Chen, Guangsheng; Pan, Shufen; Hayes, Daniel J; Tian, Hanqin (2017): Spatial and temporal patterns of plantation forests in the United States since the 1930s, links to gridded result files in different formats. PANGAEA, https://doi.org/10.1594/PANGAEA.873558, Supplement to: Chen, G et al. (2017): Spatial and temporal patterns of plantation forests in the United States since the 1930s: an annual and gridded data set for regional Earth system modeling. Earth System Science Data, 9(2), 545-556, https://doi.org/10.5194/essd-9-545-2017
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Plantation forest area in the conterminous United States (CONUS) ranked second among the world's nations in the land area apportioned to forest plantation management. As compared to the naturally-regenerated forests, plantation forests demonstrate significant differences in biophysical characteristics, and biogeochemical and hydrological cycles as a result of more intensive management practices. Inventory data have been reported for multiple time periods at plot, state and regional scales across the CONUS, but there lacks the requisite annual and spatially-explicit plantation data set over a long-term period for analysis of the role of plantation management at regional or national scale. Through synthesizing multiple inventory data sources, this study developed methods to spatialize the time series plantation forest and tree species distribution data for the CONUS over the 1928-2012 time period. According to this new data set, plantation forest area increased from near zero in the 1930s to 268.27 thousand km2 by 2012, accounting for 8.65% of the total area of forest land area in the CONUS by 2012. Regionally, the South contained the highest proportion of plantation forests, accounting for about 19.34% of total forest land area in 2012. This time series and gridded data set developed here can be readily applied in regional Earth system modeling frameworks for assessing the impacts of plantation management practices on forest productivity, carbon and nitrogen stocks, and greenhouse gas (e.g., CO2, CH4 and N2O) and water fluxes at regional or national scales.
Latitude: 38.000000 * Longitude: -96.000000
45 data points