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. Study Implications: High graded forest stands are often not readily apparent and likely require specific forest management practices. We present a tool that uses standard forest inventory measurements to predict past high grading, which can be used to inform and prioritize forest management decisions. We also present suggested modifications to the prominent decision support tool, SILVAH, that may improve its ability to prescribe optimal silvicultural treatments for high graded stands. Results from this study provide forestry professionals/landowners working in the mixed-oak forests of the northeastern United States with tools to inform forest management decisions that aim to return degraded stands to healthier and more productive states.