviewed academic literature. We assessed the state of adaptation in coastal cities as reported between 2013 and 2020, and examine major patterns in relation to average income levels and city size. Coastal cities here are defined as urban areas with central functions such as markets, medical services and schools; they are of relative importance to the surrounding area, regardless of population size; and are located entirely or partly on the coastline or within the low-elevation coastal zone (LECZ), or within the influence of coastal or tidal hydrology. Our sample covers adaptation activities in 199 cities reported in 683 articles, of which 183 were qualitatively coded using a questionnaire composed of 30 questions (see Methods for details). Our analysis is hence limited to what is being reported in the scientific literature and might include some hard-to-quantify biases that need to be addressed through additional datasets in the future, for example, by covering documents published by civil society actors on adaptation in coastal cities in the Global South where, according to our analysis, fewer studies are available than for higher-income countries. However, we argue that our approach and analysis nevertheless can provide highly relevant insights not only on urban adaptation research but also on the patterns of actual adaptation activities as adaptation research has been expanding massively, now capturing a wide spectrum of activities on the ground. Studies such as these therefore provide an increasingly important knowledge base for tracking adaptation activities 27 .

Evidence for coastal urban adaptation across the globe

The considered literature covers adaptation evidence from coastal cities in all regions and income groups, yet with some considerable differences (Fig. 1 ; see Supplementary Data 1.1 for a detailed list of countries covered in the sample). Most publications present evidence for adaptation from coastal cities in Asia (30%), followed by North America (23%), Europe (16%) and Africa (13%). Compared with the global share of inhabitants living in the LECZ between 0 m and 10 m above sea level 28 , 29 , some regions are overrepresented. This is most evident for North America, Australasia and small island states, which are home to 5%, 0.6% and 0.5% of the global population in the LECZ, respectively, yet, in our sample of coastal urban adaptation evidence, they represent 23%, 11% and 3% of assessed coastal cities. Other regions are underrepresented, which is most evident for Asia given its high number of inhabitants in the LECZ. Although inhabiting 75% of the global population in the LECZ, only 31% of our assessed urban coastal adaptation evidence stems from this region.

Green shading represents the country’s income classification according to the World Bank 82 ; the size and color of the dots visualizes the location of the covered coastal cities and their population size (Supplementary Data 3 ); the most covered coastal cities are listed according to frequency at the bottom right. Map source: Natural Earth 85 .

Source data

The majority of adaptation in coastal cities is reported in high-income economies (56%), which is in stark contrast to the fact that only 16% of the population located in the LECZ live in such economies. Of the reported coastal cities, 19% and 24% of the population are in upper- and lower-middle-income economies, respectively. Given that upper- and lower-middle-income countries account for 34% and 43% of the global population in the LECZ 28 , 29 , respectively, the coastal cities in these income groups are substantially underrepresented in our sample, meaning in the academic literature. Only 1% of the reported activities represent coastal cities in low-income economies (for example, Maputo, Beira and Inhambane in Mozambique). Given that the global population share of people who live in the low-income LECZ is about 8%, they are also underrepresented in our sample.

In terms of the coverage of different sizes of coastal cities (Supplementary Data 1.2 ), the assessed literature mostly presents evidence for adaptation in coastal cities with fewer than 250,000 inhabitants (48% of the reported cases). This pattern can partly be explained by our definition of coastal cities on the basis of their central functions, rather than population thresholds. Evidence for adaptation from mid-sized coastal cities with 250,000–1,000,000 inhabitants is less well-covered in our sample (the examples are mainly in North America and Europe). Thirty-five percent of the reported adaptation happens in coastal cities with >1,000,000 inhabitants, with a majority of cases in Africa and Asia. Some megacities (that is, cities with more than ten million inhabitants) such as New York, Jakarta, Manila and Lagos are covered by multiple studies (see Fig. 1 ). Most empirical evidence for adaptation in coastal megacities stems from Asia (57%), which aligns with the fact that 15 out of 20 coastal megacities are located in Asia 30 , and also with Asia's high overall population share in the LECZ (75%) 28 , 29 .

Hazards and trends of exposure and vulnerability

In terms of hazards, the adaptation activities reported in the sample predominantly address sea-level rise, different types of flooding and, to a lesser extent, storm surges, cyclones and erosion (see Fig. 2 ). A majority of the assessed cases (65%) considers more than one hazard. Such consideration of multiple hazards is most evident for the combination of sea-level rise with storm surges, coastal and pluvial flooding, as well as coastal erosion. This finding suggests that multi-hazard considerations nowadays play a strong role in urban climate risk assessments, in line with what the conceptual literature would be calling for 6 , 10 .

