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Validation of a Device for High-Throughput Phenotyping of Wheat Stem Flexural Rigidity
No full textWheat breeders develop new crop varieties each year with a goal to improve yields and to improve farmer success. Farmer success is threatened by stalk lodging, failure of crop stems due to high winds. Selective breeding can be used to mitigate stalk lodging by introducing varieties with enhanced bending strength characteristics. To aid breeders in identifying structurally robust stalks, a high-throughput device known as SOCEM (Strength of Crops Extrapolation Machine) can be used to identify which genetic varieties of wheat are stalk lodging resistant. Data gathered with the field-deploying SOCEM device was compared to three-point bending test results of wheat stems conducted on a universal testing machine. SOCEM results were also compared to historical reports of actual lodging percentages. In both cases the SOCEM produced accurate assessments of the structural robustness of wheat varieties. A key advantage of the SOCEM is that the data collection is faster and cheaper compared to conducting three-point bending tests or assessing lodging percentages. Data gathered with the SOCEM device could potentially supplant lodging percentage values published in variety trials and yield reports in the future and become the standard by which lodging is assessed. Data from the SOCEM provides increased numerical granularity compared to lodging percentage values and is not directly confounded by uncontrolled weather events.masters, M.S., Mechanical Engineering -- University of Idaho - College of Graduate Studies, 2022-1
A Man Says Wilderness
No full textWhen a man from the Western United States says “wilderness” what does he mean? How does he navigate these spaces? How does he relate his domestic settings with the rough land he regularly visits? Where do the borders and edges lie between those spaces? What does it look like when a man brings “wilderness” home? And finally, how do these men share intimate moments, whether violent or tender?These are the main questions I explore in this body of work. My main source is observing men in the Western United States who regularly make trips into wilderness areas. My goal is to transfigure their behavior and sensibilities into more observable forms which, in turn, gives the viewer opportunities to expand and evolve the notions they hold toward the Western United States and the people inhabiting it. I use watercolor paintings, photography, and cut paper in this effort.masters, M.F.A., Art and Architecture -- University of Idaho - College of Graduate Studies, 2022-0
Ethnography of Lunch Ladies in a Rural Community
No full textThis thesis is an ethnographic study of lunch ladies in the rural setting of Moscow, Idaho. The purpose of this research is to understand and explain the centrality of their roles within the educational food system, both as nurturers and intermediaries in federal meal programs. The existing literature surrounding this topic, often focuses on the logistics of federal policies, the nutritional policies of these policies or its relation to commercial agriculture, while little is focused on the responsibilities of the lunch ladies. This thesis examines the lived experiences of lunch ladies in a rural community through an ethnographic framework. I collected data through interviews with the lunch ladies and non-participant observations in the lunchroom. Findings from this research include COVID-19 as having both a positive and negative impact to the workplace, governmental policy in the kitchen and community mothering. The lunch ladies believe their work serving the community by physically feeding students and teaching them valuable skills.masters, M.A., Culture, Society & Justice -- University of Idaho - College of Graduate Studies, 2022-0
Application of Elastic Net Regression for Modeling COVID-19 Sociodemographic Risk Factors
No full textCOVID-19 has been at the forefront of global concern since its emergence in Decemberof 2019. Determining the social factors that drive case incidence is paramount to mitigating disease spread. Simple predictive analysis in the form of multiple regression proves to be an inefficient method for predicting COVID-19 case rate using sociodemographic factors, as many of these factors are collinear; additionally, multiple regression is insufficient as this technique results in models that overfit the data, meaning the models cannot generalize when given new data and thus perform poorly. As such, biased estimation through elastic net regression was used to conduct a broad-based analysis across the ten HHS health regions for both the pre-Delta (March 22, 2020 to June 15, 2021) and Delta (June 15, 2021 to November 1, 2021) waves of the COVID-19 pandemic. Statistically, elastic net proved to be much more accurate in its prediction when compared to multiple regression, as almost every HHS model consistently had a lower root mean square error (RMSE); additionally, these models also succeeded in remedying overfitting through verification by way of training/testing R2 evaluation. From an epidemiological standpoint, this research confirmed many of the known trends in terms of social factors that influence case incidence (such as group quarters percentage or mobile home percentage per county), while also discovering interesting trends occurring across different waves of the pandemic that give insight into the effect of measures such as vaccination. This research provides a novel approach to modeling sociodemographic risk factors against COVID-19 case rate which can easily be expanded upon in the future with a more robust set of sociodemographic factors.masters, M.S., Mathematics & Statistical Sci -- University of Idaho - College of Graduate Studies, 2022-0
