Trends in marine species distribution models: a review of methodological advances and future challenges

Correlative species distribution models (SDMs) are quantitative tools in biogeography and macroecology. Building upon the ecological niche concept, they correlate environmental covariates to species presence to model habitat suitability and predict species distributions. Since their development, SDMs have undergone substantial advances in their predictive accuracy, benefiting from increased data availability, advanced machine learning algorithms, novel data integration procedures, refined model validation techniques, and incorporation of biotic predictors. Although initially applied in terrestrial systems, these models are now also widely used in the marine environment, recognized for their value in conservation planning, fisheries management, and understanding species responses to climate variability and change. Despite their increased application, SDMs face unique challenges when applied in the marine environment. These challenges include the three-dimensional complexity of marine ecosystems, the availability of environmental covariates across suitable spatial and temporal scales, the dynamic properties of these covariates, and unique dispersal patterns and mobility traits of marine species. Here, we review recent methodological advances and emerging trends in marine SDMs. We highlight three-dimensional modelling approaches that capture species distributions below the sea surface and assess the importance of temporal resolution, particularly for modelling highly mobile marine species in dynamic marine environments. Further, we discuss the expansion in the types of occurrence data being used, including fishery-dependent and fishery-independent sources, citizen science contributions, and satellite tracking data, along with the methods used to address their associated biases. We also explore and discuss novel methodologies for environmental data collection, such as remote-sensing technologies and numeric ocean models, considering the existing limitations in spatial and temporal resolution. Together, our review synthesizes methodological innovations, highlights ongoing challenges, and discusses emerging trends within the extensive literature on marine SDMs.