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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.

a b s t r a c t Delineation of stock structure is important for understanding the ecology and management of many fish populations, particularly those with wide-ranging distributions and high levels of harvest. Southern flounder (Paralichthys lethostigma) is a popular commercial and recreational species along the southeast Atlantic coast and Gulf of Mexico, USA. Recent studies have provided genetic and otolith morphology evi- dence that the Gulf of Mexico and Atlantic Ocean stocks differ. Using age and growth data from four states (Texas, Alabama, South Carolina, and North Carolina) we expanded upon the traditional von Bertalanffy model in order to compare growth rates of putative geographic stocks of southern flounder. We improved the model fitting process by adding a hierarchical Bayesian framework to allow each parameter to vary spatially or temporally as a random effect, as well as log transforming the three model parameters (L∞, K, and t0). Multiple comparisons of parameters showed that growth rates varied (even within states) for females, but less for males. Growth rates were also consistent through time, when long-term data were available. Since within-basin populations are thought to be genetically well-mixed, our results suggest that consistent small-scale environmental conditions (i.e., within estuaries) likely drive growth rates and should be considered when developing broader scale management plans.