Abstract

Scientists have assessed the assessment of ecological vulnerability (EV) under conditions of human activity; however, the performance of existing frameworks still needs to be improved to meet the challenges of assessment. In this study, a framework that combines ecological sensitivity and ecological risk as the end point of EV assessment was established, and was used to investigate the spatiotemporal characteristics and major environmental issues of EV in Qiqihaer City, northwest of the Songnen Plain. At the same time, the Hemeroby index was introduced to explore the level of human disturbances in the high-high (HH) and low-low (LL) agglomeration areas of the ecological vulnerability index (EVI). The results show the following: (1) For the temporal dimension, from 2000 to 2015, the level of EV of the study area was moderate. For the subsystems, the land desertification sensitivity index (LSI), soil erosion sensitivity index (SSI) and ecological risk index (ERI) all showed downward trends; among these indices, the SSI and LSI decreased significantly, and the reductions were 0.0644 and 0.0516, respectively. (2) For the spatial dimension, from 2000 to 2015, EVI and subsystems showed strong spatial autocorrelation, and their spatial structural differences were more significant. Moreover, these indicators have certain internal connections, and their spatial distribution is clustered rather than random. (3) In the HH and LL regions of the EVI, the level of the human disturbance index was VI, and the proportion of this level in the HH region was higher than that in the LL region. The research results are of great significance for ecological protection, land resource utilization and sustainable development in similar areas. • Linking ecological sensitivity and risk to assessment ecological vulnerability (EV). • In the high-value area of EV, ecological land accounts for a relatively large area. • In the low-value area of EV, the level of human disturbance is relatively low. • The EV based human disturbance can provide basis for ecosystem management decisions.

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