Simulation and analysis of afforestation potential areas under different development scenarios in Yunnan Province, China

Abstract

Afforestation is recognized as a crucial strategy for mitigating global warming. Therefore, appropriate areas and scales of afforestation needed to be accurate identify and plan, due to the varying levels of economic development and ecological protection across different regions and future scenarios. This study utilized land use data, natural and socio-economic data as the indicators from 2000 to 2020. The Patch-level Land Use Simulation Model (PLUS) was employed to simulate and analyze afforestation potential areas (APAs) under four scenarios: Natural Development (NDS), Ecological Protection (EPS), Urban Development (UDS), and Cultivated Land Protection (CLPS) for the years 2035 and 2050. The results shown that: (1) the spatial distribution of APAs in Yunnan Province under different scenarios shown significant spatial heterogeneity. The APAs are mainly concentrated in economically backward areas with favorable natural conditions. Moreover, the APAs are primarily found around existing forests. (2) The EPS scenario revealed the highest afforestation potential, with 14,132.14 km2 and 13,825.76 km2 of high-APAs, and 5,204.17 km2 and 5,262.4 km2 of low-APAs expected by 2035 and 2050, respectively. The CLPS scenario shown the lowest afforestation potential. (3) The APAs are mainly influenced by natural conditions, the strictness of forest management, and the level of local economic development. Climate and soil, as fundamental natural elements, constitute the foundational conditions for these potential areas. (4) Afforestation strategies should have emphasized ’adapting to local conditions and time’ at different development stages. The program would be dynamically adjusted according to future development scenarios to maximize afforestation potential areas and ecological value. These strategies could provide valuable suggestions for future afforestation planning in Yunnan Province.

Keywords

• Climate change
• Afforestation potential area
• The PLUS model
• Scenario simulation