Role of Hydrological Process Representation on Erosion, Deposition, and Sediment Yield Estimate

Soil erosion by water is a major driven force causing land degradation. Laboratory experiments, on-site field study, and suspended sediments measurements were major fundamental approaches to study the mechanisms of soil water erosion and to quantify the erosive losses during rain events. The experimental research faces the challenge to extent the result to a wider spatial scale. Soil water erosion modeling provides possible solutions for scaling problems in erosion research, and is of principal importance to better understanding the governing processes of water erosion. However, soil water erosion models were considered to have limited value in practice. Uncertainties in hydrological simulations are among the reasons that hindering the development of water erosion model. Hydrological models gained substantial improvement recently and several water erosion models took advantages of the improvement of hydrological models. It is crucial to know the impact of changes in hydrological processes modeling on soil erosion simulation.

This dissertation work first created an erosion modeling tool (GEOtopSed) that takes advantage of the comprehensive hydrological model (GEOtop). The newly created tool was then tested and evaluated at an experimental watershed. The GEOtopSed model showed its ability to estimate multi-year soil erosion rate with varied hydrological conditions. To investigate the impact of different hydrological representations on soil erosion simulation, a 11-year simulation experiment was conducted for six models with varied configurations. The results were compared at varied temporal and spatial scales to highlight the roles of hydrological feedbacks on erosion. Models with simplified hydrological representations showed agreement with GEOtopSed model on long temporal scale (longer than annual). This result led to an investigation for erosion simulation at different rainfall regimes to check whether models with different hydrological representations have agreement on the soil water erosion responses to the changing climate. Multi-year ensemble simulations with different extreme precipitation scenarios were conducted at seven climate regions. The differences in erosion simulation results showed the influences of hydrological feedbacks which cannot be seen by purely rainfall erosivity method.

Distribution and Conservation of the Antillean Manatee in Hispaniola

Antillean manatees (Trichechus manatus manatus) were heavily hunted in the past throughout the Wider Caribbean Region (WCR), and are currently listed as endangered on the IUCN Red List of Threatened Species. In most WCR countries, including Haiti and the Dominican Republic, remaining manatee populations are believed to be small and declining, but current information is needed on their status, distribution, and local threats to the species.

To assess the past and current distribution and conservation status of the Antillean manatee in Hispaniola, I conducted a systematic review of documentary archives dating from the pre-Columbian era to 2013. I then surveyed more than 670 artisanal fishers from Haiti and the Dominican Republic in 2013-2014 using a standardized questionnaire. Finally, to identify important areas for manatees in the Dominican Republic, I developed a country-wide ensemble model of manatee distribution, and compared modeled hotspots with those identified by fishers.

Manatees were historically abundant in Hispaniola, but were hunted for their meat and became relatively rare by the end of the 19th century. The use of manatee body parts diversified with time to include their oil, skin, and bones. Traditional uses for folk medicine and handcrafts persist today in coastal communities in the Dominican Republic. Most threats to Antillean manatees in Hispaniola are anthropogenic in nature, and most mortality is caused by fisheries. I estimated a minimum island-wide annual mortality of approximately 20 animals. To understand the impact of this level of mortality, and to provide a baseline for measuring the success of future conservation actions, the Dominican Republic and Haiti should work together to obtain a reliable estimate of the current population size of manatees in Hispaniola.

In Haiti, the survey of fishers showed a wider distribution range of the species than suggested by the documentary archive review: fishers reported recent manatee sightings in seven of nine coastal departments, and three manatee hotspot areas were identified in the north, central, and south coasts. Thus, the contracted manatee distribution range suggested by the documentary archive review likely reflects a lack of research in Haiti. Both the review and the interviews agreed that manatees no longer occupy freshwater habitats in the country. In general, more dedicated manatee studies are needed in Haiti, employing aerial, land, or boat surveys.

In the Dominican Republic, the documentary archive review and the survey of fishers showed that manatees still occur throughout the country, and occasionally occupy freshwater habitats. Monte Cristi province in the north coast, and Barahona province in the south coast, were identified as focal areas. Sighting reports of manatees decreased from Monte Cristi eastwards to the adjacent province in the Dominican Republic, and westwards into Haiti. Along the north coast of Haiti, the number of manatee sighting and capture reports decreased with increasing distance to Monte Cristi province. There was good agreement among the modeled manatee hotspots, hotspots identified by fishers, and hotspots identified during previous dedicated manatee studies. The concordance of these results suggests that the distribution and patterns of habitat use of manatees in the Dominican Republic have not changed dramatically in over 30 years, and that the remaining manatees exhibit some degree of site fidelity. The ensemble modeling approach used in the present study produced accurate and detailed maps of manatee distribution with minimum data requirements. This modeling strategy is replicable and readily transferable to other countries in the Caribbean or elsewhere with limited data on a species of interest.

