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  Occupancy of Terrestrial Mammal Populations in U.S. National Parks of the Southwest

  Prudic, Kathleen L.; Buckisch, Alexander; Steidl, Robert J.; Hubbard, John A. (The University of Arizona., 2021)

  North American mammal populations face many novel and powerful threats that are changing quickly over space and time. To complicate management and conservation decisions further, few established monitoring programs that can reliably detect changes in multiple mammal populations across species exist. Knowledge about the persistent threats and long-term trends of mammal populations are of immense importance to the public, the scientific community, as well as federal and state agencies charged with managing and protecting natural resources. We used an existing camera-based protocol to estimate occupancy of several terrestrial mammal species in seven U.S. National Parks in the Sonoran Desert. We surveyed 241 sites for 365 days to evaluate the detection efficiency (detected vs expected species) in different park units, evaluate a set of environmental variables with the potential to influence occupancy (ψ) and detection (p) probabilities of terrestrial mammals, and to estimate statistical power of the protocol to detect changes in occupancy. On average, we detected 76% (95% CI: 64% – 88%) of medium-to-large sized, native, mammals known to be present in surveyed park units. Mean occupancy across all park units ranged from 0.79 (0.10 – 0.86) for coyote (Canis latrans) to 0.12 (0.04 – 0.28) for black bear (Ursus americanus). Mean detection probability was highest for black-tailed jackrabbit (Lepus californicus) (0.35, 0.27 – 0.45) and lowest for mountain lion (Puma concolor) (0.06, 0.02 – 0.19). For many species, occupancy decreased as elevation and slope increased, and detection probability increased as precipitation increased during the study period. In addition, statistical power to detect changes in occupancy between two surveys was influenced mostly by occupancy and the number of sites surveyed. Power to detect changes in occupancy only increased to around 35 survey occasions (deployment days) above which it was relatively insensitive to increases in the number of survey occasions. Similarly, species with a higher initial occupancy achieved power to detect a change in occupancy faster (fewer survey occasions) and with less survey effort (fewer sites) than species with lower initial occupancy, whereas power was insensitive to changes in detection probability above 0.40. The camera trapping protocol we evaluated is sufficient to detect changes in occupancy with high power for species that are common (ψ = 0.80 – 0.99) and relatively easy to detect (p = 0.20 – 0.99), but not for species that are rare (ψ = 0.10 – 0.50) or difficult to detect (p = 0.10 – 0.19). For rare species, we suggest increasing detection probability by using lures and baits, increasing the duration of the survey period and surveyed sites, or strategically placing cameras in known areas of high activity. We conclude that the camera trapping design is well suited for simultaneously and cost-effectively monitoring terrestrial mammal communities within and between park units over the long term. This monitoring protocol has potential to inform conservation and management of mammals within the NPS and many other areas of North America.
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  On Lieb-Robinson Bounds in Open Quantum Systems

  Sims, Robert; Roon, Eric Brandon; Ercolani, Nicholas; Keller, Christoph (The University of Arizona., 2021)

  In 1971, A. Kossakowski \cite{kossakowski} axiomatized the study of the dynamics associated to non-Hamiltonian systems of quantum particles. These have come to be known as Open Systems, and through the work of Lindblad \cite{Lindblad76}, a classification of the generators of the dynamics of such systems in the Heisenberg picture -- for bounded generators -- is known (this is not so for the unbounded case). Following the work of Gorini, Kossakowski, and Sudarshan: \cite{gks}; we prove this classification scheme in finite dimensions, where it is accessible by computational means as in \cite{alickifannes}. With this knowledge, we prove a Lieb-Robinson bound for the irreversible dynamics in the case of time-independent interactions on a countable (possibly infinite) collection of sites. Such a result was proven by \cite{Nachtergaele} for the time-dependent case, in 2011.
• The Origins and Evolution of an Early Microbial Rhodopsin Protein

  Kacar, Betul; Sephus, Cathryn Dawn; Gutenkunst, Ryan; Duhamel, Solange (The University of Arizona., 2021)

