A preliminary analysis of the correlation of food-web characteristics with hydrology and nutrient gradients in the southern Everglades

We estimated trophic position and carbon source for three consumers (Florida gar, Lepisosteus platyrhincus; eastern mosquitofish, Gambusia holbrooki; and riverine grass shrimp, Palaemonetes paludosus) from 20 sites representing gradients of productivity and hydrological disturbance in the southern Florida Everglades, U.S.A. We characterized gross primary productivity at each site using light/dark bottle incubation and stem density of emergent vascular plants. We also documented nutrient availability as total phosphorus (TP) in floc and periphyton, and the density of small fishes. Hydrological disturbance was characterized as the time since a site was last dried and the average number of days per year the sites were inundated for the previous 10 years. Food-web attributes were estimated in both the wet and dry seasons by analysis of δ15N (trophic position) and δ13C (food-web carbon source) from 702 samples of aquatic consumers. An index of carbon source was derived from a two-member mixing model with Seminole ramshorn snails (Planorbella duryi) as a basal grazing consumer and scuds (amphipods Hyallela azteca) as a basal detritivore. Snails yielded carbon isotopic values similar to green algae and diatoms, while carbon values of scuds were similar to bulk periphyton and floc; carbon isotopic values of cyanobacteria were enriched in C13compared to all consumers examined. A carbon source similar to scuds dominated at all but one study site, and though the relative contribution of scud-like and snail-like carbon sources was variable, there was no evidence that these contributions were a function of abiotic factors or season. Gar consistently displayed the highest estimated trophic position of the consumers studied, with mosquitofish feeding at a slightly lower level, and grass shrimp feeding at the lowest level. Trophic position was not correlated with any nutrient or productivity parameter, but did increase for grass shrimp and mosquitofish as the time following droughts increased. Trophic position of Florida gar was positively correlated with emergent plant stem density.

Essays on intergenerational and regional aspects of water management

This dissertation consists of three essays on different aspects of water management. The first essay focuses on the sustainability of freshwater use by introducing the notion that altruistic parents do bequeath economic assets for their offspring. Constructing a two-period, over-lapping generational model, an optimal ratio of consumption and pollution for old and young generations in each period is determined. Optimal levels of water consumption and pollution change according to different parameters, such as, altruistic degree, natural recharge rate, and population growth. The second essay concerns water sharing between countries in the case of trans-boundary river basins. The paper recognizes that side payments fail to forge water-sharing agreement among the international community and that downstream countries have weak bargaining power. An interconnected game approach is developed by linking the water allocation issue with other non-water issues such as trade or border security problems, creating symmetry between countries in bargaining power. An interconnected game forces two countries to at least partially cooperate under some circumstances. The third essay introduces the concept of virtual water (VW) into a traditional international trade model in order to estimate water savings for a water scarce country. A two country, two products and two factors trade model is developed, which includes not only consumers and producer's surplus, but also environmental externality of water use. The model shows that VW trade saves water and increases global and local welfare. This study should help policy makers to design appropriate subsidy or tax policy to promote water savings especially in water scarce countries.^

Consulting Services to Determine the Effectiveness of Vegetation Classification Using WorldView 2 Satellite Data for the Greater Everglades

The purpose of this project was to evaluate the use of remote sensing 1) to detect and map Everglades wetland plant communities at different scales; and 2) to compare map products delineated and resampled at various scales with the intent to quantify and describe the quantitative and qualitative differences between such products. We evaluated data provided by Digital Globe’s WorldView 2 (WV2) sensor with a spatial resolution of 2m and data from Landsat’s Thematic and Enhanced Thematic Mapper (TM and ETM+) sensors with a spatial resolution of 30m. We were also interested in the comparability and scalability of products derived from these data sources. The adequacy of each data set to map wetland plant communities was evaluated utilizing two metrics: 1) model-based accuracy estimates of the classification procedures; and 2) design-based post-classification accuracy estimates of derived maps.

Numerical simulation for dynamic positioning in pack ice

This thesis investigates the numerical modelling of Dynamic Position (DP) in pack ice. A two-dimensional numerical model for ship-ice interaction was developed using the Discrete Element Method (DEM). A viscous-elastic ice rheology was adopted to model the dynamic behaviour of the ice floes. Both the ship-ice and the ice-ice contacts were considered in the interaction force. The environment forces and the hydrodynamic forces were calculated by empirical formulas. After the current position and external forces were calculated, a Proportional-Integral-Derivative (PID) control and thrust allocation algorithms were applied on the vessel to control its motion and heading. The numerical model was coded in Fortran 90 and validated by comparing computation results to published data. Validation work was first carried out for the ship-ice interaction calculation, and former researchers’ simulation and model test results were used for the comparison. With confidence in the interaction model, case studies were conducted to predict the DP capability of a sample Arctic DP vessel.

