Intraspecific relationships in Paracalanus quasimodo [Calinoideae] and Temora turbinata [Calinoideae] along the southeastern coast of the United States

Paracalanus quasimodo and Temora turbinata are two calanoid copepods prominent in the planktonic communities of the southeastern United States. Despite their prominence, the species and population level structure of these copepods is yet unexplored. The phylogeographic, temporal and phylogenetic structure of P. quasimodo and T. turbinata are examined in my study. Samples were collected from ten sites along the Gulf of Mexico and Florida peninsular coasts. Three sites were sampled quarterly for two years. Individuals were screened for unique ITS-1 sequences with denaturing gradient gel electrophoresis. Unique variants were sequenced at the nuclear ITS-1 and mitochondrial COI loci. Sampling sites were analyzed for pairwise community differences and for variances between geographic and temporal groupings. Genetic variants were analyzed for phylogenetic and coalescent topology. Paracalanus quasimodo is highly structured geographically with populations divided between the Gulf of Mexico, temperate Atlantic and subtropical Atlantic, in addition to isolation by distance. No significant differences were detected between the T. turbinata samples. Both P. quasimodo and T. turbinata are stable within sites over time and between sites within a sampling period, with two exceptions. The first was a pilot sample from Miami taken two years prior to the general sampling whose community showed significant differences from most of the other Miami samples. Paracalanus quasimodo had a positive correlation of Fst with time. The second was high temporal variability detected in the samples from Fort Pierce. Phylogenetically, both P. quasimodo and T. turbinata were in well supported, congeneric clades. Paracalanus quasimodo was not monophyletic, divided into two well-supported clades. Temora turbinata variants were in one clade with insignificant support for topology within the clade and very little intraspecific variation. Paracalanus quasimodo and T. turbinata populations show opposite trends. Paracalanus quasimodo occurs near shore and shows population structure mediated by hydrological features and distance, both geographic and temporal. The phylogeny shows two deeply divergent clades suggestive of cryptic speciation. In contrast, T. turbinata populations range further offshore and show little geographic or temporal structure. However, the low genetic variation detected in this region suggests a recent bottleneck event.

Intraspecific Relationships in Paracalanus quasimodo [Calinoideae] and Temora turbinata [Calinoideae] along the Southeastern Coast of the United States

Paracalanus quasimodo and Temora turbinata are two calanoid copepods prominent in the planktonic communities of the southeastern United States. Despite their prominence, the species and population level structure of these copepods is yet unexplored. The phylogeographic, temporal and phylogenetic structure of P. quasimodo and T. turbinata are examined in my study. Samples were collected from ten sites along the Gulf of Mexico and Florida peninsular coasts. Three sites were sampled quarterly for two years. Individuals were screened for unique ITS-1 sequences with denaturing gradient gel electrophoresis. Unique variants were sequenced at the nuclear ITS-1 and mitochondrial COI loci. Sampling sites were analyzed for pairwise community differences and for variances between geographic and temporal groupings. Genetic variants were analyzed for phylogenetic and coalescent topology. Paracalanus quasimodo is highly structured geographically with populations divided between the Gulf of Mexico, temperate Atlantic and subtropical Atlantic, in addition to isolation by distance. No significant differences were detected between the T. turbinata samples. Both P. quasimodo and T. turbinata are stable within sites over time and between sites within a sampling period, with two exceptions. The first was a pilot sample from Miami taken two years prior to the general sampling whose community showed significant differences from most of the other Miami samples. Paracalanus quasimodo had a positive correlation of Fst with time. The second was high temporal variability detected in the samples from Fort Pierce. Phylogenetically, both P. quasimodo and T. turbinata were in well supported, congeneric clades. Paracalanus quasimodo was not monophyletic, divided into two well-supported clades. Temora turbinata variants were in one clade with insignificant support for topology within the clade and very little intraspecific variation. Paracalanus quasimodo and T. turbinata populations show opposite trends. Paracalanus quasimodo occurs near shore and shows population structure mediated by hydrological features and distance, both geographic and temporal. The phylogeny shows two deeply divergent clades suggestive of cryptic speciation. In contrast, T. turbinata populations range further offshore and show little geographic or temporal structure. However, the low genetic variation detected in this region suggests a recent bottleneck event.

