Ecosystem Risk Assessment Using the Comprehensive Assessment of Risk to Ecosystems (CARE) Tool

Willow Battista, Rod Fujita and Kendra Karr, Environmental Defense Fund, Oceans Program, San Francisco, CA, United States
Abstract:
Effective Ecosystem Based Management requires a localized understanding of the health and functioning of a given system as well as of the various factors that may threaten the ongoing ability of the system to support the provision of valued services. Several risk assessment models are available that can provide a scientific basis for understanding these factors and for guiding management action, but these models focus mainly on single species and evaluate only the impacts of fishing in detail. We have developed a new ecosystem risk assessment model – the Comprehensive Assessment of Risk to Ecosystems (CARE) – that allows analysts to consider the cumulative impact of multiple threats, interactions among multiple threats that may result in synergistic or antagonistic impacts, and the impacts of a suite of threats on whole-ecosystem productivity and functioning, as well as on specific ecosystem services. The CARE model was designed to be completed in as little as two hours, and uses local and expert knowledge where data are lacking. The CARE tool can be used to evaluate risks facing a single site; to compare multiple sites for the suitability or necessity of different management options; or to evaluate the effects of a proposed management action aimed at reducing one or more risks. This analysis can help users identify which threats are the most important at a given site, and therefore where limited management resources should be targeted. CARE can be applied to virtually any system, and can be modified as knowledge is gained or to better match different site characteristics. CARE builds on previous ecosystem risk assessment tools to provide a comprehensive assessment of fishing and non-fishing threats that can be used to inform environmental management decisions across a broad range of systems.