Important Source Of Variation Research Articles

Biological variation: a rapidly evolving aspect of laboratory medicine

When serial results from examinations of a measurand in laboratory medicine are made in an individual, they are unlikely to be identical over time, even when the state of health or disease in that person has not changed. In part, this is because there are many sources of variation in the pre-examination, examination and post-examination phases of generating a result. However, intrinsic biological variation additionally contributes, often being the most important source of variation. Some measurands have biological variation over the span of life, with important changes at times of rapid physiological development such as the neonatal period, puberty, and the menopause.

Neither artificial light at night, anthropogenic noise nor distance from roads are associated with oxidative status of nestlings in an urban population of songbirds

Increasing urbanization is responsible for road-related pollutants and causes an unprecedented increase in light and noise pollution, with potential detrimental effects for individual animals, communities and ecosystems. These stressors rarely act in isolation but studies dissecting the effects of these multiple stressors are lacking. Moreover, studies on urban stressors have mainly focused on adults, while exposure in early-life may be detrimental but is largely ignored. To fill this important knowledge gap, we studied if artificial light at night, anthropogenic noise and road-related pollution (using distance from roads as a proxy) explain variation in oxidative status in great tit nestlings (Parus major) in an urban population. Artificial light at night, anthropogenic noise and distance from roads were not associated with variation of the nine studied metrics of oxidative status (superoxide dismutase-SOD-, glutathione peroxidase-GPX, catalase-CAT-, non-enzymatic total antioxidant capacity-TAC-, reduced glutathione-GSH-, oxidized glutathione-GSSG-, ratio GSH/GSSG, protein carbonyls and thiobarbituric acid reactive substances-TBARS). Interestingly, for all oxidative status metrics, we found that there was more variation in oxidative status among individuals of the same nest compared to between different nests. We also showed an increase in protein carbonyls and a decrease of the ratio GSH/GSSG as the day advanced, and an increase of GPX when weather conditions deteriorated. Our study suggests that anthropogenic noise, artificial light at night and road-related pollution are not the most important sources of variation in oxidative status in great tit nestlings. It also highlights the importance of considering bleeding time and weather conditions in studies with free-living animals.

The patient safety climate in healthcare organizations (PSCHO) survey: Short-form development.

Measures of safety climate are increasingly used to guide safety improvement initiatives. However, cost and respondent burden may limit the use of safety climate surveys. The purpose of this study was to develop a 15- to 20-item safety climate survey based on the Patient Safety Climate in Healthcare Organizations survey, a well-validated 38-item measure of safety climate. The Patient Safety Climate in Healthcare Organizations was administered to all senior managers, all physicians, and a 10% random sample of all other hospital personnel in 69 private sector hospitals and 30 Veterans Health Administration hospitals. Both samples were randomly divided into a derivation sample to identify a short-form subset and a confirmation sample to assess the psychometric properties of the proposed short form. The short form consists of 15 items represented 3 overarching domains in the long-form scale-organization, work unit, and interpersonal. The proposed short form efficiently captures 3 important sources of variance in safety climate: organizational, work-unit, and interpersonal. The short-form development process was a practical method that can be applied to other safety climate surveys. This safety climate short form may increase response rates in studies that involve busy clinicians or repeated measures.

Notice: The authors have discovered an error in raw data analyzed in this paper. This article has been retracted. The corrected article is published online early as Ringelman KM, Williams CK, Castelli PM, Sieges ML, Longenecker RA, Nichols TC, Earsom AD. 2018. Estimating waterfowl carrying capacity at local scales: A case study from Edwin B. Forsythe National Wildlife Refuge, New

