Relative male and female contributions to the supercooling point of their offspring in Microvelia reticulata (Heteroptera: Veliidae)

Cold hardiness is a key life history trait in temperate and polar ectothermic species, as it affects survival during overwintering, but its evolution is poorly understood. While many studies of cold hardiness in insects have shown differences between species, populations or developmental stages, data on the relative contribution of individual genotypes to cold hardiness are scarce and mainly limited to drosophilid fly species. We used a sib‐analysis (paternal half‐sib/full‐sib breeding design) to estimate the relative contributions of parental generation to the supercooling point (SCP) of the offspring of a heteropteran non‐model insect species, Microvelia reticulata (Heteroptera: Gerromorpha: Veliidae). We found that parent identity affected significantly SCP values of their offspring. Magnitudes of estimated sire and dam variance components were similar but the distributions of individual contributions to SCP differed between sires and dams, which points to sex‐specific genetic or parental effects on SCP in this species. The animal model failed to find a realistic estimate of heritability (h²) of SCP, suggesting that the underlying genetics of SCP in M. reticulata can not be characterized by purely additive effects.     

Absence from the nest due to human disturbance induces higher nest predation risk than natural recesses in Common Eiders Somateria mollissima

Human disturbance of nesting birds may cause reduced breeding success. It is therefore necessary to assess the impact of disturbance to identify steps that minimize negative impacts. We carried out a study of nesting success at two adjacent colonies of Common Eider Somateria mollissima on the islands of Grindøya and Håkøya in northern Norway between 2006 and 2011. Over the study period, nesting success was consistently higher on Håkøya (69–82%) than on Grindøya (35–60%). Between 2009 and 2011 we used camera monitoring of individual nests to identify determinants of nest survival and predation, focusing in particular on the effect of departures from the nest due to human disturbance, which differed between the colonies due to a long‐term research project on Grindøya. Overall, absence of Common Eiders from nests due to disturbance increased the predation risk by a factor of 6.42 for an increase of one additional daily disturbance. In contrast, absence due to natural recesses did not increase nest losses. Under high levels of human disturbance, camera monitoring indicated that the main cause of breeding failure was predation, primarily by Hooded Crows Corvus cornix, but also to some extent Great Black‐backed Gulls Larus marinus. The presence of cameras did not increase the predation risk. Both the presence of researchers and the sight of Common Eider females conspicuously departing from nests are likely to have provided cues to these predators. We suggest management trials to reduce nesting disturbance through the guarding of unoccupied nests to mitigate the effects of human disturbance on reproductive success.     

Effects of a neonicotinoid pesticide on thermoregulation of African honey bees (Apis mellifera scutellata)

Thiamethoxam is a widely used neonicotinoid pesticide that, as agonist of the nicotinic acetylcholine receptors, has been shown to elicit a variety of sublethal effects in honey bees. However, information concerning neonicotinoid effects on honey bee thermoregulation is lacking. Thermoregulation is an essential ability for the honey bee that guarantees the success of foraging and many in-hive tasks, especially brood rearing. We tested the effects of acute exposure to thiamethoxam (0.2, 1, 2 ng/bee) on the thorax temperatures of foragers exposed to low (22 °C) and high (33 °C) temperature environments. Thiamethoxam significantly altered honey bee thorax temperature at all doses tested; the effects elicited varied depending on the environmental temperature and pesticide dose to which individuals were exposed. When bees were exposed to the high temperature environment, the high dose of thiamethoxam increased their thorax temperature 1–2 h after exposure. When bees were exposed to the low temperature, the higher doses of the neonicotinoid reduced bee thorax temperatures 60–90 min after treatment. In both experiments, the neonicotinoid decreased the temperature of bees the day following the exposure. After a cold shock (5 min at 4 °C), the two higher doses elicited a decrease of the thorax temperature, while the lower dose caused an increase, compared to the control. These alterations in thermoregulation caused by thiamethoxam may affect bee foraging activity and a variety of in-hive tasks, likely leading to negative consequences at the colony level. Our results shed light on sublethal effect of pesticides which our bees have to deal with.     

Persistence of a Wolbachia infection frequency cline in Drosophila melanogaster and the possible role of reproductive dormancy

Field populations of arthropods are often polymorphic for Wolbachia but the factors maintaining intermediate Wolbachia frequencies are generally not understood. In Drosophila melanogaster, Wolbachia frequencies are highly variable across the globe. We document the persistence of a Wolbachia infection frequency cline in D. melanogaster populations from eastern Australia across at least 20 years, with frequencies generally high in the tropics but lower in cool temperate regions. The results are interpreted using a model of frequency dynamics incorporating cytoplasmic incompatibility (CI), imperfect maternal transmission and Wolbachia effects on fitness. Clinal variation is less pronounced in eastern North America which may reflect annual recolonization at higher latitudes. Limited samples from Africa from latitudes matching our tropical and subtropical samples from Australia and North America show comparably high infection frequencies, but some equatorial samples show lower frequencies. Adult dormancy across cold periods may contribute to the Australian Wolbachia cline. Infected flies exposed to cold conditions for an extended period had reduced fecundity and viability, an effect not evident in unexposed controls. These fitness costs may contribute to the relatively low Wolbachia frequencies in Australian temperate areas; whereas different processes, including CI induced by young males, may contribute to higher frequencies in tropical locations.     

