Parallel evolution of character displacement driven by competitive selection in terrestrial salamanders

<p>Abstract</p> <p>Background</p> <p>Parallel evolution can occur when common environmental factors exert similar selective forces on morphological variation in populations in different geographic localities. Competition can also generate morphological shifts, and if competing species co-occur in multiple geographic regions, then repeated instances of competitively-driven morphological divergence (character displacement) can occur. Despite the importance of character displacement for inferring the role of selection in morphological evolution however, replicated instances of sympatric morphological divergence are understudied.</p> <p>Results</p> <p>I tested the hypothesis that interspecific competition generated patterns of parallel morphological divergence in multiple geographic locations where two competing salamander species, <it>Plethodon jordani </it>and <it>P. teyahalee</it>, come into contact. I used geometric morphometrics to characterize head shape and found ecological character displacement in sympatric localities on each of three distinct mountains (geographic transects), where sympatric specimens displayed greater cranial differences and an increase in cranial robustness as compared to allopatric specimens. Using a recently developed analytical procedure, I also found that the observed morphological evolution within each species was consistent among transects; both in the total amount of morphological change as well as the direction of evolution in the morphological data space. This provided strong statistical evidence of parallel morphological evolution within species across replicate geographic transects.</p> <p>Conclusions</p> <p>The results presented here reveal that the morphological evolution of each species followed a common evolutionary path in each transect. Because dispersal between sympatric locations among transects is unlikely, these findings suggest that the repeated instances of character displacement have evolved in situ. They also suggest that selection from competitive interactions plays an important role in initiating sympatric morphological divergence in these species, and drives parallel sympatric morphological divergence between species.</p

Evaluating modularity in morphometric data: challenges with the RV coefficient and a new test measure

1: Modularity describes the case where patterns of trait covariation are unevenly dispersed across traits. Specifically, trait correlations are high and concentrated within subsets of variables (modules), but the correlations between traits across modules are relatively weaker. For morphometric datasets, hypotheses of modularity are commonly evaluated using the RV coefficient, an association statistic used in a wide variety of fields. 2: In this article I explore the properties of the RV coefficient using simulated data sets. Using data drawn from a normal distribution where the data were neither modular nor integrated in structure, I show that the RV coefficient is adversely affected by attributes of the data (sample size and the number of variables) that do not characterize the covariance structure between sets of variables. Thus, with the RV coefficient, patterns of modularity or integration in data are confounded with trends generated by sample size and the number of variables, which limits biological interpretations and renders comparisons of RV coefficients across datasets uninformative. 3: As an alternative I propose the covariance ratio (CR) for quantifying modular structure, and show that it is unaffected by sample size or the number of variables. Further, statistical tests based on the CR exhibit appropriate type I error rates, and display higher statistical power relative to the RV coefficient when evaluating modular data. 4: Overall, these findings demonstrate that the RV coefficient does not display statistical characteristics suitable for reliable assessment of hypotheses of modular or integrated structure, and therefore should not be used to evaluate these patterns in morphological datasets. By contrast, the covariance ratio meets these criteria and provides a useful alternative method for assessing the degree of modular structure in morphological data

Phylogenies, the Comparative Method, and the Conflation of Tempo and Mode

The comparison of mathematical models that represent alternative hypotheses about the tempo and mode of evolutionary change is a common approach for assessing the evolutionary processes underlying phenotypic diversification. However, because model parameters are estimated simultaneously, they are inextricably linked, such that changes in tempo, the pace of evolution, and mode, the manner in which evolution occurs, may be difficult to assess separately. This may potentially complicate biological interpretation, but the extent to which this occurs has not yet been determined. In this study, we examined 160 phylogeny × trait empirical datasets, and conducted extensive numerical phylogenetic simulations, to investigate the efficacy of phylogenetic comparative methods to distinguish between models that represent different evolutionary processes in a phylogenetic context. We observed that, in some circumstances, a high uncertainty exists when attempting to distinguish between alternative evolutionary scenarios underlying phenotypic variation. When examining datasets simulated under known conditions, we found that evolutionary inference is straightforward when phenotypic patterns are generated by simple evolutionary processes that are represented by modifying a single model parameter at a time. However, inferring the exact nature of the evolutionary process that has yielded phenotypic variation when facing complex, potentially more realistic, mechanisms is more problematic. A detailed investigation of the influence of different model parameters showed that changes in evolutionary rates, marked changes in phylogenetic means, or the existence of a strong selective pull on the data, are all readily recovered by phenotypic model comparison. However, under evolutionary processes with a milder restraining pull acting on trait values, alternative models representing very different evolutionary processes may exhibit similar goodness-of-fit to the data, potentially leading to the conflation of interpretations that emphasize tempo and mode during empirical evolutionary inference. This is a mathematical and conceptual property of the considered models that, while not prohibitive for studying phenotypic evolution, should be taken into account and addressed when appropriate