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- Genre: Masters Thesis
Description
The Southwestern Willow Flycatcher (Empidonax traillii extimus) has been studied for over two decades and listed as endangered for most of that time. Though the flycatcher has been granted protected status since 1995, critical habitat designation for the flycatcher has not shared the same history. Critical habitat designation is essential for achieving the long-term goals defined in the flycatcher recovery plan where emphasis is on both the protection of this species and "the habitats supporting these flycatchers [that] must be protected from threats and loss" (U.S. Fish and Wildlife Service 2002). I used a long-term data set of habitat characteristics collected at three study areas along the Lower Colorado River to develop a method for quantifying habitat quality for flycatcher. The data set contained flycatcher nest observations (use) and habitat availability (random location) from 2003-2010 that I statistically analyzed for flycatcher selection preferences. Using both Pearson's Chi-square test and SPSS Principal Component Analysis (PCA) I determined that flycatchers were selecting 30 habitat traits significantly different among an initial list of 127 habitat characteristics. Using PCA, I calculated a weighted value of influence for each significant trait per study area and used those values to develop a habitat classification system to build predictive models for flycatcher habitat quality. I used ArcGIS® Model Builder to develop three habitat suitability models for each of the habitat types occurring in western riparian systems, native, mixed exotic and exotic dominated that are frequented by breeding flycatchers. I designed a fourth model, Topock Marsh, to test model accuracy on habitat quality for flycatchers using reserved accuracy assessment points of previous nest locations. The results of the fourth model accurately predicted a decline in habitat at Topock Marsh that was confirmed by SWCA survey reports released in 2011 and 2012 documenting a significant decline in flycatcher productivity in the Topock Marsh study area.
ContributorsChenevert-Steffler, Ann (Author) / Miller, William (Thesis advisor) / Bateman, Heather (Committee member) / Alford, Eddie (Committee member) / Arizona State University (Publisher)
Created2013
Description
Although many studies have identified environmental factors as primary drivers of bird richness and abundance, there is still uncertainty about the extent to which climate, topography and vegetation influence richness and abundance patterns seen in local extents of the northern Sonoran Desert. I investigated how bird richness and abundance differed between years and seasons and which environmental variables most influenced the patterns of richness and abundance in the Greater Phoenix Metropolitan Area.
I compiled a geodatabase of climate, bioclimatic (interactions between precipitation and temperature), vegetation, soil, and topographical variables that are known to influence both richness and abundance and used 15 years of bird point count survey data from urban and non-urban sites established by Central Arizona–Phoenix Long-Term Ecological Research project to test that relationship. I built generalized linear models (GLM) to elucidate the influence of each environmental variable on richness and abundance values taken from 47 sites. I used principal component analysis (PCA) to reduce 43 environmental variables to 9 synthetic factors influenced by measures of vegetation, climate, topography, and energy. I also used the PCA to identify uncorrelated raw variables and modeled bird richness and abundance with these uncorrelated environmental variables (EV) with GLM.
I found that bird richness and abundance were significantly different between seasons, but that richness and winter abundance were not significantly different across years. Bird richness was most influenced by soil characteristics and vegetation while abundance was most influenced by vegetation and climate. Models using EV as independent variables consistently outperformed those models using synthetically produced components from PCA. The results suggest that richness and abundance are both driven by climate and aspects of vegetation that may also be influenced by climate such as total annual precipitation and average temperature of the warmest quarter. Annual oscillations of bird richness and abundance throughout the urban Phoenix area seem to be strongly associated with climate and vegetation.
I compiled a geodatabase of climate, bioclimatic (interactions between precipitation and temperature), vegetation, soil, and topographical variables that are known to influence both richness and abundance and used 15 years of bird point count survey data from urban and non-urban sites established by Central Arizona–Phoenix Long-Term Ecological Research project to test that relationship. I built generalized linear models (GLM) to elucidate the influence of each environmental variable on richness and abundance values taken from 47 sites. I used principal component analysis (PCA) to reduce 43 environmental variables to 9 synthetic factors influenced by measures of vegetation, climate, topography, and energy. I also used the PCA to identify uncorrelated raw variables and modeled bird richness and abundance with these uncorrelated environmental variables (EV) with GLM.
I found that bird richness and abundance were significantly different between seasons, but that richness and winter abundance were not significantly different across years. Bird richness was most influenced by soil characteristics and vegetation while abundance was most influenced by vegetation and climate. Models using EV as independent variables consistently outperformed those models using synthetically produced components from PCA. The results suggest that richness and abundance are both driven by climate and aspects of vegetation that may also be influenced by climate such as total annual precipitation and average temperature of the warmest quarter. Annual oscillations of bird richness and abundance throughout the urban Phoenix area seem to be strongly associated with climate and vegetation.
ContributorsBoehme, Cameron (Author) / Albuquerque, Fabio Suzart (Thesis advisor) / Bateman, Heather L (Committee member) / Saul, Steven E (Committee member) / Arizona State University (Publisher)
Created2019