The question of whether migratory birds track a specific climatic niche by seasonal movements has important implications for understanding the evolution of migration, the factors affecting species’ distributions, and the responses of migrants to climate change. Despite much research, previous studies of bird migration have produced mixed results. However, whether migrants track climate is only one half of the question, the other being why residents remain in the same geographic range year-round. We provide a literature overview and test the hypothesis of seasonal niche tracking by evaluating seasonal climatic niche overlap across 437 migratory and resident species from eight clades of passerine birds. Seasonal climatic niches were based on a new global dataset of breeding and nonbreeding ranges. Overlap between climatic niches was quantified using ordination methods. We compared niche overlap of migratory species to two null expectations, (a) a scenario in which they do not migrate and (b) in comparison with the overlap experienced by closely related resident species, while controlling for breeding location and range size. Partly in accordance with the hypothesis of niche tracking, we found that the overlap of breeding versus nonbreeding climatic conditions in migratory species was greater than the overlap they would experience if they did not migrate. However, this was only true for migrants breeding outside the tropics and only relative to the overlap species would experience if they stayed in the breeding range year-round. In contrast to the hypothesis of niche tracking, migratory species experienced lower seasonal climatic niche overlap than resident species, with significant differences between tropical and nontropical species. Our study suggests that in seasonal nontropical environments migration away from the breeding range may serve to avoid seasonally harsh climate; however, different factors may drive seasonal movements in the climatically more stable tropical regions.Phylogenetic inference and species delimitation can be challenging in taxonomic groups that have recently radiated and where introgression produces conflicting gene trees, especially when species delimitation has traditionally relied on mitochondrial data and color pattern. Chromodoris, a genus of colorful and toxic nudibranch in the Indo-Pacific, has been shown to have extraordinary cryptic diversity and mimicry, and has recently radiated, ultimately complicating species delimitation. In these cases, additional genome-wide data can help improve phylogenetic resolution and provide important insights about evolutionary history. Here, we employ a transcriptome-based exon capture approach to resolve Chromodoris phylogeny with data from 2,925 exons and 1,630 genes, derived from 15 nudibranch transcriptomes. We show that some previously identified mimics instead show mitonuclear discordance, likely deriving from introgression or mitochondrial capture, but we confirm one “pure” mimic in Western Australia. Sister-species relationships and species-level entities were recovered with high support in both concatenated maximum likelihood (ML) and summary coalescent phylogenies, but the ML topologies were highly variable while the coalescent topologies were consistent across datasets. Our work also demonstrates the broad phylogenetic utility of 149 genes that were previously identified from eupulmonate gastropods. This study is one of the first to (a) demonstrate the efficacy of exon capture for recovering relationships among recently radiated invertebrate taxa, (b) employ genome-wide nuclear markers to test mimicry hypotheses in nudibranchs and (c) provide evidence for introgression and mitochondrial capture in nudibranchs.Scientists are increasingly using volunteer efforts of citizen scientists to classify images captured by motion-activated trail cameras. The rising popularity of citizen science reflects its potential to engage the public in conservation science and accelerate processing of the large volume of images generated by trail cameras. While image classification accuracy by citizen scientists can vary across species, the influence of other factors on accuracy is poorly understood. Inaccuracy diminishes the value of citizen science derived data and prompts the need for specific best-practice protocols to decrease error. We compare the accuracy between three programs that use crowdsourced citizen scientists to process images online Snapshot Serengeti, Wildwatch Kenya, and AmazonCam Tambopata. We hypothesized that habitat type and camera settings would influence accuracy. To evaluate these factors, each photograph was circulated to multiple volunteers. All volunteer classifications were aggregated to a single best answey of future citizen science projects, and subsequently encourage the increased use of such data.We use adaptive dynamics models to study how changes in the abiotic environment affect patterns of evolutionary dynamics and diversity in evolving communities of organisms with complex phenotypes. The models are based on the logistic competition model, and environmental changes are implemented as a temporal change of the carrying capacity as a function of phenotype. In general, we observe that environmental changes cause a reduction in the number of species, in total population size, and in phenotypic diversity. The rate of environmental change is crucial for determining whether a community survives or undergoes extinction. Until some critical rate of environmental changes, species are able to follow evolutionarily the shifting phenotypic optimum of the carrying capacity, and many communities adapt to the changing conditions and converge to new stationary states. When environmental changes stop, such communities gradually restore their initial phenotypic diversity.Leaf shape is a defining feature of how we recognize and classify plant species. Although there is extensive variation in leaf shape within many species, few studies have disentangled the underlying genetic architecture. We characterized the genetic architecture of leaf shape variation in Eurasian aspen (Populus tremula L.) by performing genome-wide association study (GWAS) for physiognomy traits. selleck chemicals To ascertain the roles of identified GWAS candidate genes within the leaf development transcriptional program, we generated RNA-Seq data that we used to perform gene co-expression network analyses from a developmental series, which is publicly available within the PlantGenIE resource. We additionally used existing gene expression measurements across the population to analyze GWAS candidate genes in the context of a population-wide co-expression network and to identify genes that were differentially expressed between groups of individuals with contrasting leaf shapes. These data were integrated with expression GWAS (eQTL) results to define a set of candidate genes associated with leaf shape variation.