Effects of light quantity and quality on early seedling development in the red mangrove Rhizophora mangle L

Seedlings of the red mangrove, Rhizophora mangle L., were grown under light conditions differing in both photosynthetic photon flux density (PPFD) and spectral quality (red:far-red ratio, R:FR). During the first 8 mo of development, parameters of stem, leaf, and root growth were affected by PPFD. Significant responses to lowered R:FR, however, were limited to internode extension. The results are moderately indicative of a strategy to persist in shade, but illustrate the complexity of light responses and suggest that precise categorization as shade-tolerant or -intolerant may be unbefitting for this species at this particular stage of development.

Capacity-based cost modeling for light rail and bus rapid transit systems

Choosing between Light Rail Transit (LRT) and Bus Rapid Transit (BRT) systems is often controversial and not an easy task for transportation planners who are contemplating the upgrade of their public transportation services. These two transit systems provide comparable services for medium-sized cities from the suburban neighborhood to the Central Business District (CBD) and utilize similar right-of-way (ROW) categories. The research is aimed at developing a method to assist transportation planners and decision makers in determining the most feasible system between LRT and BRT. ^ Cost estimation is a major factor when evaluating a transit system. Typically, LRT is more expensive to build and implement than BRT, but has significantly lower Operating and Maintenance (OM) costs than BRT. This dissertation examines the factors impacting capacity and costs, and develops cost models, which are a capacity-based cost estimate for the LRT and BRT systems. Various ROW categories and alignment configurations of the systems are also considered in the developed cost models. Kikuchi's fleet size model (1985) and cost allocation method are used to develop the cost models to estimate the capacity and costs. ^ The comparison between LRT and BRT are complicated due to many possible transportation planning and operation scenarios. In the end, a user-friendly computer interface integrated with the established capacity-based cost models, the LRT and BRT Cost Estimator (LBCostor), was developed by using Microsoft Visual Basic language to facilitate the process and will guide the users throughout the comparison operations. The cost models and the LBCostor can be used to analyze transit volumes, alignments, ROW configurations, number of stops and stations, headway, size of vehicle, and traffic signal timing at the intersections. The planners can make the necessary changes and adjustments depending on their operating practices. ^

A framework for automatic feature extraction from airborne light detection and ranging data

Recent advances in airborne Light Detection and Ranging (LIDAR) technology allow rapid and inexpensive measurements of topography over large areas. Airborne LIDAR systems usually return a 3-dimensional cloud of point measurements from reflective objects scanned by the laser beneath the flight path. This technology is becoming a primary method for extracting information of different kinds of geometrical objects, such as high-resolution digital terrain models (DTMs), buildings and trees, etc. In the past decade, LIDAR gets more and more interest from researchers in the field of remote sensing and GIS. Compared to the traditional data sources, such as aerial photography and satellite images, LIDAR measurements are not influenced by sun shadow and relief displacement. However, voluminous data pose a new challenge for automated extraction the geometrical information from LIDAR measurements because many raster image processing techniques cannot be directly applied to irregularly spaced LIDAR points. ^ In this dissertation, a framework is proposed to filter out information about different kinds of geometrical objects, such as terrain and buildings from LIDAR automatically. They are essential to numerous applications such as flood modeling, landslide prediction and hurricane animation. The framework consists of several intuitive algorithms. Firstly, a progressive morphological filter was developed to detect non-ground LIDAR measurements. By gradually increasing the window size and elevation difference threshold of the filter, the measurements of vehicles, vegetation, and buildings are removed, while ground data are preserved. Then, building measurements are identified from no-ground measurements using a region growing algorithm based on the plane-fitting technique. Raw footprints for segmented building measurements are derived by connecting boundary points and are further simplified and adjusted by several proposed operations to remove noise, which is caused by irregularly spaced LIDAR measurements. To reconstruct 3D building models, the raw 2D topology of each building is first extracted and then further adjusted. Since the adjusting operations for simple building models do not work well on 2D topology, 2D snake algorithm is proposed to adjust 2D topology. The 2D snake algorithm consists of newly defined energy functions for topology adjusting and a linear algorithm to find the minimal energy value of 2D snake problems. Data sets from urbanized areas including large institutional, commercial, and small residential buildings were employed to test the proposed framework. The results demonstrated that the proposed framework achieves a very good performance. ^

