Detecting Vegetation Recovery after Fire in A Fire-Frequented Habitat Using Normalized Difference Vegetation Index (NDVI)

Research Highlights: Fire-frequented savannas are dominated by plant species that regrow quickly following fires that mainly burn through the understory. To detect post-fire vegetation recovery in these ecosystems, particularly during warm, rainy seasons, data are needed on a small, temporal scale. In the past, the measurement of vegetation regrowth in fire-frequented systems has been labor-intensive, but with the availability of daily satellite imagery, it should be possible to easily determine vegetation recovery on a small timescale using Normalized Difference Vegetation Index (NDVI) in ecosystems with a sparse overstory. Background and Objectives: We explore whether it is possible to use NDVI calculated from satellite imagery to detect time-to-vegetation recovery. Additionally, we determine the time-to-vegetation recovery after fires in different seasons. This represents one of very few studies that have used satellite imagery to examine vegetation recovery after fire in southeastern U.S.A. pine savannas. We test the efficacy of using this method by examining whether there are detectable differences between time-to-vegetation recovery in subtropical savannas burned during different seasons. Materials and Methods: NDVI was calculated from satellite imagery approximately monthly over two years in a subtropical savanna with units burned during dry, dormant and wet, growing seasons. Results: Despite the availability of daily satellite images, we were unable to precisely determine when vegetation recovered, because clouds frequently obscured our range of interest. We found that, in general, vegetation recovered in less time after fire during the wet, growing, as compared to dry, dormant, season, albeit there were some discrepancies in our results. Although these general patterns were clear, variation in fire heterogeneity and canopy type and cover skewed NDVI in some units. Conclusions: Although there are some challenges to using satellite-derived NDVI, the availability of satellite imagery continues to improve on both temporal and spatial scales, which should allow us to continue finding new and efficient ways to monitor and model forests in the future.

A Three-Dimensional Assessment of Soil δ13C in a Subtropical Savanna: Implications for Vegetation Change and Soil Carbon Dynamics

Tree/shrub encroachment into drylands is a geographically widespread vegetation change that often modifies soil organic carbon (SOC) storage and dynamics, and represents an important yet uncertain aspect of the global carbon (C) cycle. We quantified spatial patterns of soil δ13C to 1.2 m depth in a subtropical savanna to evaluate the magnitude and timing of woody encroachment, and its impacts on SOC dynamics. Woody encroachment dramatically altered soil δ13C spatial patterns throughout the profile; values were lowest in the interiors of woody patches, increased towards the peripheries of those patches, and reached highest values in the surrounding grasslands. Soil δ13C and 14C revealed this landscape was once dominated by C4 grasses. However, a rapid vegetation change occurred during the past 100–200 years, characterized by (1) the formation and expansion of woody patches across this landscape, and (2) increased C3 forb abundance within remnant grasslands. Tree/shrub encroachment has substantially increased SOC and the proportion of new SOC derived from C3 plants in the SOC pool. These findings support the emerging perspective that vegetation in many dryland ecosystems is undergoing dramatic and rapid increases in SOC storage, with implications for the C cycle at regional and global scales.