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利用贝叶斯网络推理研究南极洲底栖生态系统级联效应。

Benthic ecosystem cascade effects in Antarctica using Bayesian network inference.

机构信息

Department of Zoology, University of Cambridge, Downing St, Cambridge, CB2 3EJ, UK.

British Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, UK.

出版信息

Commun Biol. 2020 Oct 16;3(1):582. doi: 10.1038/s42003-020-01310-8.

DOI:10.1038/s42003-020-01310-8
PMID:33067525
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7567847/
Abstract

Antarctic sea-floor communities are unique, and more closely resemble those of the Palaeozoic than equivalent contemporary habitats. However, comparatively little is known about the processes that structure these communities or how they might respond to anthropogenic change. In order to investigate likely consequences of a decline or removal of key taxa on community dynamics we use Bayesian network inference to reconstruct ecological networks and infer changes of taxon removal. Here we show that sponges have the greatest influence on the dynamics of the Antarctic benthos. When we removed sponges from the network, the abundances of all major taxa reduced by a mean of 42%, significantly more than changes of substrate. To our knowledge, this study is the first to demonstrate the cascade effects of removing key ecosystem structuring organisms from statistical analyses of Antarctica data and demonstrates the importance of considering the community dynamics when planning ecosystem management.

摘要

南极海底生物群落是独特的,与现代等同生境相比,更接近古生代的群落。然而,人们对塑造这些群落的过程以及它们可能对人为变化做出何种反应知之甚少。为了研究关键类群的减少或消失对群落动态可能产生的后果,我们使用贝叶斯网络推断来重建生态网络,并推断类群去除的变化。在这里,我们表明海绵对南极海底生物群的动态有最大的影响。当我们从网络中去除海绵时,所有主要类群的丰度平均减少了 42%,这明显比基质的变化还要大。据我们所知,这项研究首次证明了从南极数据的统计分析中去除关键生态系统结构生物会产生级联效应,并表明在规划生态系统管理时考虑群落动态的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e80d/7567847/6539ab11a0b9/42003_2020_1310_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e80d/7567847/204e610d42a3/42003_2020_1310_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e80d/7567847/c38d0fff5b60/42003_2020_1310_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e80d/7567847/9c4ce33fb41e/42003_2020_1310_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e80d/7567847/6539ab11a0b9/42003_2020_1310_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e80d/7567847/204e610d42a3/42003_2020_1310_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e80d/7567847/c38d0fff5b60/42003_2020_1310_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e80d/7567847/9c4ce33fb41e/42003_2020_1310_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e80d/7567847/6539ab11a0b9/42003_2020_1310_Fig4_HTML.jpg

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