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Quantifying change in pelagic plankton network stability and topology based on empirical long-term data

机译:基于经验长期数据定量上层浮游生物网络稳定性和拓扑结构的变化

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摘要

Over the last 34 years, Lake Muggelsee has experienced concurrent warming and nutrient reduction. While the effects of environmental change on single taxonomic or physical-chemical variables have been relatively well researched in isolation, understanding how environmental change propagates through the ecological network remains a major challenge. Capitalizing on the long-term monitoring program of the German Long-Term Ecosystem Research Network site Lake Muggelsee (1979-ongoing), we identified three time periods (1979-1995; 1996-2005; 2006-2013) which differed significantly in phytoplankton biomass and relative plankton community composition. Using multivariate first order autoregressive (MAR1) modeling on 13 pelagic plankton groups and four abiotic variables, we quantified interaction networks and indicators of stability and centrality for each period. Our results suggested that the Muggelsee network was bottom-up regulated in all periods and that stability increased over time. Moreover, in all three networks, non-trophic and indirect interactions appeared to be as commonly present as trophic and direct interactions. Using network centrality measures of betweenness and closeness, we identified keystone plankton groups and groups particularly responsive to environmental change based on variation in centrality ranks over time. Given a more comprehensive understanding of the interaction network at hand, MAR1 model-derived stability and centrality measures may potentially be used as integrated ecological indicators to monitor changes in stability of lake ecosystems and to identify particularly vulnerable components of the network. (C) 2015 Elsevier Ltd. All rights reserved.
机译:在过去的34年中,Muggelsee湖经历了同时变暖和营养减少的问题。尽管对环境变化对单个分类学或物理化学变量的影响进行了比较充分的研究,但了解环境变化如何通过生态网络传播仍然是一个重大挑战。利用德国长期生态系统研究网络站点Muggelsee湖(1979-进行中)的长期监测计划,我们确定了三个时期(1979-1995; 1996-2005; 2006-2013),这两个时期的浮游植物生物量差异很大和相对的浮游生物群落组成。使用多变量一阶自回归(MAR1)对13个浮游浮游生物组和四个非生物变量进行建模,我们量化了每个时期的相互作用网络以及稳定性和中心性指标。我们的结果表明,Muggelsee网络在所有时期都受到自下而上的监管,并且稳定性随着时间的推移而增加。此外,在所有三个网络中,非营养性和间接相互作用似乎与营养性和直接相互作用一样普遍。通过使用网络中间性和紧密性的度量,我们根据中心性等级随时间的变化,确定了基石浮游生物群和对环境变化特别敏感的群体。考虑到对交互网络的更全面的了解,MAR1模型得出的稳定性和中心性度量可能会被用作集成的生态指标,以监测湖泊生态系统稳定性的变化并确定网络中特别脆弱的部分。 (C)2015 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Ecological indicators》 |2016年第6期|76-88|共13页
  • 作者单位

    Leibniz Inst Freshwater Ecol & Inland Fisheries, Dept Ecosyst Res, Muggelseedamm 310, D-12587 Berlin, Germany;

    Leibniz Inst Freshwater Ecol & Inland Fisheries, Dept Ecosyst Res, Muggelseedamm 310, D-12587 Berlin, Germany;

    Leibniz Inst Freshwater Ecol & Inland Fisheries, Dept Ecosyst Res, Muggelseedamm 310, D-12587 Berlin, Germany;

    Leibniz Inst Freshwater Ecol & Inland Fisheries, Dept Ecosyst Res, Muggelseedamm 310, D-12587 Berlin, Germany|Free Univ Berlin, Dept Biol, Chem, Pharm, Takustr 3, D-14195 Berlin, Germany;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Community stability; Interaction networks; Long-term research; Network centrality;

    机译:社区稳定性互动网络长期研究网络中心性;

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