Modeling seed-origin oak regeneration in the central Appalachians

P. J. Gould, K. C. Steiner, M. E. McDill, J. C. Finley

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14 Scopus citations

Abstract

We describe the development of a model to quantify seed-origin oak regeneration potential in advance of complete overstory removal in central Appalachian oak stands. The model was developed using a "top-down" modeling approach that differs significantly from the approaches used to develop similar models for other regions. The modeling approach was designed to take advantage of the best data available for the region. A stand-level model was first fit using a long-term data set from Pennsylvania that was developed, in part, from operational data collected through the course of timber sales. The stand-level model describes the relationship between oak advanced regeneration distribution (the percentage of 4 m2 sample plots that contained at least one oak seedling before harvest) and third-decade seed-origin oak stocking (the percentage of growing space occupied by seed-origin oaks in the third decade after harvest). Inverse modeling was used to fit a plot-level model using a highly detailed short-term data set collected as part of an ongoing study of regeneration development in Pennsylvania. A negative exponential function (1 - e-ax) was used for the plot-level model to simplify the calculation of multiple seedling success probabilities. The plot-level model predicts the probability that a 4 m2 plot will be occupied by an oak during the third decade after harvest based on the sum of the heights of oak advanced regeneration (aggregate height). The top-down inverse modeling approach used here proved to be a feasible alternative to the more common individual seedling modeling approach, which requires more specialized data that are often difficult to obtain.

Original languageEnglish (US)
Pages (from-to)833-844
Number of pages12
JournalCanadian Journal of Forest Research
Volume36
Issue number4
DOIs
StatePublished - Apr 1 2006

All Science Journal Classification (ASJC) codes

  • Global and Planetary Change
  • Forestry
  • Ecology

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