Interactions of Biosphere and Atmosphere within Longleaf Pine Restoration Areas

Abstract

Longleaf pine forests are economically and culturally valued ecosystems in the southeastern United States. Efforts to restore the longleaf pine ecosystem have risen dramatically over the past three decades. Longleaf pine restoration generally involves varying degrees of forest harvesting and frequent applications of prescribed fire. Thus, it is important to understand their interactions with the atmosphere on a large scale. In this study, we analyzed 14 parameters of aerosols, gasses, and energy from three areas with longleaf pine restoration (named Bladen in eastern NC, Escambia in southern AL and northern FL, and Kisatchie in central LA, USA) from 2000 to 2021 using multiple satellites. Averaged across the areas, the monthly aerosol optical depth at 483.5 nm was about 0.022, and the monthly aerosol single scattering albedo was 0.97. Black carbon column mass density averaged 7.46 × 10−7 kg cm−2 across these areas, but Kisatchie had a higher monthly dust column mass density (2.35 × 10−4 kg cm−2) than Bladen or Escambia. The monthly total column ozone and CO concentration averaged about 285 DU and 135 ppbv across the three areas. Monthly SO2 column mass density was significantly higher in Bladen (4.42 × 10−6 kg cm−2) than in Escambia and Kisatchie. The monthly surface albedo in Escambia (0.116) was significantly lower than in the other areas. The monthly total cloud area fraction averaged about 0.456 across the three areas. Sensible and latent heat net flux and Bowen ratios significantly differed among the three areas. Bowen ratio and total cloud area fraction were not significantly correlated. Net shortwave of the forest surface averaged about 182.62 W m−2 across the three areas. The monthly net longwave was much lower in Bladen (−90.46 W m−2) than in Escambia and Kisatchie. These results provide the baseline information on the spatial and temporal patterns of interactions between longleaf pine forests under restoration and the atmosphere and can be incorporated into models of climate change.