Ecological character displacement in the face of gene flow: Evidence from two species of nightingales

<p>Abstract</p> <p>Background</p> <p>Ecological character displacement is a process of phenotypic differentiation of sympatric populations caused by interspecific competition. Such differentiation could facilitate speciation by enhancing reproductive isolation between incipient species, although empirical evidence for it at early stages of divergence when gene flow still occurs between the species is relatively scarce. Here we studied patterns of morphological variation in sympatric and allopatric populations of two hybridizing species of birds, the Common Nightingale (<it>Luscinia megarhynchos</it>) and the Thrush Nightingale (<it>L. luscinia</it>).</p> <p>Results</p> <p>We conducted principal component (PC) analysis of morphological traits and found that nightingale species converged in overall body size (PC1) and diverged in relative bill size (PC3) in sympatry. Closer analysis of morphological variation along geographical gradients revealed that the convergence in body size can be attributed largely to increasing body size with increasing latitude, a phenomenon known as Bergmann's rule. In contrast, interspecific interactions contributed significantly to the observed divergence in relative bill size, even after controlling for the effects of geographical gradients. We suggest that the divergence in bill size most likely reflects segregation of feeding niches between the species in sympatry.</p> <p>Conclusions</p> <p>Our results suggest that interspecific competition for food resources can drive species divergence even in the face of ongoing hybridization. Such divergence may enhance reproductive isolation between the species and thus contribute to speciation.</p

Stochastic Spatial Models in Ecology: A Statistical Physics Approach

Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.MAM is grateful to the Spanish-MINECO for financial support (under Grant FIS2013-43201-P; FEDER funds

Knowledge, attention, and psychomotor ability: A latent variable approach to understanding individual differences in simulated work performance

We compare the validity of personnel selection measures and novel tests of attention control for explaining individual differences in synthetic work performance, which required participants to monitor and complete multiple ongoing tasks. In Study 1, an online sample of young adults (N = 474, aged 18-35) based in the United States completed three-minute tests of attention control and two tests that primarily measure acquired knowledge, the Wonderlic and the Armed Forces Qualification Test (AFQT). Structural equation modeling revealed that acquired knowledge tests did not predict simulated work performance beyond attention control, whereas attention control did predict simulated work performance controlling for other measures. In Study 2, an in-lab sample of young adults from Georgia Tech and the greater Atlanta community (N = 321, aged 18-35) completed tests of attention control, processing speed, working memory capacity, and versions of two U.S. Military selection tests, one assessing acquired knowledge (the AFQT) and one assessing psychomotor ability (the Performance-Based Measures assessment from the Aviation Selection Test Battery). Structural equation modeling revealed that attention control fully mediated the relationship between the Performance Based Measures and simulated work performance, but the AFQT and processing speed retained unique prediction. We also explore possible gender differences. Collectively, these results suggest that tests of attention control may be a useful supplement to existing personnel selection measures when complex cognitive tasks are the criterion variable of interest

Attention Control Measures Improve the Prediction of Performance in Navy Trainees

We present a theoretical framework and empirical data from a sample of 490 U.S. Navy trainees (air traffic controllers, student naval aviators, and student naval flight officers) supporting the use of attention control tests in personnel selection. Current military selection tests leave room for improvement when predicting individual differences in work-relevant outcomes and reducing adverse impact. We tested whether measures of attention control, working memory capacity, and fluid intelligence improved the prediction of training success above and beyond the current composite scores used by the U.S. Military. For air traffic controllers in training, attention control explained 9.1% of the unique variance in academic performance, whereas the Armed Forces Qualification Test explained 5.2% of the unique variance. For student naval aviators, incremental validity estimates were generally small and non-significant. For student naval flight officers, attention control measures explained 11.8% of the unique variance in aviation preflight indoctrination training performance and 4.3% of the unique variance in flight performance. In general, attention control measures improved training outcome classification accuracy, and the antisaccade and selective visual arrays tests of attention control demonstrated relatively small differences between majority and minority subgroups

Attention Control Measures Improve the Prediction of Performance in Navy Trainees

We present a theoretical framework and empirical data from a sample of 490 U.S. Navy trainees (air traffic controllers, student naval aviators, and student naval flight officers) exploring the use of attention control tests in personnel selection. Current military selection tests leave room for improvement when predicting individual differences in work-relevant outcomes and reducing adverse impact. We tested whether measures of attention control, working memory capacity, and fluid intelligence improved the prediction of training success above and beyond composite scores currently used by the U.S. Military. For air traffic controllers in training, commonality analyses revealed that attention control explained 9.1% of the unique variance in academic performance, whereas the Armed Forces Qualification Test explained 5.2% of the unique variance. For student naval aviators, incremental validity estimates were generally small and non-significant. For student naval flight officers, commonality analyses revealed that attention control measures explained 11.8% of the unique variance in aviation preflight indoctrination training performance and 4.3% of the unique variance in flight performance. Although these point estimates are based on relatively small samples, they provide preliminary evidence that attention control measures might improve training outcome classification accuracy in real-world samples of military personnel