view from Burnt Ridge (the northern edge of the Knobs Region physiographic province) to Big Hill and into the Outer Bluegrass province - near Berea, KY

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Announcement: An organizational meeting of the Kentucky Old-Growth Forest Society will be held from June 15th-16th at Pine Mountain State Resort Park. For more details, go here.

The goals of the Kentucky Old-Growth Society are to:

Neil Pederson, Associate Professor, Department of Biological Sciences, Eastern Kentucky University, Richmond, KY 40475;

Ben Poulter, Research Scientist, Duke University, Durham, NC 27708;

Marc Evans, Ecology Program Manager, Kentucky Nature Preserves Commission, Frankfort, KY 40601.

Abstract

Old-growth forests provide many benefits to society such as being home to genetic diversity that some day may be useful for medical or agricultural science or magnets for ecotourism. Just as important, old-growth forests are still revealing natural history information that will help guide ecosystem restoration and management plans. Such information is especially important during this time of rapid environmental change and biological extinction, especially in the biologically diverse region of the commonwealth of Kentucky. Kentucky, however, is still relatively unexplored compared to most states east of the Great Plains. For example, Blanton Forest, a 2200+ acre tract of old-growth forest, was 'discovered' just over a decade ago. The goal of our study is to identify potential tracts of old-growth forest in Kentucky.

We used two two methods to identify potential old-growth locations (POG). Method 1 uses known old-growth sites across the commonwealth of Kentucky to calibrate characteristics of POG locations based on a generalized linear model (GLM). Method 2 applies the Stahle and Chaney (1994) model (SCM) for the prediction of old-growth forests. A qualitative comparison between the two methods shows that the SCM identifies potential old-growth locations that have a probability of ~95% or greater using the GLM. Our current GLM does a poor job at predicting POG forest; only 17% of the variability of known old-growth sites versus randomly selected points can be accounted for by this method. A small number of known old-growth sites increases the variability and weaknesses within the GLM. Another cause for the overestimation of POG using the GLM methodology may be the definition of old-growth for the known OG sites. Despite this, however, there is general agreement with the two methodologies. Two of the strongest predictors in the GLM method are slope and aspect, which are the primary predictors of old-growth in SCM. In the GLM, a 40% slope is eleven times more likely to have old-growth than a 10% slope and old-growth on south-facing slopes are 2.9 times more likely than north-facing slopes. The strongest predictor of POG in GLM, however, is road density; areas with a road density of 9 km/km2 are 149 times more likely to have old-growth than areas with a road density of 54 km/km2!

These maps of potential old-growth forests will be refined and then used as a guide for the fledgling Kentucky Old-Growth Society. The maps can also act a guide for the landscape health of the commonwealth of Kentucky because they will provide a method to quantify the amount of altered land in the region.

Poster [in Adobe Acrobat Reader Format]