Abstract
This project was completed in collaboration with Dr. Brian K. Walker at NOVA Southeastern University (host organization), and Dr. Steven G. Smith of the Cooperative Institute of Marine and Atmospheric Science at the University of Miami, Rosenstiel School of Marine, Atmospheric, and Earth Science. In 2019, the Gulf of Mexico (GOM) region was responsible for 15% of nationwide commercial landings and 15% of the value contributed to the U.S. seafood industry (NMFS, 2021). Valuable fishery-dependent data on the commercial reef fish fishery are collected from GOM fishing fleets, which are sampled and validated via the Trip Interview Program (TIP). However, the current TIP survey method is currently a randomized survey where port agents opportunistically sample commercial reef fish fishing vessles, and has room for improvement (Fitzpatrick et. al., 2017). Adding spatial strata to the survey framework would result in more statistically powerful results with less resources, and incorporate better spatial representation (Smith et. al., 2011, Smith & Walker, 2024). Therefore, the goal of this project was to provide a data analysis foundation to create a stratified random design for the GOM TIP survey by defining fishing regions as spatial strata. The project goal was achieved by completing the project objectives, which were to investigate spatial patterns in reef fish species assemblages and reef fishing effort in the GOM; and to create spatial strata by characterizing fishing regions. A multivariate approach was used to analyze catch and effort data (species assemblage/CPUE and trip characteristics/fishing effort) from the Gulf States Marine Fisheries Commission (GSFMC) Fisheries Information Network (FIN) from the years 2015 2019 by gear type (vertical line and bottom longline). Sample size (n) was 52,170 fishing trips, with vertical line representing 93% (48,317) of the trips, and bottom longline making up 7% (3,853). For species assemblages, we found 6 fishing regions each in the vertical line and bottom longline fisheries, and for fishing effort, we found 10 fishing regions in the vertical line fishery and 9 in the bottom longline fishery. These results will be used to optimize future survey sampling efforts, ultimately making them more efficient.