How does behavior drive population and community dynamics of rodents?

Understanding how population and community dynamics emerge from individual traits is essential to predict responses of animal populations and communities to habitat alterations. Individuals make decisions and are the basic unit of response to changes in the environment. Changes at the individual level can translate to population and community dynamics. Anthropogenic changes to environmental conditions occur frequently and rapidly. One anthropogenic change, biofuel feedstock production, is increasing to reduce dependency on fossil fuels. Switchgrass (Panicum virgatum) is a biofuel feedstock being planted between rows of loblolly pine (Pinus taeda). I hypothesized that changes in understory vegetation from intercropping switchgrass in pine plantations would alter intraspecific interactions, influencing individual behavioral decisions, which would then drive changes in population and community dynamics. My research aims were to assess effects of three treatments (switchgrass monocrop, switchgrass intercropped in loblolly pine, and control loblolly pine) on rodent: 1) population dynamics and community structure; 2) spatial and foraging behaviors, and patterns of reproduction; and 3) behaviors as predictors of population dynamics and community structure. My model species was the hispid cotton rat (Sigmodon hispidus), a common grassland specialist and early successional species. The cotton rat was a suitable model species because it has a relatively large geographic distribution, was easily captured at our site, and was expected to respond to change in grassy understory habitat. I studied the rodent community because they are ecosystem engineers, both prey and predators, and indicators of biodiversity. I used vegetation surveys, live-trapping, radio telemetry, giving-up density surveys, and individual-based modeling (IBM). Monocrop plots were ecological sinks with high adult cotton rat abundance but low juvenile recruitment, and control plots were ecological sources with low adult cotton rat abundance but high juvenile recruitment (Chapter II). Intercrop plots were intermediate for adult cotton rat abundance and juvenile recruitment, likely due to the mixture of cover and food (Chapter II). I also found cotton rats foraged more in monocrop than control plots, with intermediate foraging in intercrop plots (Chapter III). Females in control plots tolerated territory overlap with other females in areas with high amounts of grass (Chapter III). Then, based on an IBM, I found cotton rat populations would persist throughout 10-years of the current management in intercrop plots (Chapter IV). However, if management resulted in reduced non-grass cover, cotton rat populations would decline, whereas if management resulted in additional non-grass cover, cotton rat populations would increase in intercrop plots compared to predicted populations under current management (Chapter IV). Understanding behavioral responses as mechanisms underlying population and community level responses, allowed me to develop and use a functional and predictive IBM. My IBM can be used to predict responses of various prey species to management techniques that affect food and cover resources. My research helped to elucidate properties of populations and communities to better inform, and improve top-down predictive models and management decisions

Winter Activity of Coastal Plain Populations of Bat Species Affected by White-Nose Syndrome and Wind Energy Facilities

Across the entire distribution of a species, populations may have variable responses to environmental perturbations. Many bat species experience mortality in large portions of their range during hibernation and along migratory paths to and from wintering grounds, from White-nose syndrome (WNS) and wind energy development, respectively. In some areas, warm temperatures may allow bats to remain active through winter, thus decreasing their susceptibility to WNS and/or mortality associated with migration to wintering grounds. These areas could act as a refugia and be important for the persistence of local populations. To determine if warmer temperatures affect bat activity, we compared year-round activity of bat populations in the Coastal Plain and Piedmont of North Carolina, USA, two regions that differ in winter temperature. We established six recording stations, four along a 295-kilometer north-south transect in the Coastal Plain, and two in the Piedmont of North Carolina. We recorded bat activity over two years. We supplemented our recordings with mist-net data. Although bat activity was lower during winter at all sites, the odds of recording a bat during winter were higher at Coastal Plain sites when compared with Piedmont sites. Further, bats in the Piedmont had a lower level of winter activity compared to summer activity than bats in the Coastal Plain that had more similar levels of activity in the winter and summer. We found high bat species richness on the Coastal Plain in winter, with winter-active species including those known to hibernate throughout most of their range and others known to be long distance migrants. In particular, two species impacted by WNS, the northern long-eared bat (Myotis septentrionalis) and tricolored bat (Perimyotis subflavus), were present year round in the Coastal Plain. The tricolored bat was also present year-round in the Piedmont. In the Coastal Plain, the long distance migratory hoary bat (Lasiurus cinereus) was active in the winter but not present during the other seasons, and the long distance migratory silver-haired bat (Lasionycteris noctivagans) was active primarily in the winter, suggesting the Coastal Plain may be an overwintering ground for these two species. We suggest that the winter activity exhibited by populations of bats on the North Carolina Coastal Plain has important conservation implications and these populations should be carefully monitored and afforded protection

Glycemic Control Patterns and Kidney Disease Progression among Primary Care Patients with Diabetes Mellitus

