156 research outputs found
Atelier scientifique du projet européen "Bee Research And Virology in Europe" (B.R.A.V.E.)
No full textColloque organisé par Michel Aubert du 2 au 7 septembre 2005 Participants Michel Aubert, Brenda Ball, Mark Brown, Mike Carter, Joachim De Miranda, Ingemar Fries, Elke Genersch, Rosie Hails, Jean-Luc Imler, Norberto Milani, Robin F.A. Moritz, Magali Ribière Compte-rendu L’atelier « BRAVE » (Bee Reseach And Virus in Europe) tenu aux Treilles faisait suite à une réunion scientifique plus large qui avait été organisée par le laboratoire de l’Afssa-Sophia-Antipolis du 24 au 26 avril 2005. Cette pr..
Population dynamics of the Cape bee phenomenon: The impact of parasitic laying worker clones in apiaries and natural populations
No full textA population ecological host- parasite model is used to evaluate the potential impact of clonal parasitic laying workers of the Cape honeybee, Apis mellifera capensis on populations of Apis mellifera scutellata host colonies in apiaries and in the wild. The model includes three basic life history parameters: reproductive rate of the host colonies, transmission efficiency of the parasite and the death rate of parasitised colonies. The population dynamics of host and parasites are computed for 100 generations after an initial infestation with parasitic workers. The model reveals that infestations are likely to be fatal for apiary populations irrespective of beekeeping activities compensating for colony losses due to parasitation. Wild A. m. scutellata populations are however less likely to be affected by parasitic laying workers and stable equilibria between host and parasite occur over a wide range of the parameter space. Although it is unlikely that the parasitic clone represents a threat to the conservation of biodiversity, even low frequencies of parasitic A. m. capensis workers in wild honeybee population can cause a permanent threat to beekeeping activities
Alternating Maximization with Behavioral Cloning
No full textThe key difficulty of cooperative, decentralized planning lies in making accurate predictions about the behavior of one’s teammates. In this paper we introduce a planning method of Alternating maximization with Behavioural Cloning (ABC) – a trainable online decentralized planning algorithm based on Monte Carlo Tree Search (MCTS), combined with models of teammates learned from previous episodic runs. Our algorithm relies on the idea of alternating maximization, where agents adapt their models one at a time in round-robin manner. Under the assumption of perfect policy cloning, and with a sufficient amount of Monte Carlo samples, successive iterations of our method are guaranteed to improve joint policies, and eventually converge.Interactive Intelligenc
QTL-mapping of individual resistance against American foulbrood in haploid honeybee drone larvae (Apis mellifera)
No full textAmerican foulbrood (AFB) is a severe brood disease in honeybees. Since sustainable
treatment is not available, selection of genetically resistant honeybee stock is highly desirable. Using a
set of 291 heterozygous microsatellite markers in a bulk segregant analysis with subsequent finemapping
of haploid drone offspring from a single honeybee queen, we identified one significant and three
suggestive quantitative trait loci as well as one significant epistatic interaction influencing prepupal
survival after AFB infection. While we were not able to verify specific genes responsible for tolerance,
we suggest that developmental genes may have played an important role. The identified markers can be
used as regions of interest in future mapping or expression studies. In order to use them for markerassisted
selection in breeding programmes for AFB-resistant honeybee stock, it will be required to
evaluate these loci more extensively under variable experimental conditions.European Commission through the 6th framework collaborative Specific Targeted
Research Project BEE SHOP (Bees in Europe and Sustainable Honey Production; EU
contract number: FOOD-CT-2006-022568) and by the German Ministry for Education
and Science (BMBF) through the FUGATO-plus project FUGAPIS (Functional genome
analysis of disease resistance in honeybees, Apis mellifera; project number: 0315125A).http://link.springer.com/journal/135922015-07-31hb201
Organization of honeybee colonies: characteristics and consequences of a superorganism concept
No full textThe colonial organization of honeybees reveals numerous analogies to multicellular organisms which makes it tempting to use the term superorganism. The sterile workers fulfill the role of the somatic cells in organisms with intricate and complex interactions. These interactions are under partial control of hierarchical signals (pheromones) which are primarily used for global information of the colony. The majority of the activities in the colony is, however, regulated through local decision making and through self-organized processes which are regulated through worker threshold response variability. In honeybees this is enhanced through the highly polyandrous mating system which allows for wide genotypic variance and the presence of genetic specialists. Although both individual and colony level selection can be observed in honeybees the latter seems to be the predominant selective force. This is similar to organismic selection where selection among or within cells is less relevant to evolutionary processes than fitness at the organismic level. © Inra/DIB/AGIB/Elsevier, Pari
Organization of honeybee colonies: characteristics and consequences of a superorganism concept
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