Coastal oceanographic connectivity estimates at the global scale

Motivation Oceanographic connectivity driven by ocean currents is critical in determining the distribution of marine biodiversity. It mediates the genetic and individual exchange between populations, from structuring dispersal barriers that promote long-term isolation to enabling long-distance dispersal that underpins species expansion and resilience against climate change. Despite its significance, comprehensive estimates of oceanographic connectivity on a global scale remain unavailable, while traditional approaches, often simplistic, fail to capture the complexity of oceanographic factors contributing to population connectivity. This gap hinders a deeper understating of species’ dispersal ecology, survival, and evolution, ultimately precluding the development of effective conservation strategies aimed at preserving marine biodiversity. To address this challenge, we present a comprehensive dataset of connectivity estimates along the world’s coastlines, known for their rich marine biodiversity. These estimates are derived from a biophysical modelling framework that combines high-resolution ocean current data with graph theory to predict multi-generational stepping-stone connectivity. Alongside, we provide coastalNet, an R package designed to streamline access, analysis, and visualization of connectivity estimates. This tool enhances the utility and application of the data, adhering to the FAIR principles of Findability, Accessibility, Interoperability, and Reusability. The dataset and package set a new benchmark for research in oceanographic connectivity, allowing a better exploration of the complex dynamics of coastal marine ecosystems. Main types of variables contained Pairwise connectivity estimates (probability and time) between coastal sites. Spatial location and grain Global, equal-area hexagons with 8.45 km edge length. Time period and grain Daily, from 2000 to 2020. Major taxa and level of measurement Coastal marine biodiversity. Software format A package of functions developed for R software.