Background: Reducing glycosylated hemoglobin (HbA1c) to near or less than 7% in patients with diabetes is associated with diminished microvascular complications, but this level is not consistently achieved. The purpose of this study was to examine the relationship between fluctuations in HbA1c and changes in estimated glomerular filtration rate (eGFR) and estimated stage of chronic kidney disease (CKD) in an academic primary care practice. Methods: We analyzed data from 791 diabetic primary care patients (25% white; 75% African American) enrolled between 1998 to 2002 and followed through 2008 (mean follow-up, 7.6 1.9 years). We calculated baseline and final follow-up eGFR using the Modification of Diet in Renal Disease equation. We examined the relationship between fluctuations in HbA1c and changes in eGFR and stage of CKD using multivariable linear and logistic regression models that controlled for demographic and clinical variables associated with CKD progression. Results: From baseline to follow-up, mean eGFR in African Americans declined to a greater extent and more rapidly than in whites. Age, mean systolic blood pressure, initial HbA1c, initial eGFR, and number of HbA1c values (all P 7% (P < .02); however, this contributed little to explaining model variance. Conclusion: These data suggest that traditional demographic and clinical risk factors remain significantly associated with changes in eGFR and that the pattern of variability in HbA1c is only modestly important in contributing to changes in eGFR among African-American and white diabetic patients in primary care

2020-2021 Supreme Court Preview: Notebook Cover Page

Our traditional notebook will not be available this year due to the virtual setting. However, we have compiled this virtual notebook to provide all participating in the Supreme Court Preview an opportunity to learn more about the upcoming docket and the issues facing the Court. We hope you enjoy the wealth of information available throughout this virtual notebook

Developments in algorithmic management from an IR-perspective : Denmark

The INCODING project studies dynamics in the (co)governance of Algorithmic Management and Artificial Intelligence-techniques from a Comparative Industrial Relations-perspective. By identifying the main challenges for workers and their representatives, it aims to explore how to contribute to Inclusive and Transparent Algorithmic Management. The present stock tacking reports provide an insight on the latest developments in this field in Denmar

Multi-Bunch Instability Diagnostics via Digital Feedback Systems

Longitudinal feedback systems based on a common programmable DSP architecture have been commissioned at 4 laboratories. In addition to longitudinal feedback and beam diagnostics these exible systems have been programmed to provide diagnostics for tranverse motion. The diagnostic functions are based on transient domain techniques which record the response of every bunch while the feedback system manipulates the beam. Operational experience from 4 installations is illustrated via experimental results from PEP-II, DA NE, ALS and SPEAR. Modal growth and damping rates for transverse and longitudinal planes are measured via short (20 ms) transient excitations for unstable and stable coupled-bunch modes. Data from steady-state measurements are used to identify unstable modes, noise-driven beam motion, and noise sources. Techniques are illustrated which allow the prediction of instability thresholds from low-current measurements of stable beams. Tranverse bunch train grow-damp sequences which measure the time evolution of instabilities along the bunch train are presented and compared to signatures expected from ion and fast ion instabilities. Invited talk presented at the IEEE Particle Accelerator Conference (PAC99

Multi-Bunch Longitudinal Dynamics and Diagnostics via a Digital

A bunch-by-bunch longitudinal feedback system based on a programmable DSP architecture is used to study coupled-bunch motion and its sources. Experimental results are presented from PEP-II, DA NE, ALS and SPEAR to highlight the operational experience from 4 installations, plus show novel accelerator diagnostics possible with the digital processing system. Modal growth and damping rates are measured via short ( 20 ms) transient recordings for unstable and stable coupled-bunch modes. Data from steady-state measurements are used to identify unstable modes and noise-driven beam motion. Anovel impedance measurement technique is presented which reveals the longitudinal impedance as a function of frequency. This technique uses the measured synchronous phase and charge of every bucket to calculate the impedance seen by the beam at revolution harmonics

Machine learning can identify newly diagnosed patients with CLL at high risk of infection

Infections have become the major cause of morbidity and mortality among patients with chronic lymphocytic leukemia (CLL) due to immune dysfunction and cytotoxic CLL treatment. Yet, predictive models for infection are missing. In this work, we develop the CLL Treatment-Infection Model (CLL-TIM) that identifies patients at risk of infection or CLL treatment within 2 years of diagnosis as validated on both internal and external cohorts. CLL-TIM is an ensemble algorithm composed of 28 machine learning algorithms based on data from 4,149 patients with CLL. The model is capable of dealing with heterogeneous data, including the high rates of missing data to be expected in the real-world setting, with a precision of 72% and a recall of 75%. To address concerns regarding the use of complex machine learning algorithms in the clinic, for each patient with CLL, CLL-TIM provides explainable predictions through uncertainty estimates and personalized risk factors

Near fatal posterior reversible encephalopathy syndrome complicating chronic liver failure and treated by induced hypothermia and dialysis: a case report

<p>Abstract</p> <p>Introduction</p> <p>Posterior reversible encephalopathy syndrome is a clinico-neuroradiological entity characterized by headache, vomiting, altered mental status, blurred vision and seizures with neuroimaging studies demonstrating white-gray matter edema involving predominantly the posterior region of the brain.</p> <p>Case presentation</p> <p>We report a 47-year-old Caucasian man with liver cirrhosis who developed posterior reversible encephalopathy syndrome following an upper gastrointestinal hemorrhage and who was managed with induced hypothermia for control of intracranial hypertension and continuous veno-venous hemodiafiltration for severe hyperammonemia.</p> <p>Conclusion</p> <p>We believe this is the first documented case report of posterior reversible encephalopathy syndrome associated with cirrhosis as well as the first report of the use of induced hypothermia and continuous veno-venous hemodiafiltration in this setting.</p