Risk emerges from the interplay of hazards, exposure and vulnerability 14 . The figure displays the number of cities considering past and current patterns (orange bars), and future trends (blue and green bars) for different hazards (top), as well as the exposure and vulnerability of people and businesses, buildings and infrastructure, and environmental assets (bottom).

Studies predominantly consider past and current events with regards to hazard timescales and scenarios (Fig. 2 ). Studies often consider future hazard trends in principle but not in a quantified manner. Although modeled trends and scenarios are quite frequently used as a basis for adaptation to sea-level rise, flooding and storm surges, they are much less common for other hazards.

The picture is even more striking regarding how other risk factors—notably the exposure and vulnerability of people and assets in coastal cities—are considered. In the vast majority of coastal cities, reported adaptation considers only past and current patterns, with the population being the most important element considered, followed by particularly vulnerable groups, residential buildings and the coastline (Fig. 2 ). In scenarios in which future trends in exposed and vulnerable assets are considered, they are accounted for in a general or conceptual way, but not in terms of quantified scenarios. Across our sample, the consideration of the presented elements at risk correlates weakly with a country’s income level. The higher the income group, the more likely that exposure and vulnerability aspects are considered (Supplementary Data 1.3 ).

Responses and actors

Most of the reported adaptation in coastal cities can be categorized as technological/infrastructural and behavioral/cultural adaptation (Fig. 3 ). But combinations of these two, as well as of technological and institutional responses, were also frequently reported. Ecosystem-based responses are the least reported across all world regions, particularly in low-, lower-middle and upper-middle-income countries.

Response types are grouped (on the basis of work by Berrang-Ford et al. 27 ) into technological (that is, enabling, implementing or undertaking technological innovation or infrastructural development), behavioral or cultural (enabling, implementing or undertaking lifestyle and/or behavioral change), institutional (enhancing multi-level governance or institutional capabilities) or ecosystem-based (enhancing, protecting or promoting ecosystem services for adaptation) categories.

The prominence of different response and actor types varies across country and income groups (Fig. 3 ), as well as city size. Most cases reporting technological or infrastructural responses are from coastal cities in high-income countries. The coverage of institutional responses shows a similar pattern. A correlation analysis confirms that the higher the gross national income (GNI) per capita, the more likely that institutional adaptation (Spearman’s ρ  = 0.23, P  < 0.01) and less likely that behavioral adaptation (Spearman’s ρ  = −0.35, P  < 0.01) is mentioned (Supplementary Data 1.4 ). Institutional responses are mostly reported to be implemented by state actors, especially city governments (Supplementary Data 1.5 ), which are the most commonly mentioned actor type across our sample. Correlation analysis reveals that the higher the GNI per capita, the more likely that the city government is assessed as an actor in adaptation (Spearman’s ρ  = 0.30, P  < 0.01), and the less likely that individuals/households are mentioned (Spearman’s ρ  = −0.23, P  < 0.01) (Supplementary Data 1.6 ). Our analyses also reveal that the bigger a city, the less likely that individual/household adaptation is mentioned (Spearman’s ρ  = −0.30, P  < 0.01) and the more likely that a city government is assessed as an actor involved in adaptation (Spearman’s ρ  = 0.20, P  < 0.01) (Supplementary Data 1.6 ).

Reported behavioral or cultural responses are most likely to be assessed together with individuals or households as implementing actors (Supplementary Data 1.7 ). This response type dominates the reported adaptation evidence in coastal cities in lower-middle-income countries. Accordingly, individuals/households are mostly reported as adaptation actors here, whereas state actors such as city and sub-city governments are less frequently assessed as implementers. In contrast to this, we find a low involvement of individuals in low-income economies; however, the very small number of cases in the low-income category needs to be considered here.

Although the assessed literature mostly presents adaptation evidence implemented by one type of actor (in our sample, mostly city governments followed by individuals/households), there is also reported evidence for multiple actors involved in urban adaptation. In many cases, individuals/households and city governments are mentioned together. Furthermore, combinations of city and national governments, or a combination of the two with the sub-city local government, are reported more frequently than other combinations (Supplementary Data 1.8 ).

