<p>Cnidarians are often considered simple animals, but the more than 13,000 estimated species (e.g., corals, hydroids and jellyfish) of the early diverging phylum exhibit a broad diversity of forms, functions and behaviors, some of which are demonstrably complex. In particular, cubozoans (box jellyfish) are cnidarians that have evolved a number of distinguishing features. Some cubozoan species possess complex mating behaviors or particularly potent stings, and all possess well-developed light sensation involving image-forming eyes. Like all cnidarians, cubozoans have specialized subcellular structures called nematocysts that are used in prey capture and defense. The objective of this study is to contribute to the development of the box jellyfish Alatina alata as a model cnidarian. This cubozoan species offers numerous advantages for investigating morphological and molecular traits underlying complex processes and coordinated behavior in free-living medusozoans (i.e., jellyfish), and more broadly throughout Metazoa. First, I provide an overview of Cnidaria with an emphasis on the current understanding of genes and proteins implicated in complex biological processes in a few select cnidarians. Second, to further develop resources for A. alata, I provide a formal redescription of this cubozoan and establish a neotype specimen voucher, which serve to stabilize the taxonomy of the species. Third, I generate the first functionally annotated transcriptome of adult and larval A. alata tissue and apply preliminary differential expression analyses to identify candidate genes implicated broadly in biological processes related to prey capture and defense, vision and the phototransduction pathway and sexual reproduction and gametogenesis. Fourth, to better understand venom diversity and mechanisms controlling venom synthesis in A. alata, I use bioinformatics to investigate gene candidates with dual roles in venom and digestion, and review the biology of prey capture and digestion in cubozoans. The morphological and molecular resources presented herein contribute to understanding the evolution of cubozoan characteristics and serve to facilitate further research on this emerging cubozoan model.

A dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of requirements for the degree of Master of Science. August 2015. / iii ABSTRACT Global changes are likely to have negative impacts on many ecosystems including savannas. Semi-arid environments are notable for the wide range of seasonal patterns of leaf display in the tree communities. The environmental cues of leaf out and leaf drop are not consistent across species, and are not always directly linked to water availability, indicating that some species might be particularly sensitive to changes in climate. Strategies employed by trees which leaf early or drop their leaves late are likely to impact other aspects of their life-history and functioning so I expect particular plant functional types to be associated with particular vegetation functional traits. I assessed how variable savanna leafing strategies are among 28 species at a semi-arid savanna site at Nylsvley, and used this information to group species into plant functional types (PFTs). These PFTs were then assessed in terms of key vegetative traits to explore the life history consequences of different leafing strategies. Leaf phenology was monitored throughout one growing season and quantified using 8 key phenological metrics. The timing of leaf display tracks the timing of seasonal rainfall but with wide variation, with some species retaining their leaves throughout dry season. Other species loss some leaves throughout the growing season, some species only flushed their leaves after the first rains, and other flush before the first rains. I identified 4 clear PFTs using the MClust clustering integrated with subjective procedure. Four vegetative traits were measured: specific leaf area, leaf nitrogen, maximum stomatal conductance and wood density. I identified some clear trade-offs between vegetative traits and phenological strategies. There was also a positive relationship between degree of rain stimulated flushing metric and wood density. Using objective clustering methods to determine plant functional types has some clear advantages over more subjective methods but depends on good input data. Identifying plant functional types at Nylsvley has led to some insights into functioning of these savannas, but as there appear to be strong links between plant traits and particular leafing strategies it might be more appropriate to explore syndromes of vegetation functional traits when modelling responses to global change.

