Physiological trait networks enhance understanding of crop growth and water use in contrasting environments
Physiological trait networks enhance understanding of crop growth and water use in contrasting environments
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DOI：
10.1111/pce.14382
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发表时间：
2022-07-07
影响因子：
7.3
通讯作者：
Zhang, Huihui
中科院分区：
文献类型：
--
作者：
Gleason, Sean M.;Barnard, Dave M.;Zhang, Huihui
植物的功能来自于结构和生理特征的复杂网络。这些特征的明确表示，以及它们与其他生物物理过程的联系，需要推进我们对植物-土壤-气候相互作用的理解。我们使用陆地区域生态系统交换模拟器（TREES）来评估玉米的生理性状网络。净初级生产力（NPP）和粮食产量在五个不同的气候情景进行了模拟。模拟实现高NPP和粮食产量在高降水环境特征网络赋予高水分利用策略：深根，高气孔导度在低水势（“风险”气孔调节），高木质部导水率和高最大叶面积指数。与此相反，高NPP和粮食产量实现在干燥的环境中，低后期降水通过保水特性网络：深根，高栓塞阻力和低气孔导度在低叶水势（“保守”的气孔调节）。我们建议，我们的方法，允许同时评估生理性状，土壤特性及其相互作用（即，网络），有可能提高我们对作物在不同环境中表现的理解。相比之下，评估其他协调性状的孤立的单一性状似乎并不是预测植物性能的有效策略。
Plant function arises from a complex network of structural and physiological traits. Explicit representation of these traits, as well as their connections with other biophysical processes, is required to advance our understanding of plant-soil-climate interactions. We used the Terrestrial Regional Ecosystem Exchange Simulator (TREES) to evaluate physiological trait networks in maize. Net primary productivity (NPP) and grain yield were simulated across five contrasting climate scenarios. Simulations achieving high NPP and grain yield in high precipitation environments featured trait networks conferring high water use strategies: deep roots, high stomatal conductance at low water potential ("risky" stomatal regulation), high xylem hydraulic conductivity and high maximal leaf area index. In contrast, high NPP and grain yield was achieved in dry environments with low late-season precipitation via water conserving trait networks: deep roots, high embolism resistance and low stomatal conductance at low leaf water potential ("conservative" stomatal regulation). We suggest that our approach, which allows for the simultaneous evaluation of physiological traits, soil characteristics and their interactions (i.e., networks), has potential to improve our understanding of crop performance in different environments. In contrast, evaluating single traits in isolation of other coordinated traits does not appear to be an effective strategy for predicting plant performance.