Assessing forest edge effects in the southeastern U.S. using NASA’s G-LiHT Airborne Imager
Human activity fragments forested ecosystems, creating edge environments that may alter forest structure and composition. The intensity and penetration of edge effects reflect a range of factors, including fragment size, shape, and adjacent land cover characteristics. Remote sensing data, in particular high-resolution data from airborne platforms, offer the unique possibility to assess forest edge effects at regional scales. In this study, we used nearly 3,000 km of airborne remote sensing transects from Goddard’s Lidar, Hyperspectral, and Thermal Airborne Imager (G-LiHT) to characterize changes in canopy structure from the edge to interior of natural forests and pine plantations. We specifically examined whether plantation forest management in the southeastern U.S. region mitigates edge effects in natural forests. Previous studies have combined managed and natural forest types, potentially underestimating the extent and magnitude of forest fragmentation in the region. High-resolution (1 m) G-LiHT data were combined with time series of Landsat imagery to identify edge age and adjacent land cover information, distinguishing tree plantations from natural forest.
G-LiHT data collections in 2011 sampled 0.24% of the total area of the southeastern U.S., measuring 8562 distinct forest fragment edges. Separating pine plantations from natural forests increased regional estimates of forest fragmentation. The “soft” contrast between tree plantation and natural forest edges may limit edge effects, but soft-contrast edges were also younger on average than other edges, reflecting frequent disturbance by timber harvests. Our results illustrate the potential for airborne remote sensing instruments to quantify local variability in forest edge effects across landscapes. By testing the relative importance of proposed drivers of edge effects, we can advance our understanding of fragmentation and improve our ability to manage forest edges for carbon and biodiversity benefits.