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Time-series effective habitat area (EHA) modeling using cost-benefit raster based technique
Institution:1. Ecosystem Management, School of Environment and Rural Science, University of New England, Armidale, NSW 2351, Australia;2. NSW Office of Environment and Heritage (OEH), University of New England, Armidale, NSW 2351, Australia;1. Department of Forest Management and Applied Geoinformatics, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 3, 613 00 Brno, Czech Republic;2. Department of Biology, Faculty of Education, Palacky University, Olomouc, Purkrabská 2, 771 46 Olomouc, Czech Republic;3. Department of Geoinformatics, Faculty of Science, Palacky University, Olomouc, 17. listopadu 50, 771 46 Olomouc, Czech Republic;1. U.S. Geological Survey, Southwest Biological Science Center, Rm. 123, University of Arizona, 1110 E. So. Campus Drive, Tucson, AZ 85719, United States;2. U.S. Geological Survey, Core Science Analytics and Synthesis, Denver Federal Center Bldg. 810, Lakewood, CO 80225, United States;3. U.S. Geological Survey, USA National Phenology Network, 1955 E 6th St., Tucson, AZ 85721, United States;4. NOAA Fisheries Service, Office of Science and Technology, 1315 East West Highway, Silver Spring, MD 20910, United States
Abstract:For successful characterization of ecological processes and prioritization of habitat networks it is necessary to describe and quantify landscape structure and connectivity. However, at landscape scale, it is highly impractical to measure and map all elements of biodiversity, and therefore, biodiversity surrogates are commonly used to represent biodiversity values. Land cover and vegetation are most often used as a biodiversity surrogate. The study investigated how land use change affects the status of the biodiversity surrogates in terms of the loss or gain of habitat (areal extent), loss of habitat condition (degradation) and habitat fragmentation. Effective habitat area (EHA) and raster based cost–benefit analysis (CBA) modeling techniques were used for the assessment of the impact of land use change scenarios on wildlife habitat as biodiversity surrogates. The modeling was carried out on time-series land cover data from 1972 to 2009 for the Liverpool Range of New South Wales (NSW). The model estimated the future condition of vegetation in each and every grid-cell in the region as a function of current condition, existing land cover, and the threatening processes. The results indicated a continuous pattern of clearing in the region, while the habitat conditions were mostly static throughout the study period. There was a decline in EHA after 1993, by 3%. Clearing was identified as the main cause of such decline during the change period.
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