INTRODUCTION

Climate change adaptation, which we define as any human response that could reduce risks related to actual or expected climate change, has evolved beyond a simplistic view of a singular action and is being increasingly recognized as a multifaceted, interdependent, and complex process (Adger et al. 2005, Singh et al. 2016, Eriksen et al. 2021, Orlove 2022). To explore and better understand this complexity, adaptation scholarship has identified several categorical conceptualizations of adaptation based on intent, function, spatial scales, spatial scope, depth, timing, duration of benefits, and spontaneity (Smit et al. 2000, Kates et al. 2012, Rickards et al. 2012, Pelling et al. 2015, Berrang-Ford et al. 2015, 2021, Magnan et al. 2016, Wilson et al. 2020, Singh et al. 2021). As communities worldwide face the impacts of climate change, there is growing attention on the relative roles of these different types of adaptation to help reduce current and projected climatic risk (Eisenack and Stecker 2012, Berrang-Ford et al. 2021, Eriksen et al. 2021, Singh et al. 2021). In parallel, there is also a growing theoretical basis (Magnan et al. 2020, Schipper 2020), supported by anecdotal evidence (Rahman et al. 2021), that actual adaptation often cannot be categorized dichotomously.

In this study, we focus on one common conceptualization of adaptation: autonomous adaptation - sometimes known as “everyday adaptation” - and planned adaptation. The literature presents a range of diverse and evolving definitions (and terminology) for these types of adaptations, which we synthesize in the subsequent section. Autonomous adaptations are most often described as “everyday,” local, or self-organized practices that are undertaken by actors without external support or explicit consideration of external causes; for example, a farmer adjusts planting times or locations to deal with changes in growing season. In contrast, planned adaptations often emerge from strategic and formal processes designed to respond to external changes, such as climate change, and they tend to be larger in scope and scale with higher levels of organization and institutional support (Biagini et al. 2014); for example: national programs to develop and implement heat-resistant crop varieties. Though both adaptation types can be crucial for reducing climate risk depending on the context, the two have often been perceived and defined as the opposite or in negation of the other (Adger et al. 2007, Easterling 2007, Kates et al. 2012, Rahman and Hickey 2019, Rahman et al. 2021, Ehsan et al. 2022).

A few recent case studies have criticized this dichotomous representation, highlighting the potential of interplay or interaction between these two types of adaptation (Doherty et al. 2017, Mersha and van Laerhoven 2018, Rahman et al. 2021, Juhola et al. 2022, Lindegaard and Sen 2022). Such studies suggest that rather than the two types of adaptation occurring in isolation, there are instead interdependencies, trade-offs, and potential for collaboration between them. Scholars have hence argued that future adaptation policies and actions need to be informed by a deeper understanding of the interactions between planned and autonomous adaptation (Eriksen et al. 2021, Juhola et al. 2022).

Understanding interactions between autonomous and planned adaptation matters intellectually and for adaptation policymaking. These understandings impact the kinds of activities that we recognize as adaptation, what we choose to monitor and evaluate, and who receives financial and technical resources. National governments and multilateral organizations, which shape adaptation policymaking and fund specific programs and projects, tend to rely on the dichotomous framing of autonomous and planned adaptation. For example, the Global Stocktake process conducted under the UN Framework Convention on Climate Change (UNFCCC) currently focuses on adaptation indicators for stocktaking planned adaptation, which do not necessarily account for autonomous adaptation and the spectrum of responses between autonomous and planned. There is thus a need to continually examine and interrogate these conceptualizations and how we transfer them into policy framing, funding, and monitoring global progress on adaptation.

Although a handful of case studies have highlighted the interplay between autonomous and planned adaptations, there has not yet been a systematic global assessment of the prevalence of these interactions and the form(s) they take. This study systematically examines a global database of 1682 peer-reviewed articles to determine whether and how planned and autonomous adaptation interact and to characterize those interactions. Based on quantitative analyses, we first illustrate that many adaptation responses often thought to be purely autonomous or planned are in fact “mixed,” in that they demonstrate characteristics of both. We also present quantitative results on how adaptation outcomes may differ across autonomous, planned, and mixed adaptation. Finally, based on a qualitative typology of mixed adaptation, we introduce the concept of a “continuum” of autonomous and planned adaption and identify different ways in which the two types of adaptation complement, support, resist, constrain, or even co-exist with each other. Overall, our results highlight the relative roles that both planning as well as everyday strategies and autonomy can play in enabling adaptation in locally relevant, scalable, effective, and equitable ways.

Understanding autonomous and planned adaptation

There are multiple definitions, terminologies, and understandings of autonomous and planned adaptation (Noble et al. 2015). The first mention of autonomous adaptation in the IPCC’s second assessment report (SAR) refers to autonomous adaptation as occurring “without specific human intervention,” i.e., only in reference to adaptation in natural or ecological systems (Watson et al. 1997). This emphasis could be the result of the earlier focus on biophysical systems of the IPCC reports, or it could point to autonomous adaptation originating in natural or ecological science. In this study, we do not use this early definition focusing on ecological system, as we analyze adaptation responses in human systems. The subsequent third (TAR), fourth (AR4), and sixth (AR6) IPCC assessment report glossaries define autonomous adaptation (broadly) as “adaptation that does not constitute a conscious response to climatic stimuli” (Parry et al. 2007, Field et al. 2014, IPCC 2023). This definition better accounts for human systems, but aligns more with terms such as “agnostic,” in that it assumes an action is undertaken without implicit or explicit reference to climate change as a driver of a response (Koslov 2019). The IPCC definition overlaps with Smit et al. (2000), who define autonomous as “automatic, spontaneous, and passive” and planned as “strategic, deliberate, and active.” However, even within the various IPCC report chapters, there are references to slightly different understandings of autonomous adaptation. For example, in TAR Ch. 1 autonomous is referred to as “without external intervention” (p. 88), similar to other definitions (e.g., Smit et al. 1996, Thorn et al. 2015). The IPCC reports also make many references to literature which imply autonomous adaptation to be individual and community adaptation, without governmental influence or intervention (Stringer et al. 2010, Forsyth and Evans 2013, Leclère et al. 2013, Bawakyillenuo et al. 2016, Khanal et al. 2019, Rahman and Hickey 2019, Berrang-Ford et al. 2021).

Another understanding of autonomous that has emerged in recent literature is “everyday adaptation” (Artur and Hilhorst 2012, Strengers and Maller 2017, Castro and Sen 2022, Juhola et al. 2022, Lindegaard and Sen 2022), which has also been documented under other closely-related terms such as everyday resistance (Scott 1986, Johansson and Vinthagen 2016), everyday practices (Ross 1996), everyday agency (McMichael et al. 2019), and coping (Nunn and Kumar 2019, Korovulavula et al. 2020). This understanding is “based on how affected communities perceive and frame their vulnerability” (Forsyth and Evans 2013, Rahman and Hickey 2019) and focuses on routine, daily, often overlooked actions related to changing social-ecological conditions (Lindegaard and Sen 2022). These slight distinctions in definitions and understandings of autonomous adaptation are related to differing understandings of spontaneity and action that occurs without apparent external intervention as: a) without influence of an external actor or agent or b) without reference to a climatic stimulus. Similarly, Noble et al. (2015) also note two camps for defining autonomous adaptation: a) actions that can be described as bottom-up, carried out by agents without external inputs, or, b) actions that are in reaction to experienced climate impacts (stimuli) and can be considered routine or automatic. The prior is aligned more with the definitions given by the IPCC, whereas the latter aligns more with recent definitions and conceptualizations of everyday adaptation. Recent discussions on autonomous or everyday adaptations are starting to acknowledge that there may not be a perfect way to conceptualize all the complex spatial, temporal, and actor dimensions of this type of adaptation (Lindegaard and Sen 2022). Whether actions are “truly autonomous” or not will likely continue to be debated. For this study, we draw on more recent understandings of autonomous adaptation: self-organized responses, drawn from lived experiences of those affected, and without influence of external actors. We elaborate on the process by which we determined a definition for this analysis in the methods section.

The definition of planned adaptation is more clear-cut than autonomous adaptation. The TAR and AR4 glossaries define planned adaptation as “the result of a deliberate policy decision, based on an awareness that conditions have changed or are about to change” (McCarthy et al. 2001, Parry et al. 2007, Field et al. 2014, IPCC 2023). Planned adaptations are commonly initiated by governmental and other public bodies, as interventions through projects, programs, policies, or strategies (Rahman et al. 2021). They can include capacity-building interventions, provision of climate information services, development of climate-resilient infrastructure projects, and adaptation finance strategies, in addition to climate-related policies and regulations (Biagini et al. 2014). In this light, they are often conceived as “top-down.” However, planned adaptation is not always top-down and recent literature has highlighted planned responses that are led by communities or grassroot organizations, where government agencies serve as a supporter or facilitator of bottom-up actions (Yarina et al. 2019, Ajibade et al. 2022). The one sticky aspect of defining planned adaptation is its association with deliberateness or intentionality. We discuss this issue in the next section.

