Abstract
IntroductionClimate change is reshaping the geographical distribution of species across the globe. In marine ecosystems, climate change creates novel challenges to an environment impacted by numerous anthropogenic stressors. Forecasting shifts in species distribution, including the expansion of non-indigenous species under climate change scenarios, is a management challenge for today’s world.MethodsWe applied Bayesian Additive Regression Tree (BART) models to investigate the environmental factors modulating the occurrence and habitat preferences of the Atlantic blue crab Callinectes sapidus Rathbun, 1896 in native and non-native areas. With BART models, we also aimed to predict its current and future distributions under two climate change scenarios (RCPs 4.5 and 8.5). BART models were performed using global occurrences of the Atlantic blue crab – recorded from 1830 to 2022 – and several environmental covariates (i.e., water temperature, salinity, current velocity, and rugosity). Model accuracy was assessed with the Area Under the Curve (AUC) and True Skill Statistics (TSS) criteria. Cross-validation experiments were made to balance accuracy prediction and uncertainty model prediction intervals.Results and discussionAUC and TSS values indicated that data validation was successful for the BART model. Water temperature was the most critical variable affecting the presence probability of the Atlantic blue crab. The BART model predicts asymmetric distribution range shifts on both sides of the Atlantic Ocean. The non-native populations will experience broader shifts in their distribution range than in the native range, and the RCP 8.5 scenario model outputs predict a wider distribution range by the end of the century. Overall, we anticipate significant ecological changes in native and non-native areas. The range expansion in native areas is often equivalent to the ecological shifts induced by invasive species, so lessons learned by ecologists and managers in non-native areas will provide actionable insights to managers in native areas.
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