%0 Journal Article %1 Groenendijk2011Assessing %A Groenendijk, M. %A Dolman, A. J. %A van der Molen, M. K. %A Leuning, R. %A Arneth, A. %A Delpierre, N. %A Gash, J. H. C. %A Lindroth, A. %A Richardson, A. D. %A Verbeeck, H. %A Wohlfahrt, G. %D 2011 %J Agricultural and Forest Meteorology %K imported %N 1 %P 22--38 %R 10.1016/j.agrformet.2010.08.013 %T Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data %U http://dx.doi.org/10.1016/j.agrformet.2010.08.013 %V 151 %X AbstractThe vegetation component in climate models has advanced since the late 1960s from a uniform prescription of surface parameters to plant functional types (PFTs). PFTs are used in global land-surface models to provide parameter values for every model grid cell. With a simple photosynthesis model we derive parameters for all site years within the Fluxnet eddy covariance data set. We compare the model parameters within and between PFTs and statistically group the sites. Fluxnet data is used to validate the photosynthesis model parameter variation within a PFT classification.Our major result is that model parameters appear more variable than assumed in PFTs. Simulated fluxes are of higher quality when model parameters of individual sites or site years are used. A simplification with less variation in model parameters results in poorer simulations. This indicates that a PFT classification introduces uncertainty in the variation of the photosynthesis and transpiration fluxes. Statistically derived groups of sites with comparable model parameters do not share common vegetation types or climates.A simple PFT classification does not reflect the real photosynthesis and transpiration variation. Although site year parameters give the best predictions, the parameters are generally too specific to be used in a global study. The site year parameters can be further used to explore the possibilities of alternative classification schemes. Research highlights Variation of photosynthesis model parameters was derived from Fluxnet data. The parameters are more variable than assumed in plant functional types (PFTs). A PFT classification does not reflect the observed photosynthesis and transpiration flux variation. Statistically derived groups of sites do not share common vegetation types or climates. The derived parameters can be used to explore alternative classification schemes.

@article{Groenendijk2011Assessing, abstract = { {AbstractThe} vegetation component in climate models has advanced since the late 1960s from a uniform prescription of surface parameters to plant functional types ({PFTs}). {PFTs} are used in global land-surface models to provide parameter values for every model grid cell. With a simple photosynthesis model we derive parameters for all site years within the Fluxnet eddy covariance data set. We compare the model parameters within and between {PFTs} and statistically group the sites. Fluxnet data is used to validate the photosynthesis model parameter variation within a {PFT} {classification.Our} major result is that model parameters appear more variable than assumed in {PFTs}. Simulated fluxes are of higher quality when model parameters of individual sites or site years are used. A simplification with less variation in model parameters results in poorer simulations. This indicates that a {PFT} classification introduces uncertainty in the variation of the photosynthesis and transpiration fluxes. Statistically derived groups of sites with comparable model parameters do not share common vegetation types or {climates.A} simple {PFT} classification does not reflect the real photosynthesis and transpiration variation. Although site year parameters give the best predictions, the parameters are generally too specific to be used in a global study. The site year parameters can be further used to explore the possibilities of alternative classification schemes. Research highlights Variation of photosynthesis model parameters was derived from Fluxnet data. The parameters are more variable than assumed in plant functional types ({PFTs}). A {PFT} classification does not reflect the observed photosynthesis and transpiration flux variation. Statistically derived groups of sites do not share common vegetation types or climates. The derived parameters can be used to explore alternative classification schemes. }, added-at = {2019-08-14T18:35:35.000+0200}, author = {Groenendijk, M. and Dolman, A. J. and van der Molen, M. K. and Leuning, R. and Arneth, A. and Delpierre, N. and Gash, J. H. C. and Lindroth, A. and Richardson, A. D. and Verbeeck, H. and Wohlfahrt, G.}, biburl = {https://www.bibsonomy.org/bibtex/2f05ba1e28e6018228df38e745cb77b29/karinawilliams}, citeulike-article-id = {8013315}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.agrformet.2010.08.013}, comment = {(private-note)has table of vcmax25 derived for different pfts uses satelite-derived lai; "A critical part of the model structure is the upscaling from leaf to ecosystem model parameters based on LAI. We use satellite derived values of LAI, which is for most sites a representation of a larger area than covered by the eddy covariance flux footprint. Especially when the vegetation representation of the two observations are not in agreement errors will be introduced. In the subtropical Mediterranean region the fluxes are overestimated, particularly during summer. This is a result of the use of annual model parameters which are scaled with LAI, which may not be able to describe structural adaptation of vegetation to drought. The poor quality of the simulated fluxes for the savanna sites may be attributed to the fact that this vegetation type consists of a combination of grasslands and trees, with different vegetation characteristics that cannot be scaled up with one single value for LAI. This problem has an impact on the variation of model parameters. Further work is needed to quantify this impact, and to investigate other possibilities for the upscaling from leaf to ecosystem." "The reduction of photosynthesis when soil water is limited..." has equation, theta\_min and theta\_max are the min and max vol. soil water observed at that site. "LAI is derived from the MODIS database and is used as a proxy for phenology (ORNL DAAC, 2009). This database contains 8-day composite values of LAI for each site based on 7 km × 7 km data sets centered around the sites. From these pixels the average is calculated from observations with no clouds and no presence of snow or ice. The 8-day composites are linearly interpolated to determine daily values."}, day = 02, doi = {10.1016/j.agrformet.2010.08.013}, interhash = {97aa0641ef9a15b0081a5f501ce47e58}, intrahash = {f05ba1e28e6018228df38e745cb77b29}, issn = {01681923}, journal = {Agricultural and Forest Meteorology}, keywords = {imported}, month = jan, number = 1, pages = {22--38}, posted-at = {2017-10-11 10:49:04}, priority = {2}, timestamp = {2019-08-14T18:35:35.000+0200}, title = {Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data}, url = {http://dx.doi.org/10.1016/j.agrformet.2010.08.013}, volume = 151, year = 2011 }