A certain degree of climatic change is unavoidable, even if greenhouse gas emissions were to completely stop as of today (IPCC 2014). This makes adaptation to climate change necessary. Adapting social-ecological systems to a changing climate requires adjustments in both individual and societal behavior (Smit and Wandel 2006). Changes will be needed, both to implement technical solutions and to adjust to those climate impacts that technical solutions cannot fully offset (Adger et al. 2009).
Research into the societal dimension of adaptation focuses on two main lines of inquiry: barriers to adaptation (Moser and Ekstrom 2010) and maladaptation (Juhola et al. 2016). The former addresses the challenges practitioners and decision makers face in responding to increasingly adverse effects of climate variability and change (Biesbroek et al. 2013, Oberlack and Eisenack 2014, Lehmann et al. 2015, Moser et al. 2019). The latter points out that not all adaptation is good (Eriksen et al. 2011); some adaptation processes lead to maladaptive outcomes (Juhola et al. 2016), while others raise fairness and justice concerns (Paavola and Adger 2006, Pelling et al. 2015). In a nutshell, adaptation is difficult to roll out, and may go wrong. Therefore, careful consideration is required before taking measures to overcome barriers to adaptation.
Recent developments call for renewed reflection on these issues. One frequently cited barrier to adaptation is the inadequate provision of climate information to support decision making (Archie et al. 2014, Donatti et al. 2017). However, this barrier is now being overcome as sustained technical and institutional advances in climate modeling (Street 2016, Brasseur and Gallardo 2016, Simpkins 2017) make climate information increasingly accessible to decision makers. In the European context, for instance, a roadmap for climate services (Street 2016) sets out the first steps toward a future where administrations, businesses, and private citizens can easily access climate information. Despite the growing provision of climate information, there often remain challenges in integrating it into decision making and the ambiguity of what sort of adaptation will then follow.
We contribute toward this problem by linking two emerging discourses in the adaptation literature: on opportunities and transformation. The former discourse reflects a growing interest in going beyond a negative discussion of barriers, toward a positive understanding of factors that are currently enabling and shaping adaptation (Biesbroek et al. 2014, Oberlack 2017). The latter acknowledges the increasing importance of distinguishing between incremental and transformational adaptation (Kates et al. 2012, Lonsdale et al. 2015). These considerations enable us to formulate the following research question: Does the provision of climate information provide opportunities for both incremental and transformational adaptation? Or does it lock adaptation governance into either option?
Intuitively, climate information might appear to provide inputs primarily for incremental adaptation, i.e., the consideration of future climatic conditions in present-day decision-making processes. Transformation, by contrast, entails more fundamental alterations in existing governance structures (Pelling and Manuel-Navarrete 2011, Godfrey-Wood and Naess 2016), raising issues that go beyond mere availability of information. However, climate information also has a role to play in transformational adaptation. In fact, recent studies suggest that the generation, exchange, and contextualization of climate information is at the very heart of the transformational adaptation agenda (e.g., Tabara et al. 2018). Whether access to climate information provides opportunities for transformational adaptation as well as incremental change is thus a nontrivial question that merits a closer look.
In this paper we explore the links between provision of information and opportunities for incremental and/or transformational adaptation in the context of water governance. The water sector is severely affected by climate change (IPCC 2013, Tilleard and Ford 2016) and decision makers in the sector were quick to realize that governance solutions were required, as well as purely technical ones (Gupta and Pahl-Wostl 2013, Huitema et al. 2016). The sector is also characterized by a high degree of heterogeneity and fragmentation (Edelenbos and Teismann 2013, Eisenack 2016). These traits are typical for adaptation in general (Morrison 2017, Den Uyl and Russel 2018), and for transformational adaptation in particular (Lonsdale et al. 2015, Patterson et al. 2017).
Taking account of this heterogeneity, we address the research question using archetype analysis, a methodological approach increasingly gaining traction in sustainability science that enables researchers to develop scientifically valid generalizations about heterogeneous phenomena (Eisenack et al. 2006, Eisenack 2012). In this study, we apply archetype analysis to identify recurring patterns in situations where opportunities for adaptation are observed in the water sector. Subsequently we assess the extent to which these opportunities favor incremental or transformational adaptation. Based on 26 selected case studies on water governance adaptation from around the world, we identify six archetypical situations in which the provision of climate information constitutes an opportunity for adaptation. We find that four archetypes bear the hallmarks of incremental adaptation, while two are associated with transformational adaptation.
