Assessment of secondary succession in North Carolina: Advancing understanding of successional vegetation through coupled field and remote sensing studies

Background/Question/Methods

Secondary successional ecosystems are widespread across the southeastern US and, as a whole, comprise a substantial terrestrial sink for atmospheric carbon dioxide.  However, the transient nature of vegetation structure and function along successional trajectories means that the magnitude of this sink is unsteady through time.  Many studies have shown the temporal variability of carbon sequestration by successional ecosystems in this region; however, uncertainty remains concerning the spatial distribution of these ecosystems, spatial trends in trajectories of successional vegetation, and sensitivity of successional vegetation, trajectories and carbon dynamics to climate variability.  A clear understanding of these factors is necessary to predict future carbon sequestration and other ecological processes within this region.  A unique opportunity exists to address these and other uncertainties and to improve understanding of secondary succession in this region using high-resolution Lidar (light detection and ranging) data that were collected over the entire state of North Carolina in recent years.  Here we compare successional processes across North Carolina using Lidar data and ground-based observations along multiple successional chronosequences representing common land-use patterns from each physiographic region of the state.  Data were collected and analyzed by a team of twelve undergraduate students and their faculty mentors from five North Carolina institutions.

Results/Conclusions

We determined that vegetation characteristics derived from the statewide Lidar dataset captured general patterns of vegetation structural changes during secondary succession, but the relatively low density of Lidar pulse returns (approximately 0.1/m²) limited the power of remote sensing comparisons within chronosequences or among sites.  We combined Lidar-derived vegetation variables (canopy height, canopy density) with ground-based biometric observations (tree height, basal area, species distribution, stand age and leaf area index) and identified trajectories within each successional chronosequence related to both vegetation structure and species composition.  Comparison of these trajectories among chronosequences revealed that secondary ecosystem succession follows predictable patterns but results in a diversity of forest ecosystems across the region.