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Management of wolves is controversial in many jurisdictions where wolves live, which underscores the importance of rigor, transparency, and reproducibility when evaluating outcomes of management actions. Treves and Louchouarn 2022 (hereafter TL) predicted outcomes for various fall 2021 hunting scenarios following Wisconsin's judicially mandated hunting and trapping season in spring 2021, and concluded that even a zero harvest scenario could result in the wolf population declining below the population goal of 350 wolves specified in the 1999 Wisconsin wolf management plan. TL further concluded that with a fall harvest of > 16 wolves there was a "better than average possibility" that the wolf population size would decline below that 350-wolf threshold. We show that these conclusions are incorrect and that they resulted from mathematical errors and selected parameterizations that were consistently biased in the direction that maximized mortality and minimized reproduction (i.e., positively biased adult mortality, negatively biased pup survival, further halving pup survival to November, negatively biased number of breeding packs, and counting harvested wolves twice among the dead). These errors systematically exaggerated declines in predicted population size and resulted in erroneous conclusions that were not based on the best available or unbiased science. Corrected mathematical calculations and more rigorous parameterization resulted in predicted outcomes for the zero harvest scenario that more closely coincided with the empirical population estimates in 2022 following a judicially prevented fall hunt in 2021. Only in scenarios with simulated harvest of 300 or more wolves did probability of crossing the 350-wolf population threshold exceed zero. TL suggested that proponents of some policy positions bear a greater burden of proof than proponents of other positions to show that "their estimates are accurate, precise, and reproducible". In their analysis, TL failed to meet this standard that they demanded of others. [ABSTRACT FROM AUTHOR]

Reliable population estimates are important for making informed management decisions about wildlife species. Standardized survey protocols have been developed for monitoring population trends of the wood turtle (Glyptemys insculpta), a semi-aquatic freshwater turtle species of conservation concern throughout its distribution in east-central North America. The protocols use repeated active search surveys of defined areas, allowing for estimation of survey-specific detection probability (p) and site-specific abundance. These protocols assume population closure within the survey area during the survey period, which is unlikely to be met as wood turtles are a highly mobile species. Additionally, current protocols use a single-pass design that does not allow for separation of availability (pa) and detectability (pd). If there are systematic influences on pa or pd that are not accounted for in the survey design or data analysis, then resulting abundance estimates could be biased. The objectives of this study were to determine if pa is a random process and if pa and pd are influenced by demographic characteristics. We modified the wood turtle survey protocol used in the upper Midwest to include a double-pass design, allowing us to estimate pa and pd using a robust design capture-recapture model. The modified protocol was implemented at 14 wood turtle monitoring sites in Minnesota and Wisconsin between 2017 and 2022. Our results indicated that pa was non-random and that pd increased with turtle carapace length. Our study suggests that model assumptions for current wood turtle population models may be violated, likely resulting in an overestimation of abundance. We discuss possible protocol and modeling modifications that could result in more accurate wood turtle abundance estimates. [ABSTRACT FROM AUTHOR]

Background: The ACTION trial evaluated the effect of a modified version of the Respecting Choices´ advance care planning programme in patients with advanced cancer in six European countries. For this purpose, an advance directive acceptable for all six ACTION countries to be used for documenting the wishes and preferences of patients and as a communication tool between patients, their caregivers and healthcare staff, was needed. Aim: To describe the development of a multinational cancer specific advance directive, the ´My Preferences form´, which was first based on the 2005 Wisconsin 'Physician Orders of Life Sustaining Treatment´ Form, to be used within the ACTION trial. Methods: Framework analysis of all textual data produced by members of the international project team during the development of the ACTION advance directives (e.g. drafts, emails, meeting minutes...). Setting/participants: ACTION consortium members (N = 28) with input from clinicians from participating hospitals (N = 13) and ´facilitators´ (N = 8) who were going to deliver the intervention. Results: Ten versions of the ACTION advance directive, the ´My Preferences form´, were developed and circulated within the ACTION consortium. Extensive modifications took place; removal, addition, modification of themes and modification of clinical to lay terminology. The result was a thematically comprehensive advance directive to be used as a communication tool across the six European countries within the ACTION trial. Conclusion: This article shows the complex task of developing an advance directive suitable for cancer patients from six European countries; a process which required the resolution of several cross cultural differences in law, ethics, philosophy and practice. Our hope is that this paper can contribute to a deeper conceptual understanding of advance directives, their role in supporting decision making among patients approaching the end of life and be an inspiration to others wishing to develop a disease-specific advance directive or a standardised multinational advance directive. [ABSTRACT FROM AUTHOR]

