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\begin{document}

\title{Revealing the Demographic History of the European nightjar (Caprimulgus
europaeus).}



\author[1]{George Day}%
\author[2]{Graeme Fox}%
\author[3]{Helen Hipperson}%
\author[3]{Kathryn Maher}%
\author[3]{Rachel Tucker}%
\author[3]{Gavin Horsburgh}%
\author[1]{Dean Waters}%
\author[2]{K. L. Durrant}%
\author[1]{Kathryn Arnold}%
\author[3]{Terry Burke}%
\author[3]{J. Slate}%
\affil[1]{University of York}%
\affil[2]{University of Nottingham}%
\affil[3]{The University of Sheffield}%


\vspace{-1em}



  
  \date{May 15, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
A species' demographic history provides important context to
contemporary population genetics and a possible insight into past
responses to climate change. An individual's genome provides a window
into the evolutionary history of contemporary populations. Pairwise
Sequentially Markovian Coalescent (PSMC) analysis uses information from
a single genome to derive fluctuations in effective population size
change over the last \textasciitilde{}5 million years. Here we apply
PSMC analysis to two European nightjar (Caprimulgus europaeus) genomes,
sampled in Northwest and Southern Europe, with the aim of revealing the
demographic history of nightjar in Europe. We successfully reconstructed
effective population size over the last 5 million years for two
contemporary nightjar populations. Our analysis shows that nightjar are
responsive to global climate change, with effective population size
broadly increasing under stable warm periods and decreasing during
cooler spans and prolonged glacial periods. PSMC analysis on the
pseudo-diploid combination of the two genomes revealed fluctuations in
gene flow between the populations over time, with gene flow ceasing by
the last-glacial maximum. This pattern of differentiation is in line
with the species utilising different refugia during glacial maxima. We
suggest that nightjar in Europe may show latitudinal (East-West) genetic
structuring as a result of reduced gene flow between different glacial
refugia. Finally, our results suggest that migratory behaviour in
nightjar likely evolved prior to the last-glacial maximum, with
long-distance migration seemingly persisting throughout the Pleistocene.
However, further genetic structure analysis of nightjar from known
breeding sites across the species' contemporary range is needed to fully
understand the extent and origins of range-wide differentiation in the
species.%
\end{abstract}%



\sloppy


Revealing the Demographic History of the European nightjar
(\emph{Caprimulgus europaeus} ).

Abstract

A species' demographic history provides important context to
contemporary population genetics and a possible insight into past
responses to climate change. An individual's genome provides a window
into the evolutionary history of contemporary populations. Pairwise
sequentially Markovian coalescent (PSMC) analysis uses information from
a single genome to derive fluctuations in effective population size
change over the last \textasciitilde{}5 million years. Here we apply
PSMC analysis to two European nightjar (\emph{Caprimulgus europaeus} )
genomes, sampled in Northwest and Southern Europe, with the aim of
revealing the demographic history of nightjar in Europe. We successfully
reconstructed effective population size over the last 5 million years
for two contemporary nightjar populations. Our analysis shows that
nightjar are responsive to global climate change, with effective
population size broadly increasing under stable warm periods and
decreasing during cooler spans and prolonged glacial periods. PSMC
analysis on the pseudo-diploid combination of the two genomes revealed
fluctuations in gene flow between the populations over time, with gene
flow ceasing by the last-glacial maximum. This pattern of
differentiation is in line with the species utilising different refugia
during glacial maxima. We suggest that nightjar in Europe may show
latitudinal (East-West) genetic structuring as a result of reduced gene
flow between different glacial refugia. Finally, our results suggest
that migratory behaviour in nightjar likely evolved prior to the
last-glacial maximum, with long-distance migration seemingly persisting
throughout the Pleistocene. However, further genetic structure analysis
of nightjar from known breeding sites across the species' contemporary
range is needed to fully understand the extent and origins of range-wide
differentiation in the species.

