Plant traits alone are poor predictors of ecosystem properties and long-term ecosystem functioning

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  • Fons van der Plas
  • Thomas Schröder-Georgi
  • Alexandra Weigelt
  • Kathryn Barry
  • Sebastian Meyer
  • Adriana Alzate
  • Romain L. Barnard
  • Nina Buchmann
  • Hans de Kroon
  • Anne Ebeling
  • Nico Eisenhauer
  • Christof Engels
  • Markus Fischer
  • Gerd Gleixner
  • Anke Hildebrandt
  • Eva Koller-France
  • Sophia Leimer
  • Alexandru Milcu
  • Liesje Mommer
  • Pascal A. Niklaus
  • Yvonne Oelmann
  • Christiane Roscher
  • Christoph Scherber
  • Michael Scherer-Lorenzen
  • Stefan Scheu
  • Bernhard Schmid
  • Ernst Detlef Schulze
  • Teja Tscharntke
  • Winfried Voigt
  • Wolfgang Weisser
  • Wolfgang Wilcke
  • Christian Wirth

Earth is home to over 350,000 vascular plant species that differ in their traits in innumerable ways. A key challenge is to predict how natural or anthropogenically driven changes in the identity, abundance and diversity of co-occurring plant species drive important ecosystem-level properties such as biomass production or carbon storage. Here, we analyse the extent to which 42 different ecosystem properties can be predicted by 41 plant traits in 78 experimentally manipulated grassland plots over 10 years. Despite the unprecedented number of traits analysed, the average percentage of variation in ecosystem properties jointly explained was only moderate (32.6%) within individual years, and even much lower (12.7%) across years. Most other studies linking ecosystem properties to plant traits analysed no more than six traits and, when including only six traits in our analysis, the average percentage of variation explained in across-year levels of ecosystem properties dropped to 4.8%. Furthermore, we found on average only 12.2% overlap in significant predictors among ecosystem properties, indicating that a small set of key traits able to explain multiple ecosystem properties does not exist. Our results therefore suggest that there are specific limits to the extent to which traits per se can predict the long-term functional consequences of biodiversity change, so that data on additional drivers, such as interacting abiotic factors, may be required to improve predictions of ecosystem property levels.

Original languageEnglish
JournalNature Ecology & Evolution
Issue number12
Pages (from-to)1602-1611
Number of pages10
Publication statusPublished - 12.2020

    Research areas

  • Ecosystems Research - tree species-diversity, litter decomposition, phylogenetic diversity, subtropical forest, carbon storage, land-use, community composition, aboveground biomass, global metaanalysis, taxonomic diversity, biodiversity, community ecology, ecosystem ecology, grassland ecology