Evaluation and Modeling of One and Multi-Point Douglas-fir Site Indices Using Machine Learning in Northern California
No full textAccurately quantifying forest productivity is a vital endeavor for modern forest managers. In north central California, one-point site index equations created from stem analysis data currently serve as the most reliable means to estimate forest productivity. Although generally sufficient, current models may inherently introduce error by failing to acknowledge how site conditions differentially impact growth rates and that growth rates fluctuate as trees mature. Therefore, alternative approaches that implicitly incorporate site growth factors may be necessary to quantify the true productive potential of forested landscapes in this region.We selected 162 Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. menziesii) trees for destructive sampling via segmented stem analysis from a replicated orthogonal sampling matrix of known environmental growth factors. Predicted growth rates for stem segments were calculated using a locally established traditional one-point Douglas-fir site index equation that utilizes breast-height age and total height. These predicted growth rates were then compared to observed growth rates obtained using a two-point site index approach (i.e., age by log segment length). Results indicated no significant differences between observed and predicted growth rates for breast-height to 20 and breast-height to 30 m segments. However, significant underpredictions were identified for a majority of segments between breast-height and 30 m. Results suggest the effectiveness and utility of one and two-point site index approaches is highly dependent on past management practices (available site trees), future silvicultural objectives (short vs long-term rotation lengths), and a need to accurately predict temporal growth rates (carbon accumulation). To meet the demand for more reliable one and multi-point productivity estimates, extreme gradient boosting (XGBoost) machine learning models using climatic, edaphic, and topographic predictors were tested to evaluate prediction accuracies of Krumland and Eng (2005) site index and 10-meter site index (10MSI) – two site index approaches commonly used to calibrate regional growth and yield models. Multiple XGBoost models were created and compared for each site index method. The lowest 10-fold cross-validated RMSE value was used to select final models for each site index method. Final machine learning models were used to generate 0.4-hectare resolution raster layers of productivity for the study area.masters, M.S., Forest, Rangeland & Fire Sci -- University of Idaho - College of Graduate Studies, 2022-0
Foraging Activity and Survival of the Northern Idaho Ground Squirrel are Influenced by Climate, Hibernation, Endogenous State, and Competition with a Coexisting Congener
No full textUnderstanding the ultimate drivers of evolution and population regulation are core goals of ecology. Climate change can affect the evolution and persistence of free-ranging animals via myriad mechanistic pathways, and so is of particular interest to researchers, policy makers, and the public. Negative changes in abundance and demographic vital rates in response to climate change have been documented in some animals, but the mechanisms underpinning these relationships are often not well understood such that we lack the ability to make generalized predictions about the effects of future climate change on animal behavior, abundance, and evolution. Furthermore, species and individual level traits likely mediate the effects of climate on animals. For example, species with strongly seasonal annual cycles – like obligate hibernators – may be particularly sensitive to climate change. A better understanding of how climate interacts with and influences variation in behavior and life-history is needed to explain patterns observed in nature and inform the conservation of species, biological communities, and ecological processes. We investigated mechanisms shaping behavior and demography of the northern Idaho ground squirrel (Urocitellus brunneus), a federally threatened species endemic to a small portion of west-central Idaho, USA. The squirrels suffered population declines in the late 20th century and now persist in a fragmented metapopulation consisting of Chapter 1 tests predictions of Optimal Foraging Theory to explain variation in the amount of time northern Idaho ground squirrels allocate to aboveground foraging activity. Specifically, we sought to elucidate the effects of thermal environment, predation risk, and endogenous state on squirrel foraging activity. We also considered the effects of hibernation behavior