Decision Support Tools to Inform the Rehabilitation and Management of High Graded Forests

Abstract Numerous forests in the eastern United States have been degraded due to past exploitative timber harvesting known as high grading. High graded forest stands may not improve without active rehabilitation and may require targeted silvicultural treatments. This study focuses on high graded mixed-oak (mixed-Quercus spp.) stands and aims to develop a model that can identify past high grading and to determine modifications that may improve forest management recommendations provided by the prominent decision support tool, SILVAH. We present a model that uses standard forest inventory measurements and does not require knowledge of preharvest stand conditions to predict with moderate to high accuracy whether a stand was high graded, which could be particularly useful for nonindustrial private forests. Results indicate that modifications to SILVAH may be necessary to improve its utility for prescribing silvicultural treatments in high graded stands.