4.7 Article

Climate gradient and leaf carbon investment influence the effects of climate change on water use efficiency of forests: A meta-analysis

期刊

PLANT CELL AND ENVIRONMENT
卷 -, 期 -, 页码 -

出版社

WILEY
DOI: 10.1111/pce.14777

关键词

climate change; forests; geographical distribution; meta-analysis; photosynthetic products; water use efficiency

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Forest ecosystems are important carbon sinks, but their water-carbon cycles are affected by climate change. This meta-analysis found that elevated CO2 concentration increased leaf water use efficiency, while drought enhanced leaf and plant water use efficiency. These findings are important for predicting the carbon-water cycles of forests.
Forest ecosystems cover a large area of the global land surface and are important carbon sinks. The water-carbon cycles of forests are prone to climate change, but uncertainties remain regarding the magnitude of water use efficiency (WUE) response to climate change and the underpinning mechanism driving WUE variation. We conducted a meta-analysis of the effects of elevated CO2 concentration (eCO(2)), drought and elevated temperature (eT) on the leaf- to plant-level WUE, covering 80 field studies and 95 tree species. The results showed that eCO(2) increased leaf intrinsic and instantaneous WUE (WUEi, WUEt), whereas drought enhanced both leaf- and plant-level WUEs. eT increased WUEi but decreased carbon isotope-based WUE, possibly due to the influence of mesophyll conductance. Stimulated leaf-level WUE by drought showed a progressing trend with increasing latitude, while eCO(2)-induced WUE enhancement showed decreasing trends after >40 degrees N. These latitudinal gradients might influence the spatial pattern of climate and further drove WUE variation. Moreover, high leaf-level WUE under eCO(2) and drought was accompanied by low leaf carbon contents. Such a trade-off between growth efficiency and defence suggests a potentially compromised tolerance to diseases and pests. These findings add important ecophysiological parameters into climate models to predict carbon-water cycles of forests.

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