2020-

Permanent URI for this collection

https://hdl.handle.net/10217/182111

Browse

Now showing 1 - 20 of 2558

Open Access
2022 National Lamb Quality Audit: Phase I: Supply chain perceptions of the U.S. lamb industry. Phase II: In-plant survey of carcass characteristics related to quality and value of fed lambs and mutton
(Colorado State University. Libraries, 2023) Newman, Lauren, author; Stackhouse-Lawson, Kim, advisor; Place, Sara, committee member; Nair, Mahesh Narayanan, committee member; Garry, Franklyn, committee member; Finck, Jessica, committee member
The U.S. sheep and lamb population has slowly declined over the last eight decades, from 56 million head in 1942 to five million head in January of 2023. Sheep, often referred to as mutton in the meat industry, are mature animals that have at least two permanent incisors, spool joints, and are typically over 24 months of age. Lambs are considered young animals that lack permanent incisors, have at least one break joint, and are usually less than 14 months (USDA,1992). The U.S. lamb industry faces competition from imported lamb from Australia and New Zealand that is less expensive. This imported product increases the lamb supply within U.S. wholesale and retail stores, which, along with increased production costs, has raised concerns about the future viability of the U.S. lamb industry. In response to this pressure, the lamb supply chain can prioritize attributes that both reduce production costs and promote consumer demand. The first step in this process is to measure data from production through lamb carcass quality characteristics, especially data captured in the manufacturing settings. Benchmarking is necessary to identify needs to drive quality enhancements and to ultimately drive improvement and profitability of the lamb industry. The current National Lamb Quality Audit (NLQA) seeks to fill this gap by capturing baseline data from broad scope of the supply chain through perception surveys and in-plant audits. This baseline information will inform the lamb value chain on the current perceptions and lamb quality characteristics that may aid in identifying attributes to reduce costs and increase consumer demand. The NLQA, conducted three times since 1992, assesses the industry's progress on various quality characteristics that ultimately affect consumer demand for lamb. The most recent audit, conducted in 2015, primarily focused on the foodservice segment of the industry. As sheep genetics, management practices, available resources, and consumers' needs and expectations constantly evolve, more frequent audits that capture the entire supply-chain should be considered. The 2022 NLQA audit is designed to repeat successful portions of the 2015 audit, including a new supply chain survey to assess perceptions about the U.S. lamb industry and in-plant carcass characteristics. In phase I, 155 surveys were conducted from May 2022 through September 2022 to understand and quantify perceptions of the U.S. lamb industry. The survey was administered using a software package (Qualtrics®, Provo, Utah) customized to develop a structured order of questions for each industry segment. The survey was distributed via in-plant visits, social media, and email. Survey respondents remained anonymous, each taking approximately ten minutes to complete. Statistical analysis was conducted in Microsoft Excel and the Qualtrics® software. Thirty-two states were represented, with 88 percent of respondents identifying as the owner/operator of their respective business or operation and 86 percent representing commercial breeding operations. Respondents were asked to rank topics based on importance to their operation from 1 (least important) to 10 (most important). Animal welfare (8.9), lamb quality (8.4), and sustainability (7.6) were of most importance to producers. Respondents were also prompted to rank significant challenges in the industry (1=most important and 10=least important). The most significant challenges identified were operation costs (3.04), market volatility (3.70), and labor (4.08). Open-ended responses for defining sustainability were sorted and narrowed in terms of descriptions to find commonalities between respondents. Central themes from respondents included environmental stewardship, profitability, and producing high-quality lamb products. Results from the survey will provide valuable insight to discern gaps and opportunities between producers' viewpoints and data collected in plants to develop educational material to improve lamb quality. For phase II, in-plant assessments were conducted in four of the largest U.S. commercial lamb processing facilities across six production days from June to September 2022. On each production day, 50 percent of carcasses harvested and chilled were surveyed. Both hide-on and hide-off carcasses (n=2,605) and chilled carcasses (n=2,464) were surveyed. On the harvest floor, trained auditors collected data on mud scores, breed type, presence of horns, sex, wool length, and physiological age indicator data. Additionally, hot carcass weight (HCW), measured fat thickness (MFT), and reported USDA yield and quality grades were collected in the cooler. The distribution and summary functions of JMP® Software were used to determine the frequency distributions, means, standard deviations, and minimum and maximum values. Data was analyzed using the Type III ANOVA procedure, and a pairwise comparison was analyzed for dependent variables by treatment using the least squared means procedure in the 'lsmeans' package, of R© with the Tukey HSD adjustment. Dependent variables were YG, calculated YG, HCW, and MFT. Significance was determined at P-value ≤ 0.05. Phase II used in-plant assessments to benchmark current carcass quality characteristics related value of the fed lamb and mutton industry in the U.S. Among the carcasses (n = 1,605) that were audited for sex, 63.2 percent were wethers, 31.5 percent ewes, and 5.3 percent rams. Two percent of the carcasses were presented with horns. Of the 2,604 carcasses evaluated, 40.2 percent were speckle-faced (white-face and black-face cross), 38.8 percent were white-faced, 18.3 percent were black-faced, 1.46 percent had natural characteristics, and 1.72 percent were hair sheep. The average mud score was 2.12, and the average wool length was 5.03 cm. Additionally, 87.1 percent of the 2,437 carcasses presented two break joints indicating lamb, 5.70 percent with one break joint indicating yearling mutton, and 7.18 percent with no break joints indicating mutton. The average HCW (n=2,464) was 39.9 kg, whereas the MFT was 0.97 cm. The USDA stamped yield grade was 2.71 and 68.5 percent graded choice (CH), 22.6 percent graded prime (PR), and 8.9 percent were not graded. The 2022 NLQA in-plant survey of carcass quality characteristics will provide a current benchmark for carcass characteristics of lamb processed in the U.S. The data from this study can help industry segments to understand and develop strategic initiatives to improve the quality of fed lamb and mutton.
