Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models

Determinants of local and migratory movements of Great Lakes double-crested cormorants

We investigated how individual strategies combine with demographic and ecological factors to determine local and migratory movements in the double-crested cormorants (Phalacrocorax auritus). One hundred and forty-five cormorants were captured from 14 nesting colonies across the Great Lakes area and fitted with satellite transmitters. We first tested the hypotheses that sexual segregation, density-dependent effects, and the intensity of management operations influenced home range size during the breeding season. The influence of these factors appeared to be limited in part due to random variability in foraging and dispersal decisions at individual and colony levels. We also designed a statistical framework to investigate the degree and determinants of migratory connectivity. Our analyses revealed a significant migratory connectivity in cormorants, although we also observed a nonnegligible amount of individual variability and flexibility. Our data were most consistent with the existence of a migratory divide across the Great Lakes, with western populations using mainly the Mississippi Flyway and eastern populations the Atlantic Flyway. Previous and current studies suggest that the divide cannot be explained by past divergence in isolation, a way to diminish travel cost, or the Appalachians constituting an ecological barrier per se but is rather the consequence of the distribution of suitable stopover and nonbreeding areas. However, a parallel migration system and no migratory divide could not be entirely ruled out with present data.

Limited ecological connectivity of an arboreal marsupial across a forest/plantation landscape despite apparent resilience to fragmentation

Demographic and genetic replenishment of populations through the exchange of individuals is essential for their persistence. Habitat loss and fragmentation can reduce the permeability of landscapes, hinder dispersal and compromise the genetic integrity of populations over time. We examined ecological connectivity in an arboreal marsupial, the common ringtail possum (Pseudocheirus peregrinus) in fragmented forests of southeastern Australia. This species is potentially robust to fragmentation based on its presence in degraded landscapes and known use of plantations for foraging and nesting. Using 312 individuals screened at 15 microsatellites, we measured dispersal and gene flow across seven native Eucalyptus forest remnants surrounded by exotic Pinus radiata plantations and three sites within a large continuous forest. The permeability of the pine matrix to dispersing possums was significantly lower than that of the native forest. Small, isolated patches exhibited signatures of genetic drift, having lower heterozygosity and allelic richness than possums in large patches. Most (87%) possums were born in their sampled patch or dispersed only short distances into neighbouring remnants. The continuous forest was identified as an important source of immigrants only for proximate patches (within 2.5 km), thus emphasizing for the common ringtail possum and more specialized arboreal mammals the need to conserve large, proximate forest remnants. Our findings highlight the importance of using genetic tools to understand the long-term biological consequences of fragmentation for effective management.

Identification of a gene associated with avian migratory behaviour

Bird migration is one of the most spectacular and best-studied phenomena in behavioural biology. Yet, while the patterns of variation in migratory behaviour and its ecological causes have been intensively studied, its genetic, physiological and neurological control remains poorly understood. The lack of knowledge of the molecular basis of migration is currently not only limiting our insight into the proximate control of migration, but also into its evolution. We investigated polymorphisms in the exons of six candidate genes for key behavioural traits potentially linked to migration, which had previously been identified in several bird species, and eight control loci in 14 populations of blackcaps (Sylvia atricapilla), representing the whole range of geographical variation in migration patterns found in this species, with the aim of identifying genes controlling variation in migration. We found a consistent association between a microsatellite polymorphism and migratory behaviour only at one candidate locus: the ADCYAP1 gene. This polymorphism explained about 2.6 per cent of the variation in migratory tendency among populations, and 2.7–3.5% of variation in migratory restlessness among individuals within two independent populations. In all tests, longer alleles were associated with higher migratory activity. The consistency of results among different populations and levels of analysis suggests that ADCYAP1 is one of the genes controlling the expression of migratory behaviour. Moreover, the multiple described functions of the gene product indicate that this gene might act at multiple levels modifying the shift between migratory and non-migratory states.

