Browsing by Subject "logistic regression"
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Item Habitat relationships of seven breeding bird species in the Leon River Watershed investigated at local scales(Texas A&M University, 2005-02-17) Juarez Berrios, Edwin AlfredoOver the past 100?150 years Texas rangelands have dramatically changed from native open savannahs to dense woodlands. On the Edwards plateau, a major management concern is the increasing encroachment of Ashe juniper (Juniperus ashei). Preceding an anticipated brush management program, I investigated the presence, co-occurrence, and habitat relationships of 7 breeding bird species in the Leon River Watershed in central Texas, USA: black-capped vireo (Vireo atricapillus), golden-cheeked warbler (Dendroica chrysoparia), northern bobwhite (Colinus virginianus), white-eyed vireo (Vireo griseus), Bell?s vireo (Vireo bellii), painted bunting (Passerina ciris), and brown-headed cowbird (Molothrus ater). Vegetation characteristics were compared between sites occupied by each species and unoccupied sites using univariate analysis. Models for predicting species site occupancy were developed (using logistic regression) based on habitat characteristics correlated with the presence of each species. Two species of special concern, the endangered black-capped vireo and golden-cheeked warbler occupied 5.6% of sites and 13.8% of sites respectively, while the brood parasite brown-headed cowbird was the most widespread, occupying 86.8% of sites. Species co-occurrence patterns revealed significant associations between the golden-cheeked warbler and each of 5 other species. For most species, variables included in habitat models could be explained by knowledge of species known habitat associations. For example, the black-capped vireo was positively associated with increasing low-growing (<1.5 m) hardwood cover and with Low Stony Hill ecological sites. The golden-cheeked warbler was positively associated with increasing density of larger juniper trees, increasing variability in vertical vegetation structure, and decreasing midstory canopy of deciduous nonoaks (e.g., cedar elm [Ulmus crasifolia]). It also preferred Low Stony Hill and Steep Adobe ecological sites. Site occupancy seemed to be driven by variables that describe overall vegetation structure. In particular, cover of low-growing non-juniper vegetation and juniper tree density appeared to be important in determining site occupancy for several species. Although the models constructed were not very robust, resource managers can still benefit from such models because they provide a preliminary examination of important controlling variables. Managing rangelands to maintain or restore a mosaic of juniper patches and open shrublands are likely to help meet the habitat requirements of these bird communities.Item Logistic regression models for predicting trip reporting accuracy in GPS-enhanced household travel surveys(Texas A&M University, 2007-04-25) Forrest, Timothy LeeThis thesis presents a methodology for conducting logistic regression modeling of trip and household information obtained from household travel surveys and vehicle trip information obtained from global positioning systems (GPS) to better understand the trip underreporting that occurs. The methodology presented here builds on previous research by adding additional variables to the logistic regression model that might be significant in contributing to underreporting, specifically, trip purpose. Understanding the trip purpose is crucial in transportation planning because many of the transportation models used today are based on the number of trips in a given area by the purpose of a trip. The methodology used here was applied to two study areas in Texas, Laredo and Tyler-Longview. In these two study areas, household travel survey data and GPS-based vehicle tracking data was collected over a 24-hour period for 254 households and 388 vehicles. From these 254 households, a total of 2,795 trips were made, averaging 11.0 trips per household. By comparing the trips reported in the household travel survey with those recorded by the GPS unit, trips not reported in the household travel survey were identified. Logistic regression was shown to be effective in determining which household- and trip-related variables significantly contributed to the likelihood of a trip being reported. Although different variables were identified as significant in each of the models tested, one variable was found to be significant in all of them - trip purpose. It was also found that the household residence type and the use of household vehicles for commercial purposes did not significantly affect reporting rates in any of the models tested. The results shown here support the need for modeling trips by trip purpose, but also indicate that, from urban area to urban area, there are different factors contributing to the level of underreporting that occurs. An analysis of additional significant variables in each urban area found combinations that yielded trip reporting rates of 0%. Similar to the results of Zmud and Wolf (2003), trip duration and the number of vehicles available were also found to be significant in a full