Dynamic Bayesian networks for spatiotemporal modeling and its uncertainty in tradeoffs and synergies of ecosystem services: a case study in the Tarim River Basin, China

Ecosystem services (ESs) refer to the benefits that humans obtain from ecosystems. These services are subject to environmental changes and human interventions, which introduce a significant level of uncertainty. Traditional ES modeling approaches often employ Bayesian networks, but they fall short i...

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Bibliographic Details
Published in:	Stochastic environmental research and risk assessment Vol. 38; no. 11; pp. 4311 - 4329
Main Authors:	Hu, Yang, Xue, Jie, Zhao, Jianping, Feng, Xinlong, Sun, Huaiwei, Tang, Junhu, Chang, Jingjing
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2024 Springer Nature B.V
Subjects:	Algorithms Aquatic ecosystems Aquatic Pollution Bayesian analysis Carbon Carbon sequestration Chemistry and Earth Sciences Computational Intelligence Computer Science Earth and Environmental Science Earth Sciences Ecosystem services Ecosystems Environment Environmental changes Environmental quality Habitat changes Habitats Heterogeneity Land use Linear analysis Machine learning Math. Appl. in Environmental Science Mathematical models Modelling Networks Observational learning Original Paper Parameters Physics Probability Theory and Stochastic Processes River basin development River basins River ecology Rivers Soil conservation Spatial discrimination learning Spatial heterogeneity Statistics for Engineering Stochastic models Tradeoffs Uncertainty Waste Water Technology Water conservation Water Management Water Pollution Control Water yield China Markov blanket Ecosystem services Dynamic Bayesian networks EM algorithm Hill-climb algorithm
ISSN:	1436-3240, 1436-3259
Online Access:	Get full text
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