Dichotomous framing and its consequences for undervaluing autonomous adaptation

Since planned adaptation has often been defined as “intentional” or “deliberate” (Smit et al. 2000, Dupuis and Biesbroek 2013, Boeckmann and Rohn 2014), this has led to the frequent portrayal of autonomous as not deliberate or non-intentional, and further as reactive, short-term, low-impact, and largely ineffective (Eisenack 2012, Forsyth and Evans 2013, Preston et al. 2015). This narrow understanding of autonomous adaptation is misleading, both definitionally and contextually (Christoplos et al. 2009, Thornton and Manasfi 2010, Bonzanigo et al. 2016). It overlooks the fact that a large proportion of adaptation actions occur autonomously, at the individual and household level (intentionally or not), without formal institutional support (Ziervogel and Taylor 2008, Berrang-Ford et al. 2011, 2021, Noll et al. 2022). These actions are not only locally relevant, but often effective (Christoplos et al. 2009, Olazabal and Ruiz De Gopegui 2021, Rahman et al. 2023, Vincent 2023). Recent literature also shows that groups impacted by climate change can view autonomous adaptations as acts of sovereignty, where they draw on their own experiential knowledge and exercise agency, independent of outside intervention (Forsyth and Evans 2013, Orlove et al. 2019, Ford et al. 2020, Araos et al. 2021, Pisor et al. 2022). Despite growing recognition of its local relevance and effectiveness under some circumstances, the value of autonomous adaptation is not widely acknowledged (Füssel 2007, Goklany 2007, Klein and Juhola 2018, Rahman and Hickey 2019, Orlove et al. 2023). The definitional inconsistencies and dichotomous framing have led to normative misunderstandings of autonomous as less effective (Rahman et al. 2023, Vincent 2023) and, therefore, not as valuable for future adaptation pathways (Easterling 2007, Füssel 2007, Kala et al. 2023). Both planned and autonomous can be effective and ineffective for risk reduction, depending on the circumstances and, potentially, the ways in which they interact.

Another consequence of the dichotomous framing is that the concurrent existence of, and interaction between, autonomous and planned adaptations is often overlooked. A handful of studies examine the interaction between autonomous and planned adaptations and have shed light on the complex nature of the interplay that can occur between the two. For instance, planned adaptations, such as regulations or subsidies, may facilitate and encourage autonomous actions, but can also be at odds with autonomous local strategies, especially where cultural, traditional, and context-specific factors are ignored (Chambwera et al. 2014). This was the case, for example, in Ethiopian farming communities, where the interactions between planned and autonomous adaptation led to positive impacts at a community level by expanding autonomous options through additional resources. At the same time, the interactions also negatively impacted female-headed households for whom the time and labor demands of planned actions constrained their ability to undertake autonomous actions (Mersha and van Laerhoven 2018). Thus, the study suggests that “planned adaptation policy intervention needs to recognize the heterogeneity of actors and their autonomous adaptation to minimize the trade-offs across members of the community and to ensure [gender] equity.” In another example in Australian montane forest communities, Doherty et al. (2017) show how a hierarchy of adaptation strategies may be used to adapt to changing fire regimes over time, starting with autonomous fuel reduction strategies that evolve into more planned land use responses to cope with the increasing scale and degree of climate impacts (Doherty et al. 2017). Other recent literature emphasizes how planned adaptation can interact with and learn from Indigenous Knowledge-based and local innovation-based autonomous adaptation actions to avoid government policy-driven maladaptation (Singh et al. 2018, Wang et al. 2020, Gianelli et al. 2021, Rahman et al. 2021). Several scholars have called for broader and more nuanced examination of adaptation actions to identify how autonomous and planned actions may occur independently, and how they connect and interplay with each other (Malik and Smith 2012, Forsyth and Evans 2013, Mersha and van Laerhoven 2018, Juhola et al. 2022, Lindegaard and Sen 2022, Orlove et al. 2023). This study contributes to this literature through a systematic empirical inquiry that quantitatively and qualitatively reviews a global database on adaptation research, investigating the space between autonomous and planned types of adaptation.

METHODS

Global database of adaptation-related responses

To examine autonomous and planned adaptations, and their interplay (i.e., mixed adaptations), we use a large database of adaptation responses, collated as part of the Global Adaptation Mapping Initiative (GAMI; Berrang-Ford et al. 2021). GAMI is a global research collaboration that systematically documented adaptation-related responses in human systems described in peer-reviewed articles published between 2013 and 2019. The GAMI team comprises over 120 researchers worldwide with expertise in adaptation research and practice. A total of 1682 articles reporting on adaptation responses were included in the final GAMI dataset and were coded for 70 variables. Inclusion was predicated on four criteria: that the article focuses on human systems; documents actual adaptation (not theoretical or simulated); has a clear conceptual link to climate change (as opposed to other environmental stressors); and has a majority focus on adaptation (as opposed to mitigation or impact). Each article in the GAMI database was coded by at least two members of the coding team. Coding focused on a few fundamental questions: What climate hazards are driving responses? Who is responding? What types of responses are documented? Do adaptations have transformative potential? The final GAMI database includes answers to closed questions as well as open-ended narrative questions (these are termed as GAMI entries). The former facilitated quantitative categorical analysis (for example, descriptive statistics and summarizing studies in ordered tables), whereas the latter facilitated qualitative analysis and a contextual understanding of adaptation. More details on the screening and coding protocol of the GAMI are database discussed in Appendix 1 Section 1.1. The GAMI questions and codes used in this analysis are described in Appendix 1 Section 1.2.

Additional Coding for autonomous, planned, and mixed adaptation

The GAMI database was not systematically coded for autonomous, planned, and mixed types of adaptation, so a team of nine coders and three reconcilers (from this manuscript’s author team) conducted an additional set of coding for this study, based on the entries in the GAMI database. Following a detailed coding and reconciliation protocol (Fig. 1), each of the 1682 GAMI articles was coded for: (i) whether the response was autonomous, planned, or mixed; and (ii) details on adaptation response type or the specific action (hereafter referred to as detailed response type). Coding for autonomous, planned, and mixed followed definitions refined through an iterative process described in the next paragraph. Coders also provided an open-ended, written rationale for the classification, which often included supporting text or quotes drawn from the GAMI database entries, and specified a confidence level (low, medium, or high) based on the quantity and quality of the evidence. Coding for the detailed response type allowed for further specification of the “adaptation response type” coded in the original GAMI database, which had only four broad response types (behavioral, technological, institutional, and ecosystem-based). The detailed information on response type was coded by extracting terms directly stated in the GAMI database (e.g., climate-smart agriculture, climate information services, soil conservation, etc.) and were not specific to any one sector or actor type (details in Appendix 1, Table S1).

We specified definitions of autonomous, planned, and mixed adaptation through an iterative process. First, we drew on the literature to develop a priori definitions of autonomous and planned adaptation (e.g., Smit et al. 2000, Forsyth and Evans 2013, Rahman and Hickey 2019). Our a priori definitions are provided in Appendix 1 Section 1.1 and the a posteriori definitions, the final definitions used to code adaptation responses in GAMI entries, are provided in Table 1. We refined the definitions and examples for each of the three types through a three-phase pilot coding exercise. First, the nine coders and three reconcilers participated in a workshop to discuss and reach a common understanding of the definitions. Second, each coder coded the same batch of 25 article entries in the GAMI database. To ensure that GAMI entries provided sufficient information to accurately code, each coder also revisited the original text of the 25 articles to verify that the complete information aligned with codes based on GAMI database entries. Finally, we reconvened in a follow-up meeting to check consistency across coders. In this iterative definition setting and coding quality assurance process, we paid particular attention to the debates surrounding what is “truly” an autonomous or a planned action (as we detail in section 1.1) and deliberated the ambiguities that arise when dealing with the response and actor-type related complexities that manifest in adaptation responses. Hence, we discussed several gray areas and edge cases in order to resolve lingering discrepancies in coders’ understanding of our definitions. We also discussed how nuances in external support, formality, and autonomy often manifest in the fuzzy space between autonomous and planned. Considering the nuances of the definitions, we also decided to have each GAMI entry coded by two independent coders, followed by a code-reconciliation process (detailed in the next section).

A posteriori definitions of key words and reference examples formed the basis for our detailed coding protocol (Table 1), which guided the full coding exercise. Our a posteriori definition of autonomous adaptation is aligned with more recent understandings of autonomous adaptation (as outlined in section 1.1), which focus on self-organization, lack of external agents, and everyday experience. We do also draw, however, on the notion of autonomous adaptation as spontaneous. Overall, our detailed definitions and protocol were simply a means to conduct a consistent, empirical investigation, rather than a proposal for new definitions or framing for autonomous or planned adaptation. Our primary goal was to examine the extent to which there was an interplay between the two i.e., where and to what extent “mixed” responses were present.

During the full coding exercise, the 9 coders each coded 350–400 articles. Each entry was coded by two individuals. Following completion of all coding, three authors reconciled the entries where the two codes did not match or at least one coder had entered “unclear” or NA (n = 426 out of 1682 total articles coded; intercoder reliability of 75%). Out of the 426 articles that were reconciled, 217 articles had at least one coder suggesting that there was not enough information to code the article. So, the true errors, in terms of reliability of the autonomous, mixed, and planned coding, only occurred in 209 of the 1682 articles i.e., 12% error. For these 426 entries, the three reconcilers drew on the coders’ confidence level and open-ended justification to assign a final code. If the coding and GAMI entries provided insufficient information, the reconciler revisited the full text of the article. We excluded 94 articles during reconciliation because of insufficient information to code for adaptation type. The final database for this analysis is thus 1588 entries, each representing an academic article that documents an adaptation response in human systems.