and the squirrel’s strongly seasonal annual cycle on their foraging behavior – a novel aspect of this study. Foraging time increased as the aboveground active season progressed and hibernation approached, suggesting energetic thresholds imposed by that extreme adaptation to seasonally unsuitable conditions drive foraging behavior during the active season. Furthermore, heavy squirrels foraged less relative to lean squirrels as hibernation approached, indicating that squirrels in poor body condition accepted increasingly greater predation risk compared to their heavier counterparts as residual foraging opportunities diminished. Extreme temperatures also negatively influenced time spent foraging, meaning that an increase in overall temperature as well as increases in extreme weather events expected as a result of climate change may constrain foraging opportunities for these threatened squirrels. Management actions that improve forage abundance and quality, therefore, are likely to increase squirrel fitness and so populations by allowing squirrels to better avoid aboveground risks posed by extreme thermal conditions and predation while still attaining the necessary fat reserves to survive their long hibernation period and reproduce in the future. Chapter 2 considers the effects of seasonal temperature and precipitation metrics on survival of northern Idaho ground squirrels as well as two coexisting species – Columbian ground squirrels (Urocitellus columbianus) and yellow-pine chipmunks (Tamias amoenus) – with an eye toward predicting the effects of climate change on populations of these imperiled squirrels and herbivorous and hibernating animals more broadly. We also tested for hypothesized negative effects of competition with the larger, socially dominant Columbian ground squirrel on northern Idaho ground squirrels and whether changes in climate have implications for competitive interactions between the species. Northern Idaho ground squirrel survival was negatively density dependent, suggesting the squirrels are, in fact, food or space limited. Moreover, Columbian ground squirrel density had a sharp negative effect on northern Idaho ground squirrel survival during the active season, compelling evidence of competition between the two ground squirrel species. Winter snowfall negatively influenced northern Idaho ground squirrel survival, but positively and strongly influenced Columbian ground squirrel survival, suggesting that climate modulates competition between the congeners by influencing Columbian ground squirrel survival and so abundance and distribution. Changes in forage availability related to winter snowpack likely underpin these patterns, and this is one of the first studies to demonstrate such a mechanistic pathway by which climate can influence the demography of coexisting species. The apparent negative effects of competition on northern Idaho ground squirrel survival suggest that management actions aimed at benefiting the threatened squirrels are most likely to be successful in areas where they will not be subsequently outcompeted by Columbian ground squirrels or when coupled with control of the larger squirrels.masters, M.S., Fish & Wildlife Sciences -- University of Idaho - College of Graduate Studies, 2022-0
Understanding the Requirements for Successfully using Transfer Learning in Genetic Algorithms
No full textThis dissertation is about understanding the requirements for successfully implementingTransfer Learning (TL) in the Genetic Algorithms (GA). TL is the procedure of transferring previous knowledge from an old problem, called the source problem (S) to another problem called the target problem (T). We have performed this study by implementing the process of the TL by employing the Genetic Algorithm (GA) as the model solver. GA is a type of Evolutionary Computation (EC) inspired by biological evolution theory that using biological evolution strategies by mimicking inheriting characteristics over many generations. TL has some limitations, for example, negative transfer. This situation halts the performance of solving the target problem. Also, during our study, we found out transferring the whole final source population to the target problem is not always a beneficial strategy for solving hard or non-related problems. Our study focuses on understanding the behavior of the transferred population and how to make them more beneficial to the target solver and the GA. In this dissertation, we experimented with and evaluated several strategies for transferring knowledge including the Estimation of Distribution Algorithm (ED). We proposed an algorithm that samples the transferred population, and we evaluated our algorithm against other strategies of TL. We experimented and analyzed the effect of the content of the transferred population on the performance of the target solver. We experimented with transferring partial knowledge from the source problem to the target problem. We also experimented with sampling and transferring knowledge from multiple source problems to the target problem. The results of our studies show how TL can improve the performance of the GA in terms of the number of generations, time, effort the GA solver took to find the optimal solution. Also, analyzed factors that affect the GA performance and how to sample transferred population in terms of providing the GA with needed knowledge from the previous problem.doctoral, Ph.D., Computer Science -- University of Idaho - College of Graduate Studies, 2022-0
