This study focused on the effectiveness of integrating traditional plant community analyses with landscape ecological analyses based on remotely sensed data. A temporal analysis of plant community diversity was conducted for major plant communities of the Ray Roberts Lake area using transect monitoring data collected between 1987 and 1997. Landscape analyses were performed with FRAGSTATS*ARC using classified SPOT satellite imagery for 1987 and 1997. Although the methodology developed in this work was exploratory, it was found that characterizing the dynamics of major plant communities in the study area produced a more effective and insightful analysis of Ray Roberts Lake area landscape dynamics.

On-road remote sensing has the ability to operate in real-time, and under real world conditions, making it an ideal candidate for detecting gross polluters on major freeways and thoroughfares. In this study, remote sensing was employed to detect carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxide (NO). On-road remote sensing data taken from measurements performed in six states, (Arizona, California, Colorado, Illinois, Texas, and Utah) were cleaned and analyzed. Data mining and exploration were first undertaken in order to search for relationships among variables such as make, year, engine type, vehicle weight, and location. Descriptive statistics were obtained for the three pollutants of interest. The data were found to have non-normal distributions. Applied transformations were ineffective, and nonparametric tests were applied. Due to the extremely large sample size of the dataset (508,617 records), nonparametric tests resulted in "p" values that demonstrated "significance." The general linear model was selected due to its ability to handle data with non-normal distributions. The general linear model was run on each pollutant with output producing descriptive statistics, profile plots, between-subjects effects, and estimated marginal means. Due to insufficient data within certain cells, results were not obtained for gross vehicle weight and engine type. The "year" …

Growth of Corbicula fluminea was monitored in the laboratory. Three experiments were conducted. Experiment I utilized three substrates and one food type. Experiment II utilized three substrates and two food types. Experiments I and II were conducted to determine if substrate type or food type effected growth. Experiment III used no substrates, one food type and was conducted to determine growth response to different types of water. Clams were maintained in three substrates: sand, gravel and clay. Clams were also maintained without substrate. Growth was monitored by measuring shell length (mm) and recording the weight (mg) of clams over a period of thirty days. At the end of the test period data were evaluated for normality and homogeneity.