Assis Jorge, Fragkopoulou Eliza, Serrão Ester A, Araújo Miguel B
Centre of Marine Sciences (CCMAR/CIMAR LA), Universidade do Algarve, Faro, Portugal.
Faculty of Bioscience and Aquaculture, Nord Universitet, Bodø, Norway.
Sci Data. 2025 May 3;12(1):737. doi: 10.1038/s41597-025-05060-2.
Ocean currents are fundamental drivers of marine biodiversity distribution, mediating the exchange of genetic material and individuals between populations. Their effect ranges from creating barriers that foster isolation to facilitating long-distance dispersal, which is crucial for species expansion and resilience in the face of climate change. Despite the significance of oceanographic connectivity, comprehensive global estimates remain elusive, hindering our understanding of species' dispersal ecology and limiting the development of effective conservation strategies. We present the first dataset of connectivity estimates (including probability of connectivity and travel time) along the world's coastlines. The dataset is derived from Lagrangian simulations of passive dispersal driven by 21 years of ocean current data and can be combined with species' biological traits, including seasonality and duration of planktonic dispersal stages. Alongside, we provide coastalNet, an R package designed to streamline access, analysis, and visualization of connectivity estimates. The dataset provides a new benchmark for research in oceanographic connectivity, enabling a deeper exploration of the complex dynamics of coastal marine ecosystems and informing more effective conservation strategies.
洋流是海洋生物多样性分布的基本驱动因素，介导着种群间遗传物质和个体的交换。它们的影响范围从形成促进隔离的障碍到促进远距离扩散，这对于物种在面对气候变化时的扩张和恢复力至关重要。尽管海洋连通性很重要，但全球范围内的全面估计仍然难以捉摸，这阻碍了我们对物种扩散生态学的理解，并限制了有效保护策略的制定。我们展示了首个沿世界海岸线的连通性估计数据集（包括连通概率和旅行时间）。该数据集源自基于21年洋流数据驱动的被动扩散拉格朗日模拟，并且可以与物种的生物学特征相结合，包括浮游扩散阶段的季节性和持续时间。同时，我们提供了coastalNet，这是一个R包，旨在简化连通性估计的访问、分析和可视化。该数据集为海洋连通性研究提供了新的基准，能够更深入地探索沿海海洋生态系统的复杂动态，并为更有效的保护策略提供依据。
