Decreased abundance and diversity of culturable Pseudomonas spp. populations with increasing copper exposure in the sugar beet rhizosphere

Recent studies have indicated that culturable bacteria constitute highly sensitive bioindicators of metal-induced stress in soil. We report the impact of different copper exposure levels characteristic of contaminated agricultural soils on culturable Pseudomonas spp. in the rhizosphere of sugar beet. We observed that the abundance of Pseudomonas spp. was much more severely affected than that of the general population of culturable heterotrophic bacteria by copper. For diversity assessment, Pseudomonas isolates were divided into operational taxonomic units based on amplified ribosomal DNA restriction analysis and genomic PCR fingerprinting by universally primed PCR. Copper significantly decreased the diversity of Pseudomonas spp. in the rhizosphere and significantly increased the frequency of copper-resistant isolates. Concomitant chemical and biological analysis of copper in the rhizosphere and in bulk soil extracts indicated no rhizosphere effect and a relatively low copper bioavailability in the studied soil, suggesting that the observed effects of copper may occur at lower total concentrations in other soils. We conclude that culturable Pseudomonas sensu stricto constitutes a highly sensitive and relevant bioindicator group for the impact of copper in the rhizosphere habitat, and suggest that continued application of copper to agricultural soils poses a significant risk to successful rhizosphere colonization by Pseudomonas spp.     

Variable selection for logistic regression using a prediction-focused information criterion

In biostatistical practice, it is common to use information criteria as a guide for model selection. We propose new versions of the focused information criterion (FIC) for variable selection in logistic regression. The FIC gives, depending on the quantity to be estimated, possibly different sets of selected variables. The standard version of the FIC measures the mean squared error of the estimator of the quantity of interest in the selected model. In this article, we propose more general versions of the FIC, allowing other risk measures such as the one based on L(p) error. When prediction of an event is important, as is often the case in medical applications, we construct an FIC using the error rate as a natural risk measure. The advantages of using an information criterion which depends on both the quantity of interest and the selected risk measure are illustrated by means of a simulation study and application to a study on diabetic retinopathy.     

Goodness-of-fit diagnostics for Bayesian hierarchical models

This article proposes methodology for assessing goodness of fit in Bayesian hierarchical models. The methodology is based on comparing values of pivotal discrepancy measures (PDMs), computed using parameter values drawn from the posterior distribution, to known reference distributions. Because the resulting diagnostics can be calculated from standard output of Markov chain Monte Carlo algorithms, their computational costs are minimal. Several simulation studies are provided, each of which suggests that diagnostics based on PDMs have higher statistical power than comparable posterior-predictive diagnostic checks in detecting model departures. The proposed methodology is illustrated in a clinical application; an application to discrete data is described in supplementary material.     

Multilocus estimation of selfing and its heritability

We describe a new method of estimating the selfing rate (S) in a mixed mating population based on a population structure approach that accounts for possible intergenerational correlation in selfing rate, giving rise to an estimate of the upper limit for heritability of selfing rate (h(2)). A correlation between generations in selfing rate is shown to affect one- and two-locus probabilities of identity by descent. Conventional estimates of selfing rate based on a population structure approach are positively biased by intergenerational correlation in selfing. Multilocus genotypes of individuals are used to give maximum-likelihood estimates of S and h(2) in the presence of scoring artifacts. Our multilocus estimation of selfing rate and its heritability (MESH) method was tested with simulated data for a range of conditions. Selfing rate estimates from MESH have low bias and root mean squared error, whereas estimates of the heritability of selfing rate have more uncertainty. Increasing the number of individuals in a sample helps to reduce bias and root mean squared error more than increasing the number of loci of sampled individuals. Improved estimates of selfing rate, as well as estimates of its heritability, can be obtained with this method, although a large number of loci and individuals are needed to achieve best results.     