It is important to note that though we refer to autonomous, planned, and mixed adaptation up to this point, our final database consists of codes referring to academic articles reporting on adaptation responses, not adaptation responses per se. This distinction has implications for how we interpret our results, particularly our quantitative results where the numbers refer to academic articles and not number of adaptation responses. We call attention to four key limitations of our database. First, because the GAMI database captures only peer-reviewed literature, it is more likely to identify some types of adaptation than others. For example, the GAMI database does not elucidate adaptations documented in gray literature or adaptations being realized completely autonomously with no formal documentation (Torhan et al. 2022). Second, because academic articles have their own research focus, there is likely to be information missing about the systems that are being studied. Third, the GAMI database only includes peer-reviewed articles that explicitly mention or have a clear conceptual link to climate change. This means that while certain actions could be considered adaptation, such as agroforestry, if the peer-reviewed article only labels it as a sustainability practice and not as climate adaptation, it is not included in the database. Fourth, only a few articles in the GAMI database specifically focus on the interplay of autonomous and planned adaptation, again limiting the information available. We further elaborate these limitations and their implications for our findings in the discussion. We emphasize, however, that even with these caveats, the use of a large database allows us to develop a deeper theoretical understanding of how different adaptation types occur and interact with each other across a broad range of contexts.

Quantitative and qualitative analysis

We analyzed the coded data using three different methods: basic descriptive statistics, regression analysis, and development of a qualitative typology of mixed adaptation through inductive, thematic synthesis. First, basic counts and descriptive statistics were generated for the new codes of autonomous, planned, and mixed types. We then cross-tabulated these codes with six codes from the GAMI database to examine how autonomous, planned, and mixed adaptation varied across world regions, sectors, actor types, response types, equity in implementation, and adaptation depth and scope. The GAMI database uses the latter two codes - adaptation scope and depth - to assess the transformative potential of adaptation outcomes. This is based on a typology of different dimensions of transformational change developed by Termeer et al. (2017). In addition to these six codes from the GAMI database, we also cross-tabulated against two additional codes which were created as part of other published research conducted by the GAMI author team: the inclusion of overburdened, underserved, or underrepresented groups (hereafter referred to simply as underrepresented groups) in planning and implementing adaptations (Araos et al. 2021) and types of policy implementation tools used in adaptations (Ulibarri et al. 2022). The first allows us to determine the degree to which underrepresented groups are included in autonomous, planned, and mixed adaptation responses; the latter focuses on how policy tools differ across the three. We undertook eight cross-tabulations in total. Detailed definitions of these cross-codes are provided in Appendix 1, Table S2.

Multinomial, ordered, and binary logistic regressions were used (1) to corroborate the conditions under which the three different forms of adaptation occur, as well as their transformative potential through (2) depth, (3) scope, and (4) equity considerations through inclusion of underrepresented groups. First, we conduct two multinomial logistic regression: one that predicts autonomous or planned adaptation (versus mixed adaptation; Model1a, SM Table 3); and another that predicts mixed or planned adaptation (versus autonomous adaptation; model 1b, SM Table S4), with region, sector, actor type, response type, and policy tools for implementation as independent variables. We then conduct two ordered logistic regressions, which predict whether autonomous, planned, and mixed adaptation affects the probability that adaptation responses are medium or high (as opposed to low) in depth (model 2) and scope (model 3). To assess the likelihood of targeting any underrepresented group for autonomous, mixed, and planned, we use a binary logistic regression (model 4). More information on these models can be found in Appendix 1 - Section 2.2. R packages MASS and nnet were employed for regression analyses (Ripley 2021, Ripley and Venables 2022).

Finally, we developed a typology of mixed adaptation through qualitative, thematic synthesis of the narratives and quotes associated with responses coded as mixed. Following an inductive approach, two lead authors identified emergent themes and conceptual categories from all articles coded as “mixed.” Themes were cross reviewed by two other lead authors. We did not conduct comprehensive coding for these thematic categories since many entries classified as mixed lacked sufficient detail to characterize the nuanced interaction between autonomous and planned adaptation. The qualitative typology thus includes only articles that provide sufficient detail and, therefore, serves as an illustrative description rather than as a strict categorization.

RESULTS

Prevalence and process of autonomous, planned, and mixed

We found that a significant proportion of the adaptation articles reviewed report on adaptation responses which were mixed, in that they had aspects of both autonomous and planned adaptations. Of the articles in the GAMI database (557/1588 articles), 35% were classified as containing mixed responses, 44% as autonomous (691/1588 articles), and 21% as planned (340/1588 articles). Mixed adaptations were prevalent in adaptation articles across many geographic regions and sectors, ranging from 37% of articles in Australia and Asia to 31% in Europe (Fig. 2) and from 44% in the water sector to 30% in cities (Appendix 1, Fig. S1).

In addition to prevalence, we also investigated the process through which these adaptations unfold in practice. Process was examined through the types of actors involved, types of responses undertaken, and tools used for implementing these responses. The descriptive statistics show that articles coded as containing mixed adaptation more often involve multiple actors and more often combine response type (for instance using both technological and behavioral responses; Appendix 1, Fig. S2). The regression analysis reveals that mixed adaptations are significantly and positively associated with civil society organizations, both international/multi-national (coefficient = 1.421, p < 0.001) and subnational/local (coefficient = 0.451, p < 0.05), in comparison to autonomous adaptations (Appendix 1, Table S4), indicating the prominent role of non-governmental organizations in many mixed adaptations.

Figure 3 qualitatively shows the breakdown of detailed response types under each of the three types of adaptation. Community-led actions were spread across autonomous, mixed, and planned. For some of these actions, the problem-solving and implementation comes solely from the community, while others involved collaboration with or support from local government bodies. Agriculture-related adaptations such as changes in farming practices, or soil and water conservation, were mostly coded as autonomous or mixed, as are livelihood adaptation, local and Indigenous knowledge-based adaptation, and migration responses. One potential reason for this is that these strategies are typically undertaken by impacted people on their own, and formal processes inadequately engage with local and Indigenous Knowledge systems. Within the mixed category, prominent responses include capacity-building actions and climate information services, which combine local resources and external guidance to support adaptation efforts. This finding is supported by the regression analysis, where mixed adaptation is positively and significantly associated with capacity-building (coefficient = 0.806, p<0.05), information sharing (coefficient= 1.425, p<0.001), and economic instruments (coefficient= 1.470, p<0.001) compared to autonomous adaptation (Appendix 1, Table S4). A more systematic qualitative typology of these mixed actions is presented in the section “Typology of mixed adaptation.”

Outcomes of autonomous, planned, and mixed

We also examine how adaptation outcomes (in terms of their transformative potential and equity) varied between articles coded as autonomous, mixed, and planned (Table 2). Transformative potential of outcomes is examined through depth and scope of adaptation. Depth describes the novelty of an action i.e., the degree to which an action reflects something new and different from existing norms and practices. Scope refers to the scale of the adaptation action either in terms of geographical scale, the number of people affected, the variety of sectors involved, the magnitude of the resources allocated, etc. Equity in outcomes was examined in terms of the inclusion of underrepresented groups in implementation of the adaptation action (GAMI code “equity in implementation”). We find that a majority of articles coded as containing autonomous adaptations have low depth and scope with local, largely incremental actions, while planned adaptations more often have medium to high depth and scope (Table 2; definitions of high, medium and low are in Appendix 1, Table S2). The articles coded as mixed adaptations are situated in the middle of autonomous and planned for depth and scope. The ordered logistic regression models predicting depth (Model 2) and scope (Model 3) statistically support that planned adaptation outcomes are characterized by higher depth (coefficient = 0.817, p < 0.001) and scope (coefficient = 1.03, p < 0.001) followed by mixed adaptations (depth: coefficient = 0.459, p < 0.01; scope: coefficient = 0.508, p < 0.001) as compared to the base category of autonomous adaptations. Model intercepts (Appendix 1, Table S5) indicate a likelihood of the depth and scope to be of “high” levels (intercept = 4.910, p < 0.001), regardless of the planning type.

With respect to equity, we find that 67% of articles coded as autonomous and 64% coded as mixed explicitly include at least one underrepresented group in the implementation of the adaptation response (Table 2). On the other hand, we see lower numbers for articles coded as planned adaptations, with only 43% explicitly including at least one underrepresented group. In the logistic regression (Appendix 1, Table S5), we see systematic differences in whether equity was considered, with articles coded as planned adaptations being significantly less likely to include underrepresented groups in their implementation than mixed or autonomous (-0.455, p < 0.05).

A descriptive summary and comparison of the prevalence, process, and outcomes of the three types of adaptation can be found in Table 3.

Typology of mixed adaptations

In addition to quantitative analyses, we undertook a detailed qualitative analysis of the interplay between autonomous and planned adaptation to classify mixed adaptations into four types and nine subtypes (Table 4). This typology illustrates the Autonomous-Planned Continuum and the different ways in which autonomous and planned adaptation shape each other: at times complementing and supporting, co-existing and co-developing, even constraining. While we present different types of interactions, we found that these types were not mutually exclusive, but rather have fluid boundaries with the potential to shift or evolve into other types or subtypes.

