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Restoration efforts to increase wildlife habitat quality in agricultural landscapes have limited funding and are typically
done on a first come, first serve basis. In order to increase the efficiency of these restoration efforts, a prioritized ranking
system is needed to obtain the greatest increase in habitat quality possible for the fewest amount of hectares restored. This
project examines the use of a GIS based multi-criteria approach to prioritize lands for reforestation along the Kaskaskia
River in Illinois. Loss of forested area and corresponding increase in forest fragmentation has decreased songbird habitat
quality across the Midwestern United States. We prioritized areas for reforestation based on nine landscape metrics: available
agricultural land, forest cover gaps, edge density, proximity to river, 200 m corridor area, total forest core area, fringe
core area, distance to primary core value, and primary core area. The multi-criteria analysis revealed that high priority
areas for reforestation were most likely to be close to the riparian corridor and existing large blocks of forest. Analysis
of simulated reforestation (0, 0.5, 1.0, 5.0 10.0, 25.0, and 50.0% of highest priority parcels reforested) revealed different
responses for multiple landscape metrics used to quantify forest fragmentation following reforestation, but indicated that
the study area would get the greatest rate of return on reforestation efforts by reforesting 10.0% of the highest priority
areas. This project demonstrates how GIS and a multi-criteria analysis approach can be used to increase the efficiency of
restoration projects. This approach should be considered by land managers when attempting to identify the location and quantity
of area for restoration within a landscape. 相似文献
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