Keywords; PSMC, conservation genomics, refugia, \emph{Caprimulgus
europaeus} , demography

Introduction

Technological and methodological advancements have led to genomics
playing an increasingly important role in conservation biology
(Allendorf, 2017). Genomes provide a repository from which information
on historic changes in genetic diversity, effective population size
(\emph{N} \textsubscript{e}), speciation, and population structuring can
be inferred and used to track adaptations to environmental change
(Mather et al., 2019; Patil and Vijay, 2021). Specifically, sequence
data from a single aligned genome can be used to track historic
demographic patterns exhibited by a species or population (Li and
Durbin, 2011). Pairwise sequentially Markovian coalescent (PSMC)
analysis is a powerful tool which infers ancestral changes in\emph{N}
\textsubscript{e} from a single genome. The analysis applies
hidden-Markov modelling to the coalescence framework, treating a genome
as multiple historic genealogies partitioned by recombination events
(see Li and Durbin, 2011; Mather et al., 2019 for detailed explanation
of the method). PSMC analysis has been used to determine ancestral (up
to \textasciitilde{} 5 Mya) population trends and track time scales of
species and population divergences (e.g. \emph{Ficedula} flycatchers;
Nadachowska-Brzyska et al., 2016, \emph{Catharus} thrushes;
Termignoni-Garcia et al., 2022), as well as shedding light on periods of
gene flow among otherwise genetically structured populations (Sato et
al., 2020). PSMC analysis can be applied to pseudo-diploid genomes
constructed from two individuals from different populations to
investigate changes in gene flow and timing of divergence (Li and
Durbin, 2011; Prado-Martinez et al., 2013; Sato et al., 2020). For
example, PSMC applied to pseudo-diploid genomes from three Golden eagle
(\emph{Aquila chrysaetos} ) subspecies revealed the timing of divergence
and gene flow change among the subspecies over a time scale of
\textasciitilde{}11 million years (Sato et al., 2020). When combined
with geological and paleoclimate data, PSMC analysis can reflect a
species' past ability to adapt to environmental change, and how
different populations, or species, have been affected by broad climate
trends (Nadachowska-Brzyska et al., 2015; Mather et al., 2019).
Understanding a species' response to past environmental change allows
for predictions to be made regarding vulnerability to contemporary and
future climate change and how this may vary interspecifically under
different life histories (Kozma et al., 2018, 2016; Chattopadhyay et
al., 2019), or between populations at different locations across a
species range (Sato et al., 2020).

Over the past \textasciitilde{}5 million years the global climate has
fluctuated dramatically, oscillating between periods of extensive
glaciation and interglacial warming. Long glacial and short interglacial
periods during the mid-Pleistocene revolution (MPR; \textasciitilde{}1
Mya - 450 Kya) resulted in cooler interglacial temperatures than those
presently recorded (Pisias and Moore, 1981). However, throughout the
Mid-Brunhes Event (MBE; \textasciitilde{}450-110 Kya), interglaciations
were characterised by warmer temperatures, with comparatively less
severe glacial periods compared with the mid-Pleistocene (Candy et al.,
2010; Barth et al., 2018). During the last glacial maxima (LGM;
\textasciitilde{}110 Kya) the Fennoscandian ice sheet covered much of
Western and North Western Europe, restricting temperate zones to
contemporary Southern Eurasia (Denton and Hughes, 1981). These
significant shifts in global climate have been shown to correspond with
fluctuations in historic population size in a number of species
(Nadachowska-Brzyska et al., 2015; Kozma et al., 2016, 2018). Over
periods of cooling, temperate Western-Palearctic species will have
likely been restricted to southern refugia in Europe (Iberia, Apennines,
and Balkans; Hewitt, 1999; but see Thorup et al., 2021). Restriction to
different glacial refugia and subsequent northward expansion during
interglacial periods have been linked to contemporary population
structure and subspecies divergence in multiple species, including birds
and aerial insects (e.g. Schmitt, 2007; Hansson et al., 2008;
Nadachowska-Brzyska et al., 2016; de Greef et al., 2022). Occupation of
separate glacial refugia by different populations is thought to have
driven spatial patterns of genetic differentiation in temperate species,
with many Palearctic birds exhibiting contemporary East - West patterns
in genetic structure and speciation (e.g. Hansson et al., 2008; Lombardo
et al., 2022; V\selectlanguage{ngerman}äli et al., 2022).

