The spatial distribution of dominant tree species in an undisturbed mature stand tends to be regular and even, often exhibiting less variation than a simple Poisson model would suggest; in contrast the spatial distribution of species in a recovering or transitional stand would be expected to display considerable spatial variation. This paper studies the spatial distribution of hickory trees within the Bormann research plot of Duke Forest in an attempt to assess the degree of variation, as an indicator for forest maturation, using models recently introduced in (Wolpert \& Ickstadt, 1995). A data augmentation scheme and Markov chain Monte Carlo methods are employed to evaluate Bayesian posterior distributions.

Keywords: Bayesian hierarchical models; data augmentation; Markov chain Monte Carlo; spatial extensibility.

Available in PostScript (224 kb) and PDF (260 kb) formats. Cite as:

@InCollection{Icks:Wolp:1997,
      Author = "Katja Ickstadt and Robert L. Wolpert",
       Title = "Multiresolution Assessment of Forest Inhomogeneity",
      Editor = "Constantin Gatsonis and James S. Hodges and Robert E. Kass and
                Robert E. Mc{C}ulloch and Peter Rossi and Nozer D. Singpurwalla",
   BookTitle = "Case Studies in {B}ayesian Statistics, Volume III",
   Publisher = "Springer-Verlag",
     Address = "New York, NY",
      Series = "Lecture Notes in Statistics",
      Volume = 121,
       Pages = "371--386",
        ISBN = "0-387-94990-9",
        Year = 1997,
}