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    Author(s): Peter H. Wychoff; James S. Clark
    Date: 2000
    Source: Can. J. For. Res. 30: 156-167 (2000)
    Publication Series: Miscellaneous Publication
    PDF: View PDF  (590 KB)

    Description

    Ecologists and foresters have long noted a link between tree growth rate and mortality, and recent work suggests that i&erspecific differences in low growth tolerauce is a key force shaping forest structure. Little information is available, however, on the growth-mortality relationship for most species. We present three methods for estimating growth-mortality functions from readily obtainable field data. All use annual mortality rates and the recent growth rates of living and dead individuals. Annual mortality rates are estimated using both survival analysis and a Bayesian approach. growth rates are obtained from increment cores. Growth-mortality functions are fitted using two parametric approaches and a nonparametric approach. The three methods are compared using bootstrapped cbnfidence intervals and likelihcod ratio tests. For two example species, Acer rubrum L. and Cornus florida L., growth-mortality functions indicate a substantial difference in the two species' abilities to withstand slow growth. Both survival analysis and Bayesian estimates of mortality rates lead to similar growth-mortality functions, with the Bayesian approach providing a means to overcome the absence of long-term census data. In fitting growth-mortality functions, the nonparametric approach reveals that inflexibility in parametric methods can lead to errors in estimating mortality risk at low growth. We thus suggest that nonparametric fits be used as a tool for assessing parametric models.

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    Citation

    Wychoff, Peter H.; Clark, James S. 2000. Predicting Tree Mortality From Diameter Growth: A Comparison of Maximum Likelihood and Bayesian Approaches. Can. J. For. Res. 30: 156-167 (2000)

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https://www.fs.usda.gov/treesearch/pubs/2238