Geophysical Analysis of a Central Florida Karst Terrain using Light Detection and Ranging (LIDAR) and Ground Penetrating Radar (GPR) Derived Surfaces

Airborne LIDAR (Light Detecting and Ranging) is a relatively new technique that rapidly and accurately measures micro-topographic features. This study compares topography derived from LIDAR with subsurface karst structures mapped in 3-dimensions with ground penetrating radar (GPR). Over 500 km of LIDAR data were collected in 1995 by the NASA ATM instrument. The LIDAR data was processed and analyzed to identify closed depressions. A GPR survey was then conducted at a 200 by 600 m site to determine if the target features are associated with buried karst structures. The GPR survey resolved two major depressions in the top of a clay rich layer at ~10m depth. These features are interpreted as buried dolines and are associated spatially with subtle (< 1m) trough-like depressions in the topography resolved from the LIDAR data. This suggests that airborne LIDAR may be a useful tool for indirectly detecting subsurface features associated with sinkhole hazard.

Enhanced zinc oxide and graphene nanostructures for electronics and sensing applications

Zinc oxide and graphene nanostructures are important technological materials because of their unique properties and potential applications in future generation of electronic and sensing devices. This dissertation investigates a brief account of the strategies to grow zinc oxide nanostructures (thin film and nanowire) and graphene, and their applications as enhanced field effect transistors, chemical sensors and transparent flexible electrodes. Nanostructured zinc oxide (ZnO) and low-gallium doped zinc oxide (GZO) thin films were synthesized by a magnetron sputtering process. Zinc oxide nanowires (ZNWs) were grown by a chemical vapor deposition method. Field effect transistors (FETs) of ZnO and GZO thin films and ZNWs were fabricated by standard photo and electron beam lithography processes. Electrical characteristics of these devices were investigated by nondestructive surface cleaning, ultraviolet irradiation treatment at high temperature and under vacuum. GZO thin film transistors showed a mobility of ∼5.7 cm2/V·s at low operation voltage of <5 V and a low turn-on voltage of ∼0.5 V with a sub threshold swing of ∼85 mV/decade. Bottom gated FET fabricated from ZNWs exhibit a very high on-to-off ratio (∼106) and mobility (∼28 cm2/V·s). A bottom gated FET showed large hysteresis of ∼5.0 to 8.0 V which was significantly reduced to ∼1.0 V by the surface treatment process. The results demonstrate charge transport in ZnO nanostructures strongly depends on its surface environmental conditions and can be explained by formation of depletion layer at the surface by various surface states. A nitric oxide (NO) gas sensor using single ZNW, functionalized with Cr nanoparticles was developed. The sensor exhibited average sensitivity of ∼46% and a minimum detection limit of ∼1.5 ppm for NO gas. The sensor also is selective towards NO gas as demonstrated by a cross sensitivity test with N2, CO and CO2 gases. Graphene film on copper foil was synthesized by chemical vapor deposition method. A hot press lamination process was developed for transferring graphene film to flexible polymer substrate. The graphene/polymer film exhibited a high quality, flexible transparent conductive structure with unique electrical-mechanical properties; ∼88.80% light transmittance and ∼1.1742Ω/sq k sheet resistance. The application of a graphene/polymer film as a flexible and transparent electrode for field emission displays was demonstrated.

