The Role of the FIU Nature Preserve in Promoting Physical Activity

The FIU Nature Preserve was established over thirty-five years ago as an environmental educational center where visitors could experience and learn about local south Florida ecosystems and organisms. This 16-acre facility in the heart of the MMC campus has recently become a popular outdoor fitness destination since the inauguration of a jogging path during Fall 2013. This study set out to quantify how many people visit the FIU Nature Preserve annually, who they are, and what they are doing there. It is also assessing the effect of the FIU Nature Preserve on the overall health of the university community since studies have found that physical activity and contact with nature are positively associated with good health. A pilot was completed during Fall 2014, and the study is on track to finish March 22, 2015. To measure current visitation, two types of surveys were done on seven days across seven weeks during the spring of 2015, visitation counts and in-person surveys. By understanding the reasons and ways people discover and embark on regular use of natural areas, land managers and policy makers can make more informed decisions. As human population and development continue to grow, new ways to integrate natural areas into our urban environment and our lifestyles must be found. In this way, natural resource conservation could be championed as a way for communities to promote physical activity and good health beyond simply using their intrinsic value.

Chlorine Contribution to Quantitative Structure and Activity Relationship Models of Disinfection By-Products' Quantum Chemical Descriptors and Toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: 1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (ELUMO) via QSAR modelling and analysis; 2) to validate the models by using internal and external cross-validation techniques; 3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: 1) Linear or Multi-linear Regression (MLR); 2) Partial Least Squares (PLS); and 3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: 1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; 2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; 3) ELUMO are shown to correlate highly with the NCl for several classes of DBPs; and 4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

Spatial and Temporal Patterns in the Distribution, Behavior, and Activity of Fishes in Canals of the Everglades

Landscape characteristics, disturbances, and temporal variability influence predator-prey relationships, but are often overlooked in experimental studies. In the Everglades, seasonal disturbances force the spatial overlap of predators and prey, potentially increasing predation risk for prey. This study examined seasonal and diel patterns of fish use of canals and assessed predation risk for small fishes using an encounter rate model. I deployed an imaging sonar in Everglades canals to quantify density and swimming speeds of fishes, and detect anti-predator behaviors by small fishes. Generally, seasonal declines of marsh water-levels increased the density of large fishes in canals. Densities of small and large fishes were positively correlated and, as small-fish density increased, schooling frequency also increased. At night, schools disbanded and small fishes were observed congregating along the canal edge. The encounter rate model predicted highest predator-prey encounters during the day, but access to cover may reduce predation risk for small fishes.