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Finding Old Forests: The Structural Patterns & Distribution of Vermont's Old Growth
van Doorn, Alyssa
van Doorn, Alyssa
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Abstract
Old forests are ecologically significant yet increasingly rare across the eastern United States. In Vermont, widespread historical land use has obscured their distribution, leaving many stands undocumented. This study investigates the structural characteristics and spatial patterns of late-successional and old-growth forests in Vermont, with a focus on assessing the utility of the Vermont Old Forest Prediction Model, a MaxEnt-based tool designed to identify likely old forest locations. Thirty-three forest sites were sampled using a stratified random approach informed by the model’s suitability scores. Forest structure was measured using standardized inventory methods, and natural community classifications were assigned in the field. Results revealed that dominant tree age was positively correlated with key structural attributes such as large tree density, large tree basal area, and aboveground biomass. No significant structural variation was detected among natural community types. Multivariate analyses showed partial clustering by seral stage but weak overall separation. The prediction model's suitability scores were significantly correlated with dominant tree age, supporting its value for guiding surveys. Five previously undocumented old forests were identified, highlighting the model’s application as a conservation planning tool. This research contributes to a better understanding of old forest structure in Vermont and demonstrates how predictive modeling and field surveys can be integrated to support inventory efforts and conservation strategies.
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Date
2025-05-10