Please use this identifier to cite or link to this item:
http://hdl.handle.net/1893/31092
Appears in Collections: | Biological and Environmental Sciences Journal Articles |
Peer Review Status: | Refereed |
Title: | Demographic trade-offs predict tropical forest dynamics |
Author(s): | Rüger, Nadja Condit, Richard Dent, Daisy H DeWalt, Saara J Hubbell, Stephen P Lichstein, Jeremy W Lopez, Omar R Wirth, Christian Farrior, Caroline E |
Issue Date: | 2020 |
Date Deposited: | 4-May-2020 |
Citation: | Rüger N, Condit R, Dent DH, DeWalt SJ, Hubbell SP, Lichstein JW, Lopez OR, Wirth C & Farrior CE (2020) Demographic trade-offs predict tropical forest dynamics. Science, 368 (6487), pp. 165-168. https://doi.org/10.1126/science.aaz4797 |
Abstract: | Understanding tropical forest dynamics and planning for their sustainable management require efficient, yet accurate, predictions of the joint dynamics of hundreds of tree species. With increasing information on tropical tree life histories, our predictive understanding is no longer limited by species data but by the ability of existing models to make use of it. Using a demographic forest model, we show that the basal area and compositional changes during forest succession in a neotropical forest can be accurately predicted by representing tropical tree diversity (hundreds of species) with only five functional groups spanning two essential trade-offs—the growth-survival and stature-recruitment trade-offs. This data-driven modeling framework substantially improves our ability to predict consequences of anthropogenic impacts on tropical forests. |
DOI Link: | 10.1126/science.aaz4797 |
Rights: | This is the author’s version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in Science on 10 April 2020, 368 (6487), pp. 165-168, DOI: https://doi.org/10.1126/science.aaz4797 |
Files in This Item:
File | Description | Size | Format | |
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Ruger_et_al_Science_revised_final_v4-zusammengefu__gt-1.pdf | Fulltext - Accepted Version | 3.01 MB | Adobe PDF | View/Open |
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