Does the provision of climate information constitute an opportunity for both incremental and transformational adaptation in the context of water governance? We draw on a literature review to examine key concepts that underpin our formulation of this research question, i.e., water governance; climate information; adaptation governance; opportunities for adaptation; and incremental and transformational adaptation.
Although water management has traditionally been the remit of central public authorities, contemporary water management is better described by the broader notion of water governance. This term encompasses the interactions among a variety of public and private organizations dealing with water resources at different levels of politico-administrative organization (Brooks 2002, Huntjens et al. 2010, Bressers and Kuks 2013, Pahl-Wostl and Knieper 2014). Water governance is a complex action field, involving different sectors, scales, and domains; it encompasses a complex structure of mutual interdependencies among actors with various interests and views that need to be coordinated (Edelenbos and Teismann 2013, Eisenack 2016).
In this context, the attention of academics and practitioners has shifted away from purely technical approaches to managing water and is now increasingly focused on achieving effective interaction and coordination among all actors involved (Edelenbos and Teisman 2013). This shift is reflected in the range of measures put forward to reduce the sector’s vulnerability to climate change: although “hard” technical measures, e.g., raising dikes, have not gone out of fashion, they are increasingly embedded into “soft” approaches, involving spatial planning instruments and promotion of ecosystem-based perspectives (“living with water,” “giving space to the river,” “good ecological status”). These typically require that higher level water managers cooperate with local authorities (Kirchhoff et al. 2013) and water engineers engage with nature conservation agencies, planners, and affected parties (Bergsma 2016). Although an in-depth exploration of water governance is beyond the scope of this paper, the reader should keep in mind that the water sector has grown in social complexity, making interactions among interdependent actors crucial for the management of water resources.
As in the case of water governance, climate adaptation in general involves a broad set of actors, who play out in nested governance systems (Bisaro and Hinkel 2016). Adaptation governance corresponds to “collective efforts of multiple societal actors to address problems, or to reap the benefits, associated with impacts of climate change” (Huitema et al. 2016), with the aim of ensuring coordinated action among interdependent actors (Roggero 2015). Collective action faces social dilemmas, and climate adaptation is no exception in this respect (Bisaro and Hinkel 2016). Under the header of barriers to adaptation, scholars have identified many factors that prevent adaptation from taking place (Moser and Ekstrom 2010, Biesbroek 2014, Lehmann et al. 2015, Oberlack 2017). Many of these barriers relate to the provision of climate information.
Climate information refers to externally provided processed data, products, or evidence-based knowledge about the atmosphere-ocean system (Singh et al. 2018). This climate data originates from diverse sources such as in situ sensor measurements, remote sensing observations, or climate models (Giuliani et al. 2017) and can range from historical data to long-term climate change projections (Soares et al. 2018). Such diversification leads to a wide range of available climate information that can be used in adaptation decision making, different in its origin, form, purpose, scale, or context. The temporal character of such information is particularly important for climate adaptation. Climate information can be divided into three categories: short term (weather forecasts); medium term (seasonal and decadal climate forecasts), and long term (climate variability and climate change projections; Collins 2002, O'Brien and Vogel 2003, Ziervogel et al. 2010). There are important differences between these types of forecasts: weather forecasts predict conditions of the atmosphere, i.e., temperature, precipitation, and air movements, for the next few days, while climate forecasts are based on the statistical average of all weather events over a longer period of time (normally 30 years; Singh et al. 2018).
In the water sector, climate change projections and medium-term climate predictions play the greatest role in preparing strategic, longer term adaptive responses (Ziervogel et al. 2010, Kirchhoff 2013). However, generation of future climate information through modeling or scenario-based approaches (usually using general or regional circulation models and emission scenarios) is often associated with users’ concern regarding accuracy of such information (Grygoruk and Rannow 2017) or uncertainty about projected climate impacts (Biesbroek et al. 2014). Scholars have identified a number of further challenges related to the integration of climate information into planning and decision making. These include unwieldy rules that hamper the retrieval, processing, and use of information for decision making (Oberlack and Eisenack 2018), institutional fragmentation (Cosens et al. 2017, Okpara et al. 2018), lack of collaboration (Bettini et al. 2015) and communication (Azhoni et al. 2017), and inadequate awareness and understanding of climate change (Jones and Boyd 2011, DeCaro et al. 2017).