  The advent of cellular organisms took place sometime between the start of prebiotic chemosynthesis on Earth and the evolution of the last universal common ancestor. Cellularity is now a fundamental organizational principle shared by all life on Earth and represents a key transition in evolutionary history. The emergence of cellular organization necessitated organisms to evolve a means to permit and regulate the exchange of material between the intracellular compartment and the extracellular environment. This capability implies both the ability to embed proteins into their membranes and to translocate molecules across their membranes. Other factors integral to the progression of early cellular life were the maintenance of transmembrane potential and chemiosmotic coupling for generating and conserving energy, and pigments to absorb light energy for photosynthetic and phototrophic metabolisms. Microbial rhodopsins, a superfamily of photoactive membrane proteins, have been suggested to be the simplest and possibly most ancient form of a phototrophic metabolism, likely providing a mechanism for microbial energy capture in Earth’s early shallow marine ecosystems. The retinal-based photosystem (rhodopsin) is composed of one retinal chromophore and one opsin protein. In this system, light absorption directly drives a conformational change in the protein via the isomerization of the retinal moiety to carry out biological functions such as ion pumping and ATP synthesis. Here, computational approaches were used to investigate the evolutionary history of rhodopsin proteins, combining phylogenic reconstruction and ancestral sequence inferences. Additionally, protein structure modeling and biophysical predictions were used to reveal ancestral rhodopsin functionality. Together, these results may shed light on the evolution of pigment-based metabolisms and prove beneficial for understanding the characteristics of early cellular membranes.
• Wavelet Analysis as a Non-Stationary Approach to Validate a Simulated Mosquito Model

  Brown, Heidi E.; Dixon, Ginger; Cazelles, Bernard; Pettygrove, Sydney (The University of Arizona., 2020)

  IntroductionThe Arizona Department of Health Services, Pinal County Public Health Services District, and the University of Arizona collaborated to reform current surveillance practices for mosquitos and West Nile Virus (WNV) with strategies that are resilient to changes in climate. The Dynamic Mosquito Simulated Model developed by Morin and Comrie (2010) uses daily precipitation and temperatures to estimate mosquito abundance and was adapted and validated by Brown et al. (2015) for both Culex quinquefasciatus and Cx. tarsalis mosquito vectors. We sought to verify that the simulated mosquito model can be used as a reliable substitute for observed data, and that wavelet analysis can be applied to verify simulated model data as a substitute or supplement for observed data. To our knowledge, wavelet analysis has rarely been used with WNV data and none have used wavelet analysis to validate simulated mosquito abundance data. MethodsData were collected in Pinal County from 2012 to 2018 and restricted to 2015 to 2018 when trap locations were sampled greater than 5 nights per year for analysis. Daily weather data time series values were collected from the PRISM Climate Group at Oregon State University. The dataset was analyzed using the Wavelet_EETS wavelet analysis program developed by Dr. Cazelles and Dr. Chavez (2003) for time series, power spectrum, global spectrum, and coherency plots. ResultsTime series plots of the simulated and observed mosquito abundance show similar patterns. The simulated mosquito season begins prior to and ends after the observed season and except for the beginning of 2018 when the observed season began later in May, the observed season begins within two weeks of late-March and ends within two weeks of early-November. An extended simulated season compared to observed season was noted around November 2017 for both species, which corresponded with warmer than average temperatures compared to 2016. Comparison of wavelet power spectrums and wavelet coherency for the observed and simulated data show similar spectral patterns at 1-year periods. The plot of the phase differences between the two time series demonstrates an average lag period of 3-6 weeks between season changes of the observed and simulated data, with more variability in phase differences noted for Cx. tarsalis. DiscussionThe similar patterns in the time series, power spectrum, and global spectrum plots as well as strong association in coherency analyses demonstrate that the simulated mosquito abundance model can reliably be used as a substitute or supplement for observed data, validating it’s use as a meteorologically-based early warning system for the Pinal County region and surrogate for surveillance data in further analyses. Based on the extended simulated season and average instantaneous lag, the recommended extension for surveillance trapping is from mid-February to mid-December.
• A Risk Assessment for 1,4-dioxane in Cosmetics and Drinking Water

  Beamer, Paloma; Ng, Natasha Sonia; Griffin, Stephanie; Burgess, Jeff (The University of Arizona., 2020)

  1,4-Dioxane is a potential carcinogen that is a contaminant of drinking water and cosmetics. The present study addressed route-specific and aggregate exposure from drinking water and cosmetics. Exposure rates were generated by modeling both exposure pathways in ConsExpo Web Version 1.0.7, 31-03-2020.The generation of exposure rates allowed for the examination of 1,4-dioxane exposure in individual cosmetic products, drinking water, total cosmetic exposure, and aggregate exposure. Water had the highest exposure rates with values ranging from 1.006 x 10 -5 – 3.781 x 10-4 mg/kg-day. Cosmetic exposure rates ranged from 1.30 x 10-10 – 2.239 x 10-4 mg/kg-day. Cosmetic categories with harsh ingredients that require ethoxylation had the highest exposure rates. Route-specific cosmetic and drinking water exposure were not of concern at all exposure percentiles. Aggregated exposure started to become of concern at the 99th percentile of exposure with an aggregate risk index (ARI) of 1.85.
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  Comparison of Mixed Models and Paired T-Test for Analyzing Crossover Clinical Trials in the Presence of Missing Data

  Bell, Melanie; Vicenti, Anthony; Watkins, Joe; Zhou, Jin (The University of Arizona., 2020)