COVID-19 mortality rates increase rapidly with age, are higher among men than women, and vary across racial/ethnic groups, but this is also true for other natural causes of death. Prior research on COVID-19 mortality rates and racial/ethnic disparities in those rates has not considered to what extent disparities reflect COVID-19-specific factors, versus preexisting health differences. This study examines both questions. We study the COVID-19-related increase in mortality risk and racial/ethnic disparities in COVID-19 mortality, and how both vary with age, gender, and time period. We use a novel measure validated in prior work, the COVID Excess Mortality Percentage (CEMP), defined as the COVID-19 mortality rate (Covid-MR), divided by the non-COVID natural mortality rate during the same time period (non-Covid NMR), converted to a percentage. The CEMP denominator uses Non-COVID NMR to adjust COVID-19 mortality risk for underlying population health. The CEMP measure generates insights which differ from those using two common measures–the COVID-MR and the all-cause excess mortality rate. By studying both CEMP and COVID-MRMR, we can separate the effects of background health from Covid-specific factors affecting COVID-19 mortality. We study how CEMP and COVID-MR vary by age, gender, race/ethnicity, and time period, using data on all adult decedents from natural causes in Indiana and Wisconsin over April 2020-June 2022 and Illinois over April 2020-December 2021. CEMP levels for racial and ethnic minority groups can be very high relative to White levels, especially for Hispanics in 2020 and the first-half of 2021. For example, during 2020, CEMP for Hispanics aged 18–59 was 68.9% versus 7.2% for non-Hispanic Whites; a ratio of 9.57:1. CEMP disparities are substantial but less extreme for other demographic groups. Disparities were generally lower after age 60 and declined over our sample period. Differences in socio-economic status and education explain only a small part of these disparities. [ABSTRACT FROM AUTHOR]

Objective: Specialty care may improve diabetic foot ulcer outcomes. Medically underserved populations receive less specialty care. We aimed to determine the association between specialty care and ulcer progression, major amputation, or death. If a beneficial association is found, increasing access to specialty care might help advance health equity. Research design and methods: We retrospectively analyzed a cohort of Wisconsin and Illinois Medicare patients with diabetic foot ulcers (n = 55,409), stratified by ulcer severity (i.e., early stage, osteomyelitis, or gangrene). Within each stratum, we constructed Kaplan-Meier curves for event-free survival, defining events as: ulcer progression, major amputation, or death. Patients were grouped based on whether they received specialty care from at least one of six disciplines: endocrinology, infectious disease, orthopedic surgery, plastic surgery, podiatry, and vascular surgery. Multivariate Cox proportional hazard models estimated the association between specialty care and event-free survival, adjusting for sociodemographic factors and comorbidities, and stratifying on ulcer severity. Results: Patients who received specialty care had longer event-free survival compared to those who did not (log-rank p<0.001 for all ulcer severity strata). After adjusting, receipt of specialty care, compared to never, remained associated with improved outcomes for all ulcer severities (early stage adjusted hazard ratio 0.34, 95% CI 0.33–0.35, p<0.001; osteomyelitis aHR 0.22, 95% CI 0.20–0.23, p<0.001; gangrene aHR 0.22, 95% CI 0.20–0.24, p<0.001). Conclusions: Specialty care was associated with longer event-free survivals for patients with diabetic foot ulcers. Increased, equitable access to specialty care might improve diabetic foot ulcer outcomes and disparities. [ABSTRACT FROM AUTHOR]

In recent years, genome sequencing of filamentous fungi has revealed a high proportion of specialised metabolites with growing pharmaceutical interest. However, detecting such metabolites through in silico genome analysis does not necessarily guarantee their expression under laboratory conditions. However, one plausible strategy for enabling their production lies in modifying the growth conditions. Devising a comprehensive experimental design testing in different culture environments is time-consuming and expensive. Therefore, using in silico modelling as a preliminary step, such as Genome-Scale Metabolic Network (GSMN), represents a promising approach to predicting and understanding the observed specialised metabolite production in a given organism. To address these questions, we reconstructed a new high-quality GSMN for the Penicillium rubens Wisconsin 54–1255 strain, a commonly used model organism. Our reconstruction, iPrub22, adheres to current convention standards and quality criteria, incorporating updated functional annotations, orthology searches with different GSMN templates, data from previous reconstructions, and manual curation steps targeting primary and specialised metabolites. With a MEMOTE score of 74% and a metabolic coverage of 45%, iPrub22 includes 5,192 unique metabolites interconnected by 5,919 reactions, of which 5,033 are supported by at least one genomic sequence. Of the metabolites present in iPrub22, 13% are categorised as belonging to specialised metabolism. While our high-quality GSMN provides a valuable resource for investigating known phenotypes expressed in P. rubens, our analysis identifies bottlenecks related, in particular, to the definition of what is a specialised metabolite, which requires consensus within the scientific community. It also points out the necessity of accessible, standardised and exhaustive databases of specialised metabolites. These questions must be addressed to fully unlock the potential of natural product production in P. rubens and other filamentous fungi. Our work represents a foundational step towards the objective of rationalising the production of natural products through GSMN modelling. [ABSTRACT FROM AUTHOR]

Public funding plays a key role in reducing cost barriers to sexual and reproductive health (SRH) care in the United States. In this analysis, we examine sociodemographic and healthcare seeking profiles of individuals in three states where public funding for health services has recently changed: Arizona, Iowa, and Wisconsin. In addition, we examine associations between individuals' health insurance status and whether they experienced delays or had trouble in obtaining their preferred contraception. This descriptive study draws on data collected between 2018 to 2021 in two distinct cross-sectional surveys in each state, one among a representative sample of female residents aged 18–44 and the other among a representative sample of female patients ages eighteen and older seeking family planning services at healthcare sites that receive public funding to deliver this care. The majority of reproductive-aged women and female family planning patients across states reported having a personal healthcare provider, had received at least one SRH service in the preceding 12 months, and were using a method of birth control. Between 49–81% across groups reported receiving recent person-centered contraceptive care. At least one-fifth of each group reported wanting healthcare in the past year but not getting it, and between 10–19% reported a delay or trouble getting birth control in the past 12 months. Common reasons for these outcomes involved cost and insurance-related issues, as well as logistical ones. Among all populations except Wisconsin family planning clinic patients, those with no health insurance had greater odds of being delayed or having trouble getting desired birth control in the past 12 months than those with health insurance. These data serve as a baseline to monitor access and use of SRH services in Arizona, Wisconsin, Iowa in the wake of drastic family planning funding shifts that changed the availability and capacity of the family planning service infrastructure across the country. Continuing to monitor these SRH metrics is critical to understand the potential effect of current political shifts. [ABSTRACT FROM AUTHOR]

