Preliminary archaeoentomological analyses of permafrost-preserved cultural layers from the pre-contact Yup’ik Eskimo site of Nunalleq, Alaska : implications, potential and methodological considerations

Acknowledgements Site excavation and samples collection were conducted by archaeologists from the University of Aberdeen, with the help of archaeologists and student excavators from the University of Aberdeen University of Alaska Fairbanks and Bryn Mawr College, Kuskokwim Campus, College of Rural Alaska and residents of Quinhagak and Mekoryuk. This study is funded through AHRC grant to the project ‘Understanding Cultural Resilience and Climate Change on the Bering Sea through Yup’ik Ecological Knowledge, Lifeways, Learning and Archaeology’ to Rick Knecht, Kate Britton and Charlotta Hillderal (University of Aberdeen; AH/K006029/1). Thanks are due to Qanirtuuq Inc. and Quinhagak, Alaska for sampling permissions and to entomologists working at the CNC in Ottawa for allowing access to reference collections of beetles, lice and fleas. Yves Bousquet, Ales Smetana and Anthony E. Davies are specially acknowledged for their help with the identification of coleopteran specimens. Finally, we would also like to thank Scott Elias for useful comments on the original manuscript.Peer reviewedPublisher PD

A novel causal mechanism for grey squirrel bark stripping: The Calcium Hypothesis

AbstractGrey squirrels, Sciurus carolinensis, damage trees in the UK by stripping bark and eating the underlying phloem; squirrel motivation for damage is, however, unknown. Damage can result in deterioration of timber quality and a significant economic toll on the forestry industry. Prediction of severe damage followed by targeted killing of squirrels is the current recommended management option. However, the use of warfarin (an anticoagulant poison) is now restricted in the UK and other more humane methods of killing are labour-intensive, so an alternative solution is needed. A better understanding of what motivates grey squirrels to strip bark may enable a preventive approach to be developed. Whilst the bark stripping literature has explored predictive factors affecting the likelihood of damage, causal understanding is lacking. The aim of this review is to introduce the Calcium Hypothesis as a possible explanation for bark stripping, with a view to informing the prevention of damage. The Calcium Hypothesis states that grey squirrels damage trees to ameliorate a calcium deficiency. The main predictive factors of bark stripping behaviour each inform and lend support to the Calcium Hypothesis. Calcium is stored in tree phloem, and damage increases with phloem width, providing squirrels with more calcium per unit area ingested. Calcium levels increase in trees as active growth resumes after winter dormancy, this occurs immediately prior to the main bark stripping season of May–July, and trees growing most vigorously are at increased risk of damage. It is likely grey squirrels also have a requirement for calcium during the bark stripping season. Adult females will be under post-parturition pressures such as lactation, and juveniles will be going through their main period of bone growth, both of which likely represent a requirement for calcium – which supports an observed positive correlation between juvenile abundance and bark stripping. A high autumnal seed crop increases juvenile recruitment the following spring, and could also induce a requirement for calcium to a population due to the high phosphorus to calcium ratio of seeds. To further investigate the hypothesis, the extent to which grey squirrels can utilise calcium oxalate, as calcium occurs in bark, should be determined, and also the extent to which grey squirrels undergo seasonal periods of calcium deficiency. Increasing our causal understanding of bark stripping could inform the future development of preventive measures to aid forest management

Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines

Background: Multiple imputation (MI) provides an effective approach to handle missing covariate data within prognostic modelling studies, as it can properly account for the missing data uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling techniques to obtain the estimates of interest. The estimates from each imputed dataset are then combined into one overall estimate and variance, incorporating both the within and between imputation variability. Rubin's rules for combining these multiply imputed estimates are based on asymptotic theory. The resulting combined estimates may be more accurate if the posterior distribution of the population parameter of interest is better approximated by the normal distribution. However, the normality assumption may not be appropriate for all the parameters of interest when analysing prognostic modelling studies, such as predicted survival probabilities and model performance measures. Methods: Guidelines for combining the estimates of interest when analysing prognostic modelling studies are provided. A literature review is performed to identify current practice for combining such estimates in prognostic modelling studies. Results: Methods for combining all reported estimates after MI were not well reported in the current literature. Rubin's rules without applying any transformations were the standard approach used, when any method was stated. Conclusion: The proposed simple guidelines for combining estimates after MI may lead to a wider and more appropriate use of MI in future prognostic modelling studies

