Heritability and social brood effects on personality in juvenile and adult life-history stages in a wild passerine.

How has evolution led to the variation in behavioural phenotypes (personalities) in a population? Knowledge of whether personality is heritable, and to what degree it is influenced by the social environment, is crucial to understanding its evolutionary significance, yet few estimates are available from natural populations. We tracked three behavioural traits during different life-history stages in a pedigreed population of wild house sparrows. Using a quantitative genetic approach, we demonstrated heritability in adult exploration, and in nestling activity after accounting for fixed effects, but not in adult boldness. We did not detect maternal effects on any traits, but we did detect a social brood effect on nestling activity. Boldness, exploration and nestling activity in this population did not form a behavioural syndrome, suggesting that selection could act independently on these behavioural traits in this species, although we found no consistent support for phenotypic selection on these traits. Our work shows that repeatable behaviours can vary in their heritability and that social context influences personality traits. Future efforts could separate whether personality traits differ in heritability because they have served specific functional roles in the evolution of the phenotype or because our concept of personality and the stability of behaviour needs to be revised.

Maternal effects and heritability of annual productivity.

Within-individual consistency and among-individual heterogeneity in fitness are prerequisites for selection to take place. Within-individual variation in productivity between years, however, can vary considerably, especially when organisms become older and more experienced. We examine individual consistency in annual productivity, the covariation between survival and annual productivity, and the sources of variation in annual productivity, while accounting for advancing age, to test the individual-quality and resource-allocation life-history theory hypotheses. We use long-term data from a pedigreed, wild population of house sparrows. Within-individual annual productivity first increased and later decreased with age, but there were no selective mortality due to individual quality and no correlation between lifespan and productivity. Individuals were consistent in their annual productivity (C = 0.49). Narrow-sense heritability was low (h(2) = 0.09), but maternal effects explained much of the variation (M = 0.33). Such effects can influence evolutionary processes and are of major importance for our understanding of how variation in fitness can be maintained.

Nonperturbative heavy-quark diffusion in the quark-gluon plasma.

We evaluate heavy-quark (HQ) transport properties in a quark-gluon plasma (QGP) within a Brueckner many-body scheme employing interaction potentials extracted from thermal lattice QCD. The in-medium T matrices for elastic charm- and bottom-quark scattering off light quarks in the QGP are dominated by attractive meson and diquark channels which support resonance states up to temperatures of ~1.5T(c). The resulting drag coefficient increases with decreasing temperature, contrary to expectations based on perturbative QCD scattering. Employing relativistic Langevin simulations we compute HQ spectra and elliptic flow in sqrt[s(NN)]=200 GeV Au-Au collisions. A good agreement with electron decay data supports our nonperturbative computation of HQ diffusion, indicative for a strongly coupled QGP.

An objective, rapid and reproducible method for scoring AFLP peak-height data that minimizes genotyping error.

Amplified fragment length polymorphism (AFLP) fingerprint data are now commonly collected using DNA sequencers. AFLP genotypes are still often scored by eye from such data - a time-consuming, error-prone and subjective process. We present a semi-automated method of genotyping sequencer-collected AFLPs at predefined fragment locations (loci) within the fingerprint. Our method uses thresholds of AFLP-polymerase chain reaction-product fluorescence intensity (peak height) in order to: (i) exclude AFLP loci that are likely to contribute high rates of error to data sets, and (ii) determine the AFLP phenotype (fragment presence or absence) at the retained loci. Error rate analysis is an integral part of this process and is used to determine optimal thresholds that minimize genotyping error, while maximizing the numbers of retained loci. We show that application of this method to a large AFLP data set allows genotype calls that are rapid, objective and repeatable, facilitating the extraction of reliable genotype data for molecular ecological studies.

A high-throughput protocol for extracting high-purity genomic DNA from plants and animals.

DNA extraction techniques that employ the reversible binding of DNA to silica via chaotropic salts can deliver high-quality genomic DNA from plant and animal tissues, while avoiding the use of toxic organic solvents. Existing techniques that use this method are either prohibitively expensive, or are applicable to only a restricted set of taxa. Here we describe a cost-effective DNA extraction technique suitable for a wide range of plant and animal taxa that yields microgram quantities of high-molecular-weight genomic DNA at a throughput of 192 samples per day. Our technique is particularly robust for tissue samples that are insoluble or are rapidly discoloured or oxidized in standard DNA extraction buffers. We demonstrate the quality of DNA extracted using this method by applying the amplified fragment length polymorphism technique to plant species.

Diluted neural networks with adapting and correlated synapses.

We consider the dynamics of diluted neural networks with clipped and adapting synapses. Unlike previous studies, the learning rate is kept constant as the connectivity tends to infinity: the synapses evolve on a time scale intermediate between the quenched and annealing limits and all orders of synaptic correlations must be taken into account. The dynamics is solved by mean-field theory, the order parameter for synapses being a function. We describe the effects, in the double dynamics, due to synaptic correlations.

Chaos in neural networks with a nonmonotonic transfer function.

Time evolution of diluted neural networks with a nonmonotonic transfer function is analytically described by flow equations for macroscopic variables. The macroscopic dynamics shows a rich variety of behaviors: fixed-point, periodicity, and chaos. We examine in detail the structure of the strange attractor and in particular we study the main features of the stable and unstable manifolds, the hyperbolicity of the attractor, and the existence of homoclinic intersections. We also discuss the problem of the robustness of the chaos and we prove that in the present model chaotic behavior is fragile (chaotic regions are densely intercalated with periodicity windows), according to a recently discussed conjecture. Finally we perform an analysis of the microscopic behavior and in particular we examine the occurrence of damage spreading by studying the time evolution of two almost identical initial configurations. We show that for any choice of the parameters the two initial states remain microscopically distinct.