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Bird migration has fascinated natural historians and scientists for centuries. While the timing of migration is known to vary by species, population, sex, and individual, identifying the cause of this variation can be challenging. Here we investigate factors underlying migratory timing in a long- distance migratory bird, the Common Yellowthroat (Geothlypas trichas), using a population genomic approach. We begin by creating a map of genetic variation across geographic space (a “genoscape”) using lcWGS from across the breeding range. We then utilize genetic assays to assign 249 wintering and 1050 northward migrating birds to genetically distinct breeding populations. Additionally, we estimate the expected spring onset date in each predicted breeding region and calculate the remaining migratory distance for northward migrating birds. Our findings indicate that when population genetic structure is not a factor in the analysis, it appears that birds captured early in the season are migrating to breeding grounds where spring arrives later, which contrasts with prior research. However, when we incorporate population structure into our analysis, our results align with predictions, indicating that birds captured earlier in the season are indeed heading to breeding grounds where spring arrives earlier. Further analysis revealed that the disparity between results obtained with and without population genetic structure can be attributed to the fact that individuals from the western genetic group migrate three times the distance to the west, despite breeding at the same latitude. Our findings suggest that categorizing large numbers of migrating birds into genetically distinct groups can reveal population-specific patterns in migratory timing and shed light on the relative contributions of different selective forces responsible for the observed patterns. 

Seasonal migration is highly labile from an evolutionary perspective and known to rapidly evolve in response to selective pressures. However, long‐distance migratory birds rely partially on innate genetic programs and may be constrained in their ability to alter their migratory behavior. We take advantage of recent advances in our ability to genotype historical DNA samples to examine the temporal stability of migratory connections between breeding and nonbreeding populations (i.e. migratory connectivity) and population‐level nonbreeding distributions in the Wilson's warblerCardellina pusilla, a long‐distance migratory songbird. By assigning historical and contemporary samples collected across the nonbreeding range to genetically distinct breeding clusters, we suggest that broad‐scale population‐level nonbreeding distributions within this species have remained largely consistent within Mexico from the mid‐1900s to the present day. These findings support the idea that the nonbreeding distributions of long‐distance migrants may remain stable over long time scales, even in the face of rapid environmental change. 

Abstract A prominent challenge for managing migratory species is the development of conservation plans that accommodate spatiotemporally varying distributions throughout the year. Migratory networks are spatially‐explicit models that incorporate migratory assignment and seasonal abundance data to define patterns of connectivity between stages of the annual cycle. These models are particularly useful for widespread application because different types of migratory data can be used to quantify individual and population‐level movement across the annual cycle of migratory species. While there are clear benefits of combining migratory assignment and abundance data for the development of conservation strategies, there is a concurrent need for corresponding user‐friendly software to facilitate the integration of these data for conservation.Here, we presentmignette(migratory network tools ensemble), an R package for developing migratory network models to estimate network connectivity among migratory populations. We demonstrate the functionality ofmignettewith three empirical examples that highlight the use of different types of tracking data for migratory assignment.mignettefacilitates the modelling of migratory networks by providing R functions to: (1) define breeding and nonbreeding nodes, (2) assemble abundance and assignment data and (3) model the migratory network. Additionally,mignetteprovides R functions to visualize modelled migratory networks.With increasing availability of migratory assignment and abundance data,mignetterepresents a valuable tool for developing effective conservation strategies for migratory species. 

Abstract Large structural variants in the genome, such as inversions, may play an important role in producing population structure and local adaptation to the environment through suppression of recombination. However, relatively few studies have linked inversions to phenotypic traits that are sexually selected and may play a role in reproductive isolation. Here, we found that geographic differences in the sexually selected plumage of a warbler, the common yellowthroat (Geothlypis trichas), are largely due to differences in the Z (sex) chromosome (males are ZZ), which contains at least one putative inversion spanning 40% (31/77 Mb) of its length. The inversions on the Z chromosome vary dramatically east and west of the Appalachian Mountains, which provides evidence of cryptic population structure within the range of the most widespread eastern subspecies (G. t. trichas). In an eastern (New York) and western (Wisconsin) population of this subspecies, female prefer different male ornaments; larger black facial masks are preferred in Wisconsin and larger yellow breasts are preferred in New York. The putative inversion also contains genes related to vision, which could influence mating preferences. Thus, structural variants on the Z chromosome are associated with geographic differences in male ornaments and female choice, which may provide a mechanism for maintaining different patterns of sexual selection in spite of gene flow between populations of the same subspecies. 

