Restoration-oriented forest management is increasingly recognized as an important strategy for enhancing long-term carbon sequestration and rehabilitating degraded peri-urban forest landscapes. This study presents a scenario-based assessment of projected carbon sequestration trajectories under a National Reserve Forest Project implemented in peri-urban Wuhan, central China. Thirteen silvicultural models were grouped into three management pathways: intensive plantation cultivation, transformation of existing degraded stands, and tending of young and middle-aged forests. Carbon sequestration was evaluated over a 40-year assessment period (2024–2063) using a Biomass Expansion Factor-based accounting framework incorporating above- and belowground biomass, harvested wood products, and conservative baseline deductions consistent with national and provincial methodologies. The results indicate a sustained long-term increase in projected carbon sequestration despite periodic short-term declines associated with planned thinning and harvesting cycles. Transformation-oriented pathways contributed the largest cumulative project-scale sequestration and generally exhibited relatively strong area-normalized sequestration performance compared with intensive plantation and tending pathways. Intensive plantation systems displayed greater temporal fluctuation associated with shorter rotation cycles and repeated harvesting events. The analysis also highlights the importance of distinguishing between area-normalized sequestration efficiency and cumulative project-scale contribution, as models with moderate per-hectare performance generated substantial total carbon benefits because of their larger implementation area. The findings suggest that restoration-oriented management of existing degraded stands may provide a relatively stable long-term carbon-sequestration pathway in peri-urban forest systems where land availability for large-scale afforestation is constrained. The study also demonstrates the applicability of conservative scenario-based accounting frameworks for restoration-oriented forest carbon assessment and planning under data-limited conditions.
Zhu et al. (Mon,) studied this question.