Temporal Population Genetic Structure of Eastern Mosquitofish in a Dynamic Aquatic Landscape

We analyzed the effect of periodic drying in the Florida Everglades on spatiotemporal population genetic structure of eastern mosquitofish (Gambusia holbrooki). Severe periodic drying events force individuals from disparate sources to mix in dry season relatively deep-water refuges. In 1996 (a wet year) and 1999 (a dry year), we sampled mosquitofish at 20 dry-season refuges distributed in 3 water management regions and characterized genetic variation for 10 allozyme and 3 microsatellite loci. In 1996, most of the ecosystem did not dry, whereas in 1999, many of our sampling locations were isolated by expanses of dried marsh surface. In 1996, most spatial genetic variation was attributed to heterogeneity within regions. In 1999, spatial genetic variation within regions was not significant. In both years, a small but significant amount of variation (less than 1% of the total variation) was partitioned among regions. Variance was consistently greater than zero among long-hydroperiod sites within a region, but not among short-hydroperiod sites within a region, where hydroperiod was measured as time since last marsh surface dry-down forcing fishes into local refuges. In 1996, all sites were in Hardy–Weinberg equilibrium. In 1999, we observed fewer heterozygotes than expected for most loci and sites suggesting a Wahlund effect arising from fish leaving areas that dried and mixing in deep-water refuges.

Temporal analysis of land use and transportation investments with geographic information system

Land use and transportation interaction has been a research topic for several decades. There have been efforts to identify impacts of transportation on land use from several different perspectives. One focus has been the role of transportation improvements in encouraging new land developments or relocation of activities due to improved accessibility. The impacts studied have included property values and increased development. Another focus has been on the changes in travel behavior due to better mobility and accessibility. Most studies to date have been conducted in metropolitan level, thus unable to account for interactions spatially and temporally at smaller geographic scales. ^ In this study, a framework for studying the temporal interactions between transportation and land use was proposed and applied to three selected corridor areas in Miami-Dade County, Florida. The framework consists of two parts: one is developing of temporal data and the other is applying time series analysis to this temporal data to identify their dynamic interactions. Temporal GIS databases were constructed and used to compile building permit data and transportation improvement projects. Two types of time series analysis approaches were utilized: univariate models and multivariate models. Time series analysis is designed to describe the dynamic consequences of time series by developing models and forecasting the future of the system based on historical trends. Model estimation results from the selected corridors were then compared. ^ It was found that the time series models predicted residential development better than commercial development. It was also found that results from three study corridors varied in terms of the magnitude of impacts, length of lags, significance of the variables, and the model structure. Long-run effect or cumulated impact of transportation improvement on land developments was also measured with time series techniques. The study offered evidence that congestion negatively impacted development and transportation investments encouraged land development. ^

An indexing structure and application model for vehicles moving on road networks

Moving objects database systems are the most challenging sub-category among Spatio-Temporal database systems. A database system that updates in real-time the location information of GPS-equipped moving vehicles has to meet even stricter requirements. Currently existing data storage models and indexing mechanisms work well only when the number of moving objects in the system is relatively small. This dissertation research aimed at the real-time tracking and history retrieval of massive numbers of vehicles moving on road networks. A total solution has been provided for the real-time update of the vehicles' location and motion information, range queries on current and history data, and prediction of vehicles' movement in the near future. ^ To achieve these goals, a new approach called Segmented Time Associated to Partitioned Space (STAPS) was first proposed in this dissertation for building and manipulating the indexing structures for moving objects databases. ^ Applying the STAPS approach, an indexing structure of associating a time interval tree to each road segment was developed for real-time database systems of vehicles moving on road networks. The indexing structure uses affordable storage to support real-time data updates and efficient query processing. The data update and query processing performance it provides is consistent without restrictions such as a time window or assuming linear moving trajectories. ^ An application system design based on distributed system architecture with centralized organization was developed to maximally support the proposed data and indexing structures. The suggested system architecture is highly scalable and flexible. Finally, based on a real-world application model of vehicles moving in region-wide, main issues on the implementation of such a system were addressed. ^

