globalchange  > 气候变化与战略
DOI: 10.1016/j.scitotenv.2020.137004
论文题名:
Responses of ecosystem services to natural and anthropogenic forcings: A spatial regression based assessment in the world's largest mangrove ecosystem
作者: Sannigrahi S.; Zhang Q.; Pilla F.; Joshi P.K.; Basu B.; Keesstra S.; Roy P.S.; Wang Y.; Sutton P.C.; Chakraborti S.; Paul S.K.; Sen S.
刊名: Science of the Total Environment
ISSN: 489697
出版年: 2020
卷: 715
语种: 英语
英文关键词: Biophysical and economic valuation ; Climate change ; Data dimensionality ; Ecosystem services ; Spatial regression ; Sundarbans
Scopus关键词: Biophysics ; Climate change ; Climate models ; Decision making ; Economics ; Principal component analysis ; Regression analysis ; Data dimensionality ; Economic valuation ; Ecosystem services ; Spatial regression ; Sundarbans ; Ecosystems ; accuracy assessment ; action plan ; anthropogenic source ; decision making ; ecosystem service ; environmental economics ; land management ; mangrove ; spatial analysis ; administrative personnel ; article ; climate change ; dimensionality reduction ; ecosystem ; human ; India ; mangrove ; nonhuman ; quantitative analysis ; spatial regression ; Sundarbans
英文摘要: Most of the Earth's Ecosystem Services (ESs) have experienced a decreasing trend in the last few decades, primarily due to increasing human dominance in the natural environment. Identification and categorization of factors that affect the provision of ESs from global to local scales are challenging. This study makes an effort to identify the key driving factors and examine their effects on different ESs in the Sundarbans region, India. We carry out the analysis following five successive steps: (1) quantifying biophysical and economic values of ESs using three valuation approaches; (2) identifying six major driving forces on ESs; (3) categorizing principal data components with dimensionality reduction; (4) constructing multivariate regression models with variance partitioning; (5) implementing six spatial regression models to examine the causal effects of natural and anthropogenic forcings on ESs. Results show that climatic factors, biophysical factors, and environmental stressors significantly affect the ESs. Among the six driving factors, climate factors are highly associated with the ESs variation and explain the maximum model variances (R2 = 0.75–0.81). Socioeconomic (R2 = 0.44–0.66) and development (R2 = 27–0.44) factors have weak to moderate effects on the ESs. Furthermore, the joint effects of the driving factors are much higher than their individual effects. Among the six spatial regression models, Geographical Weighted Regression (GWR) performs the most accurately and explains the maximum model variances. The proposed hybrid valuation method aggregates biophysical and economic estimates of ESs and addresses methodological biases existing in the valuation process. The presented framework can be generalized and applied to other ecosystems at different scales. The outcome of this study could be a reference for decision-makers, planners, land administrators in formulating a suitable action plan and adopting relevant management practices to improve the overall socio-ecological status of the region. © 2020 Elsevier B.V.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/158322
Appears in Collections:气候变化与战略

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作者单位: School of Architecture, Planning, and Environmental Policy, University College Dublin, Richview, Clonskeagh, Dublin, Ireland; The Frederick S. Pardee Center for the Study of the Longer Range Future, Boston University, Boston, MA 02215, United States; School of Environmental Sciences (SES), Jawaharlal Nehru University, New Delhi, 110067, India; Soil, Water and Land-use Team, Wageningen University and Research, Droevendaalsesteeg3, Wageningen, 6708PB, Netherlands; Civil, Surveying and Environmental Engineering, The University of Newcastle, Callaghan, 2308, Australia; System Analysis for Climate Smart Agriculture, Innovation Systems for the Dry lands, ICRISAT, Patancheru, India; School of Public Administration, China University of Geosciences, Wuhan, 430074, China; Department of Geography and the Environment, University of Denver, 2050 East Iliff, Avenue, Denver, CO 80208-0710, United States; Center for the Study of Regional Development (CSRD), Jawaharlal Nehru University, New Delhi, 110067, India; Department of Architecture and Regional Planning, Indian Institute of Technology Kharagpur, Kharagpur, India

Recommended Citation:
Sannigrahi S.,Zhang Q.,Pilla F.,et al. Responses of ecosystem services to natural and anthropogenic forcings: A spatial regression based assessment in the world's largest mangrove ecosystem[J]. Science of the Total Environment,2020-01-01,715
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