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...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/171042 |
| _version_ | 1811683335996440576 |
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| 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. |
| author2 | Asian School of the Environment |
| author_facet | Asian School of the Environment 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. |
| collection | NTU |
| 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. |
| first_indexed | 2024-10-01T04:11:06Z |
| format | Journal Article |
| id | ntu-10356/171042 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:11:06Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1710422023-10-16T15:30:47Z 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. Asian School of the Environment Science::Geology Alpine Plant Communities Elevational Gradients 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. Published version Carlsbergfondet, Grant/Award Number: WaRM Network Grant; Carlsberg Foundation 2023-10-13T07:48:05Z 2023-10-13T07:48:05Z 2022 Journal Article Prager, C. M., Classen, A. T., Sundqvist, M. K., Barrios-Garcia, M. N., Cameron, E. K., Chen, L., Chisholm, C., Crowther, T. W., Deslippe, J. R., Grigulis, K., He, J., Henning, J. A., Hovenden, M., Høye, T. T. T., Jing, X., Lavorel, S., McLaren, J. R., Metcalfe, D. B., Newman, G. S., ...Sanders, N. J. (2022). Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network. Ecology and Evolution, 12(10), e9396-. https://dx.doi.org/10.1002/ece3.9396 2045-7758 https://hdl.handle.net/10356/171042 10.1002/ece3.9396 36262264 2-s2.0-85141173171 10 12 e9396 en Ecology and Evolution © 2022 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. application/pdf |
| spellingShingle | Science::Geology Alpine Plant Communities Elevational Gradients 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 |
| title | 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_short | 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 |
| topic | Science::Geology Alpine Plant Communities Elevational Gradients |
| url | https://hdl.handle.net/10356/171042 |
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