Linking ecosystem services and ecosystem health to ecological risk assessment: A case study of the Beijing-Tianjin-Hebei urban agglomeration

• Published in: The Science of the total environment Vol. 636; pp. 1442 - 1454
• Main Authors: Kang, Peng, Chen, Weiping, Hou, Ying, Li, Yuanzheng
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 15.09.2018
• Subjects: Agriculture; Beijing; case studies; China; Comprehensive assessing endpoint; Conservation of Natural Resources - methods; Controlling thresholds; Ecological risk assessment; ecological value; Ecology; Ecosystem; Ecosystem health; Ecosystem service; ecosystem services; ecosystems; environmental assessment; environmental health; Environmental Monitoring; land use; planning; risk; Risk Assessment; Risk hotspots; Urbanization; Comprehensive assessing endpoint; Ecosystem health; Ecosystem service; Controlling thresholds; Ecological risk assessment; Risk hotspots
• ISSN: 0048-9697; 1879-1026; 1879-1026
• DOI: 10.1016/j.scitotenv.2018.04.427

Scientists have paid attention to the evaluation of the risk of ecosystem service degradation under rapid urbanization; yet the performance of the existing frameworks could be improved for tackling the challenges in the evaluation. In this study, a framework combining ecosystem service with ecosystem health as an assessing endpoint of ecological risk assessment was established. The framework was applied to investigate the way in which urbanization influences the ecosystem risk of the Beijing-Tianjin-Hebei urban agglomeration. Firstly, the decrease ratio of ecosystem service was mainly distributed in the range from 0 to 15%; the mean value of ecosystem health decreased from 0.402 to 0.311 from 2000 to 2010. The number of assessment units exhibiting risk degree grade I (the lowest risk degree grade) decreased by 7.03%, while the number of assessment units exhibiting risk degree grade V (the highest risk degree grade) increased by 1.61% from 2000 to 2010. The ratio of artificial surface should be controlled below 70%, based on the fitting model and for the purpose of resilience management. Overall, the analytical framework can comprehensively evaluate the impacts of complex practices in land-use planning on ecosystems. [Display omitted] •Combination of ecosystem service with ecosystem health is an ideal endpoint for ecological risk assessment.•Considering ecosystem complexity, two machine learning model were utilized to simulate and evaluate ecological risk degree.•The ratio of artificial surface should be controlled below 70% for the purpose of resilience management.•The lowest risk degree grade I decreased by 7.03%; while the high risk degree grade V increased by 1.61%.