The intrinsic value of manatees was stronger for artisanal fishers in the Dominican Republic than in Haiti, and most Dominican fishers showed a positive attitude towards manatee conservation. The Dominican Republic is an upper middle income country with a high Human Development Index. It possesses a legal framework that specifically protects manatees, and has a greater number of marine protected areas, more dedicated manatee studies, and more manatee education and awareness campaigns than Haiti. The constant presence of manatees in specific coastal segments of the Dominican Republic, the perceived decline in the number of manatee captures, and a more conservation-minded public, offer hope for manatee conservation, as non-consumptive uses of manatees become more popular. I recommend a series of conservation actions in the Dominican Republic, including: reducing risks to manatees from harmful fishing gear and watercraft at confirmed manatee hotspots; providing alternative economic alternatives for displaced fishers, and developing responsible ecotourism ventures for manatee watching; improving law enforcement to reduce fisheries-related manatee deaths, stop the illegal trade in manatee body parts, and better protect manatee habitat; and continuing education and awareness campaigns for coastal communities near manatee hotspots.

In contrast, most fishers in Haiti continue to value manatees as a source of food and income, and showed a generally negative attitude towards manatee conservation. Haiti is a low income country with a low Human Development Index. Only a single dedicated manatee study has been conducted in Haiti, and manatees are not officially protected. Positive initiatives for manatees in Haiti include: protected areas declared in 2013 and 2014 that enclose two of the manatee hotspots identified in the present study; and local organizations that are currently working on coastal and marine environmental issues, including research and education on marine mammals. Future conservation efforts for manatees in Haiti should focus on addressing poverty and providing viable economic alternatives for coastal communities. I recommend a community partnership approach for manatee conservation, paired with education and awareness campaigns to inform coastal communities about the conservation situation of manatees in Haiti, and to help change their perceived value. Haiti should also provide legal protection for manatees and their habitat.

Advances in Dynamic Modeling and Computation for Count Data

A class of multi-process models is developed for collections of time indexed count data. Autocorrelation in counts is achieved with dynamic models for the natural parameter of the binomial distribution. In addition to modeling binomial time series, the framework includes dynamic models for multinomial and Poisson time series. Markov chain Monte Carlo (MCMC) and Po ́lya-Gamma data augmentation (Polson et al., 2013) are critical for fitting multi-process models of counts. To facilitate computation when the counts are high, a Gaussian approximation to the P ́olya- Gamma random variable is developed.

Three applied analyses are presented to explore the utility and versatility of the framework. The first analysis develops a model for complex dynamic behavior of themes in collections of text documents. Documents are modeled as a “bag of words”, and the multinomial distribution is used to characterize uncertainty in the vocabulary terms appearing in each document. State-space models for the natural parameters of the multinomial distribution induce autocorrelation in themes and their proportional representation in the corpus over time.

The second analysis develops a dynamic mixed membership model for Poisson counts. The model is applied to a collection of time series which record neuron level firing patterns in rhesus monkeys. The monkey is exposed to two sounds simultaneously, and Gaussian processes are used to smoothly model the time-varying rate at which the neuron’s firing pattern fluctuates between features associated with each sound in isolation.

The third analysis presents a switching dynamic generalized linear model for the time-varying home run totals of professional baseball players. The model endows each player with an age specific latent natural ability class and a performance enhancing drug (PED) use indicator. As players age, they randomly transition through a sequence of ability classes in a manner consistent with traditional aging patterns. When the performance of the player significantly deviates from the expected aging pattern, he is identified as a player whose performance is consistent with PED use.

All three models provide a mechanism for sharing information across related series locally in time. The models are fit with variations on the P ́olya-Gamma Gibbs sampler, MCMC convergence diagnostics are developed, and reproducible inference is emphasized throughout the dissertation.

Mathematical Modeling of Perifusion Cell Culture Experiments

In perifusion cell cultures, the culture medium flows continuously through a chamber containing immobilized cells and the effluent is collected at the end. In our main applications, gonadotropin releasing hormone (GnRH) or oxytocin is introduced into the chamber as the input. They stimulate the cells to secrete luteinizing hormone (LH), which is collected in the effluent. To relate the effluent LH concentration to the cellular processes producing it, we develop and analyze a mathematical model consisting of coupled partial differential equations describing the intracellular signaling and the movement of substances in the cell chamber. We analyze three different data sets and give cellular mechanisms that explain the data. Our model indicates that two negative feedback loops, one fast and one slow, are needed to explain the data and we give their biological bases. We demonstrate that different LH outcomes in oxytocin and GnRH stimulations might originate from different receptor dynamics. We analyze the model to understand the influence of parameters, like the rate of the medium flow or the fraction collection time, on the experimental outcomes. We investigate how the rate of binding and dissociation of the input hormone to and from its receptor influence its movement down the chamber. Finally, we formulate and analyze simpler models that allow us to predict the distortion of a square pulse due to hormone-receptor interactions and to estimate parameters using perifusion data. We show that in the limit of high binding and dissociation the square pulse moves as a diffusing Gaussian and in this limit the biological parameters can be estimated.

