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连通生物物理途径网络分析以提供建议用于海草(Zostera marina)恢复。

A network analysis of connected biophysical pathways to advice eelgrass (Zostera marina) restoration.

机构信息

Department of Ecoscience, Aarhus University, Frederiksborgvej 399, 4000, Roskilde, Denmark.

Mediterranean Institute for Advanced Studies IMEDEA (UIB-CSIC), C/ Miquel Marquès, 21, 07190, Esporles, Balearic Islands, Spain.

出版信息

Mar Environ Res. 2022 Jul;179:105690. doi: 10.1016/j.marenvres.2022.105690. Epub 2022 Jun 29.

Abstract

The North Sea and the Baltic Sea, including Danish coastal waters, have experienced a drastic decline in eelgrass Zostera marina coverage during the past century. Around 1900, eelgrass meadows covered about 6700 km of Danish coastal waters while the current potential distribution area is only about one third of this. In some areas, the potential distribution area is far from realized, and restoration efforts are needed to assist recovery. Such efforts are challenging, and resource-demanding and careful site selection is, therefore, important. In the present study, we aim to identify the connectivity of eelgrass populations as a basis for guiding site selection for restoration. We developed a coupled biophysical model to study eelgrass dispersal in the Kattegat. Partly submerged particles simulated the dispersal of reproductive eelgrass shoots containing seeds during the flowering season July-September. We then used network analysis to identify the potential connectivity between populations. We evaluated connectivity based on In-strength, Betweenness and Eigenvector centrality metrics and identified key areas in the Kattegat such as the central part of Aalborg Bay, to be considered to restore the network of Z. marina patches. The study proves the potentials of combining hydrodynamic models and network analysis to support marine conservation and planning, and highlights the importance of collaboration between ecologists, oceanographers, and practitioners in this endeavour.

摘要

北海和波罗的海,包括丹麦沿海水域,在过去一个世纪中,鳗草(Zostera marina)的覆盖面积急剧减少。大约在 1900 年,鳗草草地覆盖了丹麦沿海约 6700 公里的水域,而目前的潜在分布区域只有三分之一左右。在一些地区,潜在的分布区域远未实现,需要进行恢复努力以帮助恢复。这些努力具有挑战性,因此需要耗费资源并仔细选择地点。在本研究中,我们旨在确定鳗草种群的连通性,作为指导恢复地点选择的基础。我们开发了一个耦合的生物物理模型来研究卡特加特海峡的鳗草扩散。部分淹没的颗粒模拟了在 7 月至 9 月开花季节中含有种子的生殖鳗草嫩枝的扩散。然后,我们使用网络分析来识别种群之间的潜在连通性。我们基于强度、中间性和特征向量中心性指标来评估连通性,并确定卡特加特海峡的关键区域,如奥尔堡湾的中心区域,被认为是恢复鳗草斑块网络的关键区域。该研究证明了将水动力模型和网络分析相结合以支持海洋保护和规划的潜力,并强调了生态学家、海洋学家和实践者在这方面合作的重要性。

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