The first mixed type is found where planned interventions co-exist with autonomous adaptations. In this case, actors in a system or community employ a bundle of distinct adaptations simultaneously, with at least one autonomous and at least one planned. For example, flood-impacted households in north-central Vietnam adapted by utilizing the local government’s disaster relief in the form of rice and noodles (planned), and concurrently undertook autonomous adaptive measures to increase off-farm incomes (such as seeking jobs in urban areas; Casse et al. 2015).

The second type of mixed adaptation occurs when planned adaptation influences autonomous adaptation in several distinct ways. Sometimes, we found that planned adaptation can constrain or conflict with autonomous adaptation, limiting the range of adaptations available to actors. For instance, in Bangladesh, fishers undertook autonomous adaption to flood-driven riverbank erosion, by measures such as extending the duration of fishing hours and use of more efficient fishing gears. These adaptations were constrained when the government constructed an embankment (planned measure) which disconnected the river from nearby natural depressions, thereby impacting fish mobility and yield (Khan et al. 2018). We also found many cases where planned adaptation mobilizes or enables autonomous, through various forms of support. For example, the Climate Change and Health Adaptation Program of Canada specifically supports the First Nation and Inuit communities of Nunatsiavut and Nunavik to undertake autonomous adaptations based on Indigenous Knowledge (Richards et al. 2019). We also found cases in which planned adaptations are sustained by actors behaving autonomously, as they voluntarily continue planned measures, outside of an organized structure, and beyond the duration of a planned intervention. In one case, several measures for improved maize production promoted by the Chinese government (such as drought-tolerant varieties, technologies to manage soil moisture, and building of communal irrigation systems), were reproduced as a central component of autonomous smallholder livelihood strategies long after the programs ended (Burnham and Ma 2018).

In the third type, we find that autonomous adaptation influences planned adaptation in four distinct ways. Autonomous adaptation can constrain or conflict with planned adaptation, delaying or preventing implementation of the planned measure, or reducing its effectiveness. For instance, residents in an island community of the central Philippines opposed a planned relocation program by the municipal government that would build permanent houses for island residents on the mainland. The residents wanted to maintain their fishing-based livelihoods, and, therefore, preferred autonomous adaptations (such as building stilted houses, raising floors, and elevating belongings), over the planned relocation measure (Haynes and Tanner 2015). Autonomous adaptations can drive planned adaptation, as in cases where planned measures are undertaken specifically to support or scale-up ongoing autonomous adaptations. In Burkina Faso, local farmers autonomously initiated agricultural adaptations in the form of improved “zai pits” which are planting pits or basins that help improve soil fertility and increase water retention. Seeing the success of these autonomous adaptations, other institutions at national, local, and international scales implemented different planned adaptations, such as providing capital and dissemination of knowledge about the improved zai pits which enabled broader diffusion of the autonomous adaptation (Amaru and Chhetri 2013). Autonomous adaptations can also inform planned adaptations, in cases where planned measures take guidance from and complement autonomous actions (without providing any direct support). For example, a local NGO in Sitio Ibuan, Philippines, supported the establishment of a community food and health bank as a planned adaptation for the upland Manobo-Mamanwa ethnic minority community. This planned adaptation was informed by autonomous actions undertaken in the community called “Yuha tu Banwa," which is a traditional approach for food stocking led by women of the community (Lebel 2013). Autonomous adaptations, in some cases, evolve into planned adaptations over time, either becoming more organized through community-led institutions or institutionalized through external assistance. One example is from coastal fisheries communities in Mozambique who initiated individual adaptations such as investment in improved fishing gear, changing when and where they fish, and diversification. Over time, these individual adaptations evolved into planned adaptation as a local fishers group institutionalized these practices through negotiation among fishers, inter-community conflict resolution, and enforcement of fishing regulations (Blythe et al. 2014).

Finally, there is a fourth type, in which autonomous and planned adaptation influence each other mutually. In these cases, actors and groups adapting autonomously, and actors and groups involved with planned adaptation collaborate as equal partners. Such collaborative forms of adaptation allow for autonomy to co-exist with larger structures or organizations (these can also be referred to as co-developed or co-produced adaptations between these two types of actors/groups). For example, government researchers and farmers in the Boucle du Mouhoun region of Burkina Faso worked closely together to develop novel sorghum varieties that are climate resilient (Brocke et al. 2014). Researchers provided farmers with ex-situ seed varieties and supervised on-farm testing and seed production. Farmers seed selection tended to differ among different groups, villages, and years, indicating their agency in the participatory process. Because cases like this represent situations in which autonomous and planned adaptation influence each other relatively equally, we consider them to lie in the middle of autonomous and planned actions. Figure 4 presents these four types and nine subtypes of interactions that illustrate what we term the Autonomous-Planned Continuum that highlights the various types of influences between autonomous and planned adaptations.

DISCUSSION

Introducing and characterizing mixed adaptation

Through a large systematic assessment, this study provides evidence to reevaluate the conceptualization of adaptation as either autonomous or planned, occurring in isolation. We argue that adaptation is better described as a continuum, where a mixed type can capture the interaction between autonomous and planned adaptations. To our knowledge, this is the first large-scale study to find evidence of the prevalence of this interplay, and to illustrate the different ways in which autonomous (everyday) and planned adaptation can shape each other, both positively and negatively. Our results illustrate that, in practice, different adaptation types interact in a myriad of ways which can significantly impact the scale, equity, and transformative potential of adaptation.

A key intellectual contribution of this study is the systematic demonstration of the existence of mixed adaptation and of its presence, across regions and sectors, in reports of adaptation. A full third (35%) of peer-reviewed articles on adaptation responses globally demonstrate characteristics of both autonomous and planned adaptation. These results provide robust empirical evidence that reinforce the findings of prior, scattered case studies that have highlighted that autonomous and planned adaptation can be interlinked (Mersha and van Laerhoven 2018, Rahman and Hickey 2019, Juhola et al. 2022, Lindegaard and Sen 2022). Although the GAMI database is one of the largest extant databases on adaptation, these results nevertheless reflect only a small and biased sample of the adaptation responses occurring globally. The reported percentages do not necessarily represent proportions of autonomous, planned, and mixed adaptation on the ground. For example, the higher prevalence of planned adaptations in Europe could be because more funding is available in these regions for studies on planned adaptations. Some regions and sectors also have fewer articles than others, which likely impacts the reported prevalence. It is important to note that the primary objective of our analysis is interpretivist rather than positivist. We do not view our results as providing a precise quantification of how often each type of adaptation occurs in different regions or sectors, but rather use these results to develop a better theoretical understanding of how different types may occur. Therefore, while our database of peer-reviewed articles is neither comprehensive nor fully representative of adaptation across the world, these limitations do not impact our main results: that mixed adaptations are likely prevalent and examining their nature can help to better understand how adaptation actions actually unfold.

A second key intellectual contribution is in providing the first detailed characterization of the interplay between autonomous and planned adaptation. Our findings illustrate that the two types are not solely opposed but rather that they can influence each other both positively and negatively. As we uncovered the nine different ways in which these interactions manifested in the database, we were also struck by the number of articles where such interactions existed but had not been explicitly recognized or detailed. We suspect that such interactions are underreported, as the GAMI database (and often peer-reviewed literature more broadly) lacks detailed descriptions of how adaptation responses are implemented and how outcomes manifest (Araos et al. 2021, Berrang-Ford et al. 2021, Owen 2021). While we report our quantitative results, we interpret these numbers with caution due to potential biases and limitations of our dataset.

We also recognize that our qualitative typology of interactions between autonomous and planned adaptations is constrained by some critical limitations of our dataset. Specifically, the articles we reviewed do not explicitly seek to document interactions between autonomous and planned adaptations, information on temporality is limited, and the dataset is unlikely to capture the full-range and details of how adaptive actions are occurring in practice. For example, our typology presents types and subtypes of adaptations as static, when in fact these interactions are dynamic processes that play out over time. We further recognize that additional types and subtypes could occur outside of those analyzed here. We expect that more detailed reporting on how adaptation responses interact and develop over time will lead to the discovery of more mixed types of adaptation. There remains a need to better understand these sequential or temporally dependent pathways of adaptation. Therefore, we present this typology as a snapshot with the intention that it will be expanded and refined through future research. For these reasons, particularly at the risk of extrapolating from a non-representative data set, we choose not to provide quantitative information on the number of types and subtypes identified.

