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Identification of Conservation Priority Zones Using Spatially Explicit Valued Ecosystem Services: A Case from the Indian Sundarbans.
Sannigrahi, Srikanta; Pilla, Francesco; Basu, Bidroha; Basu, Arunima Sarkar; Zhang, Qi; Wang, Ying; Joshi, Pawan Kumar; Chakraborti, Suman; Coscieme, Luca; Keesstra, Saskia; Roy, P S; Sutton, Paul C.
Afiliación
  • Sannigrahi S; School of Architecture, Planning, and Environmental Policy, University College Dublin, Richview, Dublin, Ireland.
  • Pilla F; School of Architecture, Planning, and Environmental Policy, University College Dublin, Richview, Dublin, Ireland.
  • Basu B; School of Architecture, Planning, and Environmental Policy, University College Dublin, Richview, Dublin, Ireland.
  • Basu AS; School of Architecture, Planning, and Environmental Policy, University College Dublin, Richview, Dublin, Ireland.
  • Zhang Q; Frederick S Pardee Center for the Study of the Longer-Range Future, Frederick S Pardee School of Global Studies, Boston University, Boston, Massachusetts, USA.
  • Wang Y; School of Public Administration, China University of Geosciences, Wuhan.
  • Joshi PK; School of Environmental Sciences (SES), Jawaharlal Nehru University, New Delhi, India.
  • Chakraborti S; Center for the Study of Regional Development (CSRD), Jawaharlal Nehru University, New Delhi, India.
  • Coscieme L; School of Natural Sciences, Trinity College Dublin, Dublin, Ireland.
  • Keesstra S; Soil, Water and Land-use Team, Wageningen, University and Research, Wageningen, the Netherlands.
  • Roy PS; Civil, Surveying and Environmental Engineering, The University of Newcastle, Callaghan, Australia.
  • Sutton PC; System Analysis for Climate Smart Agriculture, Innovation Systems for the Dry Lands, ICRISAT, Patancheru, India.
Integr Environ Assess Manag ; 16(5): 773-787, 2020 Sep.
Article en En | MEDLINE | ID: mdl-32406993
Demarcation of conservation priority zones (CPZs) using spatially explicit models is the new challenge in ecosystem services (ESs) research. This study identifies the CPZs of the Indian Sundarbans by integrating 2 different approaches, that is, ESs and ecosystem health (EH). Five successive steps were followed to conduct the analysis: First, the ESs were estimated using biophysical and economic methods and a hybrid method (that combines biophysical and economic methods); second, the vigor-organization-resilience (VOR) model was used for estimating EH; third, the risk characterization value (RCV) of ESs was measured using the function of EH and ESs; fourth, Pearson correlation test was performed to analyze the interaction between ESs and EH components; and fifth, the CPZs were defined by considering 7 relevant components: ecosystem vigor, ecosystem organization, ecosystem resilience, RCV, EH, ESs, and the correlation between EH and ESs. Among the major ecoregions of the Sundarbans, the highest ESs value in economic terms is provided by the mangrove ecosystem (US$19 144.9 million per year). The highest conservation priority score was projected for the Gosaba block, which is dominated by dense mangrove forests. The estimated CPZs were found to be highly consistent with the existing biodiversity zonations. The outcome of this study could be a reference for environmentalists, land administrators, researchers, and decision makers to design relevant policies to protect the high values of the Sundarbans ecosystem. Integr Environ Assess Manag 2020;16:773-787. © 2020 SETAC.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Ecosistema / Conservación de los Recursos Naturales Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Integr Environ Assess Manag Año: 2020 Tipo del documento: Article País de afiliación: Irlanda

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Ecosistema / Conservación de los Recursos Naturales Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Integr Environ Assess Manag Año: 2020 Tipo del documento: Article País de afiliación: Irlanda
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