Characterizing Internet worm spatial-temporal infection structures

Since the Morris worm was released in 1988, Internet worms continue to be one of top security threats. For example, the Conficker worm infected 9 to 15 million machines in early 2009 and shut down the service of some critical government and medical networks. Moreover, it constructed a massive peer-to-peer (P2P) botnet. Botnets are zombie networks controlled by attackers setting out coordinated attacks. In recent years, botnets have become the number one threat to the Internet. The objective of this research is to characterize spatial-temporal infection structures of Internet worms, and apply the observations to study P2P-based botnets formed by worm infection. First, we infer temporal characteristics of the Internet worm infection structure, i.e., the host infection time and the worm infection sequence, and thus pinpoint patient zero or initially infected hosts. Specifically, we apply statistical estimation techniques on Darknet observations. We show analytically and empirically that our proposed estimators can significantly improve the inference accuracy. Second, we reveal two key spatial characteristics of the Internet worm infection structure, i.e., the number of children and the generation of the underlying tree topology formed by worm infection. Specifically, we apply probabilistic modeling methods and a sequential growth model. We show analytically and empirically that the number of children has asymptotically a geometric distribution with parameter 0.5, and the generation follows closely a Poisson distribution. Finally, we evaluate bot detection strategies and effects of user defenses in P2P-based botnets formed by worm infection. Specifically, we apply the observations of the number of children and demonstrate analytically and empirically that targeted detection that focuses on the nodes with the largest number of children is an efficient way to expose bots. However, we also point out that future botnets may self-stop scanning to weaken targeted detection, without greatly slowing down the speed of worm infection. We then extend the worm spatial infection structure and show empirically that user defenses, e.g. , patching or cleaning, can significantly mitigate the robustness and the effectiveness of P2P-based botnets. To counterattack, we evaluate a simple measure by future botnets that enhances topology robustness through worm re-infection.

Experimental nutrient enrichment causes complex changes in seagrass, microalgae, and macroalgae community structure in Florida Bay

We evaluated how changes in nutrient supply altered the composition of epiphytic and benthic microalgal communities in a Thalassia testudinum (turtle grass) bed in Florida Bay. We established study plots at four sites in the bay and added nitrogen (N) and phosphorus (P) to the sediments in a factorial design. After 18, 24, and 30 months of fertilization we measured the pigment concentrations in the epiphytic and benthic microalgal assemblages using high performance liquid chromatography. Overall, the epiphytic assemblage was P-limited in the eastern portion of the bay, but each phototrophic group displayed unique spatial and temporal responses to N and P addition. Epiphytic chlorophyll a, an indicator of total microalgal load, and epiphytic fucoxanthin, an indicator of diatoms, increased in response to P addition at one eastern bay site, decreased at another eastern bay site, and were not affected by P or N addition at two western bay sites. Epiphytic zeaxanthin, an indicator of the cyanobacteria/coralline red algae complex, and epiphytic chlorophyll b, an indicator of green algae, generally increased in response to P addition at both eastern bay sites but did not respond to P or N addition in the western bay. Benthic chlorophyll a, chlorophyll b, fucoxanthin, and zeaxanthin showed complex responses to N and P addition in the eastern bay, suggesting that the benthic assemblage is limited by both N and P. Benthic assemblages in the western bay were variable over time and displayed few responses to N or P addition. The contrasting nutrient limitation patterns between the epiphytic and benthic communities in the eastern bay suggest that altering nutrient input to the bay, as might occur during Everglades restoration, can shift microalgal community structure, which may subsequently alter food web support for upper trophic levels.

Spatio-temporal patterns and nutrient status of macroalgae in a heavily managed region of Biscayne Bay, Florida, USA

The coastal bays of South Florida are located downstream of the Florida Everglades, where a comprehensive restoration plan will strongly impact the hydrology of the region. Submerged aquatic vegetation communities are common components of benthic habitats of Biscayne Bay, and will be directly affected by changes in water quality. This study explores community structure, spatio-temporal dynamics, and tissue nutrient content of macroalgae to detect and describe relationships with water quality. The macroalgal community responded to strong variability in salinity; three distinctive macroalgal assemblages were correlated with salinity as follows: (1) low-salinity, dominated by Chara hornemannii and a mix of filamentous algae; (2) brackish, dominated by Penicillus capitatus, Batophora oerstedii, and Acetabularia schenckii; and (3) marine, dominated by Halimeda incrassata and Anadyomene stellata. Tissue-nutrient content was variable in space and time but tissues at all sites had high nitrogen and N:P values, demonstrating high nitrogen availability and phosphorus limitation in this region. This study clearly shows that distinct macroalgal assemblages are related to specific water quality conditions, and that macroalgal assemblages can be used as community-level indicators within an adaptive management framework to evaluate performance and restoration impacts in Biscayne Bay and other regions where both freshwater and nutrient inputs are modified by water management decisions.