Looking at adaptation types across regions (Fig. 3 and Supplementary Data 1.7 ), behavioral adaptation is less likely to be reported in North American coastal cities ( ϕ coefficient = −0.21, P  < 0.01) and coastal cities in Central and South America, but more likely to be reported in coastal cities in Africa and Asia. For the last two, we find less evidence for institutional and ecosystem-based adaptation; these adaptation categories are more likely to be assessed in European and North American coastal cities. Evidence for technological adaptation is most likely to be assessed in European coastal cities; research on institutional adaptation evidence features most highly in North and South America.

Speed, scope and depth of adaptation

Transformative adaptation can be assessed along the dimensions of depth (how deep institutional, and other changes, are), speed (how fast adaptation is planned and implemented) and scope (with which geographical and sectoral breadth adaptation happens) 27 , 31 . Overall, we find that reported adaptation remains at rather low depth, scope and speed in coastal cities, across all income groups and regions, with little evidence of reduced risks due to adaptation (Fig. 4 ). Neither income level nor population size predicts more or less transformative adaptation (Supplementary Data 1.9 ).

The depth, speed and scope of adaptation are dimensions of transformative adaptation 27 , 31 . Displayed numbers represent the share of studies evaluated to report low, medium or high levels of depth, speed and scope of adaptation within different country groups in terms of average income according to the World Bank 82 .

Few examples of urban adaptation with deeper changes (that is, entirely new practices that involve deep structural reform, a fundamental change in mindset, major shifts in perceptions or values, and/or changing institutional or behavioral norms) stem from cities in high-income economies or small island states. Given the small number of cases featuring such fundamental forms of adaptation, we provide an aggregated overview of specific studies below.

Some cases reported self- or state-led resettlement 32 , 33 to adapt to climate change impacts in coastal cities. In cities such as Singapore and Hong Kong 34 , and several Swedish cities 35 , existing infrastructural measures are complemented by preparedness and recovery measures, as well as ecosystem-based approaches. Progress in the institutionalization and mainstreaming of basin-wide planning, the integration of adaptation into mitigation and development planning, and the establishment of legislation to reinforce adaptation in sectors such as construction, are considered as evidence of more transformative adaptation in coastal cities. We also identified evidence for medium adaptation depth across countries with different income levels, where the assessed responses reflect a shift away from existing practices, norms or structures to some extent. In coastal cities located in high-income countries in Europe, such as Rotterdam, Dordrecht and Helsinki, medium-depth adaptation is linked to the testing of innovative, design-oriented adaptation approaches, the development of collaborative governance approaches, and public–private partnerships for improving funding and innovation 36 , 37 , 38 , 39 , 40 . In smaller US coastal cities such as Dunedin and Fernandina Beach, changes towards cross-sectoral, comprehensive and more integrative risk management plans 41 , 42 were described. Bigger US cities such as New York and Miami Beach are implementing both large-scale infrastructure investments for flood protection 43 , 44 , 45 and planning, and/or complementary adaptation measures such as ecosystem-based and soft adaptation approaches 43 , 46 .

In Asian coastal cities in lower- and upper-middle-income countries, medium-depth adaptation includes changes in adaptive behavior of individuals and households (for example, changes in livelihoods or migration 33 , 47 , 48 , 49 , 50 ), as well as institutional-scale adaptations (for example, the establishment of new institutions responsible for adaptive planning, disaster risk reduction planning at various scales, or mainstreaming climate change policies in other sectors 51 , 52 , 53 ). The only case with evidence of medium-depth adaptation in a low-income country is Maputo, Mozambique, which has mainstreamed climate change adaptation into its development plans, attributed clear responsibilities for addressing climate change impacts, and started participatory urban planning processes 54 .

For the majority of coastal cities covered in our sample, adaptation remains at low depth across income groups and regions, meaning that evidence for adaptation largely represents expansions of existing practices, with minimal change in underlying values, assumptions or norms. Examples are a continuous focus on traditional infrastructural measures to avoid flooding 55 , 56 , continued uptake of flood insurance 57 , or incremental adaptation in the form of reactive coping due to limited capacities 58 , 59 .

The scope of responses in our sample is mostly narrow, across both income groups and regions, meaning that evidence for coastal urban adaptation measures is largely localized and fragmented, with limited evidence of coordination or mainstreaming across sectors, jurisdictions or levels of governance.

The speed of coastal urban adaptation is mostly considered slow—especially in high-, upper-middle- and lower-middle-income countries, and a majority of regions. This means that adaptations are incremental, consisting of small steps and slow implementation.

Given that depth, scope and speed of adaptation were evaluated as rather low across our sample, it is not surprising that there is little evidence for risk being reduced through these measures. Although we identified some cases that present evidence for risks being overcome through, for example, ecosystem-based 60 , 61 and technological/infrastructural adaptation 45 , 62 , some are linked to negative side-effects or lacking long-term perspectives 63 or even represent maladaptation 56 , 64 , 65 .

