Abstract

Abstract. Several studies sustained the possibility that a photochemical reflectance index (PRI) directly obtained from satellite data can be used as a proxy for ecosystem light use efficiency (LUE) in diagnostic models of gross primary productivity. This modelling approach would avoid the complications that are involved in using meteorological data as constraints for a fixed maximum LUE. However, no unifying model predicting LUE across climate zones and time based on MODIS PRI has been published to date. In this study, we evaluate the effectiveness with which MODIS-based PRI can be used to estimate ecosystem light use efficiency at study sites of different plant functional types and vegetation densities. Our objective is to examine if known limitations such as dependence on viewing and illumination geometry can be overcome and a single PRI-based model of LUE (i.e. based on the same reference band) can be applied under a wide range of conditions. Furthermore, we were interested in the effect of using different faPAR (fraction of absorbed photosynthetically active radiation) products on the in-situ LUE used as ground truth and thus on the whole evaluation exercise. We found that estimating LUE at site-level based on PRI reduces uncertainty compared to the approaches relying on a maximum LUE reduced by minimum temperature and vapour pressure deficit. Despite the advantages of using PRI to estimate LUE at site-level, we could not establish an universally applicable light use efficiency model based on MODIS PRI. Models that were optimised for a pool of data from several sites did not perform well.

Highlights

  • Sound estimates of gross primary productivity (GPP) are essential for an accurate quantification of the global carbon cycle and an understanding of its variability (Schulze, 2006)

  • We evaluate the effectiveness with which MODIS-based photochemical reflectance index (PRI) can be used to estimate ecosystem light use efficiency (LUE) at study sites of four distinct plant functional types and different vegetation densities

  • Note that this LUE is not derived from the standard MOD17 parameters, but from parameters that have been optimised per site and year

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Summary

Introduction

Sound estimates of gross primary productivity (GPP) are essential for an accurate quantification of the global carbon cycle and an understanding of its variability (Schulze, 2006). Many diagnostic models of primary productivity are based on a light use efficiency approach (Running et al, 2000; Yuan et al, 2007; Beer et al, 2010, e.g.). All light use efficiency models represent photosynthetic assimilation of vegetation as a function of the amount of photosynthetically active radiation absorbed by plants (aPAR) (Monteith, 1972; Running et al, 2000). Where faPAR is the fraction of absorbed photosynthetically active radiation The simplicity of this approach, with little need for ancillary data, makes it possible to base these models on remote sensing products and meteorological fields (Hilker et al, 2008c; McCallum et al, 2009). An important prerequisite for application on the global scale is fulfilled

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