Within the adaptation literature, two fundamentally different concepts share the label of “opportunity” for adaptation: drivers forcing adaptation (see Shepherd et al. 2006, Pelling and Manuel-Navarrete 2011), and factors enabling adaptation (see Lonsdale et al. 2017, Oberlack 2017). The distinction is subtle, but important. For example, an adaptation measure that results from the traumatic experience of a flood is different from one that results from the reorganization of public administration. Both cases represent an opportunity for adaptation. Yet, they represent qualitatively different phenomena: in the former, an unforeseen catastrophic event leads to new perceptions and priorities. In the latter, an organizational measure is taken intentionally to remove a specific barrier to adaptation (see Tompkins et al. 2010).
Both concepts are important and relevant. However, because of space considerations, we focus in this study on opportunities as enabling factors, and specifically on opportunities related to the provision of climate information that help overcome existing barriers to adaptation in the water sector. The rationale for this choice is that opportunities that force adaptation can only be seized upon in a reactive way, however timely this may be. By contrast, removing barriers intentionally requires careful consideration, particularly if doing so can potentially give rise to different types of adaptation. Opportunity in this sense is thus more closely aligned to the topic of our research.
The distinction between incremental and transformational adaptation emerged as a topic of interest when climate scholars started to highlight the need for a fundamental change in socioeconomic arrangements in order to adapt to climate change (Tabara et al. 2018), and to question whether the measures currently planned and/or being taken are up to the task (Kates et al. 2012). The defining characteristics of transformational adaptation have been described in different ways: as addressing the root causes of climate vulnerability rather than only its symptoms (Wise et al. 2014); fostering long-term adaptive capacity rather than short-term vulnerability reductions (Wamsler et al. 2013); or changing habits and institutions rather than the physical infrastructure (Vine 2018). All in all, scholars seem to converge around an emphasis on long-term, reflexive adaptation processes.
Precisely drawing the line separating incremental and transformational adaptation has so far proved challenging. In principle, the distinction is similar to one that has been widely discussed in the literature of evolutionary resilience. It is recognized that a resilient social-ecological system can display two different reactions in response to an external shock: it can absorb the shock and “bounce back” to status-quo conditions or, alternatively, “bounce forth” to a new set of conditions that are equally stable and yet fundamentally different (Davoudi et al. 2013). In this sense, incremental adaptation encompasses measures that reproduce or even entrench the status quo in the face of changing conditions. By contrast, transformational adaptation encompasses measures that lead to a new system configuration.
We aim at identifying recurring patterns in situations where opportunities for adaptation are observed in the water sector. Below we provide an overview of the methodology used to generate research insights that are more widely applicable than single-case idiosyncrasies, but also of more practical relevance than overgeneralized panaceas.
We conducted a meta-analysis of 26 systematically selected research articles to identify opportunities to adaptation, using the social-ecological system (SES) framework (Ostrom 2009) to characterize each opportunity identified. Specifically, we used the articles selected by Oberlack and Eisenack (2018) for their study of barriers to adaptation in worldwide water governance (see Appendix 1 for full references). In all these case studies, opportunities for adaptation were also identified, making this selection suitable for the present analysis.
Similar to Oberlack (2017) and Oberlack and Eisenack (2018), our meta-analysis is “model-centered” (Rudel 2008); that is, it focuses on explicit causal statements found in the articles under review, and draws collections of attributes (“models”) from each of them. The rationale for this procedure is as follows. Conducting a meta-analysis of multiple case studies carried out by different authors with different goals in mind would ideally involve interviews and/or questionnaires with the authors to fill gaps and establish a degree of homogeneity in the dataset. Doing so is a resource-intensive process and goes beyond the available resources. As an alternative, the model-centered approach represents a viable second-best option. Because models are derived from explicit statements, they require less interpretation than the case study as a whole. Focusing on causal statements clearly represents a reduction of complexity. That should not be overstated, though, first, because causal statements were formulated by experts with case-level knowledge, and second, because they passed the peer-review process, which, with all its limitations, should guarantee a minimum degree of reliability. Third, causal statements should not be overstated because they can represent a substantially large and considerably detailed amount of text.
