Wenqing Zang, Zhiyong Jiang, Per G.P. Ericson, Gang Song, Sergei V. Drovetski, Takema Saitoh, Fumin Lei, Yanhua Qu. 2023: Evolutionary relationships of mitogenomes in a recently radiated Old World avian family. Avian Research, 14(1): 100097. DOI: 10.1016/j.avrs.2023.100097
Citation: Wenqing Zang, Zhiyong Jiang, Per G.P. Ericson, Gang Song, Sergei V. Drovetski, Takema Saitoh, Fumin Lei, Yanhua Qu. 2023: Evolutionary relationships of mitogenomes in a recently radiated Old World avian family. Avian Research, 14(1): 100097. DOI: 10.1016/j.avrs.2023.100097

Evolutionary relationships of mitogenomes in a recently radiated Old World avian family

Funds: This research was funded by the National Natural Science Foundation of China (NSFC32020103005), the Third Xinjiang Scientific Expedition and Research (XIKK) (2022xjkk0205) and Second Tibetan Plateau Scientific Expedition and Research (2019QZKK0501)
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  • Corresponding author:

    Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China. E-mail address: quyh@ioz.ac.cn (Y. Qu)

  • Received Date: 03 Feb 2023
  • Rev Recd Date: 19 Mar 2023
  • Accepted Date: 21 Mar 2023
  • Available Online: 14 Jun 2023
  • Publish Date: 30 Mar 2023
  • Environmentally heterogeneous mountains provide opportunities for rapid diversification and speciation. The family Prunellidae (accentors) is a group of birds comprising primarily mountain specialists that have recently radiated across the Palearctic region. This rapid diversification poses challenges to resolving their phylogeny. Herein we sequenced the complete mitogenomes and estimated the phylogeny using all 12 (including 28 individuals) currently recognized species of Prunellidae. We reconstructed the mitochondrial genome phylogeny using 13 protein-coding genes of 12 species and 2 Eurasian Tree Sparrows (Passer montanus). Phylogenetic relationships were estimated using a suite of analyses: maximum likelihood, maximum parsimony and the coalescent-based SVDquartets. Divergence times were estimated by implementing a Bayesian relaxed clock model in BEAST2. Based on the BEAST time-calibrated tree, we implemented an ancestral area reconstruction using RASP v.4.3. Our phylogenies based on the maximum likelihood, maximum parsimony and SVDquartets approaches support a clade of large-sized accentors (subgenus Laiscopus) to be sister to all other accentors with small size (subgenus Prunella). In addition, the trees also support the sister relationship of P. immaculata and P. rubeculoides ​+ ​P.atrogularis with 100% bootstrap support, but the relationships among the remaining eight species in the Prunella clade are poorly resolved. These species cluster in different positions in the three phylogenetic trees and the nodes are often poorly supported. The five nodes separating the seven species diverged simultaneously within less than half million years (i.e., between 2.71 and 3.15 million years ago), suggesting that the recent radiation is likely responsible for rampant incomplete lineage sorting and gene tree conflicts. Ancestral area reconstruction indicates a central Palearctic region origin for Prunellidae. Our study highlights that whole mitochondrial genome phylogeny can resolve major lineages within Prunellidae but is not sufficient to fully resolve the relationship among the species in the Prunella clade that almost simultaneously diversify during a short time period. Our results emphasize the challenge to reconstruct reliable phylogenetic relationship in a group of recently radiated species.

  • There often is competition for limited resources when species live in the same area, especially in the breeding season. Individuals need suitable nest sites (Martin, 1993) and sufficient food resources for survival and reproduction (Martin, 1987). They also want to avoid losses caused by interference competition (Minot and Perrins, 1986; review in Dhondt, 2012).

