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• W4318482954 abstract "The leaf economic spectrum (LES) has been repeatedly verified with regional and global datasets. However, the LES of desert plants and its drivers has not been fully explored at the species level. In this study, we sampled three desert perennial plant species (Alhagi sparsifolia, Karelinia caspia, and Apocynum venetum) at three different geographical areas of distribution in Xinjiang, China, and measured 10 leaf economic traits to determine their strategy of resource utilization. The scores of the first axis from the principal component analysis of 10 leaf economic traits as a continuous variable define the LES. This study showed that the LES did exist in desert plants in this region. The leaf economic spectrum shifted from a more conservative strategy to a more acquisitive strategy with increasing contents of soil potassium (K) and the ratio of K to phosphorus. Except for the vein density of A. venetum, which quadratically correlated with LES, the vein density, distance between veins, and vein loopiness significantly positively correlated with the LES (p < 0.05), indicating a covariation and tradeoff relationship. The annual mean temperature was significantly negatively correlated with LES, while the annual mean precipitation (MAP) and the aridity index (AI), which was calculated by the ratio of MAP to potential evapotranspiration, significantly positively correlated with the LES. Of these, vein loopiness and AI were more effective at predicting the change in LES from anatomical and climatic perspectives owing to their high regression coefficients (R2). The findings of this study will substantially improve the understanding of the strategies of desert plants to utilize resources and predict the structure and function of ecosystems." @default.
• W4318482954 created "2023-01-30" @default.
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• W4318482954 date "2023-01-28" @default.
• W4318482954 modified "2023-09-30" @default.
• W4318482954 title "Vein Network and Climatic Factors Predict the Leaf Economic Spectrum of Desert Plants in Xinjiang, China" @default.
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• W4318482954 doi "https://doi.org/10.3390/plants12030581" @default.
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• W4318482954 hasPublicationYear "2023" @default.
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