The European nightjar (\emph{Caprimulgus europaeus} ), henceforth
nightjar, is a long-distance migratory bird with a temperate breeding
distribution ranging from Northwest Europe through to East Asia
(BirdLife International, 2022). Nightjar likely originated from the
Afrotropics (Han et al., 2010), with the most closely related extant
species being an Afrotropic resident (Rufous-cheeked nightjar
\emph{Caprimulgus rufigena} ) (Han et al., 2010). Nightjar are composed
of six subspecies (\emph{C.e. europaeus} ,\emph{meridionalis} ,
\emph{sarudnyi} , \emph{unwini} , \emph{plumipes} ,\emph{dementievi} )
broadly following an East-West clinal distribution (Cleere, 1998; Cleere
et al., 2021), although mtDNA analysis has found little association
between genetic variation and current subspecies classifications
(Schweizer et al., 2020). Based on mtDNA analysis, Larsen et al., (2007)
proposed that nightjar migratory behaviour evolved at the end of the LGM
with glacial expansion and cooling temperatures likely restricting the
availability of temperate breeding habitat in Eurasia. However, it seems
unlikely that nightjar migratory behaviour developed post-LGM; with
evidence of a range-wide phylogenetic divergence in nightjar between
Eastern and Western clades, likely originating in \textasciitilde{}2.5
Mya, predating the LGM (Schweizer et al., 2020). Suitable breeding
habitat would have been available across temperate Eurasia throughout
warm interglacial periods, with breeding birds able to seek refuge in
Mediterranean or North Africa during glacial periods (Ponti et al.,
2020). If nightjars exhibited an Afro-European migration strategy
pre-LGM, paleoclimatic-driven periods of dramatic\emph{N}
\textsubscript{e} change should be evident from PSMC analysis, following
population expansion and contraction from refugia during global warming
and cooling, respectively.

Nightjar have been subject to population decline across the NW of their
range (Conway et al., 2007; Langston et al., 2007). Although current
population trends are not a cause for concern (IUCN: Least Concern;
BirdLife International, 2022), nightjar migratory behaviour and habitat
specialisation leave them sensitive to environmental change as seen in
other taxa ((Case et al., 2015; Bairlein, 2016). Its ancestral
demographic history may leave nightjar vulnerable to contemporary and
future environmental change, if, for example, populations have been
subject to bottlenecks resulting in genetic variation depletion (Bürger
and Lynch, 1995; Frankham et al., 2010; Nadachowska-Brzyska et al.,
2015; Hohenlohe et al., 2021). The reference genome for the European
nightjar was sequenced and assembled in 2021 from a bird captured in
Southern Europe during the spring migration period (Secomandi et al.,
2021). Here we use this published genome alongside a novel Pacbio HIFI
sequence, sequenced by us, sampled from a population from the extreme
North-western range limit in the UK. We apply PSMC analysis to determine
the ancestral demography of nightjar from two contemporary populations
in Europe to estimate the historic \emph{N} \textsubscript{e} change
over time from 10 Kya to 5 Mya. Specifically, we aimed to;

\begin{enumerate}
\tightlist
\item
  Investigate historic \emph{N} \textsubscript{e} trends of two
  contemporary nightjar populations relative to past climate
  fluctuations. We hypothesised that, in both populations, decreases
  in\emph{N} \textsubscript{e} will have followed periods of global
  cooling (i.e LGM (110--10 Kya)), as well as the rapid global climate
  oscillations of the MPR (\textasciitilde{}1.2 Mya - 450 Kya). We
  predict that \emph{N} \textsubscript{e} increased following periods of
  warming (i.e the warmer interglacial periods during the MBE (430--110
  Kya));
\item
  Compare \emph{N} \textsubscript{e} trends from the two contemporary
  populations and a pseudo-diploid combined genome to examine divergence
  between the two populations, addressing the hypothesis that the two
  populations will have diverged during the LGM.
\item
  Examine temporal \emph{N} \textsubscript{e} patterns to investigate
  the evolution of migratory behaviour in nightjar. We hypothesise that
  nightjar will have exhibited fluctuating \emph{N} \textsubscript{e}
  and population divergence before the LGM, suggestive of long distance
  migratory behaviour arising prior to the LGM.
\end{enumerate}

