Pheomelanin-based colouration is correlated with indices of flying strategies in the barn owl

Resource polymorphism refers to individuals from the same population foraging in alternative habitats or on alternative food. Food specialization can be associated with adaptations such as colour polymorphism, with pale and dark colours conferring differential camouflage in different habitats. Pale and dark-reddish pheomelanic Barn Owls (Tyto alba) forage on different prey species in closed and open habitats, respectively. We show here that darker-reddish owls have heavier stomach content when found dead, and their 5th secondary wing feather is more deeply anchored inside the integument. These correlations suggest that their feathers bend less when flying, and that darker-reddish Barn Owls are able sustain more intense flying than their paler conspecifics.

BME-based uncertainty assessment of the Chernobyl fallout

The vast territories that have been radioactively contaminated during the 1986 Chernobyl accident provide a substantial data set of radioactive monitoring data, which can be used for the verification and testing of the different spatial estimation (prediction) methods involved in risk assessment studies. Using the Chernobyl data set for such a purpose is motivated by its heterogeneous spatial structure (the data are characterized by large-scale correlations, short-scale variability, spotty features, etc.). The present work is concerned with the application of the Bayesian Maximum Entropy (BME) method to estimate the extent and the magnitude of the radioactive soil contamination by 137Cs due to the Chernobyl fallout. The powerful BME method allows rigorous incorporation of a wide variety of knowledge bases into the spatial estimation procedure leading to informative contamination maps. Exact measurements (?hard? data) are combined with secondary information on local uncertainties (treated as ?soft? data) to generate science-based uncertainty assessment of soil contamination estimates at unsampled locations. BME describes uncertainty in terms of the posterior probability distributions generated across space, whereas no assumption about the underlying distribution is made and non-linear estimators are automatically incorporated. Traditional estimation variances based on the assumption of an underlying Gaussian distribution (analogous, e.g., to the kriging variance) can be derived as a special case of the BME uncertainty analysis. The BME estimates obtained using hard and soft data are compared with the BME estimates obtained using only hard data. The comparison involves both the accuracy of the estimation maps using the exact data and the assessment of the associated uncertainty using repeated measurements. Furthermore, a comparison of the spatial estimation accuracy obtained by the two methods was carried out using a validation data set of hard data. Finally, a separate uncertainty analysis was conducted that evaluated the ability of the posterior probabilities to reproduce the distribution of the raw repeated measurements available in certain populated sites. The analysis provides an illustration of the improvement in mapping accuracy obtained by adding soft data to the existing hard data and, in general, demonstrates that the BME method performs well both in terms of estimation accuracy as well as in terms estimation error assessment, which are both useful features for the Chernobyl fallout study.

VOLUMES RELIES du Cabinet des titres : recherches de noblesse, armoriaux, preuves, histoires généalogiques. « Trésor d'armes généalogique ».

Recueil de blasons gravés, rangés par ordre alphabétique : Alleman-Walpergue, donné par J.-P. de Montchal à Pierre d'Hozier, en 1651.