Many phenomena in ecology, evolution, and organismal biology relate to how a system changes through time. Unfortunately, most of the statistical methods that are common in these fields represent samples as static scalars or vectors. Since variables in temporally-dynamic systems do not have stable values this representation is unideal. Differential equation and basis function representations provide alternative systems for description, but they are also not without drawbacks of their own. Differential equations are typically outside the scope of statistical inference, and basis function representations rely on functions that solely relate to the original data in regards to qualitative appearance, not in regards to any property of the original system. In this dissertation, I propose that vector autoregressive-moving average (VARMA) and vector autoregressive (VAR) processes can represent temporally-dynamic systems. Under this strategy, each sample is a time series, instead of a scalar or vector. Unlike differential equations, these representations facilitate statistical description and inference, and, unlike basis function representations, these processes directly relate to an emergent property of dynamic systems, their cross-covariance structure. In the first chapter, I describe how VAR representations for biological systems lead to both a metric for the difference between systems, the Euclidean process distance, and to a statistical test to assess whether two time series may have originated from a single VAR process, the likelihood ratio test for a common process. Using simulated time series, I demonstrate that the likelihood ratio test for a common process has a true Type I error rate that is close to the pre-specified nominal error rate, regardless of the number of subseries in the system or of the order of the processes. Further, using the Euclidean process distance as a measure of difference, I establish power curves for the test using logistic regression. The test has a high probability of rejecting a false null hypothesis, even for modest differences between series. In addition, I illustrate that if two competitors follow the Lotka-Volterra equations for competition with some additional white noise, the system deviates from VAR assumptions. Yet, the test can still differentiate between a simulation based on these equations in which the constraints on the system change and a simulation where the constraints do not change. Although the Type I error rate is inflated in this scenario, the degree of inflation does not appear to be larger when the system deviates more noticeably from model assumptions. In the second chapter, I investigate the likelihood ratio test for a common process's performance with shape trajectory data. Shape trajectories are an extension of geometric morphometric data in which a sample is a set of temporally-ordered shapes as opposed to a single static shape. Like all geometric morphometric data, each shape in a trajectory is inherently high-dimensional. Since the number of parameters in a VAR representation grows quadratically with the number of subseries, shape trajectory data will often require dimension reduction before a VAR representation can be estimated, but the effects that this reduction will have on subsequent inferences remains unclear. In this study, I simulated shape trajectories based on the movements of roundworms. I then reduced the number of variables that described each shape using principle components analysis. Based on these lower dimensional representations, I estimated the likelihood ratio test's Type I error rate and power with the simulated trajectories. In addition, I also used the same workflow on an empirical dataset of women walking (originally from Morris13) but also tried varying amounts of preprocessing before applying the workflow as well. The likelihood ratio test's Type I error rate was mildly inflated with the simulated shape trajectories but had a high probability of rejecting false null hypotheses. Without preprocessing, the likelihood ratio test for a common process had a highly inflated Type I error rate with the empirical data, but when the sampling density is lowered and the number of cycles is standardized within a comparison the degree of inflation becomes comparable to that of the simulated shape trajectories. Yet, these preprocessing steps do not appear to negatively impact the test's power. Visualization is a crucial step in geometric morphometric studies, but there are currently few, if any, methods to visualize differences in shape trajectories. To address this absence, I propose an extension to the classic vector-displacement diagram. In this new procedure, the VAR representations for two trajectories' processes generate two simulated trajectories that share the same shocks. Then, a vector-displacement diagram compares the simulated shapes at each time step. The set of all diagrams then illustrates the difference between the trajectories' processes. I assessed the validity of this procedure using two simulated shape trajectories, one based on the movements of roundworms and the other on the movements of earthworms. The result provided mixed results. Some diagrams do show comparisons between shapes that are similar to those in the original trajectories but others do not. Of particular note, diagrams show a bias towards whichever trajectory's process was used to generate pseudo-random shocks. This implies that the shocks to the system are just as crucial a component to a trajectory's behavior as the VAR model itself. Finally, in the third chapter I discuss a new R library to study dynamic systems and represent them as VAR and VARMA processes, iPARMA. Since certain processes can have multiple VARMA representations, the routines in this library place an emphasis on the reverse echelon format. For every process, there is only one VARMA model in reverse echelon format. The routines in iPARMA cover a diverse set of topics, but they all generally fall into one of four categories: simulation and study, model estimation, hypothesis testing, and visualization methods for shape trajectories. Within the chapter, I discuss highlights and features of key routines' algorithms, as well as how they differ from analogous routines in the R package MTS \citep{mtsCite}. In many regards, this dissertation is foundational, so it provides a number of lines for future research. One major area for further work involves alternative ways to represent a system as a VAR or VARMA process. For example, the parameter estimates in a VAR or VARMA model could depict a process as a point in parameter space. Other potentially fruitful areas include the extension of representational applications to other families of time series models, such as co-integrated models, or altering the generalized Procrustes algorithm to better suit shape trajectories. Based on these extensions, it is my hope that statistical inference based on stochastic process representations will help to progress what systems biologists are able to study and what questions they are able to answer about them. / A Dissertation submitted to the Department of Scientific Computing in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2017. / May 3, 2017. / Function-valued Trait, Geometric morphometrics, Shape trajectory, Stochastic process, Time series analysis, Vector autoregressive-moving average (VARMA) model / Includes bibliographical references. / Dennis E. Slice, Professor Directing Dissertation; Paul M. Beaumont, University Representative; Peter Beerli, Committee Member; Anke Meyer-Baese, Committee Member; Sachin Shanbhag, Committee Member.

