Studying interactions among anthropogenic stressors in freshwater ecosystems: A systematic review of 2396 multiple-stressor experiments

被引:0
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作者
Orr, James A. [1 ,2 ]
Macaulay, Samuel J. [1 ]
Mordente, Adriana [1 ]
Burgess, Benjamin [3 ]
Albini, Dania [1 ]
Hunn, Julia G. [4 ]
Restrepo-Sulez, Katherin [1 ]
Wilson, Ramesh [1 ]
Schechner, Anne [5 ,6 ]
Robertson, Aoife M. [7 ]
Lee, Bethany [1 ]
Stuparyk, Blake R. [8 ]
Singh, Delezia [9 ]
O'Loughlin, Isobel [1 ]
Piggott, Jeremy J. [7 ]
Zhu, Jiangqiu [10 ]
Dinh, Khuong V. [11 ]
Archer, Louise C. [12 ]
Penk, Marcin [7 ,13 ]
Vu, Minh Thi Thuy [11 ]
Juvigny-Khenafou, Noel P. D. [14 ,15 ]
Zhang, Peiyu [10 ]
Sanders, Philip [1 ]
Schaefer, Ralf B. [16 ,17 ]
Vinebrooke, Rolf D. [8 ]
Hilt, Sabine [5 ]
Reed, Thomas [18 ]
Jackson, Michelle C. [1 ]
机构
[1] Univ Oxford, Dept Biol, Oxford, England
[2] Univ Queensland, Sch Environm, Brisbane, Qld, Australia
[3] UCL, Dept Genet Evolut & Environm, London, England
[4] Univ Otago, Dept Zool, Dunedin, New Zealand
[5] Leibniz Inst Freshwater Ecol & Inland Fisheries, Berlin, Germany
[6] Ruumi ApS, Svendborg, Denmark
[7] Trinity Coll Dublin, Sch Nat Sci, Zool, Dublin, Ireland
[8] Univ Alberta, Dept Biol Sci, Edmonton, AB, Canada
[9] Univ Manitoba, Nat Resources Inst, Winnipeg, MB, Canada
[10] Chinese Acad Sci, Inst Hydrobiol, Wuhan, Peoples R China
[11] Univ Oslo, Dept Biosci, Sect Aquat Biol & Toxicol, Oslo, Norway
[12] Univ Toronto Scarborough, Dept Biol Sci, Toronto, ON, Canada
[13] Univ Coll Dublin, Sch Biol & Environm Sci, Dublin, Ireland
[14] Univ Stirling, Inst Aquaculture, Stirling, Scotland
[15] RPTU Kaiserslautern Landau, Inst Environm Sci, Kaiserslautern, Germany
[16] Univ Alliance Ruhr, Res Ctr One Hlth Ruhr, Dortmund, Germany
[17] Univ Duisburg Essen, Fac Biol, Essen, Germany
[18] Univ Coll Cork, Sch Biol Earth & Environm Sci, Cork, Ireland
基金
英国自然环境研究理事会;
关键词
antagonism; ecology; ecotoxicology; global change biology; research synthesis; synergism; CLIMATE-CHANGE; BIODIVERSITY; MODEL;
D O I
暂无
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Understanding the interactions among anthropogenic stressors is critical for effective conservation and management of ecosystems. Freshwater scientists have invested considerable resources in conducting factorial experiments to disentangle stressor interactions by testing their individual and combined effects. However, the diversity of stressors and systems studied has hindered previous syntheses of this body of research. To overcome this challenge, we used a novel machine learning framework to identify relevant studies from over 235,000 publications. Our synthesis resulted in a new dataset of 2396 multiple-stressor experiments in freshwater systems. By summarizing the methods used in these studies, quantifying trends in the popularity of the investigated stressors, and performing co-occurrence analysis, we produce the most comprehensive overview of this diverse field of research to date. We provide both a taxonomy grouping the 909 investigated stressors into 31 classes and an open-source and interactive version of the dataset (). Inspired by our results, we provide a framework to help clarify whether statistical interactions detected by factorial experiments align with stressor interactions of interest, and we outline general guidelines for the design of multiple-stressor experiments relevant to any system. We conclude by highlighting the research directions required to better understand freshwater ecosystems facing multiple stressors. We used a novel machine learning framework to compile a dataset of 2396 multiple-stressor experiments in freshwater systems and we provide a quantitative summary of this diverse field of research. We also propose a framework to help clarify whether statistical interactions detected by factorial experiments align with stressor interactions of interest, and we outline general guidelines for the design of multiple-stressor experiments relevant to any system.image
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页数:17
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