Visible disruptions of appropriate food distribution for end consumers during the onset of the COVID-19 pandemic prompted calls for an urgent, renewed look at how the U.S. agri-food system is impacted by and responds to pandemics, natural disasters, and human-made crises. Previous studies suggest the COVID-19 pandemic yielded uneven impacts across agri-food supply chain segments and regions. For a rigorously comparable assessment of the impact of COVID-19 on agri-food businesses, a survey was administered from February to April 2021 to five segments of the agri-food supply chain in three study regions (California, Florida, and the two-state region of Minnesota-Wisconsin). Results (N = 870) measuring the self-reported changes in quarterly business revenue in 2020 compared to businesses' typical experience pre-COVID-19 suggest significant differences across supply chain segments and regions. In the Minnesota-Wisconsin region, restaurants took the largest hit and the upstream supply chains were relatively unaffected. In California, however, the negative impacts were felt throughout the supply chain. Two factors likely contributed to regional differences: (1) regional disparities in pandemic evolution and governance and (2) structural differences in regional agri-food systems. Regionalized and localized planning and the development of best-practices will be necessary for the U.S. agri-food system to enhance preparedness for and resilience to future pandemics, natural disasters, and human-made crises. [ABSTRACT FROM AUTHOR]

The gut microbiome is an important factor in human health and disease. While preliminary studies have found some evidence that physical activity is associated with gut microbiome richness, diversity, and composition, this relationship is not fully understood and has not been previously characterized in a large, population-based cohort. In this study, we estimated the association between several measures of physical activity and the gut microbiota in a cohort of 720 Wisconsin residents. Our sample had a mean age of 55 years (range: 18, 94), was 42% male, and 83% of participants self-identified as White. Gut microbial composition was assessed using gene sequencing of the V3-V4 region of 16S rRNA extracted from stool. We found that an increase of one standard deviation in weekly minutes spent in active transportation was associated with an increase in alpha diversity, particularly in Chao1's richness (7.57, 95% CI: 2.55, 12.59) and Shannon's diversity (0.04, 95% CI: 0.0008, 0.09). We identified interactions in the association between Inverse Simpson's diversity and physical activity, wherein active transportation for individuals living in a rural environment was associated with additional increases in diversity (4.69, 95% CI: 1.64, 7.73). We also conducted several permutational ANOVAs (PERMANOVA) and negative binomial regression analyses to estimate the relationship between physical activity and microbiome composition. We found that being physically active and increased physical activity time were associated with increased abundance of bacteria in the family Erysipelotrichaceae. Active transportation was associated with increased abundance of bacteria in the genus Phascolarctobacterium, and decreased abundance of Clostridium. Minutes in active transportation was associated with a decreased abundance of the family Clostridiaceae. [ABSTRACT FROM AUTHOR]

Background: Schools are primary venues of influenza amplification with secondary spread to communities. We assessed K-12 student absenteeism monitoring as a means for early detection of influenza activity in the community. Materials and methods: Between September 2014 and March 2020, we conducted a prospective observational study of all-cause (a-TOT), illness-associated (a-I), and influenza-like illness–associated (a-ILI) absenteeism within the Oregon School District (OSD), Dane County, Wisconsin. Absenteeism was reported through the electronic student information system. Students were visited at home where pharyngeal specimens were collected for influenza RT-PCR testing. Surveillance of medically-attended laboratory-confirmed influenza (MAI) occurred in five primary care clinics in and adjoining the OSD. Poisson general additive log linear regression models of daily counts of absenteeism and MAI were compared using correlation analysis. Findings: Influenza was detected in 723 of 2,378 visited students, and in 1,327 of 4,903 MAI patients. Over six influenza seasons, a-ILI was significantly correlated with MAI in the community (r = 0.57; 95% CI: 0.53–0.63) with a one-day lead time and a-I was significantly correlated with MAI in the community (r = 0.49; 0.44–0.54) with a 10-day lead time, while a-TOT performed poorly (r = 0.27; 0.21–0.33), following MAI by six days. Discussion: Surveillance using cause-specific absenteeism was feasible and performed well over a study period marked by diverse presentations of seasonal influenza. Monitoring a-I and a-ILI can provide early warning of seasonal influenza in time for community mitigation efforts. [ABSTRACT FROM AUTHOR]

