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Abstract

Many species of parrots are threatened or endangered, and conservation efforts require information about the factors influencing their abundance and distribution. However, few reliable methods exist for obtaining this information. Because nearly all species of parrots are cavity nesters, abundance and distribution can be understood by modeling nest site selection behavior. The objective of this thesis is to develop new methods for understanding the factors affecting parrot nest site selection and spatial variation in nest density. I used existing point process models and developed a novel spatial distance sampling model to estimate spatial variation in nest density using data from a study of the Red-and-green Macaw (Ara chloropterus) in Fazenda Boa Vista, Brazil. Model results indicate that macaws selected nest sites on steep, south-facing slopes at intermediate to high elevations. These modeling tools are widely applicable and easily adaptable across taxa.

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