Integrative modelling reveals mechanisms linking productivity and plant species richness

James B. Grace, T. Michael Anderson, Eric W. Seabloom, Elizabeth T. Borer, Peter B. Adler, W. Stanley Harpole, Yann Hautier, Helmut Hillebrand, Eric M. Lind, Meelis Pärtel, Jonathan D. Bakker, Yvonne M. Buckley, Michael J. Crawley, Ellen I. Damschen, Kendi F. Davies, Philip A. Fay, Jennifer Firn, Daniel S. Gruner, Andy Hector, Johannes M.H. KnopsAndrew S. MacDougall, Brett A. Melbourne, John W. Morgan, John L. Orrock, Suzanne M. Prober, Melinda D. Smith

Research output: Contribution to journalArticlepeer-review

265 Scopus citations

Abstract

How ecosystem productivity and species richness are interrelated is one of the most debated subjects in the history of ecology. Decades of intensive study have yet to discern the actual mechanisms behind observed global patterns. Here, by integrating the predictions from multiple theories into a single model and using data from 1,126 grassland plots spanning five continents, we detect the clear signals of numerous underlying mechanisms linking productivity and richness. We find that an integrative model has substantially higher explanatory power than traditional bivariate analyses. In addition, the specific results unveil several surprising findings that conflict with classical models. These include the isolation of a strong and consistent enhancement of productivity by richness, an effect in striking contrast with superficial data patterns. Also revealed is a consistent importance of competition across the full range of productivity values, in direct conflict with some (but not all) proposed models. The promotion of local richness by macroecological gradients in climatic favourability, generally seen as a competing hypothesis, is also found to be important in our analysis. The results demonstrate that an integrative modelling approach leads to a major advance in our ability to discern the underlying processes operating in ecological systems.

Original languageEnglish (US)
Pages (from-to)390-393
Number of pages4
JournalNature
Volume529
Issue number7586
DOIs
StatePublished - Jan 21 2016

Bibliographical note

Funding Information:
Acknowledgements J.B.G. was supported by the US Geological Survey Ecosystems and Climate and Land use Change Programs. This work uses data from the Nutrient Network (http://nutnet.org) experiment, funded at the site scale by individual researchers. Coordination and data management were supported by funding to E.T.B. and E.W.S. from the National Science Foundation (NSF) Research Coordination Network (NSF-DEB-1042132) and Long Term Ecological Research (NSF-DEB-1234162 to Cedar Creek LTER) programs and the UMN Institute on the Environment (DG-0001-13). The Minnesota Supercomputer Institute hosts project data. The use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government. Support for site-level activities is acknowledged in the Supplementary Information. We thank D. Laughlin for comments on the manuscript.

Publisher Copyright:
© 2016 Macmillan Publishers Limited.

Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.

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