Abstract
Ecosystem-based fisheries managers are increasingly seeking quantitative and spatially-explicit information on species distributions to assist with the management of fisheries and aquatic habitats. In this study, we used boosted regression trees (BRT) to build species distribution models for a highly valued coastal teleost – pink snapper (Sparidae: Chrysophrys auratus ) across rocky reefs adjacent to Australia's most urbanised coastline. BRT models for juvenile (<25 cm total length) and adult (>32 cm total length) snapper were created using a suite of environmental and habitat predictors. A surrogate for multiple anthropogenic stressors, measured as surrounding human population density, was also included in the models. The BRT model for juvenile snapper performed well (cross-validated AUC = 0.78) and identified habitat features as the most important drivers of their distribution across the region. Juvenile snapper were commonly associated with small patch reefs of low relief adjacent to large estuarine water bodies. In contrast, the performance of the BRT model for adult snapper was weak (cross-validated AUC = 0.68) but identified human population density over habitat features as the strongest predictor of adult snapper distributions. Lower occurrences of adult snapper were associated with reef habitats adjacent to large metropolitan centres, suggesting anthropogenic stressors, such as water pollution, noise and fishing may be negatively impacting adult snapper in the region. Our results highlight essential habitats for snapper populations, notably the importance of large estuaries in the coastal seascape, which are nurseries for juvenile snapper. Knowledge of the demographic habitat associations and spatial distribution of snapper across this highly urbanised coastline will support ongoing management and monitoring of snapper populations and their key habitats. • Juvenile snapper associated with small, low relief reefs adjacent to estuaries • Adult snapper negatively associated with human population density • Results suggest impacts of human stressors on the occurrence of adult snapper • Knowledge of snapper distributions and essential habitats will assist management
Highlights
Detailed information on the spatial distribution of fishes and their essential habitats, such as nursery and spawning grounds is critical for effective ecosystem-based fisheries management (Valavanis et al, 2008)
Model validation against an independent data set revealed that the optimal juvenile snapper model performed well (AUC = 0.80, true skill statistic (TSS) = 0.31), indicating that habitat associations and spatial predictions are reliable for management purposes
In this study we demonstrated the use of boosted regression trees (BRT) in assessing the habitat associations and effect of multiple human stressors on the dis tribution of a species of significant socio-economic value along Aus tralia’s most densely populated coastline
Summary
Detailed information on the spatial distribution of fishes and their essential habitats, such as nursery and spawning grounds is critical for effective ecosystem-based fisheries management (Valavanis et al, 2008). The ability of SDMs to reliably predict species distributions across unsam pled locations may offer an opportunity to cost-effectively inform management over broad spatial scales (1–100’s km) (Pittman et al, 2007). Despite demonstrating strong spatial patterns, much of this previous research has described temperate fish-habitat relationships without predicting species distributions beyond surveyed areas (Chatfield et al, 2010). In part, this is likely due to limited availability of broad-scale habitat data required to extrapolate spatial predictions. With greater access to remotely-sensed habitat information and tools to implement appropriate survey designs (Foster et al, 2020; Linklater et al, 2019; Lucieer et al, 2019) the opportunities to build SDMs for demersal temperate fishes are growing (Galaiduk et al, 2017; Monk et al, 2010; Young and Carr, 2015)
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