Methods

Sampling Genetic Material, Extraction \& Sequencing

A female nightjar from a breeding population in the East of England
(latitude: 53.531, longitude: -0.953) was used to extract DNA for
sequencing (population henceforth referred to as NW Europe or NWE). The
bird died on 7th August 2019, so was assumed to have been part of the
breeding population and not moving through on migration, with spring and
autumn migration for nightjar occurring between April - June and late
August and September respectively. High molecular weight DNA was
extracted from a blood clot in the individual's heart using a modified
version of the phenol-chloroform protocol outlined by Sambrook et al.,
(1989). Full extraction protocol details can be found in the supporting
information. The high molecular weight DNA was then sent to the Centre
for Genomics Research facility at the University of Liverpool for PacBio
HiFi sequencing library preparation. The reference genome (for assembly
details see Secomandi et al., 2021) and 10x Genomics Illumina sequence
reads were sequenced from a single female nightjar captured in South
West Italy in spring 2021 (latitude: 40.794, longitude: 13.427) provided
by Secomandi et al., 2021) (population henceforth referred to as South
Europe or SE).

Genome Alignment

Minimap (minimap2 v. 2.18-r101; Li, 2018) and BWA mem (arXiv:1303.3997v1
{[}q-bio.GN{]}; Li, 2013) software were used to align the reads from the
NWE (HIFI reads) and SE (10 x Illumina reads) nightjars to the reference
genome, respectively. Unmapped reads were then filtered from both files
leaving only mapped reads.

PSMC Analysis

\selectlanguage{english}\selectlanguage{english}To understand ancestral changes in \emph{N} \textsubscript{e} a
Pairwise Sequential Markovian Coalescent (PSMC) method was applied to
the mapped bam files from the HIFI and 10x Illumina reads, for which the
average coverage was 30.5x and 88.1x respectively. First, consensus
sequences were generated from the aligned indexed bam files from the
HIFI and 10x reads using SAMtools mpileup command and vcfutils.pl as per
Li and Durbin, (2011) (https://github.com/lh3/psmc). Consensus files
were generated for each chromosome independently before being combined.
For the Hifi data, from the NWE genome, four chromosomes (chromosome
numbers; 3, 5, 25, and 32) failed to produce consensus files and reduced
representations for two of the four chromosomes (3 and 5) were used,
with two chromosomes (25 and 32) excluded from the analysis. This
resulted in a loss of only \textasciitilde{}1\% of genomic material for
analysis. Sex chromosomes were also excluded from the analysis for both
HIFI and 10x genomes. This resulted in 89.8\% of the NWE genome and
90.8\% of the SE genome being retained for downstream analysis.
Consensus files were then filtered for read depth and quality. In order
to reduce the effects of low coverage and collapsed regions, consensus
files were filtered by excluding reads \textasciitilde{} \textless{} \selectlanguage{english} 1/3 
and \textgreater{}2x mean depth. This resulted in removing reads
\textless{}10x and \textgreater{}60x for the Hifi data and \textless{}30
and \textgreater{}120x for the 10x reads, respectively. Finally,
filtering for base quality scores of \textless{}20 for the HIFI reads
and 10x reads were applied.

The PSMC analysis was then run on the combined consensus .fastq files
using the PSMC software package (Li and Durbin, 2011;
https://github.com/lh3/psmc). PSMC parameters used by
Nadachowska-Brzyska et al., (2015) for demographic analysis of 38
different bird species were chosen for our analysis, where ``-N'' (30)
is the number of iterations, ``-t'' (5) is the maximum time to the most
recent common ancestor, ``-r'' (5) is the initial mutation/
recombination rate (\emph{r} = \selectlanguage{greek}θ/ρ\selectlanguage{english}) and ``-p'' (4+30*2+4+6+10) denotes
the distribution of atomic time intervals. In order to determine
variation in PSMC predictions, the data were bootstrapped 100 times.

