Population divergence and connectivity through time.
To estimate population divergence and connectivity through time, we used the program MSMC-IM (Wang et al., 2020). MSMC-IM uses output from MSMC (Schiffels & Durbin, 2014) to fit an isolation with migration model to coalescent rates estimated within and among two populations (Wang et al., 2020). We performed MSMC-IM analyses separately for each species. We initially tried to run MSMC with all sampled individuals, but we were unable to get our runs to complete due to computational limitations. We therefore chose two random individuals per species per population (N = 4 total for each species except the Abyssinian Catbird where N = 3). Here, we used WhatsHap (Martin et al., 2016) to phase genotypes for all individuals. We chose this method because it uses read-based phasing and does not require large sample sizes or reference SNP panels for phasing. Phasing is required for these analyses because MSMC-IM requires estimating cross-coalescence rates between at least two individuals (i.e., ≥ four chromosomes). This is in contrast to MSMC demographic analyses with a single individual that do not require phasing between the two chromosomes sampled in a single diploid individual. We masked all regions with sequencing coverage lower that six in any individual to minimize inclusion of sites with phasing or genotyping errors. We ran MSMC with up to 20 iterations and 23 distinct time segments, as with individual-based demographic histories. Recent within-population histories were qualitatively similar to those estimated from single individuals but with less temporal resolution (results not shown). Less resolution may be expected since we are masking any genomic regions with low sequencing coverage in any individual, and therefore sampling less of the genome. Regardless, our main goal here was to estimate whether all our focal species shared the same patterns of population divergence and migration through time, and small shifts in overall resolution would not heavily impact these types of interpretations. For each species, we used the MSMC output as input for MSMC-IM to fit an isolation with migration model. In MSMC-IM, we used estimated empirical mutation rates for each species, and the recommended regularization settings for estimating migration rates and population sizes (1e-8 and 1e-6, respectively).