Open Access
250 years of climate-mediated ecological change in Santa Fe Lake, NM
(Colorado State University. Libraries, 2022) Shampain, Anna, author; Baron, Jill, advisor; Leavitt, Peter, committee member; von Fischer, Joe, committee member; Sibold, Jason, committee member
Mountain lakes are sensitive indicators of anthropogenically driven global change. Lake sediment records in the western United States have documented increased percent carbon and nitrogen and heightened primary productivity indicative of eutrophication in mountain lakes. Recent paleolimnological studies suggest atmospheric nutrient deposition and warming underlie these changes. We analyzed a short sediment core from Santa Fe Lake, NM, the southernmost subalpine lake in the Rocky Mountain Range to investigate patterns in lake biogeochemical and algal biomarkers since 1747. Lake sediments were dated using 210Pb activities and analyzed for percent C and N, δ13C, δ15N, and algal pigments representative of total biomass, chlorophytes, cryptophytes, diatoms, and other primary producers from Santa Fe Lake. Throughout the 250-year sediment record from Santa Fe Lake, we observed changes in algal community composition alongside biogeochemical alterations. During the cold dry conditions of the Little Ice Age, there were greater proportions of cyanobacteria, diatoms, and sulfur bacteria. Total algal biomass increased under increased warming and climate variability with significant increases in chlorophytes and cryptophytes. Significant rates of change occurred concurrently with increases in regional N deposition in the mid-20th century. C, N, δ13C, δ15N remained relatively stable throughout the record, until the mid-20th century when C and N increased exponentially alongside depletions in δ13C, δ15N. Our results suggest climate-driven algal assemblage changes throughout the record with regional N deposition contributing to contemporary productivity increases. The timing and magnitude of these changes differ from other studied lakes. Our findings highlight the heterogeneity of lakes' responses to changing environmental conditions in the Anthropocene and call attention to the role of climate-induced ecological change in the absence of critical N deposition.
Open Access
316L stainlesss steel modified via plasma electrolytic oxidation for orthopedic implants
(Colorado State University. Libraries, 2022) Michael, James A., II, author; Popat, Ketul C., advisor; Li, Vivan, committee member; Sampath, Walajabad S., committee member
316L stainless steel (SS) is widely used biomaterial for implantable devices and is estimated to the base material for 60% of implantable devices. However, one challenge of the material is the inhomogeneity of the surface morphology which may influence the adhesion process of host cells and bacteria. One method to create a uniform surface of 316L SS is plasma electrolytic oxidation (PEO). PEO creates an oxide layer on the outer surface thus changing the surface topography on the microscale. PEO process on SS functions by anodizing the surface via direct current in electrolyte solution. Preliminary research found that a continuous direct current over a time manufactured undesirable samples, to overcome this challenge the use of pulse timings was utilized during fabrication. This research aimed to answer the questions how do PEO modifications effect cellular adhesion and viability, and how do PEO modifications affect bacteria adhesion and viability. PEO modified 316L SS surfaces were characterized and its effects on the adhesion, morphology, and differentiation of adipocyte derived stem cells, along with the adhesion and morphology of Staphylococcus aureus was investigated.
Embargo
3D localization of cytoskeleton in mouse spermatids using stochastic optical reconstruction microscopy
(Colorado State University. Libraries, 2022) Sunny, Reshma, author; Krapf, Diego, advisor; Nikdast, Mahdi, committee member; Prasad, Ashok, committee member
It is estimated by the World Health Organization that globally 186 million individuals live with infertility. Studies have shown that cause of male infertility is unknown in 30 to 50% of the cases. Over the last several years teratozoospermias have been investigated and have been backtracked to events in spermatogenesis. The development of the acrosome and the manchette, protein and vesicle transport in spermatids, and sperm head shaping are crucial steps in the formation of healthy sperms. The cytoskeleton in spermatids plays a crucial role in shaping the sperm head. The acroplaxome exerts forces on the nucleus and gives the mammalian sperm head its species-specific shape, and also facilitates the proper attachment of the nuclear cap called the acrosome, containing the enzymes required for sperm penetration of the oocyte. The manchette should be intact and formed properly to have shortened diameter as spermatids differentiate so that it can constrict the base of the nucleus to shape the head, and also facilitate the transport of cargo to the base of the cell. Thus as studies have confirmed, the disruption in the organization of the cytoskeleton is a concern for infertility. Hence it is crucial to learn more about the cytoskeletal structures in spermatids. The goal of this thesis is to 3D localize these structures. The major structures we are interested in are the acroplaxome and the manchette. For this, we use a super-resolution microscopy method called Stochastic Optical Reconstruction Microscopy to image spermatid cytoskeleton. Our experiments confirmed the presence of α-tubulin in the manchette and that of F-actin in the manchette and the acroplaxome, as previously observed by researchers with 2D confocal images. We observed that the manchette reduces in diameter and progresses to the caudal portion of the cell at the later steps of differentiation and that the structure forms completely at step 10 and disassembles after step 14.
Embargo
A case for context in quantitative ecology: statistical techniques to increase efficiency, accuracy, and equity in biodiversity research
(Colorado State University. Libraries, 2024) McCaslin, Hanna M., author; Bombaci, Sara, advisor; Hooten, Mevin, committee member; Koons, David, committee member; Hoeting, Jennifer, committee member
The current era of ecological research is characterized by rapid technological innovation, large datasets, and numerous computational and quantitative techniques. Together, big data and advanced computing are expanding our understanding of natural systems, allowing us to capture more complexity in our models, and helping us find solutions for salient challenges facing modern ecology and conservation, including climate change and biodiversity loss. However, large datasets are often characterized by noise, complex observational processes, and other challenges that can impede our ability to apply these data to address ecological research gaps. In each chapter of this dissertation, I seek to address a data problem inherent to the 'big data' that characterizes modern ecological research. Together, they extend the strategies available for addressing a problem facing many ecologists – how to make use of the large volumes of data we are collecting given (1) current computational limitations and (2) specific sampling biases that characterize various methods for data collection. In the first chapter, I present a recursive Bayesian computing (RB) method that can be used to fit Bayesian hierarchical models in sequential MCMC stages to ease computation and streamline hierarchical inference. I also demonstrate the application of transformation-assisted RB (TARB) to a hierarchical animal movement model to create unsupervised MCMC algorithms and obtain inference about individual- and population-level migratory characteristics. This recursive procedure reduced computation