Based on the analysis of adaptation in coastal cities reported in the academic literature, we highlight five key findings and close by discussing their implications for research and policy-making in the field of coastal urban adaptation to climate change.

First, our assessment shows that the knowledge and coverage of adaptation in coastal cities is highly uneven, with some coastal cities receiving a lot of scientific attention, and large gaps remaining. For example, small and mid-sized coastal cities in Africa, Asia and Central and South America are currently not part of the global scientific debate, despite the fact that more adaptation might be happening on the ground, reported in other types of documents such as white papers or NGO reports. In our assessment based on the peer-reviewed and mostly English-language academic literature, coastal cities in low-, lower-middle and upper-middle-income countries are underrepresented. Given that cities in Africa, Asia, and Central and South America are expected to experience a highly dynamic interplay of urbanization, highly vulnerable informal settlements and future climate change impacts (see page 7 of ref. 66 ), this is a considerable gap in research that needs to be addressed urgently. Researchers and funding agencies should therefore make a dedicated push towards increasing the evidence-base, specifically in this segment of cities. Furthermore, other data sources such as non-peer-reviewed reports and other grey literature need to be assessed in the future to complement the evidence provided in the peer-reviewed scientific literature.

Second, we generally found that hazards, exposure and vulnerability are considered on the basis of past and current events and conditions. The use of future climate scenarios or other quantitative assessments taking into account future hazard trends remains scarce, and the picture is even more troublesome in terms of the future trends of exposure and vulnerability. Most reported adaptation is not based on a thorough consideration—let alone quantified scenarios—of future developments in the exposure and vulnerability of at-risk people, infrastructure, ecosystems and other assets. This leads to skewed assumptions on future risk, jeopardizing the relevance and validity of knowledge for adaptation planning. Although this finding confirms earlier observations with respect to the low consideration of future exposure and vulnerability trends in National Adaptation Plans 67 and cities 24 , it is nevertheless striking given the high importance of dynamic changes in these domains for changing future risk in coastal cities, for example, through further coastal urbanization or ongoing socio-economic marginalization 6 , 8 .

Third, we find that the lower the income group of the country the coastal cities are located in, the more likely individuals/households are reported as prime adaptation actors. At the same time, government responses and planned adaptation are more often reported in coastal cities in wealthier countries. This suggests that residents with limited resources in poorer coastal cities have to carry most of the adaptation burden 68 , which is often met with behavioral changes due to the lack of institutional and/or technological support. These results corroborate other studies regarding the inequality in the urban adaptation gap (see pages 34 of ref. 66 and page 941 of ref. 26 ), which is most pronounced among the poor.

Fourth, the bigger a city, the more likely that technological responses and protection are assessed. This relationship was also found in other studies 69 . At the same time, there is a lack of reported empirical evidence on ecosystem-based adaptation. Technology-based measures such as flood-barriers or pumping installations are essential protective mechanisms in the short- and mid-term, for example, for storm water management. However, they can lead to a lock-in and maladaptive path dependency in the long-term if coastal hazards continue to rise and hard protection fails or reaches limits of financial and technical feasibility as well as cultural acceptance 70 , 71 . More research on alternative and complementary adaptation measures is therefore needed to guide mixed approaches in the future.

Fifth, our findings suggest urgent needs for transformative adaptation in coastal cities. Across all regions and income groups, scientifically reported adaptation in coastal cities remains at rather low depth, scope and speed. Neither income level nor population size predicted more or less progressive adaptation behavior. Given the high exposure and vulnerability of many coastal cities already today, this finding is alarming as adaptation to future climate change will require many cities to go beyond business as usual risk management to effectively manage and reduce the accelerating risks and vulnerabilities 2 , 15 , 72 . This finding affirms other assessments of urban adaptation 26 and stresses the persistent need for transformative adaptation in coastal cities. It is possible that the cumulative effects of incremental responses could, over time, lead to meaningful and even transformative adaptation; however, the speed and amount of change needed to mitigate current and future risks, could mean that incremental adaptation is tantamount to playing 'catch-up' as climate impacts accelerate.

