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A balance between the feasibility and validity of measures is an important consideration for physical activity (PA) research—particularly in school-based research with youth. The present study extends previously tested calibration methods to develop and test new equations for an online version of the youth activity profile (YAP) tool, a self-report tool designed for school applications. Data were collected across different regions and seasons to develop more robust, generalizable equations. The study involved a total of 717 youth from 33 schools (374 elementary [ages 9–11 years], 224 middle [ages 11–14 years], and 119 high school [ages 14–18 years]) in two different states in the United States. Participants wore a Sensewear monitor for a full week and then completed the online YAP at school to report PA and sedentary behaviors in school and at home. Accelerometer data were processed using an R-based segmentation program to compute PA and sedentary behavior levels. Quantile regression models were used with half of the sample to develop item-specific YAP calibration equations, and these were cross validated with the remaining half of the sample. Computed values of mean absolute percentage error ranged from 15 to 25% with slightly lower error observed for the middle school sample. The new equations had improved precision compared with the previous versions when tested on the same sample. The online version of the YAP provides an efficient and effective way to capture school level estimates of PA and sedentary behaviors in youth.

Increasing temperatures in the US Midwest are projected to reduce maize yields because warmer temperatures hasten reproductive development and, as a result, shorten the grain fill period. However, there is widespread expectation that farmers will mitigate projected yield losses by planting longer season hybrids that lengthen the grain fill period. Here, we ask: (a) how current hybrid maturity length relates to thermal availability of the local climate, and (b) if farmers are shifting to longer season hybrids in response to a warming climate. To address these questions, we used county-level Pioneer brand hybrid sales (Corteva Agriscience) across 17 years and 650 counties in 10 Midwest states (IA, IL, IN, MI, MN, MO, ND, OH, SD, and WI). Northern counties were shown to select hybrid maturities with growing degree day (GDD°C) requirements more closely related to the environmentally available GDD compared to central and southern counties. This measure, termed "thermal overlap," ranged from complete 106% in northern counties to a mere 63% in southern counties. The relationship between thermal overlap and latitude was fit using split-line regression and a breakpoint of 42.8°N was identified. Over the 17-years, hybrid maturities shortened across the majority of the Midwest with only a minority of counties lengthening in select northern and southern areas. The annual change in maturity ranged from -5.4 to 4.1 GDD year-1 with a median of -0.9 GDD year-1 . The shortening of hybrid maturity contrasts with widespread expectations of hybrid maturity aligning with magnitude of warming. Factors other than thermal availability appear to more strongly impact farmer decision-making such as the benefit of shorter maturity hybrids on grain drying costs, direct delivery to ethanol biorefineries, field operability, labor constraints, and crop genetics availability. Prediction of hybrid choice under future climate scenarios must include climatic factors, physiological-genetic attributes, socio-economic, and operational constraints.

Removal and distance modeling are two common methods to adjust counts for imperfect detection in point-count surveys. Several recent articles have formulated models to combine them into a distance-removal framework. We observe that these models fall into two groups building from different assumptions about the joint distribution of observed distances and first times to detection. One approach assumes the joint distribution results from a Poisson process (PP). The other assumes an independent joint (IJ) distribution with its joint density being the product of its marginal densities. We compose an IJ+PP model that more flexibly models the joint distribution and accommodates both existing approaches as special cases. The IJ+PP model matches the bias and coverage of the true model for data simulated from either PP or IJ models. In contrast, PP models underestimate abundance from IJ simulations, while IJ models overestimate abundance from PP simulations. We apply all three models to surveys of golden-crowned sparrows in Alaska. Only the IJ+PP model reasonably fits the joint distribution of observed distances and first times to detection. Model choice affects estimates of abundance and detection but has little impact on the magnitude of estimated covariate effects on availability and perceptibility.Supplementary materials accompanying this paper appear online.

The spatial dissemination of three prevalent taxa of sooty blotch and flyspeck (SBFS) fungi under several levels of precipitation was compared during 2015 and 2016 in an Iowa apple orchard. Overhead irrigation was used to supplement ambient precipitation in order to insure SBFS spore dissemination and colony development. There were five irrigation levels, involving 1-min-long periods of irrigation that were imposed either once or twice per hour at intervals of 3, 6, or 12 h, as well as a nonirrigated control. Preselected apple fruit were inoculated with one of the three SBFS taxa to serve as sources of inoculum. Dissemination from these inoculated apple fruit was assessed at harvest by counting SBFS colonies on water-sprayed and nontreated fruit. As a further control, additional fruit were enclosed in fruit bags throughout the fruit development period. In both 2015 and 2016, the number of colonies of the SBFS fungus Peltaster gemmifer per apple increased sharply as the duration of irrigation increased, whereas the number of colonies of Microcyclosporella mali increased to a lesser extent and Stomiopeltis sp. RS1 showed no increase. In 2015, the linear relationship between the duration of irrigation-imposed precipitation levels and the number of colonies on the water-sprayed apple fruit was similar for P. gemmifer (slope = 0.09), Stomiopeltis sp. RS1 (slope = 0.07), and Microcyclosporella mali (slope = 0.13); whereas, in 2016, the slope was higher for P. gemmifer (0.28) than for Stomiopeltis sp. RS1 (−0.09) or M. mali (0.06). The results indicated that dissemination of P. gemmifer increased sharply in response to increased irrigation-imposed precipitation, and that dissemination patterns differed considerably among the three SBFS taxa. The apparent advantage of P. gemmifer in precipitation-triggered dissemination may stem from its ability to produce spores rapidly by budding. To our knowledge, this is the first article to assess splash dispersal by SBFS fungi in the field and the first to document taxon-specific patterns of dissemination in this pathogen complex.