When humanity confronts the risk of extinction of species, many people invoke precautions, especially in the face of uncertainty. Although precautionary approaches are value judgments, the optimal design and effect of precautions or lack thereof are scientific questions. We investigated Wisconsin gray wolves Canis lupus facing a second wolf-hunt in November 2021 and use three legal thresholds as the societal value judgments about precautions: (1) the 1999 population goal, 350 wolves, (2) the threshold for statutory listing under the state threatened and endangered species act, 250 wolves; and (3) state extirpation <2 wolves. This allows us to explore the quantitative relationship between precaution and uncertainty. Working from estimates of the size wolf population in April 2021 and reproduction to November, we constructed a simple linear model with uninformative priors for the period April 2021-April 2022 including an uncertain wolf-hunt in November 2021. Our first result is that the state government under-counted wolf deaths in the year preceding both wolf-hunts. We recommend better scientific analysis be used when setting wolf-hunt quotas. We find official recommendations for a quota for the November 2021 wolf-hunt risk undesirable outcomes. Even a quota of zero has a 13% chance of crossing threshold 1. Therefore, a zero death toll would be precautionary. Proponents for high quotas bear the burden of proof that their estimates are accurate, precise, and reproducible. We discuss why our approach is transferable to non-wolves. We show how scientists have the tools and concepts for quantifying and explaining the probabilities of crossing thresholds set by laws or other social norms. We recommend that scientists grapple with data gaps by explaining what the uncertainty means for policy and the public including the consequences of being wrong. [ABSTRACT FROM AUTHOR]

We studied farmworker practices and beliefs potentially contributing to transmission of bacteria and their associated antibiotic resistance genes (ARGs) among animals and farm workers to identify potential behavioral interventions to reduce the risk of bacterial transmission. Ten focus groups were conducted on eight Wisconsin dairy farms to assess potentially high-risk practices and farmworker knowledge and experiences with antibiotic use and resistance using the Systems Engineering in Patient Safety (SEIPS) framework. Farmworkers were asked to describe common on-farm tasks and the policies guiding these practices. We found workers demonstrated knowledge of the role of antibiotic stewardship in preventing the spread of ARGs. Worker knowledge of various forms of personal protective equipment was higher for workers who commonly reported glove-use. Additionally, workers knowledge regarding the importance of reducing ARG transmission varied but was higher than we had hypothesized. Programs to reduce ARG spread on dairy farms should focus on proper hand hygiene and personal protective equipment use at the level of knowledge, beliefs, and practices. [ABSTRACT FROM AUTHOR]

Introduction: Vaccination programs aim to control the COVID-19 pandemic. However, the relative impacts of vaccine coverage, effectiveness, and capacity in the context of nonpharmaceutical interventions such as mask use and physical distancing on the spread of SARS-CoV-2 are unclear. Our objective was to examine the impact of vaccination on the control of SARS-CoV-2 using our previously developed agent-based simulation model. Methods: We applied our agent-based model to replicate COVID-19-related events in 1) Dane County, Wisconsin; 2) Milwaukee metropolitan area, Wisconsin; 3) New York City (NYC). We evaluated the impact of vaccination considering the proportion of the population vaccinated, probability that a vaccinated individual gains immunity, vaccination capacity, and adherence to nonpharmaceutical interventions. We estimated the timing of pandemic control, defined as the date after which only a small number of new cases occur. Results: The timing of pandemic control depends highly on vaccination coverage, effectiveness, and adherence to nonpharmaceutical interventions. In Dane County and Milwaukee, if 50% of the population is vaccinated with a daily vaccination capacity of 0.25% of the population, vaccine effectiveness of 90%, and the adherence to nonpharmaceutical interventions is 60%, controlled spread could be achieved by June 2021 versus October 2021 in Dane County and November 2021 in Milwaukee without vaccine. Discussion: In controlling the spread of SARS-CoV-2, the impact of vaccination varies widely depending not only on effectiveness and coverage, but also concurrent adherence to nonpharmaceutical interventions. [ABSTRACT FROM AUTHOR]

There is an urgent need for childhood surveillance systems to design, implement, and evaluate interventions at the local level. We estimated obesity prevalence for individuals aged 5–17 years using a southcentral Wisconsin EHR data repository, Public Health Information Exchange (PHINEX, 2007–2012). The prevalence estimates were calculated by aggregating the estimated probability of each individual being obese, which was obtained via a generalized linear mixed model. We incorporated the random effects at the area level into our model. A weighted procedure was employed to account for missingness in EHR data. A non-parametric kernel smoothing method was used to obtain the prevalence estimates for locations with no or little data (<20 individuals) from the EHR. These estimates were compared to results from newly available obesity atlas (2015–2016) developed from various EHRs with greater statewide representation. The mean of the zip code level obesity prevalence estimates for males and females aged 5–17 years is 16.2% (SD 2.72%); 17.9% (SD 2.14%) for males and 14.4% (SD 2.00%) for females. The results were comparable to the Wisconsin Health Atlas (WHA) estimates, a much larger dataset of local community EHRs in Wisconsin. On average, prevalence estimates were 2.12% lower in this process than the WHA estimates, with lower estimation occurring more frequently for zip codes without data in PHINEX. Using this approach, we can obtain estimates for local areas that lack EHRs data. Generally, lower prevalence estimates were produced for those locations not represented in the PHINEX database when compared to WHA estimates. This underscores the need to ensure that the reference EHRs database can be made sufficiently similar to the geographic areas where synthetic estimates are being created. [ABSTRACT FROM AUTHOR]

