Effects of wind, ambient temperature and sun position on damselfly flight activity and perch orientation

© 2017 The Association for the Study of Animal Behaviour Many animals rely on movement for survival and reproduction. Directed movements incur metabolic costs, however, and animals adjust their behaviour to optimize energy expenditures in different abiotic conditions. Physical flows and solar radiation vary over time and space and influence animal behaviour at multiple spatiotemporal scales. Here, I quantify the effects of wind speed, wind direction, ambient temperature and sun position on the fine-scale movement ecology and perch orientation of a widespread damselfly, Enallagma doubledayi. Through field observations, I found that damselflies fly, forage and engage competitors in territorial interactions more often in calm rather than windy conditions. Furthermore, perched damselflies exhibit rheotaxis, in which individuals typically face into the wind, presumably to minimize biomechanical costs associated with drag and possibly to detect inbound prey on the water surface and in the air column. In contrast, ambient temperature and the position of the sun were largely unassociated with activity levels and damselfly orientation. At higher ambient temperatures, however, perched odonates faced the sun with increasing consistency, perhaps to thermoregulate by minimizing exposure to solar radiation. Taken together, these findings suggest that damselflies preferentially fly when the ratio of animal speed to wind speed is high and adjust their perch orientation to minimize energy loss. These findings strengthen conceptual links between activity budgets and perch orientation strategies among animals in variable abiotic conditions

Differentially expressed genes match bill morphology and plumage despite largely undifferentiated genomes in a Holarctic songbird

© 2015 John Wiley & Sons Ltd. Understanding the patterns and processes that contribute to phenotypic diversity and speciation is a central goal of evolutionary biology. Recently, high-throughput sequencing has provided unprecedented phylogenetic resolution in many lineages that have experienced rapid diversification. The Holarctic redpoll finches (Genus: Acanthis) provide an intriguing example of a recent, phenotypically diverse lineage; traditional sequencing and genotyping methods have failed to detect any genetic differences between currently recognized species, despite marked variation in plumage and morphology within the genus. We examined variation among 20 712 anonymous single nucleotide polymorphisms (SNPs) distributed throughout the redpoll genome in combination with 215 825 SNPs within the redpoll transcriptome, gene expression data and ecological niche modelling to evaluate genetic and ecological differentiation among currently recognized species. Expanding upon previous findings, we present evidence of (i) largely undifferentiated genomes among currently recognized species; (ii) substantial niche overlap across the North American Acanthis range; and (iii) a strong relationship between polygenic patterns of gene expression and continuous phenotypic variation within a sample of redpolls from North America. The patterns we report may be caused by high levels of ongoing gene flow between polymorphic populations, incomplete lineage sorting accompanying very recent or ongoing divergence, variation in cis-regulatory elements, or phenotypic plasticity, but do not support a scenario of prolonged isolation and subsequent secondary contact. Together, these findings highlight ongoing theoretical and computational challenges presented by recent, rapid bouts of phenotypic diversification and provide new insight into the evolutionary dynamics of an intriguing, understudied non-model system. See also the Perspective by Lifjel

The effect of habitat and body size on the evolution of vocal displays in Thraupidae (tanagers), the largest family of songbirds

© 2015 The Linnean Society of London. Animals rely on auditory cues to relay important information between individuals regarding territoriality, mating status, and individual condition. The efficacy of acoustic signals can depend on many factors, including the transmitter, the receiver, and the signalling environment. In the present study, we evaluate the effect of body size and habitat on the evolution of learned vocal displays across the tanagers (Aves: Thraupidae), a group that comprises nearly 10% of all songbird species. We find that body size affects tanager vocalizations, such that nine out of ten song characters and scores from two principal component axes were correlated with mass. More specifically, larger tanagers tended to produce slower-paced, lower-pitched vocal displays within narrower bandwidths. In contrast, habitat was correlated with only three out of ten song characters, and only one of these characters corroborated the directional predictions of the acoustic adaptation hypothesis. Thus, morphological characters, such as body mass, may play a more important role than variation among signalling environments in the evolution of avian vocal displays

Species Identification of Vagrant Empidonax Flycatchers in Northeastern North America Via Non-Invasive DNA Sequencing

Vagrant individuals from cryptic species complexes pose a persistent challenge for accurate species identification, hindering our understanding of vagrancy in these taxa. Here, we used non-invasive sampling of fecal matter to sequence the ND2 mitochondrial gene of 2 vagrant western flycatchers observed in northeastern North America. The DNAsequence data we recovered from these vagrants fell within a clade of known Empidonax difficillis (Pacific-slope Flycatcher) haplotypes. Our work provides robust records of 2 vagrant Pacific-slope Flycatchers in the northeastern US. These findings illustrate the power of non-invasive sampling for species identification of vagrants from cryptic species complexes

Longitudinal analysis of a diversity support program in biology: A national call for further assessment

© The Author(s) 2017. National calls to improve the performance and persistence of students from historically underrepresented backgrounds in science have led to a surge of research on inclusive, evidence-based teaching methods. Less work has revealed the effects of diversity support initiatives that improve campus climate and community cohesion. Here, we examine whether participation in the Biology Scholars Program (BSP) at Cornell University-a diversity support program at a prominent university-affects underrepresented racial minority (URM) student performance. We found that BSP participants are less academically prepared when they enter college but typically have GPAs similar to those of their non-BSP counterparts at graduation, thereby closing achievement gaps. Although the BSP appears to help URM students, we cannot assert that the BSP alone is responsible for these effects; future work should isolate effective strategies that contribute to student success. In response to these results, we lay out strategies that support programs could implement to maximize positive impacts

Robust Detection of Dynamic Community Structure in Networks

We describe techniques for the robust detection of community structure in some classes of time-dependent networks. Specifically, we consider the use of statistical null models for facilitating the principled identification of structural modules in semi-decomposable systems. Null models play an important role both in the optimization of quality functions such as modularity and in the subsequent assessment of the statistical validity of identified community structure. We examine the sensitivity of such methods to model parameters and show how comparisons to null models can help identify system scales. By considering a large number of optimizations, we quantify the variance of network diagnostics over optimizations (`optimization variance') and over randomizations of network structure (`randomization variance'). Because the modularity quality function typically has a large number of nearly-degenerate local optima for networks constructed using real data, we develop a method to construct representative partitions that uses a null model to correct for statistical noise in sets of partitions. To illustrate our results, we employ ensembles of time-dependent networks extracted from both nonlinear oscillators and empirical neuroscience data.Comment: 18 pages, 11 figure