Ecological restoration of terrestrial ecosystems facilitates environmental protection and enhances sustainable development of land resources. With increasingly severe land degradation, new and effective methods must be developed for the restoration of ecological functions. In this study, we developed a regional risk assessment approach to support the planning of ecological restoration of a terrestrial ecosystem located in the Daye area in central China. The study area was divided into six sub-regions where ecological risks were characterized by building a non-linear model to represent ecological interactions among the risk components there. Socio-economic conditions in the areas were evaluated and presented using an analytic hierarchy process. Assessment of different stakeholders there was conducted based on multiple-criteria decision analysis. Then, integrated assessment was performed using the technique of order preference for an ideal solution. We divided the degraded land in Daye into areas with different priorities for restoration or rectification and presented corresponding sequential time intervals for the action. The results are as follows: (i) the top priority rectification areas (totaling 358 km2) are mainly distributed in northeast and northwest regions; (ii) the high priority rectification areas are concentrated in the central region spanning 226 km2; (iii) the medium priority rectification areas comprised a large amount of arable and forest land spanning 605 km2; and (iv) the low priority rectification areas cover the rest part of the Daye area spanning 195 km2. The assessment tool was proven to be useful in planning regional ecological restoration in terrestrial ecosystems.
Establishment of an integrated decision-making method for planning the ecological restoration of terrestrial ecosystems.
Kai Guo,Xinchang Zhang,Jiamin Liu,Zhi-feng Wu,Min Chen,Kexin Zhang,Yiyun Chen
Published 2020 in Science of the Total Environment
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- Publication year
2020
- Venue
Science of the Total Environment
- Publication date
2020-06-05
- Fields of study
Medicine, Environmental Science
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- Source metadata
Semantic Scholar, PubMed
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