The extreme changes in the oceans and coasts seen in the recent past, with, for example, new temperature records 4 , 73 , 74 and low sea-ice extent 75 , highlights the scale and speed of adaptation that will be needed. Yet, taking the scientifically reported adaptation evidence as a proxy for the state of adaptation in coastal cities, our findings suggest that adaptation in coastal cities is rather slow, narrow, and fragmented (in other words, non-transformative) in an environment that is transforming rapidly. At the same time, our findings point towards an increasing range of adaptation activities in coastal cities. This evidence mapping can help to point researchers to blind spots in adaptation research in coastal cities and it provides entry points for improving urban adaptation planning.

We followed the ROSES protocol 76 to produce a systematic map of evidence for climate change adaptation in coastal cities (Supplementary Table 1 ). We base our findings on the combination of a systematic review of scientific literature on coastal urban adaptation to climate change across three reference databases (see Extended Data Fig. 1 , which follows the ROSES flow diagram for systematic reviews 77 ) with a content analysis based on a coding protocol, following the Global Adaptation Mapping Initiative (GAMI) process.

Relevant peer-reviewed, scientific, English-language literature on the topic of coastal urban adaptation was identified in a four-tiered search process.

Literature search and data extraction

Publications of the category 'cities and settlements by the sea' were extracted from the GAMI database—a systematic dataset comprising over 1,600 articles on climate adaptation. After a preliminary overview of the 361 resulting publications, further searches through the reference databases Web of Science and Scopus, and discussions among the co-authors (most of whom are well-acquainted with the literature in this particular field), it was decided that the GAMI selection did not adequately represent the large pool of existing literature on coastal urban adaptation. Hence, in a second step, a search string (in English) based on boolean search terms was used to systematically search Web of Science (Core Collection) and Scopus for relevant peer-reviewed, scientific literature over the years 2013 to 2020. The period stretches from the end of the IPCC’s fifth assessment cycle to the cut-off date for considering scientific literature of the sixth assessment cycle. With this we extended the original GAMI search by one year; we did not include 2021 and 2022 due to the coding time-frame. Although the basis of the search string was adopted from the GAMI process 78 , 79 , it was extended by tailored search terms to yield more topic-relevant publications. The search strings and respective hits can be found in Supplementary Information 1 . In a final step, the results of all three searches were combined and duplicates were removed.

We are aware that systematic searches such as this are subject to limitations. Our approach neither considered grey literature such as reports, nor did it use non-English search strings, and thus it is predominately built on English-language publications, which might have led to biases in the results. We nonetheless decided to use this approach to take steps towards a global stocktake of adaptation in coastal cities on the basis of scientific, peer-reviewed literature, using it as a first indication for the state of knowledge on coastal urban adaptation, and as a proxy for understanding where coastal cities currently stand in adapting to climate change. From the perspective of the authors, the added value in these respects outweigh the limitations of the study.

A total of 683 scientific publications entered the screening process, in which the coders assessed whether a publication should be included in the analysis. Overall, only peer-reviewed publications were considered, which excludes conference contributions (further inclusion/exclusion criteria are listed in Supplementary Information 1 ). A total of 501 publications were excluded because they did not meet the inclusion criteria. Six publications were not available in English language, and two were either not accessible or not found. Requests to the authors for access were unanswered. See Supplementary Table 2 for an overview of all included, excluded and not found or accessible publications.

The included publications were analyzed via a systematic content analysis. The publications were distributed among coders considering their interests and capacities, ensuring that no coder analyzed their own publications. Using the online survey platform SoSci Survey Version 3.5.01, coders completed one coding questionnaire per city covered in the manuscript. This means that for one publication, several questionnaires could have been completed in the case that it dealt with two or more cities. In total, 183 publications (Supplementary Table 2 ) covering 284 cases from 199 cities and/or settlements with central functions such as schools, supermarkets and medical services were included in the coding and statistical analysis, as well as four unspecified urban areas. The literature database (Supplementary Table 2 ) and the coding database (Supplementary Data 2 ) can be found as supplements.

Data quality

We ensured coder consistency and reliability through an introduction to the commonly developed questionnaire; a code book/protocol with detailed definitions of all codes (Supplementary Information 1 ); a pre-coding period with interim meetings to discuss issues and confusions; and multiple other meetings with all of the coders involved. The coding included, among others, the following categories: hazard type; exposure and vulnerability; actor type; response type; and, as indicators for transformational adaptation, the depth, speed and scope of adaptation (see Supplementary Information 1 for the full list of codes and variables). About 10% of the entire dataset (that is, 72 publications) was double-coded to check inter-coder reliability. Conflicts regarding inclusion/exclusion arose to 12.8%. Of the 16 fully double-coded publications, inter-coder variability rose to a maximum of 22.2%, meaning a convergence in roughly 80% of provided answers, which was accepted as sufficient to consider the dataset as robust. The data, in the form of codes, were extracted from the ScoSci Survey platform, cleaned and statistically analyzed in IBM SPSS Statistics 23, following the original GAMI approach 78 , 80 , 81 . Coders provided their level of confidence (low, medium, high) to evaluate the depth, speed and scope of adaptation; the final analysis only considered medium- and high-confidence judgements to increase the robustness of the findings.

