Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1002/ecy.2216
Document Shareable Link
Title (Primary) Origin context of trait data matters for predictions of community performance in a grassland biodiversity experiment
Author Roscher, C.; Schumacher, J.; Gubsch, M.; Lipowsky, A.; Weigelt, A.; Buchmann, N.; Schmid, B.; Schulze, E.-D.
Source Titel Ecology
Year 2018
Department PHYDIV
Volume 99
Issue 5
Page From 1214
Page To 1226
Language englisch
Data and Software links https://doi.org/10.1594/pangaea.846582
https://doi.org/10.1594/pangaea.866315
Supplements https://esajournals.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fecy.2216&attachmentId=2211798280
https://esajournals.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fecy.2216&file=ecy2216-sup-0001-AppendixS1.pdf
Keywords community-weighted mean traits; complementarity effects; experimental design; productivity; selection effects; trait diversity; trait plasticity; trait-based ecology.
Abstract Plant functional traits may explain the positive relationship between species richness and ecosystem functioning, but species‐level trait variation in response to growth conditions is often ignored in trait‐based predictions of community performance. In a large grassland biodiversity experiment (Jena Experiment), we measured traits on plants grown as solitary individuals, in monocultures or in mixtures. We calculated two measures of community‐level trait composition, i.e., community‐weighted mean traits (CWM) and trait diversity (Rao's quadratic entropy; FD) based on different contexts in which traits were measured (trait origins). CWM and FD values of the different measurement origins were then compared regarding their power to predict community biomass production and biodiversity effects quantified with the additive partitioning method. Irrespective of trait origin, models combining CWM and FD values as predictors best explained community biomass and biodiversity effects. CWM values based on monoculture, mixture‐mean or community‐specific trait data were similarly powerful predictors, but predictions became worse when trait values originated from solitary‐grown individuals. FD values based on monoculture traits were the best predictors of community biomass and net biodiversity effects, while FD values based on community‐specific traits were the best predictors for complementarity and selection effects. Traits chosen as best CWM predictors were not strongly affected by trait origin but traits chosen as best FD predictors varied strongly dependent on trait origin and altered the predictability of community performance. We conclude that by adjusting their functional traits to species richness and even specific community compositions, plants can change community‐level trait compositions, thereby also changing community biomass production and biodiversity effects. Incorporation of these plastic trait adjustments of plants in trait‐based ecology can improve its predictive power in explaining biodiversity–ecosystem functioning relationships.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=20403
Roscher, C., Schumacher, J., Gubsch, M., Lipowsky, A., Weigelt, A., Buchmann, N., Schmid, B., Schulze, E.-D. (2018):
Origin context of trait data matters for predictions of community performance in a grassland biodiversity experiment
Ecology 99 (5), 1214 - 1226 10.1002/ecy.2216