Changes in butterfly phenology due to climate changes have led to the need for models based on factors other than calendar date to predict butterfly development, allowing those monitoring their populations to increase the effectiveness of field surveys. In this study, we developed two simple climatic models, one using yearly accumulated growing degree days (GDD) and the other using yearly accumulated shortwave radiation flux densities (SRAD), to determine if these variables can predict first emergence of three butterfly species with less error than an approach based on the average ordinal date of first observation at a site. Furthermore, we investigated whether combining our two models would increase our ability to predict the timing of first emergence. We determined that GDD models were better at predicting first emergence than were ordinal date models and SRAD models for all species tested; however, the actual variation among these models was so small that any additional effort required to develop GDD models would not justify their use as a replacement for the simpler ordinal date models at this time, although as climate changes they may become more useful. We also determined that combined models did not improve the ability to predict first emergence.

Developing effective butterfly monitoring strategies is key to understanding how butterflies interact with urban environments, and, in turn, to developing local conservation practices. We investigated two urban habitat types (public gardens and restored/reconstructed prairies) and compared three survey methods (Pollard transects, purposive point counts, and random point counts) to determine which was most productive for detecting butterflies and assessing family diversity. We conducted 66 butterfly surveys by using each method (198 total) from May through September in 2015 and 2016 at six sites (three public gardens and three prairies) in Ames, Ankeny and Des Moines, Iowa. All survey methods were used on 11 sampling dates at each site. Overall, we observed 2,227 butterflies representing 38 species: 1,076 in public gardens and 1,151 in prairie areas. We used a smaller data set standardized for survey effort, including 1,361 of these sightings, to compare survey methods and habitat types. Although there were no significant differences in number of butterfly sightings between the two habitats, more sightings (798) were documented by using purposive point counts when compared to Pollard transects (297) or random point counts (266) (for both comparisons, p

Much field research on perennial bioenergy crops confounds effects of plant age with those of the growing season, which increases uncertainty and the potential for erroneous conclusions, particularly in maturing stands. Most studies rely on stands planted in a single year and measured across multiple subsequent seasons. These “single-start” designs lack statistical power to separate temporal from environment effects. We used a staggered start experimental design to learn if increased statistical power clarified understanding of Miscanthus × giganteus nitrogen (N) needs. We conducted a staggered start experiment with three planting years and five N rates during the M. × giganteus yield-building phase at three sites across IA, USA. Third-year yields were 21.0, 25.0, and 27.1 Mg dry matter (DM) ha−1 at the northwest (NW), central, and southeast (SE) sites, respectively. Nitrogen fertilization effects changed with establishment conditions, but not with plant age. At the most N responsive site, N fertilizer changed yields at all stand ages, but not in every year. Yield increases of 150%, 36%, and 40% were observed in 1-, 2-, and 3-year-old stands, respectively, with N addition. Nitrogen effects on 1-year-old stands were positive in SE IA (2.7 kg DM kg−1 N added), negative (− 2.3 kg DM kg−1 N) in NW IA, and variable in central IA (− 2.2–9.6 kg DM kg−1 N), suggesting a site–year-specific response. Yield increases between the first and second years varied by > 100% depending on establishment conditions, highlighting the need for repeated planting before determining economic and agronomic crop viability.

The extent to which ecological properties of restored coastal wetlands in the northern Gulf of Mexico recover to natural wetland conditions has not been synthesized. We conducted a systematic literature review and meta-analysis to evaluate whether vegetation and soil parameters at marsh sites restored through sediment addition recovered to levels found at paired reference sites. From 1342 candidate publications, we identified 25 studies ( 30 years since initial restoration) suitable for quantitative meta-analysis. Vegetation cover was 50% lower at restored sites compared to reference sites over the first 5 years of restoration while aboveground biomass was 25% higher. On average, belowground parameters (root biomass and soil organic matter) were 44 to 92% lower at restored sites during the first 15 years of restoration compared to reference sites. Mean recovery trajectories for belowground biomass and productivity, vegetation cover, and soil parameters indicated that mean values for restored sites reached reference site conditions within 30 years following restoration. We also evaluated recovery curves for the 20th percentile of site data, which we suggest provides a valuable perspective for natural resource agencies to consider when evaluating individual projects, as it should ensure higher success rates compared with using mean recovery rates to estimate success. Understanding marsh recovery rates following restoration helps future restoration design and monitoring, but recovery rates vary across measurement endpoints. Deciding on the appropriate response(s) to use as the basis of performance measures and monitoring will influence the apparent success of marsh restoration projects.