Data analysis

To obtain an overview of the dataset, descriptive statistical analyses were performed to assess the frequency and proportion of all variables. To identify potential patterns, frequencies were assessed across the World Bank income economies categories (hereafter income groups) 82 and also across regions following the classification used in ref. 27 . Moreover, we used different correlation tests to explore potential relationships that two variables, GNI per capita 83 and city size (in terms of population, Supplementary Data 3 ), have with patterns of actor involvement, adaptation type and depth, and the speed and scope of adaptation. We are aware that income indicators and the urban population size are by far not the only factors influencing adaptation in complex socio-ecological systems 84 ; however, they provide valuable, globally available and comparable starting points for not only describing, but also explaining, emerging patterns of urban coastal adaptation. Hence, our objective was to evaluate the existence of any relationship between these two variables (GNI per capita and city size) with our assessed variables. The Spearman’s rank correlation was employed to ascertain the relationship between GNI per capita and city size with actor involvement. The correlation coefficient ranges between −1 and 1, indicating negative and positive correlations, respectively. The significance of the correlation coefficient is examined by the t -test, which assesses the null hypothesis that there is no monotonic relationship between the two variables. The null hypothesis is rejected if the P -value is less than 0.05. The relationship between adaptation actors and response categories was determined using the χ 2 test, which is a common statistical method for measuring the association between binary variables. The strength and direction of the association are represented by the ϕ coefficient. This coefficient, like the Spearman correlation, ranges from −1 to 1, with values close to −1 indicating a strong negative association, values close to 1 indicating a strong positive association, and values close to 0 indicating a weak or no association. The significance of the ϕ coefficient is also examined using a P -value.

To conduct a cross-sectional comparison of population data in the LECZ across different regions, we utilized “The Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3” dataset 28 . Within this dataset, we specifically selected the population data from “Gridded Population of the World, Version 4 (GPWv4), Revision 11” and the elevation data from 'CoastalDEM90' as core datasets, due to their particular applicability in global-scale and coastal analyses. The analysis provides data about the share of residents living in the LECZ globally in the considered income economies and regions, which is used to understand the relative coverage of adaptation evidence reported in our sample.

The assessment of transformational adaptation in coastal cities builds on the coders’ qualitative evaluation of the three dimensions of transformation 31 ; that is, depth, speed and scope (definitions of the categories can be found in Supplementary Information 1 ) of the reported adaptation evidence. In addition, the confidence in their respective responses was assessed and only high- and medium-confidence evaluations were taken into account in the final assessment of speed, scope and depth.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

All data and analyses used for this study are available in the Supplementary Information , Supplementary Data , Supplementary Tables and Source Data . The Supplementary Information describes the searches (and their combinations) used to generate the literature sample, the inclusion and exclusion criteria for the literature, and a code book providing descriptions of all of the codes. Supplementary Data allows access to all correlation tables, the full coding database, and the list of sources for the city populations used in Fig. 1 . The base layer 85 for Fig. 1 is publicly available, as are the LECZ population data 28 , the country groupings according to average income levels by the World Bank 82 , and the GNI per capita 83 used for the analyses. Supplementary Table 1 displays the full ROSES map report for the study; Supplementary Table 2 provides the full list of the included and excluded literature, including the author(s), title, journal, year and doi. Source Data are provided with this paper.

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Acknowledgements

This work was supported by the following grants: The German Federal Ministry of Education and Research, via the TRANSCEND project (grant no. 01LN1710A1 to J.P., J.Z., M.G. and M.W.), the FloodAdaptVN project (grant no. 01LE1905F1 to A.R.) and the LIRLAP project (grant no. 01LE1906B1 to A.R. and M.G.); NSF CMMI CAREER (grant no. 1944664 to C.J.K.); the Japan Society for the Promotion of Science through the Grant-in-Aid Research Fellowship (grant no. 23KJ0544 to L.T.M.H.); the European Union’s Horizon 2020 research and innovation programme, via the LOCALISED project (grant agreement no. 101036458 to D.R.), the RiskPACC project (grant agreement no. 101019707 to D.R.), and the NWO (JPI Urban Europe Grant, agreement no. 438.21.445 to D.R.). We thank A. Alegria for extensive graphic design support.

