TY - JOUR

T1 - Identifying the potential areas of afforestation projects using cost-benefit analysis based on ecosystem services and farmland suitability: A case study of the Grain for Green Project in Jinan, China

AU - Li, Kai

AU - Hou, Ying

AU - Andersen, Peter Stubkjær

AU - Xin, Ruhong

AU - Rong, Yuejing

AU - Skov-petersen, Hans

PY - 2021/9/1

Y1 - 2021/9/1

N2 - To mitigate environmental problems and provide ecosystem services (ESs), afforestation projects have been implemented all over the world. However, how to maximize the benefits and minimize the costs of afforestation is still challenging. In this study, we developed a methodology using the cost-benefit analysis (CBA) to identify the potential areas for afforestation (PAAs). Using the Grain for Green Project (GFGP) in the Jinan Planning Zone, China, as a case study, we identified the increase in five ecosystem services (habitat quality, carbon sequestration, soil retention, water conservation, and reduction in non-point source pollution) as the potential benefit and farmland suitability as the potential cost, and used the benefit-cost ratio as the criterion of the PAAs identification. Moreover, we set three GFGP scenarios (mild, moderate, and strong scenarios) according to the GFGP intensity, and compared the PAAs identified by the CBA and those identified by the slope degree method (SDM), which is widely used in the practical GFGP. Based on our methodology and case study, we proposed a decision-making framework for the identification of the PAAs that can be used in different regions. The results show that ES increases and farmland suitability indicators exhibited spatial heterogeneity. Some extremely high values of the comprehensive ES increase were found in the southeast, while low values of comprehensive farmland suitability were aggregated in the northwestern plain. In all the GFGP scenarios, compared with the SDM, the CBA can identify the PAAs with higher benefits at lower costs, which indicates the advantages and stability of the CBA. In the strong scenario, the mean benefit-cost ratio of the PAAs identified by the CBA was 20.82% higher than that of the PAAs identified by the SDM. Overall, the PAAs identification from the cost-benefit perspective can contribute to delicate afforestation management especially when resources are limited.

AB - To mitigate environmental problems and provide ecosystem services (ESs), afforestation projects have been implemented all over the world. However, how to maximize the benefits and minimize the costs of afforestation is still challenging. In this study, we developed a methodology using the cost-benefit analysis (CBA) to identify the potential areas for afforestation (PAAs). Using the Grain for Green Project (GFGP) in the Jinan Planning Zone, China, as a case study, we identified the increase in five ecosystem services (habitat quality, carbon sequestration, soil retention, water conservation, and reduction in non-point source pollution) as the potential benefit and farmland suitability as the potential cost, and used the benefit-cost ratio as the criterion of the PAAs identification. Moreover, we set three GFGP scenarios (mild, moderate, and strong scenarios) according to the GFGP intensity, and compared the PAAs identified by the CBA and those identified by the slope degree method (SDM), which is widely used in the practical GFGP. Based on our methodology and case study, we proposed a decision-making framework for the identification of the PAAs that can be used in different regions. The results show that ES increases and farmland suitability indicators exhibited spatial heterogeneity. Some extremely high values of the comprehensive ES increase were found in the southeast, while low values of comprehensive farmland suitability were aggregated in the northwestern plain. In all the GFGP scenarios, compared with the SDM, the CBA can identify the PAAs with higher benefits at lower costs, which indicates the advantages and stability of the CBA. In the strong scenario, the mean benefit-cost ratio of the PAAs identified by the CBA was 20.82% higher than that of the PAAs identified by the SDM. Overall, the PAAs identification from the cost-benefit perspective can contribute to delicate afforestation management especially when resources are limited.

U2 - 10.1016/j.scitotenv.2021.147542

DO - 10.1016/j.scitotenv.2021.147542

M3 - Journal article

VL - 787

JO - Science of the Total Environment

JF - Science of the Total Environment

SN - 0048-9697

M1 - 147542

ER -