Abstract The management of wintering North American waterfowl is based on the premise that the amount of foraging habitat can limit populations. To estimate carrying capacity of winter habitats, managers use bioenergetic models to quantify energy (food) availability and energy demand, and use results as planning tools to meet regional conservation objectives. Regional models provide only coarse estimates of carrying capacity because habitat area, habitat energy values, and temporal trends in population-level demand are difficult to quantify precisely at large scales. We took advantage of detailed data previously collected on wintering waterfowl at Edwin B. Forsythe National Wildlife Refuge and surrounding marsh, New Jersey, USA, and created a well-constrained local model of carrying capacity. We used 1,223 core samples collected between 2006 and 2015 to estimate available food. We used species-specific 24-h time-activity data collected between 2011 and 2013 to estimate daily energy expenditure, morphometrically corrected for site- and day-specific thermoregulatory costs. To estimate population-level energy demand, we used standardized monthly ground-surveys (2005–2014) to create a migration curve, and proportionally scaled that to fit aerial survey data (2005–2014). Crucially, we also explicitly incorporated estimates of variance in all of these parameters and conducted a sensitivity analysis to diagnose the most important sources of variation in the model. Our results indicated that at estimated mean levels of supply (2.34 × 109 kcal) and cumulative demand (3.4 × 109 kcal), refuge resources were depleted before the end of the wintering season. However, at one standard error greater in supply and one standard error less in demand, 1.33 × 109 kcal remained on the landscape at the end of winter. Variation in model output appeared to be driven primarily by uncertainty in food abundance in high marsh habitats. This model allows for relative assessment of biases and uncertainties in carrying capacity modeling, and serves as a framework identifying critical science needs to improve local and regional waterfowl management planning.

사천시 용정천에서 하천 생태계와 하안단구 지역의 수변식물상

This study is examined river naturality and vegetative composition of river riparian zones to identify their most important sources of variation. Information on plant species cover and on physical characteristics that occur at upper, medium, and low areas was collected for 30 riparian plots located throughout the Youngjeong River in Korea. The riparian areas of river banks are dominated by mixed sediment and the vegetation is composed of herbs, shrub, and trees. The floristic characterization of riparian at this river during 2015 season was identified with a total of 28 families, 72 genera, 75 species, 13 varieties, 23 associations. The vegetations of low water‘s edge and flood way at upper region were naturally formed various vegetation communities by natural erosion. Forty plant species were identified around the upper region, where the dominant growth form was mostly trees. The flood way vegetation at middle region was both of natural vegetation and artificial vegetation. Land uses in riparian zones river levee at low region were bush or grassland as natural floodplain. The values of cover-abundance at upper, middle, and low region were total 9.26, 7.24, and 7.56, respectively. Grasses and forbs at the Youngjeong River have similar cover-abundance values. Recent, many riparian areas of this river have been lost or degraded for commercial and industrial developments. Thus, monitoring for biological diversity of plant species of this river is necessary for an adaptive management approach and the successful implementation of ecosystem management.

Factors affecting variations in the detailed fatty acid profile of Mediterranean buffalo milk determined by 2-dimensional gas chromatography

Buffalo milk is the world's second most widely produced milk, and increasing attention is being paid to its composition, particularly the fatty acid profile. The objectives of the present study were (1) to characterize the fatty acid composition of Mediterranean buffalo milk, and (2) to investigate potential sources of variation in the buffalo milk fatty acid profile. We determined the profile of 69 fatty acid traits in 272 individual samples of Mediterranean buffalo milk using gas chromatography. In total, 51 individual fatty acids were identified: 24 saturated fatty acids, 13 monounsaturated fatty acids, and 14 polyunsaturated fatty acids. The major individual fatty acids in buffalo milk were in the order 16:0, 18:1 cis-9, 14:0, and 18:0. Saturated fatty acids were the predominant fraction in buffalo milk fat (70.49%); monounsaturated and polyunsaturated fatty acids were at 25.95 and 3.54%, respectively. Adopting a classification based on carbon-chain length, we found that medium-chain fatty acids (11-16 carbons) represented the greater part (53.7%) of the fatty acid fraction of buffalo milk, whereas long-chain fatty acids (17-24 carbons) and short-chain fatty acids (4-10 carbons) accounted for 32.73 and 9.72%, respectively. The n-3 and n-6 fatty acids were 0.46 and 1.77%, respectively. The main conjugated linoleic acid, rumenic acid, represented 0.45% of total milk fatty acids. Herd/test date and stage of lactation were confirmed as important sources of variation in the fatty acid profile of buffalo milk. The percentages of short-chain and medium-chain fatty acids in buffalo milk increased in early lactation (+0.6 and +3.5%, respectively), whereas long-chain fatty acids decreased (-4.2%). The only exception to this pattern was butyric acid, which linearly decreased from the beginning of lactation, confirmation that its synthesis is independent of malonyl-CoA. These results seem to suggest that in early lactation the mobilization of energy reserves may have less influence on the fatty acid profile of buffalo milk than that of cow milk, probably due to a shorter and less severe period of negative energy balance. Parity affected the profiles of a few traits and had the most significant effects on branched-chain fatty acids. This work provided a detailed overview of the fatty acid profile in buffalo milk including also those fatty acids present in small concentrations, which may have beneficial effects for human health. Our results contributed also to increase the knowledge about the effects of some of the major factors affecting buffalo production traits and fatty acid concentrations in milk, and consequently its technological and nutritional properties.

