, Volume 17, Issue 6, pp 1095–1108 | Cite as

Seasonal Variation in the Capacity for Plant Trait Measures to Predict Grassland Carbon and Water Fluxes

  • Georg Everwand
  • Ellen L. Fry
  • Till Eggers
  • Pete Manning


There is a need for accurate predictions of ecosystem carbon (C) and water fluxes in field conditions. Previous research has shown that ecosystem properties can be predicted from community abundance-weighted means (CWM) of plant functional traits and measures of trait variability within a community (FDvar). The capacity for traits to predict carbon (C) and water fluxes, and the seasonal dependency of these trait-function relationships has not been fully explored. Here we measured daytime C and water fluxes over four seasons in grasslands of a range of successional ages in southern England. In a model selection procedure, we related these fluxes to environmental covariates and plant biomass measures before adding CWM and FDvar plant trait measures that were scaled up from measures of individual plants grown in greenhouse conditions. Models describing fluxes in periods of low biological activity contained few predictors, which were usually abiotic factors. In more biologically active periods, models contained more predictors, including plant trait measures. Field-based plant biomass measures were generally better predictors of fluxes than CWM and FDvar traits. However, when these measures were used in combination traits accounted for additional variation. Where traits were significant predictors their identity often reflected seasonal vegetation dynamics. These results suggest that database derived trait measures can improve the prediction of ecosystem C and water fluxes. Controlled studies and those involving more detailed flux measurements are required to validate and explore these findings, a worthwhile effort given the potential for using simple vegetation measures to help predict landscape-scale fluxes.


biodiversity biomass climate community weighted mean ecosystem services evapotranspiration Functional diversity photosynthesis 



This study was funded by the UK’s Natural Environment Research Council via the Centre for Population Biology and the ERASMUS Program of the EU. Thanks go to Antje Möhlmeyer, Sally Power, Nadine Prill, David Allen, Lena Everwand and Alex Hurst for support during data collection. Sarah Pierce and three anonymous reviewers provided advice and helpful comments on an earlier draft the manuscript.

Supplementary material

10021_2014_9779_MOESM1_ESM.docx (58 kb)
Supplementary material 1 (DOCX 58 kb)


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Georg Everwand
    • 1
    • 2
  • Ellen L. Fry
    • 3
  • Till Eggers
    • 4
    • 5
  • Pete Manning
    • 2
    • 6
  1. 1.Department of Crop Sciences, AgroecologyGeorg-August-University GöttingenGöttingenGermany
  2. 2.NERC Centre for Population BiologyImperial College of Science and TechnologyAscotUK
  3. 3.Department of Life SciencesImperial College of Science and TechnologyAscotUK
  4. 4.BASF SE, Global Research Crop Protection, Data Management and BiometricsLimburgerhofGermany
  5. 5.Experimental Ecology Group, Department for Biology and ChemistryUniversity of OsnabrückOsnabrückGermany
  6. 6.Institute for Plant SciencesUniversity of BernBernSwitzerland

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