%A Turner,Sara M. %A Hare,Jonathan A. %A Manderson,John P. %A Hoey,John J. %A Richardson,David E. %A Sarro,Christopher L. %A Silva,Ryan %D 2017 %J Frontiers in Marine Science %C %F %G English %K Cooperative research,species distribution models,bycatch avoidance,river herring,Oceanographic forecast %Q %R 10.3389/fmars.2017.00116 %W %L %M %P %7 %8 2017-May-01 %9 Original Research %+ Sara M. Turner,Massachusetts Division of Marine Fisheries,New Bedford, MA, USA,Sara.Turner@state.ma.us %# %! Evaluation of an Incidental Catch Distribution Forecast %* %< %T Cooperative Research to Evaluate an Incidental Catch Distribution Forecast %U https://www.frontiersin.org/articles/10.3389/fmars.2017.00116 %V 4 %0 JOURNAL ARTICLE %@ 2296-7745 %X Concern over incidental catches in commercial fisheries has been increasing, and while simple mitigation strategies have been effective, few effective mitigation strategies have been established for more complex species interactions. Incidental catches of alewife (Alosa pseudoharengus) and blueback herring (A. aestivalis) in the commercial Atlantic herring (Clupea harengus) fishery have received substantial attention on the Northeast U.S. continental shelf, despite an existing bycatch avoidance program. This study evaluates the utility of existing species distribution forecasts to predict river herring catches in the southern New England small mesh bottom trawl Atlantic herring fishery, with the ultimate goal of incorporating incidental catch forecasts into the bycatch avoidance program. Commercial Atlantic herring bottom trawl vessels assisted with field-based evaluation of alewife, blueback herring, and Atlantic herring species distribution forecast models. Vessels were equipped with conductivity, temperature, and depth probes, and sampling occurred throughout the fishery season (January–March). Locations of expected low and high forecasted incidental catches were sampled, as well as locations the captain expected to find low and high incidental catches. This allowed us to sample within the spatial area the fishery occurs, and to evaluate the forecasted conditions, and predictions, at the spatial scale of the fishery. Catch differences between high and low probability stations were small and variable, as were differences in modeled probability of species presence. No differences were observed between observations at model-predicted stations and captain-selected stations. The sampling provided a better understanding of the potential effectiveness of distribution forecasts for further reducing incidental catches. Existing models have limited use at the spatial scale of this fishery, but could be improved by developing models with fishery-dependent data. Collaborations between researchers, managers, and the Atlantic herring commercial fleet have improved relationships between the groups, and continued collaboration in the development and evaluation of incidental catch reduction tools is key for further reducing incidental catches.