time for fitting our hierarchical movement model by half compared to fitting the model with a single MCMC algorithm. Transformation-assisted RB is a relatively accessible method for reducing the computational demands of fitting complex ecological statistical models, like those for animal movement, multi-species systems, or large spatial and temporal scales. Biodiversity monitoring projects that rely on collaborative, crowdsourced data collection are characterized by huge volumes of data that represent a major facet of 'big data ecology,' and quantitative methods designed to use these data for ecological research and conservation represent a leading edge of contemporary quantitative ecology. However, because participants select where to observe biodiversity, crowdsourced data are often influenced by sampling bias, including being biased toward affluent, white neighborhoods in urban areas. Despite the growing evidence of social sampling bias, research has yet to explore how socially driven sampling bias impacts inference and prediction informed by crowdsourced data, or if existing data pre-processing or analytical methods can effectively mitigate this bias. Thus, in Chapters 2 and 3, I explored social sampling bias in data from the crowdsourced avian biodiversity platform eBird. In Chapter 2, I studied patterns of social sampling bias in the locations of eBird "hotspots" to determine whether hotspots in Fresno, California, U.S.A. are more biased by social factors than the locations of Fresno eBird observations overall. My findings support previous work showing that eBird locations are biased by demographics. Further, I found that demographic bias is most pronounced in the locations of hotspots specifically, with hotspots being more likely to occur in areas with higher proportions of non-Hispanic white residents than eBird locations overall. This relationship is reinforced because hotspots in these predominantly white areas also amass more eBird checklists overall than hotspots in areas with more demographic diversity. These findings raise concerns that the eBird hotspot system may be exacerbating spatial bias in sampling and reinforcing patterns of inequity in data availability and eBird participation, by leading to datasets and user-facing maps of birding hotspots that mostly represent predominantly white neighborhoods. Then, in Chapter 3, I investigated the impacts of not accounting for socially biased sampling when using eBird data to study patterns of urban biodiversity. The luxury effect has emerged as a prominent hypothesis in urban ecology, describing a pattern of higher biodiversity associated with greater socioeconomic status observed in many cities. Using eBird data from 2015-2019, I tested whether an avian luxury effect is observed in Raleigh-Durham, North Carolina, U.S.A. before and after accounting for social sampling bias. By jointly modeling sampling intensity and species richness, I found that sampling intensity and species richness are positively correlated and sampling bias influences the estimated relationship between species richness and income. Thus, failing to account for sampling bias can hinder our ability to accurately observe social-ecological dynamics. Additionally, I found that randomly spatially subsampling eBird data prior to analysis, as recommended by existing guidelines to mitigate sampling bias in eBird data, does not reduce biased sampling related to demographics, because there are data gaps in communities of color and low-income communities that cannot be addressed via spatial subsampling. Therefore, it is paramount that crowdsourced and contributory science projects prioritize more equitable participation in their platforms, both for more ethical, equitable practice and because current sampling inequity negatively impacts data quality and project goals. Quantitative techniques can help us understand the complex observational processes influencing ecological data, and each chapter of this dissertation highlights how tailoring statistical or computing methods to these observational contexts can advance ecological knowledge – either by extending the complexity of models we can feasibly fit, as in Chapter 1, or by acknowledging and accounting for sampling inequity, in Chapters 2 and 3. We are all participants actively shaping the ecological processes we observe, and the actions, approaches, and assumptions used in our research reflect societal systems and biases. Data are never objective, and it is dangerous and false to assume that quantitative techniques can take data out of the contexts in which they were collected. Instead, quantitative frameworks that embrace, reflect, and seek to improve the ways in which social and observational contexts inform what is observed can elevate analytical techniques to tools towards more just, inclusive, and transparent ecological research and conservation.
Open Access
A catchment is more than the sum of its reaches: post-fire resilience at multiple spatial scales
(Colorado State University. Libraries, 2024) Triantafillou, Shayla P., author; Wohl, Ellen, advisor; Rathburn, Sara, committee member; Morrison, Ryan, committee member
As wildfires are projected to increase in frequency and severity, there is a growing interest in understanding river resilience to the wildfire disturbance cascade. Numerous 3rd-order mountain catchments within the Cache la Poudre (Poudre) River basin in the Colorado Front Range, USA burned severely and extensively during the 2020 Cameron Peak fire. Many of these catchments experienced debris flows and flash floods triggered by convective storms after the fire. The downstream effects of the debris flow sediment varied along a continuum from attenuated and largely contained within the catchment, through contributing to a pre-existing debris fan at the catchment outlet, to releasing substantial volumes of water and sediment to the Poudre River. I conceptualize these catchments as exhibiting decreasing resilience to post-fire disturbance along the continuum described above based on the geomorphic evidence of relative sediment export. The characteristics affecting resilience and magnitude of response to disturbance span multiple spatial scales from the catchment to stream corridor reaches hundreds of meters in length. I conceptualize characteristics on different spatial scales as driving or resisting response to disturbance and therefore impacting the resilience outcome of the catchment. As the magnitude of resisting characteristics increases at the catchment, inter- and intra- reach scales, I hypothesize that a catchment will be more resilient to the wildfire disturbance cascade. At the catchment scale I consider geomorphic, burn, vegetation, and precipitation characteristics. I conducted longitudinally continuous surveys to measure reach-scale characteristics within each study catchment. I focus on the reach-scale geomorphic, vegetation, and burn characteristics, with a particular focus on elements that introduce inter- and intra-reach spatial heterogeneity including channel planform, beaver-modified topography, the distribution of channel and floodplain logjam distribution density, and the floodplain width/channel width ratio for the population of reaches within each catchment. The floods observed at the study catchments illustrate fire lifting the elevation above which rainfall-induced flooding occurs due to the efficient conveyance of water from hillslopes to channels after wildfire. Results suggest that inter- and intra-reach spatial heterogeneity are better descriptors of resilience than catchment-scale characteristics: resilience is associated with greater longitudinal variations in floodplain/channel width and more reaches with wide floodplains, low channel gradients, beaver-modified topography, and multi-stem deciduous vegetation.