Estimating density of a rare and cryptic high-mountain Galliform species, the Buff-throated Partridge Tetraophasis szechenyii

Estimates of abundance or density are essential for wildlife management and conservation. There are few effective density estimates for the Buff-throated Partridge Tetraophasis szechenyii, a rare and elusive high-mountain Galliform species endemic to western China. In this study, we used the temporary emigration N-mixture model to estimate density of this species, with data acquired from playback point count surveys around a sacred area based on indigenous Tibetan culture of protection of wildlife, in Yajiang County, Sichuan, China, during April–June 2009. Within 84 125-m radius points, we recorded 53 partridge groups during three repeats. The best model indicated that detection probability was described by covariates of vegetation cover type, week of visit, time of day, and weather with weak effects, and a partridge group was present during a sampling period with a constant probability. The abundance component was accounted for by vegetation association. Abundance was substantially higher in rhododendron shrubs, fir-larch forests, mixed spruce-larch-birch forests, and especially oak thickets than in pine forests. The model predicted a density of 5.14 groups/km², which is similar to an estimate of 4.7 – 5.3 groups/km² quantified via an intensive spot-mapping effort. The post-hoc estimate of individual density was 14.44 individuals/km², based on the estimated mean group size of 2.81. We suggest that the method we employed is applicable to estimate densities of Buff-throated Partridges in large areas. Given importance of a mosaic habitat for this species, local logging should be regulated. Despite no effect of the conservation area (sacred) on the abundance of Buff-throated Partridges, we suggest regulations linking the sacred mountain conservation area with the official conservation system because of strong local participation facilitated by sacred mountains in land conservation.

Methods for Imputing Missing Values and Synthesizing Confidential Values for Continuous and Magnitude Data

Abstract

Continuous variable is one of the major data types collected by the survey organizations. It can be incomplete such that the data collectors need to fill in the missingness. Or, it can contain sensitive information which needs protection from re-identification. One of the approaches to protect continuous microdata is to sum them up according to different cells of features. In this thesis, I represents novel methods of multiple imputation (MI) that can be applied to impute missing values and synthesize confidential values for continuous and magnitude data.

The first method is for limiting the disclosure risk of the continuous microdata whose marginal sums are fixed. The motivation for developing such a method comes from the magnitude tables of non-negative integer values in economic surveys. I present approaches based on a mixture of Poisson distributions to describe the multivariate distribution so that the marginals of the synthetic data are guaranteed to sum to the original totals. At the same time, I present methods for assessing disclosure risks in releasing such synthetic magnitude microdata. The illustration on a survey of manufacturing establishments shows that the disclosure risks are low while the information loss is acceptable.

The second method is for releasing synthetic continuous micro data by a nonstandard MI method. Traditionally, MI fits a model on the confidential values and then generates multiple synthetic datasets from this model. Its disclosure risk tends to be high, especially when the original data contain extreme values. I present a nonstandard MI approach conditioned on the protective intervals. Its basic idea is to estimate the model parameters from these intervals rather than the confidential values. The encouraging results of simple simulation studies suggest the potential of this new approach in limiting the posterior disclosure risk.

The third method is for imputing missing values in continuous and categorical variables. It is extended from a hierarchically coupled mixture model with local dependence. However, the new method separates the variables into non-focused (e.g., almost-fully-observed) and focused (e.g., missing-a-lot) ones. The sub-model structure of focused variables is more complex than that of non-focused ones. At the same time, their cluster indicators are linked together by tensor factorization and the focused continuous variables depend locally on non-focused values. The model properties suggest that moving the strongly associated non-focused variables to the side of focused ones can help to improve estimation accuracy, which is examined by several simulation studies. And this method is applied to data from the American Community Survey.

Dynamic classifiers for neonatal brain monitoring

Brain injury due to lack of oxygen or impaired blood flow around the time of birth, may cause long term neurological dysfunction or death in severe cases. The treatments need to be initiated as soon as possible and tailored according to the nature of the injury to achieve best outcomes. The Electroencephalogram (EEG) currently provides the best insight into neurological activities. However, its interpretation presents formidable challenge for the neurophsiologists. Moreover, such expertise is not widely available particularly around the clock in a typical busy Neonatal Intensive Care Unit (NICU). Therefore, an automated computerized system for detecting and grading the severity of brain injuries could be of great help for medical staff to diagnose and then initiate on-time treatments. In this study, automated systems for detection of neonatal seizures and grading the severity of Hypoxic-Ischemic Encephalopathy (HIE) using EEG and Heart Rate (HR) signals are presented. It is well known that there is a lot of contextual and temporal information present in the EEG and HR signals if examined at longer time scale. The systems developed in the past, exploited this information either at very early stage of the system without any intelligent block or at very later stage where presence of such information is much reduced. This work has particularly focused on the development of a system that can incorporate the contextual information at the middle (classifier) level. This is achieved by using dynamic classifiers that are able to process the sequences of feature vectors rather than only one feature vector at a time.