The last point is crucial. When the phenomenon at stake is well-studied, model-centered meta-analyses can take a very reductionistic approach to identifying causal statements and drawing models from them (e.g., Oberlack 2017, Oberlack and Eisenack 2018). “Opportunities for climate adaptation,” however, is an emerging concept, with little research to rely on. Causal statements shall therefore provide a sufficiently rich description so as to cover the whole situation in which an opportunity for adaptation arises. To this end, we deviate from Oberlack (2017) and Oberlack and Eisenack (2018) and broaden our understanding of causal statements to include the broader account in which they are embedded. Causal statements shall therefore be read as explicit narratives, providing a rich description of how a particular enabling factor (provision of climate information), when coupled with other factors leads to adaptation to climate change. A detailed illustration of how models were extracted from the source material can be found in Appendix 1.
We identified a total of 83 models in the 26 articles under scrutiny. Of these, 38 models describe an opportunity in terms of the provision of climate information. We coded these 38 models employing the common vocabulary of attributes developed by Oberlack and Eisenack (2018), which builds on the SES framework. The SES framework has a multitiered structure that allows opportunities identified to be coded at varying levels of specificity. Moreover, it is very comprehensive and is thus able to accommodate a broad set of very different situations. In a nutshell, the SES framework is both broad and deep and does not impose, ex ante, a specific level of abstraction on the analysis (see Cox 2008). This is useful when exploring potentially very heterogeneous phenomena such as opportunities for adaptation.
Our codebook retains the top-tier of the framework, distinguishing between resource systems (RS), resource units (RU), actor characteristics (A), governance systems (GS), social, economic, and political settings (S), and interactions (in our study labeled IO, so as to reflect opportunities), to which the additional category “adaptation option” (AO) was added. The second and third tiers of the codebook divide each of these categories into a further set of attributes, which were similarly modified by the authors to fit the data. One of the main authors undertook multiple rounds of coding, discussing results with the other authors to ensure inter-rater reliability of coding. Iterations continued until the codebook stabilized. In its final form the codebook comprises 116 attributes; of these, 6 describe the opportunity concerned (IO), and 110 characterizing the factors affecting it, distributed across several tiers of RS, A, GS, S, and AO. Appendix 1 contains detailed information on the final codebook and coding process.
We employed archetype analysis to explore the 38 models relevant to the provision of climate information, searching for patterns among their attributes. The reader can refer to Oberlack et al. (2019) and Eisenack et al. (2019) for a detailed account of the broader rationale underlying archetype analysis. In the context of the present research, there were two main reasons for our decision to employ archetype analysis. First, opportunities for adaptation can be expected to encapsulate a high level of heterogeneity, particularly in the context of water governance. We therefore needed an analytical approach that favors multiple, contextualized explanations, rather than single, universal ones. Second, we needed an approach that is compatible with multiple levels of abstraction, i.e., the multiple tiers of the SES framework that we employed to organize and structure the data. Archetype analysis fulfills both requirements.
Archetype analysis does not represent an analytical method per se. Rather, it is an approach compatible with multiple analytical methods (Sietz et al. 2019). It provides guidelines on how to structure an analysis in order to systematically search for possible attribute configurations (here the 110 attributes of the modified SES framework) in a given set of observations (here the 38 models of adaptation linked to the provision of climate information). Figure 1 shows how the guidelines for archetype analysis were translated into a procedure, leading from the characterization of the models to the identification of the archetypes. A full description procedure can be found in Appendix 1; here we summarize its most important features:
The analysis was done using R (R Core Team 2018). The derived archetypes satisfy the quality criteria for archetype analysis (Eisenack et al. 2019), namely: (1) they have a clear domain of validity (water governance); (2) they are not mutually exclusive (individual models can be instances of multiple archetypes, even though no two archetypes can cover exactly the same set of models); and (3) they are reoccurring (the corresponding models must appear in at least two different papers).
This section presents the six archetypes that were identified using the procedure outlined above, and completes the archetype analysis by describing the theories underpinning them.
This archetype reflects the combination of three attributes: “joint institutional arrangements,” “trust building among actors,” and “horizontal coordination”; it was observed in two different models from two different papers. Joint institutional arrangements, trust building among actors, and horizontal coordination are key descriptors of collective action, which has been a central theme in the literature on adaptation (Marshall 2013, Bisaro and Hinkel 2016). Scholars particularly stress the importance of interdependencies among actors and the crucial role of social dynamics in building adaptive capacity (Adger 2003). We observed this archetype in the context of transboundary water governance, where water management is typically fragmented. Coordination between the parties and the presence of common institutional frameworks are essential to enable adaptation. Establishment of joint institutions helps to reconcile multiple interests, balance priorities, and shape a favorable environment for the integration of climate information into decision making and design of feasible management interventions (Kistin and Ashton 2008).
