Crown plasticity and competition for canopy space: A new spatially implicit model parameterized for 250 North American tree species

Drew W. Purves, Jeremy W. Lichstein, Stephen Wilson Pacala

Research output: Contribution to journalArticlepeer-review

142 Scopus citations


Background. Canopy structure, which can be defined as the sum of the sizes, shapes and relative placements of the tree in a forest stand, is central to all aspects of forest ecology. But there is no accepted method for deriving canopy structure from the sizes, species and biomechanical properties of the individual trees in a stand. Any, such method must capture the fact that trees are highly plastic in the growth, forming tessellating crown shapes that fill all or most of the canopy space. Methodology/Principal Findings. We introduce a new, simple and rapidly-implemented model the ideal Tree Distribution, ITD-with tree form (height allometry and crown shape), growth plasticity, and space-filling, at its core. The ITD predicts the canopy status (in or out of canopy), crown depth, and total and exposed crown area of the trees in a stand, given their species, sizes and potential crown shapes. We use maximum likelihood methods, in conjunction with data from over 100,000 trees taken from forests across the coterminous US, to estimate ITD model parameters for 250 North American tree species. With only two free parameters per species-one aggregate parameter to describe crown shape, and one parameter to set the so called depth bias-the model captures between-species patterns in average canopy status, crown radius, and crown, depth, and within-species means of these metrics vs stem diameter. The model also predicts much of the variation in these metrics for a tree of a given species and size, resulting solely from deterministic responses to variation in stand structure. Conclusion/Significance. This new model, with parameters for US tree species, opens up new possibilities for understanding and modeling forest dynamics at local and regional scales, and may provide a new way to interpret remote sensing data of forest canopies, including LIDAR and aerial photography.

Original languageEnglish (US)
Article numbere870
JournalPloS one
Issue number9
StatePublished - Sep 12 2007

All Science Journal Classification (ASJC) codes

  • General
  • General Biochemistry, Genetics and Molecular Biology
  • General Agricultural and Biological Sciences


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