Aster Yellows phytoplasma (AYp; 'Candidatus Phytoplasma asteris') is an obligate bacterial pathogen that is the causative agent of multiple diseases in herbaceous plants. While this phytoplasma has been examined in depth for its disease characteristics, knowledge about the spatial and temporal dynamics of pathogen spread is lacking. The phytoplasma is found in plant's phloem and is vectored by leafhoppers (Cicadellidae: Hemiptera), including the aster leafhopper, Macrosteles quadrilineatus Forbes. The aster leafhopper is a migratory insect pest that overwinters in the southern United States, and historical data suggest these insects migrate from southern overwintering locations to northern latitudes annually, transmitting and driving phytoplasma infection rates as they migrate. A more in-depth understanding of the spatial, temporal and genetic determinants of Aster Yellows disease progress will lead to better integrated pest management strategies for Aster Yellows disease control. Carrot, Daucus carota L., plots were established at two planting densities in central Wisconsin and monitored during the 2018 growing season for Aster Yellows disease progression. Symptomatic carrots were sampled and assayed for the presence of the Aster Yellows phytoplasma. Aster Yellows disease progression was determined to be significantly associated with calendar date, crop density, location within the field, and phytoplasma subgroup. [ABSTRACT FROM AUTHOR]

Recent research shows significant economic benefit if the processing sweet corn [Zea mays L. var. rugosa (or saccharata)] industry grew crowding stress tolerant (CST) hybrids at their optimum plant densities, which may exceed current plant densities by up to 14,500 plants ha-1. However, optimum plant density of individual fields varies over years and across the Upper Midwest (Illinois, Minnesota and Wisconsin), where processing sweet corn is concentrated. The objectives of this study were to: (1) determine the extent to which environmental and management practices affect optimum plant density and, (2) identify the most appropriate recommendation domain for making decisions on plant density. To capture spatial and temporal variability in optimum plant density, on-farm experiments were conducted at thirty fields across the states of Illinois, Minnesota and Wisconsin, from 2013 to 2017. Exploratory factor analysis of twelve environmental and management variables revealed two factors, one related to growing period and the other defining soil type, which explained the maximum variability observed across all the fields. These factors were then used to quantify the strength of associations with optimum plant density. Pearson's partial correlation coefficients of 'growing period' and 'soil type' with optimum plant density were low (ρ1 = -0.14 and ρ2 = -0.09, respectively) and non-significant (P = 0.47 and 0.65, respectively). To address the second objective, six candidate recommendation domain models (RDM) were developed and tested. Linear mixed effects models describing crop response to plant density were fit to each level of each candidate RDM. The difference in profitability observed at the current plant density for a field and the optimum plant density under RDM level represented the additional processor profit ($ ha-1) from a field. The RDM built around 'Production Area' (RDMPA) appears most suitable, because plant density recommendations based on RDMPA maximized processor profits as well grower returns better than other RDMs. Compared to current plant density, processor profits and grower returns increased by $448 ha-1 and $82 ha-1, respectively at plant densities under RDMPA. [ABSTRACT FROM AUTHOR]

A 1-D full-life-cycle, Individual-based model (IBM), two-way coupled with a hydrodynamic/biogeochemical model, is demonstrated for anchovy and sardine in the N. Aegean Sea (Eastern Mediterranean). The model is stage-specific and includes a ‘Wisconsin’ type bioenergetics, a diel vertical migration and a population dynamics module, with the incorporation of known differences in biological attributes between the anchovy and sardine stocks. A new energy allocation/egg production algorithm was developed, allowing for breeding pattern to move along the capital-income breeding continuum. Fish growth was calibrated against available size-at-age data by tuning food consumption (the half saturation coefficients) using a genetic algorithm. After a ten-years spin up, the model reproduced well the magnitude of population biomasses and spawning periods of the two species in the N. Aegean Sea. Surprisingly, model simulations revealed that anchovy depends primarily on stored energy for egg production (mostly capital breeder) whereas sardine depends heavily on direct food intake (income breeder). This is related to the peculiar phenology of plankton production in the area, with mesozooplankton concentration exhibiting a sharp decrease from early summer to autumn and a subsequent increase from winter to early summer. Monthly changes in somatic condition of fish collected on board the commercial purse seine fleet followed closely the simulated mesozooplankton concentration. Finally, model simulations showed that, when both the anchovy and sardine stocks are overexploited, the mesozooplankton concentration increases, which may open up ecological space for competing species. The importance of protecting the recruit spawners was highlighted with model simulations testing the effect of changing the timing of the existing 2.5-months closed period. Optimum timing for fishery closure is different for anchovy and sardine because of their opposite spawning and recruitment periods. [ABSTRACT FROM AUTHOR]

Elevated population levels of white-tailed deer (Odocoileus virginianus Zimmerman) can drastically alter forest ecosystems and negatively impact society through human interactions such as deer vehicle collisions. It is currently difficult to estimate deer populations at multiple scales ranging from stand, county, state, and regional levels. This presents a challenge as natural resource managers develop silvicultural prescriptions and forest management practices aimed at successfully regenerating tree species in the face of deer browsing. This study utilized measurements of deer browse impact from the new tree regeneration indicator developed by the United States Department of Agriculture Forest Service Forest Inventory and Analysis (FIA) program. Seedling and sapling abundance and other plot-level characteristics were analyzed across three states (Michigan, Minnesota, and Wisconsin) in the Great Lakes Region of the United States. Socio-environmental datasets (Lyme disease cases, deer vehicle collisions, and deer density estimates) were used in conjunction with FIA data to determine their predictive power in estimating deer browse impacts by county. Predictions from random forests models indicate that using Lyme disease case reports, the number of deer-vehicle collisions, deer density estimates, and forest inventory information correctly predicted deer browse impact 70–90% of the time. Deer-vehicle collisions per county ranked highly important in the random forests for predicting deer browse impacts in all three states. Lyme disease cases ranked high in importance for the Lake States combined and for Minnesota and Wisconsin, separately. Results show the effectiveness of predicting deer browse impacts using a suite of freely available forest inventory and other socio-environmental information. [ABSTRACT FROM AUTHOR]