PSMC analysis can be applied to pseudo-diploid genomes formed from the
fusing of haploid genomes from two separate populations or species. When
PSMC is applied, deviations in \emph{N} \textsubscript{e} trends of the
pseudo-diploid genome from the two parent populations can denote
reductions in gene flow and points of divergence between the two
populations signified by the \emph{N} \textsubscript{e} of the
pseudo-diploid genome tending towards infinity (reducing coalescence
events leading to an apparent increase in Ne) (Li and Durbin, 2011;
Prado-Martinez et al., 2013; Sato et al., 2020). To determine the timing
of divergence between the two sampled populations a pseudo-diploid
genome was created by first generating pseudo-haploid genomes through
randomly sampling heterozygous alleles using Seqtk V1.3 `randbase' (-r)
(\emph{https://github.com/lh3/seqtk}; accessed Oct 25th, 2022) from both
consensus sequence files as generated above. Pseudo-haploid files were
then merged using Seqtk `mergefa' to produce a single pseudo-diploid
genome consensus file. PSMC analysis was then applied to the
pseudo-diploid genome as described above.

Finally, all PSMC results were plotted using gnuplot
(\emph{http://www.gnuplot.info/}) with the -R flag applied to export
.txt files. In order to plot the PSMC results, the data must be scaled
to real-time by using mutation rate and generation time (Li and Durbin,
2011). A generation time of 2 (-g 2) was selected for nightjars
following that used for Chuck-will's-widow (\emph{Antrostomus
carolinensis} ) (Nadachowska-Brzyska et al., 2015), with birds able to
breed in their second year (Cramp and Simmons, 1985). As no
species-specific mutation rates were available for European nightjar, a
mutation rate of \selectlanguage{greek}μ \selectlanguage{english}= 4.6 \selectlanguage{ngerman}× 10\textsuperscript{--9}was used as per Sato
et al., (2020). The mutation rate was initially estimated for collared
flycatchers (\emph{Ficedula albicollis} ) (Smeds et al., 2016), but has
since been successfully applied to other passerines (Ericson et al.,
2022), raptors (Hanna et al., 2017; Sato et al., 2020) and waterfowl
species (Ericson et al., 2017).

Results and Discussion

In this study we explored the demographic history of two modern nightjar
populations (NW and S Europe). Using PSMC we found significant
fluctuation in \emph{N} \textsubscript{e} in European nightjar over the
last 5 million years, coinciding with major paleoclimatic events
(Fig1a). The timing of initial divergence between the two nightjar
populations was \textasciitilde{}1.2Mya (Fig1A), with final divergence
found to coincide with the LGM (\textasciitilde{}110 Kya) (Fig1B).

Demographic History of European Nightjar

Our analysis suggests that nightjar have experienced significant
fluctuations in \emph{N} \textsubscript{e} over the last
\textasciitilde{}5 million years. Two of the most significant\emph{N}
\textsubscript{e} changes occurred during the Pleistocene, with both
populations (NWE \& SE) increasing throughout the early Pleistocene to a
maximum \emph{N} \textsubscript{e} of \textasciitilde{}780,000
individuals, before decreasing to \textasciitilde{}570,000 individuals
by 600 Kya during the MPR (\textasciitilde{}1 Mya - 450 Kya; Fig 1a). As
hypothesised, the \emph{N} \textsubscript{e} of both populations then
increased throughout the MBE to \textasciitilde{} 1 million individuals
by \textasciitilde{}240 Kya (Fig 1a). Both populations then decreased
in\emph{N} \textsubscript{e} until \textasciitilde{}100 Kya (Fig 1a). At
the onset of the LGP, populations exhibited a peak in\emph{N}
\textsubscript{e}, followed by a steep decline as the LGP progressed
(Fig 1a). The \emph{N} \textsubscript{e} of the two populations then
diverged in size (see below).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Fig 1 PSMC plots: A) NW Europe (Red line) and S Europe (Blue line)
sampled European nightjar, as well as pseudo-diploid genome of NW/S
Europe birds (dashed line), depicting demographic history
(\emph{N}\textsubscript{e} change) over the last \textasciitilde{}5
million years (bp), scaled with a mutation rate of 4.6 \selectlanguage{ngerman}×\selectlanguage{english} 10\selectlanguage{english}-9 per site
and generation time of 2 years. The x-axis depicts time (in years) on a
log scale, with the y-axis showing effective population size. B)
Estimated \emph{N}\textsubscript{e} for pseudo-diploid genome only
(dashed line). Approximate timings of significant periods of global
climate change are shown by shading along the x-axis. Light blue shading
= last glacial period (LGP), orange shading = Mid-Brunhes event (MBE),
and dark blue shading = Mid-Pleistocene Revolution (MPR).

