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Mapping local and global variability in plant trait distributions

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...

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Detalles Bibliográficos
Autores Principales: 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, de Vries, Franciska T., 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, van Bodegom, Peter M., Williams, Mathew, Wirth, Christian, Reich, Peter B.
Formato: Artículo (Article)
Lenguaje:Inglés (English)
Publicado: National Academy of Sciences 2017
Materias:
Nitrogen
Phosphorus
Article
Bayes theorem
Concentration (parameters)
Data base
Environment
Evergreen
Leaf area
Leaf litter
Model
Nonhuman
Plant
Prediction
Priority journal
Ecosystem
Geography
Plant dispersal
Quantitative trait
Spatial analysis
Statistical model
Plants
Bayesian modeling
Climate
Global
Plant traits
Spatial statistics
heritable
statistical
Models
Acceso en línea:https://repository.urosario.edu.co/handle/10336/22879
https://doi.org/10.1073/pnas.1708984114

Internet

https://repository.urosario.edu.co/handle/10336/22879
https://doi.org/10.1073/pnas.1708984114

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