Literature DB >> 32045970

Responses of ecosystem services to natural and anthropogenic forcings: A spatial regression based assessment in the world's largest mangrove ecosystem.

Srikanta Sannigrahi1, Qi Zhang2, Francesco Pilla3, Pawan Kumar Joshi4, Bidroha Basu3, Saskia Keesstra5, P S Roy6, Ying Wang7, Paul C Sutton8, Suman Chakraborti9, Saikat Kumar Paul10, Somnath Sen10.   

Abstract

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.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Biophysical and economic valuation; Climate change; Data dimensionality; Ecosystem services; Spatial regression; Sundarbans

Year:  2020        PMID: 32045970     DOI: 10.1016/j.scitotenv.2020.137004

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  6 in total

1.  Divergent socioeconomic-ecological outcomes of China's Conversion of Cropland to Forest Program in the subtropical mountainous area and the semi-arid Loess Plateau.

Authors:  Qi Zhang; Ying Wang; Shiqi Tao; Richard E Bilsborrow; Tong Qiu; Chong Liu; Srikanta Sannigrahi; Qirui Li; Conghe Song
Journal:  Ecosyst Serv       Date:  2020-08-12       Impact factor: 5.454

2.  Evaluating the plausible application of advanced machine learnings in exploring determinant factors of present pandemic: A case for continent specific COVID-19 analysis.

Authors:  Suman Chakraborti; Arabinda Maiti; Suvamoy Pramanik; Srikanta Sannigrahi; Francesco Pilla; Anushna Banerjee; Dipendra Nath Das
Journal:  Sci Total Environ       Date:  2020-10-06       Impact factor: 7.963

3.  Mangrove tree (Avicennia marina): insight into chloroplast genome evolutionary divergence and its comparison with related species from family Acanthaceae.

Authors:  Sajjad Asaf; Abdul Latif Khan; Muhammad Numan; Ahmed Al-Harrasi
Journal:  Sci Rep       Date:  2021-02-11       Impact factor: 4.379

4.  A Bayesian Modelling Framework for Integration of Ecosystem Services into Freshwater Resources Management.

Authors:  Michael Bruen; Thibault Hallouin; Michael Christie; Ronan Matson; Ewa Siwicka; Fiona Kelly; Craig Bullock; Hugh B Feeley; Edel Hannigan; Mary Kelly-Quinn
Journal:  Environ Manage       Date:  2022-02-16       Impact factor: 3.644

5.  Integrating the effects of driving forces on ecosystem services into ecological management: A case study from Sichuan Province, China.

Authors:  Ying Huang; Tian Feng; Shaofei Niu; Desheng Hao; Xiaoyu Gan; Bo Zhou
Journal:  PLoS One       Date:  2022-06-23       Impact factor: 3.752

6.  Spatiotemporal Variation and Driving Forces Analysis of Eco-System Service Values: A Case Study of Sichuan Province, China.

Authors:  Chengjin He; Huaiyong Shao; Wei Xian
Journal:  Int J Environ Res Public Health       Date:  2022-07-14       Impact factor: 4.614

  6 in total

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