4.8 Article

Semiempirical modeling of abiotic and biotic factors controlling ecosystem respiration across eddy covariance sites

Journal

GLOBAL CHANGE BIOLOGY
Volume 17, Issue 1, Pages 390-409

Publisher

WILEY
DOI: 10.1111/j.1365-2486.2010.02243.x

Keywords

ecosystem respiration; eddy covariance; FLUXNET; inverse modeling; leaf area index; productivity

Funding

  1. CarboEuropeIP
  2. FAO-GTOS-TCO
  3. iLEAPS
  4. Max Planck Institute for Biogeochemistry
  5. National Science Foundation
  6. University of Tuscia
  7. US Department of Energy
  8. University of Milano-Bicocca
  9. Model-Data Integration Group of the Max-Planck Institute for Biogeochemistry
  10. Natural Environment Research Council [ceh010023] Funding Source: researchfish

Ask authors/readers for more resources

In this study we examined ecosystem respiration (R-ECO) data from 104 sites belonging to FLUXNET, the global network of eddy covariance flux measurements. The goal was to identify the main factors involved in the variability of R-ECO: temporally and between sites as affected by climate, vegetation structure and plant functional type (PFT) (evergreen needleleaf, grasslands, etc.). We demonstrated that a model using only climate drivers as predictors of R-ECO failed to describe part of the temporal variability in the data and that the dependency on gross primary production (GPP) needed to be included as an additional driver of R-ECO. The maximum seasonal leaf area index (LAI(MAX)) had an additional effect that explained the spatial variability of reference respiration (the respiration at reference temperature T-ref=15 degrees C, without stimulation introduced by photosynthetic activity and without water limitations), with a statistically significant linear relationship (r2=0.52, P < 0.001, n=104) even within each PFT. Besides LAI(MAX), we found that reference respiration may be explained partially by total soil carbon content (SoilC). For undisturbed temperate and boreal forests a negative control of total nitrogen deposition (N-depo) on reference respiration was also identified. We developed a new semiempirical model incorporating abiotic factors (climate), recent productivity (daily GPP), general site productivity and canopy structure (LAI(MAX)) which performed well in predicting the spatio-temporal variability of R-ECO, explaining > 70% of the variance for most vegetation types. Exceptions include tropical and Mediterranean broadleaf forests and deciduous broadleaf forests. Part of the variability in respiration that could not be described by our model may be attributed to a series of factors, including phenology in deciduous broadleaf forests and management practices in grasslands and croplands.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available