Open Access
A characterization of Colorado Front Range and Denver basin aquifer system water stable isotope signatures
(Colorado State University. Libraries, 2024) Ulate, Isabella, author; Rugenstein, Jeremy K. C., advisor; Ronayne, Michael, committee member; Ross, Matthew, committee member
The Denver Basin Aquifer System (DBAS) is an important groundwater resource for Front Range communities and is currently experiencing increasing demand as populations grow and surface water supplies remain limited. It is necessary to better constrain aquifer recharge mechanisms to enable sustainable use of this resource. In other sedimentary basin aquifer systems, mountain front recharge has been shown to be a significant contributor to local basin groundwater recharge. In the DBAS, inputs from the mountain block are poorly understood, and previous numerical models have treated large segments of the mountain-front boundary as impermeable. However, there exist potential connections between the mountain block and the DBAS, either by direct contact of permeable units, which would facilitate underflow recharge into the basin, or by surface water infiltration to the aquifer units where they outcrop near the mountain front. To observe spatial and temporal relationships between mountain block water and DBAS water, we use water stable isotopes and characterize the δ2H and δ18O of monthly precipitation, seasonal surface waters, and groundwaters in and around the Front Range and Denver Basin. The goal of this study is to determine if differences in the isotopic composition of waters across the Front Range permit the use of δ18O and δ2H as tracers of water flow between Front Range streams and groundwater and the DBAS. We analyzed the unique signature of mountain-block water to compare with DBAS water stable isotope data collected from Castle Rock Water municipal wells. Stable isotope ratios varied spatially and temporally, with the greatest temporal variance observed in precipitation. Streams showed great spatial variance, and less significant seasonal variance between the three seasonal sampling events conducted. Groundwaters showed very little temporal variance but had great spatial variance both between the aquifer units of the DBAS and between different locations within the mountain block crystalline aquifer. The lowest δ2H and δ18O ratios were measured in winter precipitation, winter streams, and groundwater samples collected from the high-elevation Front Range. Samples of DBAS groundwaters with the lowest δ2H and δ18O ratios indicate potential hydrogeologic connection to the mountain block. Interpreted mixing lines on a d-excess versus δ18O plot support the potential DBAS-mountain block connection. The deepest aquifer units of the DBAS (Arapahoe and Laramie-Fox Hills) show the least relationship with meteoric or surface waters on both a δ2H and δ18O plot and the d-excess versus δ18O plot and have higher δ18O values than would be predicted based on their previously measured recharge ages and paleoclimate data from the region. Characterizing the spatial and temporal variations in water stable isotope signatures of the Front Range and DBAS region enhances understanding of the region's hydrology and hydrogeology. Additionally, these results help to better inform models of aquifer recharge and promote sustainable use of the DBAS resource.
Open Access
A circuitous journey of virus characterization and surveillance in North and Central America
(Colorado State University. Libraries, 2023) McMinn, Rebekah J., author; Ebel, Gregory D., advisor; Quackenbush, Sandra, committee member; Brault, Aaron, committee member; Neuwald, Jennifer, committee member
The burden of ticks and the pathogens they carry is increasing worldwide. Powassan virus (POWV, Flaviviridae: Flavivirus), the only known North American tick-borne flavivirus, is of particular concern due to rising cases and the severe morbidity of human disease. In this dissertation we evaluated the recent emergence of POWV from a culmination of field (chapter 2), in vitro (chapter 3), and in-vivo (chapter 4) studies. In addition, we determined the applicability of a vector-enabled surveillance method (xenosurveillance) in Central America (chapter 5). We first used a genetic approach to evaluate the emergence of lineage II POWV, known as deer tick virus (DTV), in parts of North America where human cases occur. We detected DTV-positive ticks from eight of twenty locations in the northeastern United States with an average infection rate of 1.4%. High-depth whole genome sequencing of eighty-four new and archival POWV and DTV samples allowed us to assess geographic and temporal phylodynamics. We observed both stable infection in the northeastern United States and patterns of geographic dispersal within and between regions. Bayesian skyline analysis demonstrated DTV population expansion over the last fifty years. This is concordant with the documented expansion of Ixodes scapularis tick populations and suggests increasing risk of human exposure as the vector spreads. Finally, we isolated sixteen novel viruses in cell culture and demonstrated limited genetic change after passage, a valuable resource for future studies investigating this emerging virus. We then assessed in vitro phenotypes of POWV on human neuronal cells using 16 genetically diverse isolates obtained from a broad geographic and temporal range. We determined over a 10,000-fold range in peak viral titer and significantly decreased cell mortality for two Midwest DTV isolates, though no clear correlation between in vitro phenotype and geo-temporal characteristics could be made. We then performed whole genome sequencing of virus post neuronal cell passage to identify potential residues of interest. Again, no residues could be linked to phenotype, though several interesting residues with increased frequency post-neuronal cell culture were identified. Based on the significant in vitro diversity observed, we sought to assess pathogenesis and tick transmission phenotypes between isolates. We noted neurological disease in mice in both lineages of POWV, with potential low-virulence strains derived from coastal New York. Additionally, we observed an early neuroinvasion phenotype for a Midwest DTV isolate. The ability to infect I. scapularis ticks was determined by feeding on infected host mice (viremic) and through an artificial infection method. Surprisingly, infection rates in ticks via viremic or artificial infection remained consistent between all five isolates tested, resulting in 12-20% infection rate. Taken together, these data demonstrate potential genotype-independent ability to infect ticks and conversely, strain-dependent differences in pathogenesis. In chapter 5, we evaluated a vector-enabled surveillance method ('xenosurveillance') in rural Guatemala. Surveillance methods that permit rapid detection of circulating pathogens are desperately needed. Xenosurveillance is a novel surveillance approach that takes advantage of mosquito feeding behavior to identify blood-borne pathogens that may be circulating in human and animal hosts. This approach circumvents invasive blood sampling of individuals and results in an abundant sample source derived from both humans and animals. In this study, twenty households from two villages (Los Encuentros and Chiquirines) in rural, southwest Guatemala were enrolled and underwent weekly prospective surveillance for 16 weeks. When febrile illness was reported in a household, recently blood-fed mosquitoes were collected from within dwellings and blood samples taken from each member of the household. Mosquitoes were identified to species and blood sources identified by sequencing. Shotgun metagenomic sequencing was used to identify circulating viruses. Culex pipiens (60.9%) and Aedes aegypti (18.6%) were the most abundant mosquitoes collected. Bloodmeal sources were most commonly human (32.6%) and chicken (31.6%), with various other mammal and avian hosts detected. Several mosquito-specific viruses were detected, including Culex orthophasma virus. Human pathogens were not detected. While more intensive sampling may be needed to detect human pathogens, sampling mosquitoes that feed on humans and domestic animals may prove valuable for monitoring pathogens with zoonotic potential.