The Colorado potato beetle, Leptinotarsa decemlineata (Say), is a major agricultural pest in the Central Sands region of Wisconsin. Imidacloprid, a neonicotinoid insecticide, has commonly been used for control of L. decemlineata since its registration in 1995. In the last 10 years, many field populations of L. decemlineata have begun to show increasing imidacloprid resistance. We studied resistance phenotype as a phenomenon that reduces neonicotinoid efficacy and has practical consequences for potato pest management. Although we have not observed complete field failure following the use of these products, multiple studies have demonstrated that the lethal concentration to kill 50% of the test organisms (LC50) in different field populations of L. decemlineata varies greatly which may suggest that resistance of L. decemlineata is heritable and involves genetic changes. An important challenge in understanding resistance is assessing the genetic mechanisms associated with resistance and classifying up-regulated genes that may be involved in combating an insecticide insult. In this study we uncovered trends in imidacloprid phenotypic response that have developed in the region by estimating the LC50 values among different field populations against a range of imidacloprid doses. The LC50 values collected in 2008–2011, and more recently in 2013 and 2014, show that some field locations remain susceptible to imidacloprid, while nearby fields (<100km) have developed high levels of resistance. We also sought to uncover potential mechanisms of resistance at each field location. We compiled a transcriptome for populations, characterized as phenotypically ‘susceptible’ and ‘resistant’, by isolating mRNA from adult beetles and analyzing gene expression level differences. Strong differences were observed in constituently up and down-regulated genes among different field populations. Most significantly, the up-regulation of 3 cytochrome p450s and a glutathione synthetase related protein in multiple resistant populations provide a mechanistic explanation of resistance evolution in L. decemlineata. [ABSTRACT FROM AUTHOR]

The present study is to investigate the brain activation associated with the informative value of negative feedback in rule acquisition. In each trial of a segmented Wisconsin Card Sorting Test, participants were provided with three reference cards and one target card, and were asked to match one of three reference cards to the target card based on a classification rule. Participants received feedback after each match. Participants would acquire the rule after one negative feedback (1-NF condition) or two successive negative feedbacks (2-NF condition). The functional magnetic resonance imaging (fMRI) results indicated that lateral prefrontal-to-parietal cortices were more active in the 2-NF condition than in the 1-NF condition. The activation in the right lateral prefrontal cortex and left posterior parietal cortex increased gradually with the amount of negative feedback. These results demonstrate that the informative value of negative feedback in rule acquisition might be modulated by the lateral prefronto-parietal loop. [ABSTRACT FROM AUTHOR]

Ecologists have long classified Midwestern prairies based on compositional variation assumed to reflect local gradients in moisture availability. The best known classification is based on Curtis’ continuum index (CI), calculated using the presence of indicator species thought centered on different portions of an underlying moisture gradient. Direct evidence of the extent to which CI reflects differences in moisture availability has been lacking, however. Many factors that increase moisture availability (e.g., soil depth, silt content) also increase nutrient supply and decrease soil mechanical impedance; the ecological effects of the last have rarely been considered in any ecosystem. Decreased soil mechanical impedance should increase the availability of soil moisture and nutrients by reducing the root costs of retrieving both. Here we assess the relative importance of soil moisture, nutrient supply, and mechanical impedance in determining prairie composition and structure. We used leaf δ13C of C3 plants as a measure of growing-season moisture availability, cation exchange capacity (CEC) x soil depth as a measure of mineral nutrient availability, and penetrometer data as a measure of soil mechanical impedance. Community composition and structure were assessed in 17 remnant prairies in Wisconsin which vary little in annual precipitation. Ordination and regression analyses showed that δ13C increased with CI toward “drier” sites, and decreased with soil depth and % silt content. Variation in δ13C among remnants was 2.0‰, comparable to that along continental gradients from ca. 500–1500 mm annual rainfall. As predicted, LAI and average leaf height increased significantly toward “wetter” sites. CI accounted for 54% of compositional variance but δ13C accounted for only 6.2%, despite the strong relationships of δ13C to CI and CI to composition. Compositional variation reflects soil fertility and mechanical impedance more than moisture availability. This study is the first to quantify the effects of soil mechanical impedance on community ecology. [ABSTRACT FROM AUTHOR]