The El Niño Southern Oscillation (ENSO) is an oceanic-atmospheric phenomenon influencing worldwide weather and climate. Its occurrence is determined by the sea surface temperature (SST) anomaly of the 3.4 Niño region in the Pacific Ocean (5°N–5°S, 120°–170°W). El Niño (EN), Neutral (NT), and La Niña (LN) are the three possible phases of ENSO, respectively, for warm, normal, and cold SST anomaly. As in other regions around the world, weather in Brazil is influenced by ENSO phases. The country is the major coffee producer in the world, and production is strongly influenced by weather conditions, which affect plant yield, harvest quality, and interactions with pests and diseases. Coffee leaf rust (CLR), caused by the fungus Hemileia vastatrix, is a major cause of coffee yield and quality losses in Brazil, and requires fungicide spray applications every season. Because CLR is highly influenced by weather conditions, it is possible to use weather variables to simulate its progress during the cropping cycle. Therefore, the aims of this study were to estimate CLR infection rate based on a validated empirical model, which has daily minimum air temperature and relative humidity as inputs, and to assess the extent of ENSO influence on the annual risk of this disease at 45 sites in Brazil. Cumulative infection rates (CIR) were estimated daily from October to June of each growing season and location, based on the prevailing ENSO phase. Differences between the extreme phases (EN-LN) were assessed by the Two-One-Sided-Tests (TOST) method. Analysis of data from eight sites, located mainly in Paraná State, provided evidence of CIR differences between EN and LN phases (G1). Evidence of no difference of CIR between EN and LN was found in 18 sites (G2), whereas 19 sites showed no evidence of differences (G3) due to relatively large variation of CIR within the same ENSO phase. The G1 sites are located mostly in Southern Brazil, where ENSO exerts a well-defined influence on rainfall regime. In contrast, the G2 sites are mainly in Minas Gerais State, which is characterized as a transition region for ENSO influence on rainfall. The G3 sites are located between the northern region of Minas Gerais State and southern region of Bahia State, which is characterized by a subhumid climate that is usually very dry during winter, and where rainfall can vary up to 300% from one year to another, influencing relative humidity and resulting in a high CIR variability. Therefore, ENSO had a well-defined influence on CIR only in Paraná State, a region with minor importance for coffee production in Brazil. No ENSO influence was found in more northerly zones where the majority of Brazilian coffee is produced. This is the first evidence of ENSO-linked regional impact on the risk of coffee rust.

Purpose Statistical equivalence testing is more appropriate than conventional tests of difference to assess the validity of physical activity (PA) measures. This article presents the underlying principles of equivalence testing and gives three examples from PA and fitness assessment research. Methods The three examples illustrate different uses of equivalence tests. Example 1 uses PA data to evaluate an activity monitor’s equivalence to a known criterion. Example 2 illustrates the equivalence of two field-based measures of physical fitness with no known reference method. Example 3 uses regression to evaluate an activity monitor’s equivalence across a suite of 23 activities. Results The examples illustrate the appropriate reporting and interpretation of results from equivalence tests. In the first example, the mean criterion measure is significantly within ±15% of the mean PA monitor. The mean difference is 0.18 METs and the 90% confidence interval of −0.15 to 0.52 is inside the equivalence region of −0.65 to 0.65. In the second example, we chose to define equivalence for these two measures as a ratio of mean values between 0.98 and 1.02. The estimated ratio of mean V˙O2 values is 0.99, which is significantly (P = 0.007) inside the equivalence region. In the third example, the PA monitor is not equivalent to the criterion across the suite of activities. The estimated regression intercept and slope are −1.23 and 1.06. Neither confidence interval is within the suggested regression equivalence regions. Conclusions When the study goal is to show similarity between methods, equivalence testing is more appropriate than traditional statistical tests of differences (e.g., ANOVA and t-tests).

The challenges of using physical activity data from accelerometers have been compounded with the recent focus on wrist-worn monitors and raw acceleration (as opposed to activity counts). Purpose This study developed and systematically evaluated a suite of new accelerometer processing models for youth. Methods Four adaptations of the Sojourn method were developed using data from a laboratory-based experiment in which youth (N = 54) performed structured activity routines. The adaptations corresponded to all possible pairings of hip or wrist attachment with activity counts (AC) or raw acceleration (RA), and they estimated time in sedentary behavior, light activity, and moderate-to-vigorous physical activity. Criterion validity was assessed using direct observation in an independent free-living sample (N = 27). Monitors were worn on both wrists to evaluate the effect of handedness on accuracy, and status quo methods for each configuration were also evaluated as benchmarks for comparison. Tests of classification accuracy (percent accuracy, κ statistics, and sensitivity and specificity) were used to summarize utility. Results In the development sample, percent accuracy ranged from 68.5% (wrist-worn AC, κ = 0.42) to 71.6% (hip-worn RA, κ = 0.50). Accuracy was lower in the free-living evaluation, with values ranging from 49.3% (hip-worn RA, κ = 0.25) to 56.7% (hip-worn AC, κ = 0.36). Collectively, the suite predicted moderate-to-vigorous physical activity well, with the models averaging 96.5% sensitivity and 67.5% specificity. However, in terms of overall accuracy, the new models performed similarly to the status quo methods. There were no meaningful differences in performance at either wrist. Conclusions The new models offered minimal improvements over existing methods, but a major advantage is that further tuning of the models is possible with continued research.