What gets missed in a dichotomy and the policy implications of a continuum

Our quantitative and qualitative analyses of the interactions between autonomous and planned adaptations also reveal the value of viewing these two adaptations as a continuum, and the significant implications for adaptation policymaking. First, our findings counter common normative assumptions about the potential outcomes of adaptation responses. It is commonly assumed that planned adaptations are more beneficial, with greater scale and transformative potential, while autonomous adaptations are only a form of short-term coping. Yet planned adaptation is failing to drive transformation at the necessary speed and scale, and often excludes underrepresented groups. Though we find that reported autonomous responses are indeed lower in depth and scope on average than planned adaptation, we also find that they are widespread and more likely to integrate the considerations of underrepresented groups planning and implementation. Our results add to a growing base of literature that highlights the importance of self-organization and autonomy in enabling transformational change (Ford et al. 2020, Juhola et al. 2022, Pisor et al. 2022, Vincent 2023). These studies have demonstrated that individual, local, traditional knowledge-based, community-based, and other adaptation types associated with autonomous adaptation, can have both individual and collective benefit (Wilson et al. 2020) and are better suited to include underserved groups and address power dynamics (Rahman et al. 2023). In several contexts, such adaptations have promoted transformative learning, built social capital and trust, and generated voluntary, non-coercive schemes (Mavhura 2017, Pisor et al. 2022). Our findings provide further depth and nuance to these studies that suggest that transformative and equitable climate change adaptation can be best achieved when planned measures support or build-on some of these autonomous measures of frontline communities rather than constrain them (Mersha and van Laerhoven 2018, Rahman et al. 2021, Lindegaard and Sen 2022). This raises the question of how the two types of adaptation can strengthen and reinforce each other, and especially how governments and multilateral organizations can support ongoing autonomous adaptation to scale-up and enhance its transformative potential.

A second key policy implication is the need to better recognize autonomous and “mixed” forms of adaptation. Presently, the Global Stocktake under the UNFCCC focuses on tracking progress on planned adaptation, or what is called “global readiness to address risk” (Adaptation Committee 2021). Such an approach emphasizes efforts from governments and multilateral organizations and risks overlooking the large proportion of adaptation that is unfolding autonomously. This shortcoming underscores the need to develop methods and indicators that capture progress on both planned and autonomous adaptation. The current work program on the Global Goal on Adaptation, also under the UNFCCC, presents an important opportunity to develop indicators that better account for the effectiveness and transformative potential of autonomous adaptation. Use of such indicators to inform global assessments will help ensure that autonomous adaptation is visible to the governments and multilateral organizations that lead many planned adaptation initiatives.

The third policy implication of our findings is the opportunity for these governments and multilateral organizations to provide technical and financial resources to support autonomous adaptation on equitable terms, as well as to scale-up and potentially learn from effective autonomous responses. In characterizing the types of interactions between autonomous and planned, particularly the cases where they support and constrain each other our results provide key insights for policymakers. We found that some governmental actors undertake planned responses with the specific objective of supporting and complementing ongoing autonomous adaptation. For example, Amaru and Chhetri (2013) detailed how NGOs and governments support adaptive cropping practices that emerge on individual farms. We also found that some actors and groups sustained and scaled autonomous adaptation responses over time. In some cases, autonomous responses evolve into highly organized, large-scale responses. For example, one study documents how individual fishers initiated autonomous adaptation measures, which were then streamlined by fishers’ groups (Johnson and Libecap 2019). These two examples of positive interaction offer potential models for policymakers seeking to amplify the positive consequences of the two approaches by taking advantage of the relative and respective strengths of each. Cases of collaboration also shed light on the conditions under which planned adaptation can provide technical and financial resources aligned with local priorities.

Our close examination of the interactions between autonomous and planned also improves understanding of the contexts in which autonomous and planned adaptation are mutually supportive. We preliminarily suggest four elements that could influence the type of interaction that emerges between the two adaptation types: compatibility of perceived pathways to achieving adaptation goals, channels of communication, actors’ flexibility, and initiative. In cases where one adaptation type constrains the other (Table 4, 2a and 3a), actors’ pathways to achieving their adaptation goals are incompatible. For example, communities resist government relocation because they perceive strengthened livelihoods as the path to effective adaptation (Jamero et al. 2017). We also see in these cases a lack of flexibility on the part of actors and no evidence of channels of communication to resolve tension. In cases of collaboration (4), we see the opposite: actors share a common pathway to achieving adaptation goals, such as where the development of resilient crops improves farmers’ livelihoods (Brocke et al. 2014) and iterative on-farm testing enabled both communication and flexibility. In the case of the bundle (1), actors pursue parallel pathways that do not necessarily overlap but also do not contradict, showing flexibility in balancing the two types in a portfolio of responses (Casse et al. 2015). In cases where autonomous and planned complement each other (2b, 2c, 3b, 3c, 3d) these elements are fuzzier. The key element is initiative: from which actors and/or institutions the response originates. While this preliminary assessment provides a starting point toward identifying the factors that influence the interplay between autonomous and planned adaptations, more detailed reporting of these interactions can help to further elucidate the contextual factors that determine when and where such types of interactions are likely to occur. Though these elements are inductive and largely hypothetical, they nevertheless help researchers and policymakers alike understand the conditions under which autonomous and planned adaptation support each other. This is a key first step to creating such conditions and ultimately contributing to more equitable and transformational adaptation overall.

CONCLUSION

Neither autonomous nor planned adaptation alone are likely to be sufficient to deal with current and projected climate change impacts. There is a need to move away from dichotomies (such as incremental versus transformational and autonomous versus planned), as they contradict the reality that effective adaptation pathways are complex and at the crossroads of multiple temporal, spatial, and social scales (Magnan et al. 2020). Our results provide valuable examples for both adaptation researchers and policymakers of the many types of interactions that can occur between autonomous and planned adaptations. We argue that understanding the respective roles, contributions of, and relationships between autonomous “everyday” adaptation and planned adaptation on a continuum is a key component in designing just, locally relevant, and scalable adaptation pathways.

LITERATURE CITED

Abass, R., A. M. Mensah, and B. Y. Fosu-Mensah. 2018. The role of formal and informal institutions in smallholder agricultural adaptation: the case of Lawra and Nandom Districts, Ghana. West African Journal of Applied Ecology 26:56–72.

Abi, M., A. Kessler, P. Oosterveer, and D. Tolossa. 2019. Adapting the current mass mobilization approach in Ethiopia to enhance its impact on sustainable land management: lessons from the Sago-kara watershed. Journal of Environmental Management 248:109336. https://doi.org/10.1016/j.jenvman.2019.109336

Adaptation Committee. 2021. Approaches to reviewing the overall progress made in achieving the global goal on adaptation. Technical paper, UNFCCC.

Adger, W., S. Agrawala, M. Mirza, C. Conde, K. O’Brien, J. Pulhin, R. Pulwarty, B. Smit, and K. Takahashi. 2007. Assessment of adaptation practices, options, constraints and capacity. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK.

Adger, W., N. W. Arnell, and E. L. Tompkins. 2005. Successful adaptation to climate change across scales. Global Environmental Change 15(2):77-86. https://doi.org/10.1016/j.gloenvcha.2004.12.005

Ajibade, I., M. Sullivan, C. Lower, L. Yarina, and A. Reilly. 2022. Are managed retreat programs successful and just? A global mapping of success typologies, justice dimensions, and trade-offs. Global Environmental Change 76:102576. https://doi.org/10.1016/j.gloenvcha.2022.102576

Amaru, S., and N. B. Chhetri. 2013. Climate adaptation: Institutional response to environmental constraints, and the need for increased flexibility, participation, and integration of approaches. Applied Geography 39:128-139. https://doi.org/10.1016/j.apgeog.2012.12.006

Araos, M., K. Jagannathan, R. Shukla, I. Ajibade, E. Coughlan de Perez, K. Davis, J. D. Ford, E. K. Galappaththi, C. Grady, A. J. Hudson, E. T. Joe, C. J. Kirchhoff, A. Lesnikowski, G. N. Alverio, M. Nielsen, B. Orlove, B. Pentz, D. Reckien, A. R. Siders, N. Ulibarri, M. van Aalst, T. Z. Abu, T. Agrawal, L. Berrang-Ford, R. B. Kerr, S. Coggins, M. Garschagen, A. Harden, K. J. Mach, A. M. Nunbogu, P. Spandan, S. Templeman, and L. L. Turek-Hankins. 2021. Equity in human adaptation-related responses: a systematic global review. One Earth 4(10):1454-1467. https://doi.org/10.1016/j.oneear.2021.09.001

Artur, L., and D. Hilhorst. 2012. Everyday realities of climate change adaptation in Mozambique. Global Environmental Change 22(2):529-536. https://doi.org/10.1016/j.gloenvcha.2011.11.013

Bawakyillenuo, S., J. A. Yaro, and J. Teye. 2016. Exploring the autonomous adaptation strategies to climate change and climate variability in selected villages in the rural northern savannah zone of Ghana. Local Environment 21(3):361-382. https://doi.org/10.1080/13549839.2014.965671

Berrang-Ford, L., J. D. Ford, and J. Paterson. 2011. Are we adapting to climate change? Global Environmental Change 21(1):25-33. https://doi.org/10.1016/j.gloenvcha.2010.09.012

Berrang-Ford, L., T. Pearce, and J. D. Ford. 2015. Systematic review approaches for climate change adaptation research. Regional Environmental Change 15:755-769. https://doi.org/10.1007/s10113-014-0708-7

