The tropical forests on the island of Borneo are among of the richest in the world in terms of tree diversity, and their capacity to store a large reservoir of carbon. The Southeast Asian forests are fundamentally different from Neotropical and African forests, with their single-family dominance by dipterocarp trees, and with inherently greater stature and biomass. The carbon productivity and allocation in Asian tropical forests is still poorly quantified, and their responses to environmental drivers are still poorly understood. Almost all recent advances in tropical forest carbon cycling research have occurred in the Neotropics, with very few studies in Asia. The principal aim of this thesis is to quantify the carbon budget of a lowland dipterocarp forest in the Lambir Hills National Park, Miri, Sarawak, Malaysian Borneo. I examined and explored the productivity and carbon cycling processes and their responses to environmental factors across two major and contrasting soil types, in particular the clay and sandy loam soils. I recorded and analysed the Net Primary Productivity (NPP) and respiration for the above- and below-ground components, and observed the responses to seasonal variation and environmental drivers. Total soil respiration was relatively high and contributed a great deal to ecosystem respiration. Variation in soil respiration rates appeared closely related to soil moisture content. I found a strong diurnal cycle in soil respiration. On the basis of the first soil carbon dioxide (CO2) efflux partitioning study undertaken in a tropical forest, the diurnal cycle in total soil respiration appeared to be entirely driven by the diurnal cycle in litter respiration, and in turn litter is strongly controlled by moisture. There was little seasonal variation in allocation of net primary productivity (NPP), but there was evidence showing potential inter-annual variability for several components of NPP. Further, the allocation of NPP showed a strong seasonal shift between the forest plots on clay and sandy loam soils. Combining all the data measured and obtained in this D.Phil. thesis, the overall carbon budget assessed in this lowland dipterocarp forest showed a high level of agreement with other studies in Asia using micrometeorological techniques and the situation appears to be comparable to tropical forests in Amazonia. The key difference is that the aboveground NPP is higher and is the largest component contributing to the overall carbon budget, with relatively higher carbon use efficiency (CUE). The lowland dipterocarp forest in Lambir shows higher allocation in the above-ground NPP, and there were also differences in NPP and its allocation between sandy and clay-rich plots.

Doctor of Philosophy / Department of Physics / Chii-Dong Lin / Imaging of molecules has always occupied an essential role in physical, chemical and biological sciences. X-ray and electron diffraction methods routinely achieve sub-angstrom spatial resolutions but are limited to probing dynamical timescales longer than a picosecond. With the advent of femtosecond intense lasers, a new imaging paradigm emerges in last decade based on laser-induced electron diffraction (LIED). It has been placed on a firm foundation by the quantitative rescattering theory, which established that large-angle e-ion elastic differential cross sections (DCS) can be retrieved from the LIED spectrum. We further demonstrate that atomic potentials can be accurately retrieved from those extracted DCSs at energies from a few to several tens of electron volts. Extending to molecules, we show mid-infrared (mid-IR) lasers are crucial to generate high-energy electron wavepackets (> 100 eV) to resolve the atomic positions in a molecule. These laser-driven 100 eV electrons can incur core-penetrating collisions where the momentum transfer is comparable to those attained in conventional keV electron diffraction. Thus a simple independent atom model (IAM), which has been widely used in conventional electron diffractions, may apply for LIED. We theoretically examine and validate the applicability of IAM for electron energies above 100 eV using e-molecule large-angle collision data obtained in conventional experiments, demonstrating its resolving powers for bond lengths about 0.05 angstrom. The Validity of IAM is also checked by an experimental LIED investigation of rare gas atoms in the mid-IR regime. We show that the electron’s high energy promotes core-penetrating collisions at large scattering angles, where the e-atom interaction is dominated by the strong short range atomic-like potential. Finally, we analyze the measured LIED spectrum of N[subscript]2 and O[subscript]2 at three mid-IR wavelengths (1.7, 2.0, and 2.3 μm). As expected, the retrieved bond lengths of N[subscript]2 at three wavelengths are about same as the equilibrium N[subscript]2 bond length. For O[subscript]2, the data is also consistent with a bond length contraction of 0.1 angstrom within 4-6 fs after tunnel ionization. This investigation establishes a foundation for this novel imaging method for spatiotemporal imaging of gas-phase molecules at the atomic scale.

