Abstract
Abstract Updated distribution ranges are crucial for conservation status assessments. Comprehensive analyses combining published literature and available data on historical catches and species distribution models (SDMs) are effective tools that could improve the prediction of more realistic scenarios for some species, especially those with limited information available and facing multiple threats. The present study aimed at generating an updated distribution for the smalltail shark Carcharhinus porosus, one of the most threatened and understudied shark species of the western Atlantic Ocean. Estimates of the key areas for this species conservation based on the SDMs, and trends in catch probabilities throughout its distribution range are provided. Four algorithms (BIOCLIM, Domain, Mahalanobis, and Maximum Entropy) were used to model the distribution of C. porosus and calculate its habitat suitability based on marine environmental variables. To assess historical catch probability trends, we built a generalized linear model from published and grey literature data. This analysis was used to estimate catch probability as an indication of population trends. SDMs suggest that the northern coast of South America (NCSA) harbours the most suitable habitats for C. porosus in the world, which was expected given its historically high catch rate in this region. In addition, there was a continuously declining catch probability trend starting in the 1970s. However, the decline was smaller for the NCSA as compared with the Gulf of Mexico and the eastern South America coast. Results indicate that the NCSA should be considered the currently most important area in the world for this species conservation. Furthermore, the lack of data throughout Central and South American marine regions hampers the evaluation of extinction risk throughout its updated distribution. Thus, research in these areas is urgently required for a more comprehensive conservation status assessment.
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More From: Aquatic Conservation: Marine and Freshwater Ecosystems
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