model encompassing both study areas.Item Nesting ecology of dickcissels on reclaimed surface-mined lands in Freestone County, Texas(Texas A&M University, 2005-02-17) Dixon, Thomas PingulSurface mining and subsequent reclamation often results in the establishment of large areas of grassland that can benefit wildlife. Grasslands have declined substantially over the last 150 years, resulting in declines of many grassland birds. The dickcissel (Spiza americana), a neotropical migrant, is one such bird whose numbers have declined in the last 30 years due to habitat loss, increased nest predation and parasitism, and over harvest (lethally controlled as an agricultural pest on its wintering range in Central and South America). Reclaimed surface-mined lands have been documented to provide important breeding habitat for dickcissels in the United States, emphasizing the importance of reclamation efforts. Objectives were to understand specific aspects of dickcissel nesting ecology (i.e., nest-site selection, nest success, and nest parasitism, and identification of nest predators) on 2 spatial scales on TXU Energy?s Big Brown Mine, near Fairfield, Texas, and to subsequently provide TXU Energy with recommendations to improve reclaimed areas as breeding habitat for dickcissels. I examined the influence of nest-site vegetation characteristics and the effects of field-level spatial factors on dickcissel nesting ecology on 2 sites reclaimed as wildlife habitat. Additionally, I developed a novel technique to identify predators at active nests during the 2003 field season. During 2002?2003, 119 nests were monitored. On smaller spatial scales, dickcissels were likely to select nest-sites with low vegetation, high densities of bunchgrasses and tall forbs, and areas with higher clover content. Probability of nest success increased with nest heights and vegetation heights above the nest, characteristics associated with woody nesting substrates. Woody nesting substrates were selected and bunchgrasses were avoided. Oak (Quercus spp.) saplings remained an important nesting substrate throughout the breeding season. On a larger scale, nest-site selection was likely to occur farther from wooded riparian areas and closer to recently-reclaimed areas. Nest parasitism was likely to occur near roads and wooded riparian areas. Results suggest reclaimed areas could be improved by planting more bunchgrasses, tall forbs (e.g., curly-cup gumweed [Grindelia squarrosa] and sunflower [Helianthus spp.]), clover (Trifolium spp.), and oaks (a preferred nesting substrate associated with higher survival rates). Larger-scale analysis suggests that larger tracts of wildlife areas should be created with wooded riparian areas comprising a minimal portion of a field?s edge.Item Statistical Relationships of the Tropical Rainfall Measurement Mission (TRMM) Precipitation and Large-scale Flow(2010-07-14) Borg, KyleThe relationship between precipitation and large-flow is important to understand and characterize in the climate system. We examine statistical relationships between the Tropical Rainfall Measurement Mission (TRMM) 3B42 gridded precipitation and large-scale ow variables in the Tropics for 2000{2007. These variables include NCEP/NCAR Re-analysis sea surface temperatures (SSTs), vertical temperature pro files, omega, and moist static energy, as well as Atmospheric Infrared Sounder (AIRS) vertical temperatures and QuikSCAT surface divergence. We perform correlation analysis, empirical orthogonal function analysis, and logistic regression analysis on monthly, pentad, daily and near-instantaneous time scales. Logistic regression analysis is able to incorporate the non-linear nature of precipitation in the relation- ship. Flow variables are interpolated to the 0.25 degrees TRMM 3B42 grid and examined separately for each month to o set the effects of the seasonal cycle. January correlations of NCEP/NCAR Re-analysis SSTs and TRMM 3B42 precipitation have a coherent area of positive correlations in the Western and Central Tropical Pacific on all time scales. These areas correspond with the South Pacific Convergence Zone (SPCZ) and the Inter Tropical Convergence Zone (ITCZ). 500mb omega is negatively correlated with TRMM 3B42 precipitation across the Tropics on all time scales. QuikSCAT divergence correlations with precipitation have a band of weak and noisy correlations along the ITCZ on monthly time scales in January. Moist static energy, calculated from NCEP/NCAR Re-analysis has a large area of negative correlations with precipitation in the Central Tropical Pacific on all four time scales. The first few Empirical Orthogonal Functions (EOFs) of vertical temperature profiles in the Tropical Pacific have similar structure on monthly, pentad, and daily timescales. Logistic regression fit coefficients are large for SST and precipitation in four regions located across the Tropical Pacific. These areas show clear thresholded behavior. Logistic regression results for other variables and precipitation are less clear. The results from SST and precipitation logistic regression analysis indicate the potential usefulness of logistic regression as a non-linear statistic relating precipitation and certain ow variables.