Longleaf Pine Extent
This layer was one of the early South Atlantic LCC indicators in the pine and prairie ecosystem. It captured the overall acres of longleaf pine in the South Atlantic geography. It has since been removed as an indicator. It was never scored in the 2015 State of the South Atlantic or used in the Blueprint because the data is summarized at too coarse a scale. We plan to revisit this indicator when finer scale data is available to depict longleaf pine extent.
Reason for Selection
Acres of longleaf pine is one of the cultural resource indicators for the South Atlantic LCC. Longleaf pine was the predominant ecosystem at the time of colonialization, so it contributes to Native Americans’ ability to experience the landscape of their historical cultural heritage. It is also an important component of the type of landscape settlers encountered with westward expansion, characterized by niche economic activities like turpentining, which is no longer practiced anywhere in the United States
Tabular data for acres of longleaf pine forest type group, along with sampling error in percentage, were obtained from the Carol Perry, Forester with the Forest Inventory & Analysis (FIA) program of the USDA Forest Service. In the longleaf pine forest type, longleaf pine occurs as a pure type or comprises a majority of the trees in the overstory. For a forest to be defined as the longleaf pine forest type, the pine component must be 50% or greater in the overstory. The data for Alabama, Florida, Georgia and South Carolina are from 2013. The data for North Carolina are from 2012.
Spatial data for the FIA unit boundaries were created by editing a county boundary dataset to match the maps shown in state level FIA reports.
Tabular data was joined with spatial data for forest inventory analysis units.
-- To better understand the accuracy of these acreage estimates, please review the sampling error information in the attribute table.
-- It would be preferable to be able to estimate longleaf pine acres by county. However, the sampling error associated with those estimates in the FIA data are large. Foresters for the FIA recommended that we look at the unit level estimates instead.
Forest Inventory and Analysis Database, St. Paul, MN: U.S. Department of Agriculture, Forest Service, Northern Research Station. <http://www.fia.fs.fed.us/>