Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data

Agricultural and Forest Meteorology (Impact Factor: 3.76). 01/2011; 151(1):22-38. DOI: 10.1016/j.agrformet.2010.08.013
Source: OAI


The 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. © 2010 Elsevier B.V.

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    • "Using the global TRY data base, Kattge et al. (2011) found that the largest part of the total variance (as much as 75 %) for several traits (including N area and SLA) was found within rather than between PFTs. Similar observations have been made by van Bodegom et al. (2012) and Wullschleger et al. (2014), while Groenendijk (2011) found that PFTs were not useful predictors of community-level photosynthetic traits. Kattge et al. (2011) also showed (in agreement with our results) that this partitioning varies considerably among traits – with some traits predicted well by PFT identity . "
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