Ecosystem health assessment of desert nature reserve with entropy weight and fuzzy mathematics methods: A case study of Badain Jaran Desert

Abstract The Badain Jaran Desert is the fourth largest desert in the world, and its ecological environment has received widespread attention. In order to accurately assess the ecosystem health of the desert, the entropy weight method and fuzzy mathematics method were used on a spatial scale. This study builds an assessment indicator system based on the criteria of physiological factors, ecological factors and environmental factors. 11 indicators from field surveys, laboratory analysis and remote sensing are selected including biomass, net primary productivity (NPP), fractional vegetation cover (FVC), water use efficiency (WUE), light utility efficiency (LUE), soil crust, soil water content, precipitation, soil organic matter, soil nutrient and species diversity. The results showed that most areas of Badain Jaran Desert were in healthy and sub-healthy status. the area in healthy and sub-healthy status accounting for 68.1% and 27.7% of the total area, respectively. there is 4% of the total area encounter an unhealthy status, and 0.2% of present the sick status. The unhealthy and sick areas were mainly distributed in the areas with frequent human activities on the edge of the desert, while the healthy and sub-healthy status are mainly distributed in the interior of the desert, indicating that the overall ecological environment of Badain Jaran Desert was relatively stable, but the protection and restoration of the ecological environment in the periphery of the desert need to be strengthened to prevent further degradation. The purpose of this study was to form a technical system of ecosystem health assessment in arid desert nature reserve, providing technical support for ecosystem health assessment, ecosystem degradation monitoring, disease prevention, ecosystem protection and restoration, sustainable development of the reserve and ecosystem health control in arid desert nature reserve.