Estimation of average annual daily traffic (AADT) using geographically weighted regression (GWR) method and geographic information system (GIS)

Annual average daily traffic (AADT) is important information for many transportation planning, design, operation, and maintenance activities, as well as for the allocation of highway funds. Many studies have attempted AADT estimation using factor approach, regression analysis, time series, and artificial neural networks. However, these methods are unable to account for spatially variable influence of independent variables on the dependent variable even though it is well known that to many transportation problems, including AADT estimation, spatial context is important. ^ In this study, applications of geographically weighted regression (GWR) methods to estimating AADT were investigated. The GWR based methods considered the influence of correlations among the variables over space and the spatially non-stationarity of the variables. A GWR model allows different relationships between the dependent and independent variables to exist at different points in space. In other words, model parameters vary from location to location and the locally linear regression parameters at a point are affected more by observations near that point than observations further away. ^ The study area was Broward County, Florida. Broward County lies on the Atlantic coast between Palm Beach and Miami-Dade counties. In this study, a total of 67 variables were considered as potential AADT predictors, and six variables (lanes, speed, regional accessibility, direct access, density of roadway length, and density of seasonal household) were selected to develop the models. ^ To investigate the predictive powers of various AADT predictors over the space, the statistics including local r-square, local parameter estimates, and local errors were examined and mapped. The local variations in relationships among parameters were investigated, measured, and mapped to assess the usefulness of GWR methods. ^ The results indicated that the GWR models were able to better explain the variation in the data and to predict AADT with smaller errors than the ordinary linear regression models for the same dataset. Additionally, GWR was able to model the spatial non-stationarity in the data, i.e., the spatially varying relationship between AADT and predictors, which cannot be modeled in ordinary linear regression. ^

Evaluating the external validity of comorbid disorders in youth using rating scales and behavior observations

To evaluate the theoretical underpinnings of current categorical approaches to classify childhood psychopathological conditions, this dissertation examined whether children with a single diagnosis of an anxiety disorder (ANX only) and children with an anxiety diagnosis comorbid with other diagnoses (i.e., anxiety + anxiety disorder [ANX + ANX], anxiety + depressive disorder [ANX + DEP], and anxiety + disruptive disorder [ANX + EXT]) could be differentiated using external validation criteria of clinical phenomenology (i.e., levels of anxiety, depression, and internalizing, externalizing and total behavior problems). This study further examined whether the four groups could be differentiated in terms of their interaction patterns with their parents and peers, respectively. The sample consisted of 129 youth and their parents who presented to the Child Anxiety and Phobia Program (CAPP) housed within the Child and Family Psychosocial Research Center at Florida International University, Miami. Youth were between the ages of 8 and 14 years old. A battery of questionnaires was used to assess participants' clinical presentation in terms of levels of anxiety, depression, and internalizing and externalizing symptoms. Family and peer interaction were evaluated through rating scales and through behavior observation tasks. Statistics based on the parameter estimates of the structured equation models indicated that all the comorbid groups were significantly different from the pure anxiety disorder group when it came to depression indices of clinical phenomenology. Further, significant differences appeared mainly in terms of the ANX + DEP comorbid group relative to the other comorbid groups. In terms of Parent-child interaction the ANX + EXT and the ANX + DEP comorbid groups were differentiated from the pure anxiety disorder and ANX + ANX comorbid group when it came to the appraisal of the parent/child relationship by the parent, and the acceptance subscale according to the mother report. In terms of peer-child interaction the ANX + EXT and the ANX + DEP comorbid groups were statistically significantly different from the pure anxiety disorder only when it came to the positive interactions and the social skills as rated by mother. Limitations and future research recommendations are discussed.

Slow Isotope Turnover Rates and Low Discrimination Values in the American Alligator: Implications for Interpretation of Ectotherm Stable Isotope Data

Stable isotope analysis has become a standard ecological tool for elucidating feeding relationships of organisms and determining food web structure and connectivity. There remain important questions concerning rates at which stable isotope values are incorporated into tissues (turnover rates) and the change in isotope value between a tissue and a food source (discrimination values). These gaps in our understanding necessitate experimental studies to adequately interpret field data. Tissue turnover rates and discrimination values vary among species and have been investigated in a broad array of taxa. However, little attention has been paid to ectothermic top predators in this regard. We quantified the turnover rates and discrimination values for three tissues (scutes, red blood cells, and plasma) in American alligators (Alligator mississippiensis). Plasma turned over faster than scutes or red blood cells, but turnover rates of all three tissues were very slow in comparison to those in endothermic species. Alligator δ15N discrimination values were surprisingly low in comparison to those of other top predators and varied between experimental and control alligators. The variability of δ15N discrimination values highlights the difficulties in using δ15N to assign absolute and possibly even relative trophic levels in field studies. Our results suggest that interpreting stable isotope data based on parameter estimates from other species can be problematic and that large ectothermic tetrapod tissues may be characterized by unique stable isotope dynamics relative to species occupying lower trophic levels and endothermic tetrapods.