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Selection of scale is critical when investigating ecological processes on landscapes because different patterns emerge in spatial data at different scales. Landscape studies commonly identify a single scale, or spatial extent of data, for assessing broad-scale habitat characteristics, without regard for the sensitivity of spatial data to the scale at which they are measured. An incorrect selection of scale can lead to misleading or erroneous inferences about how animals are associated with coarse-grained habitat characteristics. We developed and compared three statistical models for predicting presence of selected bird species inhabiting a managed forest in South Carolina: a model based only on microhabitat characteristics, a model based only on landscape characteristics (summary statistics of forest age and type calculated at different spatial scales) derived from GIS data, and a model that combined microhabitat and landscape characteristics. In general, landscape models (Somer's D = 0.61 ± 0.16; mean ± ... |
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