The ASE neurons of C. elegans are an excellent model to study neuronal asymmetry. Lateralization with respect to their genetic fate and function has been well studied, but their more subtle asymmetries have not. This work describes three such asymmetries: that of amino acid gustation, associative learning, and morphological size. In the first two of these, I found a previously uncharacterized asymmetric neuronal response with respect to amino acid gustation, and expand on the known asymmetry with respect to associative salt learning. Most of this thesis focuses on a discovered size asymmetry in the ASE pair of neurons: characterizing it, providing a functional significance, and describing some of its genetic underpinnings. Size asymmetry and the mechanisms of overall neuron growth are not well-studied, but do have functional consequences in higher organisms. This work hopefully furthers our understandings of these processes and of neuronal development in general.

Morphologies include the study of shape, size and structure for materials from atomic scale to macroscales. Properties/functions of material structures in general are dependent on morphologies, and tunable properties in chemical and physical can be realized through changing morphologies on surfaces and in bulk systems of materials. For low-dimensional materials, atomic modifications and changes in lattice morphologies can introduce varieties of fascinating phenomena and unconventional intrinsic properties in electric, mechanics chemistry and etc. The reason behind such controllability is that morphological undulation usually is consistent with the mapping of strain, which is related to atomic structures of materials. For micro/macro scale materials, interactions of surface tension, mechanical deformation, etc. dominate the morphological evolution. Structural designs and morphological control can achieve desirable functionalities, for example mechanical flexibility and liquid wettability for practical applications. Herein, strain-engineering strategies including mechanical loading and atomic displacement were applied to modify and control morphologies in materials with different length scales. We firstly investigated the fundamental mechanism of morphological evolution through various load strategies, and relationship between morphologies and the properties of material structures across from nanoscale, microscale to macroscale, including graphene, phosphorene, core-shell microparticles and soft materials/bilayers, etc. Furthermore, we demonstrated to two applications of utilizing designed morphologies, which targeted to figures out challenges in the field of energy conversion and storage to close energy loop. Therefore, we mainly focus on the relation of engineered strategy-morphology-mechanism/property-functional devices in this thesis. Firstly, engineered morphologies in nanomaterials of graphene and phosphorene were investigated through strain-localization, gradient strain, bending/pressing. The effects of surface morphologies on fundamental properties including thermal conductivities, mechanics, electrics, surface energy and chemical reactivities were studied through molecular dynamics (MD) simulations and first-principle calculations combined with experimental verifications: Increased applications of nanoporous graphene in nanoelectronics and membrane separations require ordered and precise perforation of graphene, whose scalablility and time/cost effectiveness represent a significant challenge in existing nanoperforation methods, such as catalytical etching and lithography. We reported a strain-guided perforation of graphene through oxidative etching, where nanopores nucleate selectively at the bulges induced by the pre-patterned nano-protrusions underneath. Using reactive molecular dynamics and theoretical models, we uncover the perforation mechanisms through the relationship between bulge-induced strain and enhanced etching reactivity. Parallel experiments of CVD graphene on SiO2 NPs/ SiO2 substrate verify the feasibility of such strain-guided perforation and evolution of pore size by exposure durations to oxygen plasma. When a nanodroplet is placed on a lattice surface, an inhomogeneous surface strain field perturbs the balance of van der Waals force between the nanodroplet and surface, thus providing a net driving force for nanodroplet motion. Using molecular dynamics and theoretical analysis, we studied the effect of strain gradient on modulating the movement of a nanodroplet. Both modeling and simulation showed that the driving force is opposite to the direction of strain gradient, with a magnitude that is proportional to the strain gradient as well as nanodroplet size. Two representative surfaces, graphene and copper (111) plane, were exemplified to demonstrate the controllable motion of nanodroplet. When the substrate underwent various types of reversible deformations, multiple motion modes of nanodroplets could be feasibly achieved, including acceleration, deceleration and turning, becoming a facile strategy to manipulate nanodroplets along a designed 2D pathway. Using molecular dynamics (MD) simulations, we explored the structural stability and mechanical integrity of phosphorene nanotubes (PNTs), where the intrinsic strain in the tubular PNT structure plays an important role. It was proposed that the atomic structure of larger-diameter armchair PNTs (armPNTs) could