The Sensitivity of Evapotranspiration to Inter-Specific Plant Neighbor Interactions: Implications for Models

Evapotranspiration (ET) is an important water loss flux in ecosystem water cycles, and quantifying the spatial and temporal variation of ET can improve ecohydrological models in arid ecosystems. Plant neighbor interactions may be a source of spatial and temporal variation in ET due to their effects on the above- and belowground microclimate and increased water demand for transpiration. Over longer timescales (annual to multiple years), adjustments in plant physiological traits may occur in response to neighbor environments, potentially affecting the transpiration (T) component of ET. We used a dynamic soil water model to assess the sensitivity of ET and T estimates to neighbor effects on soil moisture via competition for water, aboveground microclimate effects via canopy shading, and physiological adjustments (specifically, root distribution, stomatal behavior, and canopy leaf area). We focus on a common desert shrub (Larrea tridentata) under different inter-specific neighbor environments and precipitation regimes. Neighbors impacted T of Larrea by as much as 75% at the patch scale (plant and surrounding soil) and 30% at the stand scale. Annual T estimates were highly sensitive to changes in soil moisture associated with competition for water, and the inclusion of physiological adjustments to neighbor environments significantly impacted seasonal T. Plant neighbor interactions can significantly influence ET and soil moisture, and their inclusion in models can help explain spatial and temporal variation in water fluxes in arid ecosystems. Furthermore, physiological adjustments to neighbor environments may be an important source of variation to include in models that operate over seasonal timescales or in studies focused on plant responses to precipitation under climate change.

Incorporating periodic variability in hidden Markov models for animal movement

BackgroundClustering time-series data into discrete groups can improve prediction and provide insight into the nature of underlying, unobservable states of the system. However, temporal variation in probabilities of group occupancy, or the rates at which individuals move between groups, can obscure such signals. We use finite mixture and hidden Markov models (HMMs), two standard clustering techniques, to model long-term hourly movement data from Florida panthers (Puma concolor coryi). Allowing for temporal heterogeneity in transition probabilities, a straightforward but little-used extension of the standard HMM framework, resolves some shortcomings of current models and clarifies the movement patterns of panthers.ResultsSimulations and analyses of panther data showed that model misspecification (omitting important sources of variation) can lead to overfitting/overestimating the underlying number of movement states. Models incorporating temporal heterogeneity identify fewer underlying states, and can make out-of-sample predictions that capture observed diurnal and autocorrelated movement patterns exhibited by Florida panthers.ConclusionIncorporating temporal heterogeneity improved goodness of fit and predictive capability as well as reducing the selected number of movement states closer to a biologically interpretable level, although there is further room for improvement here. Our results suggest that incorporating additional structure in statistical models of movement can allow more accurate assessment of appropriate model complexity.

Variation in selected solid wood properties of young Pinus patula from diverse sites in the Mpumalanga escarpment area in South Africa

Regression analyses identified ‘Growth Days’ (an index expressing site moisture availability) as the only site variable contributing significantly to the prediction to wood density (R2 = 0.57), whereas the model predicting grain angle included only ‘Altitude’ (R2 = 0.60). These results surfaced during an investigative study to quantify various sources of variation in wood properties and to quantify the effect of a number of site factors on wood properties of Pinus patula grown in the Mpumalanga escarpment area of South Africa. For this purpose, 10 trees were sampled from each of 17 diverse sites for wood property analyses. The effects of site, distance from the pith and differences between trees within site on wood density, transverse shrinkage, grain angle and dynamic modulus of elasticity were investigated. The site factors considered included a wide variety of soil and climatic factors. The effect of radial distance from the pith and differences between individual trees within sites were highly significant, accounting for most of the variation in wood properties. Although the effects of a number of site factors were statistically significant, they generally explained relatively small but important variation in wood properties among sites. The study not only quantified the effects of important sources of variation on a few key wood properties, but it also revealed that the extent of differences between sites can be explained in terms of some specific site factors. It is envisaged that the results will contribute significantly towards the refinement of current forest site classification systems for improved decision-making with respect to wood quality in intensively managed plantation systems.

