生物
种间竞争
光合作用
淀粉
每年落叶的
常绿
木质部
植物
耐旱性
特质
光合能力
蒸腾作用
比叶面积
气孔导度
植物生理学
生态学
系统发育树
限制
碳水化合物
物候学
木本植物
下层林
用水效率
收敛演化
膨胀压力
垃圾箱
农学
作者
Weibin Li,Henry D. Adams,Antoine Cabon,Kailiang Yu,Drew Peltier,Nate McDowell
标识
DOI:10.1073/pnas.2605066123
摘要
Nonstructural carbohydrate (NSC) stores buffer tree metabolism, osmotic regulation, and defense, thereby mediating tolerance and survival under climate extremes. Yet, the functional and evolutionary determinants of interspecific variation in NSC remain elusive, limiting understanding and prediction of forest carbon allocation and mortality under global change. Here, we present a cross-species synthesis of NSC concentrations across multiple organs for 281 woody species from 102 mixed forest communities worldwide, where we quantified species-specific deviations from community means to disentangle intrinsic trait effects from environmental and methodological variation. We found phylogenetic signals in NSC deviations, with coniferous gymnosperms and evergreen species consistently maintaining lower stem soluble sugars and starch concentrations than co-occurring angiosperms and deciduous species, respectively. A global pattern emerged where greater stomatal sensitivity to leaf water potential was associated with declines in the relative concentrations of both sugars and starch. In contrast, xylem hydraulic safety traits showed weak and organ-dependent relationships with NSC concentrations. Sugars increased with photosynthetic capacity and declined with wood density, whereas starch showed the reverse pattern, which aligned with the distinct functional-metabolic roles of sugars and starch. By integrating trait-based ecology with a community-centered framework, our study provides global evidence that stomatal regulation, photosynthetic capacity, specific leaf area, and wood density jointly govern interspecific NSC variation, through contrasting effects on sugars and starch. These are among the most broadly measured traits globally, thus the emergent carbohydrate-trait relationships can have broad applications toward understanding and predicting forest growth and survival under climate change.
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