气候变化领域集成服务门户(CCPortal): Predicting the impacts of anthropogenic drivers on management scenarios using Bayesian belief network in the Zeribar freshwater wetland, Iran

CCPortal

DOI	10.1016/j.jnc.2024.126570
	Predicting the impacts of anthropogenic drivers on management scenarios using Bayesian belief network in the Zeribar freshwater wetland, Iran
	Pishdad, Leila; Sadoddin, Amir; Najafinejad, Ali
发表日期	2024
ISSN	1617-1381
EISSN	1618-1093
起始页码	78
卷号	78
英文摘要	The Zeribar wetland in Iran's western city of Marivan provides a valuable foundation for maintaining various aspects of social and cultural life, from water supply to recreational values, as well as for natural habitats. However, its different services have been put under strong anthropogenic pressure and urbanization processes. The present study is a part of ongoing efforts to improve understanding of the anthropogenic factors potential impact on management status of this vulnerable freshwater ecosystem, aiming to provide integrated management strategies using a Bayesian belief network (BBN) approach. A conceptual framework supporting the BBN was designed according to the main determining factors of the wetland's management including humaninduced factors, economic factors and human capital, policy context and social and cultural issues. The BBN model was parameterized using different data sources comprising literature review, face-to-face interviews, filed observation, model simulations, and experts' knowledge. Stakeholders' feedback on model accuracy and management strategies application was assessed in different workshops with representatives from locals, executives, and scientific communities. The results showed that the two subsystems of policy context and economic factors and human capital are the most important key factors influencing the target node, wetland management status. Then, fourteen alternative management scenarios (S2- S15) were generated using the improvement in prior probabilities of influencing factors, followed by evaluation and statistical comparison with the output of the current condition as the base-case scenario (S1). Under the S1 scenario, the probability of occurrence of the Strong state, in which the wetland is properly protected from anthropogenic disturbances, for the target node of the network was 25.8 %, while the most significant improvement in the wetland management status (66.4%) was observed after an improvement in all influencing variables was adopted (S15), suggesting a significant potential for improvement in the wetland management. According to the stakeholders' feedback, the constructed BBN model, and the components included in the management scenarios are useful to fill a critical gap in the current management framework. The results of this work can assist decision-makers in managing the wetland more effectively by considering all socio-economic and anthropogenic dynamics.
英文关键词	Conservation management; Conceptual framework; Bayesian network; Policy development; Socio-economic factors; Wetland management scenario
语种	英语
WOS研究方向	Biodiversity & Conservation ; Environmental Sciences & Ecology
WOS类目	Biodiversity Conservation ; Ecology
WOS记录号	WOS:001185031300001
来源期刊	JOURNAL FOR NATURE CONSERVATION
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/305086
作者单位	Gorgan University of Agricultural Sciences & Natural Resources; University of Kurdistan
推荐引用方式 GB/T 7714	Pishdad, Leila,Sadoddin, Amir,Najafinejad, Ali. Predicting the impacts of anthropogenic drivers on management scenarios using Bayesian belief network in the Zeribar freshwater wetland, Iran[J],2024,78.
APA	Pishdad, Leila,Sadoddin, Amir,&Najafinejad, Ali.(2024).Predicting the impacts of anthropogenic drivers on management scenarios using Bayesian belief network in the Zeribar freshwater wetland, Iran.JOURNAL FOR NATURE CONSERVATION,78.
MLA	Pishdad, Leila,et al."Predicting the impacts of anthropogenic drivers on management scenarios using Bayesian belief network in the Zeribar freshwater wetland, Iran".JOURNAL FOR NATURE CONSERVATION 78(2024).