Vulnerability to xylem cavitation of Hakea species (Proteaceae) from a range of biomes and life histories predicted by climatic niche

气候生态位预测了不同生物群落和生活史的哈克木属植物(山龙眼科)对木质部空穴化的脆弱性

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Abstract

BACKGROUND AND AIMS: Extreme drought conditions across the globe are impacting biodiversity, with serious implications for the persistence of native species. However, quantitative data on physiological tolerance are not available for diverse flora to inform conservation management. We quantified physiological resistance to cavitation in the diverse Hakea genus (Proteaceae) to test predictions based on climatic origin, life history and functional traits. METHODS: We sampled terminal branches of replicate plants of 16 species in a common garden. Xylem cavitation was induced in branches under varying water potentials (tension) in a centrifuge, and the tension generating 50 % loss of conductivity (stem P50) was characterized as a metric for cavitation resistance. The same branches were used to estimate plant functional traits, including wood density, specific leaf area and Huber value (sap flow area to leaf area ratio). KEY RESULTS: There was significant variation in stem P50 among species, which was negatively associated with the species climate origin (rainfall and aridity). Cavitation resistance did not differ among life histories; however, a drought avoidance strategy with terete leaf form and greater Huber value may be important for species to colonize and persist in the arid biome. CONCLUSIONS: This study highlights climate (rainfall and aridity), rather than life history and functional traits, as the key predictor of variation in cavitation resistance (stem P50). Rainfall for species origin was the best predictor of cavitation resistance, explaining variation in stem P50, which appears to be a major determinant of species distribution. This study also indicates that stem P50 is an adaptive trait, genetically determined, and hence reliable and robust for predicting species vulnerability to climate change. Our findings will contribute to future prediction of species vulnerability to drought and adaptive management under climate change.

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