Author information

A list of authors and their affiliations appears at the end of the paper.

A full list of members and their affiliations appears in the Supplementary Information.

Authors and Affiliations

Department of Geography, Ludwig-Maximilians-Universität München, Munich, Germany

Mia Wannewitz, Jan Petzold, Andrea Reimuth, Jingyao Zhou & Matthias Garschagen

Department of Environmental Sciences, Emory University, Atlanta, GA, USA

Idowu Ajibade

Department of Environmental Science and Policy, Rosenstiel School of Marine, Atmospheric, and Earth Science, University of Miami, Miami, FL, USA

Katharine J. Mach & Armen Agopian

Leonard and Jayne Abess Center for Ecosystem Science and Policy, University of Miami, Coral Gables, FL, USA

UMR LIENSs 7266, La Rochelle University-CNRS, La Rochelle, France

Alexandre Magnan

World Adaptation Science Programme, United Nations Environment Programme (Secretariat), Nairobi, Kenya

Cawthron Institute, Nelson, New Zealand

Department of Urban and Regional Planning and Geo-Information Management, Faculty ITC, University of Twente, Enschede, the Netherlands

Diana Reckien

Department of Urban Planning & Public Policy, University of California Irvine, Irvine, CA, USA

Nicola Ulibarri

Laboratory of Harbour Works, Department of Water Resources and Environmental Engineering, School of Civil Engineering, National Technical University of Athens (NTUA), Zografou, Greece

Vasiliki I. Chalastani

HafenCity University, Hamburg, Germany

Tom Hawxwell

Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa City, Japan

Lam T. M. Huynh

School of Engineering Design and Innovation and Department of Civil & Environmental Engineering, Penn State University, University Park, PA, USA

Christine J. Kirchhoff

Huntington-USC Institute on California and the West, University of Southern California, Los Angeles, CA, USA

Rebecca Miller

Bill Lane Center for the American West, Stanford University, Stanford, CA, USA

University of Ghana Business School, Department of Public Administration and Health Service Management, Accra, Ghana

Justice Issah Musah-Surugu

Nicholas School of the Environment at Duke University, Sanford School of Public Policy at Duke University, Duke University School of Law, Durham, NC, USA

Gabriela Nagle Alverio

Department of Earth and Environmental Sciences, Columbia University, New York, NY, USA

Miriam Nielsen

Department of Geography and Environmental Management, University of Waterloo, Waterloo, Ontario, Canada

Abraham Marshall Nunbogu

Global Science Team, The Nature Conservancy, Arlington, VA, USA

Brian Pentz

School of Earth and Environment, University of Leeds, Leeds, UK

Giulia Scarpa

Columbia Climate School, Columbia University, New York, NY, USA

Nadia Seeteram

School of Geography, University of Leeds, Leeds, UK

Ivan Villaverde Canosa

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The Global Adaptation Mapping Initiative Team

• Mia Wannewitz
• , Idowu Ajibade
• , Katharine J. Mach
• , Alexandre Magnan
• , Jan Petzold
• , Diana Reckien
• , Nicola Ulibarri
• , Vasiliki I. Chalastani
• , Tom Hawxwell
• , Lam T. M. Huynh
• , Christine J. Kirchhoff
• , Justice Issah Musah-Surugu
• , Gabriela Nagle Alverio
• , Miriam Nielsen
• , Abraham Marshall Nunbogu
• , Brian Pentz
• , Giulia Scarpa
• , Ivan Villaverde Canosa
•  & Matthias Garschagen

Contributions

M.W., M.G., I.A., K.J.M., A.M., J.P., D.R. and N.U. conceived and designed the experiments. M.W., I.A., K.J.M., A.M., J.P., D.R., N.U., A.A., V.I.C., T.H., L.T.M.H., C.J.K., R.M., J.I.M.-S., G.N.A., M.N., A.M.N., B.P., A.R., G.S., N.S., I.V.C. and J.Z. performed the experiments. M.W., M.G., J.P. and J.Z. analyzed the data. The Global Adaptation Mapping Initiative Team contributed the materials and analysis tools. M.W. and M.G. wrote the paper.

Corresponding author

Correspondence to Matthias Garschagen .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Peer review

Peer review information.

Nature Cities thanks Shruthi Dakey, Gregorio Iglesias and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended data fig. 1 roses flowchart for systematic maps..

