Coastal ecological risk assessment in regional scale: Application of the relative risk model to Xiamen Bay, China. (May 2015)

• Record Type: Journal Article
• Authors: Yu, Weiwei; Zhang, Luoping; Ricci, Paolo F.; Chen, Bin; Huang, Hao
• Is Part Of: Ocean & coastal management. Volume 108(2015)
• Page Start: 131
• Page End: 139
• Publication Date: 2015-05
• Subjects: Marine resources -- Management -- Periodicals; Coastal zone management -- Periodicals; Coastal ecology -- Periodicals; Ressources marines -- Périodiques; Littoral -- Aménagement -- Périodiques; Écologie littorale -- Périodiques; Coastal ecology; Coastal zone management; Marine resources -- Management; Periodicals; Electronic journals; 551.46
• DOI: 10.1016/j.ocecoaman.2014.04.027
• Languages: English
• ISSNs: 0964-5691

Abstract

Abstract: Ecological risk assessment has been regarded as an important tool for environmental management. Ecological risk assessment was conducted using Relative Risk Model in Xiamen Bay, China, the results of which were applied to inform coastal environmental management. The study area was divided into seven sub-regions, and the potentially ecological risks for both the whole bay and sub-regions were predicted and ranked by introducing a source–stressor–receptor–endpoint filter. The results showed that: (i) Jiulong River Estuary was the sub-region with highest risk; the second highest being Tongan Bay; (ii) coastal engineering major works were the biggest sources of routine risk, followed by typhoons and storm surges; (iii) oil spills were the biggest accidents contributing to risk, followed by non-routine discharges; (iv) shallow water swamp ecosystem were most likely to be affected, followed by inter-tidal mudflat ecosystem; (v) species diversity was the endpoint most likely to be affected, with population abundance of protected species being second. Monte Carlo simulations were conducted to examine the effects of uncertainty on those risk prediction. Its results suggested that the probability distributions were consistent with other examples in the literature and as expected that the uncertainty that affects results does not alter the rankings from the relative risk analysis. Highlights: Ecological risks were predicted by introducing a source–stressor–receptor–endpoint filter. Ecological risks were prioritized in terms of sub-regions, sources, accidental stressors, receptors and endpoints. Effects of uncertainty do not alter the rankings from the relative risk analysis. Relative risk model results provide useful information to plan future efforts on coastal management.