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Title: Unlocking the forest inventory data: relating individual tree performance to unmeasured environmental factors

Author: Lichstein, Jeremy W.; Dushoff, Jonathan; Ogle, Kiona; Chen, Anping; Purves, Drew W.; Caspersen, John P.; Pacala, Stephen W.;

Date: 2010

Source: Ecological Applications. 20(3): 684-699

Publication Series: Scientific Journal (JRNL)

Description: Geographically extensive forest inventories, such as the USDA Forest Service's Forest Inventory and Analysis (FIA) program, contain millions of individual tree growth and mortality records that could be used to develop broad-scale models of forest dynamics. A limitation of inventory data, however, is that individual-level measurements of light (L) and other environmental factors are typically absent. Thus, inventory data alone cannot be used to parameterize mechanistic models of forest dynamics in which individual performance depends on light, water, nutrients, etc. To overcome this limitation, we developed methods to estimate species-specific parameters relating sapling growth (G) to L using data sets in which G, but not L, is observed for each sapling. Our approach should be useful for estimating light-dependent growth functions from inventory data that lack direct measurements of L. This approach could be extended to estimate parameters relating sapling mortality to L from inventory data, as well as to deal with uncertainty in other resources (e.g., water or nutrients) or environmental factors (e.g., temperature).

Keywords: ecoinformatics, environmental data, growth, tree measurements, inventory

Publication Notes:

  • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

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Lichstein, Jeremy W.; Dushoff, Jonathan; Ogle, Kiona; Chen, Anping; Purves, Drew W.; Caspersen, John P.; Pacala, Stephen W. 2010. Unlocking the forest inventory data: relating individual tree performance to unmeasured environmental factors. Ecological Applications. 20(3): 684-699.

 


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