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Modeling predictive assessment of carbon storage using InVEST model in Uva province, Sri Lanka

Modeling predictive assessment of carbon storage using InVEST model in Uva province, Sri Lanka In the twentieth century, climate change has become one of the most severe environmental threats in the world. Carbon sequestration and storage by natural forests are considered as one of the most vital ecosystem services that reduce atmospheric CO2 which accelerates climate change. Therefore modeling the spatial distribution of carbon storage is necessary when combating climate change. Although the Uva province in Sri Lanka consists of more than ~ 50% of such forests and scrublands, the spatial distribution and quantification of carbon storage are rarely studied. Thus, the prime objective of the current study was to model and estimate the carbon storage of the Uva province in Sri Lanka using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST 3.7.0) carbon storage and sequestration modeling software. The model summarized results into a raster output of the spatial distribution of carbon storage. The results revealed that with a land area of 850,000 hectares, the study area currently stores 9663.5 million tons of carbon whereas carbon storage varies within different land use land cover (LULC) types. The LULC types with rich vegetation had a higher amount of carbon stored on a per hectare basis and vice-versa. Natural forests obtained the largest carbon stored with 6863.6 million tons which comprise ~ 71% of the total carbon stock in the area. However, this study highlights the importance of natural forests for carbon storage whereas these outcomes could be effectively used in the preparation of environmental management plans, making environmental policies, and establishing country development plans conducted by the government and other organizations. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Modeling Earth Systems and Environment Springer Journals

Modeling predictive assessment of carbon storage using InVEST model in Uva province, Sri Lanka

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References (62)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021
ISSN
2363-6203
eISSN
2363-6211
DOI
10.1007/s40808-021-01207-3
Publisher site
See Article on Publisher Site

Abstract

In the twentieth century, climate change has become one of the most severe environmental threats in the world. Carbon sequestration and storage by natural forests are considered as one of the most vital ecosystem services that reduce atmospheric CO2 which accelerates climate change. Therefore modeling the spatial distribution of carbon storage is necessary when combating climate change. Although the Uva province in Sri Lanka consists of more than ~ 50% of such forests and scrublands, the spatial distribution and quantification of carbon storage are rarely studied. Thus, the prime objective of the current study was to model and estimate the carbon storage of the Uva province in Sri Lanka using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST 3.7.0) carbon storage and sequestration modeling software. The model summarized results into a raster output of the spatial distribution of carbon storage. The results revealed that with a land area of 850,000 hectares, the study area currently stores 9663.5 million tons of carbon whereas carbon storage varies within different land use land cover (LULC) types. The LULC types with rich vegetation had a higher amount of carbon stored on a per hectare basis and vice-versa. Natural forests obtained the largest carbon stored with 6863.6 million tons which comprise ~ 71% of the total carbon stock in the area. However, this study highlights the importance of natural forests for carbon storage whereas these outcomes could be effectively used in the preparation of environmental management plans, making environmental policies, and establishing country development plans conducted by the government and other organizations.

Journal

Modeling Earth Systems and EnvironmentSpringer Journals

Published: Jun 1, 2022

Keywords: Carbon storage and sequestration; GIS; InVEST; Sri Lanka; Uva province

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