The statistical modeling of multivariate count data observed on a space–time lattice has generally focused on using a hierarchical modeling approach where space–time correlation structure is placed on a continuous, latent, process. The count distribution is then assumed to be conditionally independent given the latent process. However, in many real-world applications, especially in the modeling of criminal or terrorism data, the conditional independence between the count distributions is inappropriate. In this manuscript we propose a class of models that capture spatial variation and also account for the possibility of data model dependence. The resulting model allows both data model dependence, or self-excitation, as well as spatial dependence in a latent structure. We demonstrate how second-order properties can be used to characterize the spatio-temporal process and how misspecification of error may inflate self-excitation in a model. Finally, we give an algorithm for efficient Bayesian inference for the model demonstrating its use in capturing the spatio-temporal structure of burglaries in Chicago from 2010–2015.

A warning system for the sooty blotch and flyspeck (SBFS) fungal disease complex of apple, developed originally for use in the southeastern United States, was modified to provide more reliable assessment of SBFS risk in Iowa. Modeling results based on previous research in Iowa and Wisconsin had suggested replacing leaf wetness duration with cumulative hours of relative humidity (RH) ≥97% as the weather input to the SBFS warning system. The purpose of the present study was to evaluate the performance of a RH-based SBFS warning system, and to assess the potential economic benefits for its use in Iowa. The warning system was evaluated in two separate sets of trials—trial 1 during 2010 and 2011, and trial 2 during 2013–2015—using action thresholds based on cumulative hours of RH ≥97% and ≥90%, respectively, in conjunction with two different fungicide regimes. The warning system was compared with a traditional calendar-based system that specified spraying at predetermined intervals of 10 to 14 days. In trial 1, use of the RH ≥97% threshold caused substantial differences between two RH sensors in recording number of hours exceeding the threshold. When both RH thresholds were compared for 2013–2015, on average, RH ≥90% resulted in a 53% reduction in variation of cumulative hours between two identical RH sensors placed adjacent to each other in an apple tree canopy. Although both the SBFS warning system and the calendar-based system resulted in equivalent control of SBFS, the warning system required fewer fungicide sprays than the calendar-based system, with an average of 3.8 sprays per season (min = 2; max = 5) vs. 6.4 sprays per season (min = 5; max = 8), respectively. The two fungicide regimes provided equivalent SBFS control when used in conjunction with the warning system. A partial budget analysis showed that using the SBFS warning system with a threshold of RH ≥90% was cost effective for orchard sizes of >1 ha. The revised warning system has potential to become a valuable decision support tool for Midwest apple growers because it reduces fungicide costs while protecting apples as effectively as a calendar-based spray schedule. The next step toward implementation of the SBFS warning system in the North Central U.S. should be multiyear field testing in commercial orchards throughout the region.

This article discusses nearest neighbor (NN) methods for the analysis of spatial point patterns and the analysis of field experiments. The distance from a point to its NN, or quantities derived from that distance, can be used to test whether the observed locations are a realization of a specific spatial point process. Edge effects, caused by recording data only within a bounded study area, can be important. When locations are marked (e.g.,by the species of plant), NN methods provide information on the relationship between the marks. NN methods for field experiments can be used to model local spatial variability. Keywords: event-to-event distance; point-to-event distance; spatial process; field experiments

Prediction of feed intake from indicators would benefit the dairy industry since on-farm feed intake data are rare. The objective of this study was to examine the ability of sensor data to improve predictions of feed intake. Dry matter intake (DMI), milk yield (MY) and components, metabolic body weight (MBW; body weight0.75), and veterinary health records were collected from two cow groups (n1=47, n2=60). Automated sensors (ear tags, rumen bolus, environmental) captured measurements of cow activity, temperature, rumination and rumen pH, and barn temperature and humidity which were used to calculate THI. Random forest (RF) models were trained in R (Caret package) by 10-fold cross validation, with DMI as the response variable. Training data originated from the full study with the exception of the final day, for which DMI was then predicted. Predictive ability was evaluated against a base model excluding automated sensor data to determine changes in accuracy and the percent of variance explained (VAR). The base model included MY and components, MBW, THI, health status and parity. Base model mean square error (MSE) was 9.86, 13.25 and 12.50 kg of DMI and VAR 44.71, 42.9 and 44.85% (n = 92, 56 and 41, respectively). The correlation between actual and predicted final day DMI (CORR) was 0.05, 0.03 and 0.02 (n = 92, 56 and 41, respectively). Adding activity and temperature (first ear tag; n = 92) reduced MSE to 9.70 kg and VAR increased to 45.62% (CORR=0.20). Independently adding bolus activity, rumen temperature and pH (n = 56) to the base model also decreased MSE to 12.53 kg (VAR=46.24% and CORR=0.26). Lastly, adding activity and rumination from the second ear tag (n = 41) to the base model decreased MSE to 12.32 kg (VAR=45.63%, CORR=0.18). Automated sensors appear to explain additional variation in DMI that is not captured in the typical energy sink variables utilized when predicting intake.