Genetic architecture and maternal contributions of early‐life survival in lake trout Salvelinus namaycush

The influences of additive, non‐additive and maternal effects on early survival (uneyed embryo survival, eyed embryo survival, alevin survival and overall survival to first feeding) were quantified in lake trout Salvelinus namaycush using a 7 × 7 full‐factorial breeding design. Maternal effects followed by non‐additive genetic effects explained around one third of the phenotypic variance of the survival traits. Although the amount of additive genetic effects were low (<1%), suggesting a limited potential of the traits to respond to new selection pressures, how maternal and non‐additive genetic effects may respond to selection under certain circumstances are discussed.     

Two-stage functional mixed models for evaluating the effect of longitudinal covariate profiles on a scalar outcome

The Daily Hormone Study, a substudy of the Study of Women's Health Across the Nation (SWAN) consisting of more than 600 pre- and perimenopausal women, includes a scalar measure of total hip bone mineral density (BMD) together with repeated measures of creatinine-adjusted follicle stimulating hormone (FSH) assayed from daily urine samples collected over one menstrual cycle. It is of scientific interest to investigate the effect of the FSH time profile during a menstrual cycle on total hip BMD, adjusting for age and body mass index. The statistical analysis is challenged by several features of the data: (1) the covariate FSH is measured longitudinally and its effect on the scalar outcome BMD may be complex; (2) due to varying menstrual cycle lengths, subjects have unbalanced longitudinal measures of FSH; and (3) the longitudinal measures of FSH are subject to considerable among- and within-subject variations and measurement errors. We propose a measurement error partial functional linear model, where repeated measures of FSH are modeled using a functional mixed effects model and the effect of the FSH time profile on BMD is modeled using a partial functional linear model by treating the unobserved true subject-specific FSH time profile as a functional covariate. We develop a two-stage nonparametric regression calibration method using period smoothing splines. Using the connection between smoothing splines and mixed models, we show that a key feature of our approach is that estimation at both stages can be conveniently cast into a unified mixed model framework. A simple testing procedure for constant functional covariate effect is also proposed. The proposed methods are evaluated using simulation studies and applied to the SWAN data.     

Random effects modeling approaches for estimating ROC curves from repeated ordinal tests without a gold standard

Estimating diagnostic accuracy without a gold standard is an important problem in medical testing. Although there is a fairly large literature on this problem for the case of repeated binary tests, there is substantially less work for the case of ordinal tests. A noted exception is the work by Zhou, Castelluccio, and Zhou (2005, Biometrics 61, 600-609), which proposed a methodology for estimating receiver operating characteristic (ROC) curves without a gold standard from multiple ordinal tests. A key assumption in their work was that the test results are independent conditional on the true test result. I propose random effects modeling approaches that incorporate dependence between the ordinal tests, and I show through asymptotic results and simulations the importance of correctly accounting for the dependence between tests. These modeling approaches, along with the importance of accounting for the dependence between tests, are illustrated by analyzing the uterine cancer pathology data analyzed by Zhou et al. (2005).     

Bayesian adaptive regression splines for hierarchical data

This article considers methodology for hierarchical functional data analysis, motivated by studies of reproductive hormone profiles in the menstrual cycle. Current methods standardize the cycle lengths and ignore the timing of ovulation within the cycle, both of which are biologically informative. Methods are needed that avoid standardization, while flexibly incorporating information on covariates and the timing of reference events, such as ovulation and onset of menses. In addition, it is necessary to account for within-woman dependency when data are collected for multiple cycles. We propose an approach based on a hierarchical generalization of Bayesian multivariate adaptive regression splines. Our formulation allows for an unknown set of basis functions characterizing the population-averaged and woman-specific trajectories in relation to covariates. A reversible jump Markov chain Monte Carlo algorithm is developed for posterior computation. Applying the methods to data from the North Carolina Early Pregnancy Study, we investigate differences in urinary progesterone profiles between conception and nonconception cycles.     

On models for binomial data with random numbers of trials

A binomial outcome is a count s of the number of successes out of the total number of independent trials n=s+f, where f is a count of the failures. The n are random variables not fixed by design in many studies. Joint modeling of (s, f) can provide additional insight into the science and into the probability pi of success that cannot be directly incorporated by the logistic regression model. Observations where n= 0 are excluded from the binomial analysis yet may be important to understanding how pi is influenced by covariates. Correlation between s and f may exist and be of direct interest. We propose Bayesian multivariate Poisson models for the bivariate response (s, f), correlated through random effects. We extend our models to the analysis of longitudinal and multivariate longitudinal binomial outcomes. Our methodology was motivated by two disparate examples, one from teratology and one from an HIV tertiary intervention study.