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Second Prediction (second + prediction)
Selected AbstractsWhat shapes Eurasian lynx distribution in human dominated landscapes: selecting prey or avoiding people?ECOGRAPHY, Issue 4 2009Mathieu Basille In the multi-use landscape of southern Norway, the distribution of lynx is likely to be determined both by the abundance of their favoured prey , the roe deer , and the risk associated with the presence of humans because most lynx mortalities are caused by humans (recreational harvest, poaching, vehicle collisions). We described the distribution of the reproductive portion of the lynx population based on snow-track observations of females with dependent kittens collected over 10,yr (1997,2006) in southern Norway. We used the ecological-niche factor analysis to examine how lynx distribution was influenced by roe deer, human activity, habitat type, environmental productivity and elevation. Our first prediction that lynx should be found in areas of relatively high roe deer abundance was supported. However, our second prediction that lynx should avoid human activity was rejected, and lynx instead occupied areas more disturbed in average than those available (with the exception of the most densely occupied areas). Lynx, however, avoided the most disturbed areas and our third prediction of a trade-off between abundance of prey and avoidance of human activity was supported. On the one hand, roe deer in the most disturbed areas benefit to a large extent from current human land use practices, potentially allowing them to escape predation from lynx. On the other hand, the situation is not so favourable for the predators who are restricted in competition refuges with medium to low prey densities. The consequence is that lynx conservation will have to be achieved in a human modifed environment where the potential for a range of conflicts and high human-caused mortality will remain a constant threat. [source] Modularity, evolvability, and adaptive radiations: a comparison of the hemi- and holometabolous insectsEVOLUTION AND DEVELOPMENT, Issue 2 2001Andrew S. Yang SUMMARY Despite recent attention given to the concept of modularity and its potential contribution to the evolvability of organisms, there has been little mention of how such a contribution may affect rates of diversification or how this would be assessed. A first key prediction is that lineages with relatively greater degrees of modularity in given traits should exhibit higher rates of diversification. Four general conditions for testing this prediction of the modular evolvability hypothesis are outlined here. The potential role of modularity as a deterministic factor in adaptive radiations is best examined by looking at historic patterns of diversification rather than just levels of extant diversity, the focus of most analyses of key innovations. Recent developmental evidence supports the notion that phenotypes of juvenile and adult stages of insects with "complete" metamorphosis (Holometabola) are distinct developmental and evolvable modules compared to the highly correlated life stages of insects with "incomplete" metamorphosis (Hemimetabola). Family-level rates of diversification for these two groups were calculated from the fossil record. The Holometabola was found to have a significantly and characteristically higher rate of diversification compared to the less modular Hemimetabola, consistent with the idea that intrinsic differences in modularity can influence the long-term evolvability of organisms. The modular evolvability hypothesis also makes a second key prediction: that characters in more modular clades will exhibit greater levels of variation due to their independence. This provides an independent, phenotypically based test of the hypothesis. We discuss here how this second prediction may be tested in the case of the Hemi- and Holometabola. [source] Evolutionary history shapes the association between developmental instability and population-level genetic variation in three-spined sticklebacksJOURNAL OF EVOLUTIONARY BIOLOGY, Issue 8 2009S. VAN DONGEN Abstract Developmental instability (DI) is the sensitivity of a developing trait to random noise and can be measured by degrees of directionally random asymmetry [fluctuating asymmetry (FA)]. FA has been shown to increase with loss of genetic variation and inbreeding as measures of genetic stress, but associations vary among studies. Directional selection and evolutionary change of traits have been hypothesized to increase the average levels of FA of these traits and to increase the association strength between FA and population-level genetic variation. We test these two hypotheses in three-spined stickleback (Gasterosteus aculeatus L.) populations that recently colonized the freshwater habitat. Some traits, like lateral bone plates, length of the pelvic spine, frontal gill rakers and eye size, evolved in response to selection regimes during colonization. Other traits, like distal gill rakers and number of pelvic fin rays, did not show such phenotypic shifts. Contrary to a priori predictions, average FA did not systematically increase in traits that were under presumed directional selection, and the increases observed in a few traits were likely to be attributable to other factors. However, traits under directional selection did show a weak but significantly stronger negative association between FA and selectively neutral genetic variation at the population level compared with the traits that did not show an evolutionary change during colonization. These results support our second prediction, providing evidence that selection history can shape associations between DI and population-level genetic variation at neutral markers, which potentially reflect genetic stress. We argue that this might explain at least some of the observed heterogeneities in the patterns of asymmetry. [source] Currency Orders and Exchange Rate Dynamics: An Explanation for the Predictive Success of Technical AnalysisTHE JOURNAL OF FINANCE, Issue 5 2003Carol L. Osler Associate Professor This paper documents clustering in currency stop-loss and take-profit orders, and uses that clustering to provide an explanation for two familiar predictions from technical analysis: (1) trends tend to reverse course at predictable support and resistance levels, and (2) trends tend to be unusually rapid after rates cross such levels. The data are the first available on individual currency stop-loss and take-profit orders. Take-profit orders cluster particularly strongly at round numbers, which could explain the first prediction. Stop-loss orders cluster strongly just beyond round numbers, which could explain the second prediction. [source] | ||||||||||