A data-limited method for assessing cumulative fishing risk on bycatch

To assess fishing effects on data-poor species, impact can be derived from spatial overlap between species distribution and fishing effort and gear catchability. Here, we enhance the existing sustainability assessment for fishing effect method by estimating gear efficiency and heterogeneous density from sporadic catch data. We apply the method to two chondrichthyan bycatch species, Bight Skate and Draughtboard Shark in Australia, to assess cumulative fishing mortality (F-cum) from multiple fisheries. Gear efficiency is estimated from a Bayesian mixture distribution model and fish density is predicted by a generalized additive model. These results, combined with actual fishing effort, allow estimation of fishing mortality in each sector and subsequently, the F-cum. Risk is quantified by comparing F-cum with reference points based on life history parameters. When only the point estimates were considered, our result indicates that for the period 2009 and 2010 Bight Skate caught in 14 fisheries was at high cumulative risk (F-cum >= F-lim) while Draughtboard Shark caught by 19 fisheries was at low cumulative risk (F-cum <= F-msy). Because of the high cost of conducting cumulative risk assessments, we recommend examining the distribution of fishing effort across fisheries before carrying out the assessments.