  AB/BA crossover clinical trials are popular designs that can achieve high power with a lower number of subjects than other randomized control trial designs. They are often analyzed using paired t-test or mixed models, and like many clinical trials, are often impacted by missing data. Mixed models have been shown to produced more powerful and unbiased results in the presence of missing data than t-tests for other designs, but these two approaches have not been compared in crossover trials. We conducted a simulation study to compare the bias and power of paired t-tests and mixed models when analyzing an AB/BA crossover clinical trial in the presence of missing data. Several different missing structures were simulated under two within-subject correlations, ρ =0.3 and ρ =0.7. Both methods performed similarly when analyzing complete data, but the mixed model produced both equal or less bias estimates and higher power than the paired t-test under all simulation scenarios. In the worst-case scenario we considered, the t-tests resulted in percent bias up to -105% and power as low as 5% compared the mixed model’s percent bias of 1% and 57% power. In less severe cases, both methods had 0% bias, but mixed models still achieved an absolute power gain of 2%-6%. In the presence of missing data, the mixed model achieved higher power than the paired t-test under all simulated scenarios. The mixed model also achieved equal or less bias under all simulated scenarios. Therefore, mixed models should be used over paired t-test when analyzing AB/BA crossover clinical trial in the face of missing data.
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  Effects of Buffelgrass Removal and Nitrogen Addition on Soil Microbial Communities During an Extreme Drought in the Sonoran Desert

  Barberán, Albert; Williams, Jared Parker; Gornish, Elise; Blankinship, Joseph (The University of Arizona., 2020)

  Understanding the aboveground-belowground links between buffelgrass (Cenchrus ciliaris) invasion and soil microbial communities will be critical for developing a comprehensive understanding of arid ecosystems and for deploying successful control strategies. Buffelgrass, an invasive grass in the arid areas of the US, has drastically modified natural ecosystems. Buffelgrass control efforts have been generally unsuccessful, partly due to the insufficient understanding of how this species might alter belowground conditions in a way that promotes its own spread. In a randomized-block field experiment located at Tumamoc Hill, Arizona, we investigated the effects of buffelgrass removal via hand pulling and nitrogen addition (and their interaction) on soil microbial communities during an extreme drought. We found that these treatments did not significantly impact bacterial and archaeal community diversity and composition, while plant removal weakly affected fungal community diversity and composition. In addition, the removal treatment increased the proportion of putative chitinolytic bacteria (genus Lysobacter) and decreased the proportion of putative fungal endophytes (genus Darksidea). Buffelgrass manual removal may favor fungal endophyte death around and inside of leftover intact roots of buffelgrass, which may result in an increment of chitinolytic bacteria thriving on the degradation of fungal cell walls. Overall, my results suggest that buffelgrass removal can alter soil fungal communities and the proportion of certain microbial functional groups, and low levels of nitrogen addition during an extreme drought may not influence the effects of buffelgrass on soil microbial communities.
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  A 5-Axis Calibration System for Calibrating DOI-Correcting Gamma-Ray Detectors

  Furenlid, Lars R.; Anderson, Owen Adams; Kupinski, Matthew A.; Sabet, Hamid (The University of Arizona., 2020)

  Improving the resolution of pinhole single photon emission computed tomography (SPECT) depends on correcting parallax error at the edges of gamma-ray detectors. A novel way to achieve this is to use laser-induced optical barriers (LIOB) to restrict the spread of scintillation photons to a segment of the crystal that corresponds to a ray angle through the pinhole. The gains in resolution at the edge of the detector would be lost, however, without a way to use maximum likelihood (ML) position estimation to correlate detector response to the segment of the scintillation crystal where the gamma ray scintillated into visible photons. To find the response from a given segment of the crystal, a mean detector response function must be acquired from recording the mean detector responses when a known ray angle of gamma ray enters the detector. This motivates designing an building a novel calibration stage that has the ability to aim a pencil-beam of gamma rays into a detector at any position and angle that is possible with a photon traveling through the pinhole from the field of view.
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  Implementation of a Migrant Well-Child Health Toolkit for CAWC Healthcare Providers

  Peek, Gloanna J.; Warne, Adriana; Russell-Kibble, Audrey (The University of Arizona., 2020)

