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整合遗传学、生物物理和人口统计学的见解,确定了海草保护的关键地点。

Integrating genetics, biophysical, and demographic insights identifies critical sites for seagrass conservation.

机构信息

Department of Marine Sciences - Tjärnö Marine Laboratory, University of Gothenburg, SE-45296, Strömstad, Sweden.

Department of Marine Science, University of Gothenburg, SE-40530, Gothenburg, Sweden.

出版信息

Ecol Appl. 2020 Sep;30(6):e02121. doi: 10.1002/eap.2121. Epub 2020 Apr 15.

Abstract

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.

摘要

鳗草(Zostera marina)是北半球沿海地区的一种重要基础物种,但尽管采取了管理措施,它仍在持续减少。因此,迫切需要开发新的管理工具,以便为保护最容易局部灭绝的草地和分别确定最有价值的现有和历史草地分配有限的资源,优先保护和恢复这些草地。我们评估了瑞典西海岸两个峡湾地区复杂海岸线的 377 个鳗草草地——一个地区目前健康,另一个地区则严重退化。使用拉格朗日生物物理模型(范围:100-1000 米)评估了所有草地的芽扩散,并将其用于障碍分析和聚类;还使用种群遗传方法(20 个微卫星)评估了其中一个子集(n=22),包括多样性、结构和网络连通性。这两种方法都非常一致,得出了七个亚种群分组或管理单元(MU)。这些 MU 对应于欧洲水框架指令中使用的“水体”沿海管理的适当空间尺度。通过添加基于遗传和生物物理数据的人口统计建模作为第三种方法,我们能够评估过去、现在和未来的复合种群动态,以识别特别脆弱和有价值的草地。在进一步的应用中,我们展示了如何使用生物物理方法(使用特征值摄动理论(EPT)和 20 世纪 80 年代的分布记录)来识别失去的草地,在这些草地进行恢复将最有利于当前的复合种群。这里提出的方法组合作为一个工具包,允许同时评估不同的时间和空间尺度,并根据关键遗传、人口和生态指标对特定草地进行排名。它可以应用于任何物种或地区,我们以瑞典西海岸的鳗草为例,展示了其作为管理指南的多功能性。

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