Seasonally migratory songbirds have different historic population size characteristics than resident relatives

Modern genomic methods enable estimation of a lineage’s long-term effective population sizes back to its origins (Li and Durbin, 2011; Mazet et al., 2015; Nadachowska-Brzyska et al., 2015). This ability allows unprecedented opportunities to study the populational effects of past evolutionary and climatic phenomena on organismal lineages, and this new area of paleodemographics is likely to grow rapidly (Nadachowska‐Brzyska et al., 2022, Germain et al., 2023a; Germain et al., 2023b). We use this approach in a novel way to test hypotheses about how the adoption of a major life-history trait affected lineages’ populations relative to those without the trait.

Seasonal migration is a common life-history strategy among the world’s birds, but its effects on long-term population sizes relative to lineages that don’t have this trait are largely unknown (Newton, 2007; Rappole, 2013). Demographic differences between seasonally migratory and resident lineages have been studied for decades, but, thus far, ecological, behavioral, and genetic approaches have necessarily been focused on recent and microevolutionary phenomena (e.g. Greenberg, 1980; Tris et al., 2004; Sandercock and Jaramillo, 2002). Here, we look much deeper, contrasting changes in effective population sizes through millions of years between closely related migratory and resident lineages.

Thrushes in the genus Catharus and this group’s sister Hylocichla mustelina (Aves: Turdidae) are a model songbird system for studying the evolutionary effects of seasonal migration. This group has both migratory and resident lineages (Figure 1), and it has been important in the study of seasonal migration, divergence, and speciation (e.g. Blain et al., 2024; Delmore et al., 2015, Delmore et al., 2016; Everson et al., 2019; Justen et al., 2024; Outlaw et al., 2003; Ruegg et al., 2014; Termignoni-Garcia et al., 2022; Voelker et al., 2013; Winker, 2000; Winker, 2010; Winker and Pruett, 2006). These animals are relatively small, omnivorous or insectivorous, forest-related birds with lineages that are long-distance seasonal migrants in North America and others that are resident in tropical North and South America (Collar, 2005). The current breeding grounds of the migratory lineages span the Russian Far East, Alaska, northern Canada, and the United States, and their wintering ranges include Mexico, the Caribbean, Central America, and tropical South America. In contrast, the resident lineages occupy Mexico, Central America, and northwestern South America (Collar, 2005; Figure 2).

Figure 1

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Figure 2

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We made three predictions about effective population sizes (N_e) in seasonally migratory vs. resident lineages of these thrushes. First, we can think of North America roughly as an inverted triangle, with substantially more geographic space in the north than in the south. Among these thrushes, the migratory lineages breed in that northern, on average, larger space. The resident lineages instead currently occupy, on average, smaller geographic ranges, even in South America, where they are largely montane (Figure 2). Thus, larger breeding ranges among migrants, on average, should yield higher population sizes (N_e).

Second, climatic variability is also higher with increased latitude, often temporarily rendering vast swaths of northern North America unoccupiable to many long-distance migrant species (e.g. Colinvaux et al., 2000; Pielou, 1991). Thus, higher-latitude breeding occupancy should cause larger fluctuations in population size, meaning that variation in N_e will on average be higher among seasonal migrants. Finally, seasonal migration is likely to cause enhanced ecological (and in this case also geographic) release (i.e. in the occupancy of new niche space) in relation to resident relatives. Thus, as migratory lineages’ mobility enabled them to take advantage of seasonal resource blooms in ecosystems at higher latitudes and expand their breeding ranges (geographic and ecological expansion), their populations should, on average, have grown proportionally more and at a faster rate than sedentary lineages, thus achieving the first prediction.

Here, we test these predictions by reconstructing effective population sizes of these thrush lineages through time using whole-genome data and the pairwise sequentially Markovian coalescent (PSMC; Li and Durbin, 2011).

The focal variables of our hypotheses all lacked phylogenetic signal. Mean effective population sizes and their variation were both higher among migratory lineages, as predicted (Table 1; U=7 and 10, p<0.05 for both; one-tailed Mann-Whitney U-test). The degree of early population growth was also proportionally higher among migrants, as predicted (Table 1; U=9, p<0.05; one-tailed Mann-Whitney U-test), but the rate of this early growth was not different between the two groups (Table 1; U=21.5, p>0.05).