<p>Flooding is one of the most devastating and frequently occurring natural phenomena in the world. Due to the adverse impacts of floods on the life and property of humans, it is crucial to investigate the best flood modeling approaches for delineation of floodplain areas. Conventionally, different hydrodynamic models are used to identify the floodplain areas. However, the high computational cost, and the dependency of these models on detailed input datasets limit their application for large scale floodplain mapping in data-scarce regions. Recently, a new floodplain mapping method based on a hydrogeomorphic feature, named Height Above Nearest Drainage (<i>HAND</i>), has been proposed as a successful alternative for fast and efficient floodplain mapping at the large scale. The overall goal of this study is to improve the performance of <i>HAND</i>-based method by overcoming its current limitations. The main focus will be on extending the application of the <i>HAND</i>-based method to data-scarce environments. To achieve this goal, regionalization techniques are integrated with the floodplain models at the regional and continental scales. Considering these facts, four research objective are established to (1) Develop a regression model to create 100-year floodplain maps at a regional scale (2) Develop a classification framework for creating 100-year floodplain maps for the Contiguous United States (3) Develop a new version of the <i>HAND</i>-based method for creating probabilistic 100-year floodplain maps, and (4) Propose a general regionalization framework for transferring information from data-rich basins to data-scarce environments. </p> <p> </p> <p>In the first objective, the state of North Carolina is selected as the study area, and a regression model is developed to regionalize the available 100-year Flood Insurance Rate Maps (FIRMs) to the data-scarce regions. The regression model is an exponential equation with three independent variables including the average slope, the average elevation, and the main stream slope of the watershed. The results show that the estimated floodplains are within the expected range of accuracy of C>0.6 and F>0.9 for majority of watersheds located in the mid-altitude regions, but it overpredicts and underpredicts in the flat and mountainous regions respectively. </p> <p> </p> <p>The second objective of this research extends the spatial application of the <i>HAND</i>-based method to the entire United States by proposing a new classification framework. The proposed framework classifies the watersheds into three groups by using seven watershed characteristics related to the topography, climate and land use. The validation results show that the average error of floodplain maps is around 14% which demonstrate the reliability and robustness of the proposed framework for continental floodplain mapping. In addition to the acceptable accuracy, the proposed framework creates the floodplain maps for any watershed within the United States. </p> <p> </p> <p>The <i>HAND</i>-based method is a deterministic modeling approach to floodplain mapping. In the third objective, the probabilistic version of this method is proposed. Using a probabilistic approach to floodplain mapping provides more informative maps. In this study, a flat watershed in the state of Kansas is selected as the case study, and the performance of four probabilistic functions for floodplain mapping is compared. The results show that a linear function with one parameter and a gamma function with two parameters are the best options for this study area. It is also shown that the proposed probabilistic approach can reduce the overpredictions and underpredictions made by the deterministic <i>HAND</i>-based approach. </p> <p> </p> <p>In the fourth objective, a new regionalization framework for transferring the calibrated environmental models to data-scarce regions is proposed. This framework aims to improve the current similarity-based regionalization methods by reducing the subjectivity that exists in the selection of basin descriptors. Using this framework for the probabilistic <i>HAND</i>-based method in the third objective, the floodplains are regionalized for a large set of watersheds in the Central United States. The results show that “vertical component of centroid (or latitude)” is the dominant descriptor of spatial variabilities in the probabilistic floodplain maps. This is an interesting finding which shows how a systematic approach can help to explore the hidden descriptors for regionalization. It is demonstrated that using common methods, such as correlation coefficient calculation, or stepwise regression analysis, will not reveal the critical role of latitude on the spatial variability of floodplains.</p>

The study aims at estimation and mapping the amount of carbon allocated in above ground biomass of wood and in organo-mineral soil horizon at sites where reclamation and spontaneous succession took place on spoil heaps after coal mining. Several categories of data have been used to meet the objectives, namely ground field measurements, laboratory analyses of soil samples, airborne hyperspectral data from VNIR region, and airborne LiDAR scanning data. The digital imagery analysis, GIS modeling and multivariation statistical methods were applied in data assessment. The results show that there is a 7 600 tons of carbon allocated in above ground wood biomass in the area of 209 ha, and 8 100?12 200 tons in the soil A horizon in the region of the same size. The results proofed: 1/ statistically significant negative relationships (p < 0,01) between slope and amount of soil carbon, where higher negative correlation was for broad leaved species; 2/ statistically significant difference (p < 0,05) between amount of soil carbon under broad leaved and needle classes and under different species, the highest between soils under Alnus sp. and Pinus sp.; 3/ statistically significant relationships (p < 0,05) between the amount of carbon allocated in the aboveground wood biomass and that in the soil A horizon under the needle leaved class and under the spontaneous wood vegetation.