Berrang-Ford, L., A. R. Siders, A. Lesnikowski, A. P. Fischer, M. W. Callaghan, N. R. Haddaway, K. J. Mach, M. Araos, M. A. R. Shah, M. Wannewitz, D. Doshi, T. Leiter, C. Matavel, J. I. Musah-Surugu, G. Wong-Parodi, P. Antwi-Agyei, I. Ajibade, N. Chauhan, W. Kakenmaster, C. Grady, V. I. Chalastani, K. Jagannathan, E. K. Galappaththi, A. Sitati, G. Scarpa, E. Totin, K. Davis, N. C. Hamilton, C. J. Kirchhoff, P. Kumar, B. Pentz, N. P. Simpson, E. Theokritoff, D. Deryng, D. Reckien, C. Zavaleta-Cortijo, N. Ulibarri, A. C. Segnon, V. Khavhagali, Y. Shang, L. Zvobgo, Z. Zommers, J. Xu, P. A. Williams, I. V. Canosa, N. van Maanen, B. van Bavel, M. van Aalst, L. L. Turek-Hankins, H. Trivedi, C. H. Trisos, A. Thomas, S. Thakur, S. Templeman, L. C. Stringer, G. Sotnik, K. D. Sjostrom, C. Singh, M. Z. Siña, R. Shukla, J. Sardans, E. A. Salubi, L. S. Safaee Chalkasra, R. Ruiz-Díaz, C. Richards, P. Pokharel, J. Petzold, J. Penuelas, J. Pelaez Avila, J. B. P. Murillo, S. Ouni, J. Niemann, M. Nielsen, M. New, P. Nayna Schwerdtle, G. Nagle Alverio, C. A. Mullin, J. Mullenite, A. Mosurska, M. D. Morecroft, J. C. Minx, G. Maskell, A. M. Nunbogu, A. K. Magnan, S. Lwasa, M. Lukas-Sithole, T. Lissner, O. Lilford, S. F. Koller, M. Jurjonas, E. T. Joe, L. T. M. Huynh, A. Hill, R. R. Hernandez, G. Hegde, T. Hawxwell, S. Harper, A. Harden, M. Haasnoot, E. A. Gilmore, L. Gichuki, A. Gatt, M. Garschagen, J. D. Ford, A. Forbes, A. D. Farrell, C. A. F. Enquist, S. Elliott, E. Duncan, E. Coughlan de Perez, S. Coggins, T. Chen, D. Campbell, K. E. Browne, K. J. Bowen, R. Biesbroek, I. D. Bhatt, R. Bezner Kerr, S. L. Barr, E. Baker, S. E. Austin, I. Arotoma-Rojas, C. Anderson, W. Ajaz, T. Agrawal, and T. Z. Abu. 2021. A systematic global stocktake of evidence on human adaptation to climate change. Nature Climate Change 11:989-1000. https://doi.org/10.1038/s41558-021-01170-y

Biagini, B., R. Bierbaum, M. Stults, S. Dobardzic, and S. M. McNeeley. 2014. A typology of adaptation actions: a global look at climate adaptation actions financed through the Global Environment Facility. Global Environmental Change 25:97-108. https://doi.org/10.1016/j.gloenvcha.2014.01.003

Blythe, J., G. Murray, and M. Flaherty. 2014. Strengthening threatened communities through adaptation: insights from coastal Mozambique. Ecology and Society 19(2):6. https://doi.org/10.5751/ES-06408-190206

Boeckmann, M., and I. Rohn. 2014. Is planned adaptation to heat reducing heat-related mortality and illness? A systematic review. BMC Public Health 14(1):1112. https://doi.org/10.1186/1471-2458-14-1112

Bonzanigo, L., D. Bojovic, A. Maziotis, and C. Giupponi. 2016. Agricultural policy informed by farmers’ adaptation experience to climate change in Veneto, Italy. Regional Environmental Change 16:245-258. https://doi.org/10.1007/s10113-014-0750-5

Brocke, K. V., G. Trouche, E. Weltzien, C. P. Kondombo-Barro, A. Sidibé, R. Zougmoré, and E. Gozé. 2014. Helping farmers adapt to climate and cropping system change through increased access to sorghum genetic resources adapted to prevalent sorghum cropping systems in Burkina Faso. Experimental Agriculture 50(2):284-305. https://doi.org/10.1017/S0014479713000616

Burnham, M., and Z. Ma. 2018. Multi-scalar pathways to smallholder adaptation. World Development 108:249-262. https://doi.org/10.1016/j.worlddev.2017.08.005

Casse, T., A. Milhøj, and T. P. Nguyen. 2015. Vulnerability in north-central Vietnam: do natural hazards matter for everybody? Natural Hazards 79(3):2145-2162. https://doi.org/10.1007/s11069-015-1952-y

Castro, B., and R. Sen. 2022. Everyday adaptation: theorizing climate change adaptation in daily life. Global Environmental Change 75:102555. https://doi.org/10.1016/j.gloenvcha.2022.102555

Chambwera, M., G. Heal, C. Dubeux, S. Hallegatte, L. Leclerc, A. Markandya, and J. Neumann. 2014. Economics of adaptation. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.

Christoplos, I., S. Anderson, M. Arnold, V. Galaz, M. Hedger, R. J. Klein, and K. le Goulven. 2009. The human dimension of climate adaptation: the importance of local and institutional issues. Commission on Climate Change and Development.

Cloutier, G., M. Papin, and C. Bizier. 2018. Do-it-yourself (DIY) adaptation: civic initiatives as drivers to address climate change at the urban scale. Cities 74:284–291. https://doi.org/10.1016/j.cities.2017.12.018

Dinarès, M., and D. Saurí. 2015. Water consumption patterns of hotels and their response to droughts and public concerns regarding water conservation: the case of the Barcelona hotel industry during the 2007-2008 episode. Documents d’Anàlisi Geogràfica 61(3):623. https://doi.org/10.5565/rev/dag.255

Doherty, M. D., S. Lavorel, M. J. Colloff, K. J. Williams, and R. J. Williams. 2017. Moving from autonomous to planned adaptation in the montane forests of southeastern Australia under changing fire regimes. Austral Ecology 42(3):309-316. https://doi.org/10.1111/aec.12437

Dupuis, J., and R. Biesbroek. 2013. Comparing apples and oranges: the dependent variable problem in comparing and evaluating climate change adaptation policies. Global Environmental Change 23(6):1476-1487. https://doi.org/10.1016/j.gloenvcha.2013.07.022

Easterling, W. E. 2007. Climate change and the adequacy of food and timber in the 21st century. Proceedings of the National Academy of Sciences 104(50):19679-19679. https://doi.org/10.1073/pnas.0710388104

Ehsan, S., R. A. Begum, K. N. Abdul Maulud, and M. S. Mia. 2022. Assessing household perception, autonomous adaptation and economic value of adaptation benefits: evidence from West Coast of Peninsular Malaysia. Advances in Climate Change Research 13(5):738-758. https://doi.org/10.1016/j.accre.2022.06.002

Eisenack, K. 2012. Archetypes of adaptation to climate change. In: Human-nature interactions in the Anthropocene. Routledge, Abingdon, Oxfordshire, UK.

Eisenack, K., and R. Stecker. 2012. A framework for analyzing climate change adaptations as actions. Mitigation and Adaptation Strategies for Global Change 17:243-260. https://doi.org/10.1007/s11027-011-9323-9

Eriksen, S., E. L. F. Schipper, M. Scoville-Simonds, K. Vincent, H. N. Adam, N. Brooks, B. Harding, D. Khatri, L. Lenaerts, D. Liverman, M. Mills-Novoa, M. Mosberg, S. Movik, B. Muok, A. Nightingale, H. Ojha, L. Sygna, M. Taylor, C. Vogel, and J. J. West. 2021. Adaptation interventions and their effect on vulnerability in developing countries: help, hindrance or irrelevance? World Development 141:105383. https://doi.org/10.1016/j.worlddev.2020.105383

Field, C. B., V. R. Barros, and Intergovernmental Panel on Climate Change, editors. 2014. Climate change 2014: impacts, adaptation, and vulnerability: Working Group II contribution to the fifth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, New York, New York, USA. https://doi.org/10.1017/CBO9781107415379

Ford, J. D., N. King, E. K. Galappaththi, T. Pearce, G. McDowell, and S. L. Harper. 2020. The resilience of Indigenous Peoples to environmental change. One Earth 2(6):532-543. https://doi.org/10.1016/j.oneear.2020.05.014

Forsyth, T., and N. Evans. 2013. What is autonomous adaption? Resource scarcity and smallholder agency in Thailand. World Development 43:56-66. https://doi.org/10.1016/j.worlddev.2012.11.010

Füssel, H.-M. 2007. Adaptation planning for climate change: concepts, assessment approaches, and key lessons. Sustainability Science 2:265-275. https://doi.org/10.1007/s11625-007-0032-y

Gianelli, I., L. Ortega, J. Pittman, M. Vasconcellos, and O. Defeo. 2021. Harnessing scientific and local knowledge to face climate change in small-scale fisheries. Global Environmental Change 68:102253. https://doi.org/10.1016/j.gloenvcha.2021.102253

Goklany, I. M. 2007. Integrated strategies to reduce vulnerability and advance adaptation, mitigation, and sustainable development. Mitigation and Adaptation Strategies for Global Change 12:755-786. https://doi.org/10.1007/s11027-007-9098-1

Haynes, K., and T. M. Tanner. 2015. Empowering young people and strengthening resilience: youth-centred participatory video as a tool for climate change adaptation and disaster risk reduction. Children’s Geographies 13(3):357-371. https://doi.org/10.1080/14733285.2013.848599

Hellin, J., B. Ratner, R. Meinzen-Dick, and S. Lopez-Ridaura. 2018. Increasing social-ecological resilience within small-scale agriculture in conflict-affected Guatemala. Ecology and Society 23(3):5. https://doi.org/10.5751/ES-10250-230305

IPCC. 2023. Climate Change 2022 - Impacts, Adaptation and Vulnerability: Working Group II Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. First edition. Cambridge University Press, Cambridge, UK.

