Chen Zhizhong, Zan Mei, Kong Jingjing
School of Geographic Science and Tourism, Xinjiang Normal University, Ürümqi, China.
Xinjiang Laboratory of Lake Environment and Resources in the Arid Zone, Ürümqi, China.
Sci Rep. 2025 Aug 14;15(1):29774. doi: 10.1038/s41598-025-14714-5.
Forest carbon sink potential assessment in arid regions remains a critical challenge for climate change mitigation. This study integrates multi-source remote sensing and forest inventory data to model Xinjiang's forest age and carbon density (2019 baseline: 186.76 Mg/hm biomass, 93.38 Mg/hm carbon density, 46-year average age), revealing a south-to-north "low-high-low" spatial pattern. Using predictive models excluding anthropogenic and natural disturbances, we project forest carbon stock to reach 203.71 ± 2.31 Tg C by 2030 and 283.08 ± 4.23 Tg C by 2060, with declining carbon sink rates (3.67 ± 0.57 Tg C/a in 2019-2030 vs. 2.65 ± 0.56 Tg C/a in 2031-2060). Notably, Xinjiang's forests could offset 14.6% and 9.5% of regional CO emissions during these periods. Economic cost analysis via panel fixed benefit modeling identifies afforestation suitability in Northeast Xinjiang, while conservation measures are prioritized elsewhere, particularly in high-elevation ridge zones. This research provides a methodological framework for arid region carbon sink enhancement and informs region-specific forest management strategies under climate change.
干旱地区森林碳汇潜力评估仍然是缓解气候变化的一项关键挑战。本研究整合多源遥感和森林清查数据，对新疆森林的年龄和碳密度进行建模（2019年基线：生物量186.76 Mg/hm，碳密度93.38 Mg/hm，平均年龄46年），揭示了从南到北“低-高-低”的空间格局。利用排除人为和自然干扰的预测模型，我们预计到2030年森林碳储量将达到203.71±2.31 Tg C，到2060年将达到283.08±4.23 Tg C，碳汇速率呈下降趋势（2019-2030年为3.67±0.57 Tg C/年，2031-2060年为2.65±0.56 Tg C/年）。值得注意的是，在此期间，新疆的森林可抵消该地区14.6%和9.5%的碳排放。通过面板固定效益模型进行的经济成本分析确定了新疆东北部的造林适宜性，而其他地区则优先采取保护措施，特别是在高海拔山脊地带。本研究为干旱地区增强碳汇提供了一个方法框架，并为气候变化下特定区域的森林管理策略提供了参考。