The Life and Death of Barn Beetles: Faunas from Manure and Stored Hay inside Farm Buildings in Northern Iceland

This research was funded by the Commonwealth Scholarship Commission and received support from the Research Budget of the Department of Archaeology at the University of Aberdeen. This project was undertaken as part of doctoral studies supervised by Dr Karen Milek, to whom V.F. is especially grateful for her support and advice. Thomas Birch, Sigrún Inga Garðarsdóttir, and Paul Ledger provided invaluable assistance during fieldwork. V.F. would like to dedicate this paper to Tom and Sía, who met during this fieldwork and are getting married this year. Many people from Fornleifastofnun Íslands – Garðar Guðmundsson, Ólöf Þorsteinsdóttir, Þóra Pétursdóttir, Adolf Friðriksson and Uggi Ævarsson – as well as Unnstein Ingason, Ágústa Edwald, and Mark Young, helped with fieldwork logistics. Special thanks are due to all the Icelandic farmers and their families who kindly allowed us to collect insects on their farms and provided help when needed: Hermann Aðalsteinsson, Hermína Fjóla Ingólfsdóttir, Guðmundur Skúlason, Sigrún Á. Franzdóttir, Dúna Magnúsdóttir, Sverrir Steinbergsson, Valgeir Þorvaldsson, Reynir Sveinsson, Jónas Þór Ingólfsson, and Ívar Ólafsson. Eva Panagiotakopulu, Jan Klimaszewski, Ales Smetana, Georges Pelletier, Gabor Pozsgai, and Jenni Stockham helped with some of the beetle identifications. A.J.D. acknowledges the support of National Science Foundation through ARC 1202692. Consultation of the BugsCEP database (Buckland & Buckland, 2006) aided the redaction of this paper. The authors would like to thank David Smith and two anonymous reviewers for insightful comments that helped improve the quality of this paper.Peer reviewedPostprin

Infants in Control: Rapid Anticipation of Action Outcomes in a Gaze-Contingent Paradigm

Infants' poor motor abilities limit their interaction with their environment and render studying infant cognition notoriously difficult. Exceptions are eye movements, which reach high accuracy early, but generally do not allow manipulation of the physical environment. In this study, real-time eye tracking is used to put 6- and 8-month-old infants in direct control of their visual surroundings to study the fundamental problem of discovery of agency, i.e. the ability to infer that certain sensory events are caused by one's own actions. We demonstrate that infants quickly learn to perform eye movements to trigger the appearance of new stimuli and that they anticipate the consequences of their actions in as few as 3 trials. Our findings show that infants can rapidly discover new ways of controlling their environment. We suggest that gaze-contingent paradigms offer effective new ways for studying many aspects of infant learning and cognition in an interactive fashion and provide new opportunities for behavioral training and treatment in infants

The impact of alcohol consumption on patterns of union formation in Russia 1998–2010: An assessment using longitudinal data

Using data from the Russian Longitudinal Monitoring Survey, 1998–2010, we investigated the extent to which patterns of alcohol consumption in Russia are associated with the subsequent likelihood of entry into cohabitation and marriage. Using discrete-time event history analysis we estimated for 16–50 year olds the extent to which the probabilities of entry into the two types of union were affected by the amount of alcohol drunk and the pattern of drinking, adjusted to allow for social and demographic factors including income, employment, and health. The results show that individuals who did not drink alcohol were less likely to embark on either cohabitation or marriage, that frequent consumption of alcohol was associated with a greater chance of entering unmarried cohabitation than of entering into a marriage, and that heavy drinkers were less likely to convert their relationship from cohabitation to marriage