Johansson, A., and S. Vinthagen. 2016. Dimensions of everyday resistance: an analytical framework. Critical Sociology 42(3):417-435. https://doi.org/10.1177/0896920514524604

Johnson, R. N., and G. D. Libecap. 2019. Contracting problems and regulation: the case of the fishery. Pages 345-362 in: Fisheries economics. Routledge, Abingdon, Oxfordshire, UK. https://doi.org/10.4324/9781315193182-21

Juhola, S. K., J. Käyhkö, M. Heikkinen, T.-S. Neset, and H. Tuhkanen. 2022. Governance and everyday adaptations? Examining the disconnect between planned and autonomous adaptation through justice outcomes. Ecology and Society 27(4):41. https://doi.org/10.5751/ES-13664-270441

Kala, N., C. Balboni, and S. Bhogale. 2023. Climate adaptation. VoxDevLit 7(1).

Kamal, A. S. M. M., M. Shamsudduha, B. Ahmed, S. M. K. Hassan, Md. S. Islam, I. Kelman, and M. Fordham. 2018. Resilience to flash floods in wetland communities of northeastern Bangladesh. International Journal of Disaster Risk Reduction 31:478–488. https://doi.org/10.1016/j.ijdrr.2018.06.011

Karlsson, M., and G. K. Hovelsrud. 2015. Local collective action: adaptation to coastal erosion in the Monkey River Village, Belize. Global Environmental Change 32:96–107. https://doi.org/10.1016/j.gloenvcha.2015.03.002

Kates, R. W., W. R. Travis, and T. J. Wilbanks. 2012. Transformational adaptation when incremental adaptations to climate change are insufficient. Proceedings of the National Academy of Sciences 109(19):7156-7161. https://doi.org/10.1073/pnas.1115521109

Khan, A., A. Charles, and D. Armitage. 2018. Place-based or sector-based adaptation? A case study of municipal and fishery policy integration. Climate Policy 18(1):14-23. https://doi.org/10.1080/14693062.2016.1228520

Khanal, U., C. Wilson, V.-N. Hoang, and B. L. Lee. 2019. Autonomous adaptations to climate change and rice productivity: a case study of the Tanahun district, Nepal. Climate and Development 11(7):555-563. https://doi.org/10.1080/17565529.2018.1469965

Klein, J., and S. Juhola. 2018. The influence of administrative traditions and governance on private involvement in urban climate change adaptation. Review of Policy Research 35(6):930-952. https://doi.org/10.1111/ropr.12294

Korovulavula, I., P. D. Nunn, R. Kumar, and T. Fong. 2020. Peripherality as key to understanding opportunities and needs for effective and sustainable climate-change adaptation: a case study from Viti Levu Island, Fiji. Climate and Development 12(10):888-898. https://doi.org/10.1080/17565529.2019.1701972

Koslov, L. 2019. Avoiding climate change: “agnostic adaptation” and the politics of public silence. Annals of the American Association of Geographers 109(2):568–580. https://doi.org/10.1080/24694452.2018.1549472

Laurice Jamero, M., M. Onuki, M. Esteban, X. K. Billones-Sensano, N. Tan, A. Nellas, H. Takagi, N. D. Thao, and V. P. Valenzuela. 2017. Small-island communities in the Philippines prefer local measures to relocation in response to sea-level rise. Nature Climate Change 7(8):581–586. https://doi.org/10.1038/nclimate3344

Lebel, L. 2013. Local knowledge and adaptation to climate change in natural resource-based societies of the Asia-Pacific. Mitigation and Adaptation Strategies for Global Change 18:1057-1076. https://doi.org/10.1007/s11027-012-9407-1

Leclère, D., P.-A. Jayet, and N. de Noblet-Ducoudré. 2013. Farm-level autonomous adaptation of European agricultural supply to climate change. Ecological Economics 87:1-14. https://doi.org/10.1016/j.ecolecon.2012.11.010

Lindegaard, L. S., and L. T. H. Sen. 2022a. Everyday adaptation, interrupted agency and beyond: examining the interplay between formal and everyday climate change adaptations. Ecology and Society 27(4):42. https://doi.org/10.5751/ES-13610-270442

Lipset, D. 2013. The new state of nature: rising sea-levels, climate justice, and community-based adaptation in Papua New Guinea (2003-2011). Conservation and Society 11(2):144. https://doi.org/10.4103/0972-4923.115726

Magnan, A. K., E. L. F. Schipper, M. Burkett, S. Bharwani, I. Burton, S. Eriksen, F. Gemenne, J. Schaar, and G. Ziervogel. 2016. Addressing the risk of maladaptation to climate change. WIREs Climate Change 7(5):646-665. https://doi.org/10.1002/wcc.409

Magnan, A. K., E. L. F. Schipper, and V. K. E. Duvat. 2020. Frontiers in climate change adaptation science: advancing guidelines to design adaptation pathways. Current Climate Change Reports 6(4):166–177. https://doi.org/10.1007/s40641-020-00166-8

Malik, A. S., and S. C. Smith. 2012. Adaptation to climate change in low-income countries: lessons from current research and needs from future research. Climate Change Economics 3(02):1250005. https://doi.org/10.1142/S2010007812500054

Mavhura, E. 2017. Applying a systems-thinking approach to community resilience analysis using rural livelihoods: the case of Muzarabani district, Zimbabwe. International Journal of Disaster Risk Reduction 25:248-258. https://doi.org/10.1016/j.ijdrr.2017.09.008

McCarthy, J. J., IPCC, and O. F. Canziani, editors. 2001. Climate change 2001: impacts, adaptation, and vulnerability: contribution of Working Group II to the third assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK. https://www.ipcc.ch/site/assets/uploads/2018/03/WGII_TAR_full_report-2.pdf

McMichael, C., M. Katonivualiku, and T. Powell. 2019. Planned relocation and everyday agency in low-lying coastal villages in Fiji. Geographical Journal 185(3):325-337. https://doi.org/10.1111/geoj.12312

Mersha, A. A., and F. van Laerhoven. 2018. The interplay between planned and autonomous adaptation in response to climate change: insights from rural Ethiopia. World Development 107:87-97. https://doi.org/10.1016/j.worlddev.2018.03.001

Mulligan, J., J. Harper, P. Kipkemboi, B. Ngobi, and A. Collins. 2017. Community-responsive adaptation to flooding in Kibera, Kenya. Proceedings of the Institution of Civil Engineers - Engineering Sustainability 170(5):268–280. https://doi.org/10.1680/jensu.15.00060

Muriu-Ng’ang’a, F. W., M. Mucheru-Muna, F. Waswa, and F. S. Mairura. 2017. Socio-economic factors influencing utilisation of rain water harvesting and saving technologies in Tharaka South, Eastern Kenya. Agricultural Water Management 194:150–159.https://doi.org/10.1016/j.agwat.2017.09.005

Pelling, M., K. O’Brien, and D. Matyas. 2015. Adaptation and transformation. Climatic Change 133(1):113–127.https://doi.org/10.1007/s10584-014-1303-0

Noble, I. R., S. Huq, Y. A. Anokhin, J. A. Carmin, D. Goudou, F. P. Lansigan, B. Osman-Elasha, A. Villamizar, A. Patt, and K. Takeuchi. 2015. Adaptation needs and options. Pages 833-868 in Climate Change 2014 Impacts, Adaptation and Vulnerability: Part A: Global and Sectoral Aspects. Cambridge University Press, Cambridge, UK.

Noll, B., T. Filatova, A. Need, and A. Taberna. 2022. Contextualizing cross-national patterns in household climate change adaptation. Nature Climate Change 12(1):30-35. https://doi.org/10.1038/s41558-021-01222-3

Nunn, P., and R. Kumar. 2019. Measuring peripherality as a proxy for autonomous community coping capacity: a case study from Bua Province, Fiji Islands, for improving climate change adaptation. Social Sciences 8(8):225. https://doi.org/10.3390/socsci8080225

Olazabal, M., and M. Ruiz De Gopegui. 2021. Adaptation planning in large cities is unlikely to be effective. Landscape and Urban Planning 206:103974. https://doi.org/10.1016/j.landurbplan.2020.103974

Orlove, B. 2022. The concept of adaptation. Annual Review of Environment and Resources 47(1):535-581. https://doi.org/10.1146/annurev-environ-112320-095719

Orlove, B., K. Milch, L. Zaval, C. Ungemach, J. Brugger, K. Dunbar, and C. Jurt. 2019. Framing climate change in frontline communities: anthropological insights on how mountain dwellers in the USA, Peru, and Italy adapt to glacier retreat. Regional Environmental Change 19(5):1295-1309. https://doi.org/10.1007/s10113-019-01482-y

Orlove, B., P. Sherpa, N. Dawson, I. Adelekan, W. Alangui, R. Carmona, D. Coen, M. K. Nelson, V. Reyes-García, J. Rubis, G. Sanago, and A. Wilson. 2023. Placing diverse knowledge systems at the core of transformative climate research. Ambio 52(1431–1447). https://doi.org/10.1007/s13280-023-01857-w

Owen, G. 2021. Equity and justice as central components of climate change adaptation. One Earth 4(10):1373-1374. https://doi.org/10.1016/j.oneear.2021.09.008

Parry, M. L., O. Canziani, J. Palutikof, P. Van der Linden, and C. Hanson. 2007. Climate change 2007 - impacts, adaptation and vulnerability: Working group II contribution to the fourth assessment report of the IPCC. Cambridge University Press.

