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Abstract BackgroundRapid morphological change is emerging as a consequence of climate change in many systems. It is intuitive to hypothesize that temporal morphological trends are driven by the same selective pressures that have established well-known ecogeographic patterns over spatial environmental gradients (e.g., Bergman’s and Allen’s rules). However, mechanistic understanding of contemporary morphological shifts is lacking. ResultsWe combine morphological data and whole genome sequencing from a four-decade dataset in the migratory bird hermit thrush (Catharus guttatus) to test whether morphological shifts over time are accompanied by genetic change. Using genome-wide association, we identify alleles associated with body size, bill length, and wing length. Shifts in morphology and concordant shifts in morphology-associated alleles over time would support a genetic basis for the observed changes in morphology over recent decades, potentially an adaptive response to climate change. In our data, bill size decreases were paralleled by genetic shifts in bill size-associated alleles. On the other hand, alleles associated with body size showed no shift in frequency over time. ConclusionsTogether, our results show mixed support for evolutionary explanations of morphological response to climate change. Temporal shifts in alleles associated with bill size support the hypothesis that selection is driving temporal morphological trends. The lack of evidence for genetic shifts in body size alleles could be explained by a large role of plasticity or technical limitations associated with the likely polygenic architecture of body size, or both. Disentangling the mechanisms responsible for observed morphological response to changing environments will be vital for predicting future organismal and population responses to climate change. 

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. 

Preservation of genetic diversity is critical to the resilience of species in the face of global change. To meet international calls to preserve at least 90% of species’ genetic diversity, researchers and conservationists need a way to reliably predict genetic diversity loss resulting from human activities ( 1 ). On page 1431 of this issue, Exposito-Alonso et al. present a mathematical framework that elegantly bridges biodiversity and population genetics theory to model the relationship between genetic diversity and habitat loss ( 2 ). This approach builds on methods already used by biodiversity policy experts for predicting species extinctions based on habitat loss ( 3 ) and should be useful to those tasked with setting goals for preserving genetic diversity. 

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. 

Abstract Conservation units (CUs) are an essential tool for maximizing evolutionary potential and prioritizing areas across a species’ range for protection when implementing conservation and management measures. However, current workflows for identifying CUs on the basis of neutral and adaptive genomic variation largely ignore information contained in patterns of isolation by distance (IBD), frequently the primary signal of population structure in highly mobile taxa, such as birds, bats, and marine organisms with pelagic larval stages. While individuals located on either end of a species’ distribution may exhibit clear genetic, phenotypic, and ecological differences, IBD produces subtle changes in allele frequencies across space, making it difficult to draw clear boundaries for conservation purposes in the absence of discrete population structure. Here, we highlight potential pitfalls that arise when applying common methods for delineating CUs to continuously distributed organisms and review existing methods for detecting subtle breakpoints in patterns of IBD that can indicate barriers to gene flow in highly mobile taxa. In addition, we propose a new framework for identifying CUs in all organisms, including those characterized by continuous genomic differentiation, and suggest several possible ways to harness the information contained in patterns of IBD to guide conservation and management decisions.