DOI: 10.1016/j.marpolbul.2014.04.011
Scopus记录号: 2-s2.0-84902081121
论文题名: A study of anthropogenic and climatic disturbance of the New River Estuary using a Bayesian belief network
作者: Nojavan A. F. ; Qian S.S. ; Paerl H.W. ; Reckhow K.H. ; Albright E.A.
刊名: Marine Pollution Bulletin
ISSN: 0025-326X
EISSN: 1879-3363
出版年: 2014
卷: 83, 期: 1 起始页码: 107
结束页码: 115
语种: 英语
英文关键词: Bayesian belief network
; Estuarine eutrophication
; Harmful algal blooms
; Hypoxia
; Nutrients
; Water quality
Scopus关键词: Complex networks
; Estuaries
; Eutrophication
; Nutrients
; River pollution
; Water quality
; Conditional probability tables
; Harmful algal blooms
; Hypoxia
; Knowledge communication
; Moment matching method
; North Carolina , USA
; Scientific discipline
; Water quality indicators
; Bayesian networks
; algal bloom
; anthropogenic effect
; Bayesian analysis
; bioindicator
; climate effect
; estuarine ecosystem
; eutrophication
; hypoxia
; marine pollution
; nutrient enrichment
; pollution effect
; water quality
; article
; Bayesian belief network
; climate
; estuary
; eutrophication
; nonhuman
; nutrient
; probability
; sea pollution
; statistical analysis
; statistical model
; United States
; water management
; water quality
; Bayes theorem
; climate
; climate change
; ecosystem
; theoretical model
; New River Estuary
; North Carolina
; United States
; algae
; Bayes Theorem
; Climate
; Climate Change
; Ecosystem
; Estuaries
; Eutrophication
; Models, Theoretical
; North Carolina
; Water Quality
Scopus学科分类: Agricultural and Biological Sciences: Aquatic Science
; Earth and Planetary Sciences: Oceanography
; Environmental Science: Pollution
英文摘要: The present paper utilizes a Bayesian Belief Network (BBN) approach to intuitively present and quantify our current understanding of the complex physical, chemical, and biological processes that lead to eutrophication in an estuarine ecosystem (New River Estuary, North Carolina, USA). The model is further used to explore the effects of plausible future climatic and nutrient pollution management scenarios on water quality indicators. The BBN, through visualizing the structure of the network, facilitates knowledge communication with managers/stakeholders who might not be experts in the underlying scientific disciplines. Moreover, the developed structure of the BBN is transferable to other comparable estuaries. The BBN nodes are discretized exploring a new approach called moment matching method. The conditional probability tables of the variables are driven by a large dataset (four years). Our results show interaction among various predictors and their impact on water quality indicators. The synergistic effects caution future management actions. © 2014 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/85500
Appears in Collections: 过去全球变化的重建 全球变化的国际研究计划
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作者单位: Nicholas School of the Environment, Duke University, Durham, NC 27708, United States; Department of Environmental Sciences, University of Toledo, Toledo, OH 43606, United States; Institute of Marine Sciences, University of North Carolina at Chapel Hill, Morehead City, NC 28557, United States
Recommended Citation:
Nojavan A. F.,Qian S.S.,Paerl H.W.,et al. A study of anthropogenic and climatic disturbance of the New River Estuary using a Bayesian belief network[J]. Marine Pollution Bulletin,2014-01-01,83(1)