Some of the most problematic agricultural weeds found in the Midwest United States are found in the Amaranthaceae family, such as Amaranthus palmeri and A. tuberculatus. These summer annual weeds are troublesome due to their competitive ability, high seed production, and resistance to herbicides from several modes of action which complicates management in field crops and has led to significant yield loss. Achyranthes japonica and Iresine rhizomatosa are two perennial species in the same family as A. palmeri and A. tuberculatus that occur in similar habitats as one another, but differ in invasiveness. Achyranthes japonica is a non-native, invasive species that is becoming a threat to forested areas and has been observed along agricultural field margins. Iresine rhizomatosa also occurs in forest habitats but is an endangered species in Illinois. This research seeks to determine the comparative life history and relative competitiveness of closely related weedy species when challenged with a dominant species. Specifically, select, closely related weedy species in the Amaranthaceae plant family that occur in southern Illinois were compared, i.e., Achyranthes japonica, Amaranthus palmeri, Amaranthus tuberculatus, and Iresine rhizomatosa. The first study examined the life history characteristics of A. japonica in regards to survivorship, growth and fecundity at two sites in southern Illinois (Chapter 2). Achyranthes japonica is a relatively new invasive species that has been poorly studied. This experiment showed that regardless of site, environmental factors had a significant effect on seedling emergence and seed viability, which decreased from 2012 to 2013 during a drought year and rebounded from 2013 to 2014 following flooding. On average, individuals at the driest site had higher performance and fecundity, regardless of year. The second experiment tested the relative competitive effect and response of the Amaranthaceae species to Glycine max, first in a greenhouse study that tested shading and nitrogen resource drawdown for each species, and second in a controlled field experiment that tested intraspecific competition (Chapter 3). In addition, A. japonica seedlings were planted as either unmanipulated seedlings (uncut A. japonica) or as a seedling cut back to the soil surface at the four-node stage (cut A. japonica) at which point seedlings have reached a perennial growth stage. The greenhouse experiment showed that the four species each drew down light significantly, but not nitrogen. Shading decreased the aboveground biomass of the species in comparison to unshaded controls. Supplemental nitrogen, however, increased the aboveground biomass of A. palmeri and A. japonica. The supporting controlled field experiment showed that the competitive response of the weed species to the presence of G. max showed a reduction in height compared to the weed species grown in monocultures. Glycine max and the weed species, except I. rhizomatosa, showed a similar competitive effect and response when aboveground biomass was measured. Achyranthes japonica attained the highest belowground biomass when grown as a monoculture and in the presence of G. max. A competitive effect ranking was determined to be A. palmeri > A. tuberculatus > cut A. japonica = uncut A. japonica = I. rhizomatosa with the competitive response ranking being the inverse. The third study implemented an integral projection model (IPM) to determine the population growth rate of each species and how they compared to one another (Chapter 4). This experiment showed that A. palmeri, A. tuberculatus and A. japonica each had a population growth rate greater than one indicating rapidly growing populations. By contrast, I. rhizomatosa had a population growth rate less than one indicating a declining population. The results suggest that A. japonica has not yet shown the ability to escape management strategies in agricultural fields implemented by farmers, but it is still an aggressive invasive species that farmers and land owners need to be able to identify. This species has many similar characteristics to the Amaranthus species, such as the ability to colonize in areas with limiting resources, continual flushes of germination throughout the growing season, the ability to outcompete other weed species, and high fecundity but, A. japonica also is a perennial species that can withstand removal of shoot material and has a high germination rate. Based on these results, only early detection and rapid response methods should be relied on to keep these species out of areas in and around agricultural fields. Iresine rhizomatosa’s performance in these studies was consistent with its rarity.

No description available.

No description available.

Evolutionary relationships are key to modern understanding of biological systems. Phylogenetic search is the means by which these relationships are inferred. Phylogenetic search is NP-Hard. As such it is necessary to employ heuristic methods. This work proposes new methods based on viewing the relationships between species as sets of partitions. These methods produce more parsimonious phylogenies than current methods.

京都大学 / 新制・課程博士 / 博士(人間健康科学) / 甲第24143号 / 人健博第106号 / 新制||人健||7(附属図書館) / 京都大学大学院医学研究科人間健康科学系専攻 / (主査)教授 十一 元三, 教授 澤本 伸克, 教授 村井 俊哉 / 学位規則第4条第1項該当 / Doctor of Human Health Sciences / Kyoto University / DFAM