remain stable at higher temperature, but the high intrinsic strain in the hoop direction renders zigzag PNTs (zigPNTs) less favorable. The mechanical properties of PNTs, including the Young’s modulus and fracture strength, are sensitive to the diameter, showing a size dependence. A simple model is proposed to express the Young’s modulus as a function of the intrinsic axial strain which in turns depends on the diameter of PNTs. A new phosphorous allotrope, closed-edged bilayer phosphorene nanoribbon, was proposed via radially deforming armchair phosphorene nanotubes. Using molecular dynamics simulations, the transformation pathway from round phosphorene nanotubes falls into two types of collapsed structures: arc-like and sigmoidal bilayer nanoribbons, dependent on the number of phosphorene unit cells. The fabricated nanoribbions are energetically more stable than their parent nanotubes. It was also found via ab initio calculations that the band structure along tube axis substantially changes with the structural transformation. The direct-to-indirect transition of band gap was highlighted when collapsing into the arc-like nanoribbons but not the sigmoidal ones. Furthermore, the band gaps of these two types of nanoribbons showed significant size-dependence of the nanoribbon width, indicative of wider tunability of their electrical properties. Secondly, we studied fundamental mechanisms of generating fascinating surface morphologies on the micro materials/structures of core/shell microsphere driven by surface instability, which is not different those in nanoscale. The island-like dot pattern on spherical substrate were investigated: Through strain-induced morphological instability, protruding patterns of roughly commensurate nanostructures are self-assembled on the surface of spherical core/shell systems. A three-dimensional (3D) phase field model was established for closed substrate. We investigated both numerically and analytically the kinetics of the morphological evolution, from grooves to separated islands which are sensitive to substrate curvature, misfit strain and modulus ratio between core and shell. The faster growth rate of surface undulation was associated with the core/shell system of harder substrate, larger radius or misfit strain. Based on a Ag core/SiO2 shell system, the self-assemblies of SiO2 nano-islands were explored experimentally. The numerical and experimental studies herein could guide the fabrication of ordered quantum structures via surface instability on closed and curved substrates. Up to macroscale material structures, the variety and controllability surface morphologies on soft materials and bilayer films were realized through pre-pattern defects of cavities and in-plane compression. The checkboard and wrinkling surface patterns were observed in different systems through both finite element simulations and 3D printing technique: A rich diversity of surface topologies is controllably engineered by patterning cavities embedded beneath the surface of soft materials. Upon external compression, the surface undergoes the reversible transformation from the flat surface to various surface topographies, including the periodic checkerboard pattern with alternatively convex and concave features. To design the surface features, both 2D and 3D finite element based-simulations were performed. It was demonstrated that the periodic surface features with controllable morphology, such as 1D waves, checkerboard pattern and mutually perpendicular apexes, etc. can be realized through varying cavity geometries (e.g., relative inter-cavity distance, shapes and biaxial/uniaxial load). Based on 3D printed prototypes, we further conducted experiments to validate the simulation results of 2D morphologies. The patterned cavities in soft materials made designing a variety of reversible surface features possible, offering an effective fabrication approach for wide application across multiple scales. Wrinkle formation followed by sharp strain localization is commonly observed in compressed stiff film/soft substrate systems. However, cavities or defects beneath the film may directly trigger the formation of local ridges and then folding configurations at a relatively small compressive strain, and a mixture of wrinkles and folds upon further compression. The morphological transition is different than those of defect-free substrates. Numerical simulations of continuously compressed bilayer with pre-patterned cavities were carried out to elucidate the transition mechanism of surface patterns. Parallel experiments of cavities-patterned bilayer prototypes by 3D-printing were also performed to validate the findings in simulations. A rich diversity of periodic surface topologies, including overall spreading waves, localizations, saw-like and co-existing features of folds and wrinkles can be obtained by varying the diameter, depth and spacing of cavities, which provides a potential approach to engineer various surface patterns for applications. Since these discussed material structures are promising candidates for energy/environmental applications, two device-level functional systems/products here utilize intriguing morphologies in both nanoscale and macroscale. To close energy loop, the energy conversion reactor (chemical loop reduction of CO2) and the energy storage device (flexible lithium ion battery) were demonstrated: We reported an effective reduction