Environmental heterogeneity modulates the effect of plant diversity on the spatial variability of grassland biomass
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
Authors
Plant productivity varies due to environmental heterogeneity, and theory suggests that plant diversity can reduce this variation. While there is strong evidence of diversity effects on temporal variability of productivity, whether this mechanism extends to variability across space remains elusive. Here we determine the relationship between plant diversity and spatial variability of productivity in 83 grasslands, and quantify the effect of experimentally increased spatial heterogeneity in environmental conditions on this relationship. We found that communities with higher plant species richness (alpha and gamma diversity) have lower spatial variability of productivity as reduced abundance of some species can be compensated for by increased abundance of other species. In contrast, high species dissimilarity among local communities (beta diversity) is positively associated with spatial variability of productivity, suggesting that changes in species composition can scale up to affect productivity. Experimentally increased spatial environmental heterogeneity weakens the effect of plant alpha and gamma diversity, and reveals that beta diversity can simultaneously decrease and increase spatial variability of productivity. Our findings unveil the generality of the diversity-stability theory across space, and suggest that reduced local diversity and biotic homogenization can affect the spatial reliability of key ecosystem functions.
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | 1809 |
| Zeitschrift | Nature Communications |
| Jahrgang | 14 |
| Ausgabenummer | 1 |
| Anzahl der Seiten | 11 |
| ISSN | 2041-1723 |
| DOIs | |
| Publikationsstatus | Erschienen - 12.2023 |
Bibliographische Notiz
Funding Information:
This work was generated using data from the Nutrient Network ( http://www.nutnet.org ) experiment, funded at the site-scale by individual researchers. Coordination and data management have been supported by funding to ETB and EWS from the National Science Foundation Research Coordination Network (NSF-DEB-1042132) and Long Term Ecological Research (NSF-DEB-1234162 and NSF-DEB-1831944 to Cedar Creek LTER) programs, and the Institute on the Environment (DG-0001-13). We also thank the Minnesota Supercomputer Institute for hosting project data and the Institute on the Environment for hosting Network meetings. Soil analyses were supported, in part, by USDA-ARS grant 58-3098-7-007 to ETB. This is KBS contribution #2344. NE and SH acknowledge the support of iDiv funded by the German Research Foundation (DFG– FZT 118, 202548816) and NE acknowledges funding by the DFG (Ei 862/29-1 and Ei 862/31-1). M.P. and R.T. were supported by the Estonian Research Council (PRG609), and the European Regional Development Fund (Centre of Excellence EcolChange). Y.L. is thankful to MPG Ranch for funding. A.J. acknowledges German Ministry for Education and Research (BMBF) for funding this research (SUSALPS; FKZ 031B0516C). N.G.S. acknowledges funding from the National Science Foundation (DEB-2045968) and Texas Tech University. Funding for the project comes from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. [101002987] to J.C.). This project was supported by grants from the Universidad Nacional de Mar del Plata (EXA1043/21), CONICET (PIP 2841) and ANPCyT (PICT 2019-3466) to O.I. and P.D.
Publisher Copyright:
© 2023, The Author(s).
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