Climate change is one of the most challenging and defining issues that has resulted in substantial societal, economic, and environmental impacts across the world. To assess the potential climate change impact, climate projections are generated with General Circulation Models (GCMs). However, the climate change signals remain uncertain and GCMs have difficulty in representing regional climate features. Therefore, comprehensive knowledge of climate change signals and reliable high-resolution climate projections are highly desired. This dissertation aims to address such challenges by developing climate projections with multi-model ensembles for climate impact assessment. This includes: i) developing multi-model ensembles to analyze global changes in all water components within the hydrological cycle and quantify the uncertainties with GCM projections; ii) development of bias correction models for generating high-resolution daily maximum and minimum temperature projections with individual GCMs and multi-model ensemble means over Canada; iii) proposing bias correction models with individual GCMs and multi-model ensemble means for high-resolution daily precipitation projections for Canada. The proposed models are capable of developing high-resolution climate projections at a regional scale and exploring the climate change signals. The reliable climate projections generated could provide valuable information for formulating appropriate climate change mitigation and adaptation strategies across the world. / Thesis / Doctor of Philosophy (PhD)

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No description available.

Informed forest management requires accurate, up-to-date information. Ground-based forest inventory is commonly conducted to generate estimates of forest characteristics with a predetermined level of statistical confidence. As the importance of monitoring forest resources has increased, budgetary and logistical constraints often limit the resources needed for precise estimates. In this research, the incorporation of ancillary information in planted loblolly pine (Pinus taeda L.) forest inventory was investigated. Additionally, a simulation study using synthetic populations provided the basis for investigating the effects of plot and stand-level inventory aggregations on predictions and projections of future forest conditions. Forest regeneration surveys are important for assessing conditions immediately after plantation establishment. An unmanned aircraft system was evaluated for its ability to capture imagery that could be used to automate seedling counting using two computer vision approaches. The imagery was found to be unreliable for consistent detection in the conditions evaluated. Following establishment, conditions are assessed throughout the lifespan of forest plantations. Using small area estimation (SAE) methods, the incorporation of light detection and ranging (lidar) and thinning status improved the precision of inventory estimates compared with ground data alone. Further investigation found that reduced density lidar point clouds and lower resolution elevation models could be used to generate estimates with similar increases in precision. Individual tree detection estimates of stand density were found to provide minimal improvements in estimation precision when incorporated into the SAE models. Plot and stand level inventory aggregations were found to provide similar estimates of future conditions in simulated stands without high levels of spatial heterogeneity. Significant differences were noted when spatial heterogeneity was high. Model form was found to have a more significant effect on the observed differences than plot size or thinning status. The results of this research are of interest to forest managers who regularly conduct forest inventories and generate estimates of future stand conditions. The incorporation of auxiliary data in mid-rotation stands using SAE techniques improved estimate precision in most cases. Further, guidance on strategies for using this information for predicting future conditions is provided. / Doctor of Philosophy / Informed forest management requires accurate, up-to-date information. Groundbased sampling (inventory) is commonly used to generate estimates of forest characteristics such as total wood volume, stem density per unit area, heights, and regeneration survival. As the importance of assessing forest resources has increased, resources are often not available to conduct proper assessments. In this research, the incorporation of ancillary information in planted loblolly pine (Pinus taeda L.) forest inventory was investigated. Additionally, a simulation study investigated the effects of two forest inventory data aggregation methods on predictions and projections of future forest conditions. Forest regeneration surveys are important for assessing conditions immediately after tree planting. An unmanned aircraft system was evaluated for its ability to capture imagery that could be used to automate seedling counting. The imagery was found to be unreliable for use in accurately detecting seedlings in the conditions evaluated. Following establishment, forest conditions are assessed at additional points in forest development. Using a class of statistical estimators known as small-area estimation, a combination of ground and light detection and ranging data generated more confident estimates of forest conditions. Further investigation found that more coarse ancillary information can be used with similar confidence in the conditions evaluated. Forest inventory data are used to generate estimates of future conditions needed for management decisions. The final component of this research found that there are significant differences between two inventory data aggregation strategies when forest conditions are highly spatially variable. The results of this research are of interest to forest managers who regularly assess forest resources with inventories and models. The incorporation of ancillary information has potential to enhance forest resource assessments. Further, managers have guidance on strategies for using this information for estimating future conditions.

