Optimizing spatial allocation schemes with a focus on carbon fixation services by the integration of GIS and a robust algorithmic approach - Guo, Eryan; He, Jing (Frontiers in Forests and Global Change, 2025)
As global climate change becomes more severe, forests, as important carbon sinks, are of great significance for mitigating climate change and protecting the ecological environment. The study took typical forest farms in southern China as the research area, constructed a multi-objective forest planning model based on Simulated Annealing Algorithm, and interfaced with geographic information systems. The aim is to achieve long-term scientific and rational arrangement of forest management measures to balance wood production and forest carbon storage. The results confirm that under the constraints of forest classification management and age structure adjustment of artificial forests, different optimization scenarios gradually stabilize corresponding logging intensity and forest resources from year 40 onwards. By assigning weights to the net present value of wood and carbon sequestration in the objective function, this study explores the impact of social preferences on spatial allocation schemes for forest management. When the carbon sequestration weight is 100%, the current savings are greater than those of other optimized scenarios starting in the 35th year, at roughly 8.8 × 104 m3, and the current carbon storage is superior to those of other optimized scenarios starting in the 25th year, at 4.9 × 104 t. In summary, this research can provide a scientific basis for actual forest management decisions, which is beneficial for improving forest carbon sequestration services, maintaining ecological balance, and promoting regional ecological sustainable development.