RepOrting standards for Systematic Evidence Syntheses (ROSES) were used to follow a standardized and transparent approach to searching and screening scientific literature. For each step in the process, numbers of publications are disclosed.

Supplementary information

Supplementary information.

Supplementary information on GAMI authors, literature searches, inclusion and exclusion criteria and the code book.

Reporting Summary

Supplementary table 1.

The ROSES map report.

Supplementary Table 2

A list of the literature included and excluded.

Supplementary Data 1

Correlation Tables 1.1–1.9.

Supplementary Data 2

Coding database.

Supplementary Data 3

Data sources for city populations.

Source Data Fig. 1

Unprocessed geospatial urban population and income data.

Source Data Fig. 2

Raw data: the considered risk factors in the assessed coastal cities.

Source Data Fig. 3

Raw data: the number of cities per response and actor type.

Source Data Fig. 4

Raw data: the speed, scope and depth of reported adaptation.

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Wannewitz, M., Ajibade, I., Mach, K.J. et al. Progress and gaps in climate change adaptation in coastal cities across the globe. Nat Cities 1 , 610–619 (2024). https://doi.org/10.1038/s44284-024-00106-9

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Received : 20 November 2023

Accepted : 15 July 2024

Published : 26 August 2024

Issue Date : September 2024

DOI : https://doi.org/10.1038/s44284-024-00106-9

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Burkina Faso + 4 more

Modeling Climate Analogues of Climate Smart Village sites in West and Central Africa: Case Study from Benin, Burkina Faso, Mali, Niger, and Tchad

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Anani Ogou (1)*, Manjari Singh (1), Desire M. Kagabo (1), Mathieu Ouédraogo (1), and Peter Laderäch(1) | 1-Alliance of Bioversity International and CIAT *Corresponding Author Email : [email protected], elaborated in July 2024

INTRODUCTION AND BACKGROUND

Climate analogue is a term given to represent locations/sites/places which are witnessing similar climates in present or in the future (James D. Ford et al., 2010). It is a tool used in order to implement on the ground the Future of Farm (FoF) approach developed by the Alliance of Bioversity and CIAT, which aims at helping farmers to learn climate resilience strategies opportunities from analogues sites to be used later on in the reference site (CCAFS, 2013).

In order to help farmers and rural communities from TARSPro project Climate Smart Villages (CSV) sites in Worogui-Goura (Benin), Ouda (Burkina Faso), Sabenebougou (Mali), Kieche (Niger), and Tambling (Tchad), the Alliance of Bioversity International and CIAT intends to support the implementation of Future of Farm (FoF) in collaboration with the NARES in West and Central Africa Region for a better resilience of small scale farmers in this region.

• GPS coordinate of CSV site of Worogui-Goura (Benin), Ouda (Burkina Faso), Sabébébougou (Mali), Kiéché (Niger), and Tambling (Tchad).
• Growing season was considered from May to October, which corresponds to the rainy season in these countries, and thus the crop growing season.
• Climate variables considered for computing analogues were the mean monthly temperature and total precipitation. WorldClim data at 30sec resolution ( https://www.worldclim.org/data/worldclim21.html ) provided the present day climate data, and thus were considered as the target data. The future climate data (CMIP5; https://www.worldclim.org/data/v1.4/cmip5_30s.html ) is available as the downscaled products of 33 Global Climate Models at RCP 8.5 for the year 2050 (IPCC, 2023).
• To avoid biasness in model selection, random sampling was done.
• Climate Dissimilarity Index (CDI) was computed using CCAFS formula (CCAFS, 2013) for each variable (temperature and Precipitation).
• R.3.4 was used for modeling the climate Analogues data

CONCLUSION & RECOMMENDATIONS AND WAY FORWARD

The Climate Analogues modeling tool is a science-based decision making tool that helps taking advantage of climate change adaptation and mitigation options for a better planning of CSA which leads to better resilience of rural communities to the changing climate in the future. A comprehensive list of the top ten sites exhibiting higher similarity with the future climate of selected villages in the year 2050 were made available to each country team. A questionnaire have been developed by CIAT and shared with country team to make a prescreening of the top 3 sites among the 10 taking into account some feasibility conditions such as CSA, socio-cultural and economic opportunities to learn, proximity of the analogues sites, accessibility, and the socio-political conflict situation in the country.

The implementation of the Farm of the Future (FoF) approach in TARSPro intervention countries, namely, Benin, Burkina Faso, Mali, Niger, and Tchad is planned to be held with the rural communities in early beginning of September 2024.

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Burkina Faso: IMF Country Report No. 24/250 (July 2024)

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