White-tailed deer (Odocoileus virginianus) are commonly exposed to disease agents that affect livestock but environmental factors that predispose deer to exposure are unknown for many pathogens. We trapped deer during winter months on two study areas (Northern Forest and Eastern Farmland) in Wisconsin from 2010 to 2013. Deer were tested for exposure to six serovars of Leptospira interrogans (grippotyphosa, icterohaemorrhagiae, canicola, bratislava, pomona, and hardjo), bovine viral diarrhea virus (BVDV-1 and BVDV-2), infectious bovine rhinotracheitis virus (IBR), and parainfluenza 3 virus (PI3). We used logistic regression to model potential intrinsic (e.g., age, sex) and extrinsic (e.g., land type, study site, year, exposure to multiple pathogens) variables we considered biologically meaningful to exposure of deer to livestock pathogens. Deer sampled in 2010–2011 did not demonstrate exposure to BVDV, so we did not test for BVDV in subsequent years. Deer had evidence of exposure to PI3 (24.7%), IBR (7.9%), Leptospira interrogans serovar pomona (11.7%), L. i. bratislava (1.0%), L. i. grippotyphosa (2.5%) and L. i. hardjo (0.3%). Deer did not demonstrate exposure to L. interrogans serovars canicola and icterohaemorrhagiae. For PI3, we found that capture site and year influenced exposure. Fawns (n = 119) were not exposed to L. i. pomona, but land type was an important predictor of exposure to L. i. pomona for older deer. Our results serve as baseline exposure levels of Wisconsin white-tailed deer to livestock pathogens, and helped to identify important factors that explain deer exposure to livestock pathogens. [ABSTRACT FROM AUTHOR]

Few studies have evaluated the rate of infection or mode of transmission for wildlife diseases, and the implications of alternative management strategies. We used hunter harvest data from 2002 to 2013 to investigate chronic wasting disease (CWD) infection rate and transmission modes, and address how alternative management approaches affect disease dynamics in a Wisconsin white-tailed deer population. Uncertainty regarding demographic impacts of CWD on cervid populations, human and domestic animal health concerns, and potential economic consequences underscore the need for strategies to control CWD distribution and prevalence. Using maximum-likelihood methods to evaluate alternative multi-state deterministic models of CWD transmission, harvest data strongly supports a frequency-dependent transmission structure with sex-specific infection rates that are two times higher in males than females. As transmissible spongiform encephalopathies are an important and difficult-to-study class of diseases with major economic and ecological implications, our work supports the hypothesis of frequency-dependent transmission in wild deer at a broad spatial scale and indicates that effective harvest management can be implemented to control CWD prevalence. Specifically, we show that harvest focused on the greater-affected sex (males) can result in stable population dynamics and control of CWD within the next 50 years, given the constraints of the model. We also provide a quantitative estimate of geographic disease spread in southern Wisconsin, validating qualitative assessments that CWD spreads relatively slowly. Given increased discovery and distribution of CWD throughout North America, insights from our study are valuable to management agencies and to the general public concerned about the impacts of CWD on white-tailed deer populations. [ABSTRACT FROM AUTHOR]

Three H14 influenza A virus (IAV) isolates recovered in 2010 during routine virus surveillance along the Mississippi Migratory Bird Flyway in Wisconsin, U.S.A. raised questions about the natural history of these rare viruses. These were the first H14 IAV isolates recovered in the Western Hemisphere and the only H14 IAV isolates recovered since the original four isolates in 1982 in Asia. Full length genomic sequencing of the 2010 H14 isolates demonstrated the hemagglutinin (HA) gene from the 1982 and 2010 H14 isolates showed 89.6% nucleotide and 95.6% amino acid similarity and phylogenetic analysis of these viruses placed them with strong support within the H14 subtype lineage. The level of genomic divergence observed between the 1982 and 2010 viruses provides evidence that the H14 HA segment was circulating undetected in hosts and was not maintained in environmental stasis. Further, the evolutionary relationship observed between 1982 H14 and the closely related H4 subtype HA segments were similar to contemporary comparisons suggesting limited adaptive divergence between these sister subtypes. The nonstructural (NS) segment of one 2010 isolate was placed in a NS clade isolated infrequently over the last several decades that includes the NS segment from a previously reported 1982 H14 isolate indicating the existence of an unidentified pool of genomic diversity. An additional neuraminidase reassortment event indicated a recent inter-hemispheric gene flow from Asia into the center of North America. These results demonstrate temporal and spatial gaps in the understanding of IAV natural history. Additionally, the reassortment history of these viruses raises concern for the inter-continental spread of IAVs and the efficacy of current IAV surveillance efforts in detecting genomic diversity of viruses circulating in wild birds. [ABSTRACT FROM AUTHOR]

Background: Respiratory Syncytial Virus (RSV) is the leading cause of lower respiratory-tract infections in infants and young children worldwide. Despite this, only six complete genome sequences of original strains have been previously published, the most recent of which dates back 35 and 26 years for RSV group A and group B respectively. Methodology/Principal Findings: We present a semi-automated sequencing method allowing for the sequencing of four RSV whole genomes simultaneously. We were able to sequence the complete coding sequences of 13 RSV A and 4 RSV B strains from Milwaukee collected from 1998-2010. Another 12 RSV A and 5 RSV B strains sequenced in this study cover the majority of the genome. All RSV A and RSV B sequences were analyzed by neighbor-joining, maximum parsimony and Bayesian phylogeny methods. Genetic diversity was high among RSV A viruses in Milwaukee including the circulation of multiple genotypes (GA1, GA2, GA5, GA7) with GA2 persisting throughout the 13 years of the study. However, RSV B genomes showed little variation with all belonging to the BA genotype. For RSV A, the same evolutionary patterns and clades were seen consistently across the whole genome including all intergenic, coding, and non-coding regions sequences. Conclusions/Significance: The sequencing strategy presented in this work allows for RSV A and B genomes to be sequenced simultaneously in two working days and with a low cost. We have significantly increased the amount of genomic data that is available for both RSV A and B, providing the basic molecular characteristics of RSV strains circulating in Milwaukee over the last 13 years. This information can be used for comparative analysis with strains circulating in other communities around the world which should also help with the development of new strategies for control of RSV, specifically vaccine development and improvement of RSV diagnostics. [ABSTRACT FROM AUTHOR]

