To assess ecosystem succession in the coastal plain region of North Carolina we used Lidar remote sensing combined with ground-based measurements. Our study area is on private land located in Hoke County, NC. The uplands of the property are dominated by plantation pines, (Pinus palustris and Pinus taeda). Lower elevations consist mainly of wetlands composed of Acer rubrum and Nyssa sylvatica. The uplands have been managed through prescribed burnings and chemical treatments to thin out unwanted species while the lower contours have been left relatively undisturbed. During fall 2010, a total of 14 permanent 20x20-m plots were established. Plots encompassed natural pine, pine plantation, and maple/gum stands of various ages. Age and height of the three largest trees in each plot were determined using an increment borer and hypsometer, respectively. Trees were identified to species and the diameter at breast height was measured, using a diameter tape, for species with a diameter > 5 cm. To learn about the productivity within stands, leaf area index (LAI) was measured at nine subplots within each plot using a LAI 2000 plant canopy analyzer. These measurements in combination with lidar-based stand characteristics offer an insight into how secondary succession progresses in the coastal plain
Results/Conclusions
Preliminary results show that wetland stands have a greater species richness than upland stands. This may be the result of moisture differences or suppression of hardwood invasion in the uplands due to the regular burning and pine straw harvesting. The oldest upland stand had a lesser density of trees and an LAI reading around 1.0. The counterpart stand in the wetlands had a greater density of trees and an LAI around 2.3. Leaf area increased with increasing tree density. Within the natural pine forest it was shown that density decreased with increasing age. In both the natural pine and wetland forests older stands had a greater total basal area than the younger stands. Data suggests that secondary succession in the forests of this region vary according to geography and local management practices. The data from this study can be combined with data from the mountains and the piedmont to obtain a picture of succession throughout the state.