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Herr, A.M. 1992. Assessing spatial patterns of greater sandhill crane nesting habitat using GIS and remote sensing. M.S. Thesis, University of Minnesota. 34 pp.


The goal of this research was to develop a descriptive GIS model to identify potential nesting habitat of greater sandhill cranes (Grus canadensis tabida) in northwestern Minnesota. Three objectives of the project were: (1) to produce necessary data layers for the model, including a vegetation map classified from Landsat Thematic Mapper data, (2) to characterize 22 known nest sites within an area used to develop the model using a raster-based GIS, and (3) to verify the applicability of the model to known locations of ten additional nest sites within a test area.

The modeling approach involved five fundamental steps: generating data layers, describing nest sites, testing for discrepancies between observed and expected distributions of nest sites, generating the model, and assessing the model. Using the vegetation map derived from the satellite classification, the study area was divided into potentially suitable and unsuitable nesting vegetation. Six additional habitat variables associated with 22 nest sites were measured with a raster GIS. These variables were distances to nearest paved highway, light duty road, unimproved road, building, and agricultural field, and width of undisturbed buffer. Each of the six habitat variables was divided into three or four zones of influence which represented different levels of suitability for nesting chances. Chi square analyses were conducted to quantify the importance of each habitat feature. Based on these analyses, potential nesting vegetation was categorized as optimal, sub-optimal, marginal, or unsuitable habitat for nesting. The model was projected onto a test area to assess the applicability of the model to known locations of ten additional nest sites.

The model indicated that some pairs nested in sub-optimal and marginal areas despite the apparent availability of optimal habitat. The absence of nesting pairs in optimal habitat may be accounted for by conditions and assumptions inherent in the data and modeling approach, unanswered questions concerning behavior of nesting cranes, uncertainty that all nest sites in the study area were known, and the inability to model or detect certain landscape features and local parameters. A fundamental outcome derived from the nesting habitat model was an understanding of the assumptions and limitations that are inherent in such modeling approaches.

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