To examine why the degree of initial migrant population growth was higher but the rate of growth was not, we considered that this might be because that growth extended over a longer period of time. To our surprise, we found that these growth periods were remarkably long, ranging from 0.63 to 4.29 Myr and averaging 2.51 Myr (Table 1, Figure 3). Migratory lineages did have a longer initial period of growth (migrants mean deltaT = 3.10 Myr vs. resident mean deltaT = 1.72 Myr; Table 1; U=9, p<0.05).

Figure 3

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In addition to testing our hypotheses, our results reveal other important attributes of these songbirds. First, they appear to show few of the general population declines at the beginning of the last glacial period (~115 Kya) that Nadachowska-Brzyska et al., 2016, found among a global sampling of birds (Figures 4 and 5). Second, and more importantly, there is a general lack of temporal synchrony in historic population size changes (Figures 4 and 5), despite considerable geographic proximity and overlap of ranges (especially during the nonbreeding season). Finally, a pattern widely shared in the group is that most of the recent populations are below each lineage’s historic peak, and this trend predates the arrival of humans in the New World (Figures 4 and 5). A striking exception is C. ustulatus swainsonii, which has had remarkable long-term growth (Figure 5).

Figure 4

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Figure 5

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To our knowledge, this is the first study to contrast long-term effective population size changes among closely related species to test a priori hypotheses about the population effects of a major life-history trait; here, we focused on seasonal migration. This perspective offers several new insights into migrant demographics and evolutionary ecology. Migratory thrush lineages showed higher effective population sizes, greater population size variation, and proportionally larger initial population growth than resident relatives. A migratory life-history strategy thus imbues these lineages with population size characteristics that are fundamentally different, on average, from those of resident relatives.

Although migratory thrush lineages showed higher proportional initial growth than resident relatives, this was not achieved through rapid adaptation to new geographic and ecological opportunities as we predicted. Population growth in migrants and residents was positive early in the lineages’ histories (deltaT) in all cases but one (C. aurantiirostris), and it occurred over fairly long periods of time (Table 1, Figures 3 and 5). That this process initially (on average) involves millions of years of population growth in this group, apparently extended by a migratory life-history strategy that provided access to higher latitudes (Table 1; Appendix 1—table 1), is an insight from our study that should be examined in future work from a broader taxonomic perspective. While actual census population sizes would likely have shown considerable variation across this time, especially after the glacial cycles of the Pleistocene began ~2.6 Mya, the long-term effective population sizes of migrants tended to show steady increases, achieving peaks on average almost 3 Myr after the lineages’ PSMC inception (Figures 1 and 5; Table 1).

With deltaT being generally long but highly variable (Table 1), one can envision in this group a sort of ur-thrush trajectory in which unique, lineage-specific processes occur as each evolves, influenced by geography, ecological factors, and life-history strategy. These long periods of early growth are concordant with the initial expansion or adaptation phases of taxon cycles, a conceptual framework of lineage expansion and contraction over time through interactions between biogeography and evolutionary ecology (Pepke et al., 2019; Ricklefs and Bermingham, 2002; Ricklefs and Cox, 1972; Wilson, 1961).

Another noteworthy pattern widely shared in this group is that most recent populations are below each lineage’s historic peak (Figures 4 and 5). This, too, is reminiscent of taxon cycles (smaller populations in later stages), and this trend both predates the arrival of humans in the New World (Figure 5) and reflects a broader pattern of historic avian declines (Germain et al., 2023b). Yet another pattern is a general lack of temporal synchrony in historic population size changes, despite considerable geographic proximity and overlap of ranges (Figures 4 and 5). In their review of taxon cycles, Ricklefs and Bermingham, 2002, inferred from such a lack of similarity among lineages that each is in a unique population-environment relationship, responding idiosyncratically in a coevolutionary relationship with factors such as parasites, predators, pathogens, and competitors.