Nutrient effects on seagrass epiphyte community structure in Florida Bay

A field experiment was employed in Florida Bay investigating the response of seagrass epiphyte communities to nitrogen (N) and phosphorus (P) additions. While most of the variability in epiphyte community structure was related to uncontrolled temporal and spatial environmental heterogeneity, P additions increased the relative abundance of the red algae–cyanobacterial complex and green algae, with a concomitant decrease in diatoms. When N was added along with P, the observed changes to the diatoms and the red algae–cyanobacterial complex were in the same direction as P-only treatments, but the responses were decreased in magnitude. Within the diatom community, species relative abundances, species richness, and diversity responded weakly to nutrient addition. P additions produced changes in diatom community structure that were limited to summer and were stronger in eastern Florida Bay than in the western bay. These changes were consistent with well-established temporal and spatial patterns of P limitation. Despite the significant change in community structure resulting from P addition, diatom communities from the same site and time, regardless of nutrient treatment, remained more similar to one another than to the diatom communities subject to identical nutrient treatments from different sites and times. Overall, epiphyte communities exhibited responses to P addition that were most evident at the division level.

Temporal and Spatial Variability of Mesozooplankton in a Shallow Sub-Tropical Bay: Influence of Top-Down Control

Quantifying the relationship between mesozooplankton and water quality parameters identifies the factors that structure the mesozooplankton community and can be used to generate hypotheses regarding the mechanisms that control the mesozooplankton population and potentially the trophic network. To investigate this relationship, mesozooplankton and water quality data were collected in Florida Bay from 1994 to 2004. Three key characteristics were found in the mesozooplankton community structure: (1) there are significant differences between the four sub-regions of Florida Bay; (2) there is a break in May of 1997 with significant differences before and after this date; and (3) there is a positive correlation between mesozooplankton abundance and salinity. The latter two characteristics are closely correlated with predator abundance, indicating the importance of top-down control. Hypersaline periods appear to provide a refuge from predators, allowing mesozooplankton to increase in abundance despite the increased physiological stress.

Effects of an extreme temperature event on the behavior and age structure of an estuarine top predator, Carcharhinus leucas

The frequency of extreme environmental events is predicted to increase in the future. Understanding the short- and long-term impacts of these extreme events on large-bodied predators will provide insight into the spatial and temporal scales at which acute environmental disturbances in top-down processes may persist within and across ecosystems. Here, we use long-term studies of movements and age structure of an estuarine top predator—juvenile bull sharks Carcharhinus leucas—to identify the effects of an extreme ‘cold snap’ from 2 to 13 January 2010 over short (weeks) to intermediate (months) time scales. Juvenile bull sharks are typically year-round residents of the Shark River Estuary until they reach 3 to 5 yr of age. However, acoustic telemetry revealed that almost all sharks either permanently left the system or died during the cold snap. For 116 d after the cold snap, no sharks were detected in the system with telemetry or captured during longline sampling. Once sharks returned, both the size structure and abundance of the individuals present in the nursery had changed considerably. During 2010, individual longlines were 70% less likely to capture any sharks, and catch rates on successful longlines were 40% lower than during 2006−2009. Also, all sharks caught after the cold snap were young-of-the-year or neonates, suggesting that the majority of sharks in the estuary were new recruits and several cohorts had been largely lost from the nursery. The longer-term impacts of this change in bull shark abundance to the trophic dynamics of the estuary and the importance of episodic disturbances to bull shark population dynamics will require continued monitoring, but are of considerable interest because of the ecological roles of bull sharks within coastal estuaries and oceans.

An Indexing Structure and Application Model for Vehicles Moving on Road Networks

Moving objects database systems are the most challenging sub-category among Spatio-Temporal database systems. A database system that updates in real-time the location information of GPS-equipped moving vehicles has to meet even stricter requirements. Currently existing data storage models and indexing mechanisms work well only when the number of moving objects in the system is relatively small. This dissertation research aimed at the real-time tracking and history retrieval of massive numbers of vehicles moving on road networks. A total solution has been provided for the real-time update of the vehicles’ location and motion information, range queries on current and history data, and prediction of vehicles’ movement in the near future. To achieve these goals, a new approach called Segmented Time Associated to Partitioned Space (STAPS) was first proposed in this dissertation for building and manipulating the indexing structures for moving objects databases. Applying the STAPS approach, an indexing structure of associating a time interval tree to each road segment was developed for real-time database systems of vehicles moving on road networks. The indexing structure uses affordable storage to support real-time data updates and efficient query processing. The data update and query processing performance it provides is consistent without restrictions such as a time window or assuming linear moving trajectories. An application system design based on distributed system architecture with centralized organization was developed to maximally support the proposed data and indexing structures. The suggested system architecture is highly scalable and flexible. Finally, based on a real-world application model of vehicles moving in region-wide, main issues on the implementation of such a system were addressed.

Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis

Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.