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.

维持并激活集合种群（meta-populations）内的演化进程，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，能够帮助更高效地聚焦保护工作，并预测种群对未来人为与环境压力的响应方式。作为关键建群种与栖息地提供者，大叶藻（Zostera marina，鳗草）对包括渔业在内的生态系统功能具有至关重要的意义。本研究基于遗传学与生物物理模型，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评估。研究团队利用20个微卫星位点（microsatellite loci）与一系列分析方法，对23个采样点的遗传多样性、种群结构与基因迁移情况展开分析。基于可追溯至19世纪末的当代与历史分布数据，研究人员采用拉格朗日扩散模拟（Lagrangian dispersal simulations）对海洋连通性进行分析。无论是基于遗传学还是海洋学分析，所得到的种群集群、连通性障碍与连通网络均高度相似。单世代扩散模型并不符合实际情况，而整合了踏脚石扩散（stepping-stone dispersal）、现存与历史分布数据的多世代模型，则能够很好地拟合并还原遗传连通性模式。在该时空尺度下，花苗随海洋洋流被动漂流是基因流的主要驱动因素，而现存的遗传连通性强烈反映了本齐（Benzie）1999年提出的"扩散过往之幽灵（ghost of dispersal past）"效应。明确划分种群集群、连通性热点区域，以及近一个世纪以来连通性受限的区域，对于鳗草的空间管理、保护与修复工作而言是至关重要的信息。