The fraction of absorbed photosynthetically active radiation absorbed by plant canopies (FAPAR) is a critical biophysical variable for extrapolating ecophysiological measurements from leaf to landscape scale (Asner et al., 1998). The absorbed PAR represents the available light energy for plant productivity and is therefore the key variable influencing photosynthesis, transpiration and energy balance in most production efficiency models (PEMs; Prince & Goward, 1995; Ruimy et al., 1999; Myneni et al., 2002; Morisette et al., 2006; Gobron et al., 2006). In situ measurement of FAPAR requires simultaneous measurement of photosynthetically active radiation (PAR) above and below a canopy, as well as estimation of the canopy architecture information to account for the nonleaf absorptions (Gower et al., 1999; Huemmrich et al., 2005; Gobron & Verstraete, 2009). This approach is often difficult to implement as it is time-consuming and limited in spatial coverage. Therefore, spatially continuous FAPAR is often derived by either developing empirical relationships with satellite sensor-derived spectral vegetation indices (e.g. Normalized Difference Vegetation Index (NDVI); Prince & Goward, 1995; Fensholt et al., 2004) and leaf area index (LAI; Ruimy et al., 1999) or through inversion of physically based radiative transfer models using satellite remote sensing data as constraints (Knyazikhin et al., 1998; Myneni et al., 2002; Deng et al., 2006; Gobron et al., 2006; Baret et al., 2007).
A number of FAPAR products have been developed from spectral data acquired through satellite sensors (e.g. the Moderate Resolution Imaging Spectroradiometer (MODIS) FAPAR (Knyazikhin et al., 1998); Medium Resolution Imaging Spectrometer (MERIS)-MGVI (Gobron et al., 2002); and CYCLOPES FAPAR (Baret et al., 2007)). However, these FAPAR products often represent the fraction of photosynthetically active radiation absorbed by the whole canopy (i.e. FAPARcanopy), while the vegetation canopy is composed of both photosynthetically active vegetation (PAV) and nonphotosynthetic vegetation (NPV, e.g. branches, stem, senescent foliage; Asner et al., 1998; Zhang et al., 2005, 2009). As the fraction of PAR absorbed by NPV is not utilized in photosynthesis, calculating FAPARcanopy would result in overestimation of the actual FAPAR utilized in initiating photosynthesis in the photosystems (i.e. both photosystem I (PSI) and photosystem II (PSII); hereafter referred to as FAPARps). Asner et al. (1998) reported that in forests with LAI < 3, the nonphotosynthetic components of the canopy (e.g. stem) increased the actual canopy FAPAR by 10–40%. This overrepresentation of FAPAR absorbed by photosynthetic components of the canopy would lead to errors in terrestrial vegetation primary productivity estimates predicted by PEM models that use these datasets. Therefore, there is a need to formulate new approaches to derive only FAPAR absorbed by the photosynthetic components of the canopy (i.e. FAPARps).
Although FAPARps is a crucial input for quantifying plant productivity, it is often ignored or generalized by many researchers when accounting for the amount of PAR used for photosynthesis in PEM at regional to global scales. This is mainly because of a lack of adequate techniques/data to derive this variable at large spatial scales. As measuring FAPARps in the field is quite challenging, few studies have attempted to derive FAPARps. For example, Zhang et al. (2005) used simulated data from a coupled leaf and canopy radiative transfer model (i.e. PROSAIL-2; Jacquemoud & Baret, 1990; Braswell et al., 1996) and MODIS reflectance data to derive different components of FAPAR (i.e. FAPARcanopy, FAPARleaf and FAPARchlorophyll). Their study showed that the estimates of FAPARchlorophyll were indeed lower than those of FAPARcanopy. Hanan et al. (2002) used an inversion approach to derive FAPAR absorbed by canopy chlorophyll from net ecosystem exchange (NEE; CO2) data from eddy covariance flux tower measurements. However, these studies did not suggest how FAPARps could be generated at large spatial scales.
This paper presents an attempt to derive FAPARps using NEE data measured using the eddy covariance method. The derived FAPARps data were then related to contrasting spectral vegetation indices (i.e. two multi-band based vegetation indices – the NDVI (Rouse et al., 1973) and the Enhanced Vegetation Index (EVI; Huete et al., 2002); and a red-edge based vegetation index, the MERIS Terrestrial Chlorophyll Index (Dash & Curran, 2004)) derived from satellite sensor data. The aim of this exercise was to determine the potential of using the vegetation indices as surrogates of FAPARps at large spatial scales. Finally, the paper compares the estimated FAPARps with two operational FAPAR products (i.e. MODIS FAPAR and CYCLOPES FAPAR) with the aim of determining the disparity between these products and the FAPARps.