Quantification of leukocyte genomic 5-methylcytosine levels reveals epigenetic plasticity in healthy adult cloned cattle

Successful somatic cell nuclear transfer (SCNT) requires epigenetic reprogramming of a differentiated donor cell nucleus. Incorrect reprogramming of epigenetic markings such as DNA methylation is associated with compromised prenatal development and postnatal abnormalities. Clones that survive into adulthood, in contrast, are assumed to possess a normalized epigenome corresponding to their normal phenotype. To address this point, we used capillary electrophoresis to measure 5-methylcytosine (5mC) levels in leukocyte DNA of 38 healthy female bovine clones that represented five genotypes from the Simmental breed and four genotypes from the Holstein breed. The estimated variance in 5mC level within clone genotypes of both breeds [0.104, 95% confidence interval (CI): 0.070-0.168] was higher than between clone genotypes (0, CI: 0-0.047). We quantified the contribution of SCNT to this unexpected variability by comparing the 19 Simmental clones with 12 female Simmental monozygotic twin pairs of similar age. In Simmental clones, the estimated variability within genotype (0.0636, CI: 0.0358-0.127) was clearly higher than in twin pairs (0.0091, CI: 0.0047-0.0229). In clones, variability within genotype (0.0636) was again higher than between genotypes (0, CI: 0-0.077). Twins, in contrast, showed lower variability within genotypes (0.0091) than between genotypes (0.0136, CI: 0.00250-0.0428). Importantly, the absolute deviations of 5mC values of individual SCNT clones from their genotype means were fivefold increased in comparison to twins. Further comparisons with noncloned controls revealed DNA hypermethylation in most of the clones. The clone-specific variability in DNA methylation and DNA hypermethylation clearly show that healthy adult SCNT clones must be considered as epigenome variants.

On the behaviour of marginal and conditional AIC in linear mixed models

In linear mixed models, model selection frequently includes the selection of random effects. Two versions of the Akaike information criterion, aic, have been used, based either on the marginal or on the conditional distribution. We show that the marginal aic is not an asymptotically unbiased estimator of the Akaike information, and favours smaller models without random effects. For the conditional aic, we show that ignoring estimation uncertainty in the random effects covariance matrix, as is common practice, induces a bias that can lead to the selection of any random effect not predicted to be exactly zero. We derive an analytic representation of a corrected version of the conditional aic, which avoids the high computational cost and imprecision of available numerical approximations. An implementation in an R package (R Development Core Team, 2010) is provided. All theoretical results are illustrated in simulation studies, and their impact in practice is investigated in an analysis of childhood malnutrition in Zambia.

Incongruent fitness landscapes, not tradeoffs, dominate the adaptation of vesicular stomatitis virus to novel host types

Host radiation refers to the ability of parasites to adapt to new environments and expand or change their niches. Adaptation to one specific environment may involve a loss in adaptation to a second environment. Thus, fitness costs may impose limits to niche expansion and constitute the cost of specialization. Several reports have addressed the cost of host radiation in vesicular stomatitis virus (VSV), but in some cases the experimental setup may have resulted in the overestimation of fitness costs. To clarify this issue, experiments were carried out in which a reference strain of VSV was allowed to adapt to HeLa, MDCK and BHK-21 cells, and to a regime of alternation between HeLa and Madin–Darby canine kidney (MDCK) cells. Measurement of viral fitness on each cell type showed that most virus populations behaved as generalists, and increased in fitness in all environments. Tradeoffs, where a fitness increase in one environment led to a fitness decrease in another environment, were rare. These results highlight the importance of using appropriate methods to measure fitness in evolved virus populations, and provide further support to a model of evolutionary dynamics in which costs due to incongruent landscapes provided by different environments are more common than tradeoffs.

Generalized linear mixed models: a practical guide for ecology and evolution

How should ecologists and evolutionary biologists analyze nonnormal data that involve random effects? Nonnormal data such as counts or proportions often defy classical statistical procedures. Generalized linear mixed models (GLMMs) provide a more flexible approach for analyzing nonnormal data when random effects are present. The explosion of research on GLMMs in the last decade has generated considerable uncertainty for practitioners in ecology and evolution. Despite the availability of accurate techniques for estimating GLMM parameters in simple cases, complex GLMMs are challenging to fit and statistical inference such as hypothesis testing remains difficult. We review the use (and misuse) of GLMMs in ecology and evolution, discuss estimation and inference and summarize 'best-practice' data analysis procedures for scientists facing this challenge.