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Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference
Causal effects of biodiversity on ecosystem functions can be estimated using experimental or observational designs — designs that pose a tradeoff between drawing credible causal inferences from correlations and drawing generalizable inferences. Here, we develop a design that reduces this tradeoff an...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163230/ https://www.ncbi.nlm.nih.gov/pubmed/37147282 http://dx.doi.org/10.1038/s41467-023-37194-5 |
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author | Dee, Laura E. Ferraro, Paul J. Severen, Christopher N. Kimmel, Kaitlin A. Borer, Elizabeth T. Byrnes, Jarrett E. K. Clark, Adam Thomas Hautier, Yann Hector, Andrew Raynaud, Xavier Reich, Peter B. Wright, Alexandra J. Arnillas, Carlos A. Davies, Kendi F. MacDougall, Andrew Mori, Akira S. Smith, Melinda D. Adler, Peter B. Bakker, Jonathan D. Brauman, Kate A. Cowles, Jane Komatsu, Kimberly Knops, Johannes M. H. McCulley, Rebecca L. Moore, Joslin L. Morgan, John W. Ohlert, Timothy Power, Sally A. Sullivan, Lauren L. Stevens, Carly Loreau, Michel |
author_facet | Dee, Laura E. Ferraro, Paul J. Severen, Christopher N. Kimmel, Kaitlin A. Borer, Elizabeth T. Byrnes, Jarrett E. K. Clark, Adam Thomas Hautier, Yann Hector, Andrew Raynaud, Xavier Reich, Peter B. Wright, Alexandra J. Arnillas, Carlos A. Davies, Kendi F. MacDougall, Andrew Mori, Akira S. Smith, Melinda D. Adler, Peter B. Bakker, Jonathan D. Brauman, Kate A. Cowles, Jane Komatsu, Kimberly Knops, Johannes M. H. McCulley, Rebecca L. Moore, Joslin L. Morgan, John W. Ohlert, Timothy Power, Sally A. Sullivan, Lauren L. Stevens, Carly Loreau, Michel |
author_sort | Dee, Laura E. |
collection | PubMed |
description | Causal effects of biodiversity on ecosystem functions can be estimated using experimental or observational designs — designs that pose a tradeoff between drawing credible causal inferences from correlations and drawing generalizable inferences. Here, we develop a design that reduces this tradeoff and revisits the question of how plant species diversity affects productivity. Our design leverages longitudinal data from 43 grasslands in 11 countries and approaches borrowed from fields outside of ecology to draw causal inferences from observational data. Contrary to many prior studies, we estimate that increases in plot-level species richness caused productivity to decline: a 10% increase in richness decreased productivity by 2.4%, 95% CI [−4.1, −0.74]. This contradiction stems from two sources. First, prior observational studies incompletely control for confounding factors. Second, most experiments plant fewer rare and non-native species than exist in nature. Although increases in native, dominant species increased productivity, increases in rare and non-native species decreased productivity, making the average effect negative in our study. By reducing the tradeoff between experimental and observational designs, our study demonstrates how observational studies can complement prior ecological experiments and inform future ones. |
format | Online Article Text |
id | pubmed-10163230 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-101632302023-05-07 Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference Dee, Laura E. Ferraro, Paul J. Severen, Christopher N. Kimmel, Kaitlin A. Borer, Elizabeth T. Byrnes, Jarrett E. K. Clark, Adam Thomas Hautier, Yann Hector, Andrew Raynaud, Xavier Reich, Peter B. Wright, Alexandra J. Arnillas, Carlos A. Davies, Kendi F. MacDougall, Andrew Mori, Akira S. Smith, Melinda D. Adler, Peter B. Bakker, Jonathan D. Brauman, Kate A. Cowles, Jane Komatsu, Kimberly Knops, Johannes M. H. McCulley, Rebecca L. Moore, Joslin L. Morgan, John W. Ohlert, Timothy Power, Sally A. Sullivan, Lauren L. Stevens, Carly Loreau, Michel Nat Commun Article Causal effects of biodiversity on ecosystem functions can be estimated using experimental or observational designs — designs that pose a tradeoff between drawing credible causal inferences from correlations and drawing generalizable inferences. Here, we develop a design that reduces this tradeoff and revisits the question of how plant species diversity affects productivity. Our design leverages longitudinal data from 43 grasslands in 11 countries and approaches borrowed from fields outside of ecology to draw causal inferences from observational data. Contrary to many prior studies, we estimate that increases in plot-level species richness caused productivity to decline: a 10% increase in richness decreased productivity by 2.4%, 95% CI [−4.1, −0.74]. This contradiction stems from two sources. First, prior observational studies incompletely control for confounding factors. Second, most experiments plant fewer rare and non-native species than exist in nature. Although increases in native, dominant species increased productivity, increases in rare and non-native species decreased productivity, making the average effect negative in our study. By reducing the tradeoff between experimental and observational designs, our study demonstrates how observational studies can complement prior ecological experiments and inform future ones. Nature Publishing Group UK 2023-05-05 /pmc/articles/PMC10163230/ /pubmed/37147282 http://dx.doi.org/10.1038/s41467-023-37194-5 Text en © The Author(s) 2023, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Dee, Laura E. Ferraro, Paul J. Severen, Christopher N. Kimmel, Kaitlin A. Borer, Elizabeth T. Byrnes, Jarrett E. K. Clark, Adam Thomas Hautier, Yann Hector, Andrew Raynaud, Xavier Reich, Peter B. Wright, Alexandra J. Arnillas, Carlos A. Davies, Kendi F. MacDougall, Andrew Mori, Akira S. Smith, Melinda D. Adler, Peter B. Bakker, Jonathan D. Brauman, Kate A. Cowles, Jane Komatsu, Kimberly Knops, Johannes M. H. McCulley, Rebecca L. Moore, Joslin L. Morgan, John W. Ohlert, Timothy Power, Sally A. Sullivan, Lauren L. Stevens, Carly Loreau, Michel Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference |
title | Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference |
title_full | Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference |
title_fullStr | Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference |
title_full_unstemmed | Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference |
title_short | Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference |
title_sort | clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163230/ https://www.ncbi.nlm.nih.gov/pubmed/37147282 http://dx.doi.org/10.1038/s41467-023-37194-5 |
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