Affichage des résultats 741 à 760 sur 1231 au total
Systematics is the study of characters distribution and evolution among species. Recent advances in molecular biology and genomics provide systematists with a tremendous amount of characters never previously attained by morphology alone. Despite its limitations, I argue here that morphology would continue to be fundamental to the systematic practice and that the genomic revolution would result in a renaissance in the conceptualization and homologization of morphological data. I will mainly focus on two taxonomic programs, namely DNA barcoding and phylogeny inference, and try to place morphological systematics within the broader frame of the Extended Evolutionary Synthesis.
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Animal conflict is usually seen as static, where each competitor has a definite underlying quality (i.e. condition, good genes) that determines its signal level. However, although many morphological signals are fixed during early development, some signals remain flexible through life (e.g. vocalisation, most behavioural traits). The level of signals of an individual can thus often fluctuate to avoid interferences, to adapt to both the presence of an audience or the resource holding potential and motivation of opponents. These fluctuations raise the question of how individuals decide at each moment their level of investment in signalling to claim a resource. Animals are indeed expected to constantly modulate their investment in a contest according to the payoff. Because of the inherent difficulty to study the temporal dynamics of communication between several individuals, how animals decide to enter or leave the contest and to what level invest in signalling has received mainly theoretical developments. Using the barn owl (Tyto alba) as a model species, I will present recent advances in the understanding of the role of cognition (individual recognition, memory) and social interactions in the dynamics of a communication process.
Mathematical and computational approaches based on network theory and complex system dynamics are increasingly showing their potential to address open problems on the spreading of communicable diseases on a spatially structured and heterogeneous human population. I will review my recent research work in this direction presenting studies on both fundamental problems and specific epidemic events. On the theoretical side, I will show how the mathematical formalism of reaction-diffusion processes and metapopulation networks can shed light on the impact of the complex features characterising individuals' mobility patterns on the propagation of emerging infections. How do traveling flows, journey duration and difference in travel frequency impact local mixing and transmission of influenza-like diseases? How do the mobility of individuals and their distribution in space determine dominance/co-dominance regimes in case of multiple interacting strains of the same pathogen? Besides these fundamental research questions, the same formalism can form the basis of data-driven computational models for the spatial spreading of real infection events. In case of an epidemic emergency, such models represent valuable tools for estimating in real time the transmission potential of the disease, providing assessment of the epidemic situation and projections of possible unfolding scenarios. I will discuss the two paradigmatic examples of the 2009 H1N1 pandemic and of the MERS-CoV outbreak.
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Chemical risk assessment is, to date, predominantly focussed on “single species – single compound” toxicity testing of short-lived species. This approach cannot practically be used to assess all possible wildlife-pollutant combinations, and particularly falls short when assessing risk for species with life histories that do not suit laboratory experimentation. Long-lived species such as sea turtles and crocodiles are one example. In this seminar, we will present ongoing work on the exposure and accumulation of organic pollutants in sea turtles and crocodiles, and the application of computer models that integrate ecology, physiology and ecotoxicology as a basis for risk assessment for such long-lived species.
The distributions of the Trans-Himalayan large herbivores are fragmented, engendering a spatial heterogeneity in their species-richness. We capitalised on this natural-experiment situation to understand the niche dynamics of herbivores in relation to the number of sympatric species. We used the blue sheep Pseudois nayaur, a relatively widely distributed mountain ungulate, as a model species to address the issue. We selected three discrete valleys in three protected areas with almost similar environmental features but varying wild ungulate species richness, and studied the species' diet and habitat utilization in them. Habitat variables were observed in the field and microhistological faecal analysis was carried out to determine the habitat and diet widths of the animal in the three areas with different ungulate species richness. The habitat- and diet-niche widths were determined using the Shannon's H' Index. The results showed that habitat width of blue sheep has a negative relationship with the number of sympatric species. However, contrary to our expectation, there was a hump-shaped relationship between blue sheep's diet width and the sympatric species richness, with the diet width being narrower in areas of allopatry as well as in areas with greater number of sympatric species, and the widest diet spectrum in areas with moderate species richness. We suspect that the narrow diet width in allopatry is out of choice, while it is out of necessity in areas with greater number of sympatric species due to resource partitioning. We suggest that interactions with sympatric species lead to niche adjustment of mountain ungulates, and underscore the importance of including biotic interactions in species distribution models, which have often been neglected.
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Animals often show substantial variation in dispersal behaviour and resident individuals are more likely to inbreed. At least part of the variation in dispersal behaviour may be phenotype-dependent, potentially leading to non-random inbreeding with respect to a particular phenotype. Here we show that non-random inbreeding in structured populations can have important implications for estimates of the effect of inbreeding (inbreeding depression). We do this using a long-term individual-based data set for a population of Eurasian dippers (Cinclus cinclus), a bird species living exclusively along streams and rivers. Extensive pedigree data show that close inbreeding is relatively common in this species. However, inbreeding birds are not a random subsample of the population but are smaller on average. Given the significant heritability of body size, inbred individuals are smaller due to both additive genetic and inbreeding effects. Importantly, the effects of inbreeding are overestimated if additive genetic effects are not accounted for. We show how estimating the effects of inbreeding within an animal model framework removes this bias, highlighting the importance of integrating quantitative genetics and animal behaviour when measuring the effects of inbreeding in the wild.
Deux équipes présentent des résultats ou des questions qui leurs sont propres afin de favoriser de nouvelles discussions au sein du laboratoire.
Deux équipes présentent des résultats ou des questions qui leurs sont propres afin de favoriser de nouvelles discussions au sein du laboratoire.
Deux équipes présentent des résultats ou des questions qui leurs sont propres afin de favoriser de nouvelles discussions au sein du laboratoire.«Telling metabolic stories to explore metabolomics data: A case study on the Yeast response to cadmium exposure» Cecilia Coimbra Klein et«Sénescence et sélection sexuelle chez les populations naturelles de vertébrés» Jean-Francois Lemaitre
Deux équipes présentent des résultats ou des questions qui leurs sont propres afin de favoriser de nouvelles discussions au sein du laboratoire.
Deux équipes présentent des résultats ou des questions qui leurs sont propres afin de favoriser de nouvelles discussions au sein du laboratoire.
Deux équipes présentent des résultats ou des questions qui leurs sont propres afin de favoriser de nouvelles discussions au sein du laboratoire.
Papers evaluating measures of explained variation, or similar indices, invariably use independence from censoring as the most important criterion. And they invariably end up suggesting that some measures meet this criterion, and some don't, leading to a conclusion that the first are better than the second. As a consequence, users are offered measures that cannot be used with time-dependant covariates and effects, not to mention extensions to repeated events or multi state models. We explain in this paper that the above mentioned criterion is of no use in studying such measures, since it simply favours those that make an implicit assumption of a model being valid everywhere. Measures not making such an assumption are disqualified, even though they are better in every other respect. We show that if these, allegedly inferior, measures are allowed to make the same assumption, they are easily corrected to satisfy the `independent-from-censoring' criterion. Even better, it is enough to make such an assumption only for the times greater than the last observed failure time $tau$. Which, in contrast with the `preferred' measures, makes it possible to use all the modelling flexibility up-to $tau$, and assume whatever one wants after $tau$. As a consequence, we claim that measures being proffered as better in the existing reviews, are exactly those that are inferior