Sensory adaptations reshaped intrinsic factors underlying morphological diversification in bats.

BACKGROUND: Morphological evolution may be impacted by both intrinsic (developmental, constructional, physiological) and extrinsic (ecological opportunity and release) factors, but can intrinsic factors be altered by adaptive evolution and, if so, do they constrain or facilitate the subsequent diversification of biological form? Bats underwent deep adaptive divergences in skull shape as they evolved different sensory modes; here we investigate the potential impact of this process on two intrinsic factors that underlie morphological variation across organisms, allometry, and modularity. RESULTS: We use comparative phylogenetic and morphometric approaches to examine patterns of evolutionary allometry and modularity across a 3D geometric morphometric dataset spanning all major bat clades. We show that allometric relationships diverge between echolocators and visually oriented non-echolocators and that the evolution of nasal echolocation reshaped the modularity of the bat cranium. CONCLUSIONS: Shifts in allometry and modularity may have significant consequences on the diversification of anatomical structures, as observed in the bat skull.

Adaptive landscape and functional diversity of Neotropical cichlids: implications for the ecology and evolution of Cichlinae (Cichlidae; Cichliformes).

Morphological, lineage and ecological diversity can vary substantially even among closely related lineages. Factors that influence morphological diversification, especially in functionally relevant traits, can help to explain the modern distribution of disparity across phylogenies and communities. Multivariate axes of feeding functional morphology from 75 species of Neotropical cichlid and a stepwise-AIC algorithm were used to estimate the adaptive landscape of functional morphospace in Cichlinae. Adaptive landscape complexity and convergence, as well as the functional diversity of Cichlinae, were compared with expectations under null evolutionary models. Neotropical cichlid feeding function varied primarily between traits associated with ram feeding vs. suction feeding/biting and secondarily with oral jaw muscle size and pharyngeal crushing capacity. The number of changes in selective regimes and the amount of convergence between lineages was higher than expected under a null model of evolution, but convergence was not higher than expected under a similarly complex adaptive landscape. Functional disparity was compatible with an adaptive landscape model, whereas the distribution of evolutionary change through morphospace corresponded with a process of evolution towards a single adaptive peak. The continentally distributed Neotropical cichlids have evolved relatively rapidly towards a number of adaptive peaks in functional trait space. Selection in Cichlinae functional morphospace is more complex than expected under null evolutionary models. The complexity of selective constraints in feeding morphology has likely been a significant contributor to the diversity of feeding ecology in this clade.

GoodFibes: An R Package for The Detection of Muscle Fibers from diceCT Scans.

Contrast enhanced computed-tomography imaging like diffusible iodine-based contrast-enhanced computed tomography (diceCT) can provide detailed information on muscle architecture important to comparative analyses of functional morphology, using non-destructive approaches. However, manual segmentation of muscle fascicles/fibers is time-consuming, and automated approaches are at times inaccessible and unaffordable. Here, we introduce GoodFibes, an R package for reconstructing muscle architecture in 3D from diceCT image stacks. GoodFibes uses textural analysis of image grayscale values to track straight or curved fiber paths through a muscle image stack. Accessory functions provide quality checking, fiber merging, and 3D visualization and export capabilities. We demonstrate the utility and effectiveness of GoodFibes using two datasets, from an ant and bat diceCT scans. In both cases, GoodFibes provides reliable measurements of mean fiber length compared to traditional approaches, and is as effective as currently available software packages. This open-source, free to use software package will help to improve access to tools in the analysis of muscle fiber anatomy using diceCT scans. The flexible and transparent R-language environment allows other users to build on the functions described here and permits direct statistical analysis of the resulting fiber metrics. We hope that this will increase the number of comparative and evolutionary studies incorporating these rich and functionally important datasets.