Master's Project: Describing Forest Structure in Southern Blue Ridge Cove Forests: A LiDAR-Based Analysis

Ervin, Jamie

EXECUTIVE SUMMARY: The Southern Blue Ridge Mountains contain some of the largest contiguous patches of old growth forests in the eastern United States. Known for both their beauty and biodiversity, these forests provide rare insight into what the Appalachian landscape may have looked like prior to EuroAmerican settlement. Mountaintrue – a North Carolina-based nonprofit conservation organization – supports ecological restoration as a guiding principle in forest management. For nearly three decades, Mountaintrue (formerly the WNC Alliance) has been a prominent local voice for protecting old growth forests on public lands. Cove forests occupy mid-elevation slopes in concave, mesic coves throughout the Blue Ridge region. Due in part to their sheltered topography and low fire return interval, major natural disturbances are less common in cove forests than nearly any other Appalachian forest community. As a result, these forests tend to reach a late-successional old growth stage if left unlogged. Many of the region’s best-known, most charismatic old growth forest stands lie in cove forests at sites like Joyce Kilmer Memorial Forest and Great Smoky Mountains National Park. Light Detection and Ranging (LiDAR) data has become a popular tool for analyzing forest structure over large landscapes. Publicly-available, high-quality LiDAR data now exists for much of the Southern Blue Ridge. Mountaintrue has begun incorporating LiDAR analysis into their forest advocacy work, and is interested in exploring new methods for using the data to study old growth forests. This project report is a compilation of research collected for Mountaintrue throughout the summer and fall of 2016. LiDAR-derived canopy height models are applied to existing old growth cove forest stands in Pisgah and Nantahala National Forests, and Great Smoky Mountains National Park. A unique method for studying these forests’ horizontal structure is developed using grey-level co-occurrence texture statistics. Products of the project include: --A collection of charts comparing horizontal forest structure in areas with different anthropogenic disturbance histories in Great Smoky Mountains National Park --An analysis of statistical differences between texture values in old growth and second growth cove forests --A collection of regression models which identify occurrences of old growth cove forests throughout the study area with ~60% accuracy based on LiDAR canopy height --A new simple method for studying horizontal canopy heterogeneity using LiDAR canopy height models and texture-based neighborhood statistics These results will aid Mountaintrue’s work to identify old growth forests remotely, and might support future ecological restoration and forest management work in cove forests. The report concludes with a series of recommendations which may improve upon the methods used in this study.

Master's Project: Describing Forest Structure in Southern Blue Ridge Cove Forests: A LiDAR-Based Analysis

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