High value of short rotation coppice plantations for phytodiversity in rural landscapes

The demand for wood from short rotation coppice (SRC) plantations as a renewable energy source is currently increasing and could affect biodiversity in agricultural areas. The objective was to evaluate the contribution of SRC plantations to phytodiversity in agricultural landscapes assessed as species richness, species–area relationships, Shannon indices, detrended correspondence analysis on species composition, Sørensen similarities, habitat preference proportions, and species proportions found in only one land use. Vegetation surveys were conducted on 12 willow (Salix spp.) and three poplar (Populus spp.) coppice sites as well as on surrounding arable lands, grasslands and forests in central Sweden and northern Germany. SRC plantations were richer in plant species (mean: 30 species per 100 m²) than arable land (10), coniferous forests (13) and mixed forests in Germany (12). Comparing SRC plantations with other land uses, we found lowest similarities in species composition with arable lands, coniferous forests and German mixed forests and highest similarities with marginal grassland strips, grasslands and Swedish mixed forests. Similarity depended on the SRC tree cover: at increased tree cover, SRC plantations became less similar to grasslands but more similar to forests. The SRC plantations were composed of a mixture of grassland (33%), ruderal (24%) and woodland (15%) species. Species abundance in SRC plantations was more heterogeneous than in arable lands. We conclude that SRC plantations form novel habitats leading to different plant species composition compared to conventional land uses. Their landscape‐scale value for phytodiversity changes depending on harvest cycles and over time. As a structural landscape element, SRC plantations contribute positively to phytodiversity in rural areas, especially in land use mosaics where these plantations are admixed to other land uses with dissimilar plant species composition such as arable land, coniferous forest and, at the German sites, also mixed forest.     

The influence of time,soil characteristics,and land‐use history on soil phosphorus legacies: a global meta‐analysis

Agriculturally driven changes in soil phosphorus (P) are known to have persistent effects on local ecosystem structure and function, but regional patterns of soil P recovery following cessation of agriculture are less well understood. We synthesized data from 94 published studies to assess evidence of these land‐use legacies throughout the world by comparing soil labile and total P content in abandoned agricultural areas to that of reference ecosystems or sites remaining in agriculture. Our meta‐analysis shows that soil P content was typically elevated after abandonment compared to reference levels, but reduced compared to soils that remained under agriculture. There were more pronounced differences in the legacies of past agriculture on soil P across regions than between the types of land use practiced prior to abandonment (cropland, pasture, or forage grassland). However, consistent patterns of soil P enrichment or depletion according to soil order and types of post‐agricultural vegetation suggest that these factors may mediate agricultural legacies on soil P. We also used mixed effects models to examine the role of multiple variables on soil P recovery following agriculture. Time since cessation of agriculture was highly influential on soil P legacies, with clear reductions in the degree of labile and total P enrichment relative to reference ecosystems over time. Soil characteristics (clay content and pH) were strongly related to changes in labile P compared to reference sites, but these were relatively unimportant for total P. The duration of past agricultural use and climate were weakly related to changes in total P only. Our finding of reductions in the degree of soil P alteration over time relative to reference conditions reveals the potential to mitigate these land‐use legacies in some soils. Better ability to predict dynamics of soil nutrient recovery after termination of agricultural use is essential to ecosystem management following land‐use change.     

The effects of thinning and gypsy moth defoliation on wood volume growth in oaks

Stem dissection and dendroecological methods were used to examine the effects of thinning and defoliation by gypsy moth (Lymantria dispar L.) on wood volume increment in oaks (Quercus rubra L., Q. alba L., Q. prinus L.). A model was developed to evaluate radial volume increment growth at three time periods: before defoliation, during defoliation and after defoliation, as a function of species, defoliation intensity and crown position. Volume increment during these same time periods was also compared at different stem locations. Trees were defoliated for two consecutive years and results indicated that volume loss was greater during the second year of defoliation with complete recovery taking 2–3 years after defoliation. Oaks in thinned stands had similar reductions in annual volume increment during defoliation as those in the unthinned stand. Annual volume increment demonstrated a decreasing trend from stump to base of the live crown and volume increment of the lowest log (from stump height to 1.37 m), was always higher than upper log sections, even during defoliation. Both earlywood and latewood increments were reduced during defoliation; however, latewood reductions were distributed along entire stems while earlywood reductions were greater on upper stem sections within the crown.     

A signed-rank test for clustered data

Summary .   We consider the problem of comparing two outcome measures when the pairs are clustered. Using the general principle of within-cluster resampling, we obtain a novel signed-rank test for clustered paired data. We show by a simple informative cluster size simulation model that only our test maintains the correct size under a null hypothesis of marginal symmetry compared to four other existing signed rank tests; further, our test has adequate power when cluster size is noninformative. In general, cluster size is informative if the distribution of pair-wise differences within a cluster depends on the cluster size. An application of our method to testing radiation toxicity trend is presented.