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Stochastic Models for Conifer Tree Crown Profiles

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We perform a feasibility study of using stochastic models to describe the profile of tree crowns and to capture the stochastic nature of the tree crown form for five conifer species of the Sierra Nevada. In 70% of the cases investigated we found that we could model tree crown profiles as a quadratic or cubic trend in conjunction with a simple autoregressive moving average model (ARMA). In the remaining cases we used a quadratic or cubic trend in conjunction with white noise. These stochastic ARMA models are visually and statistically an improvement over using Euclidean geometric crown profile models. Competing models were judged by using Akaike's Information Criterion (AIC) to achieve a parsimonious model. It was found that first-order moving average MA(1) models or first-order autoregressive AR(1) models were adequate for modeling the majority of the cases studied and that these models were qualitatively similar. MA(1) models were preferred over the AR(1) models because less information is required to simulate them. For. Sci. 43(1):25-34.

Keywords: Tree crown architecture; time-series models

Document Type: Journal Article

Affiliations: Graduate Student Researcher, Department of Environmental Science, Policy and Management, University of California, Berkeley

Publication date: 1997-02-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 in forestry

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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