Comprehensive assessment of potential forestation land in China considering factors of vegetation resilience and top vegetation succession

Abstract

China is currently the world’s largest carbon emitter and has pledged to achieve carbon neutrality by 2060, which requires significant reductions in emissions and the removal of carbon dioxide removal. Precise and efficient forestation has become a key strategy to increase carbon sequestration and mitigate the effects of climate change. In order to obtain a high-accuracy distribution area of potential forestation land, a variety of influencing factors on potential forestation land were selected in this study, including vegetation factors and environmental factors. Combining the two models “law of the minimum factors (LMF)” and “equal weight classification (EWC)” predicts the spatial distribution pattern of potential forestation land in China. And, we calculated the available forestation area in each province and predicted future forest coverage. The results showed that the potential forestation area using the LMF method reached approximately 5.65 × 105 km2, and the potential forestation area using the EMC method reached approximately 4.95 × 105 km2. Combining the two models, the final potential forestation area in China was approximately 6.29 × 105 km2, of which approximately 1.02 × 105 km2 was evaluated as a high-confidence area. If all potential forestation land obtained from the two models was successfully planted, China’s forest coverage rate would reach nearly 26 %. Two newly introduced vegetation factors, namely vegetation resilience and top vegetation succession, were considered in this study to make the prediction results of potential forestation distribution more accurate and reasonable. In addition, the results obtained in this study can provide certain assistance for the specific implementation of national forestation policies, and can provide a reference for promoting forestation actions and achieving the goal of carbon neutrality.

Keywords

• Potential forestation land
• Vegetation resilience
• Vegetation succession
• Confidence evaluation
• Spatial distribution pattern