1219 | 262 | Assessing ecological risk changes in Wuhan, China | Zhong Zhang
Ecological Risk Assessment (ERA) is a cornerstone of ecosystem management, and aims at identifying potential harms caused by human activities. However, previous ERA approaches typically considered only a single risk factor and failed to provide a comprehensive assessment of the overall ecological risk. To address this issue, we propose a new ERA framework that integrates the Landscape Ecological Risk Index (LERI) and Habitat Degradation Index (HDI) to explore spatiotemporal variations of ecological risk changes in Wuhan from 1996 to 2019. It considers the interrelationships between threat sources and receptors, as well as the morphological structure of patches, to extract the spatial information of ecological risks. Our results indicate that: (1) Wuhan’s cropland decreased by 1760.98km2 (-38.95%), mainly converting to construction land and woodland. Simultaneously, construction land expanded outwards from the city center (+895.72km2). (2) Total Ecological Risk Index (SERI) retains the “low-high-low” pattern of both LERI and HDI from the inside out, and the high ecological risks are characterized by radiation from the central urban boundary to the surrounding areas. The lower-risk areas of the SERI converted mainly to the low-risk areas, and the area of higher-risk experienced a larger increase (+1083.45km2), mainly from high-risk areas, while the total SERI of Wuhan tends to move towards the north and east. (3) Spatially, the hot spots are mainly concentrated in the north of Wuhan, and the cold spots are mainly located in the center of Wuhan. Confidence degrees of both hot and cold spots decrease from their center to the external areas. Additionally, the distribution of High-High and Low-Low clusters are similar to cold-hotspots. Given the current global environmental crisis, ecological risk research is more important than ever, and our new ERA framework is developed to provide valuable insights for urban planners to mitigate ecological risk.
Zhong Zhang
Department of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, China; Hyperspectral Computing Laboratory, Department of Technology of Computers and Communications, Escuela Politécnica, University of Extremadura, Cáceres 10071, Spain.
ID Abstract: 262