Combining sources of high-resolution fishery-dependent data from the northeast United States to develop a catch rate time series

Abstract Fishery-dependent data, despite being a valuable resource, is often underutilized in addressing scientific inquiries comprehensively. Similar to citizen science data, it possesses significant potential to enhance our comprehension of changing species abundances and distributions. In this study, we present an illustrative example of harnessing available fishery-dependent data from the northeast United States to generate a valuable scientific output. Our approach involves combining data sets from two high-resolution fishery-dependent research and monitoring programs: (1) the Northeast Fisheries Science Center’s Study Fleet Program and (2) the Northeast Fisheries Observer Programs. By focusing on data collected from vessels employing bottom trawl gear, we construct a novel data set and establish a nominal catch per unit effort index specific to black sea bass (Centropristis striata), a commonly targeted species. To augment this data set, we incorporate additional variables pertaining to ecological and economic factors that could influence catch rates. The expanded data set is then used to develop a catch rate standardization using a generalized additive model. This study not only exemplifies how these unique, high-resolution data sets can be effectively leveraged for scientific purposes but also provides a detailed account of the methodology employed to compile these extensive data sets. We suggest that similar techniques could be applied to other species within the region or to analogous data sets from different regions. Advancing methodologies for utilizing fishery-dependent data in scientific research is a cost effective means for improving our understanding of species abundance and ecosystem dynamics. Moreover, it presents an opportunity to demonstrate the value of incorporating the knowledge and experiences of fishers and other stakeholders quantitatively into the scientific process. By tapping into the wealth of information provided by fishery-dependent data, we can make significant strides in expanding our scientific knowledge and informing sustainable management practices.