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A spatial model of waterfowl nest site selection in grassland nesting cover

Abstract

Ducks Unlimited's (DU) mission statement is focused on providing for the annual lifecycle needs of migratory waterfowl. The largest impacts to the success and numbers of continental populations are determined by their activities on the breeding grounds. To model and therefore manage habitats and landscapes for ducks (Anas and Aythya spp.) it is necessary to understand several characteristics of their behavior. This research builds a model of nest site selection from nest probability based on remotely sensed data, presence data and minimum threshold theory. The methods used are applicable to other sensor platforms as well as other target species or phenomenon. Using data compression techniques, logistic regression, and spatial statistical functions (Ripley's k-function, a global k-function, and Multiple Response Permutation Procedure) we tested the observed point patterns and developed a point process model to predict nesting patterns. The application of this type of fine resolution database, validated by empirical data, will be more powerful than either classified remote sensing data or field level nest demographic data alone. In the largest of the five study sites, which was also the site with the greatest number of observations, the pattern of nests were significantly different from Poisson. The model developed to fit these data was tested using the other sites and the observed data on the other four sites were not shown to be significantly different from the model. The tests for spatial association showed some evidence negative association between Blue-winged Teal and Gadwall as well as between successful and unsuccessful nest. There is some evidence that a process of natural selection may exist and the future studies should be designed with this in mind. These data will be used as a baseline for future habitat manipulation and controlled experiments on the DU Goebel Ranch complex. The results of this and future studies will be used as the basis for DU strategic planning of habitat programs in the Missouri Coteau.

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forestry
ecology
remote sensing

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