Responses analysis of ecosystem functional variables to land surface biophysical and climate variables using satellite imagery in Mongolia

In arid and semi-arid regions, any change in precipitation regime and summer thermal stresses could alter ecosystem function, such as vegetation productivity and evapotranspiration (ET). In this study, we investigated the responses of ecosystem function to land surface biophysical variables derived from satellite observations in Mongolia over the last 10 years. Our specific purposes are to examine spatial and temporal patterns of vegetation indices, land surface temperature (LST), soil moisture (SM), and climatic variables; and to investigate the responses of gross primary productivity (GPP) and ET to land surface biophysical variables. Various satellite datasets were prepared, including land cover, NDVI, albedo, LST, air temperature and vapor pressure deficit (VPD) from MODIS, and AMSR-E SM data for a period of 2000-2011 (partially from 2002 to 2011). We used ET and GPP data produced by the Breathing Earth System Simulator (BESS) using MODIS atmosphere and land products as ecosystem functional variables. Additionally, we collected monthly temperature and precipitation data from 67 weather stations in Mongolia. NDVI explained well the spatial and temporal variations of GPP. With respect to land cover and elevation gradients, the biophysical and climatic variables varied distinctly. Precipitation explained 78% of the spatial variation of NDVI. Regions with lower NDVI showed good positive correlations between NDVI and precipitation. On the other hand, the permafrost regions with higher NDVI showed good positive correlations between NDVI and LST. Our results indicate that NDVI temporal variations is significantly associated with precipitation (r > 0.74), and satellite-driven LST also provides useful information on dryland vegetation dynamics (r < -0.77). In this presentation, it was addressed the responses of ET and GPP to the land surface biophysical and climatic variables. Our study demonstrates usefulness of satellite data in understanding temporal and spatial dynamics of dryland ecosystem biophysical variables and analyzing responses of ecosystem functional variables to the biophysical and climatic variables.