Patterns of Understory Evergreen Shrubs in Two Wilderness Areas of George Washington-Jefferson National Forest using Remote Sensing and Terrain Analysis

Abstract

This study evaluated the distribution and environmental controls of understory evergreen shrub communities within two federally designated wilderness areas of southwest Virginia at Mountain Lake and Peters Mountain, where human disturbances and access are limited. We focused primarily on the dominant understory evergreen shrubs Rhododendron maximum and Kalmia latifolia. Remotely sensed datasets, topographic variables, and ecological analyses were integrated to investigate relationships between shrub occurrence, topographic gradients, and canopy structure. Landsat imagery and VBMP orthoimages were combined with LiDAR-supported structural information to characterize understory vegetation patterns across heterogeneous forest environments. Spatial analyses demonstrated that evergreen shrub communities were preferentially associated with mesic topographic settings, riparian corridors, north-facing slopes, and areas exhibiting reduced solar exposure and greater moisture retention. The study identified limitations in conventional optical remote sensing approaches for detecting sub-canopy vegetation under dense overstory conditions and offered a new approach to overcome this challenge. The integration of terrain metrics and multi-source geospatial datasets improved shrub mapping accuracy and strengthened interpretation of understory spatial variability. Ecologically, dense shrub layers contribute to reduced tree seedling recruitment, altered nutrient cycling, and shifts in understory biodiversity. These findings emphasize the significance of monitoring understory vegetation for forest management and conservation frameworks in Appalachian ecosystems.