139 resultados para Measures of Contradiction


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Aim Test hypotheses that present biodiversity and endemic species richness are related to climatic stability and/or biome persistence.Location Africa south of 15° S. Methods Seventy eight HadCM3 general circulation model palaeoclimate experiments spanning the last 140,000 years, plus a pre-industrial experiment,were used to calculate measures of climatic variability for 0.5° grid cells. Models were fitted relating distributions of the nine biomes of South Africa,Lesotho and Swaziland to present climate. These models were used to simulate potential past biome distribution and extent for the 78 palaeoclimate experiments, and three measures of biome persistence. Climatic response surfaces were fitted for 690 bird species regularly breeding in the region and used to simulate present species richness for cells of the 0.5° grid. Species richness was evaluated for residents, mobile species (nomadic or partially/altitudinally migrant within the region), and intra-African migrants, and also separately for endemic/near-endemic (hereafter ‘endemic’) species as a whole and those associated with each biome. Our hypotheses were tested by analysing correlations between species richness and climatic variability or biome persistence. Results The magnitude of climatic variability showed clear spatial patterns. Marked changes in biome distributions and extents were projected, although limited areas of persistence were projected for some biomes. Overall species richness was not correlated with climatic variability, although richness of mobile species showed a weak negative correlation. Endemic species richness was significantly negatively correlated with climatic variability. Strongest correlations, however, were positive correlations between biome persistence and richness of endemics associated with individual biomes. Main conclusions Low climatic variability, and especially a degree of stability enabling biome persistence, is strongly correlated with species richness of birds endemic to southern Africa. This probably principally reflects reduced extinction risk for these species where the biome to which they are adapted persisted

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Attending to stimuli that share perceptual similarity to learned threats is an adaptive strategy. However, prolonged threat generalization to cues signalling safety is considered a core feature of pathological anxiety. One potential factor that may sustain over-generalization is sensitivity to future threat uncertainty. To assess the extent to which Intolerance of Uncertainty (IU) predicts threat generalization, we recorded skin conductance in 54 healthy participants during an associative learning paradigm, where threat and safety cues varied in perceptual similarity. Lower IU was associated with stronger discrimination between threat and safety cues during acquisition and extinction. Higher IU, however, was associated with generalized responding to threat and safety cues during acquisition, and delayed discrimination between threat and safety cues during extinction. These results were specific to IU, over and above other measures of anxious disposition. These findings highlight: (1) a critical role of uncertainty-based mechanisms in threat generalization, and (2) IU as a potential risk factor for anxiety disorder development.

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The Plant–Craig stochastic convection parameterization (version 2.0) is implemented in the Met Office Regional Ensemble Prediction System (MOGREPS-R) and is assessed in comparison with the standard convection scheme with a simple stochastic scheme only, from random parameter variation. A set of 34 ensemble forecasts, each with 24 members, is considered, over the month of July 2009. Deterministic and probabilistic measures of the precipitation forecasts are assessed. The Plant–Craig parameterization is found to improve probabilistic forecast measures, particularly the results for lower precipitation thresholds. The impact on deterministic forecasts at the grid scale is neutral, although the Plant–Craig scheme does deliver improvements when forecasts are made over larger areas. The improvements found are greater in conditions of relatively weak synoptic forcing, for which convective precipitation is likely to be less predictable.

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We study the relationship between the sentiment levels of Twitter users and the evolving network structure that the users created by @-mentioning each other. We use a large dataset of tweets to which we apply three sentiment scoring algorithms, including the open source SentiStrength program. Specifically we make three contributions. Firstly we find that people who have potentially the largest communication reach (according to a dynamic centrality measure) use sentiment differently than the average user: for example they use positive sentiment more often and negative sentiment less often. Secondly we find that when we follow structurally stable Twitter communities over a period of months, their sentiment levels are also stable, and sudden changes in community sentiment from one day to the next can in most cases be traced to external events affecting the community. Thirdly, based on our findings, we create and calibrate a simple agent-based model that is capable of reproducing measures of emotive response comparable to those obtained from our empirical dataset.