Pisor, A. C., X. Basurto, K. G. Douglass, K. J. Mach, E. Ready, J. M. Tylianakis, A. Hazel, M. A. Kline, K. L. Kramer, J. S. Lansing, M. Moritz, P. E. Smaldino, T. F. Thornton, and J. H. Jones. 2022. Effective climate change adaptation means supporting community autonomy. Nature Climate Change 12(3):213-215. https://doi.org/10.1038/s41558-022-01303-x

Preston, B. L., J. Mustelin, and M. C. Maloney. 2015. Climate adaptation heuristics and the science/policy divide. Mitigation and Adaptation Strategies for Global Change 20(3):467-497. https://doi.org/10.1007/s11027-013-9503-x

Rahman, M. F., D. Falzon, S. Robinson, L. Kuhl, R. Westoby, J. Omukuti, E. L. F. Schipper, K. E. McNamara, B. P. Resurrección, D. Mfitumukiza, and Md. Nadiruzzaman. 2023. Locally led adaptation: promise, pitfalls, and possibilities. Ambio 52(1543–1557). https://doi.org/10.1007/s13280-023-01884-7

Rahman, T., A. Albizua, B. Soubry, and W. Tourangeau. 2021. A framework for using autonomous adaptation as a leverage point in sustainable climate adaptation. Climate Risk Management 34:100376. https://doi.org/10.1016/j.crm.2021.100376

Rahman, T., and G. Hickey. 2019. What does autonomous adaptation to climate change have to teach public policy and planning about avoiding the risks of maladaptation in Bangladesh? Frontiers in Environmental Science 7:2. https://doi.org/10.3389/fenvs.2019.00002

Richards, G., J. Frehs, E. Myers, and M. V. Bibber. 2019. Commentary the climate change and health adaptation program: Indigenous climate leaders’ championing adaptation efforts. Health Promotion and Chronic Disease Prevention in Canada: Research, Policy and Practice 39(4):127-130. https://doi.org/10.24095/hpcdp.39.4.03

Rickards, L., S. M. Howden, L. Rickards, and S. M. Howden. 2012. Transformational adaptation: agriculture and climate change. Crop and Pasture Science 63(3):240–250. https://doi.org/10.1071/CP11172

Ripley, B. 2021. Support functions and datasets for Venables and Ripley’s MASS R package MASS version 7.3-45.

Ripley, B., and W. Venables. 2022. nnet: feed-forward neural networks and multinomial log-linear models. https://doi.org/10.32614/CRAN.package.nnet

Ross, K. 1996. Streetwise: the French invention of everyday life. Parallax 2(1):67-75. https://doi.org/10.1080/13534649609362005

Schipper, E. L. F. 2020. maladaptation: when adaptation to climate change goes very wrong. One Earth 3(4):409–414. https://doi.org/10.1016/j.oneear.2020.09.014

Scott, J. 1986. Everyday forms of peasant resistance. Journal of Peasant Studies 13(2):5-35. https://doi.org/10.1080/03066158608438289

Singh, C., P. Dorward, and H. Osbahr. 2016. Developing a holistic approach to the analysis of farmer decision-making: implications for adaptation policy and practice in developing countries. Land Use Policy 59:329-343. https://doi.org/10.1016/j.landusepol.2016.06.041

Singh, C., S. Iyer, M. G. New, R. Few, B. Kuchimanchi, A. C. Segnon, and D. Morchain. 2021. Interrogating ‘effectiveness’ in climate change adaptation: 11 guiding principles for adaptation research and practice. Climate and Development 0(0):1-15. https://doi.org/10.1080/17565529.2021.1964937

Singh, C., A. Rahman, A. Srinivas, and A. Bazaz. 2018. Risks and responses in rural India: implications for local climate change adaptation action. Climate Risk Management 21:52-68. https://doi.org/10.1016/j.crm.2018.06.001

Smit, B., I. Burton, R. J. Klein, and J. Wandel. 2000. An anatomy of adaptation to climate change and variability. Pages 223-251 in: Societal adaptation to climate variability and change. Springer. https://doi.org/10.1007/978-94-017-3010-5_12

Smit, B., D. McNabb, and J. Smithers. 1996. Agricultural adaptation to climatic variation. Climatic Change 33:7-29. https://doi.org/10.1007/BF00140511

Strengers, Y., and C. Maller. 2017. Adapting to ‘extreme’ weather: mobile practice memories of keeping warm and cool as a climate change adaptation strategy. Environment and Planning A: Economy and Space 49(6):1432-1450. https://doi.org/10.1177/0308518X17694029

Stringer, L. C., D. D. Mkwambisi, A. J. Dougill, and J. C. Dyer. 2010. Adaptation to climate change and desertification: perspectives from national policy and autonomous practice in Malawi. Climate and Development 2(2):145-160. https://doi.org/10.3763/cdev.2010.0042

Termeer, C. J. A. M., A. Dewulf, and G. R. Biesbroek. 2017. Transformational change: governance interventions for climate change adaptation from a continuous change perspective. Journal of Environmental Planning and Management 60(4):558-576. https://doi.org/10.1080/09640568.2016.1168288

Thorn, J., T. F. Thornton, and A. Helfgott. 2015. Autonomous adaptation to global environmental change in peri-urban settlements: evidence of a growing culture of innovation and revitalisation in Mathare Valley Slums, Nairobi. Global Environmental Change 31:121-131. https://doi.org/10.1016/j.gloenvcha.2014.12.009

Thornton, T. F., and N. Manasfi. 2010. Adaptation - genuine and spurious: demystifying adaptation processes in relation to climate change. Environment and Society 1(1):132-155. https://doi.org/10.3167/ares.2010.010107

Torhan, S., C. A. Grady, I. Ajibade, E. K. Galappaththi, R. R. Hernandez, J. I. Musah-Surugu, A. M. Nunbogu, A. C. Segnon, Y. Shang, N. Ulibarri, D. Campbell, E. T. Joe, J. Penuelas, J. Sardans, M. a. R. Shah, and the G. A. M. Team. 2022. Tradeoffs and synergies across global climate change adaptations in the food-energy-water nexus. Earth’s Future 10(4):e2021EF002201. https://doi.org/10.1029/2021EF002201

Ulibarri, N., I. Ajibade, E. K. Galappaththi, E. T. Joe, A. Lesnikowski, K. J. Mach, J. I. Musah-Surugu, G. Nagle Alverio, A. C. Segnon, A. R. Siders, G. Sotnik, D. Campbell, V. I. Chalastani, K. Jagannathan, V. Khavhagali, D. Reckien, Y. Shang, C. Singh, and Z. Zommers. 2022. A global assessment of policy tools to support climate adaptation. Climate Policy 22(1):77-96. https://doi.org/10.1080/14693062.2021.2002251

Vincent, K. 2023. Development geography II: community-based adaptation and locally-led adaptation. Progress in Human Geography 47(4):604-612. https://doi.org/10.1177/03091325231166076

Wang, W., X. Zhao, J. Cao, H. Li, and Q. Zhang. 2020. Barriers and requirements to climate change adaptation of mountainous rural communities in developing countries: the case of the eastern Qinghai-Tibetan Plateau of China. Land Use Policy 95:104354. https://doi.org/10.1016/j.landusepol.2019.104354

Watson, R. T., M. C. Zinyowera, and R. H. Moss. 1997. Climate change 1995: impacts, adaptations and mitigation of climate change: scientific-technical analyses. Ecology 78(8):2644. https://doi.org/10.2307/2265930

Wilkes, A., A. P. Barnes, B. Batkhishig, A. Clare, B. Namkhainyam, Tserenbandi, N. Chuluunbaatar, and T. Namkhainyam. 2017. Is cross-breeding with indigenous sheep breeds an option for climate-smart agriculture? Small Ruminant Research 147:83–88. https://doi.org/10.1016/j.smallrumres.2016.12.036

Wilson, R. S., A. Herziger, M. Hamilton, and J. S. Brooks. 2020. From incremental to transformative adaptation in individual responses to climate-exacerbated hazards. Nature Climate Change 10(3):200-208. https://doi.org/10.1038/s41558-020-0691-6

Yarina, L., M. Mazereeuw, and L. Ovalles. 2019. A retreat critique: deliberations on design and ethics in the flood zone. Journal of Landscape Architecture 14(3):8-23. https://doi.org/10.1080/18626033.2019.1705570

Ziervogel, G., and A. Taylor. 2008. Feeling stressed: integrating climate adaptation with other priorities in South Africa. Environment: Science and Policy for Sustainable Development 50(2):32-41. https://doi.org/10.3200/ENVT.50.2.32-41