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      Improved allometric models to estimate the aboveground biomass of tropical trees

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          Abstract

          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.

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          Very high resolution interpolated climate surfaces for global land areas

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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 high-resolution data set of surface climate over global land areas

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                Author and article information

                Journal
                Global Change Biology
                Global Change Biology
                Wiley
                1354-1013
                1365-2486
                October 2014
                June 21 2014
                October 2014
                : 20
                : 10
                : 3177-3190
                Affiliations
                [1 ] UMR 5174 Laboratoire Evolution et Diversité Biologique CNRS & Université Paul Sabatier Toulouse 31062 France
                [2 ] Departamento de Ecología de la Biodiversidad Instituto de Ecología Universidad Nacional Autónoma de México Apartado Postal 1354, Hermosillo Sonora C.P. 83000 México
                [3 ] Makeni Savanna Research project Box 50323 Lusaka Zambia
                [4 ] Department of Global Ecology Carnegie Institution for Science Stanford 94305 CA USA
                [5 ] Universidade de São Paulo Rua do Matão Travessa 14 n 321 Cidade Universitaria Sao Paulo 05508‐090 Brazil
                [6 ] Departamento de Ciencias Forestales Universidad Nacional de Colombia Calle 59A No. 63‐20 Medellín Colombia
                [7 ] Department of Ecology and Natural Resource Management Norwegian University of Life Sciences P.O. Box 5003 Ås 1432 Norway
                [8 ] Department of Environmental Dynamics National Institute for Research in the Amazon ‐ INPA Av. André Araújo No. 2936 Manaus AM CEP 69 060‐000 Brazil
                [9 ] School of Geography University of Leeds Leeds LS2 9JT UK
                [10 ] Forest Department Food and Agriculture Organisation of the United Nations Viale delle Terme di Caracalla Rome 00153 Italy
                [11 ] Smithsonian Tropical Research Institute Balboa, Ancon Panama Republic of Panama
                [12 ] School of GeoSciences University of Edinburgh Crew Building Edinburgh EH9 3JN UK
                [13 ] IRET Libreville BP 13354 Gabon
                [14 ] Instituto Tecnológico de Costa Rica Cartago 159‐7050 Costa Rica
                [15 ] UMR AMAP IRD Montpellier 34000 France
                [16 ] Carrera 5 No 14‐05 Cota Cundinamarca Colombia
                [17 ] CIRAD UPR BSEF Montpellier F‐34398 France
                Article
                10.1111/gcb.12629
                24817483
                c1301da9-eaf8-4f33-82c0-2fc87a728311
                © 2014

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