Climate vulnerability assessments (CVAs) provide a framework for systematically evaluating climate impacts over a broad range of species to allow for a deeper understanding of the kinds of risks a fishery faces. The CVA method detailed here allows for analysis with existing information, thus making it more accessible in data-limited settings. Most CVA methods (like other risk assessments) combine the exposure of a species to climate change and decadal variability and the sensitivity of species to these stressors. These two components are then combined to estimate an overall vulnerability for each species in the assessment. Quantitative data are used when available, but qualitative information and expert opinion are used when quantitative data is lacking. The US Northeast Climate Vulnerability Assessment developed by scientists at the National Oceanographic and Atmospheric Administration (NOAA) serves as a useful example for how to conduct a regional climate vulnerability assessment (Hare et al. 2016).
We have developed a modified spreadsheet version of this NOAA CVA that can more easily be applied in data-limited and capacity-limited contexts. This spreadsheet tool draws on the Hare methodology to generate overall sensitivity attribute and exposure factor scores using a logic rule formula, while replacing the time-consuming and data-intensive process of quantifying expert certainty in each sensitivity attribute and exposure factor with a more qualitative collaborative scoring process. The spreadsheet also restructures the exposure scoring formula used in the NOAA CVA to differentiate separate scoring components for a magnitude of change score in the region and a spatial overlap score for each species. This differentiation enables users to more rapidly score the likely consequences of the various climate change components that will impact a given region on each species therein and further quantifies the Hare methodology to balance the omission of expert certainty.
For each exposure factor, we provide an overview definition and factor-specific scoring “bin” language to enable accurate scoring without requiring precision. In addition, a more comprehensive list of globally-possible exposure factors is provided, and users are recommended to tailor their selected exposure factors to those relevant in their region of study.
To further improve user clarity around the sensitivity attributes and exposure factors, each variable in the spreadsheet is organized into a group category.
Lastly, the spreadsheet quantifies the directional effect of climate change score by taking the average of individual variable scores.
The spreadsheet tool, as well as the manuscript for the full NOAA analysis by Hare et al. (2016), are provided here, in addition to a primer on how to use our CVA spreadsheet. An example version of the CVA spreadsheet is also provided, prepopulated with three species common to the Caribbean region.