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Landscape patterns as habitat predictors: Building and testing models for cavity-nesting birds in the Uinta Mountains of Utah, USA

Landscape Ecology

By:
and
DOI: 10.1023/A:1020219914926

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Abstract

The ability to predict species occurrences quickly is often crucial for managers and conservation biologists with limited time and funds. We used measured associations with landscape patterns to build accurate predictive habitat models that were quickly and easily applied (i.e., required no additional data collection in the field to make predictions). We used classification trees (a nonparametric alternative to discriminant function analysis, logistic regression, and other generalized linear models) to model nesting habitat of red-naped sapsuckers (Sphyrapicus nuchalis), northern flickers (Colaptes auratus), tree swallows (Tachycineta bicolor), and mountain chickadees (Parus gambeli) in the Uinta Mountains of northeastern Utah, USA. We then tested the predictive capability of the models with independent data collected in the field the following year. The models built for the northern flicker, red-naped sapsucker, and tree swallow were relatively accurate (84%, 80%, and 75% nests correctly classified, respectively) compared to the models for the mountain chickadee (50% nests correctly classified). All four models were more selective than a null model that predicted habitat based solely on a gross association with aspen forests. We conclude that associations with landscape patterns can be used to build relatively accurate, easy to use, predictive models for some species. Our results stress, however, that both selecting the proper scale at which to assess landscape associations and empirically testing the models derived from those associations are crucial for building useful predictive models.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Landscape patterns as habitat predictors: Building and testing models for cavity-nesting birds in the Uinta Mountains of Utah, USA
Series title:
Landscape Ecology
DOI:
10.1023/A:1020219914926
Volume
17
Issue:
3
Year Published:
2002
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Landscape Ecology
First page:
233
Last page:
245
Number of Pages:
13