The eelgrass Zostera marina is an important foundation species of coastal areas in the Northern Hemisphere, but is continuing to decline, despite management actions. The development of new management tools is therefore urgent in order to prioritize limited resources for protecting meadows most vulnerable to local extinctions and identifying most valuable present and historic meadows to protect and restore, respectively. We assessed 377 eelgrass meadows along the complex coastlines of two fjord regions on the Swedish west coast—one is currently healthy and the other is substantially degraded. Shoot dispersal for all meadows was assessed with Lagrangian biophysical modeling (scale: 100–1,000 m) and used for barrier analysis and clustering; a subset (n = 22) was also assessed with population genetic methods (20 microsatellites) including diversity, structure, and network connectivity. Both approaches were in very good agreement, resulting in seven subpopulation groupings or management units (MUs). The MUs correspond to a spatial scale appropriate for coastal management of “waterbodies” used in the European Water Framework Directive. Adding demographic modeling based on the genetic and biophysical data as a third approach, we are able to assess past, present, and future metapopulation dynamics to identify especially vulnerable and valuable meadows. In a further application, we show how the biophysical approach, using eigenvalue perturbation theory (EPT) and distribution records from the 1980s, can be used to identify lost meadows where restoration would best benefit the present metapopulation. The combination of methods, presented here as a toolbox, allows the assessment of different temporal and spatial scales at the same time, as well as ranking of specific meadows according to key genetic, demographic and ecological metrics. It could be applied to any species or region, and we exemplify its versatility as a management guide for eelgrass along the Swedish west coast.

中文翻译：

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整合遗传学，生物物理学和人口学的见识，可以确定海草保护的关键地点。

鳗草带状疱疹（Zostera）码头是北半球沿海地区的重要基础物种，但尽管采取了管理措施，但仍在继续减少。因此，迫切需要开发新的管理工具，以便优先分配有限的资源来保护最容易遭受当地物种灭绝的草甸，并确定最有价值的现有和历史悠久的草甸分别进行保护和恢复。我们在瑞典西海岸两个峡湾地区的复杂海岸线上评估了377片鳗草草甸，其中一个目前健康，另一个严重退化。用拉格朗日生物物理模型（范围：100–1,000 m）评估了所有草甸的枝条散布，并用于障碍分析和聚类；一个子集（ñ 还使用种群遗传方法（20个微卫星）评估了= 22），包括多样性，结构和网络连通性。两种方法都非常吻合，导致了七个亚人群分组或管理单位（MU）。MU对应于欧洲水框架指令中适用于沿海管理“水体”的空间尺度。添加基于遗传和生物物理数据的人口统计模型作为第三种方法，我们能够评估过去，现在和将来的种群动态，以识别特别脆弱和有价值的草地。在进一步的应用中，我们展示了如何利用特征值扰动理论（EPT）和1980年代的分布记录，利用生物物理方法来识别丢失的草地，在这些草地上的恢复将最有利于当前的种群迁移。这些方法的组合（此处以工具箱的形式提供）允许同时评估不同的时空尺度，并根据关键的遗传，人口和生态指标对特定的草地进行排名。它可以应用于任何物种或地区，我们以其多功能性作为瑞典西海岸鳗草的管理指南。