Reproducibility of fluctuating asymmetry measurements in plants: Sources of variation and implications for study design

Fluctuating asymmetry (FA), i.e. small, non-directional deviations from perfect symmetry in morphological characters, increases under genetic and/or environmental stress. Ecological and evolutionary studies addressing FA became popular in past decades; however, their outcomes remain controversial. The discrepancies might be at least partly explained by inconsistent and non-standardised methodology. Our aim was to improve the methodology of these studies by identifying factors that affect the reproducibility of FA measurements in plant leaves. Six observers used a highly standardised measurement protocol to measure FA using the width, area and weight of the same set of leaves of 10 plant species that differed in leaf size, shape of the leaf margin and other leaf traits. On average, 24% of the total variation in the data was due to measurement error. Reproducibility of measurements varied with the shape of leaf margin, leaf size, the measured character and the experience of the observer. The lowest reproducibility of the width of leaf halves was found for simple leaves with serrate margins and the highest for simple leaves with entire margins and for compound pinnate leaves. The reproducibility was significantly lower for the weight of leaf halves than for either their width or area, especially for plants with small leaves. The reproducibility was also lower for measurements made by experienced observers than by naïve observers. The size of press-dried leaves decreased slightly but significantly relative to fresh leaves, but the FA of press-dried leaves adequately reflected the FA of fresh leaves. In contrast, preservation in 60% ethanol did not affect leaf size, but it decreased the width-based values of FA to 89.3% of the values measured from fresh leaves. We suggest that although reproducibility of leaf FA measurements depends upon many factors, the shape of the leaf margin is the most important source of variation. We recommend, whenever possible, choosing large-leaved plants with entire leaf margins as model objects for studies involving measurements of FA using the width of leaf halves. These measurements should be conducted with high accuracy from images of fresh or press-dried leaves.

Effect of season and breed group on the follicular population and cyclicity of heifers under tropical conditions.

The aim was to determine the effect of season and breed group on follicular population, and presence and size of CL of heifers under tropical conditions. The seasons were hot-dry (March-June), hot-humid (July-October), and fresh-humid (November-February). Thirty Zebu (Brahman) and 38 F1 (Simmental × Brahman) heifers were used. Five evaluations were made in each season, at intervals of 7days, to assess ovarian activity by ultrasound. Follicles were classified as small (≤4mm), middle (4.1-8mm), and large (≥8.1mm) sizes, and also the size of CL, when present, was measured. Data were analyzed using analysis of variance and logistic regression procedures. Mean number of small follicles was 11.6 ± 2.3 with no effect of season, breed group, or their interaction (P > 0.05). Mean number of middle follicles was influenced by season and breed group; the highest average was found in the fresh-humid season (4.0 ± 0.2) and in F1 heifers (3.6 ± 0.2; P < 0.05). The highest mean number of large follicles was in the hot-humid season (1.4 ± 0.1; P < 0.05). The highest maximum follicle diameter (MFD) mean was registered in the hot-humid season (1.3mm; P < 0.05) and the lowest proportion of heifers with CL occurred in fresh-humid season (33.3%; P < 0.05). No effect of season, breed group, and interaction on the maximum diameter of the CL was found. In conclusion, season was a very important source of variation. Heifers in the hot-humid season had the largest follicles and MFD, and better cyclicity.

Adjusting MtDNA Quantification in Whole Blood for Peripheral Blood Platelet and Leukocyte Counts.

