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      Estimating forest above‐ground biomass with terrestrial laser scanning: Current status and future directions

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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 Concordance Correlation Coefficient to Evaluate Reproducibility

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              Improved allometric models to estimate the aboveground biomass of tropical trees.

              Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven-dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as covariates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter-height relationship depended linearly on a bioclimatic stress variable E, which compounds indices of temperature variability, precipitation variability, and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter-height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development. © 2014 John Wiley & Sons Ltd.
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                Journal
                Methods in Ecology and Evolution
                Methods Ecol Evol
                Wiley
                2041-210X
                2041-210X
                August 2022
                June 09 2022
                August 2022
                : 13
                : 8
                : 1628-1639
                Affiliations
                [1 ]CAVElab, Computational and Applied Vegetation Ecology, Department of Environment, Faculty of Bioscience Engineering Ghent University Ghent Belgium
                [2 ]PLECO, Plants and Ecosystems, Faculty of Science Antwerp University Wilrijk Belgium
                [3 ]Department of Geographical Sciences University of Maryland College Park Maryland USA
                [4 ]Department of Geography University College London London UK
                [5 ]NERC NCEO‐UCL London UK
                [6 ]Independent Developer of Free Software Koblenz Germany
                [7 ]Swiss Federal Institute WSL Birmensdorf Switzerland
                [8 ]Laboratory of Geo‐Information Science and Remote Sensing Wageningen University Wageningen The Netherlands
                [9 ]AMAP, Univ Montpellier, IRD, CNRS, INRAE, CIRAD Montpellier France
                [10 ]Department of Forest Management, Centre for Agricultural Research in Suriname (CELOS) Paramaribo Suriname
                [11 ]NASA Goddard Space Flight Center Greenbelt Maryland USA
                [12 ]Plant Systematic and Ecology Laboratory (LaBosystE), Department of Biology, Higher Teachers' Training College University of Yaoundé I Yaoundé Cameroon
                [13 ]School of Ecosystem and Forest Sciences The University of Melbourne Parkville Vic. Australia
                Article
                10.1111/2041-210X.13906
                b272fead-684e-424e-b9c3-e762199aa859
                © 2022

                http://onlinelibrary.wiley.com/termsAndConditions#vor

                http://doi.wiley.com/10.1002/tdm_license_1.1

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