A comparison of prediction models for cover type transitions and their effects on harvest schedules in coastal Oregon
establishment in coastal Oregon. Several species can gain
control of the site depending on stand conditions as well as
management practices. In this study, three cover type
transition models were developed using data from the Siuslaw
National Forest to predict stand establishment patterns in
aggregate forest planning.
Two discrete alternative probability models were
analyzed. The full model included the cover type and age of
the mature stand before harvest as well as vegetation
management treatments. The reduced model included only the
cover type of the mature stand. A third model, the naive
model, consisted of assigning the old-stand cover type to
the regenerated stand with probability one.
Discrete alternative probability models constitute a
challenge in evaluation and validation. A residualgenerating
procedure developed in this study allowed graphic
analysis of residual plots. Although specification bias in
these models remains a potential concern, the full model
gave the best fit of the models analyzed in this study.
The different cover type transition models developed
here resulted in substantially different forest plans in
terms of harvest levels, financial return, and forest
structure. The full model produced forest plans with lower
harvest levels and financial returns, but greater biological
diversity, than the other models investigated in this study.
These results were achieved primarily through the typeconversion
effects of vegetation management treatments.
The attractiveness of vegetation management depended on
minimum rotation age requirements as well as cover type
conversion policies in the forest planning formulation.
Vegetation management was most effective at short minimum
rotation ages. Type conversion policies requiring either
constant or non-decreasing biological diversity over time
resulted in forest plans in which vegetation management was
consistently a marginal or unprofitable investment.
Given the substantial impact of different cover type
transition models on forest plan results, and the
indications of systematic bias in the models tested here,
additional study on predicting cover type transition
patterns is recommended. Recognition of the spatial
configuration of hardwood seed sources surrounding the
reforestation areas is likely to be an important area of
School:Oregon State University
School Location:USA - Oregon
Source Type:Master's Thesis
Keywords:forest management mathematical models site quality
Date of Publication:03/03/1992