We attribute the higher variation in N_e among migrants to be the result of the relative instability of northern biomes compared with tropical ones through glacial-interglacial cycles (e.g. Colinvaux et al., 2000; Pielou, 1991).

The thrush lineages in our study are from the genus Catharus and its sister, the single species in the genus Hylocichla. These comprise Nearctic-Neotropic seasonal migrants and Neotropical residents. Among the latter, some lineages (C. aurantiirostris, occidentalis, frantzii, and mexicanus) have some populations that exhibit some short-distance migration—likely partial migration or hard-weather movements, either in elevation or with extreme northern populations moving south (Collar, 2005). These lineages thus comprise two groups, which for simplicity we will refer to as ‘seasonal migrants’ and ‘residents’: seasonal migrants with extensive latitudinal movements, and residents that are either wholly sedentary or with some individuals moving rather limited distances within the Neotropics. The eight migrant lineages are: H. mustelina, C. fuscescens, C. guttatus E (eastern lineage), C. guttatus W (western lineage), C. minimus, C. ustulatus swainsonii, C. u. ustulatus, and C. bicknelli. (Note that four of these lineages represent two deeply divergent lineages, each within what are currently considered two biological species, C. guttatus and C. ustulatus; Topp et al., 2013.) The six resident lineages are: C. aurantiirostris, C. fuscater, C. frantzii, C. gracilirostris, C. mexicanus, and C. occidentalis. Over the full evolutionary history of this Hylocichla-Catharus clade, changes among lineages occurred in the trait of long-distance migration (Outlaw et al., 2003; Voelker et al., 2013; Winker and Pruett, 2006; Figure 1). Our study does not assume that this trait was constant within each lineage after the speciation events when these switches occurred. Instead, we consider that for a major trait like long-distance migration, losses and gains at the full lineage level are likely to be infrequent, and that current evidence of trait distribution on a phylogeny provides a powerful comparative framework in which to elucidate the effects of that trait on other lineage attributes.

DNA was extracted from high-quality voucher specimens or blood samples for 14 thrush lineages (Appendix 1—table 1; data are available on NCBI-SRA, see Delmore and Winker, 2024). Whole-genome sequencing libraries were constructed using Nextera (Illumina) DNA Flex Library Prep kits, and libraries were sequenced on a NovaSeq S4 (Illumina, San Diego, CA, USA) using paired-end 150 bp reads. Reads were aligned to the C. ustulatus genome (inland subspecies, Reference bCatUst1, NCBI PRJNA613294) using bwa (mem algorithm with default settings, Li and Durbin, 2009). We did not use a maskfile. Identical treatment of all lineages in these respects should provide a strong foundation for a comparative study like this among close relatives. Resulting .sam files were converted to .bam format with samtools (Li et al., 2009); picardtools was used to clean, sort, and add read groups to .bam files (https://broadinstitute.github.io/picard/; RRID:SCR_006525). Between 97% and 98% of reads mapped to the reference for an average read depth of 23× (range 15.9–29.8×).

We analyzed whole-genomic data from the .bam files using the PSMC approach in the software package psmc (Li and Durbin, 2011; our code is available at doi 10.6084/m9.figshare.28828478). This analysis uses pairwise (allelic) estimates of coalescent times for each locus across the genome in a nonoverlapping manner, developing a distribution of times to most recent common ancestor, and the frequency of these coalescent events is inversely proportional to effective population size (Li and Durbin, 2011; Mather et al., 2020).

We used a generation time of 2.5 year, taken as an average among many of these species (Dellinger et al., 2020; Evans et al., 2020; Mack and Yong, 2020; Saether et al., 2005; Townsend et al., 2020; Whitaker et al., 2020), and a mutation rate of 2.3×10⁻⁹ mutations per site per year (Smeds et al., 2016). Single individuals represent lineage characteristics using this approach (Li and Durbin, 2011; Mazet et al., 2015; Nadachowska-Brzyska et al., 2015). Importantly for our focal questions, variations in these parameters do not affect the shape of the curve of population sizes (N_e) through time, but rather the values of the time and N_e estimates (Nadachowska-Brzyska et al., 2015). Being closely related and of similar size, we expect these taxa to have very similar generation times and mutation rates (e.g. Bird et al., 2020; Healy et al., 2014). However, seasonal migration can have an effect on survival and thus generation time, and Bird et al., 2020, produced modeled estimates for this group, providing an alternate approach. The basis for these modeled values is tiny, and the accuracy of the modeled results is uncertain, so we use these estimates with caution. But as a check on our results, we ran all of our analyses again with the variable generation times given by Bird et al., 2020. As expected, most of the differences are time-related, and, importantly, the overall results are not different (Appendix 1—table 2).