Alterations of mitochondrial DNA copy number (mtDNAcn) in the blood (mitochondrial to nuclear DNA ratio) appear associated with several systemic diseases, including primary mitochondrial disorders, carcinogenesis, and hematologic diseases. Measuring mtDNAcn in DNA extracted from whole blood (WB) instead of from peripheral blood mononuclear cells or buffy coat may yield different results due to mitochondrial DNA present in platelets. The aim of this work is to quantify the contribution of platelets to mtDNAcn in whole blood [mtDNAcn(WB)] and to propose a correction formula to estimate leukocytes' mtDNAcn [mtDNAcn(L)] from mtDNAcn(WB). Blood samples from 10 healthy adults were combined with platelet-enriched plasma and saline solution to produce artificial blood preparations. Aliquots of each sample were combined with five different platelet concentrations. In 46 of these blood preparations, mtDNAcn was measured by qPCR. MtDNAcn(WB) increased 1.07 (95%CI 0.86, 1.29; p<0.001) per 1000 platelets present in the preparation. We proved that leukocyte count should also be taken into account as mtDNAcn(WB) was inversely associated with leukocyte count; it increased 1.10 (95%CI 0.95, 1.25, p<0.001) per unit increase of the ratio between platelet and leukocyte counts. If hematological measurements are available, subtracting 1.10 the platelets/leukocyte ratio from mtDNAcn(WB) may serve as an estimation for mtDNAcn(L). Both platelet and leukocyte counts in the sample are important sources of variation if comparing mtDNAcn among groups of patients when mtDNAcn is measured in DNA extracted from whole blood. Not taking the platelet/leukocyte ratio into account in whole blood measurements, may lead to overestimation and misclassification if interpreted as leukocytes' mtDNAcn.

Intervalo de parto em ovinos da raça Santa Inês

Objective was to study some environmental effects on the calving interval in Santa Ines sheep. Data were used experimental sheep flock of Santa Ines, Federal University of Piauí, Campus Profª Cinobelina Elvas, in Bom Jesus-PI. Environmental effects on the studied range of delivery were prenatal: birth year, birth type, age of mother at birth and weight of dam. The study of environmental effects on the calving interval was analyzed and the means were tested by the Students Newman Keuls test at 5% probability. It was observed range of calving interval medium 281.10 ± 64.76 days. The effects of year and season of calving were significant on the calving interval (P 0, 05), calving interval. The effects of year of birth and season of calving were important sources of variation on the calving interval, which reflects the need to consider these effects in models of genetic and phenotypic evaluation.

Short communication: Variations in major mineral contents of Mediterranean buffalo milk and application of Fourier-transform infrared spectroscopy for their prediction.

The aims of this study were (1) to assess variability in the major mineral components of buffalo milk, (2) to estimate the effect of certain environmental sources of variation on the major minerals during lactation, and (3) to investigate the possibility of using Fourier-transform infrared (FTIR) spectroscopy as an indirect, noninvasive tool for routine prediction of the mineral content of buffalo milk. A total of 173 buffaloes reared in 5 herds were sampled once during the morning milking. Milk samples were analyzed for Ca, P, K, and Mg contents within 3h of sample collection using inductively coupled plasma optical emission spectrometry. A Milkoscan FT2 (Foss, Hillerød, Denmark) was used to acquire milk spectra over the spectral range from 5,000 to 900 wavenumber/cm. Prediction models were built using a partial least square approach, and cross-validation was used to assess the prediction accuracy of FTIR. Prediction models were validated using a 4-fold random cross-validation, thus dividing the calibration-test set in 4 folds, using one of them to check the results (prediction models) and the remaining 3 to develop the calibration models. Buffalo milk minerals averaged 162, 117, 86, and 14.4mg/dL of milk for Ca, P, K, and Mg, respectively. Herd and days in milk were the most important sources of variation in the traits investigated. Parity slightly affected only Ca content. Coefficients of determination of cross-validation between the FTIR-predicted and the measured values were 0.71, 0.70, and 0.72 for Ca, Mg, and P, respectively, whereas prediction accuracy was lower for K (0.55). Our findings reveal FTIR to be an unsuitable tool when milk mineral content needs to be predicted with high accuracy. Predictions may play a role as indicator traits in selective breeding (if the additive genetic correlation between FTIR predictions and measures of milk minerals is high enough) or in monitoring the milk of buffalo populations for dairy industry purposes.

A Bayesian spatial random effects model characterisation of tumour heterogeneity implemented using Markov chain Monte Carlo (MCMC) simulation