The attributes making up this archetype are “local watershed units” and “awareness of climate change impacts,” appearing in three models across three papers. This archetype highlights the link between the “local” dimension of the watershed concerned and impacts of climate change. It thus encompasses those branches of the adaptation literature addressing the (single) “level” of socioeconomic organization best suited to deliver adaptation and stressing that local actors know best how climate change translates into impacts (Brooks 2002, Agrawal 2008, Nordgren et al. 2016). At the local level, climate impacts might be grasped more easily, which gives climate concerns a higher chance to be integrated into management practices. Experience of local-level vulnerability to climate change motivates actors to integrate climate information into water management practices and deliver effective responses (O'Connor et al. 1999). Adaptation here takes place within existing practices.
This archetype describes the combination of “local watershed units” and “institutional incentives and priorities.” It represents three models from two different papers. Like the previous one, this archetype reflects the scholarly debates on the most appropriate level of adaptation. Here, however, the focus is on the alignment of institutional incentives with the requirements for local-level adaptation in response to climate impacts experienced at this level. This relates to a broader debate in the literature on environmental governance regarding the correspondence between institutional boundaries and the costs and benefits linked to managing particular resources (Young 2002, Young 2010), a topic that adaptation scholars have also addressed (Farber 2009, Shobe and Burtraw 2012). From this perspective, the provision of climate information represents an opportunity for adaptation if it is provided in a way that fits with the interests and mandates of the (local) actors concerned (Whitely Binder 2006, Hamlet 2011, Hurlbert and Diaz 2013).
The attributes characterizing this archetype are “local watershed units” and “available data on climate projections at the local scale,” identifying two models from two different papers. Climate research literature on scenario building highlights the need for highly contextualized knowledge for decision making (Cohen 1990, Hostetler 1994, Grimmond et al. 2010). It is often difficult for decision makers to know how to respond to low-resolution climate projections. In contrast, opportunities for adaptation emerge when climate information is provided at a local scale (O'Connor et al. 1999, Whitely Binder 2006). Speaking the language of local climate impacts makes climate information more accessible to decision makers, and more relevant to existing mindsets, institutions, and biophysical particularities (Füssel 2007).
Combining “current climate stimuli” and “long-term focus,” this archetype reflects two models from two papers. Literature at the intersection between resilience and climate adaptation highlights the need for adaptation to climate change to be informed by a vision of the long-term development of the social-ecological system concerned (Tschakert and Dietrich 2010, Davoudi et al. 2013). In this sense, opportunities for supporting long-term and effective adaptation arise from the coproduction of useful knowledge as a result of collaboration between scientists and stakeholders (Kirchhoff et al. 2013, Pulwarty and Maia 2015). Such direct collaboration between stakeholders and climate scientists aims at improving stakeholders’ understanding of climatic stimuli and its impacts on the governed water system. It reconciles information supply and concrete demand needs by integrating expertise from both sides, which leads to increased capacity while dealing with adaptation related problems. This kind of partnership implies long-term iterative interactions that allows for advancing formal and informal networks, and therefore is likely to result in successful and sustainable societal outcomes. Specifically, such collaborations go beyond the mere planning of individual measures, directly impacting regional policies and promoting development of new communities of practices (as in Wilder et al. 2010).
This archetype combines “awareness of climate impacts” and “institutional incentives and priorities” as observed in two models from two papers. Much of the literature on adaptation focuses on learning, stressing how adaptation often needs to be compatible with shared beliefs about the workings of the social-ecological system (Pahl-Wostl 2009, Baird et al. 2014). Learning plays a crucial role in shaping actors’ behavior, particularly when regulatory arrangements are unwieldy and complex, and/or insufficient on their own to foster the direct integration of climate change concerns in formal decision-making processes (Storbjörk 2010). The key insight is that learning ensures a higher level of awareness of climate impacts among managers and decision makers. It enables actors to circumvent institutional barriers to adaptation by exploiting flexibility in existing arrangements and seeking synergies with other institutional arrangements. For example, recognition of potential adverse effects of climate variability on a resource system and of the need for a tailored climate information may result in seizing opportunities by integrating climate change issues into decision making under the umbrella of related existing institutional mechanisms that prioritize efficient use and conservation of water resources (Boer 2010, Farley et al. 2011). This leads to a higher adaptive capacity in terms of increasing institutional flexibility and ensures long-term, reflexive adaptation.
