ABSTRACT: In this study, based on the regional land-use risk space division (regional ecological risk source/receptor space identification) using production-living-ecology analysis, three spatial function indexes, i.e., production, living, and ecology function indexes, were proposed for regional ecological risk assessment (RERA) with respect to human disturbance. The first two indexes can be regarded as regional ecological risk source indexes, whereas the final index can be regarded as a regional ecological risk receptor index. Using an artificial assignment method based on the land-use types and Defense Meteorological Program Operational Line-Scan System (DMSP/OLS) nighttime light intensity data, these three spatial function indexes were effectively manifested. By incorporating these indexes with eco-environmental vulnerability proxies, an RERA framework was established and applied in the Poyang Lake Eco-economic Zone (PLEZ), which is an ecological-protection and economic-development coordination-oriented region in China. The results suggest that (1) the DMSP/OLS nighttime light intensity data correlated well with the spatial distribution of regional urban/town areas; consequently, it was reasonable to use this dataset for representing regional production-living function space (urban/town area). (2) Overall, the forestlands and winter waterbodies of Poyang Lake were in the high-risk grade, and so did the Nanchang City construction land area; in contrast, the final risk levels of winter wetlands and croplands were relatively low. (3) Owing to the highest human disturbance (including both production and consumption human activities) and eco-environmental vulnerability level, urban/town areas such as Nanchang City had the highest final risk grade. (4) The low, medium, high, and very high-risk grades accounted for 21.22%, 39.53%, 36.31%, and 2.94% of the region, respectively. I believe that the proposed land use function indexes will be helpful in conducting human-caused RERA research in the future. Furthermore, the assessment results can provide a scientific basis for regional ecological risk management within the PLEZ.
