The effect of metapopulation processes on the spatial scale of adaptation across an environmental gradient

We show that the butterfly Aricia agestis (Lycaenidae) is adapted to its thermal environment in via integer changes in the numbers of generations per year (voltinism): it has two generations per year in warm habitats and one generation per year in cool habitats in north Wales (UK). Voltinism is an “adaptive peak” since individuals having an intermediate number of generations per year would fail to survive the winter, and indeed no populations showed both voltinism types in nature. In spite of this general pattern, 11% of populations apparently possess the “wrong” voltinism for their local environment, and population densities were lower in thermally intermediate habitat patches. Population dynamic data and patterns of genetic differentiation suggest that adaptation occurs at the metapopulation level, with local populations possessing the voltinism type appropriate for the commonest habitat type within each population network. When populations and groups of populations go extinct, they tend to be replaced by colonists from the commonest thermal environment nearby, even if this is the locally incorrect adaptation. Our results illustrate how stochastic population turnover can impose a limit on local adaptation over distances many times larger than predicted on the basis of normal dispersal movements

Travelling waves for a non-monotone bistable equation with delay: existence and oscillations

We consider a bistable (0\textless{}\theta\textless{}1 being the three constant steady states) delayed reaction diffusion equation, which serves as a model in population dynamics. The problem does not admit any comparison principle. This prevents the use of classical technics and, as a consequence, it is far from obvious to understand the behaviour of a possible travelling wave in $+\infty$. Combining refined {\it a priori} estimates and a Leray Schauder topological degree argument, we construct a travelling wave connecting 0 in $-\infty$ to \lq\lq something" which is strictly above the unstable equilibrium $\theta$ in $+\infty$. Furthemore, we present situations (additional bound on the nonlinearity or small delay) where the wave converges to 1 in $+\infty$, whereas the wave is shown to oscillate around 1 in $+\infty$ when, typically, the delay is large

PATHWAY DETECTION AND GEOMETRICAL DESCRIPTION FROM ALS DATA IN FORESTED MOUNTANEOUS AREA

International audienceIn the last decade, airborne laser scanning (ALS) systems have become an alternative source for the acquisition of altimeter data. Compared to high resolution orthoimages, one of the main advantages of ALS is the ability of the laser beam to penetrate vegetation and reach the ground underneath. Therefore, 3D point clouds are essential data for computing Digital Terrain Models (DTM) in natural and vegetated areas. DTMs are a key product for many applications such as tree detection, flood modelling, archeology or road detection. Indeed, in forested areas, traditional image-based algorithms for road and pathway detection would partially fail due to their occlusion by the canopy cover. Thus, crucial information for forest management and fire prevention such as road width and slope would be misevaluated. This paper deals with road and pathway detection in a complex forested mountaneous area and with their geometrical parameter extraction using lidar data. Firstly, a three-step image-based methodology is proposed to detect road regions. Lidar feature orthoimages are first generated. Then, road seeds are both automatically and semi-automatically detected. And, a region growing algorithm is carried out to retrieve the full pathways from the seeds previously detected. Secondly, these pathways are vectorized using morphological tools, smoothed, and discretized. Finally, 1D sections within the lidar point cloud are successively generated for each point of the pathways to estimate more accurately road widths in 3D. We also retrieve a precise location of the pathway borders and centers, exported as vector data

Low statistical power in biomedical science:a review of three human research domains

Studies with low statistical power increase the likelihood that a statistically significant finding represents a false positive result. We conducted a review of meta-analyses of studies investigating the association of biological, environmental or cognitive parameters with neurological, psychiatric and somatic diseases, excluding treatment studies, in order to estimate the average statistical power across these domains. Taking the effect size indicated by a meta-analysis as the best estimate of the likely true effect size, and assuming a threshold for declaring statistical significance of 5%, we found that approximately 50% of studies have statistical power in the 0–10% or 11–20% range, well below the minimum of 80% that is often considered conventional. Studies with low statistical power appear to be common in the biomedical sciences, at least in the specific subject areas captured by our search strategy. However, we also observe evidence that this depends in part on research methodology, with candidate gene studies showing very low average power and studies using cognitive/behavioural measures showing high average power. This warrants further investigation

Replication Validity of Initial Association Studies:A Comparison between Psychiatry, Neurology and Four Somatic Diseases

CONTEXT:There are growing concerns about effect size inflation and replication validity of association studies, but few observational investigations have explored the extent of these problems. OBJECTIVE:Using meta-analyses to measure the reliability of initial studies and explore whether this varies across biomedical domains and study types (cognitive/behavioral, brain imaging, genetic and "others"). METHODS:We analyzed 663 meta-analyses describing associations between markers or risk factors and 12 pathologies within three biomedical domains (psychiatry, neurology and four somatic diseases). We collected the effect size, sample size, publication year and Impact Factor of initial studies, largest studies (i.e., with the largest sample size) and the corresponding meta-analyses. Initial studies were considered as replicated if they were in nominal agreement with meta-analyses and if their effect size inflation was below 100%. RESULTS:Nominal agreement between initial studies and meta-analyses regarding the presence of a significant effect was not better than chance in psychiatry, whereas it was somewhat better in neurology and somatic diseases. Whereas effect sizes reported by largest studies and meta-analyses were similar, most of those reported by initial studies were inflated. Among the 256 initial studies reporting a significant effect (p<0.05) and paired with significant meta-analyses, 97 effect sizes were inflated by more than 100%. Nominal agreement and effect size inflation varied with the biomedical domain and study type. Indeed, the replication rate of initial studies reporting a significant effect ranged from 6.3% for genetic studies in psychiatry to 86.4% for cognitive/behavioral studies. Comparison between eight subgroups shows that replication rate decreases with sample size and "true" effect size. We observed no evidence of association between replication rate and publication year or Impact Factor. CONCLUSION:The differences in reliability between biological psychiatry, neurology and somatic diseases suggest that there is room for improvement, at least in some subdomains

Species abundance patterns in an ecosystem simulation studied through Fisher's logseries

We have developed an individual-based evolving predator-prey ecosystem simulation that integrates, for the first time, a complex individual behaviour model, an evolutionary mechanism and a speciation process, at an acceptable computational cost. In this article, we analyse the species abundance patterns observed in the communities generated by our simulation, based on Fisher's logseries. We propose a rigorous methodology for testing abundance data against the logseries. We show that our simulation produces coherent results, in terms of relative species abundance, when compared to classical ecological patterns. Some preliminary results are also provided about how our simulation is supporting ecological field results

A Review of Controlling Motivational Strategies from a Self-Determination Theory Perspective: Implications for Sports Coaches

The aim of this paper is to present a preliminary taxonomy of six controlling strategies, primarily based on the parental and educational literatures, which we believe are employed by coaches in sport contexts. Research in the sport and physical education literature has primarily focused on coaches’ autonomysupportive behaviours. Surprisingly, there has been very little research on the use of controlling strategies. A brief overview of the research which delineates each proposed strategy is presented, as are examples of the potential manifestation of the behaviours associated with each strategy in the context of sports coaching. In line with self-determination theory (Deci & Ryan, 1985; Ryan & Deci, 2002), we propose that coach behaviours employed to pressure or control athletes have the potential to thwart athletes’ feelings of autonomy, competence,and relatedness, which, in turn, undermine athletes’ self-determined motivation and contribute to the development of controlled motives. When athletes feel pressured to behave in a certain way, a variety of negative consequences are expected to ensue which are to the detriment of the athletes’ well-being. The purpose of this paper is to raise awareness and interest in the darker side of sport participation and to offer suggestions for future research in this area