Large-scale,millennial-length temperature reconstructions from tree-rings

Over the past two decades, the dendroclimate community has produced various annually resolved, warm season temperature reconstructions for the extratropical Northern Hemisphere. Here we compare these tree-ring based reconstructions back to 831 CE and present a set of basic metrics to provide guidance for non-specialists on their interpretation and use. We specifically draw attention to (i) the imbalance between (numerous) short and (few) long site chronologies incorporated into the hemispheric means, (ii) the beneficial effects of including maximum latewood density chronologies in the recently published reconstructions, (iii) a decrease in reconstruction covariance prior to 1400 CE, and (iv) the varying amplitudes and trends of reconstructed temperatures over the past 1100 years. Whereas the reconstructions agree on several important features, such as warmth during medieval times and cooler temperatures in the 17th and 19th centuries, they still exhibit substantial differences during 13th and 14th centuries. We caution users who might consider combining the reconstructions through simple averaging that all reconstructions share some of the same underlying tree-ring data, and provide four recommendations to guide future efforts to better understand past millennium temperature variability.     

Bayesian Quantile Regression for Longitudinal Studies with Nonignorable Missing Data

Summary .  We study quantile regression (QR) for longitudinal measurements with nonignorable intermittent missing data and dropout. Compared to conventional mean regression, quantile regression can characterize the entire conditional distribution of the outcome variable, and is more robust to outliers and misspecification of the error distribution. We account for the within-subject correlation by introducing a   ℓ₂   penalty in the usual QR check function to shrink the subject-specific intercepts and slopes toward the common population values. The informative missing data are assumed to be related to the longitudinal outcome process through the shared latent random effects. We assess the performance of the proposed method using simulation studies, and illustrate it with data from a pediatric AIDS clinical trial.     

Analysis of genetic changes in radiated and non-radiated bulk oat (Avena sativa L.) populations

Summary In both radiated and non-radiated oat populations inbreeding coefficients increased more slowly than was expected on the assumption of full selfing and equal selective values for homozygotes and heterozygotes. Assuming 1% outcrossing for oats and a selective value of 1.0 for the mean, the heterozygotes for two loci governing crown rust reaction have an advantage of 50% over the homozygotes. This study supports previous observations that the heterozygote often has a decided advantage in predominantly self-pollinated crops.     

ABC as a flexible framework to estimate demography over space and time: some cons,many pros

The analysis of genetic variation to estimate demographic and historical parameters and to quantitatively compare alternative scenarios recently gained a powerful and flexible approach: the Approximate Bayesian Computation (ABC). The likelihood functions does not need to be theoretically specified, but posterior distributions can be approximated by simulation even assuming very complex population models including both natural and human‐induced processes. Prior information can be easily incorporated and the quality of the results can be analysed with rather limited additional effort. ABC is not a statistical analysis per se, but rather a statistical framework and any specific application is a sort of hybrid between a simulation and a data‐analysis study. Complete software packages performing the necessary steps under a set of models and for specific genetic markers are already available, but the flexibility of the method is better exploited combining different programs. Many questions relevant in ecology can be addressed using ABC, but adequate amount of time should be dedicated to decide among alternative options and to evaluate the results. In this paper we will describe and critically comment on the different steps of an ABC analysis, analyse some of the published applications of ABC and provide user guidelines.     

Gait stability,variability and complexity on inclined surfaces

This study evaluated the gait stability, variability, and complexity of healthy young adults on inclined surfaces. A total of 49 individuals walked on a treadmill at their preferred speed for 4 min at inclinations of 6%, 8%, and 10% in upward (UP) and downward (DOWN) conditions, and in horizontal (0%) condition. Gait variability was assessed using average standard deviation trunk acceleration between strides (VAR), gait stability was assessed using margin of stability (MoS) and maximum Lyapunov exponent (λs), and gait complexity was assessed using sample entropy (SEn). Trunk variability (VAR) increased in the medial-lateral (ML), anterior-posterior, and vertical directions for all inclined conditions. The SEn values indicated that movement complexity decreased almost linearly from DOWN to UP conditions, reflecting changes in gait pattern with longer and slower steps as inclination increased. The DOWN conditions were associated with the highest variability and lowest stability in the MoS ML, but not in λs. Stability was lower in UP conditions, which exhibited the largest λs values. The overall results support the hypothesis that inclined surfaces decrease gait stability and alter gait variability, particularly in UP conditions.     

Describing Ordinal Odds Ratios for Stratified r × c Tables

For an r × ctable with ordinal responses, odds ratios are commonly used to describe the relationship between the row and column variables. This article shows two types of ordinal odds ratios where local‐global odds ratios are used to compare several groups on a c‐category ordinal response and a global odds ratio is used to measure the global association between a pair of ordinal responses. When there is a stratification factor, we consider Mantel‐Haenszel (MH) type estimators of these odds ratios to summarize the association from several strata. Like the ordinary MH estimator of the common odds ratio for several 2 × 2 contingency tables, the estimators are used when the association is not expected to vary drastically among the strata. Also, the estimators are consistent under the ordinary asymptotic framework in which the number of strata is fixed and also under sparse asymptotics in which the number of strata grows with the sample size. Compared to the maximum likelihood estimators, simulations find that the MH type estimators perform better especially when each stratum has few observations. This article provides variances and covariances formulae for the local‐global odds ratios estimators and applies the bootstrap method to obtain a standard error for the global odds ratio estimator. At the end, we discuss possible ways of testing the homogeneity assumption.     

The recolonization of Europe by brown bears Ursus arctos Linnaeus, 1758 after the Last Glacial Maximum

1. At the end of the Last Glacial Maximum brown bears Ursus arctos recolonized the glacial landscape of Central and Northern Europe faster than all other carnivorous mammal species of the Holocene fauna. Ursus arctos was recorded in Northern Europe from the beginning of the Late-Glacial. The recolonization of northern Central Europe may have taken place directly after the maximum glaciation. The distribution of the brown bear was restricted to glacial refugia only during the Last Glacial Maximum, for probably no more than 10 000 years. 2. Genetic analyses have suggested three glacial refugia for the brown bear: the Iberian Peninsula, the Italian Peninsula and the Balkans. Subfossil records of Ursus arctos from north-western Moldova as well as reconstructed environmental conditions during the Last Glacial Maximum in this area suggest to us a fourth glacial refuge for the brown bear. Because of its connection to the Carpathians, we designate this as the ‘Carpathian refuge’. 3. Due to the low genetic distance between brown bears of northern Norway, Finland, Estonia, north-eastern Russia and the northern Carpathians (the so-called eastern lineage), the Carpathians were considered the geographical origin of the recolonization of these regions. During the recolonization of northern Europe the brown bear probably reached these areas rapidly from the putative Carpathian refuge.