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Research article - Peer-reviewed, 2022

Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

Prager, Case M.; Classen, Aimee T.; Sundqvist, Maja K.; Noelia Barrios-Garcia, Maria; Cameron, Erin K.; Chen, Litong; Chisholm, Chelsea; Crowther, Thomas W.; Deslippe, Julie R.; Grigulis, Karl; He, Jin-Sheng; Henning, Jeremiah A.; Hovenden, Mark; Hoye, Toke T. Thomas; Jing, Xin; Lavorel, Sandra; McLaren, Jennie R.; Metcalfe, Daniel B.; Newman, Gregory S.; Nielsen, Marie Louise;
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A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities.


alpine plant communities; climate change; elevational gradients; global change; mountains; warming

Published in

Ecology and Evolution
2022, volume: 12, number: 10, article number: e9396
Publisher: WILEY

Authors' information

Prager, Case M.
University of Michigan
Classen, Aimee T.
University of Michigan
Classen, Aimee T.
University of Copenhagen
Sundqvist, Maja K. (Sundqvist, Maja)
University of Copenhagen
Swedish University of Agricultural Sciences, Department of Forest Ecology and Management
Noelia Barrios-Garcia, Maria
Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)
Noelia Barrios-Garcia, Maria
University of Vermont
Cameron, Erin K.
Saint Marys University - Canada
Chen, Litong
Chinese Academy of Sciences
Chisholm, Chelsea
Swiss Federal Institutes of Technology Domain
Crowther, Thomas W.
Swiss Federal Institutes of Technology Domain
Deslippe, Julie R.
Victoria University Wellington
Grigulis, Karl
Universite Grenoble Alpes (UGA)
He, Jin-Sheng
Peking University
Henning, Jeremiah A.
University of South Alabama
Hovenden, Mark
University of Tasmania
Hoye, Toke T. Thomas
Aarhus University
Jing, Xin
University of Copenhagen
Jing, Xin
Lanzhou University
Lavorel, Sandra
Communaute Universite Grenoble Alpes
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UKÄ Subject classification

Climate Research

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