Abstract
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.
Original language | English |
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Article number | 2607 |
Journal | Nature Communications |
Volume | 14 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2023 |
Bibliographical note
Publisher Copyright:© 2023, The Author(s).
Funding
We thank E. Seabloom, A. Asmus, H. Correa, J. Firn, and F. Isbell for their input. The views herein are solely those of the authors and do not necessarily reflect those of the Federal Reserve Bank of Philadelphia or the Federal Reserve System. We thank UMN Supercomputer Institute for hosting data and IoE for hosting Network meetings. We acknowledge support from NASA BioSCape to L.E.D. and P.A. We acknowledge support from SF Long- 354 Term Ecological Research (LTER) Network Communications Office and US NSF 823 DEB- 355 1545288. This study used data from the Nutrient Network ( http://www.nutnet.org ), funded at the site-scale by individual researchers. Coordination and data management was supported by funding to E. Borer and E. Seabloom from NSF-DEB-1042132 and Institute on the Environment (DG-358 0001-13) and to E.B., and P.B.R from LTER (DEB-1234162, DEB-1831944). We also acknowledge support from DEB-0620652, NSF grants DEB-1242531, DEB-1753859, and DBI-202189 to P.B.R.; TULIP Laboratory of Excellence (ANR-10-LABX-41) to M.L.; and CEREEP-Ecotron Ile De France (CNRS/ENS UMS 3194), Regional Council of Ile- de-France (DIM Program R2DS I-05-098/R), GoF/ANR’s Investissements d’Avenir program (ANR-11-INBS-0001 AnaEE France; ANR-10-IDEX- 0001-02 PSL) to X.R. This is Kellogg Biological Station Contribution no. 2338. Soil analyses were supported, in part, by Oregon State University, University of Minnesota, and USDA-ARS grant 58-3098-7-007 to E.T.B.
Funders | Funder number |
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Hawkesbury Institute for the Environment | DG-358 0001-13 |
LTER | DEB-1234162, DBI-202189, DEB-1831944, CNRS/ENS UMS 3194, DEB-1242531, ANR-10-LABX-41, DEB-0620652, DEB-1753859 |
NASA BioSCape | US NSF 823 DEB- 355 1545288 |
NSF-DEB-1042132 | |
Regional Council of Ile-de-France | ANR-11-INBS-0001, I-05-098/R, ANR-10-IDEX- 0001-02 PSL |
Minnesota State University-Mankato | |
USDA-Agricultural Research Service | 58-3098-7-007 |
Oregon State University |
ASJC Scopus subject areas
- General Chemistry
- General Biochemistry, Genetics and Molecular Biology
- General Physics and Astronomy