Open Access
A clonable selenium nanoparticle in action: high resolution localization of FtsZ using electron tomography
(Colorado State University. Libraries, 2021) Borgognoni, Kanda, author; Ackerson, Christopher J., advisor; Neilson, James, committee member; Kennan, Alan J., committee member; Tsunoda, Susan, committee member
A meaningful understanding of biochemistry requires that we understand the function of proteins, which is heavily dependent on their structure and location within an organism. As the Resolution Revolution of cryo-electron microscopy gains unprecedented ground largely due to the recent development of commercially available direct electron detectors, energy filters, and high-end computation, thousands of protein structures have been solved at atomic or near-atomic resolution, with the highest resolution structure to date being solved at 1.2 Å. A major challenge that has limited the broad use of cryo-electron tomography (cryo-ET) is locating a protein of interest in an organism, as no commercially available high-contrast markers which can be generated in vivo exist. Herein, we present a breakthrough study which aims to solve this problem by synthesizing high contrast metal nanoparticles labeling desired proteins in situ. We isolated a Glutathione Reductase-like Metalloid Reductase (GRLMR), which can reduce selenite and selenate into selenium nanoparticles (SeNPs), from Pseudomonas moraviensis stanleyae found in the roots of a Se hyperaccumulator Stanleya pinnata, or Desert Princes' Plume. A recombinant variant, denoted as a clonable Selenium NanoParticle (cSeNP), was fused to filamentous temperature sensitive protein Z (FtsZ), and the chimera was expressed in vivo using a T7 expression system in model organism E. coli for a proof-of-concept study. Because the SeNPs biogenically produced are amorphous, they exist in a quasistable state and are composed of polymeric Sen in the form of chains and rings that are constantly breaking and reforming. To stabilize the particles during cellular preservation ex aqua, a disproportionation-like reaction can be done either in vivo or as a post-fixation step to form crystalline metal selenide (MSe) NPs that can withstand the processing liquids used. Thereafter, electron tomography was used to acquire a tilt series that was reconstructed into a tomogram and segmented using IMOD, generating a model representing MSeNPs labeling FtsZ filaments. As such, we have demonstrated the potential of using cSeNP as a high resolution marker for cryo-ET. While our study relied on traditional preservation and embedment techniques, we anticipate that for cells preserved via vitrification, cloned SeNPs can be used without subsequent transformation to MSeNPs, as the amorphous particles are stable in aqueous media. Prospectively, we expect that clonable nanoparticle technology will revolutionize cryo-ET, allowing us to localize proteins in vivo at high resolution while maintaining organism viability through metal immobilization. Furthermore, this technique can be expanded to other imaging modalities, such as light microscopy and X-ray tomography, through the discovery and engineering of other clonable nanoparticles.
Open Access
A combined classification and queuing system optimization approach for enhanced battery system maintainability
(Colorado State University. Libraries, 2022) Pirani, Badruddin, author; Cale, James, advisor; Simske, Steven, committee member; Miller, Erika, committee member; Keller, Josh, committee member
Battery systems are used as critical power sources in a wide variety of advanced platforms (e.g., ships, submersibles, aircraft). These platforms undergo unique and extreme mission profiles that necessitate high reliability and maintainability. Battery system failures and non-optimal maintenance strategies have a significant impact on total fleet lifecycle costs and operational capability. Previous research has applied various approaches to improve battery system reliability and maintainability. Machine learning methodologies have applied data-driven and physics-based approaches to model battery decay and predict battery state-of-health, estimation of battery state-of-charge, and prediction of future performance. Queuing theory has been used to optimize battery charging resources ensure service and minimize cost. However, these approaches do not focus on pre-acceptance reliability improvements or platform operational requirements. This research introduces a two-faceted approach for enhancing the overall maintainability of platforms with battery systems as critical components. The first facet is the implementation of an advanced inspection and classification methodology for automating the acceptance/rejection decision for batteries prior to entering service. The purpose of this "pre-screening" step is to increase the reliability of batteries in service prior to deployment. The second facet of the proposed approach is the optimization of several critical maintenance plan design attributes for battery systems. Together, the approach seeks to simultaneously enhance both aspects of maintainability (inherent reliability and cost-effectiveness) for battery systems, with the goal of decreasing total lifecycle cost and increasing operational availability.
Open Access
A comparative analysis of wetland and riparian vegetation on Bureau of Land Management land in the western US
(Colorado State University. Libraries, 2023) Binck, Elin, author; Sueltenfuss, Jeremy, advisor; Reynolds, Lindsay, committee member; Smith, Melinda, committee member; Havrilla, Caroline, committee member
In 2011, the BLM deployed its first of three Assessment, Inventory, and Monitoring (AIM) programs as a large-scale, standardized ecological monitoring effort across the agency's land. The first two programs, known as Terrestrial AIM and Lotic AIM, were designed to sample all terrestrial and river ecosystems throughout the landscape. In 2019, the agency piloted its third AIM program, specifically targeting riparian areas and wetlands. This study addressed two main questions: 1) How do wetland and riparian areas sampled with the Terrestrial AIM program compare to those sampled with the Riparian and Wetland (R&W) AIM program, and 2) What are the drivers of plant community composition of the wetlands and riparian areas sampled on BLM land? I developed a set of criteria to identify sites sampled with Terrestrial AIM that had characteristics of wetlands or riparian areas. I then compared vegetation cover, floristic quality metrics, and species composition using nonmetric multidimensional scaling (NMDS) to those sites sampled with R&W AIM. R&W AIM sites had much greater foliar cover, hydrophytic species cover, and perennial cover, but Terrestrial sites had slightly higher floristic metric values. I similarly analyzed the R&W sites on their own, incorporating wetland-specific data that is collected with the new program. I found that sites that met the criteria to be classified as wetlands in the Terrestrial data were a distinct population from the sites sampled with R&W AIM. The main drivers of plant community composition among sites sampled with R&W AIM were elevation and the distribution of surface water, but impacts of grazing were also apparent. All sites assessed by both AIM programs had floristic quality metrics characteristic of highly impacted wetland systems. This study indicates the value of the new R&W AIM program for its ability to perform wetland-specific ecological monitoring, provide valuable data on the health of wetlands, and provide baseline condition that can help guide land management practices into the future.