Essays on Intergenerational and Regional Aspects of Water Management

This dissertation consists of three essays on different aspects of water management. The first essay focuses on the sustainability of freshwater use by introducing the notion that altruistic parents do bequeath economic assets for their offspring. Constructing a two-period, over-lapping generational model, an optimal ratio of consumption and pollution for old and young generations in each period is determined. Optimal levels of water consumption and pollution change according to different parameters, such as, altruistic degree, natural recharge rate, and population growth. The second essay concerns water sharing between countries in the case of trans-boundary river basins. The paper recognizes that side payments fail to forge water-sharing agreement among the international community and that downstream countries have weak bargaining power. An interconnected game approach is developed by linking the water allocation issue with other non-water issues such as trade or border security problems, creating symmetry between countries in bargaining power. An interconnected game forces two countries to at least partially cooperate under some circumstances. The third essay introduces the concept of virtual water (VW) into a traditional international trade model in order to estimate water savings for a water scarce country. A two country, two products and two factors trade model is developed, which includes not only consumers and producer’s surplus, but also environmental externality of water use. The model shows that VW trade saves water and increases global and local welfare. This study should help policy makers to design appropriate subsidy or tax policy to promote water savings especially in water scarce countries.

Geochemical and stable isotope composition of Middle Campanian marl-limestone rhythmites of the Lehrte West Syncline near Hannover (Lower Saxony, northern Germany)

A cyclic marl-limestone succession of Middle-Late Campanian age has been investigated with respect to a Milankovitch-controlled origin of geochemical data. In general, the major element geochemistry of the marl-limestone rhythmites can be explained by a simple two-component mixing model with the end-members calcium carbonate and 'average shale'-like material. Carbonate content varies from 55 to 90%. Non-carbonate components are clay minerals (illite, smectite) and biogenic silica from sponge spicules, as well as authigenically formed zeolites (strontian heulandite) and quartz. The redox potential suggests oxidizing conditions throughout the section. Trace element and stable isotopic data as well as SEM investigations show that the carbonate mud is mostly composed of low-magnesium calcitic tests of planktic coccolithophorids and calcareous dinoflagellate cysts (calcispheres). Diagenetic overprint results in a decrease of 2% d18O and an increase in Mn of up to 250 ppm. However, the sediment seems to preserve most of its high Sr content compared to the primary low-magnesium calcite of co-occurring belemnite rostra. The periodicity of geochemical cycles is dominated by 413 ka and weak signals between 51 and 22.5 ka, attributable to orbital forcing. Accumulation rates within these cycles vary between 40 and 50 m/Ma. The resulting cyclic sedimentary sequence is the product of (a) changes in primary production of low-magnesium calcitic biogenic material in surface waters within the long eccentricity and the precession, demonstrated by the CaCO3 content and the Mg/Al, Mn/Al and Sr/Al ratios, and (b) fluctuations in climate and continental weathering, which changed the quality of supplied clay minerals (the illite/smectite ratio), demonstrated by the K/Al ratio. High carbonate productivity correlates with smectite-favouring weathering (semi-arid conditions, conspicuously dry and moist seasonal changes in warmer climates). Ti as the proxy indicator for the detrital terrigenous influx, as well as Rb, Si, Zr and Na, shows only low frequency signals, indicating nearly constant rates of supply throughout the more or less pure pelagic carbonate deposition of the long-lasting third-order Middle-Upper Campanian sedimentary cycle.

Lead isotope ratios of basalts from DSDP Leg 37 (Table 1)

Analyses of Pb from mid-ocean ridge basalts obtained from DSDP Leg 37 lie on a line of near-zero-age slope. The data seem consistent with an evolutionary model of three stages, the beginning of the second stage being at about 600 m.y. - the model age obtained for the least radiogenic Pb. The beginning of the third stage of evolution at the time of formation of the rocks apparently did not change the average Th/U ratio since measured values are consistent with the ratio deduced from Pb isotope ratios. Ratios of U/Pb are not consistent with Pb isotope ratios, however, thus ruling out a simple two-stage evolutionary model.