The focus of this study is the development of a statistical modelling procedure for characterising intra-tumour heterogeneity, motivated by recent clinical literature indicating that a variety of tumours exhibit a considerable degree of genetic spatial variability. A formal spatial statistical model has been developed and used to characterise the structural heterogeneity of a number of supratentorial primitive neuroectodermal tumours (PNETs), based on diffusion-weighted magnetic resonance imaging. Particular attention is paid to the spatial dependence of diffusion close to the tumour boundary, in order to determine whether the data provide statistical evidence to support the proposition that water diffusivity in the boundary region of some tumours exhibits a deterministic dependence on distance from the boundary, in excess of an underlying random 2D spatial heterogeneity in diffusion. Tumour spatial heterogeneity measures were derived from the diffusion parameter estimates obtained using a Bayesian spatial random effects model. The analyses were implemented using Markov chain Monte Carlo (MCMC) simulation. Posterior predictive simulation was used to assess the adequacy of the statistical model. The main observations are that the previously reported relationship between diffusion and boundary proximity remains observable and achieves statistical significance after adjusting for an underlying random 2D spatial heterogeneity in the diffusion model parameters. A comparison of the magnitude of the boundary-distance effect with the underlying random 2D boundary heterogeneity suggests that both are important sources of variation in the vicinity of the boundary. No consistent pattern emerges from a comparison of the boundary and core spatial heterogeneity, with no indication of a consistently greater level of heterogeneity in one region compared with the other. The results raise the possibility that DWI might provide a surrogate marker of intra-tumour genetic regional heterogeneity, which would provide a powerful tool with applications in both patient management and in cancer research.

Hidden item variance in multiple mini-interview scores.

The extant literature has largely ignored a potentially significant source of variance in multiple mini-interview (MMI) scores by "hiding" the variance attributable to the sample of attributes used on an evaluation form. This potential source of hidden variance can be defined as rating items, which typically comprise an MMI evaluation form. Due to its multi-faceted, repeated measures format, reliability for the MMI has been primarily evaluated using generalizability (G) theory. A key assumption of G theory is that G studies model the most important sources of variance to which a researcher plans to generalize. Because G studies can only attribute variance to the facets that are modeled in a G study, failure to model potentially substantial sources of variation in MMI scores can result in biased estimates of variance components. This study demonstrates the implications of hiding the item facet in MMI studies when true item-level effects exist. An extensive Monte Carlo simulation study was conducted to examine whether a commonly used hidden item, person-by-station (p×s|i) G study design results in biased estimated variance components. Estimates from this hidden item model were compared with estimates from a more complete person-by-station-by-item (p×s×i) model. Results suggest that when true item-level effects exist, the hidden item model (p×s|i) will result in biased variance components which can bias reliability estimates; therefore, researchers should consider using the more complete person-by-station-by-item model (p×s×i) when evaluating generalizability of MMI scores.

Influence of genetic and non genetic factors on growth traits of Bharat Merino sheep in sub-temperate climate of Kodai hills of Tamil Nadu, India

In the present study, the data on 1649 Bharat Merino (BM) lambs; progeny of 144 sires over the year from 2000 to 2014 available at Southern Regional Research Centre (SRRC), Central Sheep and Wool Research Institute, Mannavanur were considered for the analysis. The different economic growth traits used for the analysis were birth weight (BWT), weaning weight (3MWT), 6 month weight (6MWT), 12 month weight (12MWT) and greasy fleece yield (GFY). The overall least-square means for weights (in kg) were 3.28±0.02, 19.08±0.23, 25.00±0.35, 34.79±0.59 and 2.13±0.07 for BWT, 3MWT, 6MWT, 12MWT and GFY respectively. Different non genetic factors such as year, sex, type of birth and dam's age had significant (P&lt;0.01) influence on BWT and 3MWT. Season influenced the BWT (P&lt;0.05) while it had no significant effect on 3MWT. Six month weight was also significantly (P&lt;0.05) influenced by all non-genetic factors taken under present study. Twelve month weight was significantly affected by year (P&lt;0.01), sex and season (P&lt;0.05). Similarly, analysis of variance showed that the year, sex of the lambs (P&lt;0.01) and season (P&lt;0.05) were important sources of variation on GFY of Bharat Merino sheep. Lambs born single had higher values of BWT and 3MWT than that of the lambs born as twins. The trend of the increase in BWT and 3MWT of the lambs is being observed up to the period when the age of their corresponding dams is 4-5 years. The findings of the present study showed that non - genetic factors play an important role in the expression of genetic potential in the lambs as well as growth performance of Bharat Merino sheep under sub temperate conditions of Kodai hills of Tamil Nadu, India. The genetic parameters estimated of 6MWT indicate that it is most suitable for use as selection criterion. Improvement of body weight of BM sheep seems feasible in selection programs, as some of the related traits are moderately heritable and those traits specially are well correlated, which could suggest that these traits are useful in selection programs.