Open Access
A comparison of suicide loss and non-suicide loss: the impact on family communication and affect
(Colorado State University. Libraries, 2023) Belzil, Eva, author; Quirk, Kelley, advisor; Ortega, Lilyana, committee member; Willis, Danielle, committee member
Suicide loss and non-suicide loss impact thousands of people globally each year. Literature to date has identified ways suicide-loss can impact individuals and families in unique ways but has not indicated what specific aspects of family function are impacted for suicide-bereaved family members. Further, it is unclear whether family members can turn to each other to provide and receive support after their loss. The purpose of this study was to understand how suicide loss of a family member impacts individuals when compared to suicide loss of a non-family member. Additionally, this study aimed to understand how suicide loss of a family member impacts family dynamics on specific levels of communication, affect expression, affect connection, and general family functioning when compared to non-suicide family member loss. Perceived familial support was predicted to moderate the relationship between type of loss and these family function variables. Participants (N = 174) filled out 4 self-report measures that assessed family function prior to their loss, grief experiences, family communication, affect expression, affect connection, and family function after their loss. An independent samples t-test and a hierarchical multiple regression with a moderation analysis were run to examine the relationships between the predictor and outcome variables described above. When compared to individuals who experienced a non-family member suicide loss, individuals who experienced family member suicide loss reported more intense grief experiences (p = .03) but did not report significantly different family function. When compared to non-suicide family member loss, individuals who lost a family member to suicide reported lower family affect connection (p < .05) and lower family affect connection (p < .05), but did not report significantly different family function or family communication. Perceived familial support did not moderate these main effects.
Open Access
A compiler for hierarchical task-based programming on distributed-memory
(Colorado State University. Libraries, 2022) Dubois, Alexandre, author; Pouchet, Louis-Noël, advisor; Rajopadhye, Sanjay, committee member; Wilson, James, committee member
Today, computation intensive applications are run on heterogeneous clusters of machines and use the Message Passing Interface (MPI), which provides a library interface for message-passing between non-shared memory computational resources but comes at a high application development cost. Task-based programming, such as the Concurrent Collection (CnC) model, makes parallelism implicit by only describing task dependencies. This model has recently been extended to model programs with a hierarchical task-based representation, which allows to view tasks at different levels of decomposition, allowing to dispatch tasks of different level optimally to the different available architectures. This thesis main work was to design an algorithm following a graph-based approach to transform a restricted class of single-level regular kernel to a two-level representation in the CnC model extended with hierarchical concepts. This transformation will alleviate performance boost by reducing communication cost and allowing the use of optimized tasks implementation at a coarse level. After describing the CnC programming model concepts, the structure of the proposed graph based tiling algorithm will be developed. Then, the compiler implementing this algorithm on an Intermediate Representation representing a CnC program and generating a C++ version of the kernel using a new hierarchical CnC runtime. Finally, the overhead of this runtime on a shared memory system for a 3D synthetic benchmark representing a classic linear-algebra dependency pattern. This characterization is done to help the user choose the target volume of tasks tile that has to be given as input of the tiling algorithm. The main recommendation is to target a minimization of the number of super- tasks in the runtime while keeping the number of sub-tasks in every super-task under the order of 10000 sub-tasks.
Open Access
A comprehensive approach to modeling musculoskeletal aging and injury: an emphasis on Nrf2-related pathogenesis
(Colorado State University. Libraries, 2021) Andrie, Kendra M., author; Santangelo, Kelly S., advisor; Hamilton, Karyn, committee member; Goodrich, Laurie, committee member; Podell, Brendan, committee member; Muñoz Gutiérrez, Juan, committee member; Miller, Benjamin, committee member
Osteoarthritis (OA) is a degenerative joint disease that affects over 730 million people globally, over 30 million Americans, and is the leading cause of disability in adults. The underlying pathogenesis is multifactorial and largely undetermined, with a variety of cellular pathways and risk factors contributing to disease onset and progression. The crux of this work is that downregulation in nuclear factor erythroid-2 related factor-2 (Nrf2)-signaling in musculoskeletal tissue serves as a central driver for persistent low-grade inflammation, dysregulation of redox homeostasis, mitochondrial dysfunction, and protein dyshomeostasis, all of which contribute to OA progression. To explore the role of this pathway in OA, we utilized the Hartley OA-prone guinea pig model, which develops naturally occurring idiopathic disease with pathology that mimics human disease. My global hypothesis is supported by preliminary data that demonstrates that aging Hartley guinea pig knee joint tissues have decreased expression of Nrf2 mRNA and protein, which coincides with disease onset and remains decreased throughout OA progression. We investigated the utility of a novel nutraceutical and Nrf2-activator in delaying both the onset and progression of idiopathic OA in this model. The ultimate goal of this work is to (1) identify key molecular pathways involved in the etiopathogenesis of OA, with a particular focus on the contribution of the Nrf2 pathway; (2) investigate the utility of a novel nutraceutical and Nrf2-activator in delaying the onset and/or progression of OA in the Hartley guinea pig, and (3) examine the effects of Nrf2-activation on long bone strength. The inclusion of a musculoskeletal condition beyond OA was also pursued; as such, the clinical and histologic manifestations of a novel rectus femoris myotendinous junction injury model was characterized in rats. Ultimately, this work seeks to advance the understanding of musculoskeletal aging and injury through the analysis of key structural and functional outcome measures to further develop appropriate therapeutic targets for disease prevention and treatment.
Open Access
A comprehensive compendium of Arabidopsis RNA-seq data
(Colorado State University. Libraries, 2020) Halladay, Gareth A., author; Ben-Hur, Asa, advisor; Chitsaz, Hamidreza, committee member; Reddy, Anireddy, committee member
In the last fifteen years, the amount of publicly available genomic sequencing data has doubled every few months. Analyzing large collections of RNA-seq datasets can provide insights that are not available when analyzing data from single experiments. There are barriers towards such analyses: combining processed data is challenging because varying methods for processing data make it difficult to compare data across studies; combining data in raw form is challenging because of the resources needed to process the data. Multiple RNA-seq compendiums, which are curated sets of RNA-seq data that have been pre-processed in a uniform fashion, exist; however, there is no such resource in plants. We created a comprehensive compendium for Arabidopsis thaliana using a pipeline based on Snakemake. We downloaded over 80 Arabidopsis studies from the Sequence Read Archive. Through a strict set of criteria, we chose 35 studies containing a total of 700 biological replicates, with a focus on the response of different Arabidopsis tissues to a variety of stresses. In order to make the studies comparable, we hand-curated the metadata, pre-processed and analyzed each sample using our pipeline. We performed exploratory analysis on the samples in our compendium for quality control, and to identify biologically distinct subgroups, using PCA and t-SNE. We discuss the differences between these two methods and show that the data separates primarily by tissue type, and to a lesser extent, by the type of stress. We identified treatment conditions for each study and generated three lists: differentially expressed genes, differentially expressed introns, and genes that were differentially expressed under multiple conditions. We then visually analyzed these groups, looking for overarching patterns within the data, finding around a thousand genes that participate in stress response across tissues and stresses.
