Disentangling the effects of tree size and light limitation on growth in the Amazon using LiDAR
Scott
C
Stark, University of Arizona, scstark@email.arizona.edu
Scott
R.
Saleska, University of Arizona, saleska@email.arizona.edu
(Presenting)
Brian
J.
Enquist, University of Arizona, benquist@email.arizona.edu
Monica
Takako
Shimabukuro, National Institute for Space Research (INPE), takako@dsr.inpe.br
Individual trees grow as a function of their size. These size dependencies have important stand-level ramifications, influencing competitive thinning, tree size distributions, and production rates. The relationship between growth rate and tree size may be governed by the geometry of vascular transport networks as well as changing patterns of resource limitation. We propose to test a general metabolic production model that is based upon these premises with data on individual tree growth and light environments. To conduct this test, light availability at the crown of individual trees must be estimated or directly measured. Small footprint LiDAR remote sensing data presents a unique opportunity to predict light environments by generating fine-grained data (meter scale resolution) on the spatial structure of the canopy. Here we develop a model to predict light penetration from canopy structure using LiDAR data, anticipating LiDAR surveys that will be conducted in the Tapajos National forest, PA, and near Manaus, AM, Brazil in 2008.
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