    A large number of experimental studies have shown that intra- and inter-specific competition can reduce breeding success and population size (Schoener, 1983; Finch, 1990; Gurevitch et al., 1992). House Wrens (Troglodytes aedon) that co-habit with Tree Swallows (Tachycineta bicolor) have lower reproductive success rate than wrens living in swallow-free plots (Finch, 1990). The first egg laying date of Eurasian Blue Tits (Cyanistes caeruleus) is affected by intra-specific and inter-specific interference, but no such relationship has been found in a closely related species, the Great Tit (Parus major, Møller et al., 2018). The reproductive output of the central nest is adversely affected by their short-distance neighbors containing conspecifics but not heterospecific ones (Deeming et al., 2017). Most studies have concentrated on the breeding behavior of conspecific or heterospecific neighbors to evaluate intra- and inter-specific competition. Breeding synchrony may also be an important environmental indicator as needs for resources vary hugely as nestlings grow. Competition might lead greater intervals among neighbors in terms of delay in breeding and might have effects on reproduction in neighbors.

    Some species are sufficiently abundant and show no obvious spatial heterogeneity, while others are range-restricted and influenced by both habitat composition and local environment (Laube, 2011). Regarding the question of what affects the size of the distribution, most studies concentrated on non-behavioral environmental or spatial factors (e.g. Szabo et al., 2009; Boucher-Lalonde et al., 2014) but few have investigated behaviors. Zhang et al. (2019) attributed the difference in the distribution size of Cinereous (Parus cinereus) and Varied Tits (Sittiparus varius) to their personalities because the relatively wider-spread Cinereous Tit is more exploratory, active, and risk-prone than the Varied Tit, a locally distributed species, is. We predict that anti-interference capability of the narrowly-distributed Varied Tit may be weaker than that of the relatively widely-distributed Cinereous Tit.

    Artificial nestboxes are widely used in studies of birds, particularly in field research, because they attract breeding birds. As a result, it is an effective tool to gather reproduction data (Møller et al., 2014) to study demographic shift, life history evolution, quantitative genetics, and sexual selection (Evans et al., 2002). To ensure sufficiency, usually large numbers of artificial nestboxes are provided, but only a small number are occupied every year (Mänd et al., 2005).

    In this study, we measured intra- and inter-specific spatial distribution of used artificial nestboxes and investigated whether the intersection of neighbors’ living area affected the breeding outcome of the focal breeding pair. Two hole-nesting passerine species, Cinereous Tit and Varied Tit, were concentrated on. Based on which we proposed three hypotheses: (1) the distance of nests within species is longer than that between them, (2) conspecific and heterospecific neighbors both have a negative impact on the focal nest, and (3) the range-restricted species, Varied Tits, are more vulnerable to neighbor influence than the relatively wider-spread Cinereous Tits.

    Starting from 2016, this study was carried out every year from early April through mid-July for three consecutive years in Liaoning Xianrendong National Nature Reserve (39°54ʹ‒40°03ʹ N, 122°53ʹ‒123°03ʹ E). Yet ten years before this study began artificial nestboxes had already been installed and supplemented or replaced every year. All boxes had a base dimension of 15 ​cm ​× ​15 ​cm and a height of 30 ​cm. The opening was round, with a diameter of 3 ​cm or 3.5 ​cm, and located about 7 ​cm below the box cover. The artificial nestboxes were hung mainly on Pinus densiflora, Quercus mongolica and Pinus koraiensis, at a height of 2–3 ​m from the ground.

    All boxes were hung randomly on both sides along infrequent paths in the reserve. Their locations were recorded using OvitalMap (Beijing Ovital Software Co. Ltd. 2016). The average distance between two nearest ones was around 30 m. Weekly recording included the laying date, the species (available since incubation) and reproductive parameters such as clutch size, the number of hatchlings, ten-day-old nestlings and fledglings. We then calculated the hatching rate (the number of hatchlings/clutch size) and reproductive success rate (the number of fledglings/clutch size). The distances from the central nestbox to (1) the nearest ones, (2) the nearest nestbox occupied by a conspecific, and (3) the nearest nestbox occupied by a heterospecific were all measured using OvitalMap.

