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Since the onset of fisheries science, monitoring programs have been implemented to support stock assessments and fisheries management. Here, we take inventory of the monitoring programs of the U.S. Gulf of Mexico (GOM) surveying fish and invertebrates and conduct a gap analysis of these programs. We also compile a large monitoring database encompassing much of the monitoring data collected in the U.S. GOM using random sampling schemes and employ this database to fit statistical models to then map the spatial distributions of 61 fish and invertebrate functional groups, species and life stages of the U.S. GOM. Finally, we provide recommendations for improving current monitoring programs and designing new programs, and guidance for more comprehensive use and sharing of monitoring data, with the ultimate goal of enhancing the inputs provided to stock assessments and ecosystem-based fisheries management (EBFM) projects in the U.S. GOM. Our inventory revealed that 73 fisheries-independent and fisheries-dependent programs have been conducted in the U.S. GOM, most of which (85%) are still active. One distinctive feature of monitoring programs of the U.S. GOM is that they include many fisheries-independent surveys conducted almost year-round, contrasting with most other marine regions. A major sampling recommendation is the development of a coordinated strategy for collecting diet information by existing U.S. GOM monitoring programs for advancing EBFM.

Climate change impacts physical and chemical properties of the oceans, and these changes affect the ecology of marine organisms. One important ecological consequence of climate change is the distribution shift of marine species toward higher latitudes. Here, the prevalence of nearly 150 species of fish and invertebrates were investigated to find changes in their distributions over 35 years along a subtropical coast within the Gulf of Mexico. Our results show that 90 species increased their occupancy probability, while 33 decreased (remaining species neither increase or decrease), and the ranges of many species expanded. Using rarefaction analysis, which allows for the estimation of species diversity, we show that species diversity has increased across the coast of Texas. Climate-mediated environmental variables are related to the changes in the occupancy probability, suggesting the expansion of tropical species into the region is increasing diversity., Masami Fujiwara et al. investigate the prevalence and distribution of nearly 150 fish and marine invertebrate species along the Gulf of Mexico over 35 years. They find that the expansion of tropical species into this region due to climate-mediated factors is increasing species diversity.

Climate change affects temperatures, sea level, and salinities, all of which can affect fish distributions. In order to assess the impact of climate change on the marine fish communities of Texas, fish diversity response to climate variables was modeled. Leveraging 33 years of gillnet survey data from eight major bays along the coast of Texas, asymptotic Shannon diversity was estimated for each bay, season, and year using rarefaction analysis. This allowed for the estimation of spatial, temporal, and seasonal trends in fish diversity. In order to assess the impact of climate-related variables on the fish communities of Texas, we associated the Shannon diversity index with environmental variables using a repeated measures model approach. We found significant increasing trends in fish diversity across all eight bays in fall and six of eight bays in spring. Among the variables identified as significant, temperature, salinity, and sea level stood out as most important for driving the increase in fish diversity. Our results suggest that observed increases may be attributable to changing habitat availability resulting from sea-level rise and increasing winter temperatures. Mangrove expansion and warmer winters are likely allowing for range expansion by tropical species, driving the observed increase in fish diversity.

This study investigated the contribution of shrimp stocks in supporting the production of valuable predator species. Fishery-independent data on white shrimp, brown shrimp, and selected fish species (spotted seatrout, red drum, and southern flounder) were collected from 1986 to 2014 by the Texas Parks and Wildlife Department, and converted to catch-per-unit effort (CPUE). Here, the associations between the CPUEs of fish species as predators and those of shrimp species as prey in each sampled bay and sampling season were analyzed using co-integration analysis and Partial Least Squares Regression (PLSR). Co-integration analysis revealed significant associations between 31 of 70 possible fish/shrimp pairings. The analysis also revealed discernible seasonal and spatial patterns. White shrimp in August and brown shrimp in May were associated with fish CPUEs in bays located along the lower coast of Texas, whereas white shrimp in November was more strongly associated with fish CPUEs in bays located on the upper coast. This suggests the possible influence of latitudinal environmental gradient. The results of the PLSR, on the other hand, were not conclusive. This may reflect the high statistical error rates inherent to the analysis of short non-stationary time series. Co-integration is a robust method when analyzing non-stationary time series, and a majority of time series in this study was non-stationary. Based on our co-integration results, we conclude that the CPUE data show significant associations between shrimp abundance and the three predator fish species in the tested regions. Published version