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    Author(s): Gary L. Gadbury; Michael S. Williams; Hans T. Schreuder
    Date: 2004
    Source: Gen. Tech. Rep. RMRS-GTR-124. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 10 p.
    Publication Series: General Technical Report (GTR)
    Station: Rocky Mountain Research Station
    PDF: Download Publication  (420 B)


    This paper evaluates changes in growth of pine stands in the state of Georgia, U.S.A., using USDA Forest Service Forest Inventory and Analysis (FIA) data. In particular, data representing an additional 10-year growth cy-cle has been added to previously published results from two earlier growth cycles. A robust regression procedure is combined with a bootstrap technique to produce estimates of mean growth with confidence intervals for the fourth, fifth, and sixth inventories of natural pine stands sampled between 1961 and 1990. Results suggest that sixth cycle growth rates of pine stands in Georgia remain fairly constant with rates observed in the fifth growth cy-cle, though they are not up to the level of growth observed in the fourth cycle. Overall, we conclude that growth in the stands screened for this analysis declined between the fourth and fifth cycles but stabilized in the sixth cycle. Inferences cannot be extended to the entire state of Georgia but only to the unknown population represented by the screened dataset of undisturbed natural pine stands. We highlight some specifics on what can and cannot be inferred from FIA data and recommend future actions to increase the chance of detecting changes and revealing factors that might be associated with the changes. The recent switch in FIA to annualized inventories will make it more likely that changes such as these will be easier to detect and interpret in the future.

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    Gadbury, Gary L.; Williams, Michael S.; Schreuder, Hans T. 2004. Revisiting the southern pine growth decline: Where are we 10 years later?. Gen. Tech. Rep. RMRS-GTR-124. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 10 p.


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    bootstrap, cause-effect, forest inventory and analysis, robust regression

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