introduction - Pennsylvania Natural Heritage Program

Data AnalysisBiological Diversity AreasData on species of special concern and natural communities obtained during the 2001 and 2002 field seasonswere combined with prior existing data and summarized. All sites with rare species and/or naturalcommunities, as well as exceptional examples of more common natural communities were selected forinclusion in Biological Diversity Areas (BDAs). Plant species nomenclature follows Rhoads and Block (2000).Data on the occupied habitat area for each site selected was then compiled in a GIS format using ESRIArcView 3.2a software. From the occupied habitat data, boundaries defining core habitat and supportingnatural landscape for each BDA were determined based upon physical factors (e.g., slope, aspect, hydrology),ecological factors (e.g., species composition, disturbance regime), and buffer specifications provided byjurisdictional government agencies. Boundaries tend to vary in size and extent depending on the physicalcharacteristics of a given site and the ecological requirements of its unique natural elements. For instance, twowetlands of exactly the same size occurring in the same region may require very different buffers if onereceives mostly ground water and the other mostly surface water, or if one supports migratory waterfowl andthe other does not. BDAs were then assigned a significance rank to help prioritize future conservation efforts.This ranking is based on the extent, condition, and rarity of the unique feature, as well as the quality of thesurrounding landscape (see Appendix I for further description of ranks).Landscape Conservation AreasLandscape Conservations Areas (LCAs) were designated around landscape features that function as a linkingelement within an aggregation of BDAs, and/or large blocks of contiguous forest. LCAs designated aroundcontiguous forest were identified by means of GIS analysis, refined through aerial photograph inspection, andselected based on size. Further analysis of blocks for comparison purposes was conducted to assess percentroadless area, miles of stream, acres of coniferous forest, and acres of natural wetlands.Forest Block IdentificationForested areas in Clearfield County were first identified through a classification of Pennsylvania’s NationalLand Cover Database (NLCD), downloaded from the Pennsylvania Spatial Data Access website(http://pasda.psu.edu). To identify blocks of contiguous core forest habitat, fragmenting features and edgeinfluencedforest areas were removed from the forested areas. Because the level of disturbance whicheffectively prevents movement is different for different species, contiguous forest blocks were identified attwo levels. Tier I was designed to reflect the requirements of most vertebrates with relatively largeterritories (birds, larger mammals) and was used identify LCA boundaries. Fragmenting features for tier Iwere identified as: interstate, US route, and state route roads; major rivers and large streams. Tier II wasdesigned to reflect the requirements of species more sensitive to fragmentation: small mammals,amphibians and reptiles, and large invertebrates. Fragmenting features were identified as: all features usedfor Tier I; all roads, regardless of substrate, 6 m or wider, as recorded in GIS map layers available fromPennDOT and the Clearfield County Planning Office. The Tier II blocks identified roadless core habitatareas and were used as supplemental information to compare the quality of Tier I blocks. For both blocktiers, edge-influenced forest areas were identified as any forest within 100 m of a fragmenting feature or anon-forest land cover type. A further buffer of 50 m was added to ensure that core forest area would be atleast 100 m in width at all points within a contiguous forest block.Block RefinementAerial photographs (Clearfield County Planning Office, 2000) were inspected to locate any powerline orpipeline right-of-ways, new roads, gas wells, mined areas, and other non-forest areas within contiguousforest blocks 5000 acres and above in size. NLCD forest data was re-analyzed using the more complete16