Overall, historic nightjar \emph{N} \textsubscript{e} in Europe
decreased and increased during periods of cooling and warming
respectively (Fig 1a). Nightjar are insectivorous habitat specialists
requiring clear fell, heathland, or woodland edge to breed (Cleere,
1998), feeding primarily on Lepidoptera (Mitchell et al., 2022). With
reductions in temperature and glacial expansion, prey and habitat
availability will have been constrained to more southerly latitudes
(Schmitt, 2007), likely corresponding with a reduction in nightjar
distribution and thus \emph{N} \textsubscript{e}. For example, the
decrease in nightjar \emph{N} \textsubscript{e} \textasciitilde{}1.2 Mya
-- \textasciitilde{} 600 Kya (Fig1a) overlapped the MPR
(\textasciitilde{}1 Mya - 450 Kya), which was characterised by shortened
interglacial periods and cooler average temperatures which restricted
the northward resurgence of temperate animal and plant communities
(Pisias and Moore, 1981; Head and Gibbard, 2015). Conversely, warmer
temperatures will have likely increased the availability of suitable
habitat across northerly latitudes (Schmitt, 2007; Candy et al., 2010).
Indeed the stable climate of the late Pliocene and early Pleistocene
(Head and Gibbard, 2015), as well as the short glacial and warm
interglacial periods of the MBE (Candy et al., 2010; Barth et al., 2018)
associated with increases in nightjar\emph{N} \textsubscript{e} in our
study (Fig 1a). Similarly, the dramatic\emph{N} \textsubscript{e}
increase during the late Pleistocene prior to the LGP (Fig 1a) coincided
with the Eemian warm phase (\textasciitilde{}127 Kya; Bergoeing, 2017),
which was characterised by the expansion and persistence of temperate
plant communities into northerly latitudes (Van Andel and Tzedakis,
1996; Sanchez Goni et al., 1999; Lisiecki and Raymo, 2005). Following
similar trends exhibited by other Afro-Palearctic migrants (i.e
\emph{Ficedcula} flycatchers; Nadachowska-Brzyska et al., 2016),
\emph{N} \textsubscript{e} of both nightjar populations greatly
decreased as the LGP continued, likely restricting nightjar to Southern
European refugia (Schmitt, 2007; Lombardo et al., 2022) or North Africa
(Thorup et al., 2021). Bootstrapping indicates caution is required
regarding exact timings of \emph{N} \textsubscript{e} fluctuations
(Supporting Information). However, PSMC analysis in other Caprimulgids
(i.e.: Chuck-will's-widow) and Afro-Palearctic migrants (i.e.: Common
cuckoo,\emph{Cuculus canorus} ) (Nadachowska-Brzyska et al., 2015), have
shown similar fluctuating trends in\emph{N} \textsubscript{e} over the
same timeframe, suggesting that the estimated timings of \emph{N}
\textsubscript{e} change with paleoclimatic events in our study are
reasonable.

Population Structure and Divergence in Nightjar

When applied to a pseudo-diploid genome derived from two different
populations, PSMC analysis can be used to determine the timing of
population divergence. This is signalled by the pseudo-diploid\emph{N}
\textsubscript{e} diverging from the two parent populations and tending
towards infinity (Prado-Martinez et al., 2013). This occurs because
coalescence events between the two populations were severely reduced or
ceased, leading to an increase in\emph{N} \textsubscript{e} as
interpreted by the analysis. In our analysis, the pseudo-diploid
\emph{N} \textsubscript{e} trend appeared to diverge from the NWE and SE
populations \textasciitilde{}1.2 Mya (Fig 1a). However, true divergence
(the point at which\emph{N} \textsubscript{e} tends to infinity) does
not occur until \textasciitilde{}40 Kya (Fig 1b).Even taking into
account f the \textasciitilde{}35Ky error window suggested by the
bootstrapping (Supporting Information), the main divergence event
between the NWE and SE populations occurred within the LGP (Fig 1b).

