This dataset depicts indices of forest fragmentation within the U.S. Northeast region. This dataset can help inform prioritization of landscapes for conservation through identification of more intact forested areas. Forest fragmentation was assessed using information derived from the National Land Cover Dataset (NLCD) and USGS 1:100,000 scale roads. Within each forested ecoregion in the World Wildlife Fund ecoregions dataset, landscape units (land units) were defined using U.S. Census Bureau TIGER highway networks. Land units were blocks of forested land bounded by highways and were required to be at least 2,000 hectares in size. Land units smaller than 2,000 hectares or areas within urban areas were excluded from this analysis. The [...]
Summary
This dataset depicts indices of forest fragmentation within the U.S. Northeast region. This dataset can help inform prioritization of landscapes for conservation through identification of more intact forested areas. Forest fragmentation was assessed using information derived from the National Land Cover Dataset (NLCD) and USGS 1:100,000 scale roads. Within each forested ecoregion in the World Wildlife Fund ecoregions dataset, landscape units (land units) were defined using U.S. Census Bureau TIGER highway networks. Land units were blocks of forested land bounded by highways and were required to be at least 2,000 hectares in size. Land units smaller than 2,000 hectares or areas within urban areas were excluded from this analysis. The NLCD dataset was converted into two categories: forest (including woody wetlands) and nonforest (including water). USGS roads were converted to 30 meter rasters and superimposed on the NLCD dataset. All forest patches less than 1 hectare were reclassified to match the surrounding land cover type to reduce the time required for processing the analysis. The spatial pattern analysis software tool FRAGSTATS was then used to calculate a large set of landscape and patch level metrics. The density of all 1:100,000 scale roads (except 4-wheel drive roads) was determined for each land unit. A subset of these metrics was then extracted to calculate unweighted ordinal scores; these metrics include road density, total core area index (percentage of all forest area within a land unit that is considered core area, based on a 90 meter edge buffer distance), mean nearest neighbor (average distance in meters from one forest patch to the nearest forest patch), class area (total amount of forest in hectares within each land unit), and percentage of landscape (percentage of land unit composed of forest). These metrics were converted to ordinal scores using natural breaks (Jenks optimization) with 5 classes. These ordinal scores were then summed to create an overall fragmentation index. This dataset represents only a subset of the information contained in the forest fragmentation database compiled by CBI. Please contact CBI directly for the full forest fragmentation database. This dataset is described in detail in: Heilman, G.E. Jr., J.R. Strittholt, N.C. Slosser, and D.A. DellaSala. 2002. Forest fragmentation of the conterminous United States: assessing forest intactness through road density and spatial characteristics. BioScience 52(5): 411-422.