Identifying spatial patterns in fisheries bycatch

Full Title: Identifying spatial patterns in fisheries bycatch: using models to improve the stability of bycatch estimates and aid fisheries management

Participants: Michelle Sims (lead), Tara Cox, Rebecca Lewison

Fisheries bycatch, or incidental take, is a pressing conservation and Fisheries management issue. Identifying spatial patterns of bycatch is an important element in managing and mitigating bycatch occurrences. Because bycatch events are rare and events and fishing effort are highly variable in space and time, maps of raw bycatch rates, the ratio of bycatch to fishing effort, can be misleading. Here we show how bycatch mapping can be enhanced through the use of Bayesian hierarchical spatial models.  We compare model-based estimates of bycatch rates to raw rates.  The model-based estimates were more precise and fit the data well.  Using these results, we demonstrate the utility of this approach for providing information to managers on bycatch probabilities and cross-taxa bycatch comparisons.  To illustrate this approach, we present an analysis of bycatch data from the US gillnet fishery in the Northwest Atlantic.  The goals of this analysis are to produce more reliable estimates of bycatch rates, assess similarity of spatial patterns between taxa and identify areas of elevated risk of bycatch.