The two modern populations used in this study are spatially distant and
behaviorally distinct as they exhibit different migration strategies
(Evens et al., 2017). Nightjars breeding in Western Europe typically
migrate through Iberia during spring migration, with Eastern breeders
migrating through Italy and SE Europe (Evens et al., 2017; Norevik et
al., 2017). In other trans-Saharan migrants, such migratory behaviour is
thought to be ancestral and `hard wired' into populations, likely
predating the Pleistocene (Thorup et al., 2021). Although the SE bird in
our study was trapped during the spring migration period (Secomandi et
al., 2021), it is probable that the individual's breeding population was
located within Central to Eastern Europe as suggested by recent tracking
studies (e.g., Norevik et al., 2017).

As in other migratory Palearctic birds (e.g., Lesser
whitethroat\emph{Sylvia curruca} ; Olsson et al., 2013; Pied wagtail
\emph{Motacilla alba} ; Li et al., 2016), we suggest that nightjar may
exhibit East-West genetic structuring, but investigation is required.
Results from MtDNA analysis have suggested that nightjar can be divided
into Eastern and Western lineages, with divergence being deeper (c. 2.9
Mya) (Schweizer et al., 2020) than that suggested by our PSMC analysis
(initial divergence \textasciitilde{}1.2 Mya, cessation of gene flow
\textasciitilde{}40 Kya +- 35 Ky; Fig 1). However, the samples
contributing to Schweizer et al.'s (2020) work spanned a much broader
latitudinal range (encompassing W Europe to Asia) than those in our
study and likely represented a deeper divergence. Much of the structure
in contemporary Palearctic and Nearctic animal populations are
fundamentally linked to past glacial and interglacial cycles, which have
led to the contraction of temperate breeding populations into Southern
refugia, and subsequent northward recolonisation during warmer
interglacial periods (Hewitt, 2004; Nadachowska-Brzyska et al., 2016;
Yao et al., 2022; de Greef et al., 2022). Previously panmictic
populations may become isolated from one another in different refugia,
during periods of glaciation, leading to genetic differentiation
post-interglacial expansion (Hewitt et al., 2001).

Considering the timings of gene flow reduction and divergence between
the two populations it is likely that the ancestral states of both
populations utilised different refugia over historic glacial periods and
most recently the LGM. Owing to the apparent divide in contemporary
migration routes we suggest that the NWE population will have utilised
the Iberia refugium and the SE sampled population the Italian refugia
during glacial periods. Whilst most Western Palearctic avifauna (117 out
of 131 studied by Parau and Wink, 2021) show admixture among
populations, our study suggests that nightjar exhibit genetic structure
within their Eurasian breeding range. With the sampling information
available our results tentatively reflect East-West structuring in the
European nightjar population, likely diverging during isolation in
different glacial refugia during periods of glaciation. However, it
should be noted that the SE individual may belong to the Southern
European \emph{C.e.meridionalis} subspecies and instead our results
might reflect divergence between \emph{C.e.meridionalis} and the
nominate \emph{C.e.europaeus} (NWE individual) subspecies. Nevertheless,
validity of the \emph{C.e.meridionalis} subspecies remains questionable,
with as yet no genetic evidence to support the subspecies status (Del
Hoyo et al., 2014; BirdLife International, 2022). Nightjars of the
nominate race\emph{C.e.europaeus} migrate through Italy and SE Europe
(Evens et al., 2017; Norevik et al., 2017). Given the individual used in
this study was sampled during spring migration, it is likely that the
bird was migrating to breeding grounds at a higher latitude and belongs
to\emph{C.e.europaeus} . However, further work is required to resolve
population genetic structure across the species range, and there is a
wider need to resolve the molecular phylogeny of European nightjar and
its subspecies.

