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Published on: December 27, 2017
Resource Segmentation: A New Dimension of the Segmentation Hypothesis in Drought Adaptive Strategies and Its Links to
Chen Yue1,2, Huimin Wang1,2, Frederick C Meinzer3
1Qianyanzhou Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Abstract:
The segmentation hypothesis, a framework for understanding plant drought adaptive strategy, has long been based on hydraulic resistance and vulnerability. Storage of water and carbohydrate resources is another critical function and shapes plant drought adaption and fitness together with hydraulic efficiency and vulnerability. However, patterns and implications of the interdependency of stored water and carbohydrate resources in the context of the segmentation hypothesis are poorly understood. We measured resource pools (relative water content [RWC] soluble sugar [SS] and starch [S]) and anatomical features of leaves and supporting twigs for 36 trees in a subtropical population during the dry season when the Budyko's aridity index was 0.362. For each tree, we rank-transformed the RWC (RWCrank), SS (SSrank), and S (Srank) and characterised the resource segmentation within organs using Ln(RWCrank/SSrank) and Ln(RWCrank/Srank). We also assessed the resource segmentation between organs using the difference in resource pools between leaves and twigs (RWCleaf-twig, SSleaf-twig, and Sleaf-twig). Resource segmentation was much more effective than the organ-level resource pool alone in predicting intraspecific variation of tree growth rates. Fast-growing individuals were mainly characterised by lower leaf Ln(RWCrank/SSrank), higher twig Ln(RWCrank/SSrank), and lower SSleaf-twig. The resource segmentation strategy of fast-growing individuals was associated with anatomical attributes that facilitate phloem SS loading and unloading and thus water supply upstream. Our results highlight that resource segmentation is an important dimension of plant drought adaptive strategies and enables better prediction of tree growth vigour than resource pool attributes individually.
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