  Purpose. The purpose of this QI project was to implement a Migrant Well-Child Health Toolkit at Casa Alitas Welcome Center (CAWC) that serves as a guideline for volunteer medical professionals in conducting comprehensive well-child examinations on migrant children upon arrival to the migrant shelter in Tucson, Arizona.Background. Arizona is one of ten U.S. states that houses nearly three-quarters of children in immigrant families (Linton et al., 2016). The migrant population arrives with unique healthcare needs and is more likely to immigrate with pre-existing health conditions and exposure to traumatic events because of their turbulent migration histories (Seery et al., 2015). Conducting comprehensive well-child assessments on newly migrated children will prepare them for school entry, identify immediate health needs, assess developmental milestones, and ensure vaccinations are up to date (AAP, 2020a). Methods. This QI project used a pre and post-survey design. The Migrant Well-Child Health Toolkit is comprised of current recommendations for migrant well-child visits according to the AAP, CDC, WHO, Bright Futures Guidelines, SAMHSA, and Arizona’s EPSDT program. A pre-recorded PowerPoint presentation delivered provider training to the participants on the toolkit. A pre-survey assessed their prior knowledge of conducting well-child examinations on migrant children. The post-survey evaluated their learning and readiness to implement the intervention and included questions to determine the toolkit's initial validation. Results. A convenience sample of 10 participants (n=10) completed the project’s components with a response rate of 10.8%. All of the project’s outcomes were met; increased provider knowledge in migrant child health, confidence in performing well-child health screenings, and intent to conduct well-child health assessments at CAWC. Additionally, 90% (n=9) of CAWC providers indicated that the toolkit contains the resources necessary to conduct well-child screenings on migrant children. Conclusion. The findings suggest that the toolkit was developed with high-quality evidence, clear presentation, and offers the resources necessary to conduct well-child screenings at CAWC. This data serves as an initial step to inform future efforts that promote health equity and guides an implementation strategy to integrate the Migrant Well-Child Health Toolkit into clinical practice when caring for migrant children.
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  Modification of the Hot-Dry-Windy Index Using High Resolution Rapid Refresh Model Data

  Castro, Christopher L.; Schulze, Scott; Niu, Guo-Yue; Falk, Donald A. (The University of Arizona., 2020)

  Fire weather is defined as the meteorological conditions conducive to the rapid spread and intensification of a wildfire. It is generally agreed that sudden and rapid wildfire intensification is one of the greatest hazards facing wildfire managers today. The Hot-Dry-Windy (HDW) Index created by Srock et al. (2018) provides a means for predicting rapid wildfire intensification. A limitation of the HDW index is the temporal output of once every six hours when utilizing the National Centers for Environmental Prediction (NCEP) Coupled Forecast System Model Version 2 (CFsV2) data. The use of National Oceanic and Atmosphere Administration (NOAA) High Resolution Rapid Refresh (HRRR) model data has the benefits of being able to capture mesoscale processes along with a six-fold increase in the temporal outputs of the HDW index. This assists in the capture of a high fire spread rate due to a rapid change in meteorological conditions that would have been otherwise missed by the coarser resolution provided by the original model. This analysis was made with the meteorological model data in the window of a historic wildfire case featuring Santa Ana winds (SAWs). The HRRR data was found to be much more capable of modeling the terrain of the coastal mountain ranges in the southern California area. The mesoscale modeling capability also aided in the HDW Index not suffering as severely from artificially lowered values near the coast when compared with the CFsV2 output.
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  Using Coupled Hydrogeophysical Modeling to Assess the Relative Value of Proposed Gravity and Water Level Observations to Support Water Resources Decision Making

  Ferre, Paul; Dicke, Tristan; Yeh, Tian-Chyi Jim; Kennedy, Jeffrey R. (The University of Arizona., 2020)

  Decisions about the permitting of new groundwater extractions often depend on the perceived impact of those withdrawals on groundwater levels in wells and flow in nearby streams. Owing to subsurface abnormalities and varying hydraulic flow conditions that can occur in the subsurface, there is much uncertainty when assessing possible impacts. Using an ensemble modeling approach can better inform these decisions, which quantifies both the most likely outcome, and the associated uncertainty given, limits on subsurface hydrogeologic information. The ensemble approach encompasses the uncertainty that is possible in the domain by varying parameters in the model. Each model in the ensemble is weighted to a degree that reduces the uncertainty of future predictions, thereby improving decision making. Groundwater levels in wells are one of the most common hydrologic measurements, but it can be prohibitively expensive to drill wells to add new observation points to inform decision making. Time-lapse gravity measurements provide a proxy method to gain insight into the subsurface hydrologic conditions. While gravity measurements are less direct than groundwater levels, it can be considerably less expensive to add monitoring points. In this study, an ensemble of models is developed for a synthetic catchment. Forecasts of drawdown in one well due to the addition of another well are the prediction of interest (POI). This POI is then converted to a utility value to maximize the satisfaction for decision making. The accuracy and uncertainty of the forecasts are calculated with and without added observations (water levels and gravity). This is investigated for the addition of another well at three different locations. The result is a panel of maps of the basin showing the relative expected value of an added observation at each location for improving the satisfaction of decision-makers. This panel can be used to choose among monitoring well or gravity measurement locations before data are collected, dependent on the location of the additional well. The same approach can be extended to consider multiple measurements of different types.
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  Using Big-Data to Develop Catchment-Scale Hydrological Models for Chile

