Explaining biogeography through ocean circulation and abiotic variability

Oceanic transport and environmental variability are key for structuring marine populations and designing protection and management plans. While previous regionalizations of the Mediterranean Sea have provided valuable insights into objectively discretizing the marine seascape, they only suggest impacts on biogeography without explicitly testing them. Additionally, these studies often overlooked small-scale, high-frequency processes and focused predominantly on near-surface layers, neglecting deeper biomes.

To address these limitations, (i) we utilize a data-assimilative model and remote-sensing observations at high resolution, and (ii) we focus on two Mediterranean species with contrasting ecological traits, including adult phases exploiting both epi- and meso-pelagic layers as well as highly dispersive early-life stages. Our target species are the red mullet (Mullus barbatus), a demersal fish mainly distributed in the continental shelf, and the deep-water red shrimp (Aristeus antennatus), a pelagic marine decapod. Using passive Lagrangian particles advected within two-dimensional flow fields at several depths, we construct networks of connected areas and cluster them to identify hydrodynamic provinces. The average of these provinces reveals recurrent spatial patterns aligned with multiscale oceanographic features. In parallel, we use seawater temperature gridded data and a community detection algorithm to look for regions based on geographical proximity and temperature similarity. It produces clusters that we then average to mean abiotic regionalizations. Finally, we integrate independent observed biogeographies of the target species, and employ statistical modeling to explain these biogeographies as a combined effect of ocean circulation and abiotic clusters. This approach advances our understanding of biogeographical patterns, by deciphering two regimes depending on spatial scales, teasing apart the respective role of oceanic circulation and abiotic variability and how the latter are modulated by the target species’ ecological traits.

This robust framework helps exploring the controls of the spatial organization of marine life and could be used to predict future biodiversity reorganization in the ocean.