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Reserve networks based on richness hotspots and representation vary with scaleAuthor(s): Susan A. Shriner; Kenneth R. Wilson; Curtis H. Flather
Source: Ecological Applications. 16(5): 1660-1673.
Publication Series: Scientific Journal (JRNL)
Station: Rocky Mountain Research Station
PDF: View PDF (314.55 KB)
DescriptionWhile the importance of spatial scale in ecology is well established, few studies have investigated the impact of data grain on conservation planning outcomes. In this study, we compared species richness hotspot and representation networks developed at five grain sizes. We used species distribution maps for mammals and birds developed by the Arizona and New Mexico Gap Analysis Programs (GAP) to produce 1-km2, 100-km2, 625-km2, 2500-km2, and 10 000-km2 grid cell resolution distribution maps. We used these distribution maps to generate species richness and hotspot (95th quantile) maps for each taxon in each state. Species composition information at each grain size was used to develop two types of representation networks using the reserve selection software MARXAN. Reserve selection analyses were restricted to Arizona birds due to considerable computation requirements. We used MARXAN to create best reserve networks based on the minimum area required to represent each species at least once and equal area networks based on irreplaceability values. We also measured the median area of each species’ distribution included in hotspot (mammals and birds of Arizona and New Mexico) and irreplaceability (Arizona birds) networks across all species.
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CitationShriner, Susan A.; Wilson, Kenneth R.; Flather, Curtis H. 2006. Reserve networks based on richness hotspots and representation vary with scale. Ecological Applications. 16(5): 1660-1673.
Keywordsbiodiversity, conservation planning, grain, hotspots, map resolution, MARXAN, representation, reserve selection, selection algorithms, spatial scale, species richness
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