Offshore snapper and shark distributions are predicted by prey and area of nearby estuarine environments in the Gulf of Mexico, USA

Ba Pickens,Md Campbell,Wb Driggers,Jc Taylor

doi:10.3354/meps13925

Abstract

Seascape ecology has demonstrated that marine fishes are associated with multiscale habitat characteristics; however, most species distribution models focus on only a few predictors (e.g. depth, temperature), and this limits knowledge of essential fish habitat characteristics. Our objectives were to (1) determine habitat associations of offshore predatory marine fishes using a comprehensive suite of predictors, including area of nearby estuarine environments, (2) assess variable influence, and (3) model the spatial distribution of selected fishes in the families Carcharhinidae and Lutjanidae. We hypothesized that the concept of coastal outwelling would be evidenced by species associations with areas of nearby estuarine environments, and prey abundance would correlate with predator distributions. Species distribution models were developed for 2 snapper and 3 shark species in the northern Gulf of Mexico, USA. We used 34 multiscale predictors to evaluate how fish probability of presence or catch per unit effort (CPUE) were associated with oceanography, geography, substrate, area of nearby wetlands and estuaries, and prey abundance. Boosted regression trees, a machine-learning technique, modeled the most influential variables and predicted distributions. Model validation showed an overall accuracy of 79-86%, and CPUE models explained >40% of model deviance. Oceanographic variables, particularly mixed layer depth, were most influential and most frequently selected. As hypothesized, predatory fish distributions were predicted by prey abundances, and shark distributions were predicted by area of nearby coastal wetlands and estuaries. Our findings suggest that spatial models can provide novel insights into prey associations and linkages of marine species with nearby wetlands and estuaries.

Highlights

Knowledge of species-specific spatial distributions is fundamental to meeting conservation and management objectives (Elith & Leathwick 2009, Guisan et al 2013)
We developed a distance to shore variable from the climatologies for bottom water temperature, bottom spatial boundaries of the Submerged Lands Act salinity, mixed layer depth (MLD), and bottom cur- (Office for Coastal Management 2020), which distinrent velocity for U- and V- directions from the HYbrid guishes federal and state managed waters based on distance from shore
Boosted regression trees (BRTs) automatically test interaction terms because of the model structure, and we found that age-1 red snapper moved farther offshore where they were in close proximity to an artificial structure or where spring MLD was deeper (Fig. 4)

Summary

Introduction

Knowledge of species-specific spatial distributions is fundamental to meeting conservation and management objectives (Elith & Leathwick 2009, Guisan et al 2013). Seascape analyses have confirmed expectations that marine fish distributions are dynamic over multiple spatial and temporal scales (Mannocci et al 2017), including broad-scale effects such as offshore reef fish distribution being associated with distant mangrove and seagrass habitats (Olds et al 2012, Martin et al 2015). Depth and sea surface temperature (SST) are the most frequently utilized variables when examining the spatial distributions of marine organisms (MeloMerino et al 2020) These variables are often correlated, and temperature can define the extent of species distributions based on an optimization of physiological conditions for organisms (Kearney & Porter 2009). Modeling studies have identified the ecological requirements for marine fishes in this management context (Moore et al 2016, Pennino et al 2016), and while predator−prey overlap is expected, few studies have tested the predictive capacity of these biological predictor variables at ocean-basin scales (Robinson et al 2011, Pickens et al 2021c)

Objectives

Methods

Findings

Discussion

Conclusion