Our archetype analysis identifies six recurring situations in which opportunities for adaptation in water governance arise. The analysis focuses specifically on opportunities linked to the provision of climate information and whether these opportunities are for incremental or transformational adaptation. Results suggest that the provision of climate information is not limited to adaptations consisting of incremental, marginal changes in existing practices, but are also associated with transformational adaptation. Specifically, two of the six archetypes identified, “System evolution” and “Learning,” enable transformational adaptation, in the former as a result of the focus on long-term implications of current impacts, and in the latter arising from reflection among actors on how to address climate impacts in the context of available institutional arrangements. These two archetypes fit well into narratives characterizing transformational adaptation as adaptation that (1) focuses on reducing future vulnerabilities rather than simply preserving present conditions; and (2) questions the capacity of existing institutions to respond to climate change (Mustelin and Handmer 2013, Lonsdale et al. 2015).
In relation to the overarching research question addressed by this study, these results are encouraging: they suggest that the provision of climate information can constitute an opportunity for adaptation that goes beyond purely incremental adjustments to a changing climate. This result is particularly encouraging in the light of the current situation, where barriers to adaptation translate into a lack of tangible adaptation measures on the ground (Berrang-Ford et al. 2011). Although uncertainty, ambiguity, and lack of information are known barriers to adaptation, the opportunities that emerge to overcome such barriers are apparently not restricted to incremental adaptation. Removing barriers through the provision of climate information will not, it seems, lock adaptation governance into an incremental approach. At least under certain circumstances, it can also give rise to transformational change.
Given the exploratory nature of this study, it seems too early to draw conclusions from the actual composition of the archetypes identified here. Instead, it is probably safer to regard them as starting points for further research. From this perspective, with reference to the two “transformational” archetypes highlighted above, advancements in the conceptualization of opportunities for adaptation shall be linked to the way social-ecological systems evolve over time and to possibilities for double and triple-loop learning as a key step toward change. With reference to the other “incremental” archetypes, advancements seem to lie on collective action, as well as on matters of scale, given that three of the remaining four archetypes stress the local dimension of the resource unit. Future research will tell if developing concepts of opportunities for adaptation along these lines will align with empirical observation.
By focusing primarily on the analysis of opportunities for climate adaptation, the present study identifies archetypical situations in which integration of climate information constitutes an opportunity for adaptation and on the nature of adaptation that follows. Given the increasing amount of available climate information for adaptation decision making, it is worthwhile for future research to consider how different types of climate information are used in different ways and can thus influence opportunities for adaptation. There are already first attempts in this direction (Haasnoot et al. 2012, Singh et al. 2018, Hinkel et al. 2019). The archetype approach may also play a role here by informing the development of climate services, for instance by providing tailored climate products and information.
With a rapid development in provision of environmental information as well as in all kinds of information and communication technologies, processing and constantly governing growing amounts of data has become increasingly challenging. The case of information provision for climate adaptation is certainly no exception. Several questions emerge: what new data should be gathered? Who is responsible for collecting and processing the data, coordination of databases, and dissemination of information? How can this data and information be shared and combined to ensure more sustainable decision making and how the impact can be monitored? We are thus about to observe a great shift in the role information is playing within the governance context. A further link to the emerging field of research in informational governance and environmental sustainability is worth exploring as well (Soma et al. 2016, Giuliani et al. 2017).
Having outlined the implications of the present analysis for adaptation research, we can now tentatively explore the policy implications. The fact that the provision of climate information can enable transformational adaptation calls for policy support in boosting collaborative processes and social learning, e.g., building knowledge hubs (Ziervogel et al. 2016). Leaving aside the distinction between incremental and transformational adaptation, the overarching message emerging from the archetypes seems to be that opportunities for adaptation arise when the provision of climate information is embedded in a broader process. In this respect, current efforts by policy makers to establish new climate services and further develop existing ones are a welcome development, which may well contribute to boosting adaptation. These efforts are more likely to facilitate adaptation if policy makers adopt a process orientation (Brasseur and Gallardo 2016). However, judging from initiatives such as the European roadmap for climate services, at present there is a focus on developing markets for climate services (Street 2016), thus making them product oriented. It remains to be seen whether these efforts will be successful in promoting adaptation, or whether they will give rise to new barriers.
