From connection to conservation: temporal trends in coastal populations connectivity and implications for marine spatial planning

Human activities and climate change increasingly threaten biodiversity and marine resources, demanding effective management programs that can adapt over time. A critical aspect of this effort is understanding population connectivity, i.e. the exchange of individuals among fragmented subpopulations. Population connectivity is a crucial process supporting the persistence, regeneration, and evolution of species distribution, with significant implications for ecosystem function and biodiversity. Connectivity data are essential for setting, implementing, and monitoring conservation goals, especially in marine spatial planning. In coastal ecosystems, connectivity is primarily driven by the dispersal of pelagic larvae, influenced by ocean currents and species-specific life-history traits (e.g., spawning periods, larval duration). These factors are environmentally sensitive and vary over short timescales, due to meteorological and life-history stochasticities, and on longer timescales because of climate-driven changes. Yet, the extent of the resulting connectivity variations on different timescales and our ability to anticipate them are largely unknown. Indeed, connectivity assessments often rely on snapshot studies that may not capture temporal variability.

Our study investigates the robustness of empirical and simulated population connectivity estimates in the face of a shifting climate. Using Mediterranean gorgonians as models, we integrate connectivity estimated from (1) the genetic analysis of hundreds of samples collected following a time-structured sampling strategy (historical samples and per-cohort samples from 2022) and (2) biophysical larval dispersal simulations based on a very-high-resolution (~500m) hydrodynamical model and including non-sampled populations. We compare the inter-annual variability of connectivity over the recent past (estimated between 2001 and today) and its amplitude with a longer-term trend (measured on an interdecadal scale). This approach enables the distinction between the impact of ongoing climate-driven changes and the natural variability arising from the stochasticity of the influencing parameters. Overall, this work aims to establish a baseline for predicting how frequently connectivity estimates should be updated. By sharing these results with French and Italian policymakers, we will directly contribute to the objectives of the EU Biodiversity Strategy for 2030.