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

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. Al...

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Main Authors: Prager, Case M., Classen, Aimee T., Sundqvist, Maja K., Barrios-Garcia, Maria noelia, Cameron, Erin K., Chen, Litong, Chisholm, Chelsea, Crowther, Thomas W., Deslippe, Julie R., Grigulis, Karl, He, Jin-Sheng, Henning, Jeremiah A., Hovenden, Mark, Høye, Toke T. Thomas, Jing, Xin, Lavorel, Sandra, McLaren, Jennie R., Metcalfe, Daniel B., Newman, Gregory S., Nielsen, Marie Louise, Rixen, Christian, Read, Quentin D., Rewcastle, Kenna E., Rodriguez-Cabal, Mariano, Wardle, David A., Wipf, Sonja, Sanders, Nathan J.
Format: Article in Journal/Newspaper
Language:unknown
Published: IPCC 2022
Subjects:
warming
global change
alpine plant communities
climate change
elevational gradients
mountains
Ecology and Evolutionary Biology
Science
Arctic
Online Access:https://hdl.handle.net/2027.42/175055
https://doi.org/10.1002/ece3.9396
id ftumdeepblue:oai:deepblue.lib.umich.edu:2027.42/175055
record_format openpolar
institution Open Polar
collection University of Michigan: Deep Blue
op_collection_id ftumdeepblue
language unknown
topic warming
global change
alpine plant communities
climate change
elevational gradients
mountains
Ecology and Evolutionary Biology
Science
spellingShingle warming
global change
alpine plant communities
climate change
elevational gradients
mountains
Ecology and Evolutionary Biology
Science
Prager, Case M.
Classen, Aimee T.
Sundqvist, Maja K.
Barrios-Garcia, Maria noelia
Cameron, Erin K.
Chen, Litong
Chisholm, Chelsea
Crowther, Thomas W.
Deslippe, Julie R.
Grigulis, Karl
He, Jin-Sheng
Henning, Jeremiah A.
Hovenden, Mark
Høye, Toke T. Thomas
Jing, Xin
Lavorel, Sandra
McLaren, Jennie R.
Metcalfe, Daniel B.
Newman, Gregory S.
Nielsen, Marie Louise
Rixen, Christian
Read, Quentin D.
Rewcastle, Kenna E.
Rodriguez-Cabal, Mariano
Wardle, David A.
Wipf, Sonja
Sanders, Nathan J.
Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network
topic_facet warming
global change
alpine plant communities
climate change
elevational gradients
mountains
Ecology and Evolutionary Biology
Science
description 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.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 ...
format Article in Journal/Newspaper
author Prager, Case M.
Classen, Aimee T.
Sundqvist, Maja K.
Barrios-Garcia, Maria noelia
Cameron, Erin K.
Chen, Litong
Chisholm, Chelsea
Crowther, Thomas W.
Deslippe, Julie R.
Grigulis, Karl
He, Jin-Sheng
Henning, Jeremiah A.
Hovenden, Mark
Høye, Toke T. Thomas
Jing, Xin
Lavorel, Sandra
McLaren, Jennie R.
Metcalfe, Daniel B.
Newman, Gregory S.
Nielsen, Marie Louise
Rixen, Christian
Read, Quentin D.
Rewcastle, Kenna E.
Rodriguez-Cabal, Mariano
Wardle, David A.
Wipf, Sonja
Sanders, Nathan J.
author_facet Prager, Case M.
Classen, Aimee T.
Sundqvist, Maja K.
Barrios-Garcia, Maria noelia
Cameron, Erin K.
Chen, Litong
Chisholm, Chelsea
Crowther, Thomas W.
Deslippe, Julie R.
Grigulis, Karl
He, Jin-Sheng
Henning, Jeremiah A.
Hovenden, Mark
Høye, Toke T. Thomas
Jing, Xin
Lavorel, Sandra
McLaren, Jennie R.
Metcalfe, Daniel B.
Newman, Gregory S.
Nielsen, Marie Louise
Rixen, Christian
Read, Quentin D.
Rewcastle, Kenna E.
Rodriguez-Cabal, Mariano
Wardle, David A.
Wipf, Sonja
Sanders, Nathan J.
author_sort Prager, Case M.
title Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network
title_short Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network
title_full Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network
title_fullStr Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network
title_full_unstemmed Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network
title_sort integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: an example from the warm network
publisher IPCC
publishDate 2022
url https://hdl.handle.net/2027.42/175055
https://doi.org/10.1002/ece3.9396
genre Arctic
genre_facet Arctic
op_relation Prager, Case M.; Classen, Aimee T.; Sundqvist, Maja K.; Barrios-Garcia, Maria noelia
Cameron, Erin K.; Chen, Litong; Chisholm, Chelsea; Crowther, Thomas W.; Deslippe, Julie R.; Grigulis, Karl; He, Jin-Sheng
Henning, Jeremiah A.; Hovenden, Mark; Høye, Toke T. Thomas
Jing, Xin; Lavorel, Sandra; McLaren, Jennie R.; Metcalfe, Daniel B.; Newman, Gregory S.; Nielsen, Marie Louise; Rixen, Christian; Read, Quentin D.; Rewcastle, Kenna E.; Rodriguez-Cabal, Mariano
Wardle, David A.; Wipf, Sonja; Sanders, Nathan J. (2022). "Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network." Ecology and Evolution (10): n/a-n/a.
2045-7758
https://hdl.handle.net/2027.42/175055
doi:10.1002/ece3.9396