Abstract The ability of animals to sync the timing and location of molting (the replacement of hair, skin, exoskeletons or feathers) with peaks in resource availability has important implications for their ecology and evolution. In migratory birds, the timing and location of pre-migratory feather molting, a period when feathers are shed and replaced with newer, more aerodynamic feathers, can vary within and between species. While hypotheses to explain the evolution of intraspecific variation in the timing and location of molt have been proposed, little is known about the genetic basis of this trait or the specific environmental drivers that may result in natural selection for distinct molting phenotypes. Here we take advantage of intraspecific variation in the timing and location of molt in the iconic songbird, the Painted Bunting (Passerina ciris) to investigate the genetic and ecological drivers of distinct molting phenotypes. Specifically, we use genome-wide genetic sequencing in combination with stable isotope analysis to determine population genetic structure and molting phenotype across thirteen breeding sites. We then use genome-wide association analysis (GWAS) to identify a suite of genes associated with molting and pair this with gene-environment association analysis (GEA) to investigate potential environmental drivers of genetic variation in this trait. Associations between genetic variation in molt-linked genes and the environment are further tested via targeted SNP genotyping in 25 additional breeding populations across the range. Together, our integrative analysis suggests that molting is in part regulated by genes linked to feather development and structure (GLI2andCSPG4) and that genetic variation in these genes is associated with seasonal variation in precipitation and aridity. Overall, this work provides important insights into the genetic basis and potential selective forces behind phenotypic variation in what is arguably one of the most important fitness-linked traits in a migratory bird. 

Seasonal migration is a dynamic natural phenomenon that allows organisms to exploit favourable habitats across the annual cycle. While the morphological, physiological and behavioural changes associated with migratory behaviour are well characterized, the genetic basis of migration and its link to endogenous biological time-keeping pathways are poorly understood. Historically, genome-wide research has focused on genes of large effect, whereas many genes of small effect may work together to regulate complex traits like migratory behaviour. Here, we explicitly relax stringent outlier detection thresholds and, as a result, discover how multiple biological time-keeping genes are important to migratory timing in an iconic raptor species, the American kestrel ( Falco sparverius ). To validate the role of candidate loci in migratory timing, we genotyped kestrels captured across autumn migration and found significant associations between migratory timing and genetic variation in metabolic and light-input pathway genes that modulate biological clocks ( top1, phlpp1, cpne4 and peak1) . Further, we demonstrate that migrating individuals originated from a single panmictic source population, suggesting the existence of distinct early and late migratory genotypes (i.e. chronotypes). Overall, our results provide empirical support for the existence of a within-population-level polymorphism in genes underlying migratory timing in a diurnally migrating raptor. 

Abstract Identifying genetic conservation units (CUs) in threatened species is critical for the preservation of adaptive capacity and evolutionary potential in the face of climate change. However, delineating CUs in highly mobile species remains a challenge due to high rates of gene flow and genetic signatures of isolation by distance. Even when CUs are delineated in highly mobile species, the CUs often lack key biological information about what populations have the most conservation need to guide management decisions. Here we implement a framework for CU identification in the Canada Warbler (Cardellina canadensis), a migratory bird species of conservation concern, and then integrate demographic modelling and genomic offset to guide conservation decisions. We find that patterns of whole genome genetic variation in this highly mobile species are primarily driven by putative adaptive variation. Identification of CUs across the breeding range revealed that Canada Warblers fall into two evolutionarily significant units (ESU), and three putative adaptive units (AUs) in the South, East, and Northwest. Quantification of genomic offset, a metric of genetic changes necessary to maintain current gene–environment relationships, revealed significant spatial variation in climate vulnerability, with the Northwestern AU being identified as the most vulnerable to future climate change. Alternatively, quantification of past population trends within each AU revealed the steepest population declines have occurred within the Eastern AU. Overall, we illustrate that genomics‐informed CUs provide a strong foundation for identifying current and future regional threats that can be used to inform management strategies for a highly mobile species in a rapidly changing world. 

Abstract Migration is driven by a combination of environmental and genetic factors, but many questions remain about those drivers. Potential interactions between genetic and environmental variants associated with different migratory phenotypes are rarely the focus of study. We pair low coverage whole genome resequencing with a de novo genome assembly to examine population structure, inbreeding, and the environmental factors associated with genetic differentiation between migratory and resident breeding phenotypes in a species of conservation concern, the western burrowing owl (Athene cunicularia hypugaea). Our analyses reveal a dichotomy in gene flow depending on whether the population is resident or migratory, with the former being genetically structured and the latter exhibiting no signs of structure. Among resident populations, we observed significantly higher genetic differentiation, significant isolation‐by‐distance, and significantly elevated inbreeding. Among migratory breeding groups, on the other hand, we observed lower genetic differentiation, no isolation‐by‐distance, and substantially lower inbreeding. Using genotype–environment association analysis, we find significant evidence for relationships between migratory phenotypes (i.e., migrant versus resident) and environmental variation associated with cold temperatures during the winter and barren, open habitats. In the regions of the genome most differentiated between migrants and residents, we find significant enrichment for genes associated with the metabolism of fats. This may be linked to the increased pressure on migrants to process and store fats more efficiently in preparation for and during migration. Our results provide a significant contribution toward understanding the evolution of migratory behavior and vital insight into ongoing conservation and management efforts for the western burrowing owl.