Assessment of land ecosystem health with Monte Carlo simulation: A case study in Qiqihaer, China

A better understanding of the level of land ecosystem health in a region is helpful for policymakers in developing measures for eco-space management. During the evaluation process, uncertainty is inevitable because of different methods of determining the related weights. In this study, a Monte Carlo simulation was used to construct a sample of the indicator weights to quantify the uncertainty in the process of land ecosystem health assessment to improve the accuracy of the assessment result. This study used a new evaluation framework of pressure, state (vigor-organization -resilience-function) and response to assess the level of land ecosystem health in Qiqihaer City from 2000 to 2015. Then, the spatial heterogeneity among the levels of land ecosystem health was examined using hotspot spatial analyses. Our results showed the following: (1) the overall level of land ecosystem health in Qiqihaer city was ordinary (Ⅲ), and the average values of the related indices were 0.554 (2000) and 0.563 (2015). Hotspots and coldspots identified by the land ecosystem health index had obvious overlapping areas from 2000 to 2015, among them, approximately 30.6% of the hotspot area (high-value area) was located in the Zhalong Nature Reserve, and approximately 15.6% of the coldspot area (low-value area) was located in city centres and the boundary of the study area. (2) The average values of the land ecosystem health pressure and response indexes were low, while the average values of the land ecosystem health states index changed greatly. However, in terms of spatial heterogeneity, the spatial differences were small for the pressure index and the states index, and the spatial difference in the response index was large. The assessment results objectively reflect the health status of the regional land ecosystem and have very important theoretical and practical significance for safeguarding similar regional ecological security and promoting social and economic sustainable development.