Abstract
The southwestern willow flycatcher (SWFL; Empidonax traillii extimus) is an endangered songbird whose habitat has declined dramatically over the last century. Understanding habitat selection patterns and the ability to identify potential breeding areas for the SWFL is crucial to the management and conservation of this species. We developed a multiscaled model of SWFL breeding habitat with a Geographic Information System (GIS), survey data, GIS variables, and multiple logistic regressions. We obtained presence and absence survey data from a river-ine ecosystem and a reservoir delta in south-central Arizona, USA, in 1999. We extracted the GIS variables from satellite imagery and digital elevation models to characterize vegetation and floodplain within the project area. We used multiple logistic regressions within a cell-based (30 x 30 m) modeling environment to (1) determine associations between GIS variables and breeding-site occurrence at different spatial scales (0.09-72 ha), and (2) construct a predictive model. Our best model explained 54% of the variability in breeding-site occurrence with the following variables: vegetation density at the site (0.09 ha), proportion of dense vegetation and variability in vegetation density within a 4.5-ha neighborhood, and amount of floodplain or flat terrain within a 41-ha neighborhood. The density of breeding sites was highest in areas that the model predicted to be most suitable within the project area and at an external test site 200 km away. Conservation efforts must focus on protecting not only occupied patches, but also surrounding riparian forests and floodplain to ensure long-term viability of SWFL. We will use the multiscaled model to map SWFL breeding habitat in Arizona, prioritize future survey effort, and examine changes in habitat abundance and quality over time.
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