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WIREs Clim Change
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Addressing the risk of maladaptation to climate change

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This paper reviews the current theoretical scholarship on maladaptation and provides some specific case studies—in the Maldives, Ethiopia, South Africa, and Bangladesh—to advance the field by offering an improved conceptual understanding and more practice‐oriented insights. It notably highlights four main dimensions to assess the risk of maladaptation, that is, process, multiple drivers, temporal scales, and spatial scales. It also describes three examples of frameworks—the Pathways, the Precautionary, and the Assessment frameworks—that can help capture the risk of maladaptation on the ground. Both these conceptual and practical developments support the need for putting the risk of maladaptation at the top of the planning agenda. The paper argues that starting with the intention to avoid mistakes and not lock‐in detrimental effects of adaptation‐labeled initiatives is a first, key step to the wider process of adapting to climate variability and change. It thus advocates for the anticipation of the risk of maladaptation to become a priority for decision makers and stakeholders at large, from the international to the local levels. Such an ex ante approach, however, supposes to get a clearer understanding of what maladaptation is. Ultimately, the paper affirms that a challenge for future research consists in developing context‐specific guidelines that will allow funding bodies to make the best decisions to support adaptation (i.e., by better capturing the risk of maladaptation) and practitioners to design adaptation initiatives with a low risk of maladaptation. WIREs Clim Change 2016, 7:646–665. doi: 10.1002/wcc.409 This article is categorized under: Vulnerability and Adaptation to Climate Change > Learning from Cases and Analogies
The role of maladaptation in increasing vulnerability and, in turn, the influence of increased vulnerability on the risk of maladaptation. Panel A. Maladaptation (M) affects vulnerability (V) through increasing either the system's exposure (E) or its ecosystems’ and /or society's sensitivity (ES and SS, respectively) to climate‐related changes, both extreme events and gradual changes. Panel B shows that in turn, the increase in vulnerability (V) exacerbates the risk of maladaptation (M), depending on the initiatives (I) undertaken to cope with vulnerability. Part a/State 1 describes the initial situation, that is, the current state of vulnerability (V1) as a result of the current combination of the system's exposure (E1) and its ecosystems’ and society's sensitivity (ES1 and SS1). State 1 applies before any adaptation initiative. To cope with current risks and vulnerability, however, authorities, for example, decide for an initiative (I1) in the name of adaptation, but that in fact reveals being maladaptive (M1). An example is a network of dykes set up after a storm surge in a low‐lying coastal area (I1)—for example, what happened since the 18th century in New Orleans, LA; or since the 1950s in Charente‐Maritime, France. Although a network of dykes can make the area more secure immediately, it perversely tends to induce more and more urbanization behind the dyke, thus inducing partly irreversible impacts on coastal ecosystems and a growing sensitivity of the population to extreme events (due to a decrease in hazard awareness and preparation, as well as to an overconfidence in the effectiveness of hard defenses that in fact usually suffer from a lack of maintenance). This leads to a State 2 where ecosystems’ sensitivity has changed (from ES1 to ES2), as well as society's one (from SS1 to SS2). Obviously, climate change being ongoing, exposure also increases (from E1 to E2). As a result, the system's vulnerability is also exacerbated (from V1 to V2). Conditions have changed and thus the nature of risk too, so that new answers are needed. Owing to new challenges (e.g., increased coastal population density and economic activities), it is decided to add new dykes (I2)—as it happened in New Orleans after cyclone Betsy in 1965—and/or to increase the height of the existing protections—for example, what happened in Charente‐Maritime after the Xynthia Storm in 2010. Of course, such a decision puts more pressure on coastal ecosystems (e.g., loss of the wetlands in the Eastern boundary of New Orleans), so that their sensitivity to climate‐related changes moves from ES2 to ES3. If this hard‐defense option is not accompanied with drastic urbanization constrains, alert systems, and population's awareness programs—which partly describes the post‐Xynthia situation in France—, it is at risk of not reducing society's sensitivity, which will on the contrary increase (from SS2 to SS3). In parallel, climate change naturally increases exposure to sea‐related hazards (from E2 to E3), as sea level is rising and even in the case of no change in current storms patterns. At the end, vulnerability increases again (from V2 to V3). Part b/And so on until the risk of maladaptation is not enough considered and become fully part of the design of adaptation choices. This schematically illustrates the role of maladaptation in increasing long‐term vulnerability (Panel B a/), that is, the less maladaptation is addressed upstream, and the more vulnerability is at risk of increasing. It, however, also highlights a feedback effect: the more vulnerability increases, the more the system is maladapted, and the more it is at risk of maladaptation in the future. Such a vicious cycle emphasizes a maladaptation process made of both natural (especially climate change) and anthropogenic (environmental degradations, increase in coastal population densities, non diversified economies, etc.) drivers.
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The four critical dimension of maladaptation in the Pathways, Precautionary, and Assessment frameworks. This figure shows to what extent the various guidelines of the three frameworks exposed in this paper address each of the four critical dimensions of maladaptation raised in Insights from the Field: Illustrative Concrete Examples section and discussed in the Case Studies section, that is, process (P), multiple drivers (MD), temporal scales (TS), and spatial scales (SS). The circles are colored depending on whether the papers being at the root of each framework do or do not explicitly make a link with the four critical dimensions of maladaptation. The white colored circle means no explicit mention in the text(s) of origin.
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