Data from: Seascape genetics and biophysical connectivity modelling support conservation of the seagrass Zostera marina in the Skagerrak-Kattegat region of the eastern North Sea

Maintaining and enabling evolutionary processes within meta-populations is critical to resistance, resilience and adaptive potential. Knowledge about which populations act as sources or sinks, and the direction of gene flow, can help to focus conservation efforts more effectively and forecast how populations might respond to future anthropogenic and environmental pressures. As a foundation species and habitat provider, Zostera marina (eelgrass) is of critical importance to ecosystem functions including fisheries. Here we estimate connectivity of Z. marina in the Skagerrak-Kattegat region of the North Sea based on genetic and biophysical modelling. Genetic diversity, population structure and migration were analysed at 23 locations using 20 microsatellite loci and a suite of analytical approaches. Oceanographic connectivity was analysed using Lagrangian dispersal simulations based on contemporary and historical distribution data dating back to the late 19th century. Population clusters, barriers and networks of connectivity were found to be very similar based on either genetic or oceanographic analyses. A single-generation model of dispersal was not realistic, whereas multi-generation models that integrate stepping-stone dispersal and extant and historic distribution data were able to capture and model genetic connectivity patterns well. Passive rafting of flowering shoots along oceanographic currents is the main driver of gene flow at this spatial-temporal scale and extant genetic connectivity strongly reflects the “ghost of dispersal past” sensu Benzie 1999. The identification of distinct clusters, connectivity hotspots and areas where connectivity has become limited over the last century is critical information for spatial management, conservation and restoration of eelgrass.

维持并实现集合种群（meta-populations）内的演化过程，对于种群的抗性、恢复力与适应潜力至关重要。明晰哪些种群充当源种群或汇种群，以及基因流的方向，可助力更高效地开展保护工作，并预测种群对未来人为活动与环境压力的响应模式。作为基础物种与栖息地提供者，大叶藻（Zostera marina，鳗草）对包括渔业在内的各类生态系统功能具有关键支撑作用。本研究依托遗传学与生物物理建模手段，对北海斯卡格拉克-卡特加特海域的大叶藻种群连通性进行了量化评估。研究团队在23个采样位点，采用20个微卫星位点（microsatellite loci）结合一系列分析方法，对种群的遗传多样性、种群结构与迁移模式进行了解析。本研究依托可追溯至19世纪末的当代与历史分布数据，通过拉格朗日扩散模拟（Lagrangian dispersal simulations）开展了海洋连通性分析。研究结果显示，基于遗传学分析与海洋学分析得到的种群聚类、连通性障碍与连通网络结构高度相似。单世代扩散模型无法准确反映实际情况，而整合了踏脚石扩散（stepping-stone dispersal）、当代与历史分布数据的多世代模型，则能够较好地复现并模拟遗传连通模式。在该时空尺度下，花茎随海洋洋流被动漂流是驱动基因流的主要机制，当前观测到的遗传连通性强烈反映了Benzie 1999所述的‘过往扩散之影（ghost of dispersal past）’这一概念。明确不同的种群聚类、连通性热点区域，以及近一个世纪以来连通性出现受限的区域，可为鳗草的空间管理、保护与修复提供关键决策信息。