The potential role of plant oxygen and sulphide dynamics in die-off events of the tropical seagrass, Thalassia testudinum

1 Oxygen and sulphide dynamics were examined, using microelectrode techniques, in meristems and rhizomes of the seagrass Thalassia testudinum at three different sites in Florida Bay, and in the laboratory, to evaluate the potential role of internal oxygen variability and sulphide invasion in episodes of sudden die-off. The sites differed with respect to shoot density and sediment composition, with an active die-off occurring at only one of the sites. 2 Meristematic oxygen content followed similar diel patterns at all sites with high oxygen content during the day and hyposaturation relative to the water column during the night. Minimum meristematic oxygen content was recorded around sunrise and varied among sites, with values close to zero at the die-off site. 3 Gaseous sulphide was detected within the sediment at all sites but at different concentrations among sites and within the die-off site. Spontaneous invasion of sulphide into Thalassia rhizomes was recorded at low internal oxygen partial pressure during darkness at the die-off site. 4 A laboratory experiment showed that the internal oxygen dynamics depended on light availability, and hence plant photosynthesis, and on the oxygen content of the water column controlling passive oxygen diffusion from water column to leaves and belowground tissues in the dark. 5 Sulphide invasion only occurred at low internal oxygen content, and the rate of invasion was highly dependent on the oxygen supply to roots and rhizomes. Sulphide was slowly depleted from the tissues when high oxygen partial pressures were re-established through leaf photosynthesis. Coexistence of sulphide and oxygen in the tissues and the slow rate of sulphide depletion suggest that sulphide reoxidation is not biologically mediated within the tissues of Thalassia. 6 Our results support the hypothesis that internal oxygen stress, caused by low water column oxygen content or poor plant performance governed by other environmental factors, allows invasion of sulphide and that the internal plant oxygen and sulphide dynamics potentially are key factors in the episodes of sudden die-off in beds of Thalassia testudinum . Root anoxia followed by sulphide invasion may be a more general mechanism determining the growth and survival of other rooted plants in sulphate-rich aquatic environments.

Developing performance measures of mangrove wetlands using simulation models of hydrology, nutrient biogeochemistry, and community dynamics

The goal of mangrove restoration projects should be to improve community structure and ecosystem function of degraded coastal landscapes. This requires the ability to forecast how mangrove structure and function will respond to prescribed changes in site conditions including hydrology, topography, and geophysical energies. There are global, regional, and local factors that can explain gradients of regulators (e.g., salinity, sulfides), resources (nutrients, light, water), and hydroperiod (frequency, duration of flooding) that collectively account for stressors that result in diverse patterns of mangrove properties across a variety of environmental settings. Simulation models of hydrology, nutrient biogeochemistry, and vegetation dynamics have been developed to forecast patterns in mangroves in the Florida Coastal Everglades. These models provide insight to mangrove response to specific restoration alternatives, testing causal mechanisms of system degradation. We propose that these models can also assist in selecting performance measures for monitoring programs that evaluate project effectiveness. This selection process in turn improves model development and calibration for forecasting mangrove response to restoration alternatives. Hydrologic performance measures include soil regulators, particularly soil salinity, surface topography of mangrove landscape, and hydroperiod, including both the frequency and duration of flooding. Estuarine performance measures should include salinity of the bay, tidal amplitude, and conditions of fresh water discharge (included in the salinity value). The most important performance measures from the mangrove biogeochemistry model should include soil resources (bulk density, total nitrogen, and phosphorus) and soil accretion. Mangrove ecology performance measures should include forest dimension analysis (transects and/or plots), sapling recruitment, leaf area index, and faunal relationships. Estuarine ecology performance measures should include the habitat function of mangroves, which can be evaluated with growth rate of key species, habitat suitability analysis, isotope abundance of indicator species, and bird census. The list of performance measures can be modified according to the model output that is used to define the scientific goals during the restoration planning process that reflect specific goals of the project.