Elucidating the Space-Time Structure of Low Level Warm Season Precipitation Processes in the Southern Appalachian Mountains Using Models and Observations

Light rainfall is the baseline input to the annual water budget in mountainous landscapes through the tropics and at mid-latitudes. In the Southern Appalachians, the contribution from light rainfall ranges from 50-60% during wet years to 80-90% during dry years, with convective activity and tropical cyclone input providing most of the interannual variability. The Southern Appalachians is a region characterized by rich biodiversity that is vulnerable to land use/land cover changes due to its proximity to a rapidly growing population. Persistent near surface moisture and associated microclimates observed in this region has been well documented since the colonization of the area in terms of species health, fire frequency, and overall biodiversity. The overarching objective of this research is to elucidate the microphysics of light rainfall and the dynamics of low level moisture in the inner region of the Southern Appalachians during the warm season, with a focus on orographically mediated processes. The overarching research hypothesis is that physical processes leading to and governing the life cycle of orographic fog, low level clouds, and precipitation, and their interactions, are strongly tied to landform, land cover, and the diurnal cycles of flow patterns, radiative forcing, and surface fluxes at the ridge-valley scale. The following science questions will be addressed specifically: 1) How do orographic clouds and fog affect the hydrometeorological regime from event to annual scale and as a function of terrain characteristics and land cover?; 2) What are the source areas, governing processes, and relevant time-scales of near surface moisture convergence patterns in the region?; and 3) What are the four dimensional microphysical and dynamical characteristics, including variability and controlling factors and processes, of fog and light rainfall? The research was conducted with two major components: 1) ground-based high-quality observations using multi-sensor platforms and 2) interpretive numerical modeling guided by the analysis of the in situ data collection. Findings illuminate a high level of spatial – down to the ridge scale - and temporal – from event to annual scale - heterogeneity in observations, and a significant impact on the hydrological regime as a result of seeder-feeder interactions among fog, low level clouds, and stratiform rainfall that enhance coalescence efficiency and lead to significantly higher rainfall rates at the land surface. Specifically, results show that enhancement of an event up to one order of magnitude in short-term accumulation can occur as a result of concurrent fog presence. Results also show that events are modulated strongly by terrain characteristics including elevation, slope, geometry, and land cover. These factors produce interactions between highly localized flows and gradients of temperature and moisture with larger scale circulations. Resulting observations of DSD and rainfall patterns are stratified by region and altitude and exhibit clear diurnal and seasonal cycles.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

Role of Vinculin in Regulating Force-Sensitive Dynamics of Adherens Junctions During Collective Cell Migration

Dynamic processes such as morphogenesis and tissue patterning require the precise control of many cellular processes, especially cell migration. Historically, these processes are thought to be mediated by genetic and biochemical signaling pathways. However, recent advances have unraveled a previously unappreciated role of mechanical forces in regulating these homeostatic processes in of multicellular systems. In multicellular systems cells adhere to both deformable extracellular matrix (ECM) and other cells, which are sources of applied forces and means of mechanical support. Cells detect and respond to these mechanical signals through a poorly understood process called mechanotransduction, which can have profound effects on processes such as cell migration. These effects are largely mediated by the sub cellular structures that link cells to the ECM, called focal adhesions (FAs), or cells to other cells, termed adherens junctions (AJs).

Overall this thesis is comprised of my work on identifying a novel force dependent function of vinculin, a protein which resides in both FAs and AJs - in dynamic process of collective migration. Using a collective migration assay as a model for collective cell behavior and a fluorescence resonance energy transfer (FRET) based molecular tension sensor for vinculin I demonstrated a spatial gradient of tension across vinculin in the direction of migration. To define this novel force-dependent role of vinculin in collective migration I took advantage of previously established shRNA based vinculin knock down Marin-Darby Canine Kidney (MDCK) epithelial cells.

The first part of my thesis comprises of my work demonstrating the mechanosensitive role of vinculin at AJ’s in collectively migrating cells. Using vinculin knockdown cells and vinculin mutants, which specifically disrupt vinculin’s ability to bind actin (VinI997A) or disrupt its ability to localize to AJs without affecting its localization at FAs (VinY822F), I establish a role of force across vinculin in E-cadherin internalization and clipping. Furthermore by measuring E-cadherin dynamics using fluorescence recovery after bleaching (FRAP) analysis I show that vinculin inhibition affects the turnover of E-cadherin at AJs. Together these data reveal a novel mechanosensitive role of vinculin in E-cadherin internalization and turnover in a migrating cell layer, which is contrary to the previously identified role of vinculin in potentiating E-cadherin junctions in a static monolayer.

For the last part of my thesis I designed a novel tension sensor to probe tension across N-cadherin (NTS). N-cadherin plays a critical role in cardiomyocytes, vascular smooth muscle cells, neurons and neural crest cells. Similar to E-cadherin, N-cadherin is also believed to bear tension and play a role in mechanotransduction pathways. To identify the role of tension across N-cadherin I designed a novel FRET-based molecular tension sensor for N-cadherin. I tested the ability of NTS to sense molecular tension in vascular smooth muscle cells, cardiomyocytes and cancer cells. Finally in collaboration with the Horwitz lab we have been able to show a role of tension across N-cadherin in synaptogenesis of neurons.