Embargo
A comprehensive study of Salmonella infections and microbial analysis of probiotics on beef cattle
(Colorado State University. Libraries, 2023) Thompson, Tyler Warren, author; Nair, Mahesh Narayanan, advisor; Geornaras, Ifigenia, committee member; Belk, Keith, committee member; Noyes, Noelle, committee member; Morley, Paul, committee member
Non-typhoidal Salmonella remains a significant concern for food safety in the United States, causing millions of infections, hospitalizations, and deaths yearly. The Healthy People 2030 initiative set forth by the U.S. Department of Health and Human Services aims to address this issue by establishing goals and objectives for national health promotion and disease prevention, including two objectives focused on Salmonella control in the food supply. The recent declaration of Salmonella as an adulterant in certain poultry products by the U.S. Department of Agriculture further highlights the urgency of this issue. To align with the Healthy People 2030 goals and achieve a 25% reduction in salmonellosis, the U.S. Department of Agriculture's Food Safety and Inspection Service (FSIS) implemented new performance standards for beef products. However, such policies must be supported by quantitative microbial risk assessments (QMRA) to determine their impact on Salmonella infections. Therefore, these analyses would benefit from a systematic review examining existing literature on Salmonella, considering factors such as illness rates, exposure, and bacterial loads. This review included 42 articles that provided data necessary for fitting a dose-response model to empirical data that describes how dose, virulence group, and food vector affect illness (attack) rates. Results from the mixed-effects logistic regression model showed significant impacts of log dose consumed, virulence group, and food vector on illness rates. Notably, Salmonella serogroups of "Higher" virulence were found to be associated with greater odds of illness than "Lower" virulence strains. The study highlights the need for improved data reporting and standardized outbreak investigations to enhance the fitting of models to outbreak data. By considering factors like serovar group and food vector in the modeling process, regulators can demonstrate what influences attack rate to frame more effective food safety policies. In conclusion, this systematic review provides valuable insights into Salmonella infection risk from food sources and emphasizes the importance of evidence-based policies to reduce the burden of Salmonella-related illnesses and improve food safety in the United States. Liver abscesses in beef cattle are a common problem associated with highly-fermentable carbohydrate diets during finishing, leading to decreased production efficiency and aggregate carcass value. Dietary antimicrobial supplementation, such as tylosin, helps to control liver abscesses but raises concerns about selection for antimicrobial resistance. This study examined the impact of a probiotic mixture of propionic and lactic acid bacteria on microbial communities and antimicrobial resistance genes (ARGs) in fecal and liver abscess samples from beef cattle alongside Salmonella populations of mesenteric lymphatic tissues. Treatment diets fed in this study included a probiotic mixture alone (DFM), inclusion of Tylosin (TYL), a combination of including both (DFM+TYL), and a control group diet that did not include any supplements (CON). Fecal samples were collected at the time that feeding started, and then 28 d before arriving at the abattoir, where liver abscesses and mesenteric lymph nodes were sampled. Fecal and liver abscess samples were subjected to 16S rRNA and targeted enriched shotgun metagenomics to evaluate microbial communities and resistance genes of bacteria present. A portion of the liver abscess and mesenteric lymph nodes were tested for presence of Salmonella using PCR with further analysis of enumeration and serotype classification for mesenteric lymph nodes. Results showed no differences (P > 0.05) between the fecal microbiomes of the different treatment groups, and the addition of tylosin or probiotic mixture did not impact the fecal resistome. Similarly, no differences (P > 0.05) were observed between the liver abscess microbiomes of the different (P > 0.05) treatment groups, with Fusobacteria and Bacteroidetes being the dominant phyla in liver abscesses. Results indicated that incorporating DFMs did not affect Salmonella prevalence in the cattle's mesenteric lymph nodes or liver abscesses. Presence of Salmonella was found at low levels in only 22% of samples (91 positive out of 503 samples), just below 1 log CFU/g, and was predominantly represented by the C1 serogroup in mesenteric lymph nodes. These findings suggest that while diet interventions may not have a substantial impact, Salmonella can colonize mesenteric lymphatic tissues in cattle at low frequencies and concentrations. Treatment groups tested had no impact (P > 0.05) on fecal and liver abscesses microbiomes and resistance gene presence, along with no impact on Salmonella prevalence in liver abscesses or mesenteric lymphatic tissues.
Open Access
A conductor's analysis: John Mackey's Wine-dark sea: symphony for band
(Colorado State University. Libraries, 2020) Weber, Shannon Denise, author; Phillips, Rebecca, advisor; Grapes, K. Dawn, committee member; Kenney, Wes, committee member; Pedrós-Gascón, Antonio, committee member
This thesis provides a study of the composer John Mackey and his music. In the last twelve years, Mackey has become internationally renowned and one of the most widely performed composers in the band world. Mackey has received numerous awards and honors for his musical contributions. His unique compositional style is distinguishable in his works regardless of the genre. Audiences, conductors, and performers alike continue to find enjoyment in his music due to his creative, rhythmic, and unique scoring for winds and percussion. This document includes biographical information on the composer, provides insight into his compositional style, and thoroughly analyzes the symphony for band, Wine-Dark Sea. Wine- Dark Sea was commissioned in 2014 by Jerry Junkin and the University of Texas Wind Ensemble, in celebration of the 100th anniversary of the Sarah and Ernest Butler School of Music. The symphony is a programmatic piece that tells the story of Odysseus, Homer's hero from The Odyssey, through three exciting and dramatic movements. Distinctive characteristics of this piece include Mackey's unique use of meter changes, extended techniques in winds and percussion, and recurring programmatic themes. Wine-Dark Sea is Mackey's longest work to date, one of his most challenging works for performers and conductor, and is especially captivating for the audience.