Ecology and Evolution
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op_doi https://doi.org/10.1002/ece3.939610.1111/j.1654-1103.2004.tb02266.x
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spelling ftumdeepblue:oai:deepblue.lib.umich.edu:2027.42/175055 2023-12-31T10:02:18+01:00 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. Barrios-Garcia, Maria noelia Cameron, Erin K. Chen, Litong Chisholm, Chelsea Crowther, Thomas W. Deslippe, Julie R. Grigulis, Karl He, Jin-Sheng Henning, Jeremiah A. Hovenden, Mark Høye, Toke T. Thomas Jing, Xin Lavorel, Sandra McLaren, Jennie R. Metcalfe, Daniel B. Newman, Gregory S. Nielsen, Marie Louise Rixen, Christian Read, Quentin D. Rewcastle, Kenna E. Rodriguez-Cabal, Mariano Wardle, David A. Wipf, Sonja Sanders, Nathan J. 2022-10 application/pdf https://hdl.handle.net/2027.42/175055 https://doi.org/10.1002/ece3.9396 unknown IPCC Wiley Periodicals, Inc. Prager, Case M.; Classen, Aimee T.; Sundqvist, Maja K.; Barrios-Garcia, Maria noelia Cameron, Erin K.; Chen, Litong; Chisholm, Chelsea; Crowther, Thomas W.; Deslippe, Julie R.; Grigulis, Karl; He, Jin-Sheng Henning, Jeremiah A.; Hovenden, Mark; Høye, Toke T. Thomas Jing, Xin; Lavorel, Sandra; McLaren, Jennie R.; Metcalfe, Daniel B.; Newman, Gregory S.; Nielsen, Marie Louise; Rixen, Christian; Read, Quentin D.; Rewcastle, Kenna E.; Rodriguez-Cabal, Mariano Wardle, David A.; Wipf, Sonja; Sanders, Nathan J. (2022). "Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network." Ecology and Evolution (10): n/a-n/a. 2045-7758 https://hdl.handle.net/2027.42/175055 doi:10.1002/ece3.9396 Ecology and Evolution McCain, C. M. ( 2007 ). Could temperature and water availability drive elevational species richness patterns? A global case study for bats. Global Ecology and Biogeography, 16, 1 – 13. Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., & Jarvis, A. ( 2012 ). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965 – 1978 (for WorldClim 2018 database citation). Hillebrand, H., Bennett, D. M., & Cadotte, M. W. ( 2008 ). Consequences of dominance: A review of evenness effects on local and regional ecosystem processes. Ecology, 89, 1510 – 1520. Heskel, M., Greaves, H., Kornfeld, A., Gough, L., Atkin, O. K., Turnbull, M. H., Shaver, G., & Griffin, K. L. ( 2013 ). Differential physiological responses to environmental change promote woody shrub expansion. Ecology and Evolution, 3 ( 5 ), 1149 – 1162. Hovenden, M. J., Leuzinger, S., Newton, P. C. D., Fletcher, A., Fatichi, S., Lüscher, A., Reich, P. B., Andresen, L. C., Beier, C., Blumenthal, D. M., Chiariello, N. R., Dukes, J. S., Kellner, J., Hofmockel, K., Niklaus, P. A., Song, J., Wan, S., Classen, A. T., & Langley, J. A. ( 2019 ). Globally consistent influences of seasonal precipitation limit grassland biomass response to elevated CO2. Nature Plants, 5, 167 – 173. IPCC. ( 2014 ). Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC 151 pp. Isbell, F., Gonzalez, A., Loreau, M., Cowles, J., Díaz, S., Hector, A., Mace, G. M., Wardle, D. A., O’Connor, M. I., Duffy, J. E., Turnbull, L. A., Thompson, P. L., & Larigauderie, A. ( 2017 ). Linking the influence and dependence of people on biodiversity across scales. Nature, 546, 65 – 72. Jain, M., Flynn, D. F. B., Prager, C. M., Hart, G. M., DeVan, C. M., Ahrestani, F. S., Palmer, M. I., Bunker, D. E., Knops, J. M. H., Jouseau, C. F., & Naeem, S. ( 2014 ). The importance of rare species: a trait-based assessment of rare species contributions to functional diversity and possible ecosystem function in tall-grass prairies. Ecology and Evolution, 4, 104 – 112. Jetz, W., McGeoch, M. A., Guralnick, R., Ferrier, S., Beck, J., Costello, M. J., Fernandez, M., Geller, G. N., Keil, P., Merow, C., Meyer, C., Muller-Karger, F. E., Pereira, H. M., Regan, E. C., Schmeller, D. S., & Turak, E. ( 2019 ). Essential biodiversity variables for mapping and monitoring species populations. Nature Ecology & Evolution, 3, 539 – 551. Kardol, P., Fanin, N., & Wardle, D. A. ( 2018 ). Long-term effects of species loss on community properties across contrasting ecosystems. Nature, 557, 710 – 713. Kivlin, S. N., Winston, G. C., Goulden, M. L., & Treseder, K. K. ( 2014 ). Environmental filtering affects soil fungal community composition more than dispersal limitation at regional scales. Fungal Ecology, 12, 14 – 25. Kleyer, M., Dray, S., Bello, F., Lepš, J., Pakeman, R. 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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.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 ... Article in Journal/Newspaper Arctic University of Michigan: Deep Blue

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