Sensitivity Analysis for Not-at-Random Missing Data in Trial-Based Cost-Effectiveness Analysis : A Tutorial

Cost-effectiveness analyses (CEA) of randomised controlled trials are a key source of information for health care decision makers. Missing data are, however, a common issue that can seriously undermine their validity. A major concern is that the chance of data being missing may be directly linked to the unobserved value itself [missing not at random (MNAR)]. For example, patients with poorer health may be less likely to complete quality-of-life questionnaires. However, the extent to which this occurs cannot be ascertained from the data at hand. Guidelines recommend conducting sensitivity analyses to assess the robustness of conclusions to plausible MNAR assumptions, but this is rarely done in practice, possibly because of a lack of practical guidance. This tutorial aims to address this by presenting an accessible framework and practical guidance for conducting sensitivity analysis for MNAR data in trial-based CEA. We review some of the methods for conducting sensitivity analysis, but focus on one particularly accessible approach, where the data are multiply-imputed and then modified to reflect plausible MNAR scenarios. We illustrate the implementation of this approach on a weight-loss trial, providing the software code. We then explore further issues around its use in practice

Conservation of genetic uniqueness in remaining populations of red squirrels (Sciurus vulgaris L.) in the South of England

The Eurasian red squirrel (Sciurus vulgaris) is an emblematic species for conservation, and its decline in the British Isles exemplifies the impact that alien introductions can have on native ecosystems. Indeed, red squirrels in this region have declined dramatically over the last 60 years due to the spread of squirrelpox virus following the introduction of the gray squirrel (Sciurus carolinensis). Currently, red squirrel populations in Britain are fragmented and need to be closely monitored in order to assess their viability and the effectiveness of conservation efforts. The situation is even more dramatic in the South of England, where S. vulgaris survives only on islands (Brownsea Island, Furzey Island, and the Isle of Wight). Using the D‐loop, we investigated the genetic diversity and putative ancestry of the squirrels from Southern England and compared them to a European dataset composed of 1,016 samples from 54 populations. We found that our three populations were more closely related to other squirrels from the British Isles than squirrels from Europe, showed low genetic diversity, and also harbored several private haplotypes. Our study demonstrates how genetically unique the Southern English populations are in comparison with squirrels from the continental European range. We report the presence of four private haplotypes, suggesting that these populations may potentially harbor distinct genetic lineages. Our results emphasize the importance of preserving these isolated red squirrel populations for the conservation of the species

Comparison of imputation methods for handling missing covariate data when fitting a Cox proportional hazards model: a resampling study

<p>Abstract</p> <p>Background</p> <p>The appropriate handling of missing covariate data in prognostic modelling studies is yet to be conclusively determined. A resampling study was performed to investigate the effects of different missing data methods on the performance of a prognostic model.</p> <p>Methods</p> <p>Observed data for 1000 cases were sampled with replacement from a large complete dataset of 7507 patients to obtain 500 replications. Five levels of missingness (ranging from 5% to 75%) were imposed on three covariates using a missing at random (MAR) mechanism. Five missing data methods were applied; a) complete case analysis (CC) b) single imputation using regression switching with predictive mean matching (SI), c) multiple imputation using regression switching imputation, d) multiple imputation using regression switching with predictive mean matching (MICE-PMM) and e) multiple imputation using flexible additive imputation models. A Cox proportional hazards model was fitted to each dataset and estimates for the regression coefficients and model performance measures obtained.</p> <p>Results</p> <p>CC produced biased regression coefficient estimates and inflated standard errors (SEs) with 25% or more missingness. The underestimated SE after SI resulted in poor coverage with 25% or more missingness. Of the MI approaches investigated, MI using MICE-PMM produced the least biased estimates and better model performance measures. However, this MI approach still produced biased regression coefficient estimates with 75% missingness.</p> <p>Conclusions</p> <p>Very few differences were seen between the results from all missing data approaches with 5% missingness. However, performing MI using MICE-PMM may be the preferred missing data approach for handling between 10% and 50% MAR missingness.</p