Modelling the influence of biotic factors on species distribution patterns

Biotic interactions can have large effects on species distributions yet their role in shaping species ranges is seldom explored due to historical difficulties in incorporating biotic factors into models without a priori knowledge on interspecific interactions. Improved SDMs, which account for biotic factors and do not require a priori knowledge on species interactions, are needed to fully understand species distributions. Here, we model the influence of abiotic and biotic factors on species distribution patterns and explore the robustness of distributions under future climate change. We fit hierarchical spatial models using Integrated Nested Laplace Approximation (INLA) for lagomorph species throughout Europe and test the predictive ability of models containing only abiotic factors against models containing abiotic and biotic factors. We account for residual spatial autocorrelation using a conditional autoregressive (CAR) model. Model outputs are used to estimate areas in which abiotic and biotic factors determine species’ ranges. INLA models containing both abiotic and biotic factors had substantially better predictive ability than models containing abiotic factors only, for all but one of the four species. In models containing abiotic and biotic factors, both appeared equally important as determinants of lagomorph ranges, but the influences were spatially heterogeneous. Parts of widespread lagomorph ranges highly influenced by biotic factors will be less robust to future changes in climate, whereas parts of more localised species ranges highly influenced by the environment may be less robust to future climate. SDMs that do not explicitly include biotic factors are potentially misleading and omit a very important source of variation. For the field of species distribution modelling to advance, biotic factors must be taken into account in order to improve the reliability of predicting species distribution patterns both presently and under future climate change.

Using Clinical Trial Simulators to Analyse the Sources of Variance in Clinical Trials of Novel Therapies for Acute Viral Infections.

BackgroundAbout 90% of drugs fail in clinical development. The question is whether trials fail because of insufficient efficacy of the new treatment, or rather because of poor trial design that is unable to detect the true efficacy. The variance of the measured endpoints is a major, largely underestimated source of uncertainty in clinical trial design, particularly in acute viral infections. We use a clinical trial simulator to demonstrate how a thorough consideration of the variability inherent in clinical trials of novel therapies for acute viral infections can improve trial design.Methods and FindingsWe developed a clinical trial simulator to analyse the impact of three different types of variation on the outcome of a challenge study of influenza treatments for infected patients, including individual patient variability in the response to the drug, the variance of the measurement procedure, and the variance of the lower limit of quantification of endpoint measurements. In addition, we investigated the impact of protocol variation on clinical trial outcome. We found that the greatest source of variance was inter-individual variability in the natural course of infection. Running a larger phase II study can save up to $38 million, if an unlikely to succeed phase III trial is avoided. In addition, low-sensitivity viral load assays can lead to falsely negative trial outcomes.ConclusionsDue to high inter-individual variability in natural infection, the most important variable in clinical trial design for challenge studies of potential novel influenza treatments is the number of participants. 100 participants are preferable over 50. Using more sensitive viral load assays increases the probability of a positive trial outcome, but may in some circumstances lead to false positive outcomes. Clinical trial simulations are powerful tools to identify the most important sources of variance in clinical trials and thereby help improve trial design.

The Ins and Outs of Icelandic Unemployment

This paper presents new data on Icelandic labour market flows between employment, unemployment, and inactivity, constructed from the microdata in Statistics Iceland‘s Labour Force Survey (LFS). An analysis of the contribution of the transition rates to the dynamics of unemployment is then performed. Assuming a fixed labour force yields results comparable to previous estimates in Iceland, with a third of the variation in steady-state unemployment explained by the job finding rate, a significant departure from what is found in Anglo-Saxon, continental European, and Nordic economies. Taking account of movements in and out of the labour force has a significant effect on contributions of transition rates to variations in steady-state unemployment, with inactivity transitions accounting for roughly a third of the variability in steady-state unemployment and a dead-even split of the remaining two-thirds between the employment-unemployment and unemployment-employment transition rates. This contribution of inactivity transitions is comparable to that in the UK, US, and Spain. The background information available in the LFS indicates that some heterogeneity exists in the contributions by gender. The participation margin is thus an important source of variation in unemployment and needs to be accounted for to fully understand the drivers of Icelandic labour market fluctuations. Furthermore, ignoring transitions in and out of the labour force generates misleading results on the relative importance of the transition rates between employment and unemployment states in Iceland.