  Gupta, Hoshin V.; De la Fuente, Luis Andrés; Condon, Laura E.; Ferré, Paul Ty (The University of Arizona., 2021)

  Streamflow prediction is very important to the economic and human development of a country. For example, it is used in the quantification and distribution of the water resource, and in the design of new hydraulic infrastructure, risk quantification, rapid response to mitigate flooding, etc. For this reason, learning how to improve our estimation of streamflow must be one of the aspirations of any surface hydrologist. Chile has an extensive stream gauge network, which is part of the new CAMELS-CL database. This database also includes data about several static attributes for each of the 516 catchments represented within it, which provides us with a valuable database that can be used to develop process-based and data-based models with the ultimate goal of implementing a national hydrological model.Recent studies have shown that Machine Learning (ML) can provide better predictive performance than traditional process-based (PB) models. In hydrology, Kratzert et al. (2019), Nearing et al. (2020a), and others have reported similar results when comparing an ML-based model with the extensively studied and calibrated SAC-SMA and other benchmark models over the USA. This finding creates the opportunity to bridge the gap between ML-based and PB models by transferring insights gained via the process of developing a ML model into improvements of the PB model(s). With this in mind, we implemented the GR4J process-based catchment model as a baseline, and two ML-based models, Random Forest (RF) decision tree approach, and the Long-Short Term Memory (LSTM) dynamic state variable approach, on 322 selected Chilean catchments. The three models were compared in detail to examine their strengths and weakness, and to determine the best candidate for a national model. Our results showed that none of the three models performed “best” across the entire country, and all of them had problems in the north of Chile, indicating that additional informative attributes and variables must be incorporated into the database. Furthermore, the models showed complementary performance abilities, which opens the opportunity to develop an ensemble of the three or more models in the future to merge their respective strengths. Overall, the model performance results were found to be related to the meteorological forcings, but also with certain climatic conditions such as aridity, which emerges as an important variable to characterize the behaviors of different catchments.
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  Was the Himalaya Higher During the Mid-Miocene?

  Quade, Jay; Krupa, Anthony Joseph; DeCelles, Peter G.; Kapp, Paul A. (The University of Arizona., 2020)

  The uplift history of the Himalaya and Tibet is crucial to understanding both the geodynamic evolution of the orogen and its influence on the Asian climate system. Here we reconstruct paleoelevation in the northern Himalaya using the hydrogen isotope composition (δD) of synkinematic micas (dated to 13.4 ± 0.3 Ma) in a ductile shear zone bounding the Lhagoi Kangri dome. These micas equilibrated at high temperatures (447 ± 48°C) with a water composition (δD = -179‰ VSMOW) consistent with infiltration of high-elevation precipitation into the shear zone. We used multiple lapse rates to compare this value with contemporaneous sea-level precipitation recorded in Siwalik paleosol carbonate within the Himalayan foreland basin. These lapse rates provide paleoelevation estimates ranging from 5.8 – 6.5 km for the regional catchment that provided water to the shear zone during displacement, ~1 km higher than modern average elevation (~5 km). Similar late Miocene paleoelevation results from the Zhada basin ~850 km along strike to the west suggests that more than one area of the northern Himalaya experienced elevation loss during the late Neogene.
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  Territoriality in Transitional Justice and Land Restitution: Guatemala’s Communities of Population in Resistance After Resettlement

  Oglesby, Elizabeth; Treacy, Nathan; Banister, Jeffrey; Wilder, Margaret (The University of Arizona., 2020)

  Land and property restitution initiatives have received increasing attention in transitional justice debates, as calls have grown to examine the connections between transitional justice and broader issues of socioeconomic development. Drawing on insights from critical geography, this paper argues that land must be understood not only in terms of its economic value as a means of reparation, but also as a way for communities to contest state-making practices in the wake of violent conflict. Focusing on the experience of Guatemala’s Communities Population in Resistance of the Sierra (CPR–Sierra), a coalition of Mayan communities that fled the Guatemalan Army massacres of the early 1980s, resisted forced resettlement, and challenged the narrow, market-oriented approach of Guatemala’s post-war land restitution and reallocation schemes, I argue that the land restitution program carried out during Guatemala’s peace process constituted a multi-dimensional process of territorialization that had the effect of constraining and fragmenting possibilities for collective social organizing and coalition-building among resettled community groups. In responding to these processes, the meaning of land in restitution initiatives has been at the center of how the CPR–Sierra articulate their struggle today. In addition to its material significance, CPR communities today articulate land’s significance in symbolic and political terms as the geographic basis for an organized, nonviolent struggle against the Guatemalan state that they view as the only means of fulfilling the peace process.
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  The Neuropeptide Corazonin Promotes Higher Rates of Foraging in Apis mellifera Workers

