Mapping local and global variability in plant trait distributions
2017
Butler, Ethan | Datta, Abhirup | Flores-Moreno, Habacuc | Chen, Ming | Wythers, Kirk | Fazayeli, Farideh | Banerjee, Arindam | Atkin, Owen | Kattge, Jens | Amiaud, Bernard | Blonder, Ben | Boenisch, Gerhard | Bond-Lamberty, Ben | Brown, Kerry | Byun, Chaeho | Campetella, Giandiego | Cerabolini, Bruno | Cornelissen, Johannes | Craine, Josep | Craven, Dylan | de Vries, Franciska | Diaz, Sandra | Domingues, Tomas | Forey, Estelle | González-Melo, Andrés | Gross, Nicolas | Han, Wenxuan | Hattingh, Wesley | Hickler, Thomas | Jansen, Steven | Kramer, Koen | Kraft, Nathan | Kurokawa, Hiroko | Laughlin, Daniel | Meir, Patrick, S | Minden, Vanessa | Onoda, Yusuke | Peñuelas, Josep | Read, Quentin | Sack, Lawren | Schamp, Brandon | Soudzilovskaia, Nadejda | Spasojevic, Marko | Sosinski, Enio | Thornton, Peter | Valladares, Fernando | van Bodegom, Peter | Williams, Mathew | Wirth, Christian | Reich, Peter | Department of Forest Resources, University of Minnesota, St. Paul, MN, USA | Department of Biostatistics [Baltimore] ; Johns Hopkins University (JHU) | University of Minnesota [Twin Cities] (UMN) ; University of Minnesota System (UMN) | Guangzhou Institute of Geochemistry [Chinese Academy of Sciences (CAS), Guangzhou, China] (GIGCAS) ; Chinese Academy of Sciences [Beijing] (CAS) | Department of Computer Science and Engineering ; University of Minnesota System (UMN) | Australian National University (ANU) | German Centre for Integrative Biodiversity Research (iDiv) | Ecologie et Ecophysiologie Forestières [devient SILVA en 2018] (EEF) ; Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL) | Environmental Change Institute ; University of Oxford | Max Planck Institute for Biogeochemistry (MPI-BGC) ; Max-Planck-Gesellschaft | Joint Global Change Research Institute ; University Research Court | Department of Geography and Geology, Kingston University, Kingston upon Thames, UK | Seoul National University [Seoul] (SNU) | Università degli Studi di Camerino = University of Camerino (UNICAM) | Department of Theoretical and Applied Sciences [Insubria] ; Universitá degli Studi dell’Insubria = University of Insubria [Varese] (Uninsubria) | Jonah Ventures | School of Earth and Environmental Sciences [Manchester] (SEES) ; University of Manchester [Manchester] | Insituto Multidisciplinario de Biologia Vegetal ; Universidad Nacional de Córdoba [Argentina] | Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP) ; Universidade de São Paulo = University of São Paulo (USP) | Étude et compréhension de la biodiversité (ECODIV) ; Université de Rouen Normandie (UNIROUEN) ; Normandie Université (NU)-Normandie Université (NU) | Universidad del Rosario [Bogota] | Centre d'Études Biologiques de Chizé - UMR 7372 (CEBC) ; Institut National de la Recherche Agronomique (INRA)-La Rochelle Université (ULR)-Centre National de la Recherche Scientifique (CNRS) | College of Resources and Environmental Sciences, Ministry of Agriculture, Key Laboratory of Arable Land Conservation (North China) ; China Agricultural University (CAU) | Key Laboratory of Biogeography and Bioresource in Arid Land, Xinjiang Institute of Ecology and Geography ; Chinese Academy of Sciences [Changchun Branch] (CAS) | School of Animal, Plant & Environmental Sciences ; University of the Witwatersrand [Johannesburg] (WITS) | Department of Physical Geography and Ecosystem Science [Lund] ; Skane University Hospital [Lund] | Universität Ulm - Ulm University [Ulm, Allemagne] | Alterra - Green World Research ; Wageningen University and Research [Wageningen] (WUR) | Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California | Tohoku University [Sendai] | University of Wyoming (UW) | Research School of Biology ; Australian National University (ANU) | Carl Von Ossietzky Universität Oldenburg = Carl von Ossietzky University of Oldenburg (OFFIS) | Kyoto University | Centre d'Estudis Avançats de Blanes (CEAB) ; Consejo Superior de Investigaciones Cientificas [España] = Spanish National Research Council [Spain] (CSIC) | Department of Forestry, Michigan State University, East Lansing | Department of Ecology and Evolutionary Biology ; University of California (UC) | Department of Biology, Algoma University, Marie, OA, Canada ; Algoma University | Institute of Environmental Sciences [Leiden] (CML) ; Universiteit Leiden = Leiden University | Laboratorio de Planejamento Ambiental | Oak Ridge National Laboratory [Oak Ridge] (ORNL) ; UT-Battelle, LLC | Climate Change Science Institute [Oak Ridge] (CCSI) ; Oak Ridge National Laboratory [Oak Ridge] (ORNL) ; UT-Battelle, LLC-UT-Battelle, LLC | Escuela Superior de Ciencias Experimentales y Tecnológicas, Departamento de Biología y Geología ; Universidad Rey Juan Carlos = Rey Juan Carlos University (URJC) | School of Geosciences [Edinburgh] ; The University of Edinburgh | Department of Systematic Botany and Functional Biodiversity ; Leipzig University / Universität Leipzig | Department of Forest Resources ; University of Minnesota [Twin Cities] (UMN) ; University of Minnesota System (UMN)-University of Minnesota System (UMN) | European Project: 609398,EC:FP7:PEOPLE,FP7-PEOPLE-2013-COFUND,AGREENSKILLSPLUS(2014)
International audience
Show more [+] Less [-]English. Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (N-m) and phosphorus (P-m), we characterize how traits vary within and among over 50,000 similar to 50 x 50-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.
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