cefe.cnrs-mop.fr Under natural selection, individuals tend to adapt to their local environmental conditions, resulting in a pattern of LOCAL ADAPTATION (see Glossary). Local adaptation can occur if the direction of selection changes for an allele among habitats (antagonistic environmental effect), but it might also occur if the intensity of selection at several loci that are maintained as polym...

Divergent natural selection promotes local adaptation and can lead to reproductive isolation of populations in contrasting environments; however, the genetic basis of local adaptation remains largely unresolved in natural populations. Local adaptation might result from antagonistic pleiotropy, where alternate alleles are favoured in distinct habitats, and polymorphism is maintained by selection...

Evolutionary theory suggests that divergent natural selection in heterogeneous environments can result in locally adapted plant genotypes. To understand local adaptation it is important to study the ecological factors responsible for divergent selection. At a continental scale, variation in climate can be important while at a local scale soil properties could also play a role. We designed an ex...

The extent to which parasites are locally adapted to their hosts has important implications for human health and agriculture. A recently developed conceptual framework--the geographic mosaic theory of coevolution--predicts that local maladaptation should be common and largely determined by the interplay between gene flow and spatially variable reciprocal selection. Previous investigation of thi...

Coevolution is one of the major processes organizing the earth's biodiversity, but it remains unclear when and how it may generate species diversity. The study by Parchman et al. () in this issue of Molecular Ecology provides the clearest evidence to date that divergent local adaptation in a coevolving interaction may lead to speciation on one side of an interaction but not necessarily on the o...

Gain adaptation algorithms for neural networks typically adjust learning rates by monitoring the correlation between successive gradients. Here we discuss the limitations of this approach, and develop an alternative by extending Sutton’s work on linear systems to the general, nonlinear case. The resulting online algorithms are computationally little more expensive than other acceleration techni...

Department of Biology, Washington University, St. Louis, Missouri (A. R. I), institute of Zoology, Johannes Gutenberg University, Mainz, Federal Republic of Germany (ti. H.), Zoological Society of London, London, England (G. M.), Minnesota Zoological Gardens, Apple Valley (U.S.S.), Department of Environmental and Forest Biology, State University of New York, Syracuse (W M.S.), and Department of...

Populations of widely distributed species encounter and must adapt to local environmental conditions. However, comprehensive characterization of the genetic basis of adaptation is demanding, requiring genome-wide genotype data, multiple sampled populations, and an understanding of population structure and potential selection pressures. Here, we used single-nucleotide polymorphism genotyping and...

Prolonged exposure to an oriented line shifts the perceived orientation of a subsequently observed line in the opposite direction, a phenomenon known as the tilt aftereffect (TAE). Here we consider whether the TAE for line stimuli is mediated by a mechanism that integrates the local parts of the line into a single global entity prior to the site of adaptation, or the result of the sum of local ...

The k–Nearest Neighbor algorithm (k-NN) uses a classification criterion that depends on the parameter k. Usually, the value of this parameter must be determined by the user. In this paper we present an algorithm based on the NN technique that does not take the value of k from the user. Our approach evaluates values of k that classified the training examples correctly and takes which classified ...