Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 531347
Title Mapping local and global variability in plant trait distributions
Author(s) Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc; Chen, Ming; Wythers, Kirk R.; Fazayeli, Farideh; Banerjee, Arindam; Atkin, Owen K.; Kattge, Jens; Amiaud, Bernard; Blonder, Benjamin; Boenisch, Gerhard; Bond-Lamberty, Ben; Brown, Kerry A.; Byun, Chaeho; Campetella, Giandiego; Cerabolini, Bruno E.L.; Cornelissen, Johannes H.C.; Craine, Joseph M.; Craven, Dylan; Vries, Franciska T. De; Díaz, Sandra; Domingues, Tomas F.; Forey, Estelle; González-Melo, Andrés; Gross, Nicolas; Han, Wenxuan; Hattingh, Wesley N.; Hickler, Thomas; Jansen, Steven; Kramer, Koen; Kraft, Nathan J.B.; Kurokawa, Hiroko; Laughlin, Daniel C.; Meir, Patrick; Minden, Vanessa; Niinemets, Ülo; Onoda, Yusuke; Peñuelas, Josep; Read, Quentin; Sack, Lawren; Schamp, Brandon; Soudzilovskaia, Nadejda A.; Spasojevic, Marko J.; Sosinski, Enio; Thornton, Peter E.; Valladares, Fernando; Bodegom, Peter M. Van; Williams, Mathew; Wirth, Christian; Reich, Peter B.; Schlesinger, William H.
Source Proceedings of the National Academy of Sciences of the United States of America 114 (2017)51. - ISSN 0027-8424 - p. E10937 - E10946.
Department(s) Philosophy
Centre for Crop Systems Analysis
Publication type Refereed Article in a scientific journal
Publication year 2017
Keyword(s) Bayesian modeling - Climate - Global - Plant traits - Spatial statistics
Abstract 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 (Nm) and phosphorus (Pm), we characterize how traits vary within and among over 50,000 ∼50×50-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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