Self-reported youth physical activity (PA) is typically overestimated. We aimed to calibrate and validate a self-report tool among English youth. Four-hundred-and-two participants (aged 9&ndash, 16 years, 212 boys) wore SenseWear Armband Mini devices (SWA) for eight days and completed the self-report Youth Activity Profile (YAP) on the eighth day. Calibration algorithms for temporally matched segments were generated from the YAP data using quantile regression. The algorithms were applied in an independent cross-validation sample, and student- and school-level agreement were assessed. The utility of the YAP algorithms to assess compliance to PA guidelines was also examined. The school-level bias for the YAP estimates of in-school, out-of-school, and weekend moderate-to-vigorous PA (MVPA) were 17.2 (34.4), 31.6 (14.0), and &minus, 4.9 (3.6) min&middot, week&minus, 1, respectively. Out-of-school sedentary behaviour (SB) was over-predicted by 109.2 (11.8) min&middot, 1. Predicted YAP values were within 15%&ndash, 20% equivalence of the SWA estimates. The classification accuracy of the YAP MVPA estimates for compliance to 60 min&middot, day&minus, 1 and 30 min&middot, school-day&minus, 1 MVPA recommendations were 91%/37% and 89%/57% sensitivity/specificity, respectively. The YAP generated robust school-level estimates of MVPA and SB and has potential for surveillance to monitor compliance with PA guidelines. The accuracy of the YAP may be further improved through research with more representative UK samples to enhance the calibration process and to refine the resultant algorithms.

Per- and polyfluoroalkyl substances are synthetic environmental pollutants previously used for packaging applications as a grease, oil, and water-resistant coating. Exposure reported in previous studies highlighting potential concerns with public health. This study evaluated performance of coated paper packaging used for microwave popcorn, snacks, and sandwich bags for presence of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS). Current paper packaging materials: seven popcorn bags and three snack and sandwich bags were analysed for PFOA and PFOS and compared to concentrations in microwave popcorn bags between 2005 and 2018. Only two microwave popcorn bags had average PFOA content above the limit of quantitation of 5.11 ng g

Numerous predictive models have been developed to determine the likelihood that non-native plants will escape from cultivation and potentially become invasive. Given the substantial biological and economic costs that can result from the introduction of a new invasive plant and the unending pressures of world trade and transport, the creation and implementation of effective predictive models are becoming increasingly important. One key question in the development of such models focuses on the geographic scope at which models can best be developed and applied. We have developed models to predict woody-plant naturalization in five local areas within the Upper Midwest (United States). Herein, we consider whether naturalization can be reasonably predicted from a single model for the entire region or whether local models are required for each specific area. We develop a random forest model to predict the probability of naturalization in the region and compare out-of-sample prediction errors between the regional and local models. The regional model makes better predictions of the probability of naturalization for those species observed to naturalize but worse predictions for those not currently observed to naturalize. This model development process has given us an opportunity (not previously addressed in the literature) to examine the strengths and weaknesses of local and regional approaches, with the ultimate intent of optimizing geographic scope.

Detection of somatic mutations in human leukocyte antigen (HLA) genes using whole-exome sequencing (WES) is hampered by the high polymorphism of the HLA loci, which prevents alignment of sequencing reads to the human reference genome. We describe a computational pipeline that enables accurate inference of germline alleles of class I HLA-A, B and C genes and subsequent detection of mutations in these genes using the inferred alleles as a reference. Analysis of WES data from 7,930 pairs of tumor and healthy tissue from the same patient revealed 298 nonsilent HLA mutations in tumors from 266 patients. These 298 mutations are enriched for likely functional mutations, including putative loss-of-function events. Recurrence of mutations suggested that these 'hotspot' sites were positively selected. Cancers with recurrent somatic HLA mutations were associated with upregulation of signatures of cytolytic activity characteristic of tumor infiltration by effector lymphocytes, supporting immune evasion by altered HLA function as a contributory mechanism in cancer.

Background: Previously, we showed that vegetable oil is necessary for carotenoid absorption from salad vegetables. Research is needed to better define the dose effect and its interindividual variation for carotenoids and fat-soluble vitamins.Objective: The objective was to model the dose-response relation between the amount of soybean oil in salad dressing and the absorption of 1) carotenoids, phylloquinone, and tocopherols in salad vegetables and 2) retinyl palmitate formed from the provitamin A carotenoids.Design: Women (n = 12) each consumed 5 vegetable salads with salad dressings containing 0, 2, 4, 8, or 32 g soybean oil. Blood was collected at selected time points. The outcome variables were the chylomicron carotenoid and fat-soluble vitamin area under the curve (AUC) and maximum content in the plasma chylomicron fraction (Cmax). The individual-specific and group-average dose-response relations were investigated by fitting linear mixed-effects random coefficient models.Results: Across the entire 0-32-g range, soybean oil was linearly related to the chylomicron AUC and Cmax values for α-carotene, lycopene, phylloquinone, and retinyl palmitate. Across 0-8 g of soybean oil, there was a linear increase in the chylomicron AUC and Cmax values for β-carotene. Across a more limited 0-4-g range of soybean oil, there were minor linear increases in the chylomicron AUC for lutein and α- and total tocopherol. Absorption of all carotenoids and fat-soluble vitamins was highest with 32 g oil (P < 0.002). For 32 g oil, the interindividual rank order of the chylomicron AUCs was consistent across the carotenoids and fat-soluble vitamins (P < 0.0001).Conclusions: Within the linear range, the average absorption of carotenoids and fat-soluble vitamins could be largely predicted by the soybean oil effect. However, the effect varied widely, and some individuals showed a negligible response. There was a global soybean oil effect such that those who absorbed more of one carotenoid and fat-soluble vitamin also tended to absorb more of the others. This trial was registered at clinicaltrials.gov as NCT02867488.

