title: Implications of spatial data variations for protected areas management: an example from East Africa.
abstract: Geographic information systems and remote sensing technologies have become an important tool for visualizing conservation management and developing solutions to problems associated with conservation. When multiple organizations separately develop spatial data representations of protected areas, implicit error arises due to variation between data sets. We used boundary data produced by three conservation organizations (International Union for the Conservation of Nature, World Resource Institute, and Uganda Wildlife Authority), for seven Ugandan parks, to study variation in the size represented and the location of boundaries. We found variation in the extent of overlapping total area encompassed by the three data sources, ranging from miniscule (0.4 %) differences to quite large ones (9.0 %). To underscore how protected area boundary discrepancies may have implications to protected area management, we used a landcover classification, defining crop, shrub, forest, savanna, and grassland. The total area in the different landcover classes varied most in smaller protected areas (those less than 329 km(2)), with forest and cropland area estimates varying up to 65 %. The discrepancies introduced by boundary errors could, in this hypothetical case, generate erroneous findings and could have a significant impact on conservation, such as local-scale management for encroachment and larger-scale assessments of deforestation.
authors.affiliation: Department of Natural Resources and the Environment, University of New Hampshire, 114 James Hall, 56 College Road, Durham, NH, 03824, USA, nick.dowhaniuk@unh.edu.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Dowhaniuk
authors.forename: Joel
authors.initials: J
authors.lastname: Hartter
authors.forename: Sadie J
authors.initials: SJ
authors.lastname: Ryan
mesh_terms: D003247:Conservation of Natural Resources; D040362:Geographic Information Systems; D058998:Remote Sensing Technology; D012107:Research Design; D014197:Trees; D014454:Uganda; D035501:Uncertainty