Introduction
Long-distance migratory species pose distinct challenges to studies of
ecology, evolution, and conservation because they occupy different
geographical regions throughout the year that can be separated by
thousands of kilometers. At each stage in the migratory annual cycle,
migrant populations are subject to various stressors that can influence
their fitness . As a result, effective conservation efforts require
understanding migratory connectivity, defined as the links between
different geographic regions used across the annual cycle . In the past
20 years, population genetics has become a well-established means for
tracking migratory populations, especially for studies involving large
sample sizes or small-bodied individuals . However, the value of genetic
markers is often limited by the amount of genetic differentiation in a
species and the availability of genetic data from individuals across the
annual cycle .
Population assignment methods originated in the early 1980s and 1990s as
a means of identifying breeding origins of migratory individuals back to
distinct tributaries (in the case of fish) or geographic regions (in the
case of bears) . Early methods relied on genetic markers that were
limited to identifying only deep phylogeographic breaks within species .
In recent years, next generation sequencing has facilitated the
screening of a significantly larger number of genetic markers allowing
for the delineation of breeding populations at finer spatial scales .
Cost-effective delineation of patterns of migratory connectivity was
made possible by designing single nucleotide polymorphisms (SNP) assays
for a subset of these markers that were particularly useful for
population assignment . While recent reductions in the cost of whole
genome sequencing have made it possible to directly use low-coverage
whole genome sequencing (lcWGS) data to screen migrant samples, the lack
of software capable of dealing with the increase in marker number has
prevented this method from being used for population assignment (DeSaix
et al. in review).
Low-coverage WGS has made sequencing more affordable for non-model
organisms by reducing the sequencing effort per individual, however it
has distinct challenges. One of these challenges is dealing with low
sequencing read depths per individual, which necessitates the use of
probabilistic frameworks for genotype calling to account for the
uncertainty inherent in the data . Accurate estimates of parameters such
as allele frequency can be obtained by prioritizing larger sample sizes
of individuals with lower sequencing depth . Guidelines for achieving
accurate allele frequency estimation with lcWGS include sequencing
individuals at a minimum of 1X coverage or having at least 10
individuals sequenced with a total sequencing depth of at least 10X . To
take advantage of lcWGS data for population assignment, DeSaix et al.
(in review ) recently developed a software package, WGSassign,
that accounts for uncertainty inherent to lcWGS data in population
assignment tests. Here, for the first time, we use lcWGS data to assign
migrants to their population of origin.
The American Redstart (Setophaga ruticilla ) is an ideal system
for evaluating the potential gains in effectiveness achievable by using
lcWGS data for population assignment because previous studies using a
variety of methods provide a strong foundation for comparisons. The
American Redstart is a widely distributed migratory songbird with a
breeding distribution across North America and stationary nonbreeding
distribution throughout the Caribbean, northern South America, Central
America, and Mexico . For several decades, the American Redstart has
been a model species for understanding migratory ecology and has been
used to elucidate territoriality on the wintering grounds , foraging
behavior , habitat selection , and carry-over effects of stressors
across the annual cycle . Phylogeographic structure has previously been
detected between a small region in the Maritime Provinces, specifically
in Newfoundland and New Brunswick in the northeastern portion of the
range, and the rest of the continental breeding range using mtDNA .
Subsequent analysis of migratory connectivity using mtDNA revealed that
Newfoundland breeders overwintered on the islands of Puerto Rico and the
Dominican Republic, while continental breeding birds overwintered across
the entire nonbreeding range . Stable isotope studies have shown strong
migratory connectivity, with eastern breeding birds overwintering in the
Caribbean and western breeding birds overwintering in Central America
and Mexico , but whether these migratory differences correspond to
genetic differentiation has not been tested.
Here we aim to demonstrate the effectiveness of using lcWGS data for
population assignment of nonbreeding individual using the American
Redstart as a model species. Our main objectives were: 1) Identify
population-specific migratory connectivity in the American Redstart
using lcWGS data, 2) Assess conservation implications of migratory
connectivity by identifying relative abundance and trends in population
size, and 3) Provide study design recommendations to facilitate the use
of lcWGS data in other population assignment studies. Our results have
broad implications for improving our understanding of the ecology and
evolution of migratory species through conservation genomics approaches.