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.
Data-Poor Ecological Risk Assessment of Multiple Stressors
