Oscar Johnson

Understanding the factors that govern variation in genetic structure across species is key to the study of speciation and population genetics. Genetic structure has been linked to several aspects of life history, such as foraging strategy, habitat association, migration distance, and dispersal ability, all of which might influence dispersal and gene flow. Comparative studies of population genetic data from species with differing life histories provide opportunities to tease apart the role of dispersal in shaping gene flow and population genetic structure. Here, we examine population genetic data from sets of bird species specialized on a series of Amazonian habitat types hypothesized to filter for species with dramatically different dispersal abilities: stable upland forest, dynamic floodplain forest, and highly dynamic riverine islands. Using genome-wide markers, we show that habitat type has a significant effect on population genetic structure, with species in upland forest, floodplain forest, and riverine islands exhibiting progressively lower levels of structure. Although morphological traits used as proxies for individual-level dispersal ability did not explain this pattern, population genetic measures of gene flow are elevated in species from more dynamic riverine habitats. Our results suggest that the habitat in which a species occurs drives the degree of population genetic structuring via its impact on long-term fluctuations in levels of gene flow, with species in highly dynamic habitats having particularly elevated gene flow. These differences in genetic variation across taxa specialized in distinct habitats may lead to disparate responses to environmental change or habitat-specific diversification dynamics over evolutionary time scales.

The stipple-throated antwrens of the genus Epinecrophylla (Aves: Thamnophilidae) are represented by eight species primarily found in the lowlands of the Amazon Basin and the Guiana Shield. The genus has a long and convoluted taxonomic history, with many attempts made to address the taxonomy and systematics of the group. Here we employ massively parallel sequencing of thousands of ultraconserved elements (UCEs) to provide both the most comprehensive subspecies-level phylogeny of Epinecrophylla antwrens and the first population-level genetic analyses for most species in the genus. Most of our results are robust to a diversity of phylogenetic and population genetic methods, but we show that even with thousands of loci we are unable to fully resolve the relationships between some western Amazonian species in the haematonota group. We uncovered phylogenetic relationships between taxa and patterns of population structure that are discordant with both morphology and current taxonomy. For example, we found deep genetic breaks between taxa in the ornata group that are currently regarded as species, and in the haematonota and leucophthalma groups we found paraphyly at the species and subspecies levels, respectively. As has been found in many Amazonian taxa, our phylogenetic results show that the major river systems of the Amazon Basin appear to have an effect on the genetic structure and range limits within Epinecrophylla. Our population genetics analyses showed extensive admixture between some taxa despite their deep genetic divergence.  We present a revised taxonomy for the group and suggest areas for further study.

How the microbiome interacts with hosts across evolutionary time is poorly understood. To address this question, datasets comprised of many host species are required to conduct comparative analyses. Here, we have analyzed 142 intestinal microbiome samples from 92 birds belonging to 74 species from Equatorial Guinea, using the 16S rRNA gene. Using four definitions for microbial taxonomic units (97%OTU, 99%OTU, 99%OTU with singletons removed, ASV), we conducted alpha and beta diversity analyses and used phylogenetic comparative methods to assess the evolution of the microbiome as a trait of bird species. We find that raw abundances and diversity varied between the datasets but relative patterns were largely consistent across datasets. Host taxonomy, diet and locality were significantly associated with microbiomes, at generally similar levels using three distance metrics. Phylogenetic comparative methods were used to assess the relationship between the microbiome as a trait of a host species and the underlying bird phylogeny. We find that a neutral Brownian motion model does not explain variation in microbiomes. Instead, a White Noise model that indicates the trait contains little to no phylogenetic signal, is most likely across many definitions of "microbiome trait". While there was some support for the Ornstein-Uhlenbeck model (that invokes selection), the level of support was similar to our White Noise simulation, further supporting the White Noise model as the best explanation for the evolution of the microbiome as a trait of avian hosts. Our study highlights the qualitatively minor impact that different analytical choices can have on results and that biological interpretations can be robust to method choice.

Migratory birds often form flocks on their wintering grounds, but important details of social structure such as the patterns of association between individuals are virtually unknown. We analysed networks of co-membership in short-term flocks for wintering golden-crowned sparrows (Zonotrichia atricapilla) across three years and discovered social complexity unsuspected for migratory songbirds. The population was consistently clustered into distinct social communities within a relatively small area (~ 7 ha). Birds returned to the same community across years, with mortality and recruitment leading to some degree of turnover in membership. These spatiotemporal patterns were explained by the combination of space use and social preference – birds that flocked together in one year flocked together again in the subsequent year more often than were expected based on degrees of home range overlap. Our results suggest that a surprising level of social fidelity across years leads to repeatable patterns of social network structure in migratory populations.