Modeling the dynamic habitat and breeding population of Southwestern Willow Flycatcher
Citation
Eben H Paxton, James R Hatten, and Mark K Sogge, Modeling the dynamic habitat and breeding population of Southwestern Willow Flycatcher: .
Summary
To aid in the management and conservation of Southwestern Willow Flycatcher (Empidonax traillii extimus, hereafter “Flycatcher�), we developed numerous models of flycatcher breeding habitat at Roosevelt Lake, AZ. For model development and testing, we compiled 10 years of flycatcher territory data that were obtained from intensive fieldwork between 1996 and 2005. We identified riparian vegetation annually in the project area from Landsat Thematic Mapper images, and extracted floodplain features from a digital elevation model. We created a novel class of temporal (i.e., multiyear) variables by characterizing the stability and variability in breeding habitat over a 6-year time interval. We used logistic regression to determine associations [...]
Summary
To aid in the management and conservation of Southwestern Willow Flycatcher (Empidonax traillii extimus, hereafter “Flycatcher�), we developed numerous models of flycatcher breeding habitat at Roosevelt Lake, AZ. For model development and testing, we compiled 10 years of flycatcher territory data that were obtained from intensive fieldwork between 1996 and 2005. We identified riparian vegetation annually in the project area from Landsat Thematic Mapper images, and extracted floodplain features from a digital elevation model. We created a novel class of temporal (i.e., multiyear) variables by characterizing the stability and variability in breeding habitat over a 6-year time interval. We used logistic regression to determine associations between environmental variables and flycatcher territory occurrence, and to test specific hypotheses. We mapped the probability of territory occurrence with a GIS and determined model accuracies with a classification table and a 10-year population database. Environmental features that were associated with breeding flycatchers included floodplain size, proximity to water, and the density, heterogeneity, age and stability of riparian vegetation. Our best model explained 79% of the variability in the flycatcher breeding population at Roosevelt Lake. The majority of predicted flycatcher habitat formed between 1996 and 2004 on an exposed lakebed not, vert, similar3 years after water levels receded during a prolonged drought. A high correlation between annual reservoir levels and predicted breeding habitat (r = −0.82) indicates that we can create and manage habitat for conservation purposes. Our predictive models quantify and assess the relative quality of flycatcher breeding habitat remotely, and can be used to evaluate the effectiveness of habitat restoration activities. Numerous techniques we developed can be used to characterize riparian vegetation and patch dynamics directly off of satellite imagery, thereby increasing its utility for conservation purposes.
Published in Ecological Modelling, volume 221, issue 13-14, on pages 12 - 12, in 2010.
