Zooming in on Environmental Predictors of an Overfished Species in the Gulf of Mexico Using GIS and Classification Trees

Red snapper (RS) is one of the most important managed species in the northern Gulf of Mexico (nGOM) because of its high value to commercial and recreational fisheries. Stocks have been severely depleted and continue to be “overfished” despite management measures for their recovery. Understanding RS spatial distribution patterns and which factors are useful in predicting (un)favorable habitat may assist managers in devising more effective stock management strategies. We analyzed juvenile RS catch data collected by the NMFS fisheries-independent surveys over 21 years in the nGOM. To select and examine the environmental drivers of juvenile RS occurrence, we constructed a classification tree on presence/absence of RS using 30+ predictors, including bathymetric, biological, geographic and anthropogenic categories. We also used hotspot analysis to identify the RS high density (CPUE) sites. Because RS is an important bycatch species of the Gulf shrimp fishery, we also examined hotspot patterns under two regimes of fishing effort: high (HSE) and low shrimping effort (LSE).

Our multivariate model retained 18 environmental predictors. The most influential were bathymetric followed by geographic and biological predictors; physical and anthropogenic categories ranked lowest. Notably, complexity in predictors was related to scale and location. For instance, the “Western Coastal” cluster required the most partitions and was the only cluster where both anthropogenic variables, oil/gas platform density and shrimping effort, were useful predictors. 21% of the observations, were classified by the first split as absence of RS attributed to habitat that was either too shallow (depth strata < 13m) or too deep (> 73m). The “Western Offshore” cluster had the highest probability of predicting presence of RS. In this group, a few shallower and deeper strata, corresponding to ranges of 15-18m and 27-55m, respectively, had very high probability of RS presence (0.86), accounting for about 1/3 of the presence cases. Overall, a good agreement was achieved between the classification tree and the hotspot approaches, as both identified the western region of the nGOM as the most important habitat for RS. In addition, the hotspot analysis suggested that a change in high density sites may have occurred from HSE to LSE years. We speculate that the difference in hotspot location may have resulted from the post-Katrina reduction of shrimping effort and recommend further investigation to refine the analysis and include the most recent years (2009-2010). Our findings may provide useful insights to prioritize EFH for red snapper in the nGOM.