Essays in dynamic optimal taxation: working experience, unemployment scarring and poverty

This thesis investigates the design of optimal tax systems in dynamic environments. The first essay characterizes the optimal tax system where wages depend on stochastic shocks and work experience. In addition to redistributive and efficiency motives, the taxation of inexperienced workers depends on a second-best requirement that encourages work experience, a social insurance motive and incentive effects. Calibrations using U.S. data yield higher expected optimal marginal income tax rates for experienced workers for most of the inexperienced workers. They confirm that the average marginal income tax rate increases (decreases) with age when shocks and work experience are substitutes (complements). Finally, more variability in experienced workers' earnings prospects leads to increasing tax rates since income taxation acts as a social insurance mechanism. In the second essay, the properties of an optimal tax system are investigated in a dynamic private information economy where labor market frictions create unemployment that destroys workers' human capital. A two-skill type model is considered where wages and employment are endogenous. I find that the optimal tax system distorts the first-period wages of all workers below their efficient levels which leads to more employment. The standard no-distortion-at-the-top result no longer holds due to the combination of private information and the destruction of human capital. I show this result analytically under the Maximin social welfare function and confirm it numerically for a general social welfare function. I also investigate the use of a training program and job creation subsidies. The final essay analyzes the optimal linear tax system when there is a population of individuals whose perceptions of savings are linked to their disposable income and their family background through family cultural transmission. Aside from the standard equity/efficiency trade-off, taxes account for the endogeneity of perceptions through two channels. First, taxing labor decreases income, which decreases the perception of savings through time. Second, taxation on savings corrects for the misperceptions of workers and thus savings and labor decisions. Numerical simulations confirm that behavioral issues push labor income taxes upward to finance saving subsidies. Government transfers to individuals are also decreased to finance those same subsidies.

Stress Inversion Using LiDAR Tunnel Deformation Measurements

Far-field stresses are those present in a volume of rock prior to excavations being created. Estimates of the orientation and magnitude of far-field stresses, often used in mine design, are generally obtained by single-point measurements of stress, or large-scale, regional trends. Point measurements can be a poor representation of far-field stresses as a result of excavation-induced stresses and geological structures. For these reasons, far-field stress estimates can be associated with high levels of uncertainty. The purpose of this thesis is to investigate the practical feasibility, applications, and limitations of calibrating far-field stress estimates through tunnel deformation measurements captured using LiDAR imaging. A method that estimates the orientation and magnitude of excavation-induced principal stress changes through back-analysis of deformation measurements from LiDAR imaged tunnels was developed and tested using synthetic data. If excavation-induced stress change orientations and magnitudes can be accurately estimated, they can be used in the calibration of far-field stress input to numerical models. LiDAR point clouds have been proven to have a number of underground applications, thus it is desired to explore their use in numerical model calibration. The back-analysis method is founded on the superposition of stresses and requires a two-dimensional numerical model of the deforming tunnel. Principal stress changes of known orientation and magnitude are applied to the model to create calibration curves. Estimation can then be performed by minimizing squared differences between the measured tunnel and sets of calibration curve deformations. In addition to the back-analysis estimation method, a procedure consisting of previously existing techniques to measure tunnel deformation using LiDAR imaging was documented. Under ideal conditions, the back-analysis method estimated principal stress change orientations within ±5° and magnitudes within ±2 MPa. Results were comparable for four different tunnel profile shapes. Preliminary testing using plastic deformation, a rough tunnel profile, and profile occlusions suggests that the method can work under more realistic conditions. The results from this thesis set the groundwork for the continued development of a new, inexpensive, and efficient far-field stress estimate calibration method.

On The Dirichlet Distribution

The Dirichlet distribution is a multivariate generalization of the Beta distribution. It is an important multivariate continuous distribution in probability and statistics. In this report, we review the Dirichlet distribution and study its properties, including statistical and information-theoretic quantities involving this distribution. Also, relationships between the Dirichlet distribution and other distributions are discussed. There are some different ways to think about generating random variables with a Dirichlet distribution. The stick-breaking approach and the Pólya urn method are discussed. In Bayesian statistics, the Dirichlet distribution and the generalized Dirichlet distribution can both be a conjugate prior for the Multinomial distribution. The Dirichlet distribution has many applications in different fields. We focus on the unsupervised learning of a finite mixture model based on the Dirichlet distribution. The Initialization Algorithm and Dirichlet Mixture Estimation Algorithm are both reviewed for estimating the parameters of a Dirichlet mixture. Three experimental results are shown for the estimation of artificial histograms, summarization of image databases and human skin detection.

Nonequilibrium critical scaling from quantum thermodynamics

The emerging field of quantum thermodynamics is contributing important results and insights into archetypal many-body problems, including quantum phase transitions. Still, the question whether out-of-equilibrium quantities, such as fluctuations of work, exhibit critical scaling after a sudden quench in a closed system has remained elusive. Here, we take a novel approach to the problem by studying a quench across an impurity quantum critical point. By performing density matrix renormalization group computations on the two-impurity Kondo model, we are able to establish that the irreversible work produced in a quench exhibits finite-size scaling at quantum criticality. This scaling faithfully predicts the equilibrium critical exponents for the crossover length and the order parameter of the model, and, moreover, implies a new exponent for the rescaled irreversible work. By connecting the irreversible work to the two-impurity spin correlation function, our findings can be tested experimentally.