    The data was analyzed in SPSS version 21.0 (IBMCorp. Armonk, NY). An index of dispersion (Fowler et al., 1997) was calculated to ascertain the box distribution pattern. Mixed effect regression was used to test factors (the explanatory variable: neighbor type; and the random factors: box number and year) that affected the intra- and inter-specific nest spacing (the response variables: the distance between the focal nest and its nearest conspecific/heterospecific nest). We used mixed effect models to explore the influence of spatial distribution on the hatching rate of the focal nest (the explanatory variables: conspecific distance, heterospecific distance; and the random factors: box number and year) and linear models to explore the influence of spatial distribution on the reproductive success rate of the focal nest (the explanatory variables: conspecific distance, heterospecific distance). We used mixed effect models to explore the influence of breeding behavior on the hatching rate of the focal nest (the explanatory variables: neighbor type, neighbor hatching rate, and breeding synchrony; and the random factors: box number and year) and linear models to explore the influence of breeding behavior on the reproductive success rate of the focal nest (the explanatory variables: neighbor type, neighbor reproductive success rate and breeding synchrony). All analyses were considered significant at a probability value of <0.05.

    In total, 340, 451 and 434 nestboxes were investigated in 2016, 2017 and 2018, respectively. Each year less than half were occupied (Table 1) mainly by Cinereous Tits and Varied Tits, while few were occupied by other species such as Marsh Tits (Poecile palustris) and Daurian Redstarts (Phoenicurus auroreus). Over the 3 years, 20 boxes were used twice by Cinereous Tits, 17 boxes were used twice by Varied Tits, and 1 box was used thrice by each. All boxes were randomly dispersed within 500 ​m on both sides of the path (e.g., Fig. 1, dispersion indices χ2 = 13.46, df ​= ​19), as were those occupied by both Varied Tits (χ2 ​= ​8.68, df ​= ​19) and Cinereous Tits (χ2 ​= ​18.02, df ​= ​19).

    Table  1.  The total number of nestboxes placed, occupied and the occupancy rate in 2016, 2017, and 2018. The main species that used the artificial nestbox were Varied Tit and Cinereous Tit.
    YearTotal number of nestboxesTotal number of boxes occupiedBox occupancy rate (%)Number of boxes occupied by Varied TitNumber of boxes occupied by Cinereous Tit
    201634010129.714438
    201745117137.926758
    201843417941.243969
     | Show Table
    DownLoad: CSV
    Figure  1.  Maps of Liaoning Xianrendong National Nature Reserve showing the distribution of the nestboxes. Solid black lines suggest the range on both sides of the paths. Circles indicate position of nestboxes in 2018 and the species occupying them.

    The distance between breeding nests was significantly affected by neighbor type (F ​= ​29.652, P ​< ​0.001), but not species (F ​= ​1.304, P ​= ​0.254). The distance between intraspecific breeding nests of Varied Tits was significantly longer than that between interspecific nests (Fig. 2A). For Cinereous Tits, the same was true (Fig. 2B). However, reproduction of Varied and Cinereous Tits was not significantly relevant to the distance from their neighbor’s nest (Table 2).

    Figure  2.  Using mixed effect models to test the relationship between box distance and neighbor type (conspecific/heterspecific), box number and year. (A) Mean distance between the focal nest of Varied Tit (Sittiparus varius) and its conspecific and heterospecific neighbors. The distance between intraspecific breeding nests (116.28 ​± ​72.5 ​m, n ​= ​140) was significantly longer than that between interspecific nests (87.17 ​± ​68.78 ​m, t ​= ​−3.537, P ​= ​0.001). The mixed effect model had the statistics F3,311 ​= ​6.419, r2 ​= ​0.059, P ​< ​0.001. (B) Mean distance between the focal nest of Cinereous Tit (Parus cinereus) and its conspecific and heterospecific neighbors. The distance between intraspecific nests (108.40 ​± ​71.04 ​m, n ​= ​155) was significantly longer than that between interspecific nests (79.80 ​± ​55.50 ​m, t ​= ​−4.108, P ​< ​0.001). The mixed effect model had the statistics F3,311 ​= ​5.769, r2 ​= ​0.053, P ​< ​0.001.
    Table  2.  Statistical results of the effect of conspecific and heterospecific neighboring nest distance on the focal nest’s hatching rate (mixed effect models) and reproductive success (linear models). The mixed effect model for the Cinereous Tit had the statistics n ​= ​70, r2 ​= ​0.055, and for the Varied Tit n ​= ​72, r2 ​= ​0.026. The linear model for the Cinereous Tit had the statistics n ​= ​53, F2,14 ​= ​0.121, r2 ​= ​0.017, and for the Varied Tit n ​= ​53, F2,16 ​= ​0.282, r2 ​= ​0.034.
    Hatching rateReproductive success
    t-valuePt-valueP
    Cinereous Tit
    Conspecific distance1.810.0750.0410.968
    Heterospecific distance0.300.765−0.4880.633
    Varied Tit
    Conspecific distance−0.2670.791−0.1930.849
    Heterospecific distance1.2410.2190.6000.557
     | Show Table
    DownLoad: CSV

