Spatial and temporal factors associated with nest survival of Gray Flycatchers in managed ponderosa pine forests

Gray Flycatchers (Empidonax wrightii) breed in a variety of habitats in the arid and semi‐arid regions of the western United States, but little is known about their breeding biology, especially in the northern portion of their range where they nest in ponderosa pine (Pinus ponderosa) forests. From May to July 2014 and 2015, we conducted surveys for singing male Gray Flycatchers along the eastern slope of the Cascade Range in Washington, U.S.A, monitored flycatcher nests, and quantified nest‐site vegetation. We used a logistic‐exposure model fit within a Bayesian framework to model the daily survival probability of flycatcher nests. During the 2 yr of our study, we monitored 141 nests, with 93% in ponderosa pines. Mean clutch size was 3.6 eggs and the mean number of young fledged per nest was 3.2. Predation accounted for 90% of failed nests. We found a positive association between daily nest survival and both nest height and distance of nest substrates from the nearest tree. Flycatchers that locate their nests higher above the ground and further from adjacent trees may be choosing the safest alternative because higher nests may be less exposed to terrestrial predators and nests in trees that are farther from other trees may be less exposed to arboreal predators such as jays (Corvidae) that may forage in patches with connected canopies. Nests in trees farther from other trees may also allow earlier detection of approaching predators and thus aid in nest defense.     

Detection of genetic variants affecting cattle behaviour and their impact on milk production: a genome‐wide association study

Behaviour traits of cattle have been reported to affect important production traits, such as meat quality and milk performance as well as reproduction and health. Genetic predisposition is, together with environmental stimuli, undoubtedly involved in the development of behaviour phenotypes. Underlying molecular mechanisms affecting behaviour in general and behaviour and productions traits in particular still have to be studied in detail. Therefore, we performed a genome‐wide association study in an F₂ Charolais × German Holstein cross‐breed population to identify genetic variants that affect behaviour‐related traits assessed in an open‐field and novel‐object test and analysed their putative impact on milk performance. Of 37 201 tested single nucleotide polymorphism (SNPs), four showed a genome‐wide and 37 a chromosome‐wide significant association with behaviour traits assessed in both tests. Nine of the SNPs that were associated with behaviour traits likewise showed a nominal significant association with milk performance traits. On chromosomes 14 and 29, six SNPs were identified to be associated with exploratory behaviour and inactivity during the novel‐object test as well as with milk yield traits. Least squares means for behaviour and milk performance traits for these SNPs revealed that genotypes associated with higher inactivity and less exploratory behaviour promote higher milk yields. Whether these results are due to molecular mechanisms simultaneously affecting behaviour and milk performance or due to a behaviour predisposition, which causes indirect effects on milk performance by influencing individual reactivity, needs further investigation.     

Losing the last feather: feather loss as an antipredator adaptation in birds

Birds often lose feathers during predation attempts, and thisability has evolved as a means of escape. Because predatorsare more likely to grab feathers on the rump and the back thanon the ventral side of an escaping bird, we predicted that theformer feathers would have evolved to be relatively looselyattached as an antipredator strategy in species that frequentlydie from predation. We estimated the force required to removefeathers from the rump, back, and breast by pulling featherswith a spring balance from a range of European bird speciesin an attempt to investigate ecological factors associated withease of feather loss during predation attempts. The force requiredto loosen a feather from the rump was less than that requiredto loosen a feather from back, which in turn was less than thatrequired to loosen a feather from the breast. The relative forceneeded to loosen rump feathers compared with feathers from theback and the breast was smaller for prey species preferred bythe most common predator of small passerine birds, the sparrowhawkAccipiter nisus. Likewise, the relative force was also smallerin species with a high frequency of complete tail loss amongfree-living birds, which we used as an index of the frequencyof failed predation attempts. The relative force required toremove feathers from the rump was smaller in species with ahigh frequency of fear screams, another measure of the relativeimportance of predation as a cause of death. Feather loss requiredparticularly little force among solitarily breeding bird speciesthat suffer the highest degree of predation. Antipredator defensein terms of force required to remove feathers from the rumpwas larger in species with a strong antiparasite defense interms of T-cell–mediated immune response. These findingsare consistent with the hypothesis that different defenses areantagonistic and that they are traded off against each other.     

A simulation approach for power calculation in large cohort studies based on multistate models

Realistic power calculations for large cohort studies and nested case control studies are essential for successfully answering important and complex research questions in epidemiology and clinical medicine. For this, we provide a methodical framework for general realistic power calculations via simulations that we put into practice by means of an R‐based template. We consider staggered recruitment and individual hazard rates, competing risks, interaction effects, and the misclassification of covariates. The study cohort is assembled with respect to given age‐, gender‐, and community distributions. Nested case‐control analyses with a varying number of controls enable comparisons of power with a full cohort analysis. Time‐to‐event generation under competing risks, including delayed study‐entry times, is realized on the basis of a six‐state Markov model. Incidence rates, prevalence of risk factors and prefixed hazard ratios allow for the assignment of age‐dependent transition rates given in the form of Cox models. These provide the basis for a central simulation‐algorithm, which is used for the generation of sample paths of the underlying time‐inhomogeneous Markov processes. With the inclusion of frailty terms into the Cox models the Markov property is specifically biased. An “individual Markov process given frailty” creates some unobserved heterogeneity between individuals. Different left‐truncation‐ and right‐censoring patterns call for the use of Cox models for data analysis. p‐values are recorded over repeated simulation runs to allow for the desired power calculations. For illustration, we consider scenarios with a “testing” character as well as realistic scenarios. This enables the validation of a correct implementation of theoretical concepts and concrete sample size recommendations against an actual epidemiological background, here given with possible substudy designs within the German National Cohort.