  Corby-Harris, Vanessa; Dornhaus, Anna; Obernesser, Bethany Taylor; Nighorn, Alan (The University of Arizona., 2020)

  Honey bee workers take on specific roles within the colony. Young adult workers (~1 week old) perform in-hive tasks such as cleaning or brood care (“nursing”), while older workers forage for pollen, nectar, and water. This behavioral shift is regulated by hormones such as juvenile hormone (JH) and vitellogenin (vg), however the role of other hormones in this process is less-well understood. Additionally, stressors like poor nutrition and infection can accelerate this behavioral transition leading to precocious foraging and may result in reduced forager performance and accelerated colony decline. The neurohormone corazonin (crz), an 11 amino acid peptide with structural similarity to vertebrate gonadotropin-releasing hormone (GnRH) and invertebrate adipokinetic hormone (AKH), plays a part in determining caste identity in ants and other Hymenopterans. Harpegnathos ants performing nest-associated tasks have higher levels of vg and low levels of crz, while ants performing tasks outside of the nest have low vg and higher crz expression. Crz is a proposed stress hormone demonstrating a variety of functions across several groups of insects, however, the exact purpose of this hormone has yet to be identified in honey bees. In this study, I explore the molecular mechanism underlying the nutritional stress response that leads to precocious foraging, and whether crz is involved in this response. Additionally, I examine whether crz plays a role in the behavioral transition of honey bee nurses to foragers by injecting honey bee workers in the head with crz peptide. I found that although age did not have a significant effect on crz expression, starvation altered crz expression. Finally, I found that bees injected with crz take greater amounts of foraging trips than bees injected with a control and bees that were left un-injected.
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  Crohn's Disease: Dysbiosis and IL-7

  Wilson, Jean; Runyan, Raymond; Suarez, Shea'la; Zavros, Yana; Viswanathan, V.K. (The University of Arizona., 2020)

  Crohn's Disease (CD) is a chronic inflammatory bowel disease that destroys a patient's gastrointestinal (GI) tract. CD is thought to be mediated mostly by cluster of differentiation 4 (CD4)+ T helper 1 (TH1) T-cells initially in response to the commensal gut microbiota, leading to chronic inflammation and destruction of the intestines.1 Environmental factors, genetic predisposition, dysbiosis, and antibiotic use are some of the proposed mechanisms for CD development.2-4 The current treatments include anti-Interleukin(IL)-12/23 monoclonal5 antibody (mAb), anti-Tumor Necrosis Factor-α (TNF-α) mAb,6 antibiotics,7 corticosteroids,8, and anti-α4β7 mAb9 therapies. In some patients, these treatments do not allow long-term remission, and others become resistant to the medications. These therapies target downstream cytokines such as TNFα,6 α4β7,9, and IL-12/235 produced by effector T-cells (Teff). A new pharmaceutical target that looks promising is the cytokine IL-7. Commensal gut microbiota promotes Teff cells to make Interferon-γ (IFN-γ) that then stimulates intestinal epithelial cells (IECs) to produce IL-7, causing the upregulation of the α4β7 Teff cell gut-homing integrin. As more Teff cells migrate to the intestines and produce IFN-γ, increased IL-7 production by IECs occurs, creating a positive feedback loop.10, 11 Thus, decreasing IL-7 with a monoclonal antibody could decrease Teff cell migration to the intestines, and subsequently decrease the pro-inflammatory cytokines that promote chronic inflammation and tissue destruction seen in CD. Dysbiosis, the change in the microbiota profile that results in disease, has been strongly correlated to CD.12 However, the use of Fecal Microbiota Transplants (FMTs) to attempt to normalize the microbiota has not been entirely successful for all CD patients.13 Administering an anti-IL-7Rα mAb before FMT could decrease inflammatory cells, increasing the likelihood that the FMT is successful, and allow for remission in CD patients.
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  Feeding Trials Analyzing the Production Effects of Dietary Additives in Growing Cattle

  Diaz, Duarte E.; Grijalva, Pablo Cesar; Garcia, Samuel R.; Wulf, Duane M. (The University of Arizona., 2020)