    The hatching rate of Varied Tits (n ​= ​144, r2 ​= ​0.892) was not related to recorded breeding behavior of their neighbors (hatching rate, t ​= ​0.773, P ​= ​0.982; and breeding synchrony, t ​= ​−0.419, P ​= ​0.333). Its reproductive success rate (n ​= ​38, r2 ​= ​0.270, F5,32 ​= ​2.362, P ​= ​0.062) was negatively related to that of their neighbors (t ​= ​−2.677, P ​= ​0.012) and positively related to the interaction between neighbor type and the reproductive success rate of the neighbor (t ​= ​2.142, P ​= ​0.040). Separate analyses on intraspecific neighbor and interspecific neighbor showed that the reproductive success of Varied Tits was negatively related to that of intraspecific neighbor (t ​= ​−2.889, P ​= ​0.011, Fig. 3) and not significantly related to that of interspecific neighbor (t ​= ​−0.086, P ​= ​0.932, Fig. 3). The reproductive effect of Cinereous Tits (hatching rate, n ​= ​140, r2 ​= ​0.758; and reproductive success rate, n ​= ​34, r2 ​= ​0.201, F5,28 ​= ​1.404, P ​= ​0.253) was not significantly affected by the recorded breeding behavior of their neighbors.

    Figure  3.  Using linear regression to test the relationship between the reproductive success of the Varied Tit and that of its intraspecific neighbor (Varied Tit) and interspecific neighbor (Cinereous Tit), respectively. The reproductive success of the Varied Tits decreased with increasing reproductive success of intraspecific neighbor (t ​= ​−2.889, P ​= ​0.011) and was not significantly related to that of interspecific neighbor (t ​= ​−0.086, P ​= ​0.932). The blue and red spots represented intra- and inter-specific neighbors. The solid lines were the linear regression lines.

    There was spatially separated nest sites selection for Varied Tits and Cinereous Tits. The distance between nests was longer within than between species. While both inter- and intra-specific competitions affect site selection (Tarjuelo et al., 2017) and food abundance (Teather, 1992), intraspecific competition in particular also impacts mate choice (Martínez-Rivera and Gerhardt, 2008) and extra-pair mating (Birkhead et al., 1985). To reduce such competition, individuals of the same species may space each other's nesting sites farther apart. Thus, intra-specific nests were more sparsely spaced. Deeming (2017) also shows that the conspecific nest distance is longer than the heterospecific one for Blue Tits and Great Tits. These results support that intraspecific competition in nest selection is more intense than interspecific competition.

    Regarding spatial distribution, Varied and Cinereous Tits showed a similar pattern. The distance to their neighbor’s nest was not significantly relevant to reproduction. But intense competition arises from the relatively short distance between two nests of the same species, which may adversely affect the reproduction of the breeding nest (Deeming et al., 2017). In our study, fewer than half of the installed boxes were occupied. The average distance between two nearest nestboxes was around 30 m, about twice the distance between two nearest neighbors. The space interval was relatively sufficient, and that was not so drastic to affect the reproductive success.

