Jonathan Seaquist

Declining biological production as a part of an ongoing land degradation process is considered a severe environmental problem in the dry northern and northwestern regions of China. The aim of this study is to develop and adapt a satellite data-driven gross primary production model called Lund University light use efficiency model (LULUE) to temperate conditions in order to map gross primary production (GPP) for the Grasslands of Inner Mongolia Autonomous Region (IMAR), China, from 1982 to 1999. The water stress factor included in the original model has been complemented with two temperature stress factors. In addition, algorithms that allocate the proportions of C3/C4 photosynthetic pathways used by plants and that compute temperature-based C3 maximum efficiency values have been incorporated in the model. The applied light use efficiency (LUE) model is using time series of the Normalized Difference Vegetation Index (NDVI), CLouds from AVHRR (CLAVR) from the 8-km resolution NOAA Pathfinder Land Data Set (PAL). Quasi-daily rainfall and monthly minimum and maximum temperatures, together with soil texture information, are used to compute water limitations to plant growth. The model treats bare soil evaporation and actual transpiration separately, a refinement that is more biophysically realistic, and leads to enhanced precision in our water stress term, especially across vegetation gradients. Based on ground measurements of net primary production (NPP) at one site, the LULUE reproduces the variability of primary production better than CENTURY or NDVI alone. Mean annual GPP between 1982 and 1999 range from about 100 g/m(2) in desert regions in the west to about 4000 g/m(2) in the northeast of IMAR, and the coefficient of variation for GPP is highest near the margins of the deserts in the west where rainfall is erratic. Linear trends fitted through the 18-year time series reveal that the western regions have encountered no change, while a large area in the center of the IMAR shows marked increases in GPP. In the northeast, negative trends in GPP are noted and coincide with rainfall trends. Though the high inter-annual variability in primary production undermines the identification of significant trends, we could not isolate any general decline in grassland primary production.