  In the first study, thirty-two Hereford x Simmental steers (250.0±15 kg Initial BW) were assigned to four dietary treatments in a completely randomized design (4 steers/pen, 2 pens/treatment) in order to evaluate the effects of supplementing Monensin (MON; Rumensin; Elanco Animal Health, Greenfield, IN) in comparison and in combination (CMB) with a proprietary Probiotic blend (PRO; MultSacch®, Biomart Nutrição Animal Imp. and Exp. Ltda.) on the growth performance, feed efficiency, and on cost of gain. Individual feed intake was monitored using a GrowSafe System (GrowSafe Systems Ltd. Calgary, AB, Canada) and weights were recorded weekly for a 90 d growth data period. Supplementation with PRO and CMB both increased Gain:Feed (G:F) by 6% with respect to control (CON) steers (P = 0.01). No treatment effects were detected in initial body weight (IBW), final body weight (FBW), or average daily gain (ADG) (P > 0.05). DMI was lowest in CMB steers (P = 0.04), and this same group had the lowest cost of gain (P < 0.001). Our findings indicate that when compared with MON, PRO seems to be just as effective in stabilizing intraruminal milieu and increasing ruminal fiber utilization when steers are fed rapidly fermentable carbohydrate grain-based diets, thus improving feed efficiency without the need of MON supplementation. However, combined use of PRO and MON results in the lowest cost of gain (P = 0.03). Further experimentation is required to ascertain the effect substituting MON with different mixtures of probiotics will have long term on cattle growth performance and profitability. The second study consisted in feeding Red Angus steers (n=24; 260 ± 25 kg) in order to analyze the effects of supplementation of zilpaterol hydrochloride (ZH) under heat stress conditions on respiration rate (RR), rectal temperature (RT), growth performance (GP), Biological Impedance Analysis (BIA), carcass traits (CT), and complete blood count (CBC). Steers were randomly assigned to a 2 x 2 factorial treatment arrangement (n=6/group) with factors including heat stress (HS; Temperature Humidity Index (THI) = 73 to 85) or thermal neutral (TN; THI=68) conditions and with/without supplementation of ZH (0 or 8.38 mg/kg/d on 88% DM basis). Steers were provided 9 d to acclimate to tie stalls rooms under TN conditions before starting the study. TN steers were pair-fed to the average daily dry matter intake (DMI) of HS steers. Ad libitum water intake (WI) was recorded daily. HS and TN steers were harvested on d 22 and 23, respectively. By design, DMI did not differ between environment or supplement groups (P>0.31). Initial body weight did not differ between environments or supplement groups (P>0.62). RT, RR, and WI were greater (P<0.01) in HS steers compared to TN steers. There was a supplement by environment interaction (P=0.02) for RT, as HS steers fed ZH had lower RT than HS control steers (39.1 vs 39.5 ℃, respectively). Average Daily Gain (ADG) was 20% higher (P=0.04) in HS steers compared to TN steers. BIA phase angle (PA), resistance (R), and reactance (Rc) values were significantly lower in HS steers by 19%, 8.5%, and 25%, respectively (P ≤ 0.04). CT and CBC did not differ due to environment, treatment, or environment by treatment interactions (P>0.05). Our results suggest that feedlot steers under our experimental conditions display some sensitivity to HS through GP, RR, RT, and BIA; however, this does not translate to a significant impact on CT or CBC. Furthermore, ZH supplementation did not appear to impact animal well-being negatively.
• A Remote Sensing Method for Estimating Productivity Measures in Guayule Using High-Resolution Spectral and Structural Data

  Didan, Kamel; Combs, Truman Patrick; Jarchow, Christopher; Dierig, David; Waller, Peter (The University of Arizona., 2020)

  The agricultural sector, with its market-driven crop economics and evolving strategies toward resource and pest management, has entered the age of “precision” or “digital” farming. The ongoing efforts to commercialize guayule (Parthenium argentatum Gray) as an alternative source of natural rubber requires creative solutions to estimating crop productivity if the adoption of guayule rubber should expand and do so sustainably. Satellite remote sensing products such as the Normalized Difference Vegetation Index (NDVI) are often linked to plant phenology and common measures of plant development such as crop biomass (i.e., fresh or dry weight) or volume for large regions at coarse spatial resolutions (pixels that are tens-of-meters to kilometers in size). Similarly, commercially-available multispectral sensors mounted to unmanned aircraft systems (UAS; i.e., drones) now offer spatial resolutions well below one meter, effectively allowing for individual plant or leaf-level observations. Structure-from-Motion (SfM) photogrammetry, which re-creates 3-dimensional (3-D) scenes from dense collections of true-color images, is also being linked to biomass and volume measures via crop surface models which incorporate canopy height (CH) information. Until recently, these data were largely viewed independently. We assessed the performance of regression models integrating both NDVI and CH information for estimating measures of crop productivity, including fresh weight (FW), dry weight (DW), fresh volume (FV), fresh-weight-density (FWD; the fresh weight of plant material adjusted by its freshly harvested volume), and dry-weight-density (DWD; the dry weight of plant material adjusted by its freshly harvested volume). Model parameters included mean pixel NDVI, SfM-derived mean canopy height (CH), a term representing the interaction between NDVI and CH, and categorical variables representing the variability of resource allocation within the vertical profile (i.e., at multiple levels, or tiers) in guayule. The FWD model incorporating NDVI, CH, NDVI:CH interaction, and tier parameters reported a mean absolute percentage error (MAPE) between 9 and 13% when comparing field measurements and model predictions, the best-performer of all response variables considered. The full FWD model incorporating all independent variable terms was reduced to a model inclusive of only NDVI and tier parameters for comparison against model predictions based on Sentinel-2 satellite data, which lack canopy height information. MAPE between FWD model predictions based on UAS and satellite imagery were below 3% across all UAS surveys and corresponding satellite scenes evaluated, suggesting model predictions scaled to medium spatial resolution data sources are achievable and reliable.
• Innovative Algae-based Heatsink System for Data Center Integration

