The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
A fully traits-based approach to modeling global vegetation distribution
Open accessAbstract
Significance: Models on vegetation dynamics are indispensable for our understanding of climate change impacts. These models contain variables describing vegetation attributes, so-called traits. However, the direct impacts of trait variation on global vegetation distribution are unknown. We derived global trait maps based on information on environmental drivers. Subsequently, we characterized nine globally representative vegetation types based on their trait combinations and could make valid predictions of their global occurrence probabilities based on trait maps. This study provides a proof of concept for the link between plant traits and vegetation types, stimulating enhanced application of trait-based approaches in vegetation modeling. We envision that our approach, our observation-driven trait maps, and vegetation maps may inspire a new generation of powerful traits-based vegetation models.
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The worldwide leaf economics spectrum
Wright, I. J., Reich, P. B., Westoby, M., Ackerly, D. D., Baruch, Z., Bongers, F., Cavender-Bares, J., Chapin, T., Cornelissen, J. H. C., Diemer, M., et al. (2004) · Nature · doi:10.1038/nature02403 · Cited by 9,021
Estimating historical changes in global land cover: Croplands from 1700 to 1992
Ramankutty, N., & Foley, J. A. (1999) · Global Biogeochemical Cycles · doi:10.1029/1999gb900046 · Cited by 2,074
The statistical power of abnormal-social psychological research: A review.
Cohen, J. (1962) · The Journal of Abnormal and Social Psychology · doi:10.1037/h0045186 · Cited by 1,824
Cited by
The global spectrum of plant form and function
Díaz, S., Kattge, J., Cornelissen, J. H. C., Wright, I. J., Lavorel, S., Dray, S., Reu, B., Kleyer, M., Wirth, C., Colin Prentice, I., et al. (2016) · Nature · doi:10.1038/nature16489 · Cited by 3,365
Global trait–environment relationships of plant communities
Bruelheide, H., Dengler, J., Purschke, O., Lenoir, J., Jiménez-Alfaro, B., Hennekens, S. M., Botta-Dukát, Z., Chytrý, M., Field, R., Jansen, F., et al. (2018) · Nature Ecology & Evolution · doi:10.1038/s41559-018-0699-8 · Cited by 614
Self-citationHypervolume concepts in niche‐ and trait‐based ecology
Blonder, B. (2018) · Ecography · doi:10.1111/ecog.03187 · Cited by 389
Intraspecific trait variation across scales: implications for understanding global change responses
Moran, E. V., Hartig, F., & Bell, D. M. (2016) · Global Change Biology · doi:10.1111/gcb.13000 · Cited by 346
Fisher, R. A., Muszala, S., Verteinstein, M., Lawrence, P., Xu, C., McDowell, N. G., Knox, R. G., Koven, C., Holm, J., Rogers, B. M., et al. (2015) · Geoscientific Model Development · doi:10.5194/gmd-8-3593-2015 · Cited by 337
Metadata
- Authors
- van Bodegom, P. M., Douma, J. C., & Verheijen, L. M.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2014-09-15
- Volume
- 111
- Issue
- 38
- Pages
- 13733-13738
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2148685117
- Cited by
- 258
- References
- 3
- FWCI
- 21.30
- Type
- journal article
- Language
- en
- Open access
- green
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- van Bodegom, P. M., Douma, J. C., & Verheijen, L. M. (2014). A fully traits-based approach to modeling global vegetation distribution. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1304551110
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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