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Ecological Risk Assessment is a formal process widely applied to terrestrial, marine, and freshwater ecosystems to evaluate the likelihood of adverse ecological effects occurring as a result of exposure to natural or anthropogenic stressors. For many species, data is sparse and semi-quantitative methodologies provide valuable insight for ecosystem management. Recent statistical developments have improved the quality of these analyses yet a rigorous theoretical framework to assess the cumulative impact of multiple stressors is lacking.We present EcoRAMS, a web application and open-source software module that provides easy-to-use, statistically-robust ecological risk assessments of multiple stressors in data-poor contexts. The software receives attribute scores for two variables (e.g. exposure-sensitivity, productivity-susceptibility, severity-likelihood) via CSV templates and outputs results according to a probabilistic metric of risk.We demonstrate comparative results across a range of assumptions, using simulated and empirical datasets including up to five stressors. Accounting for multiple stressors even when data is limited provides a more detailed analysis of risk that may otherwise be understated in single stressor analyses.This application will allow quantification of risk across data-poor contexts for which statistical results have been previously unavailable. The web app format of EcoRAMS.net lowers the barrier of use for practitioners and scientists at any level of statistical training.

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 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.

Small-scale fishing (SSF) communities face numerous current and future climate-related stressors. While many studies address the perceived resilience or latent adaptive capacity of these communities to such stressors, little existing work analyzes the observable responses of coastal communities to documented or ongoing climate-related stressors. Here we provide an analytical framework for exploring community responses to distinct stressors, as well as the attributes of communities that mediate different response types. We provide an example application of this framework to display the utility of this approach in categorizing observed community responses documented in existing literature. Application of this framework to the broader and growing body of literature describing responses of SSF communities to environmental perturbations will allow for greater insight into the characteristics of both communities and stressors that drive adaptive, reactive, or coping responses.