  Ida, Aletheia; Ghaemi, Sara; Hickenbottom, Kerri; Youssef, Omar (The University of Arizona., 2020)

  Rising carbon dioxide levels leading to global warming, along with the increasing demand for resources as the world population grows, cause an urgent need to expand renewable energy resources and promote their availability and affordability. The building industry, accountable for one third of global energy usage and forty percent of direct and indirect CO₂ emissions (Buildings A source of enormous untapped efficiency potential, 2020), should move past reliance on fossil fuel driven power plants, and become energy pods capable of self-reliance in clean energy generation through solar power and biofuels producing local energy for occupants needs. us Although developers and industry professionals have started incentivizing photovoltaics in large quantities and wind and water turbines occasionally, they have taken ephemeral steps to embrace biofuels, the source of renewable fuel capable of replacing fossil fuels. This thesis investigates the integration of photovoltaic bioreactors in hyperscale data centers as a testbed for large-scale biomass production units. The increasing dependence of society on information technology (IT) is becoming even more apparent amidst the global COVID-19 pandemic. As schools and businesses shift to online modalities, and regular communication between humans has shifted to internet-based contact, data centers grow rapidly. As a result, energy demands exponentially increase as servers run continuously and produce endless amounts of waste heat. According to the Office of Energy Efficiency and Renewable Energy (EERE), these facilities "are one of the most energy-intensive building types, consuming 10 to 50 times the energy per floor space of a typical commercial office building. Collectively, these spaces account for approximately 2% of the total U.S." (Strutt) Because of the extreme heat-generation from densely packed IT equipment, the data center provides a unique testbed for bio-based heat recovery and heat sink systems. Through this research two algae species - Chlorella Vulgaris (C. vulgaris) and Scenedesmus sp. (Scenedesmus) - , are used to examine the possibility of using water-based algae to utilize the excessive heat, cool the servers, reduce the buildings energy consumption and additionally their dependency on conventional cooling systems, and use the high heat capacity of water to store the heat produced by the systems during the day. Coupling the system with stack ventilation and night flush cooling tends to can reduce the buildings' mechanical cooling needs even further. A physical testbed for the algae species demonstrates information extracted from visual observation, growth rate measures, and temperature, light, and humidity sensing. Carbon dioxide sequestration potential is calculated based on rule-of-thumb literature review data. The accumulative data that was collected allows for a better understanding of algae behavior in uncontrolled temperatures and environments to inform innovative solutions to decrease data centers' energy consumption, carbon footprint, and utility bills.
• Characterizing the Atmospheric Mixed Layer During the North American Monsoon at Walnut Gulch Experimental Watershed

  Castro, Christopher L.; Zeng, Xubin; Perkins, John M.; Goodrich, Dave C. (The University of Arizona., 2020)

  The Haar wavelet covariance transform is applied to ground-based LIDAR backscatter profiles to provide high resolution local time series of planetary boundary layer (PBL) height. This method is used to produce a PBL height dataset at the USDA ARS Walnut Gulch Experimental Watershed (WGEW) in Tombstone, AZ over the 2017 summer North American monsoon season. The WGEW site has a long term record of hydrological and meteorological measurements in an arid environment with complex terrain and variable vegetation, which provides an interesting case to study of temporal and spatial variations of the convective PBL in such an environment, and their relationship to the development of summer air mass thunderstorms. PBL height is correlated with heat and moisture fluxes in the area, as well as precipitation rates and soil moisture, to help characterize the effects of recirculation of moisture over the course of the monsoon season on rainfall in the region. We find that the boundary layer tends toward lower heights of and later daily development over the course of the season, dropping around of 540 m on average by September. An analysis of dry-down times following active monsoon periods reveals a change of average PBL h of 220 m/day for the 3 days following significant rainfall, slowing to 80 m/day for the remaining 2 days before the lower atmosphere and surface dry out. Results are compared with a single slab boundary layer model based on surface sensible heat flux, and a strong linear correlation is found, especially earlier in the season, with an R2 of 0.992 for the month of June and an average R2 of 0.95 for the entire summer.

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