A habitat overlap analysis derived from Maxent for Tamarisk and the South-western Willow Flycatcher

York et al., 2011

A maximum entropy model used to determine the extent of dense tamarisk cover as well as the potential habitat available for SWFL within the project area. 2008 Landsat Thematic Mapper images and a digital elevation model were used as the input variables within the five USGS watershed units flowing into the northern arm of Lake Mead (encompassing the Virgin River). The study determined that tamarisk beetles would like impact available SWFL habitat within the study region in the short term, but could increase available habitat long-term if managed appropriately.

Modeling the Dynamic Habitat and Breeding Population of Southwestern Willow Flycatcher

Hatten, et al., 2010

A model developed utilizing 10 years of flycatcher territory data from Roosevelt Lake, AZ. The GIS model explained 79% of the variability in the flycatcher breeding population at Roosevelt Lake. The model determined a high correlation between reservoir levels and predicted habitat, suggesting that habitat can be created and managed for conservation purposes.

Using a Remote Sensing/GIS Model to Predict Southwestern Willow Flycatcher Breeding Habitat along the Rio Grande, New Mexico

Hatten et al., 2007

The first large-scale predictive model of its kind for SWFL habitat, this expands on the modeling techniques Hatten developed in 2004 to map potential habitat along a large section of the Upper-Middle Rio Grande.

Mapping and Monitoring Southwestern Willow Flycatcher Breeding Habitat in Arizona: A Remote Sensing Approach

Dockens and Paradzick (eds.), 2004

A detailed discussion of the development and testing of a model to predict southwestern willow flycatcher breeding habitat in Arizona, with discussion of the GIS-based model and a case study analysis using the model in Roosevelt Lake.

A Multiscaled Model of Southwestern Willow Flycatcher Breeding Habitat

Hatten and Paradzick, 2003

A GIS model of SWFL breeding habitat developed from riparian habitat data along portions of the San Pedro, Gila, and Salt Rivers, and Tonto Creek. The best model explained 54% of the variability in breeding-site occurrence and was used to map habitat in Arizona and examine changes in habitat abundance and quality over time.