Evolution of Migratory Behaviour in Nightjar

Following the timeline proposed by our study (Fig 1), it seems unlikely
that nightjar migratory behaviour developed post-LGM as suggested by
Larsen et al., (2007). The dramatically fluctuating \emph{N}
\textsubscript{e} prior to the LGM throughout the Pleistocene may
reflect periods of significant population expansion and contraction
associated with climate driven changes in temperate breeding habitat
availability (Ponti et al., 2020). If nightjar had exhibited a sedentary
Afrotropic distribution prior to the LGM we might expect to see less
severe fluctuation in\emph{N} \textsubscript{e} relative to global
climate change (Kimmitt et al., 2023; but see Speckled mousebird;
\emph{Colius striatus} in Nadachowska-Brzyska et al., 2015). Similarly,
if migratory behaviour had not developed until \textasciitilde{}20,000
ya, we would expect divergence between populations to occur exclusively
post-LGM. However, our results highlight that whilst gene flow appeared
to cease between the NWE and SE populations towards the LGM (Fig 1b),
population divergence occurred as early as \textasciitilde{}1.2 Mya (Fig
1a), with subsequent episodes of mixing ensued during periods of range
expansion. Our results suggest that long-distance migratory behaviour in
nightjar evolved prior to the LGM and was maintained throughout the
Pleistocene, likely predating the initial divergence 1.2Mya recorded in
our study (Fig 1a). This is corroborated by the deeper divergence
(2.9Mya) between range-wide East-West lineages recorded by Schweizer et
al., (2020), which may indicate a migratory divide. Our results
contribute to the growing consensus that long distance migratory
behaviour in contemporary Western-Palearctic avifauna predates the LGM
(i.e. Ponti et al., 2020; Ralston et al., 2021; Thorup et al., 2021;
Kimmitt et al., 2023).

Limitations of PSMC analysis

Results of PSMC analysis are influenced by the scaling applied to plots,
determined by mutation rate and generation time (Li and Durbin, 2011;
Mather et al., 2019). However), the overall pattern of\emph{N}
\textsubscript{e} change will remain the same independent of scaling
parameters (Nadachowska-Brzyska et al., 2016). Data on both of these
parameters are often limited for study species (e.g. see Sato et al.,
2020; Chattopadhyay et al., 2019; Ericson et al., 2022), including
nightjar. Thanks to the wealth of PSMC studies over a multitude of avian
taxa (e.g., Nadachowska-Brzyska et al., 2015, 2016; Kozma et al., 2018;
Sato et al., 2020; Bruniche-Olsen et al., 2021) parameters suited to a
wide range of avifauna can be selected, such as those used in our study
as per Sato et al., (2020). Therefore, whilst caution must be applied
concerning the timings and magnitudes of \emph{N} \textsubscript{e}
change, as highlighted by bootstrapping (see Supporting Information), we
believe that PSMC analysis provides a valuable method to associate
broad\emph{N} \textsubscript{e} trends concurrent climate cycles.

Conclusion

PSMC is a useful tool to characterise past demography and resolve timing
of species and population differentiation, processes which underlie
contemporary genetic and demographic patterns. Results from our PSMC
analysis suggest that nightjar were highly susceptible to climatic
variation, increasing in number during warm interglacials and long
periods of relative climate stability. The historical context provided
by our research suggests that the current climate best suits nightjar.
Limitations on population size are likely primarily anthropogenic, with
humans responsible for the mass deforestation and agriculturalisation of
Europe from 8.2 Kya (Kaplan et al. 2009). Habitat loss, fragmentation,
degradation and disturbance are reported as the primary drivers of
contemporary population reduction in nightjar (Langston et al., 2007;
Lowe et al., 2014; Ashpole et al., 2015). Although nightjar have been
shown to persist through historic climate change, contemporary
anthropogenic pressures may reduce the ability of the species to adapt
to the current rapidly changing climate.

As in multiple other Palearctic and Nearctic birds, our analysis
suggests that restriction to different refugia during glacial cycles may
have driven divergence within the European population of nightjar. Our
analysis suggests a complete cessation of gene flow between the two
populations by \textasciitilde{}14 Kya during the LGM, although mixing
under current interglacial conditions is likely. Genetic structure
within the European population has significant conservation
implications, potentially delimiting the current population into smaller
conservation units. Our results also suggest that migratory behaviour in
nightjar evolved prior to the LGM, persisting throughout the
Pleistocene. However, further research is needed to understand the
spatial context of this apparent range-wide genetic structure, as well
as to clarify timing of long-distance migration evolution, as well as
current taxonomic assignations. We recommend a range-wide molecular
analysis, including population genetics, of nightjar to better
understand the extent and origins of divergence within the species. Such
research would also aid ongoing taxonomic uncertainties surrounding
subspeciation in nightjar (Schweizer et al., 2020). Finally, while
caution is needed, here PSMC analysis has provided a useful insight into
the demographic past of nightjar in Europe, which has highlighted the
nightjar population genetics as a valuable future research direction.

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