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. ^

The Influence of Servicescape and Local Food Attributes on Pleasure and Revisit Intention in an Upscale-Casual Dining Restaurant

The current study looks at the relationship between servicescape, emotional product involvement, perceived quality of local foods, the positive emotion of pleasure, and revisit intention in an upscale buffet style restaurant on a university campus in the Southeastern U.S. Test results show positive relationships between all of the constructs in the proposed conceptual model. The study also gives practitioners and academics insights into practices that can help to market the use of local foods through the restaurant environment in order to engage emotionally involved customers. This marketing can illicit pleasurable feelings and increase perceived product quality of local foods with the purpose of getting customers to revisit the restaurant. Suggestions for further research on the subject are proposed.

Mining the online social network data: Influence, summarization, and organization

Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

Mining the Online Social Network Data: Influence, Summarization, and Organization

Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

Influence of Soil Biogeochemical Properties on the Invasiveness of Old World Climbing Fern (Lygodium microphyllum)

The state of Florida has one of the most severe exotic species invasion problems in the United States, but little is known about their influence on soil biogeochemistry. My dissertation research includes a cross-continental field study in Australia, Florida, and greenhouse and growth chamber experiments, focused on the soil-plant interactions of one of the most problematic weeds introduced in south Florida, Lygodium microphyllum (Old World climbing fern). Analysis of field samples from the ferns introduced and their native range indicate that L microphyllum is highly dependent on arbuscular mycorrhizal fungi (AMF) for phosphorus uptake and biomass accumulation. Relationship with AMF is stronger in relatively dry conditions, which are commonly found in some Florida sites, compared to more common wet sites where the fern is found in its native Australia. In the field, L. microphyllum is found to thrive in a wide range of soil pH, texture, and nutrient conditions, with strongly acidic soils in Australia and slightly acidic soils in Florida. Soils with pH 5.5 - 6.5 provide the most optimal growth conditions for L. microphyllum, and the growth declines significantly at soil pH 8.0, indicating that further reduction could happen in more alkaline soils. Comparison of invaded and uninvaded soil characteristics demonstrates that L. microphyllum can change the belowground soil environment, with more conspicuous impact on nutrient-poor sandy soils, to its own benefit by enhancing the soil nutrient status. Additionally, the nitrogen concentration in the leaves, which has a significant influence in the relative growth rate and photosynthesis, was significantly higher in Florida plants compared to Australian plants. Given that L. microphyllum allocates up to 40% of the total biomass to rhizomes, which aid in rapid regeneration after burning, cutting or chemical spray, hence management techniques targeting the rhizomes look promising. Over all, my results reveal for the first time that soil pH, texture, and AMF are major factors facilitating the invasive success of L. mcirophyllum. Finally, herbicide treatments targeting rhizomes will most likely become the widely used technique to control invasiveness of L. microphyllum in the future. However, a complete understanding of the soil ecosystem is necessary before adding any chemicals to the soil to achieve a successful long-term invasive species management strategy.