DOI: 10.5061/dryad.cfxpnvx3v
title: How adaptive capacity shapes the Adapt, React, Cope Response to climate impacts: insights from small-scale fisheries

description: As the impacts of climate change on human society accelerate, coastal
 communities are vulnerable to changing environmental conditions. The
 capacity of communities and households to respond to these changes (i.e.,
 their adaptive capacity) will determine the impacts of climate and
 co-occurring stressors. To date, empirical evidence linking theoretical
 measures of adaptive capacity to community and household responses remains
 limited. Here we conduct a global meta-analysis examining how metrics of
 adaptive capacity translate to human responses to change (Adapt, React,
 Cope Response) in 22 small-scale fishing case studies from 20 countries
 (n=191 responses).  Using both thematic and Qualitative
 Comparative Analysis, we evaluate how responses to climate, environmental,
 and social change were influenced by domains of adaptive capacity. Our
 findings show that adaptive responses at the community level only occurred
 in situations where the community had Access to Assets, in combination
 with other domains including Diversity and Flexibility, Learning and
 Knowledge, and Natural Capital. In contrast, Access to Assets was
 nonessential for adaptive responses at the household level. Adaptive
 households demonstrated Diversity and Flexibility when supported by strong
 Governance or Institutions and were able often able to substitute Learning
 and Knowledge and Natural Capital with one another. Standardized metrics
 of adaptive capacity are essential to designing effective policies
 promoting resilience in natural resource-dependent communities and
 understanding how social and ecological aspects of communities interact to
 influence responses. Our framework describes how small-scale fishing
 communities and households respond to environmental changes and can inform
 policies that support vulnerable populations.
description: This data set was collected through a systematic review of the
 literature used to select case studies related to small-scale fisheries
 and adaptive capacity and used for a crisp set Qualitative Comparative
 Analysis. First, we conducted a Google Scholar search
 using the following strings (“small-scale fisheries” OR “artisanal
 fisheries” OR “subsistence fisheries”) and (“social ecological systems”
 “community resilience environmental change response OR adapt”) to identify
 instances of SSF responses to biological or physical stressors. The first
 set of terms allowed us to focus on the responses to stressors of SSF,
 defined by Teh and Sumaila (2013) as: (1) targeting species for household
 consumption or local markets; (2) occurring at a relatively low level of
 economic activity; (3) minimally mechanized; (4) operated nearshore; (5)
 performed by the fisher/fisher’s family; (6) minimally managed; and/or (7)
 undertaken for cultural or ceremonial purposes. The second set was used to
 find studies where empirical responses to stressors (verified through the
 case study methods) were documented for social ecological systems, as we
 were interested specifically in the adaptive capacity of intertwined
 human-natural systems.  Second, we reviewed abstracts for the initial
 1,650 search results. We excluded non peer-reviewed primary research
 articles (i.e. government reports, unpublished theses, book chapters, and
 synthesis papers), that were unrelated to SSF, or that focused on
 hypothetical adaptive capacity rather than empirical assessments of
 responses. This yielded 85 potential case studies for further evaluation.
 Third, we limited our final analysis to case studies that met two
 criteria: (1) explicitly examined empirical adaptive response of SSF
 communities or households to a specific stressor (or set of stressors);
 and (2) considered situations where at least one primary stressor was
 biological or physical. The inclusion of biological or physical stressors
 ensured that our work was relevant to climatic adaptation. Responses were
 scaled by community and household to determine if domains influenced
 adaptive capacity response differently at these two levels. This selection
 process yielded examples of responses from 22 case studies.
 Once case studies were collected, they were coded according to a
 coding database. Specifically, we coded each paper for responses to single
 stressors (or multiple stressors) into three response categories coined
 the ARC Response: Adapt (proactive planning and/or collective action);
 React (unplanned response, but some action was taken); and Cope (no
 action, a passive acceptance) (Bennett et al. 2014). We considered the ARC
 Response at two levels: community and household/individual (hereafter
 “household”). We assigned these levels according to the case study
 authors’ description. Responses at the level of an individual or household
 were assigned to the household level (e.g. individual or household choice
 to buy a new type of fishing gear). Responses at levels of organization
 broader than a household, were assigned to community (e.g. fishing
 associations that pursued aquaculture farming).  
 Building on the existing adaptive capacity literature, we also
 coded for presence or absence of four broad categories of domains
 anticipated to influence adaptive capacity: Diversity and Flexibility,
 Access to Assets; Learning and Knowledge, Governance and Institutions
 (Adger et al. 2003b; Brooks et al. 2005; Allison et al. 2009; Bennett et
 al. 2014; Whitney et al. 2017; Table 1). Additionally, we added a fifth
 category—Natural Capital—stock(s) of natural resources generating
 ecosystem goods and services (Costanza et al. 1997).
 Each of the five domains was composed of specific determinants
 (Table 1). If any determinants were reported to be present, the parent
 domain was considered present. If none of the determinants were reported,
 we considered the parent domain absent. We recorded “not available” (N/A)
 for determinants/domains that were not described by the original authors
 to assure the coders did not infer associations that were not directly
 reported. Initially, we planned to code responses at the determinant
 level, but few case studies recorded determinant detail across all
 domains. Thus, we analyzed responses at an aggregated level. 
description: Please see uploaded ReadMe file, as well as Table 1. We also
 submitted the DOIs of the publications (case studies) that we coded to
 retrieve the data used for the QCA.