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Title: Projecting global and regional forest area under the Shared Socioeconomic Pathways using an updated Environmental Kuznets Curve model

Source: Forests

Author(s)Nepal, Prakash ; Korhonen, Jaana ; Prestemon, Jeffrey P.; Cubbage, Frederick W.

Publication Year: 2019  View PDF »

Category: Journal Articles

Abstract: 

Forest resources are critical to environmental, economic, and social development, and there is substantial interest in understanding how global forest area will evolve in the future. Using an Environmental Kuznets Curve (EKC) model of total forest area that we updated using more recent data sets, we projected forest area through 2100 in 168 countries using variables including income, rural population density, and the size of the labor force under different world visions drawn from alternative. Intergovernmental Panel on Climate Change socioeconomic pathways (SSPs). Results provided support for the existence of an EKC for total forest area, with rural population density negatively affecting forest area and labor force size positively affecting forest area. The projections showed modest and continuous increases in global forest area in all the SSPs, but varying trends for major world regions, which is consistent with the projected trends from the explanatory variables in each country. Aggregate global forest area is projected to increase by 7% as of 2100 relative to 2015 levels in SSP3, which predicts a future with the lowest rate of economic growth, and by 36% in SSP5, which is a future with the highest rate of economic growth and greater economic equality across countries. The results show how projections driven only by income produce biased results compared to the projections made with an EKC that includes rural population density and labor force variables.



Keywords: Environmental Kuznets Curve; shared socioeconomic pathways; global forest area projections; forest sector modeling; forest sector policy

Publication Review Process: Formally Refereed

File size: 2,048 kb(s)

Date posted: 05/28/2019

This publication is also viewable on Treesearch:  view
RITS Product ID: 94111

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