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      Greater hydraulic safety contributes to higher growth resilience to drought across seven pine species in a semi-arid environment

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          Abstract

          Quantifying inter-specific variations of tree resilience to drought and revealing the underlying mechanisms are of great importance to the understanding of forest functionality, particularly in water-limited regions. So far, comprehensive studies incorporating investigations in inter-specific variations of long-term growth patterns of trees and the underlying physiological mechanisms are very limited. Here, in a semi-arid site of northern China, tree radial growth rate, inter-annual tree-ring growth responses to climate variability, as well as physiological characteristics pertinent to xylem hydraulics, carbon assimilation and drought tolerance were analyzed in seven pine species growing in a common environment. Considerable inter-specific variations in radial growth rate, growth response to drought and physiological characteristics were observed among the studied species. Differently, the studied species exhibited similar degrees of resistance to drought-induced branch xylem embolism, with water potential corresponding to 50% loss hydraulic conductivity ranging from −2.31 to −2.96 MPa. We found that higher branch hydraulic efficiency is related to greater leaf photosynthetic capacity, smaller hydraulic safety margin and lower woody density (P < 0.05, linear regressions), but not related to higher tree radial growth rate (P > 0.05). Rather, species with higher hydraulic conductivity and photosynthetic capacity were more sensitive to drought stress and tended to show weaker growth resistance to extreme drought events as quantified by tree-ring analyses, which is at least partially due to a trade-off between hydraulic efficiency and safety across species. This study thus demonstrates the importance of drought resilience rather than instantaneous water and carbon flux capacity in determining tree growth in water-limited environments.

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          Towards a worldwide wood economics spectrum.

          Wood performs several essential functions in plants, including mechanically supporting aboveground tissue, storing water and other resources, and transporting sap. Woody tissues are likely to face physiological, structural and defensive trade-offs. How a plant optimizes among these competing functions can have major ecological implications, which have been under-appreciated by ecologists compared to the focus they have given to leaf function. To draw together our current understanding of wood function, we identify and collate data on the major wood functional traits, including the largest wood density database to date (8412 taxa), mechanical strength measures and anatomical features, as well as clade-specific features such as secondary chemistry. We then show how wood traits are related to one another, highlighting functional trade-offs, and to ecological and demographic plant features (growth form, growth rate, latitude, ecological setting). We suggest that, similar to the manifold that tree species leaf traits cluster around the 'leaf economics spectrum', a similar 'wood economics spectrum' may be defined. We then discuss the biogeography, evolution and biogeochemistry of the spectrum, and conclude by pointing out the major gaps in our current knowledge of wood functional traits.
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            A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests

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              The world-wide ‘fast-slow’ plant economics spectrum: a traits manifesto

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                Author and article information

                Contributors
                Journal
                Tree Physiology
                Oxford University Press (OUP)
                1758-4469
                April 2022
                April 07 2022
                October 28 2021
                April 2022
                April 07 2022
                October 28 2021
                : 42
                : 4
                : 727-739
                Affiliations
                [1 ]CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, Liaoning, China
                [2 ]Daqinggou Ecological Research Station, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, Liaoning, China
                [3 ]University of Chinese Academy of Sciences, Beijing 100049, China
                [4 ]Institute of Sand Land Control and Utilization, Fuxin 123000, Liaoning, China
                [5 ]CAS Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, Guangdong, China
                Article
                10.1093/treephys/tpab137
                34718811
                ec0a8e54-ac9f-485c-bb4e-8776fa1bea02
                © 2021

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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