    The breeding success of Varied Tits may or may not be affected by that of their neighbors. The type matters. Between conspecific neighbors there is a negative correlation whereas between heterospecific ones, no identifiable correlation. Competition can reduce the number of offsprings (Gurevitch et al., 1992). In resource-restricted habitat, we are likely to detect the effect of density-dependence on reproduction in territorial species (Dhondt, 2010). When the conspecifics reproduce in the same area, there will be severe competition for food (Krüger et al., 2012). Food shortage is known to disrupt reproduction.

    However, Cinereous Tits did not show significant correlation to any recorded reproductive behavior of their neighbors. The results are supported by Møller’s (2018) finding that the breeding behavior of Blue Tits is affected by conspecifics but not Great Tits. In other words, the effect of competition on demographic variables has interspecific divergence. This may result from the either the scramble or exploitation-type competition for food both within and between species, and interference competition between different body sizes (Dhondt, 1977, 2010), as Cinereous Tits are larger than Varied Tits. Interspecific divergence may be related to the variances in clutch size of the two species. In our research site, the clutch size of Varied Tits is mostly 7–9, and the clutch size of Cinereous Tits is 7–13. Flexible adjustment of clutch size might be one of the ways for big tits to reduce competition. Behavioral differences may also contribute to the divergence. Active individuals can get more food resources under the same circumstance (David et al., 2011). So Varied Tits, which are less exploratory, active, and risk-taking than Cinereous Tits (Zhang et al., 2019), get less. Reproductive success of Cinereus Tits is not significantly affected.

    This study focused on one option of breeding site, namely through artificial nestboxes, rather than exhausting all possibilities. For example, nests in natural cavities are not considered. This is because on the reserve, where dead wood is removed in a timely manner, natural cavities are in insufficient supply. Before the breeding season, in March, we ringed the birds on the experimental site. During the entire breeding test period, unringed individuals were rarely spotted. Therefore, we assume that, at least in the area where artificial nest boxes were hung, natural nests were negligible.

    Boxes that are too densely distributed can even negatively affect the breeding behavior of birds, especially in areas where natural nests are extremely scarce. Thus, artificial nestboxes usually have low occupancy rate (Mänd et al., 2005; Deeming et al., 2017). This knowledge can be applied to the arrangement of nestboxes for bird study and conservation.

    Our results show that intra- and inter-specific competition affects the nest distribution of two hole-nesting species. The effect on reproductive outcome has interspecific divergence. The reproductive outcome of Varied Tits is significantly affected by its conspecific and heterospecific neighbors, but that of Cinereous Tits is not affected.

    YJ conceived the experiments, analyzed the data, wrote the manuscript, and reviewed the drafts; YB conceived and designed the experiments, performed the experiments, analyzed the data, and wrote the manuscript; RM analyzed the data; JZ performed the experiments; DW conceived and designed the experiments, and reviewed drafts of the paper. All authors read and approved the final manuscript.

    All our study procedures were approved by Liaoning Xianrendong National Nature Reserve.

    The authors declare that they have no competing interests.

    Thanks for the support of Liaoning Xianrendong National Nature Reserve. This work was supported by the National Natural Science Foundation of China (No. 31872231 to DW, No. 32000316 to YJ).