A limitation of this research is that the analysis focuses on research papers dealing with water governance, a field where both adaptation and transformation are well-established concepts. Although this is convenient for our analysis, it also limits the external validity of our results: opportunities for adaptation in other sectors such as developmental aid or agriculture may look very different. This is particularly the case for the two transformational archetypes whose specific features are closely linked to water management discourses such as adaptive management and social learning.
Furthermore, the fact of relying on a rather specific field such as water governance may prove a double-edged sword. On the one hand, it may facilitate the emergence of archetypes, given the similarity of perspectives within a narrowly defined epistemic community. On the other hand, it may also be a source of blind spots in the analysis: articles will not report about those things water governance scholars are not interested in. This is a general problem for meta-analyses. It may be less of an issue here, though, given the tendency of governance scholars toward rich case description.
A further limitation is that the analysis focuses on literature addressing barriers to adaptation, not opportunities. This was unavoidable, given the scant attention adaptation scholars have so far given to opportunities. The implications of relying on articles about barriers to adaptation are two-fold. First, scientific publications have limited space: given that opportunities were not the main focus of the papers, one cannot help wondering whether some opportunities, and if so how many, did not make it into the final manuscripts because of space limitations. Second, it becomes difficult to disentangle opportunities and barriers: opportunities identified by our research may, to some extent, simply be mirror images of the barriers the same articles report upon.
Some considerations are due concerning the low number of models covered by the six archetypes; specifically, opportunities linked to the provision of climate information were identified in 13 models out of 38. Given that the archetypes were constructed inductively and not deductively (that is, they were not formulated on the basis of prior knowledge), this is quite remarkable. Moreover, models were grouped on the basis of shared general characteristics, i.e., higher tier attributes of the SES framework, whenever they diverged with regard to details (lower tier attributes). This procedure resulted in archetypes characterized by rather general attributes, and yet even these covered only two or three models in each case. This suggests that opportunities for climate adaptation represent a very heterogeneous research field. A certain degree of convergence, and development of more streamlined conceptualizations, can be expected as the field reaches maturity. Time will tell whether future research using more sophisticated conceptual approaches enables the identification of suites of archetypes that provide a better coverage of the observed models.
Despite these limitations, this study confirms the ability of archetype analysis to identify and meaningfully interpret patterns of attributes in a very heterogeneous field. It is thus a promising approach for application in a field such as climate adaptation in the water governance sector where context dependence makes it extremely difficult to draw lessons that are valid beyond the individual case study. Archetype analysis has the potential to deliver research insights at an intermediate level of abstraction: more widely applicable than single-case idiosyncrasies, but also of more practical relevance than overgeneralized panaceas.
In this study we explored opportunities for climate adaptation in the context of water governance. We focused on opportunities arising from the provision of climate information. Further, we asked whether these are limited to opportunities for incremental adaptation, or whether provision of climate information can also give rise to transformational adaptation. To address this question, we carried out an archetype analysis of opportunities for adaptation described in 26 peer-reviewed research articles. In each article, opportunities were searched for, coded using the SES framework, and finally bundled into archetypes that encompass similar opportunities reappearing across multiple cases. Six such archetypes were identified, each one representing an opportunity for adaptation characterized by a distinct set of attributes. Two of these archetypes are associated with specific narratives in the discourse on transformational adaptation, suggesting that opportunities for adaptation linked to the provision of climate information are not necessarily limited to incremental adaptation. However, the results display a high degree of heterogeneity in the characterization of opportunities, indicating the need for further research to develop more streamlined conceptualizations of the phenomenon. The results of this study suggest some avenues toward further conceptual development that could be explored by future studies of opportunities for climate adaptation.
We want to thank Christoph Oberlack and Susanne Moser as well as two anonymous reviewers for their useful comments on previous versions of this manuscript. The research was funded by the state of Berlin’s Elsa-Neumann-Scholarship. We acknowledge support by the German Research Foundation (DFG) and the Open Access Publication Fund of Humboldt-Universität zu Berlin.
Data sharing is not applicable to this article because no new data were created or analyzed in this study.
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