Spatio-temporal hierarchical modeling is an extremely attractive way to model the spread of crime or terrorism data over a given region, especially when the observations are counts and must be modeled discretely. The spatio-temporal diffusion is placed, as a matter of convenience, in the process model allowing for straightforward estimation of the diffusion parameters through Bayesian techniques. However, this method of modeling does not allow for the existence of self-excitation, or a temporal data model dependency, that has been shown to exist in criminal and terrorism data. In this manuscript we will use existing theories on how violence spreads to create models that allow for both spatio-temporal diffusion in the process model as well as temporal diffusion, or self-excitation, in the data model. We will further demonstrate how Laplace approximations similar to their use in Integrated Nested Laplace Approximation can be used to quickly and accurately conduct inference of self-exciting spatio-temporal models allowing practitioners a new way of fitting and comparing multiple process models. We will illustrate this approach by fitting a self-exciting spatio-temporal model to terrorism data in Iraq and demonstrate how choice of process model leads to differing conclusions on the existence of self-excitation in the data and differing conclusions on how violence spread spatially-temporally in that country from 2003–2010.

BACKGROUND: Since the introduction of glyphosate-resistant (GR) crops, growers have often relied on glyphosate-only weed control programs. As a result, multiple weeds have evolved resistance to glyphosate. A 5 year study including 156 growers from Illinois, Iowa, Indiana, Nebraska, North Carolina and Mississippi in the United States was conducted to compare crop yields and net returns between grower standard weed management programs (SPs) and programs containing best management practices (BMPs) recommended by university weed scientists. The BMPs were designed to prevent or mitigate/manage evolved herbicide resistance. RESULTS: Weed management costs were greater for the BMP approach in most situations, but crop yields often increased sufficiently for net returns similar to those of the less expensive SPs. This response was similar across all years, geographical regions, states, crops and tillage systems. CONCLUSIONS: Herbicide use strategies that include a diversity of herbicide mechanisms of action will increase the long-term sustainability of glyphosate-based weed management strategies. Growers can adopt herbicide resistance BMPs with confidence that net returns will not be negatively affected in the short term and contribute to resistance management in the long term. © 2014 Society of Chemical Industry

Summary Weed seeds in and on the soil are the primary cause of weed infestations in arable fields. Previous studies have documented reductions in weed seedbanks due to cropping system diversification through extended rotation sequences, but the impacts of different rotation systems on additions to and losses from weed seedbanks remain poorly understood. We conducted an experiment in Iowa, USA, to determine the fates of Setaria faberi and Abutilon theophrasti seeds in 2-, 3- and 4-year crop rotation systems when seed additions to the soil seedbank were restricted to a single pulse at the initiation of the study. Over the course of the experiment, seedlings were removed as they emerged and prevented from producing new seeds. After 41 months, seed population densities dropped >85% for S. faberi and >65% for A. theophrasti, but differences between rotation systems in the magnitude of seedbank reductions were not detected. Most of the reductions in seedbank densities took place from autumn through early spring in the first 5 months following seed deposition, before seedling emergence occurred, suggesting that seed predation and/or seed decay was important. For S. faberi, total cumulative seedling emergence and total seed mortality did not differ between rotation systems. In contrast, for A. theophrasti, seedling emergence was 71% lower and seed mortality was 83% greater in the 3- and 4-year rotation systems than in the 2-year system. Results of this study indicate that for certain weed species, such as A. theophrasti, crop rotation systems can strongly affect life-history processes associated with soil seedbanks.

Abundance estimates from animal point-count surveys require accurate estimates of detection probabilities. The standard model for estimating detection from removal-sampled point-count surveys assumes that organisms at a survey site are detected at a constant rate; however, this assumption is often not justified. We consider a class of N-mixture models that allows for detection heterogeneity over time through a flexibly defined time-to-detection distribution (TTDD) and allows for fixed and random effects for both abundance and detection. Our model is thus a combination of survival time-to-event analysis with unknown-N, unknown-p abundance estimation. We specifically explore two-parameter families of TTDDs, e.g. gamma, that can additionally include a mixture component to model increased probability of detection in the initial observation period. We find that modeling a TTDD by using a two-parameter family is necessary when data have a chance of arising from a distribution of this nature. In addition, models with a mixture component can outperform non-mixture models even when the truth is non-mixture. Finally, we analyze an Overbird data set from the Chippewa National Forest using mixed effect models for both abundance and detection. We demonstrate that the effects of explanatory variables on abundance and detection are consistent across mixture TTDDs but that flexible TTDDs result in lower estimated probabilities of detection and therefore higher estimates of abundance., Expands previous simulation study and adds simulations across a range of `true' detection values

The sap-sucking insects (order Hemiptera), including aphids, planthoppers, whiteflies and stink bugs, present one of the greatest challenges for pest management in global agriculture. Insect neurotoxins offer an alternative to chemical insecticides for controlling these pests, but require delivery into the insect hemocoel. Here we use the coat protein of a luteovirus, an aphid-vectored plant virus, to deliver a spider-derived, insect-specific toxin that acts within the hemocoel. The luteovirid coat protein is sufficient for delivery of fused proteins into the hemocoel of pea aphids, Acyrthosiphon pisum, without virion assembly. We show that when four aphid pest species-A. pisum, Rhopalosiphum padi, Aphis glycines and Myzus persicae-feed on a recombinant coat protein-toxin fusion, either in an experimental membrane sachet or in transgenic Arabidopsis plants, they experience significant mortality. Aphids fed on these fusion proteins showed signs of neurotoxin-induced paralysis. Luteovirid coat protein-insect neurotoxin fusions represent a promising strategy for transgenic control of aphids and potentially other hemipteran pests.