  • Bachtrog, D., Thornton, K., Clark, A., Andolfatto, P., 2006. Extensive introgression of mitochondrial DNA relative to nuclear genes in the Drosophila yakuba species group. Evolution 60, 292-302.
    Bernt, M., Donath, A., Juhling, F., Externbrink, F., Florentz, C., Fritzsch, G., et al., 2013. MITOS: improved de novo metazoan mitochondrial genome annotation. Mol. Phylogenet. Evol. 69, 313-319.
    Bouckaert, R.R., Heled, J., Kuehnert, D., Vaughan, T.G., Wu, C.H., Xie, D., et al., 2014. Beast 2: a software platform for Bayesian evolutionary analysis. PLoS Comp. Biol. 10, e1003537.
    Chan, K.M.A., Levin, S., 2005. Leaky prezygotic isolation and porous genome: rapid introgression of maternally inherited DNA. Evolution 59, 720-729.
    Chen, M.Y., Liang, D., Zhang, P., 2015. Selecting question-specific genes to reduce incongruence in phylogenomics: a case study of jawed vertebrate backbone phylogeny. Syst. Biol. 64, 1104-1120.
    Chifman, J., Kubatko, L.S., 2014. Quartet inference from SNP data under the coalescent model. Bioinformatics 30, 3317-3324.
    Chifman, J., Kubatko, L.S., 2015. Identifiability of the unrooted species tree topology under the coalescent model with time-reversible substitution processes, site-specific rate variation, and invariable sites. J. Theor. Biol. 374, 35-47.
    Da Silva, F.S., Cruz, A.C.R., de Almeida Medeiros, D.B., Silva, S.P., Nunes, M.R.T., Martins, L.C., et al., 2020. Mitochondrial genome sequencing and phylogeny of Haemagogus albomaculatus, Haemagogus leucocelaenus, Haemagogus spegazzinii, and Haemagogus tropicalis (Diptera: Culicidae). Sci. Rep. 10, 16948.
    Deng, X.D., Li, J.W., Vasconcelos, P.M., Cohen, B.E., Kusky, T.M., 2014. Geochronology of the Baye Mn oxide deposit, southern Yunnan Plateau: Implications for the late Miocene to Pleistocene paleoclimatic conditions and topographic evolution. Geochim. Cosmochim. Acta 139, 227-247.
    Drovetski, S.V., Semenov, G., Drovetskaya, S.S., Fadeev, I.V., Red’kin, Y.A., Voelker, G., 2013. Geographic mode of speciation in a mountain specialist avian family endemic to the Palearctic. Ecol. Evol. 3, 1518-1528.
    Dickinson, E.C., 2003. The Howard & Moore Complete Checklist of the Birds, 3rd ed. Princeton University Press, Princeton.
    Drovetski, S.V., Fadeev, I.V., Rakovic, M., Lopes, R.J., Boano, G., Pavia, M., et al., 2018. A test of the European Pleistocene refugial paradigm, using a Western Palaearctic endemic bird species. Proc. R. Soc. B 285, 20181606.
    Drummond, A.J., Suchard, M.A., Xie, D., Rambaut, A., 2012. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol. Biol. Evol. 29, 1969-1973.
    Duchene, S., Archer, F.I., Vilstrup, J., Caballero, S., Morin, P.A., 2011. Mitogenome phylogenetics: the impact of using single regions and partitioning schemes on topology, substitution rate and divergence time estimation. PLoS One 6, e27138.
    Edwards, S.V., Xi, Z., Janke, A., Faircloth, B.C., McCormack, J.E., Glenn, T.C., et al., 2016. Implementing and testing the multispecies coalescent model: a valuable paradigm for phylogenomics. Mol. Phylogenet. Evol. 94, 447-462.
    Esquerre, D., Ramirez-Alvarez, D., Pavon-Vazquez, C.J., Troncoso-Palacios, J., Garin, C.F., Keogh, J.S., et al., 2019. Speciation across mountains: phylogenomics, species delimitation and taxonomy of the Liolaemus leopardinus clade (Squamata, Liolaemidae). Mol. Phylogenet. Evol. 139, 106524.
    Favre, A., Packert, M., Pauls, S.U., Jahnig, S.C., Uhl, D., Michalak, I., et al., 2015. The role of the uplift of the Qinghai-Tibetan Plateau for the evolution of Tibetan biotas. Biol. Rev. 90, 236-253.
