Cai Lu, Luo Yining, Lan Yan, Shu Guoxiang, Huang Denghong, Zhou Zhongfa, Yan Lihui
School of Karst Science, Guizhou Normal University, Guiyang 550025, China.
State Engineering Technology Institute for Karst Desertification Control, Guiyang 550025, China.
Plants (Basel). 2025 Aug 11;14(16):2493. doi: 10.3390/plants14162493.
Under the backdrop of global climate warming, both forest vegetation greening and resilience decline coexist, and the consistency of these trends at the regional scale remains controversial. This study uses the kNDVI (Kernel Normalized Difference Vegetation Index) and TAC (Temporal Autocorrelation) index framework, combined with BEAST and Random Forest methods, to quantify and analyze the spatiotemporal evolution of forest resilience and its driving factors in Southwest China from 2000 to 2022. The results show the following: (1) Forest resilience exhibits a "high in the northwest and low in the southeast" spatial distribution, with a temporal pattern of "increase-decrease-increase." The years 2010 and 2015 are key turning points. Trend shift analysis divides resilience into six types. (2) Although forest vegetation shows a clear greening trend, resilience does not necessarily increase with greening, and in some areas, an "increase in greening-decline in resilience" asynchronous pattern appears. (3) The annual average temperature, precipitation, and solar radiation are the main climate factors and their influence on resilience follows a nonlinear relationship. Higher temperatures and increased radiation may suppress resilience, while increased precipitation can enhance it. This study suggests incorporating the TAC indicator into ecological monitoring and early warning systems, along with applying trend classification results for region-specific management to improve the scientific basis and adaptability of forest governance under climate change.
在全球气候变暖的背景下,森林植被绿化和恢复力下降并存,这些趋势在区域尺度上的一致性仍存在争议。本研究采用核归一化植被指数(kNDVI)和时间自相关(TAC)指数框架,结合贝叶斯进化分析采样树(BEAST)和随机森林方法,对2000年至2022年中国西南地区森林恢复力的时空演变及其驱动因素进行量化分析。结果表明:(1)森林恢复力呈现“西北高东南低”的空间分布,时间上呈“上升—下降—上升”的格局。2010年和2015年是关键转折点。趋势转移分析将恢复力分为六种类型。(2)虽然森林植被呈现出明显的绿化趋势,但恢复力并不一定随绿化而增加,在一些地区出现了“绿化增加—恢复力下降”的异步格局。(3)年平均气温、降水量和太阳辐射是主要气候因子,它们对恢复力的影响呈非线性关系。较高的温度和增加的辐射可能抑制恢复力,而增加降水量则可增强恢复力。本研究建议将TAC指标纳入生态监测和预警系统,并应用趋势分类结果进行区域针对性管理,以提高气候变化下森林治理的科学依据和适应性。