Background: The goal of this study was to evaluate the effects of L-Dopa medication in Parkinson's disease (PD) on brain activation during the performance of a set-shifting task. Using fMRI, we have previously studied the patterns of activity observed in patients with PD after overnight removal of dopaminergic medication compared with control participants during the performance of different stages of the Wisconsin Card Sorting Task (WCST). The results revealed decreased cortical activity in the PD group compared to controls in the conditions that significantly required striatum, while increased cortical activity was observed when striatum was not involved. However, the effect of dopaminergic medication in PD patients on those patterns of activity has not yet been studied. Methodology/Principal Findings: Here, eleven PD patients at early stage of the disease taking L-Dopa medication were recruited and underwent two fMRI sessions while performing the WCST: one session while taking their normal dose of medication and the other following overnight dopaminergic medication withdrawal. We found that L-dopa medication helped restoring a normal pattern of activity when matching and not planning was required, by increasing cortical activity in the premotor cortex. This effect was even stronger in the motor loop, i.e. when the putamen was required for controls, when matching following negative feedback. However, the medication did not change the pattern of activity in conditions relying primarily on a cognitive loop, i.e. when the caudate nucleus was required. Conclusions/Significance: These studies provide explanation at the neural level regarding the relatively poor effects of LDopa on the cognitive deficits observed in PD. [ABSTRACT FROM AUTHOR]

Background: Blastomycosis is a potentially fatal mycosis that is acquired by inhaling infectious spores of Blastomyces dermatitidis present in the environment. The ecology of this pathogen is poorly understood, in part because it has been extremely difficult to identify the niche(s) it occupies based on culture isolation of the organism from environmental samples. Methodology/Principal Findings: We investigated the ecology of blastomycosis by performing maximum entropy modeling of exposure sites from 156 cases of human and canine blastomycosis to provide a regional-scale perspective of the geographic and ecologic distribution of B. dermatitidis in Wisconsin. Based on analysis with climatic, topographic, surface reflectance and other environmental variables, we predicted that ecologic conditions favorable for maintaining the fungus in nature occur predominantly within northern counties and counties along the western shoreline of Lake Michigan. Areas of highest predicted occurrence were often in proximity to waterways, especially in northcentral Wisconsin, where incidence of infection is highest. Ecologic conditions suitable for B. dermatitidis are present in urban and rural environments, and may differ at the extremes of distribution of the species in the state. Conclusions/Significance: Our results provide a framework for a more informed search for specific environmental factors modulating B. dermatitidis occurrence and transmission and will be useful for improving public health awareness of relative exposure risks. [ABSTRACT FROM AUTHOR]

Urban change (urbanization) has dominated land change science for several decades. However, few studies have focused on what many scholars call the urban densification process (i.e., urban intensity expansion) despite its importance to both planning and subsequent impacts to the environment and local economies. This paper documents past urban densification patterns and uses this information to predict future densification trends in southeastern Wisconsin (SEWI) by using a rich dataset from the United States and by adapting the well-known Land Transformation Model (LTM) for this purpose. Urban densification is a significant and progressive process that often accompanies urbanization more generally. The increasing proportion of lower density areas, rather than higher density areas, was the main characteristic of the urban densification in SEWI from 2001 to 2011. We believe that improving urban land use efficiency to maintain rational densification are effective means toward a sustainable urban landscape. Multiple goodness-of-fit metrics demonstrated that the reconfigured LTM performed relatively well to simulate urban densification patterns in 2006 and 2011, enabling us to forecast densification to 2016 and 2021. The predicted future urban densification patterns are likely to be characterized by higher densities continue to increase at the expense of lower densities. We argue that detailed categories of urban density and specific relevant predictor variables are indispensable for densification prediction. Our study provides researchers working in land change science with important insights into urban densification process modeling. The outcome of this model can help planners to identify the current trajectory of urban development, enabling them to take informed action to promote planning objectives, which could benefit sustainable urbanization definitely., Competing Interests: The authors have declared that no competing interests exist.

In this paper we revisit the classic theory of forest succession that relates shade tolerance and species replacement and assess its validity to understand patch-mosaic patterns of forested ecosystems of the USA. We introduce a macroscopic parameter called the "shade tolerance index" and compare it to the classic continuum index in southern Wisconsin forests. We exemplify shade tolerance driven succession in White Pine-Eastern Hemlock forests using computer simulations and analyzing approximated chronosequence data from the USDA FIA forest inventory. We describe this parameter across the last 50 years in the ecoregions of mainland USA, and demonstrate that it does not correlate with the usual macroscopic characteristics of stand age, biomass, basal area, and biodiversity measures. We characterize the dynamics of shade tolerance index using transition matrices and delimit geographical areas based on the relevance of shade tolerance to explain forest succession. We conclude that shade tolerance driven succession is linked to climatic variables and can be considered as a primary driving factor of forest dynamics mostly in central-north and northeastern areas in the USA. Overall, the shade tolerance index constitutes a new quantitative approach that can be used to understand and predict succession of forested ecosystems and biogeographic patterns.

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions.