I'm an evolutionary biologist who studies how species' genomes are shaped by patterns of individual movement like dispersal and seasonal migration. Some of my recent work uses genome sequence data to identify cryptic species of migratory birds, link breeding and wintering ranges of declining North American songbirds, and document recent range shifts in Anna's Hummingbirds.
I'm currently a postdoctoral research associate in the Kern Lab at the University of Oregon Institute for Ecology and Evolution, where I'm working on applying machine learning methods to estimate life history parameters like dispersal distance and population density from genetic data. I did my PhD in the Klicka Lab at the University of Washington Department of Biology and the Burke Museum of Natural History, where my dissertation was focused on the impacts of seasonal migration on genetic diversity in birds.
Scroll down for more info on my research, links to code, and pictures of animals.
Most of my work involves implementing and developing population genetic models to estimate how long ago populations split from each other, how often they exchange migrants, or how big their past populations were. I'm particularly interested in how geography and dispersal interact to shape genetic variation and the capacity for local adaptation (see more in the migration section), and in understanding the limits of information available in DNA sequence data. In practice this involves a mix of sample collection in the field, labwork to prepare DNA for sequencing, and a lot of bioinformatic analysis (mostly R, some python, bash as needed). I spend most of my time attempting to think through how the assumptions of theoretical models interact with the reality of empirical data collection to shape reasonable interpretations of model inferences.
Recently I've been working with my labmate Ethan Linck on an analysis of how minor-allele frequency filters (a common way of cleaning sequence data) can alter inferences from genetic clusering algorithms (preprint here). We have a few other ideas for incorporating uncertainty in visualization techniques in the works too (hopefully up this summer). I also developed a set of interactive simulation apps for undergraduate classes that allow students to build intution for how selection, migration, and drift interact to cause differences in allele frequencies among populations (drift simulator, selective sweep simulator).
Around 30% of bird species migrate seasonally between different habitats, and similar migratory behaviors are found in (among others) butterflies, insects, fish, mammals, snakes, flatworms, fruit flies, and people. My dissertation research is focused on understanding how this process impacts speciation and the capacity for local adaptation in birds. Historically most migratory species were thought to be genetically homogenous, because spatial mixing of genotypes between years should spread genetic variation widely across the range. My research on vireos (pdf), buntings (pdf), and hummingbirds (working on it) has found that a strong correlation between geographic and genetic distance (i.e. "isolation by distance") is instead found even in small bodied species that migrate without family groups, suggesting effective gene flow across the range is relatively low despite the species' large annual movements. Introgression among strongly divergent lineages is frequently observed at range boundaries, but at least in the species I have studied rarely spreads to the center of the range. This combination of IBD and persistent hybrid clines suggests that selection plays an important role in maintaining population differentiation in migratory birds.
How does the interaction of gene flow, drift, and selection shape variation across the genome of migratory species? How much information about past demographics or selective regimes can be reliably inferred from genomic data? I'm currently working on a set of simulation studies and a whole-genome sequence analysis in order to address these questions in the Rufous/Allen's Hummingbird Species Complex.
"All species ranges are the result of successful past range expansions" - Keitt et al. 2001, Am Nat.
I'm interested in how species ranges change over time, and how human modification of the landscape has shaped their evolution over the last hundred years. Recently I've analyzed two cases (both currently in review): a drop in elevation ranges in Puerto Rican Anolis lizards likely caused by forest regrowth on former agricultural lands during industrialization, and the dramatic northern range expansion of the Anna's Hummingbird caused by introduced plants and hummingbird feeders.
For recent updates see my github
driftR: an interactive population genetic simulation website that allows students to explore the impacts of genetic drift, selection, migration, mutation, and population sizes on a variety of summary statistics.https://cjbattey.shinyapps.io/driftR/
adaptR: simulate selective sweeps and other processes with varying selection over time.https://cjbattey.shinyapps.io/adaptR/
structurePlotter: plot output of genotype clustering algorithms with fancy color selection and a permutation algorithm to deal with label switching.https://cjbattey.shinyapps.io/structurePlotter/
A random subset of recent pictures. Find more on my tumblr
PhD Candidate, Klicka Lab
University of Washington Dept. of Biology
548 Kincaid Hall, Box 351800
Seattle, WA 98195-1800