Terrestrial habitats surrounding isolated wetlands are a critical resource for many pond-breeding amphibian species, yet few studies have examined the terrestrial distribution of post-metamorphic juveniles and adults. We used an encircling drift fence at a breeding pond in conjunction with partial fences at 90, 172, and 332 m from the wetland to estimate the terrestrial distribution of adult marbled salamanders (Ambystoma opacum; four breeding seasons) and mole salamanders (A. talpoideum; two seasons), as well as the dispersion of newly metamorphosed A. opacum (one summer). For newly metamorphosed A. opacum, 79% emigrated ,90 m from the wetland, and 8% moved beyond 172 m; movement distance was unrelated to body size. Distribution of adult A. opacum varied among years, with an average of 28% (range 23-31%) occurring beyond 172 m in all years. Averaged across two years, 51% of adult A. talpoideum occurred beyond 172 m. Lognormal models provided a good fit to both the juvenile and adult ambystomatid distributions, and parameters differed between age classes, sexes, species, and years within species. For adult A. opacum a buffer radius of 300 m or 340 m, depending on the year, is estimated to include 95% of adults; for A. talpoideum the estimate is 464 m or 501 m. A reanalysis of distribution data for seven ambystomatid species shows that a previous estimate of a 164-m radius to protect 95% of a population underestimates the needed buffer radius by 185 m. Because our study wetland requires a nearly 500 m wide radius to protect 95% of its ambystomatid adults, preservation of similar communities may require much more surrounding terrestrial habitat than previously thought.

In ecotoxicology, toxicokinetic–toxicodynamic models are increasingly being used to relate toxicant concentration to survival. These have a toxicokinetic component that specifies a model for toxicant uptake and elimination and a toxicodynamic component that specifies a model for the relationship between internal body concentration of toxicant and the hazard rate. Often, the toxicodynamic model is a proportional hazards model and the data to evaluate the model is interval censored. We develop diagnostic methods to assess the appropriateness of the toxicokinetic and hazard models for interval-censored data. A log-cumulative hazard plot is used to assess visually the proportional hazard assumption. This can be further evaluated by an approximate test based on a linear regression. Martingale residuals for interval-censored data are poorly behaved, and their use is not recommended. If the proportional hazard assumption is valid, the kinetic model can be assessed by a plot of toxicant concentration against the average of log-cumulative hazard for each concentration. The use of these diagnostic tools is illustrated by using data on Hyalella azteca survival during and after exposure to copper sulfate and sodium pentachlorophenol. The model that was initially proposed did not fit the data well, but the diagnostic tools suggested appropriate modifications. The diagnostic tools can be applied more generally to interval-censored survival data. Copyright © 2013 John Wiley & Sons, Ltd.

The selection, introduction, and cultivation of non-native woody plants beyond their native ranges can have great benefits, but also unintended consequences. Among these consequences is the tendency for some species to naturalize and become invasive pests in new environments to which they were introduced. In lieu of lengthy and costly field trials, risk-assessment models can be used to predict the likelihood of naturalization. We compared the relative performance of five established risk-assessment models on species datasets from two previously untested areas: southern Minnesota and northern Missouri. Model classification rates ranged from 64.2 to 90.5%, biologically significant errors ranged from 4.4 to 9.3%, and horticulturally limiting errors ranged from 6.6 to 30.4%. For the random forest model, we investigated the importance of variables used to predict naturalization by examining datasets for five distinct study areas across the Upper Midwest. Geographic-risk ratios were the most important predictors of species' tendency to naturalize. Other factors, such as quick maturity, record of invading elsewhere, and production of fleshy, bird-dispersed fruit were also important in the random forest models. Although some models tested need additional refinement, the random forest models maintain robustness and provide additional information on plant-specific characteristics that contribute to naturalization.

Estimation of design power requires knowledge of treatment effect size and error variance, which are often unavailable for ecological studies. In the absence of prior information on these parameters, investigators can compare an alternative to a reference design for the same treatment(s) in terms of its precision at equal sensitivity. This measure of relative performance calculates the fractional error variance allowed of the alternative for it to just match the power of the reference. Although first suggested as a design tool in the 1950s, it has received little analysis and no uptake by environmental scientists or ecologists. We calibrate relative performance against the better known criterion of relative efficiency, in order to reveal its unique advantage in controlling sensitivity when considering the precision of estimates. The two measures differ strongly for designs with low replication. For any given design, relative performance at least doubles with each doubling of effective sample size. We show that relative performance is robustly approximated by the ratio of reference to alternative $$\alpha $$ quantiles of the $$F$$ distribution, multiplied by the ratio of alternative to reference effective sample sizes. The proxy is easy to calculate, and consistent with exact measures. Approximate or exact measurement of relative performance serves a useful purpose in enumerating trade-offs between error variance and error degrees of freedom when considering whether to block random variation or to sample from a more or less restricted domain.

