The Influence of Phosphorus on Periphyton Mats from the Everglades and Three Tropical Karstic Wetlands

The distinctive karstic, freshwater wetlands of the northern Caribbean and Central American region support the prolific growth of calcite-rich periphyton mats. Aside from the Everglades, very little research has been conducted in these karstic wetlands, which are increasingly threatened by eutrophication. This study sought to (i) test the hypothesis that water depth and periphyton total phosphorus (TP) content are both drivers of periphyton biomass in karstic wetland habitats in Belize, Mexico and Jamaica, (ii) provide a taxonomic inventory of the periphytic diatom species in these wetlands and (iii) examine the relationship between periphyton mat TP concentration and diatom assemblage at Everglades and Caribbean locations. ^ Periphyton biomass, nutrient and diatom assemblage data were generated from periphyton mat samples collected from shallow, marl-based wetlands in Belize, Mexico and Jamaica. These data were compared to a larger dataset collected from comparable sites within Everglades National Park. A diatom taxonomic inventory was conducted on the Caribbean samples and a combination of ordination and weighted-averaging modeling techniques were used to compare relationships between periphyton TP concentration, periphyton biomass and diatom assemblage composition among the locations. ^ Within the Everglades, periphyton biomass showed a negative correlation with water depth and mat TP, while periphyton mat percent organic content was positively correlated with these two variables. These patterns were also exhibited within the Belize, Mexico and Jamaica locations, suggesting that water depth and periphyton TP content are both drivers of periphyton biomass in karstic wetland systems within the northern Caribbean region. ^ A total of 146 diatom species representing 39 genera were recorded from the three Caribbean locations, including a distinct core group of species that may be endemic to this habitat type. Weighted averaging models were produced that effectively predicted mat TP concentration from diatom assemblages for both Everglades (R2=0.56) and Caribbean (R2=0.85) locations. There were, however, significant differences among Everglades and Caribbean locations with respect to species TP optima and indicator species. This suggests that although diatoms are effective indicators of water quality in these wetlands, differences in species response to water quality changes can reduce the predictive power of these indices when applied across systems. ^

Examining Technology Adoption and Management Perception of Inventory Management Systems: The Case of Aruba Restaurants

The purpose of this paper is to explore the use of automated inventory management systems (IMS) and identify the stage of technology adoption for restaurants in Aruba. A case study analysis involving twelve members of the Aruba Gastronomic Association was conducted using a qualitative research design to gather information on approaches currently used as well as the reasons and perceptions managers/owners have for using or not using automated systems in their facilities. This is the first study conducted using the Aruba restaurant market. Therefore, the application of two technology adoption models was used to integrate critical factors relevant to the study. Major findings indicated the use of an automated IMS in restaurants is limited, thus underscoring the lack of adoption of technology in this area. The results also indicated that two major reasons that restaurants are not adopting IMS technology are budgetary constraints and service support. This study is imperative for two reasons: (1) the results of this study can be used as a comparison for future IMS adoption, not only for Aruba’s restaurant industry but also for other Caribbean destinations and the U.S., (2) this study also provides insight into the additional training and support help needed in hospitality technology services.

The relationship of managers' self -reported leadership practices and their spirituality

The role of spirituality in leadership in business and other organizations has gained growing recognition. The purpose of this study was to explore the relationship between spirituality and nine selected transformational leadership practices. Community leaders (N = 138) in business, education, and other professions who were graduates of a 10-week leadership program, Leadership Fort Lauderdale, from 1994 to 2004 completed the Spirituality Assessment Scale (SAS), the Leadership Practices Inventory (LPI), and four transformational leadership items of the Multifactor Leadership Questionnaire (MLQ). ^ The predictor variables were participants' scores on the LPI and MLQ. The criterion variable was their score on the SAS. Stepwise multiple regression analysis was used to test the hypothesis: Is there a combination of nine selected transformational leadership practices that would account for a significant portion of the variance of each of two spirituality measures? The Definitive and Correlated dimensions and Total spirituality score of the SAS were used in the analysis. ^ Results showed that two of the LPI leadership practices were significantly related to spirituality. The variable Inspiring a Shared Vision accounted for 10% of the variance of the SAS Definitive dimension. The variable Encouraging the Heart accounted for 30% of the variance of the Correlated dimension. For the Total spirituality score, two models were revealed. In the first model, Encouraging the Heart accounted for 28% of the variance of the total spirituality score. In the second model, Encouraging the Heart and Inspiring a Shared Vision together accounted for 31% of the total spirituality score. None of the transformational leadership practices from the MLQ were significantly related to spirituality. ^ The data partially support the hypothesis: two of the nine leadership variables did in combination correlate with leaders' spirituality. The results also support at least a partial relationship between spirituality and certain transformational leadership practices among leaders in various spheres, such as education, business, and other professions. ^

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 (E LUMO) 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) E LUMO 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.

Diatom-based Models for Inferring Hydrology and Periphyton Abundance in a Subtropical Karstic Wetland: Implications for Ecosystem-Scale Bioassessment

We developed diatom-based prediction models of hydrology and periphyton abundance to inform assessment tools for a hydrologically managed wetland. Because hydrology is an important driver of ecosystem change, hydrologic alterations by restoration efforts could modify biological responses, such as periphyton characteristics. In karstic wetlands, diatoms are particularly important components of mat-forming calcareous periphyton assemblages that both respond and contribute to the structural organization and function of the periphyton matrix. We examined the distribution of diatoms across the Florida Everglades landscape and found hydroperiod and periphyton biovolume were strongly correlated with assemblage composition. We present species optima and tolerances for hydroperiod and periphyton biovolume, for use in interpreting the directionality of change in these important variables. Predictions of these variables were mapped to visualize landscape-scale spatial patterns in a dominant driver of change in this ecosystem (hydroperiod) and an ecosystem-level response metric of hydrologic change (periphyton biovolume). Specific diatom assemblages inhabiting periphyton mats of differing abundance can be used to infer past conditions and inform management decisions based on how assemblages are changing. This study captures diatom responses to wide gradients of hydrology and periphyton characteristics to inform ecosystem-scale bioassessment efforts in a large wetland.

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.