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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. Knops
  • Andrew S. MacDougall, Brett A. Melbourne, John W. Morgan, John L. Orrock, Suzanne M. Prober, Melinda D. Smith
  • US Geological Survey
  • Wake Forest University
  • University of Minnesota Twin Cities
  • Utah State University
  • Martin Luther University Halle-Wittenberg
  • Utrecht University
  • Institute for Chemistry and Biology of the Marine Environment
  • University of Tartu
  • University of Washington
  • Trinity College Dublin
  • Imperial College London
  • University of Wisconsin-Madison
  • University of Colorado Boulder
  • Grassland Soil and Water Research Laboratory
  • Queensland University of Technology
  • University of Maryland, College Park
  • University of Oxford
  • School of Biological Sciences
  • University of Guelph
  • La Trobe University
  • CSIRO
  • Colorado State University

Research output: Contribution to journalArticleAcademicpeer-review

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
Pages (from-to)390-393
Number of pages4
JournalNature
Volume529
Issue number7586
DOIs
Publication statusPublished - 21 Jan 2016

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • article
  • biodiversity
  • biomass
  • biomass production
  • climate
  • ecosystem
  • ecosystem productivity
  • environmental factor
  • nonhuman
  • plant
  • plant species richness
  • priority journal
  • soil fertility
  • species richness
  • structural equation modeling

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