Hilgers et al., 2024, recently showed that artifactual peaks can occur due to recent time parameter settings in the PSMC program (Li and Durbin, 2011) that are often used as a default setting. They recommended that such recent peaks can be eliminated by breaking the first atomic time interval (typically 4) into either two (2+2) or four (1+1+1+1) smaller windows. We had four lineages that appeared to have such peaks: H. mustelina, C. fuscescens, C. guttatus E, and C. gracilirostris. For the latter three, breaking the recent period parameter into four windows (1+1+1+1) eliminated these peaks. For H. mustelina, smaller windows (2+2 and 1+1+1+1) made the recent peak even higher, so we have used the default setting (the most conservative result), as we did with the remaining taxa that did not show such peaks.

The PSMC method is not foolproof; e.g., aspects of selection, inbreeding, and isolation can affect population size estimates (Mather et al., 2020). No method of genomic population demographic reconstruction is known to be consistently and reliably accurate (Marchi et al., 2021), but uniform application of a powerful method like PSMC to genome-scale data in a closely related group of lineages can provide new insights into the evolutionary effects of major life-history strategies.

For all variables, PSMC output for times more recent than 50 Kya was ignored, because recent estimates of effective population size using this method are less reliable (Li and Durbin, 2011; Nadachowska-Brzyska et al., 2016). We consider this to be a conservative cutoff date. Our two focal variables, mean effective population size (N_e) and the coefficient of variation (SD/mean), were obtained from standard PSMC output. Our examination of early population growth involved deriving two additional variables from the PSMC output: degree of initial growth (1 - (N_trough/N_peak)), and rate of growth (degree/time period over which initial growth occurred; the latter we term deltaT; Figure 6).

Figure 6

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We note that estimates of the dates of divergence events in Catharus evolution vary by study, genetic marker, methodology, and parameter estimates such as generation time and mutation or substitution rates (Outlaw et al., 2003; Topp et al., 2013; Voelker et al., 2013; Winker and Pruett, 2006). Date estimates in our study that differ from previous work reflect these methodological issues, and here it is the relative values among lineages within our study that are most important.

We tested the assumption of phylogenetic independence of continuous characters obtained from the PSMC analyses using a phylogeny reconstructed using maximum likelihood from 1.5 Mb of autosomal sequence from chromosome 22 in MEGA X (Kumar et al., 2018; Figure 1), which produced the expected topology given prior work (e.g. Everson et al., 2019), and, for phylogenetic independence, the Abouheif-Moran approach (Abouheif, 1999; Münkemüller et al., 2012) as implemented in the R package adephylo (Jombart et al., 2010). For those variables not showing phylogenetic signal, we tested our hypotheses using a one-tailed Mann-Whitney U-test. This nonparametric test has the advantage of not requiring that particular assumptions are met (e.g. homogeneity of variance) nor precise measurements (thus accommodating uncertainty in our N_e estimates; Sokal and Rohlf, 1995; Whitlock and Schluter, 2015).

Data are available on NCBI-SRA at accession numbers PRJNA1112856 and PRJNA979932.

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Author details

1. Kevin Winker

   University of Alaska Museum and Department of Biology and Wildlife, Fairbanks, United States

   Contribution

   Conceptualization, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   For correspondence

   kevin.winker@alaska.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-8985-8104

2. Kira Delmore

   1. Department of Biology, Texas A&M University, College Station, United States
   2. Ecology, Evolution, and Environmental Biology, Columbia University, New York, United States

   Contribution

   Conceptualization, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4108-9729

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