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Title: Demographic trade-offs predict tropical forest dynamics
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.
Authors:
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Award ID(s):
1939559
Publication Date:
NSF-PAR ID:
10182967
Journal Name:
Science
Volume:
368
Issue:
6487
Page Range or eLocation-ID:
165 to 168
ISSN:
0036-8075
Sponsoring Org:
National Science Foundation
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    Methods

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