Modeling species distribution in response to a set of physically monitored and remotely sensed environmental predictors has been growing as an integrative tool for estimating species habitats and assessing the future consequences of anthropogenic and climate-driven perturbations. In this study, the Maximum Entropy algorithm was applied to seasonal Species Distribution Models (SDM) to identify the habitat preferences of fin whales and the potential ecological drivers, over a 20-year period in the Western and Central Mediterranean Sea. External independent datasets and null-model validations were employed to evaluate the performance of the models. The results indicate that Chlorophyll a concentration and currents, which characterize the epipelagic layer, are the most significant ecological parameters, supporting the hypothesis that prey biomass availability drives habitat suitability year-round. The distribution of suitable areas shows strong seasonal variation, with higher concentration during Spring and Summer, and a broader spatial extent during the other seasons, particularly in Fall. Furthermore, the emergence of temporally suitable hot-spots supports the hypothesis of seasonal movements. These outcomes suggest that fin whales can successfully track resource fluctuations, adjusting their distribution even in temporary habitats. The results inform conservation strategies by helping prioritize temporally and spatially sensitive spots for the species protection in the context of a rapidly changing Mediterranean Sea.

Seasonal habitat suitability and distribution patterns of Mediterranean fin whales / Papale, E.; Arcangeli, A.; Azzellino, A.; Bellingeri, M.; Bergamini, G.; Buscaino, G.; Calogero, G.; Cañadas, A.; David, L.; De Stephanis, R.; Di-Méglio, N.; Lanfredi, C.; Giacoma, C.; Gnone, G.; Mussi, B.; Pace, D. S.; Pintore, L.; Pireddu, L.; Salazar-Sierra, J. M.; Tepsich, P.; Violi, B.; Giovannini, A.. - In: ECOLOGICAL INFORMATICS. - ISSN 1574-9541. - 90:(2025), pp. 1-11. [10.1016/j.ecoinf.2025.103362]

Seasonal habitat suitability and distribution patterns of Mediterranean fin whales

Lanfredi, C.;Pace, D. S.;
2025

Abstract

Modeling species distribution in response to a set of physically monitored and remotely sensed environmental predictors has been growing as an integrative tool for estimating species habitats and assessing the future consequences of anthropogenic and climate-driven perturbations. In this study, the Maximum Entropy algorithm was applied to seasonal Species Distribution Models (SDM) to identify the habitat preferences of fin whales and the potential ecological drivers, over a 20-year period in the Western and Central Mediterranean Sea. External independent datasets and null-model validations were employed to evaluate the performance of the models. The results indicate that Chlorophyll a concentration and currents, which characterize the epipelagic layer, are the most significant ecological parameters, supporting the hypothesis that prey biomass availability drives habitat suitability year-round. The distribution of suitable areas shows strong seasonal variation, with higher concentration during Spring and Summer, and a broader spatial extent during the other seasons, particularly in Fall. Furthermore, the emergence of temporally suitable hot-spots supports the hypothesis of seasonal movements. These outcomes suggest that fin whales can successfully track resource fluctuations, adjusting their distribution even in temporary habitats. The results inform conservation strategies by helping prioritize temporally and spatially sensitive spots for the species protection in the context of a rapidly changing Mediterranean Sea.
2025
environmental satellite data; habitat suitability; presence-only models; species distribution modeling; seasonality: Balaenoptera physalus
01 Pubblicazione su rivista::01a Articolo in rivista
Seasonal habitat suitability and distribution patterns of Mediterranean fin whales / Papale, E.; Arcangeli, A.; Azzellino, A.; Bellingeri, M.; Bergamini, G.; Buscaino, G.; Calogero, G.; Cañadas, A.; David, L.; De Stephanis, R.; Di-Méglio, N.; Lanfredi, C.; Giacoma, C.; Gnone, G.; Mussi, B.; Pace, D. S.; Pintore, L.; Pireddu, L.; Salazar-Sierra, J. M.; Tepsich, P.; Violi, B.; Giovannini, A.. - In: ECOLOGICAL INFORMATICS. - ISSN 1574-9541. - 90:(2025), pp. 1-11. [10.1016/j.ecoinf.2025.103362]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1744000
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