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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. 

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.

 

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.

 

Habitat-specific thermal responses are well documented in various organisms and likely determine the vulnerability of populations to climate change. However, the underlying roles of genetics and plasticity that shape such habitat-specific patterns are rarely investigated together. Here we examined the thermal plasticity of the butterfly Bicyclus dorothea originating from rainforest and ecotone habitats in Cameroon under common garden conditions. We also sampled wild-caught butterflies from forest and ecotone sites and used RADseq to explore genome-wide population differentiation. We found differences in the level of phenotypic plasticity across habitats. Specifically, ecotone populations exhibited greater sensitivity in wing eyespot features with variable development temperatures relative to rainforest populations. Known adaptive roles of wing eyespots in Bicyclus species suggest that this morphological plasticity is likely under divergent selection across environmental gradients. However, we found no distinct population structure of genome-wide variation between habitats, suggesting high level of ongoing gene flow between habitats is homogenizing most parts of the genome.

 

Low‐coverage whole‐genome sequencing (WGS) is increasingly used for the study of evolution and ecology in both model and non‐model organisms; however, effective application of low‐coverage WGS data requires the implementation of probabilistic frameworks to account for the uncertainties in genotype likelihoods.

Here, we present a probabilistic framework for using genotype likelihoods for standard population assignment applications. Additionally, we derive the Fisher information for allele frequency from genotype likelihoods and use that to describe a novel metric, theeffective sample size, which figures heavily in assignment accuracy. We make these developments available for application through WGSassign, an open‐source software package that is computationally efficient for working with whole‐genome data.

Using simulated and empirical data sets, we demonstrate the behaviour of our assignment method across a range of population structures, sample sizes and read depths. Through these results, we show that WGSassign can provide highly accurate assignment, even for samples with low average read depths (<0.01X) and among weakly differentiated populations.

Our simulation results highlight the importance of equalizing the effective sample sizes among source populations in order to achieve accurate population assignment with low‐coverage WGS data. We further provide study design recommendations for population assignment studies and discuss the broad utility of effective sample size for studies using low‐coverage WGS data.

 

Pleistocene climate cycles are well documented to have shaped contemporary species distributions and genetic diversity. Northward range expansions in response to deglaciation following the Last Glacial Maximum (LGM; approximately 21 000 years ago) are surmised to have led to population size expansions in terrestrial taxa and changes in seasonal migratory behaviour. Recent findings, however, suggest that some northern temperate populations may have been more stable than expected through the LGM. We modelled the demographic history of 19 co-distributed boreal-breeding North American bird species from full mitochondrial gene sets and species-specific molecular rates. We used these demographic reconstructions to test how species with different migratory strategies were affected by glacial cycles. Our results suggest that effective population sizes increased in response to Pleistocene deglaciation earlier than the LGM, whereas genetic diversity was maintained throughout the LGM despite shifts in geographical range. We conclude that glacial cycles prior to the LGM have most strongly shaped contemporary genetic diversity in these species. We did not find a relationship between historic population dynamics and migratory strategy, contributing to growing evidence that major switches in migratory strategy during the LGM are unnecessary to explain contemporary migratory patterns. 

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.