Open Access
A conductors guide to the use of ensemble pedaling and acoustic recreation of electronic delay processing in the wind band music of Viet Cuong
(Colorado State University. Libraries, 2023) Pouncey, Benjamin Allen, author; Phillips, Rebecca L., advisor; Grapes, K. Dawn, committee member; Taylor, James, committee member; Doe, Sue, committee member
The purpose of this thesis is to provide a conductor's analysis of two unique orchestration techniques utilized in Viet Cuong's wind band music. Viet Cuong (b. 1990) is an award–winning contemporary American composer whose eclectic sound has been described as "alluring" and "wildly inventive" by The New York Times. Two approaches to orchestration have been identified by the composer as distinctive elements of his compositional voice: ensemble pedaling, and the acoustic recreation of electronic delay processing. Sound and Smoke (2011) is Cuong's earliest available work for wind band and exemplifies early application of these techniques. Over the course of his career, Cuong has continued to employ and develop these approaches in select works, including Vital Sines (2022). Therefore, this document provides detailed examination of ensemble pedaling, and the acoustic recreation of electronic delay processing appearing in Cuong's Sound and Smoke, with select examples provided from Vital Sines to serve as a comparison of these techniques in the composer's recent body of work. The research conducted was completed concurrently with the Colorado State University Wind Symphony's performance preparation of Sound and Smoke in the 2023 spring semester. The information presented serves as a resource for the preparation and performance of Viet Cuong's music for wind band.
Open Access
A critical analysis of participatory research in the social sciences
(Colorado State University. Libraries, 2022) Russell, Gregory, author; Champ, Joseph, advisor; Arthur, Tori, committee member; Carcasson, Martin, committee member; Flores, David, committee member; Humphrey, Michael, committee member
In this dissertation, I put forward ethical, methodological, and epistemological reasons that warrant the presence of participants in the appraisal of social scientific research products. I discuss the nature of appraisal through Wittgenstein's linguistic philosophy and use it to support the claim that participatory research holds the capacity to improve formalized appraisal processes in cultural research. Extending the critique into a consideration of Western and Indigenous epistemologies, I attempt to deconstruct the ways in which Western academic research, specifically social scientific research, perpetrates colonialism and how, through participatory research, social scientific research practices might begin the process of decolonization. I then discuss how descriptive analytic techniques can make participant appraisal viable in academic contexts by showing how participatory strategies can license non-immersive data-collection methods, e.g., general interview-based research, in ways that are typically associated with those that are immersive, e.g., participant-observation.
Embargo
A data-driven characterization of municipal water uses in the contiguous United States of America
(Colorado State University. Libraries, 2024) Chinnasamy, Cibi Vishnu, author; Arabi, Mazdak, advisor; Sharvelle, Sybil, committee member; Warziniack, Travis, committee member; Goemans, Christopher, committee member
Municipal water systems in the United States (U.S.) are facing increasing challenges due to changing urban population dynamics and socio-economic conditions as well as from the impacts of weather extremities on water availability and quality. These challenges pose a serious risk to the municipal water providers by hindering their ability to continue providing safe drinking water to residents while also securing adequate supply for economic growth. A data-driven approach has been developed in this study to characterize the trends, patterns, and urban scaling relationships in municipal water consumption across the Contiguous United States. Then using sophisticated and robust statistical methods, water consumption patterns are modeled, identifying key climatic, socio-economic, and regional factors. The first chapter of this data-driven study looked at municipal water uses of 126 cities and towns across the U.S. from 2005 to 2017, analyzing the temporal trends and spatial patterns in water consumption and identifying the influencing factors. Water usage in gallons per person per day, ratio of commercial, industrial, and institutional (CII) to Residential water use, and percent outdoor water consumption were statistically calculated using aggregated monthly and annual water use data. The end goal was to statistically relate the variations in CII to Residential water use ratio across the municipalities with their local climatic, socio-economic, and regional factors. The results indicate an overall decreasing trend in municipal water use, 2.6 gallons per person annually, with greater reductions achieved in the residential sector. Both Residential and CII water use exhibit significant seasonality over an average year. Large cities, particularly in the southern and western parts of the U.S. with arid climates, had the highest demand for water but also showed the largest annual reductions in their per capita water consumption. This study also revealed that outdoor water use varied significantly from 3 to 64 percent of the Total water consumption across the U.S., and it was highest in smaller cities in the western and arid regions. Factors such as April precipitation, annual vapor pressure deficit, number of employees in the manufacturing sector, total percentage of houses built before 1950, and total percentage of single-family houses explain much of the variation in CII to Residential water use ratio across the CONUS. The second chapter leverages high-resolution, smart-metered water use data from over 900 single-family households in Arizona for the water year 2021. This part of the study characterizes the determinants or drivers of water consumption patterns, specifically in single-family households, and presents a framework of statistical methods for analyzing smart-metered water consumption data in future research. A novel approach was developed to characterize household appliance efficiency levels using clustering techniques on 5-second interval data. Integrating water consumption data with detailed spatial information of the household and building characteristics, along with local climatic factors, yielded a robust mixed-effects model that captured the variations in household water uses with high accuracy at a monthly time-step. Local air temperature, household occupancy level, presence of a swimming pool, the year the household was built, and the efficiency of indoor appliances and irrigation systems were exhibited to be the key factors influencing variations in household water use. The third and fourth chapter of this study reanalyzed the water consumption data of those 126 municipalities. The third chapter dwelled into the estimation of the state of water consumption efficiencies or economics of scale in the municipal water systems using an econometrics framework called urban scaling theory. A parsimonious mixed-effects model that combined the effects of socio-economic, built environment, and regional factors, such as climate zones and water use type, was developed to model annual water uses. The results confirm efficiencies in water systems as cities grow and become denser, with CII water use category showing the highest efficiency gains followed by the Residential and Total water use categories. A key finding is the estimation of the unique variations in water use efficiency patterns across the U.S. These variations are influenced by factors such as population, housing characteristics, the combined effects of climate type and geographical location of the cities, and the type of water use category (Residential or CII) that dominates in each city. The fourth or the final chapter synthesizes the lessons learned previously about the drivers of municipal water uses and explores the development of a model for predicting monthly water consumption patterns using machine learning algorithms. These algorithms demonstrated improved capabilities in predicting the Total monthly water use more accurately than the previous modeling efforts, also controlling for factors with multi-collinearity. Climatic variables (like precipitation and vapor pressure deficit), socio-economic and built environment variables (such as income level and housing characteristics), and regional factors (including climate type and water use type dominance in a city), were confirmed by the machine learning algorithms to strongly influence and cause variations in the municipal water consumption patterns. Overall, this study showcases the power of data-driven approaches to effectively understand the nuances in municipal water uses. Integration of the lessons learned and the statistical frameworks used in this study can empower water utilities and city planners to manage municipal water demands with greater resiliency and efficiency.