abstract: Aboveground net primary production (ANPP) is an important ecosystem process that, in drylands, is most frequently limited by water availability. Water availability for plants is in part controlled by the water holding capacity of soils. Available water holding capacity (AWHC) of soils is strongly influenced by soil texture and depth. This study drew upon localized rain gauge data and four data-sets of cover-line and biomass data to estimate ANPP and to determine annual precipitation (PPT). I measured soil depth to caliche and texture by layer of 112 plots across the four landscape units for which estimation of ANPP were available. A pedotransfer function was used to estimate AWHC from soil depth increments to depth of caliche measurements and texture analysis. These data were analyzed using simple and multivariate regression to test the effect of annual precipitation and available water holding capacity on aboveground net primary production. Soil texture remained constant among all plots (sandy loam) and depth to caliche varied from 15.16 cm to 189 cm. AWHC and the interaction term (PPT*AWHC) were insignificant (p=0.142, p=0.838) and annual PPT accounted for 18.4% of the variation in ANPP. The y-intercept was significantly different for ANPP ~ annual PPT when considering AWHC values either above or below 3 cm. Shrub ANPP was insensitive to precipitation regardless of AWHC (R2=-0.012, R2=0.014). Results from this study indicate that a model incorporating annual PPT and AWHC may not serve as a good predictor for ANPP at a site level where there is little variation in soil texture. / Dissertation/Thesis / Masters Thesis Sustainability 2019

Quandles, which are algebraic structures related to knots, can be used to color knot diagrams, and the number of these colorings is called the quandle coloring invariant. We strengthen the quandle coloring invariant by considering a graph structure on the space of quandle colorings of a knot, and we call our graph the quandle coloring quiver. This structure is a categorification of the quandle coloring invariant. Then, we strengthen the quiver by decorating it with Boltzmann weights. Explicit examples of links that show that our enhancements are proper are provided, as well as background information in quandle theory.

In 2003 Cohn and Umans introduced a new group-theoretic framework for doing fast matrix multiplications, with several conjectures that would imply the matrix multiplication exponent $\omega$ is 2. Their methods have been used to match one of the fastest known algorithms by Coppersmith and Winograd, which runs in $O(n^{2.376})$ time and implies that $\omega \leq 2.376$. This thesis discusses the framework that Cohn and Umans came up with and presents some new results in constructing combinatorial objects called uniquely solvable puzzles that were introduced in a 2005 follow-up paper, and which play a crucial role in one of the $\omega = 2$ conjectures.

Estimation of biomass has high importance for economic, ecologic and climatic reasons due to the multiple ecosystem services offered by forested landscapes. Measurements that are taken in the field incur personal and economic costs. Nevertheless, biomass surveying based on remote sensing techniques offer efficiency thanks to covering large areas. The European Space Agency (ESA) Sentinel-1 satellite offers promising capabilities for above-ground biomass (AGB) estimation through synthetic aperture radar (SAR) based microwave remote sensing. In this study, experimental AGB estimations based on Sentinel-1 C-band data were produced over the Remingstorp estate (Västergötland County, Sweden) to analyze its performance over boreal productive forests. The obtained measurements were compared against reference values obtained by combining photogrammetric, aerial laser scanning (ALS) and field measurements. Thus, a reference high-resolution canopy height model (CHM) was produced from the difference between photogrammetric digital surface model (DSM) values and ALS digital terrain model (DTM) values. The comparison of CHM observations against diameter at breast height (DBH) field measurements revealed the existence of a vegetation height - vegetation volume relationship for the study species (Pinus Sylvestris and Picea Abbies), which allowed bole volume estimation based on vegetation height values. SAR-based AGB estimates were produced by defining statistical relationships between backscatter intensity and interferometric coherence measurements against reference CHM values. Additionally, evaluation of biomass estimation through interferometric (InSAR) height was possible by comparing against reference photogrammetric DSM. Backscatter signal saturation of C-band at low biomass volumes prevented quantification of biomass but permitted differentiation between forested and non-forested surfaces. Estimation of AGB through interferometric coherence was possible through modeling volumetric decorrelation, which on the contrary prevented biomass retrieval from InSAR height. Due to the given frequency properties at C-band, HV cross-polarized channel was used in all cases for better detection of the canopy layer. Image acquisition under stable conditions was a priority to avoid noise derived from variable dielectric properties, acquisition geometry effects and temporal decorrelation. Hence, image acquisitions under stable hydrometeorological conditions (i. e. stable frozen or dry) and for the lowest repeat-pass interval (i. e. 6-days) were prioritized.