Benthic Macrophyte Distribution and Abundance in Estuarine Mangrove Lakes and Estuaries: Relationships to Environmental Variables

Annual mean salinity, light availability, and sediment depth to bedrock structured the submerged aquatic vegetation (SAV) communities in subtropical mangrove-lined estuaries. Three distinct SAV communities (i.e., Chara group, Halodule group, and Low SAV coverage group) were identified along the Everglades–Florida Bay ecotone and related to water quality using a discriminant function model that predicted the type of plant community at a given site from salinity, light availability, and sediment depth to bedrock. Mean salinity alone was able to correctly classify 78% of the sites and reliably separated the Chara group from the Halodule group. The addition of light availability and sediment depth to bedrock increased model accuracy to 90% and further distinguished the Chara group from the Halodule group. Light availability was uniquely valuable in separating the Chara group from the Low SAV coverage group. Regression analyses identified significant relationships between phosphorus concentration, phytoplankton abundance, and light availability and suggest that a decline in water transparency, associated with increasing salinity, may have also contributed to the historical decline of Chara communities in the region. This investigation applies relationships between environmental variables and SAV distribution and provides a case study into the application of these general principals to ecosystem management.

Disturbance and recovery following catastrophic grazing: studies of a successional chronosequence in a seagrass bed

In August 1997, a large aggregation of the common sea urchin, Lytechinus variegatus, was discovered moving southward through a lush and productive seagrass monoculture of Syringodium filiforme in the Florida Keys, FL. Sea urchin densities at the grazing front were greater than 300 individuals m−2 which resulted in the overgrazing of seagrasses and a complete denuding of all vegetation from this area. The steady rate of the grazing front migration permitted the estimation of the time since disturbance for any point behind this grazing front allowing the use of a chronosequence approach to investigate the processes early on in succession of these communities. In May 1999, six north-south parallel transects were established across the disturbed seagrass communities and into the undisturbed areas south of the grazing front. Based on the measured rates of the migration of the grazing front, we grouped 60 sites into five categories (disturbed, recently grazed, active grazing front, stressed and undisturbed). The large scale loss of seagrass biomass initiated community-wide cascading effects that significantly altered resource regimes and species diversity. The loss of the seagrass canopy and subsequent death and decay of the below-ground biomass resulted in a de-stabilization of the sediments. As the sediments were eroded into the water column, turbidity significantly increased, reducing light availability and significantly reducing the sediment nitrogen pool and depleting the seed bank. The portion of the chronosequence that has had the longest period of recovery now consists of a mixed community of seagrass and macroalgae, as remnant survivors and quick colonizers coexist and jointly take advantage of the open space.

Leakage temperature dependency aware real-time scheduling for power and thermal optimization

Catering to society's demand for high performance computing, billions of transistors are now integrated on IC chips to deliver unprecedented performances. With increasing transistor density, the power consumption/density is growing exponentially. The increasing power consumption directly translates to the high chip temperature, which not only raises the packaging/cooling costs, but also degrades the performance/reliability and life span of the computing systems. Moreover, high chip temperature also greatly increases the leakage power consumption, which is becoming more and more significant with the continuous scaling of the transistor size. As the semiconductor industry continues to evolve, power and thermal challenges have become the most critical challenges in the design of new generations of computing systems. ^ In this dissertation, we addressed the power/thermal issues from the system-level perspective. Specifically, we sought to employ real-time scheduling methods to optimize the power/thermal efficiency of the real-time computing systems, with leakage/ temperature dependency taken into consideration. In our research, we first explored the fundamental principles on how to employ dynamic voltage scaling (DVS) techniques to reduce the peak operating temperature when running a real-time application on a single core platform. We further proposed a novel real-time scheduling method, “M-Oscillations” to reduce the peak temperature when scheduling a hard real-time periodic task set. We also developed three checking methods to guarantee the feasibility of a periodic real-time schedule under peak temperature constraint. We further extended our research from single core platform to multi-core platform. We investigated the energy estimation problem on the multi-core platforms and developed a light weight and accurate method to calculate the energy consumption for a given voltage schedule on a multi-core platform. Finally, we concluded the dissertation with elaborated discussions of future extensions of our research. ^

Non-consumptive effects of predators in coral reef communities and the indirect consequences of marine protected areas