Multi-Physics Investigation of a Natural Circulation Molten Salt Micro-Reactor that Utilizes an Experimental In-Pile Device to Improve Core Physics and System Thermal-Hydraulic Performance
No full textThe Molten Salt Reactor (MSR) concept is a rapidly evolving Generation IV design that has recently attracted favorable attention due to the potential for reducing waste generation, realizing passive safety features, and seizing on the opportunity for cost effective economics. An investigation into the power transient behavior of an autonomous load following, natural circulation MSR system is important to quantifying operational and safety performance under dynamic conditions. This paper presents the results of a STAR-CCM+ and a comparative simple asymmetric, one-dimensional, finite-element numerical model to solve the compound dynamic MSR power behavior subject to flow and temperature reactivity feedback only. Results show that reactor power is affected by fuel salt flow velocity (global) and temperatures (local) in a coupled, time-delayed manner that results in a unique compound dynamic closed-loop power feedback mechanism. This novel simulation approach opens the possibility of performing inexpensive computations to evaluate time-dependent reactor performance relative to thermo-physical fuel salt limitations. Natural circulation MSRs are stable and potentially provide a leap in safety and reliability.doctoral, Ph.D., Nuclear Engr & Industrial Mgmt -- University of Idaho - College of Graduate Studies, 2022-0
Grizzly Bears and Their Management in the Western Bitterroot Ecosystem
No full textGrizzly bears (Ursus arctos horribilis) were extirpated from central Idaho’s Bitterroot Ecosystem (BE) by 1946. After a failed attempt to reintroduce grizzlies to the BE in the 1990s, individual grizzlies have been documented in the region since 2007, dispersing from other established populations to the north. To explore BE residents’ tolerance towards grizzlies and their management and who they trust and do not trust for grizzly management, this research uses interviews and focus groups to collect data that can inform proactive conservation and management efforts amidst potential natural recovery. Results indicate: (1) distrust of management agencies and conservation organizations that stems from general perceptions of untrustworthiness and the wolf reintroduction that occurred in central Idaho in the mid-1990s, (2) trust-building preferences, including accessible staff and participatory opportunities, and ways for agencies and organizations to increase perceptions of trustworthiness, (3) intolerance towards management that stems from perceptions of an inequitable constitutive process that excludes BE residents from decision-making, potential threats from Endangered Species Act regulations, and a lack of clarity about current and future management plans, (4) preferred actions to increase tolerance towards management, including a decentralized decision-making process, educational outreach about grizzlies, and a hunting season, (5) intolerance towards grizzlies that stems from safety, economic, and cultural concerns, and (6) tolerance towards grizzlies that stems from appreciation and the belief in their right to exist. These findings suggest that improved communication efforts about management intentions and a more equitable constitutive process may address issues of social injustice and some of the material and non-material costs of grizzly presence to improve BE residents’ tolerance and foster more trusting relationships.masters, M.S., Natural Resources -- University of Idaho - College of Graduate Studies, 2022-0
Investigating Head Start Teachers' Science Teaching Attitudes and Efficacy
No full textThe purpose of this study is to explore the relation between Head Start teachers' science teaching attitudes and efficacy. A total of 150 teachers participated in the study from eight states and 22 Head Start centers. Teachers’ science teaching attitudes and efficacy were measured using validated quantitative rating scales via the online survey software, Qualtrics. Teachers’ attitudes toward teaching science were measured by the Preschool Teacher Attitude and Beliefs Toward Science Questionnaire (P-TABS). Teachers’ science teaching efficacy was measured by the Teacher Efficacy and Attitudes toward Science, Technology, Engineering, Mathematics (T-STEM) – Science subscale. Data were analyzed using a multilevel regression approach. Results showed that Head Start teachers’ perceived challenges were significantly associated with science teaching efficacy beliefs, as was teacher comfort, and child benefit beliefs. Child benefit beliefs were the only domain of science teaching attitudes that were significantly associated with science teaching outcome expectancy. This finding shows the potential in improving early childhood teachers’ attitudes towards early science education by enhancing their science teaching efficacy.masters, M.S., Family and Consumer Sciences -- University of Idaho - College of Graduate Studies, 2022-1