Above-level testing is the practice administering a test level—of usually an academic achievement or aptitude test—to a gifted or high achieving child. This procedure is widely accepted in gifted education circles, on the basis of theoretical claims that above-level testing raises the test ceiling, increases variability among gifted students’ scores, improves reliability of data, reduces regression toward the mean, and improves interpretation of data from gifted students. However, above-level testing has not been subject to careful psychometric scrutiny. In this study, I examine reliability data, growth trajectories, distributions, and group differences of above-level test scores obtained from the Iowa Tests of Basic Skills (ITBS) and Iowa Tests of Educational Development (ITED). Subjects in this study were 224 students tested a total of 435 times while enrolled in a gifted magnet program for middle schoolers. Longitudinal analyses performed with hierarchical linear modeling indicate that substantial differences exist between students from overrepresented ethnicities (White and Asian Americans) and those from underrepresented ethnicities (Hispanic and African Americans) in both initial scores and the rate of score gains. Gender differences existed only for the rate of score increases for above-level reading scores. Socioeconomic differences existed, but did not have a unique impact beyond that of the ethnicity variable. A discussion of the place of these results within the wider gifted education research context and suggestions for further research are included. An appendix to the study gives information about item difficulty indexes for every item in the ITBS/ITED core battery for the eighth, ninth, and tenth grade levels of Form C.

Large-scale geological storage of CO₂ is likely to bring CO₂ plumes into contact with existing wellbores and faults, which can act as pathways for leakage of stored CO₂ Modeling the flux of CO₂ along a leaky pathway requires transport properties along the pathway. We provide an approach based on the analogy between the leakage pathway in wells that exhibit sustained casing pressure (SCP) and the rate-limiting part of the leakage pathway in any wellbore that CO₂ might encounter. By using field observations of SCP to estimate transport properties of a CO₂ leakage pathway, we obtain a range of CO₂ fluxes for the cases of buoyancy-driven (post-injection) and pressure-driven (during injection) leakage. The fluxes in example wells range from background levels to three orders of magnitude higher than flux at the natural CO₂ seep in Crystal Geyser, Utah. We estimate a plausible range of fault properties from field data in the Mahogany Field using a shale gouge ratio correlation. The estimated worst-case CO₂ flux is slightly above background range. The flux along fault could be attenuated to zero by permeable layers that intersect the fault. The attenuation is temporary if layers are sealed at other end. Counterintuitively, greater elevation in pressure at the base of the fault can result in less CO₂ leakage at the top of the fault, because the capillary entry pressure is exceeded for more permeable layers. Since non-negligible leakage rates are possible along wellbores, it is important to be able to diagnose whether leakage is occurring. Concurrent pressure and temperature measurements are especially valuable because they independently constrain the effective permeability of a leakage path along wellbore. We describe a simple set of coupled analytical models that enable diagnosis of above-zone monitoring data. Application to data from a monitoring well during two years of steady CO₂ injection shows that the observed pressure elevation requires a model with an extremely large leakage rate, while the temperature model shows that this rate would be large enough to raise the temperature in the monitoring zone significantly, which is not observed. The observation well is unlikely to be leaking. Extraction of brine from the aquifer offers advantage over standard storage procedure by greatly mitigating pressure elevation during CO₂ injection. A proper management of the injection process helps reduce the risk of leakage associated with wellbores and faults. We provide strategies that optimize the injection of CO₂ which involve extraction of brine in two scenarios, namely injecting dissolved CO₂ and supercritical CO₂. For surface dissolution case we are concerned with bubble point contour, while for supercritical CO₂ injection we are concerned with breakthrough of CO₂ at extractors. In a surface dissolution project, the CO₂ concentration front shape when it reaches the saturation pressure contour defines the maximum areal extent of CO₂-saturated brine and hence the aquifer utilization efficiency. We illustrate the reduction of utilization efficiency due to heterogeneity of the aquifer. We develop an optimal control strategy of the injection/extraction rates to maximize the utilization efficiency. We further propose an optimal well pattern orientation strategy. Results show that the approach nearly compensates the reduction of utilization efficiency due to heterogeneity. In a supercritical CO₂ injection that involves brine extraction, the problem of avoiding breakthrough of CO₂ at extraction wells can be addressed by optimizing flow rates at each extractor and injector to delay breakthrough as long as possible. We use the Capacitance-Resistive Model (CRM) to conduct the optimization. CRM runs rapidly and requires no prior geologic model. Fitting the model to data recorded during early stages of CO₂ injection characterizes the connectivities between injection and brine-extraction wells. The fitted model parameters are used to optimize subsequent CO₂ injection in the formation. Field illustration shows a significant improvement in CO₂ storage efficiency. / text