Time Course of Radiation Use Efficiency in a Shortgrass Ecosystem: Consequences for Remotely Sensed Estimation of Primary Production

A reliable estimation of primary production of terrestrial ecosystems is often a prerequisite for land survey and management, while being important also in ecological and climatological studies. At a regional scale, grassland primary production estimates are increasingly being made with the use of satellite data. In a currently used approach, regional gross, net, and aboveground net primary productivity (GPP, NPP, and ANPP) are derived from the parametric model of Monteith and are calculated as the product of the fraction of incident photosynthetically active radiation absorbed by the canopy (fAPAR) and gross, net, and aboveground net production (radiation-use) efficiencies (ϵg, ϵn, and ϵan); fAPAR being derived from indices calculated from satellite-measured reflectances in the red and near infrared. The accuracy and realism of the primary production values estimated by this approach therefore largely depend on an accurate estimation of ϵg, ϵn, and ϵan. However, data are scarce for production efficiencies of semiarid grasslands, and their time and spatial variations are poorly documented, often leading to large errors for the estimates. In this paper, a modeling approach taking into account relevant ecosystem processes and based on extensive field data was used to estimate time variations of ϵg, ϵn and ϵan of a shortgrass site in Arizona. These variations were explained by variations in plant water stress, temperature, leaf aging, and processes such as respiration and changes in allocation pattern between above- and below-ground compartments. Over the 3 study years, averaged values of ϵg, ϵn, and ϵan were found to be 1.92, 0.74, and 0.29 g DM (MJ IPAR)−1, respectively. ϵg and ϵn exhibited large interannual and seasonal variations mainly due to changes in water limitations during the growing season. Interannual variations of ϵan were much less important. However, for shorter periods, ϵan exhibited very contrasting values from regrowth to senescence. The calculation of ANPP seems less prone to errors due to environmental effects when computed on an annual basis. When estimating GPP and NPP, better results are expected if water limitations are taken into account. This could be possible through the estimation of a water-stress factor by using surface temperature or other indices derived from thermal infrared remote sensing data. The limitations due to temporally varying efficiencies, shown here for shortgrass ecosystems, are also relevant to all drought-exposed ecosystems, particularly those with abundant evergreen or perennial species.