The Devils Hole pupfish, Cyprinodon diabolis, is a federally-endangered fish that is endemic to Devils Hole, a discontiguous part of Death Valley National Park in Nye County, Nevada. Due to its status, Devils Hole pupfish monitoring must be non-obtrusive and thereby exclude techniques that require handling fish. Due to a recent decline in pupfish abundance, Devils Hole pupfish managers have expressed a need for a model that describes population dynamics. This population model would be used to identify vulnerable life history stage(s) and inform management actions. We constructed a set of individual-based simulation models designed to explore effects of population processes and evaluate assumptions. We developed a baseline model, whose output best resembled both observed length-frequency data and predicted intra-annual abundance patterns. We then ran simulations with 5 % increases in egg-larval, juvenile, and adult survival rates to better understand Devils Hole pupfish life history, thereby helping identify vulnerable life history stages that should become the target of management actions. Simulation models with temporally constant adult, juvenile, and egg-larval survival rates were able to reproduce observed length-frequency distributions and predicted intra-annual population patterns. In particular, models with monthly adult and juvenile survival rates of 80 % and an egg-larval survival rate of 4.7 % replicated patterns in observed data. Population growth was most affected by 5 % increases in egg-larval survival, whereas adult and juvenile survival rates had similar but lesser effects on population growth. Outputs from the model were used to assess factors suspected of influencing Devils Hole pupfish population decline.

The importance of E. coli as an indicator organism in fresh water has led to numerous studies focusing on cell properties and transport behavior. However, previous studies have been unable to assess if differences in E. coli cell surface properties and genomic variation are associated with different environmental habitats. In this study, we investigated the variation in characteristics of E. coli obtained from stream water and stream bottom sediments. Cell properties were measured for 77 genomically different E. coli strains (44 strains isolated from sediments and 33 strains isolated from water) under common stream conditions in the Upper Midwestern United States: pH 8.0, ionic strength 10 mM and 22°C. Measured cell properties include hydrophobicity, zeta potential, net charge, total acidity, and extracellular polymeric substance (EPS) composition. Our results indicate that stream sediment E. coli had significantly greater hydrophobicity, greater EPS protein content and EPS sugar content, less negative net charge, and higher point of zero charge than stream water E. coli. A significant positive correlation was observed between hydrophobicity and EPS protein for stream sediment E. coli but not for stream water E. coli. Additionally, E. coli surviving in the same habitat tended to have significantly larger (GTG)5 genome similarity. After accounting for the intrinsic impact from the genome, environmental habitat was determined to be a factor influencing some cell surface properties, such as hydrophobicity. The diversity of cell properties and its resulting impact on particle interactions should be considered for environmental fate and transport modeling of aquatic indicator organisms such as E. coli.

Ecosystem boundary retreat due to human-induced pressure is a generally observed phenomenon. However, studies that document thresholds beyond which internal resistance mechanisms are overwhelmed are uncommon. Following the Deepwater Horizon (DWH) oil spill, field studies from a few sites suggested that oiling of salt marshes could lead to a biogeomorphic feedback where plant death resulted in increased marsh erosion. We tested for spatial generality of and thresholds in this effect across 103 salt marsh sites spanning ∼430 kilometers of shoreline in coastal Louisiana, Alabama, and Mississippi, using data collected as part of the natural resource damage assessment (NRDA). Our analyses revealed a threshold for oil impacts on marsh edge erosion, with higher erosion rates occurring for ∼1-2 years after the spill at sites with the highest amounts of plant stem oiling (90-100%). These results provide compelling evidence showing large-scale ecosystem loss following the Deepwater Horizon oil spill. More broadly, these findings provide rare empirical evidence identifying a geomorphologic threshold in the resistance of an ecosystem to increasing intensity of human-induced disturbance. Fil: Silliman, Brian R.. University of Duke; Estados Unidos Fil: Dixon, Philip M.. Iowa State University; Estados Unidos Fil: Wobus, Cameron. Abt Associates; Estados Unidos Fil: He, Qiang. University of Duke; Estados Unidos Fil: Daleo, Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; Argentina. University of Duke; Estados Unidos Fil: Hughes, Brent B.. University of Duke; Estados Unidos. University of California; Estados Unidos Fil: Rissing, Matthew. Abt Associates; Estados Unidos Fil: Willis, Jonathan M.. University of Louisiana at Lafayette; Estados Unidos Fil: Hester, Mark W.. University of Louisiana at Lafayette; Estados Unidos

Excessive demands on maternal nutritional status may be a risk factor for poor birth outcomes. This study examined the association between breastfeeding during late pregnancy (≥ 28 weeks) and the risk of having a small-for-gestational-age (SGA) newborn, using a matched case-control design (78 SGA cases: birthweight

Growing demand for corn due to the expansion of corn ethanol production has increased concerns that corn demand will be met by growing corn more intensively and shifting cropland from cropping systems with lower environmental impact into continuous corn (CC). Cropping system choice may also be influenced by the advantage of the high nutrient uptake of CC, which allows higher manure application rates and lowers manure management costs. A binary logistic regression model is used to estimate the probability of crop rotation choice as a function of proximity to concentrated animal feeding operations (CAFOs) and ethanol plants during 2004/2005 and 2006/2007 in the Des Moines Lobe region of Iowa. The probability of CC is found to be elevated in the vicinity of large hog operations as well as in a larger area around ethanol plants. The probability of CC around hog-feeding operations decreases rapidly with distance away from the facility, but the large number of hog facilities in the region results in a large cumulative influence. Understanding the multiple motivations for cropping system choices is vital to forming effective agricultural policy. © 2012 Society of Chemical Industry and John Wiley & Sons, Ltd