Potential spatial mismatches between marine predators and their prey in the Southern Hemisphere in response to climate change [Dataset]

This work was supported by MCIN/AEI/10.13039/501100011033 and NextGenerationEU/PRTR, Grant no. FJC2020-043762-I to M.B; J.O. was supported by Universitat de Barcelona through the PREDOCS-UB grant (2021); A.F.-A. was supported by Ministerio de Ciencia e Innovación, Grant no. PRE2021-099287 from the project ProOeans (PID2020-118097RB-I00); F.R. was supported by the Ramón y Cajal program (RYC2020-030078-I); D.M. was supported by the CIDEGENT program of the Generalitat Valenciana (CIDEGENT/2021/058); This research was also supported by the projects SOSPEN (PID2021-124831OA-I00), SEASentinels (CNS2022-135631) and ProOceans (PID2020-118097RB-I00). This research contributes to the objectives of Q-MARE (a PAGES working group). This work acknowledges the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S). This research is also part of the Integrated Marine Ecosystem Assessments (iMARES) research group funded by Agència de Gestió d'Ajuts Universitaris i de Recerca (Generalitat de Catalunya) Grant no. 2021 SGR 00435

1. Scripts classified in the following folders: 1. Presences and Absences: Scripts for creating pseudo-absence points for each study area (other data is also included, e.g., bathymetry). 2. Environmental Data: Scripts for extracting, cleaning, and preparing environmental data for analysis. 3. Fitting: Scripts used to fit species distribution models, calculate the cutoff, and analyze spatial autocorrelation. 4. Predict: Scripts for making predictions based on the fitted models. 2. Datasets: Occurrence Data: The datasets containing species occurrence records after cleaning. Bas_etal_2025/1. Presences and absences/1. NZAU/CSV_ocurrences_NZAU/ Bas_etal_2025/1. Presences and absences/2. South_America/CSV_ocurrences_South_America/ Bas_etal_2025/1. Presences and absences/3. Southern_Africa/CSV_ocurrences_Southern_Africa/ Pseudo-absence Data: The datasets created after the generation of pseudo-absences for modeling species distributions. Bas_etal_2025/1. Presences and absences/1. NZAU/CSV_pseudoabsences_NZAU/ Bas_etal_2025/1. Presences and absences/2. South_America/CSV_pseudoabsences_South_America/ Bas_etal_2025/1. Presences and absences/3. Southern_Africa/CSV_pseudoabsences_Southern_Africa/ Environmental Data: The datasets consisting of the extraction of the environmental variables for each occurrence and pseudo-absence. Bas_etal_2025/2. Environmental data/Dataset after 6. extract_environmentalData_SH_SDM/NZAU/ Bas_etal_2025/2. Environmental data/Dataset after 6. extract_environmentalData_SH_SDM/South_America/ Bas_etal_2025/2. Environmental data/Dataset after 6. extract_environmentalData_SH_SDM/Southern_Africa/

Peer reviewed