Dong Yuntao, Fang Ouya, Deng Ying, Lai Jiangshan, Jia Hengfeng
Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China.
University of the Chinese Academy of Sciences, Beijing 101408, China.
iScience. 2025 Jun 30;28(8):113043. doi: 10.1016/j.isci.2025.113043. eCollection 2025 Aug 15.
While climate extremes are conventionally considered primary triggers of extreme growth suppression (EGS) in trees, the role of trees' intrinsic resistance capacity in mediating EGS remains a persistent knowledge gap. By analyzing 4,599 EGSs across 2,631 juniper trees at 61 sites on the Tibetan Plateau, we quantified the influence of intrinsic and extrinsic factors on EGS using a random forest model and a piecewise structural equation model. The results showed tree resistance exerted 1.7× greater effect on EGS likelihood than climatic variables of the current year, mediated through both direct physiological pathways and indirect age-related effects. Tree age negatively modulated resistance capacity. These findings fundamentally challenge the climate-centric paradigm in dendroecology, which emphasizes the critical role of individual tree physiology in mediating climate responses. Our mechanistic framework advances a predictive model of forest dynamics under climate change by integrating resilience with traditional climate-growth relationships.
虽然极端气候通常被认为是树木极端生长抑制(EGS)的主要触发因素,但树木的内在抗性能力在介导EGS中的作用仍然是一个长期存在的知识空白。通过分析青藏高原61个地点2631棵杜松树上的4599次EGS,我们使用随机森林模型和分段结构方程模型量化了内在和外在因素对EGS的影响。结果表明,树木抗性对EGS可能性的影响比当年气候变量大1.7倍,通过直接生理途径和与年龄相关的间接效应介导。树木年龄对抗性能力有负向调节作用。这些发现从根本上挑战了树木生态学中以气候为中心的范式,该范式强调个体树木生理在介导气候响应中的关键作用。我们的机制框架通过将恢复力与传统气候-生长关系相结合,推进了气候变化下森林动态的预测模型。