Predators exert strong direct and indirect effects on ecological communities by intimidating their prey. Non-consumptive effects (NCEs) of predators are important features of many ecosystems and have changed the way we understand predator-prey interactions, but are not well understood in some systems. For my dissertation research I combined a variety of approaches to examine the effect of predation risk on herbivore foraging and reproductive behaviors in a coral reef ecosystem. In the first part of my dissertation, I investigated how diet and territoriality of herbivorous fish varied across multiple reefs with different levels of predator biomass in the Florida Keys National Marine Sanctuary. I show that both predator and damselfish abundance impacted diet diversity within populations for two herbivores in different ways. Additionally, reef protection and the associated recovery of large predators appeared to shape the trade-off reef herbivores made between territory size and quality. In the second part of my dissertation, I investigated context-dependent causal linkages between predation risk, herbivore foraging behavior and resource consumption in multiple field experiments. I found that reef complexity, predator hunting mode, light availability and prey hunger influenced prey perception of threat and their willingness to feed. This research argues for more emphasis on the role of predation risk in affecting individual herbivore foraging behavior in order to understand the implications of human-mediated predator removal and recovery in coral reef ecosystems.^

Non-Consumptive Effects of Predators in Coral Reef Communities and the Indirect Consequences of Marine Protected Areas

Predators exert strong direct and indirect effects on ecological communities by intimidating their prey. Non-consumptive effects (NCEs) of predators are important features of many ecosystems and have changed the way we understand predator-prey interactions, but are not well understood in some systems. For my dissertation research I combined a variety of approaches to examine the effect of predation risk on herbivore foraging and reproductive behaviors in a coral reef ecosystem. In the first part of my dissertation, I investigated how diet and territoriality of herbivorous fish varied across multiple reefs with different levels of predator biomass in the Florida Keys National Marine Sanctuary. I show that both predator and damselfish abundance impacted diet diversity within populations for two herbivores in different ways. Additionally, reef protection and the associated recovery of large predators appeared to shape the trade-off reef herbivores made between territory size and quality. In the second part of my dissertation, I investigated context-dependent causal linkages between predation risk, herbivore foraging behavior and resource consumption in multiple field experiments. I found that reef complexity, predator hunting mode, light availability and prey hunger influenced prey perception of threat and their willingness to feed. This research argues for more emphasis on the role of predation risk in affecting individual herbivore foraging behavior in order to understand the implications of human-mediated predator removal and recovery in coral reef ecosystems.

Leakage Temperature Dependency Aware Real-Time Scheduling for Power and Thermal Optimization

Catering to society’s demand for high performance computing, billions of transistors are now integrated on IC chips to deliver unprecedented performances. With increasing transistor density, the power consumption/density is growing exponentially. The increasing power consumption directly translates to the high chip temperature, which not only raises the packaging/cooling costs, but also degrades the performance/reliability and life span of the computing systems. Moreover, high chip temperature also greatly increases the leakage power consumption, which is becoming more and more significant with the continuous scaling of the transistor size. As the semiconductor industry continues to evolve, power and thermal challenges have become the most critical challenges in the design of new generations of computing systems. In this dissertation, we addressed the power/thermal issues from the system-level perspective. Specifically, we sought to employ real-time scheduling methods to optimize the power/thermal efficiency of the real-time computing systems, with leakage/ temperature dependency taken into consideration. In our research, we first explored the fundamental principles on how to employ dynamic voltage scaling (DVS) techniques to reduce the peak operating temperature when running a real-time application on a single core platform. We further proposed a novel real-time scheduling method, “M-Oscillations” to reduce the peak temperature when scheduling a hard real-time periodic task set. We also developed three checking methods to guarantee the feasibility of a periodic real-time schedule under peak temperature constraint. We further extended our research from single core platform to multi-core platform. We investigated the energy estimation problem on the multi-core platforms and developed a light weight and accurate method to calculate the energy consumption for a given voltage schedule on a multi-core platform. Finally, we concluded the dissertation with elaborated discussions of future extensions of our research.