    Fjeldsa, J., Bowie, R.C.K., Rahbek, C., 2012. The role of mountain ranges in the diversification of birds. Annu. Rev. Ecol. Evol. Syst. 43, 249-265.
    Ghalambor, C.K., Huey, R.B., Martin, P.R., Tewksbury, J.J., Wang, G., 2016. Are mountain passes higher in the tropics? Janzen’s hypothesis revisited. Integr. Comp. Biol. 46, 5-17.
    Gill, F., Donsker, D., 2016. IOC World Bird List, version 6.1. . (Accessed 20 December 2022).
    Gill, F., Donsker, D., Rasmussen, P., 2022. IOC World Bird List, vol. 2. . (Accessed 20 December 2022).
    Gonzalez-Castellano, I., Pons, J., Gonzalez-Ortegon, E., Martenez-Lage, A., 2020. Mitogenome phylogenetics in the genus Palaemon (Crustacea: Decapoda) sheds light on species crypticism in the rockpool shrimp P. elegans. PLoS One 15, e0237037.
    Hatchwell, B.J., 2005. Family Prunellidae (accentors). In: Del Hoyo, J., Elliott, J., Christie, D.A. (Eds.), Handbook of the Birds of the World. Lynx Editions, Barcelona, pp. 496–513.
    Hoang, D.T., Chernomor, O., von Haeseler, A., Minh, B.Q., Vinh, L.S., 2018. UFBoot2: improving the ultrafast bootstrap approximation. Mol. Biol. Evol. 35, 518-522.
    Irisarri, I., Meyer, A., 2016. The identification of the closest living relative(s) of tetrapods: phylogenomic lessons for resolving short ancient internodes. Syst. Biol. 65, 1057-1075.
    Katoh, K., Standley, D.M., 2013. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772-780.
    Kohler, T., Maselli, D., 2009. Mountains and Climate Change – from Understanding to Action. Geographica Bernesia, Bern.
    Kreft, H., Jetz, W., 2007. Global patterns and determinants of vascular plant diversity. P. Natl. Acad. Sci. USA 104, 5925-5930.
    Lafon, C.W., 2004. High biodiversity: an assessment of mountain biodiversity. Divers. Distrib. 10, 75-76.
    Lerner, H.R.L., Meyer, M., James, H.F., Hofreiter, M., Fleischer, R.C., 2011. Multilocus resolution of phylogeny and timescale in the extant adaptive radiation of Hawaiian honeycreepers. Curr. Biol. 21, 1838-1844.
    Liu, B., Alstrom, P., Olsson, U., Fjeldså, J., Quan, Q., Roselaar, K.C.S., et al., 2017. Explosive radiation and spatial expansion across the cold environments of the Old World in an avian family. Ecol. Evol. 7, 6346-6357.
    Maddison, W.P., Knowles, L.L., 2006. Inferring phylogeny despite incomplete lineage sorting. Syst. Biol. 55, 21-30.
    Matzke, N.J., 2013. Probabilistic historical biogeography: new models for founder-event speciation, imperfect detection, and fossils allow improved accuracy and model-testing. Front. Biogeogr. 5, 242-248.
    Matzke, N.J., 2014. Model selection in historical biogeography reveals that founder-event speciation is a crucial process in island clades. Syst. Biol. 63, 951-970.
    Meng, G., Li, Y., Yang, C., Liu, S., 2019. MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization. Nucleic Acids Res. 47, e63.
    Miao, Y., Herrmann, M., Wu, F., Yan, X., Yang, S., 2012. What controlled Mid-Late Miocene long-term aridification in Central Asia? -Global cooling or Tibetan Plateau uplift: a review. Earth Sci. Rev. 112, 155-172.
    Mitchell, N., Lewis, P.O., Lemmon, E.M., Lemmon, A.R., Holsinger, K.E., 2017. Anchored phylogenomics improves the resolution of evolutionary relationships in the rapid radiation of Protea L. Am. J. Bot. 104, 102-115.
    Meyer, M., Kircher, M., 2010. Illumina sequencing library preparation for highly multiplexed target capture and sequencing. Cold Spring Harb. Protoc. 6, prot5448.
    Nguyen, L.T., Schmidt, H.A., von Haeseler, A., Minh, B.Q., 2015. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268-274.
    Oliver, J.C., 2013. Microevolutionary processes generate phylogenomic discordance at ancient divergences. Evolution 67, 1823-1830.