Vat photopolymerization's (VP) use in large-scale industrial manufacturing is limited due to poor scalability, and limited catalogue of engineering polymers. The challenges in scalability stem from an inherent process paradox: the feature resolution, part size, and manufacturing throughput cannot be maximized simultaneously in standard VP platforms. In addition, VP's inability to process viscous and high-molecular weight engineering polymers limits the VP materials catalogue. To address these limitations, the research presented in this work was conducted in two stages: (1) Development and modeling of new VP platforms to address the scalability and viscosity challenges, and (2) Investigating the influence of using the new processes on the cured polymer network structure and mechanical properties. First, a scanning mask projection vat photopolymerization (S-MPVP) system was developed to address the scalability limitations in VP systems. The process paradox was resolved by scanning the mask projection device across the resin surface while simultaneously projecting the layer as a movie. Using actual projected pixel irradiance distribution, a process model was developed to capture the interaction between projected pixels and the resin, and predict the resulting cure profile with an error of 2.9%. The S-MPVP model was then extended for processing heterogeneous UV scattering resins (i.e. UV curable polymer colloids). Using computer vision, the scattering of incident UV radiation on the resin surface was successfully captured and used to predict scattering-compensated printing parameters (bitmap pattern, exposure time , scanning speed). The developed reverse-curing model was used to successfully fabricate complex features using photocurable SBR latex with XY errors < 1.3%. To address the low manufacturing throughput of VP systems, a recoat-less, volumetric curing VP system that fabricates parts by continuously irradiating the resin surface with a movie composed of different gray-scaled bitmap images ( Free-surface movie mask projection (FreeMMaP)) was developed. The effect of cumulative exposure on the cure profile (X,Y,Z dimensions) was investigated and used to develop an iterative gray-scaling algorithm that generated a combination of gray-scaled bitmap images and exposure times that result in accurate volumetric curing (errors in XY plane and Z axis < 5% and 3% respectively). Results of this work demonstrate that the elimination of the recoating process increased manufacturing speed by 8.05 times and enabled high-resolution fabrication with highly viscous resins or soft gels. Then, highly viscous resins were made processible in VP systems by using elevated processing temperatures to lower resin viscosity. New characterization techniques were developed to determine the threshold printing temperature and time that prevented the onset of thermally-induced polymerization. The effect of printing temperature on curing, cured polymer structure, cured polymer mechanical properties, and printable aspect ratio was also investigated using diacrylate and dimethacrylate resins. Results of this investigation revealed increasing printing temperature resulted in improvements in crosslink density, tensile strength, and printability. However, presence of hydroxl groups on the resin backbone caused deterioration of crosslink density, mechanical properties, and curing properties at elevated printing temperatures. Finally, the lack of a systematic, constraint based approach to resin design was bridged by using the results of earlier process-structure-property explorations to create an intuitive framework for resin screening and design. Key screening parameters (such as UV absorptivity, plateau storage modulus) and design parameters (such as photoinitiator concentration, polymer concentration, UV blocker concentration) were identified and the methods to optimize them to meet the desired printability metrics were demonstrated using case studies. Most work in vat photopolymerization either deal with materials development or process development and modeling. This dissertation is placed at the intersection of process development and materials development, thus giving it an unique perspective for exploring the inter-dependency of machine and material. The process models, machines and techniques used in this work to make a material printable will serve as a guide for chemists and engineers working on the next generation of vat photopolymerization machines and materials. / Doctor of Philosophy / Vat Photopolymerization (VP) is a polymer-based additive manufacturing platform that uses UV light to cure a photo-sensitive polymer into the desired shape. While parts fabricated via VP exhibit excellent surface finish and high-feature resolution, their use for commercial manufacturing is limited because of its poor scalability for large-scale manufacturing and limited selection of engineering materials. This work focuses on the development of new VP platforms, process models and the investigation of the process-structure-property relationships to mitigate these limitations and enable fabrication of performance polymers. The first section of the dissertation presents the development of two new VP platforms to address the limitations in scalability. The Scanning Mask Projection Vat Photopolymerization (S-MPVP)) was developed to fabricate large area parts with high-resolution features and the Free-surface movie mask projection (FreeMMaP) VP platform was developed to enable high-speed, recoat-less, volumetric fabrication of 3D objects. Computer-vision based models were developed to investigate the influence of these new processes on the resultant cure shape and dimensional accuracy. Process models that can: (1) predict the cure profile for given input printing parameters (error < 3%), (2) predict the printing parameters (exposure time, bitmap gray-scaling) required for accurate part fabrication in homogeneous and UV scattering resins, and (3) generate gray-scaled bitmap images that can induce volumetric curing inside the resin (dimensional accuracy of 97% Z axis, 95% XY axis), were designed and demonstrated successfully. In the second portion of this work, the use of high-temperature VP to enable processing of high-viscosity resins and expansion of materials catalogue is presented. New methods to characterize the resin's thermal stability are developed. Techniques to determine the printing temperature and time that will prevent the occurrence of thermally-induced polymerization are demonstrated. Parts were fabricated at different printing temperatures and the influence of printing temperature on the resultant mechanical properties and polymer network structure was studied. Results of this work indicate that elevated printing temperature can be used to alter the final mechanical properties of the printed part and improve the printability of the high-resolution, slender features. Finally, the results of the process-structure-property investigations conducted in this work were used to guide the development of a resin design framework that highlights the parameters, metrics, and methods required to (1) identify printable resin formulations, and (2) tune printable formulations for optimal photocuring. Elements of this framework were then combined into an intuitive flowchart to serve as a design tool for chemists and engineers.