method for splitting air-containing CO2 into CO for high-value chemicals, through a chemical looping redox scheme with Cu-doped LaFeO3 perovskites as efficient oxygen carriers for splitting CO2 with a high-concentration of O2 (e.g. 1:5 O2/CO2 molar ratio, mimicking 1:1 CO2/air mixture). Up to 2.28 mol/kg CO yield was achieved with good stability in the CO2 splitter, five times higher than that with the conventional pristine LaFeO3 perovskite. Through ab initio calculations, we uncovered that the exsolution of metallic Cu on the surface of reduced perovskite is capable of mitigating the competition between CO2 and O2 for the re-oxidation step. This air-stable and scalable scheme can economically integrate with upstream DAC and downstream gas-to-liquids plants, exhibiting up to 94.5% and 42.8% reduction in net CO2 emission for valuable chemicals production (methanol and acetic acid) when compared with the coal gasifier-based route and this redox scheme using pure CO2, respectively. Flexible batteries, seamlessly compatible with flexible and wearable electronics, attract a great deal of research attention. Current designs of flexible batteries are unable to meet one of the most extreme yet common deformation scenarios in practice, folding, while retaining high energy density. Inspired by origami folding, we proposed a novel strategy to fabricate zigzag-like lithium ion batteries with superior foldability. The battery structure could approach zero-gap between two adjacent energy storage segments, achieving an energy density that is 96.4% of that in a conventional stacking cell. A foldable battery thus fabricated demonstrated an energy density of 275 Wh L-1 and was resilient to fatigue over 45,000 dynamic cycles with a folding angle of 130°, while retaining stable electrochemical performance. Additionally, the power stability and resilience to nail shorting of the foldable battery were also examined.

Master of Science / Department of Biology / Michael Tobler / Natural selection drives the evolution of traits to optimize organismal performance, but optimization of one aspect of performance can often influence other aspects of performance. Here, we asked how phenotypic variation between locally adapted fish populations affect locomotion and ventilation, testing for functional trade-offs as well as trait-performance correlations. Specifically, we investigated two populations of livebearing fish (Poecilia mexicana) that inhabit distinct habitat types (hydrogen-sulfide-rich springs and adjacent nonsulfidic streams). For each individual fish, we quantified different metrics of burst-start swimming during simulated predator attacks, steady swimming, as well as gill ventilation. Coinciding with theoretical predictions, we documented significant population differences in all aspects of performance, with fish from sulfidic habitats exhibiting higher steady swimming performance and higher ventilation capacity but slower burst-starts. There was a significant functional trade-off between steady and burst-speed swimming, but not between different aspects of locomotion and ventilation, indicating modularity of traits associated with either aspect of function. While our findings about population differences in locomotion performance largely parallel the results from previous studies, we provide novel insights about how morphological variation might impact ventilation and ultimately oxygen acquisition. Overall, our analyses provided insights into the functional consequences of previously documented phenotypic variation, which will help to disentangle the effects of different sources of selection that may coincide along complex environmental gradients.

Typescript. / Digitized by Kansas Correctional Industries

The interrelationship of the chondrichthyan subclasses is evaluated based on divergence in the nature of the suspensorium, the preorbital cranial anatomy, the distribution of major venous sinuses and localization of hematopoietic tissue. The anatomy of representative extant taxa was examined by radiography and/or dissection. Fossil selachians, paraselachians, and holocephalans of the Bear Gulch of Montana, U.S.A. (Mississippian, Namurian E2B) were studied for evidence of vascular pigmentation, suspensorium, and cranial, branchial, and pectoral anatomy. These studies validate the suspensorial condition of autodiastyly and suggest autodiastyly is a fundamental condition involved in the basic radiation of Chondrichthyes. The plesiomorphous condition of all gnathostomes is proposed to be sutodiastylic, with the hyoid arch modified for the support of an opercular covering. A precerebral fontanelle is primary within Chondrichthyes, being lost in Holocephali as cranial remodeling induces ethmoid canal formation. The holocephalan pattern of cranial vascularization is based on the more general selachian plan. Thus, given the formulation of a morphocline based on selachian, paraselachian, and holocephalan data, seemingly distinct selachian and holocephalan vascular elements are shown to be analogous. Similarly, the unique patterns of lymphomyeloid tissue distribution identified for each subclass may also be explained on the basis of general plan which has been subject to relocalization stresses. Finally, both the morphocline and a cladistical analysis of the data support a cochliodont ancestry for extant holocephalans.

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