    Philippe, H., Henner Brinkmann, H., Lavrov, D.V., Littlewood, D.T.J., Michael Manuel, M., Worheide, G., et al., 2011. Resolving difficult phylogenetic questions: why more sequences are not enough. PLoS Biol. 9, e1000602.
    Prum, R.O., Berv, J.S., Dornburg, A., Field, D.J., Townsend, J.P., Lemmon, E.M., et al., 2015. A comprehensive phylogeny of birds (Aves) using targeted next-generation DNA sequencing. Nature 526, 569-573.
    Rambaut, A., 2012. FigTree Version 1.4.0. . (Accessed 10 October 2020).
    Ruggiero, A., Hawkins, B.A., 2008. Why do mountains support so many species of birds? Ecography 31, 306-315.
    Song, G., Zhang, R., Alstrom, P., Irestedt, M., Cai, T., Qu, Y., et al., 2018. Complete taxon sampling of the avian genus Pica (magpies) reveals ancient relictual populations and synchronous Late-Pleistocene demographic expansion across the Northern Hemisphere. J. Avian Biol. 49, e01612.
    Song, G., Zhang, R.Y., Machado-Stredel, F., Alstrom, P., Johansson, U.S., Irestedt, M., et al., 2020. Great journey of Great Tits (Parus major group): origin, diversification, and historical demographics of a broadly-distributed bird lineage. J. Biogeogr. 47, 1585-1598.
    Stepanyan, L.S., 2003. Conspectus of the Ornithological Fauna of Russia and Adjacent Territories (Within the Borders of the USSR as a Historic Region). Academkniga, Moscow.
    Svardal, H., Salzburger, W., Malinsky, M., 2021. Genetic variation and hybridization in evolutionary radiations of cichlid fishes. Annu. Rev. Anim. Biosci. 9, 55-79.
    Swofford, D.L., 2021. PAUP* (Version PAUP* v.4.0a169). Phylogenetic Analysis Using Parsimony (*and Other Methods). . (Accessed 5 January 2021).
    Tarver, J.E., dos Reis, M., Mirarab, S., Moran, R.J., Parker, S., O’Reilly, J.E., et al., 2016. The interrelationships of placental mammals and the limits of phylogenetic inference. Genome Biol. Evol. 8, 330-344.
    Wang, W., McKay, B.D., Dai, C., Zhao, N., Zhang, R., Qu, Y., et al., 2013. Glacial expansion and diversification of an East Asian montane bird, the green-backed tit (Parus monticolus). J. Biogeogr. 40, 1156-1169.
    Yu, P., Zhou, L., Yang, W., Miao, L., Li, Z., Zhang, X., et al., 2021. Comparative mitogenome analyses uncover mitogenome features and phylogenetic implications of the subfamily Cobitinae. BMC Genomics 22, 50.
    Yu, Y., Harris, A.J., Blair, C., He, X.J., 2015. RASP (Reconstruct Ancestral State in Phylogenies): a tool for historical biogeography. Mol. Phylogenet. Evol. 87, 46-49.
    Yu, Y., Harris, A.J., He, X., 2010. S-DIVA (statistical dispersal-vicariance analysis): a tool for inferring biogeographic histories. Mol. Phylogenet. Evol. 56, 848-850.
    Zhang, Q., Ree, R.H., Salamin, N., Xing, Y., Silvestro, D., 2021. Fossil-informed models reveal a boreotropical origin and divergent evolutionary trajectories in the walnut family (Juglandaceae). Syst. Biol. 71, 242-258.
    Zhang, R., Song, G., Qu, Y., Alstrom, P., Ramos, R., Xing, X., et al., 2012. Comparative phylogeography of two widespread magpies: importance of habitat of preference and breeding behavior on genetic structure in China. Mol. Phylogenet. Evol. 65, 562-572.
    Zhao, M., Chang, Y., Kimball, R.T., Zhao, J., Lei, F., Qu, Y., 2019. Pleistocene glaciation explains the disjunct distribution of the Chestnut-vented Nuthatch (Aves, Sittidae). Zool. Scr. 48, 33-45.
    Zhao, N., Dai, C., Wang, W., Zhang, R., Qu, Y., Lei, F., 2012. Pleistocene climate changes shaped the divergence and demography of Asian populations of the great tit Parus major: evidence from phylogeographic analysis and ecological niche models. J. Avian Biol. 43, 297-310.
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