Grazing intensity monitoring in Northern China steppe: Integrating CENTURY model and MODIS data

• Published in: Ecological indicators Vol. 11; no. 1; pp. 175 - 182
• Main Authors: Feng, X.M., Zhao, Y.S.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.01.2011
• Subjects: aboveground biomass; anthropogenic activities; atmospheric precipitation; CENTURY; China; climate change; Computer simulation; correlation; dust storms; Ecosystems; Grazing; Grazing intensity; growing season; humans; land cover; land use; livestock; moderate resolution imaging spectroradiometer; MODIS; MODIS data; Monitoring; remote sensing; Seasons; simulation models; soil water content; Spatial variation; Steppe grassland; Steppes; temperature; vegetation cover; China; China, People's Rep., Inner Mongolia; China, People's Rep; Steppe grassland; Spatial variation; CENTURY; MODIS data; Grazing intensity
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2009.07.002

Steppe, an important belt to protect North China from dust storms, is vulnerable and has been degraded in recent decades because of climatic change and heavy grazing. In order to improve steppe management, this study presents a framework for the monitoring of grazing intensity in Xilingol steppe of middle Inner Mongolia, northern China, by integrating the CENTURY ecosystem model-based simulation and remotely sensed MODIS data-based inversion. The CENTURY model worked well after calibrations using field data 1991–1995 of Xilinhaote and Zhenglan Banner observation stations (the correlation coefficient between simulated and observed above ground biomass (AGB) is 0.85). In order to run CENTURY spatially, regional input were formulated including data such as temperature, precipitation, AGB and soil water content (SWC) at the beginning of growing season in 2002, vegetation cover and land use. The modeled AGB at the end of the growing season in 2002 was compared with that inverted from MODIS data. The spatial variation of grazing in the research area was estimated with an iterative adjusting method. Results showed that grazing is variable throughout the study area. Grazing intensity is high and concentrated in the southwest and middle of Abarger Banner, and is low and extensive on the south of Xilinhaote, west of West Ujumchin Banner and northwest of Keshiketeng Banner. This result is comparable with the field conditions. From this work, it can be concluded that human activities such as livestock grazing can be monitored at broad scales with the integration of ecosystem modeling and remote sensing approaches.