Species distribution modelling in the Southwestern Atlantic Ocean: A systematic review and trends

Species distribution modelling (SDM) of marine organisms is widely developed for biogeography, ecology and management purposes. However, most studies continue to focus on the Global North, with fewer examples for the Global South. We carried out a bibliometric analysis to characterise aspects of studies conducting SDM for species in the Southwestern Atlantic Ocean (SWAO), focusing on the type of input data, taxonomic groups studied, focus of research, methods applied, and international collaboration between countries. Studies on megafauna and fisheries resources, based on presence-only and scenopoetic input data, applying Maximum Entropy (MaxEnt) and generalized linear/additive models (GLM/GAM) predominate. Models applied to biogeography/current species distribution were the most common, followed by biological invasion. Brazil figures as the most prolific country publishing in SWAO, and has more collaborations with the United States of America, Europe, and South Africa than with its neighbours Uruguay and Argentina, who formed a separate cluster. Research groups based on coauthorship of the 30 most frequent authors seem to be mostly isolated, with only two research groups collaborating to each other. In addition, we fit a Binomial generalised linear model (BGLM) to explore how many predictors (layers) would be sufficient to reach an excellent modelling performance based on Area Under the Curve (AUC) values. The BGLM indicated at least 5-8 layers would be necessary to have a 50 % chance of achieving excellent model performance (AUC >= 0.9), but we urge caution regarding this result and briefly discuss it. The literature review was used as a baseline to discuss aspects of our findings and highlight the need to increase SDM application in the SWAO and to strengthen international collaboration between Latin American countries. Finally, we provide recommendations on how researchers could approach some of the gaps we found.