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Taxonomic reassessment of captive sugar gliders using genetic analyses and complementary acoustic data

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Abstract

Accurate species identification is crucial for managing ex-situ populations, especially in cryptic species complexes where taxonomic uncertainty may compromise conservation. The sugar glider (Petaurus breviceps s.l.) is a small nocturnal marsupial commonly bred in zoos and is popular in the exotic pet trade. Recent taxonomic revisions revealed substantial cryptic diversity within the complex, raising concerns about species identity and geographic origin of captive individuals. We used an integrative approach combining genetic and acoustic analyses to assess the taxonomic status of captive P. breviceps s.l. populations. Phylogenetic analyses of mitochondrial ND2 and ND4 genes showed a strong genetic affinity between European and United States captive populations, suggesting a shared origin within the New Guinean lineage. These findings support their reclassification as Petaurus papuanus. Despite their captive origin, these populations showed unexpectedly high haplotype diversity, likely due to repeated introductions from genetically distinct but geographically close wild populations. However, within-group homogeneity indicates limited genetic exchange among breeding lines. Acoustic analyses of the barking call revealed intraspecific variability but little species-specificity, indicating a minor role in reproductive isolation. Our findings underscore the importance of taxonomic clarity and structured genetic management for conserving captive population integrity.

Data availability

Data is provided within the manuscript or supplementary material files. Sequenced fragments of the mitochondrial ND2, ND4, and nuclear ω-globin are available on GenBank (https://www.ncbi.nlm.nih.gov/) under accession numbers: PV701819-PV701993. Recordings of wild individuals are available on iNaturalist (https://www.inaturalist.org/). Additional acoustic data recorded during this study are available from the corresponding author upon request.

References

  1. Lockwood, J. L. et al. When pets become pests: the role of the exotic pet trade in producing invasive vertebrate animals. Front. Ecol. Environ. 17, 323–330 (2019).

    Google Scholar 

  2. Grant, R. A., Montrose, V. T. & Wills, A. P. ExNOTic: should we be keeping exotic pets? Animals 7, 47. https://doi.org/10.3390/ani7060047 (2017).

    Google Scholar 

  3. Hvilsom, C. et al. Understanding geographic origins and history of admixture among chimpanzees in European zoos, with implications for future breeding programmes. Heredity 110, 586–593 (2013).

    Google Scholar 

  4. Bickford, D. et al. Cryptic species as a window on diversity and conservation. Trends Ecol. Evol. 22, 148–155 (2007).

    Google Scholar 

  5. Thabah, A. et al. Genetic divergence and echolocation call frequency in cryptic species of Hipposideros larvatus s.l. (Chiroptera: Hipposideridae) from the Indo-Malayan region. Biol. J. Linn. Soc. 88, 119–130 (2006).

    Google Scholar 

  6. Schneiderová, I., Pluháček, J., Bearder, S. & Rosti, H. Evidence-based practice bioacoustics reveals the uniqueness of an ex-situ tree hyrax population. J. Zoo Aquar Res. 12, 42–48 (2024).

    Google Scholar 

  7. Munds, R. A., Nekaris, K. A. I. & Ford, S. M. Taxonomy of the Bornean slow loris, with new species Nycticebus Kayan (Primates, Lorisidae). Am. J. Primatol. 75, 46–56 (2013).

    Google Scholar 

  8. Hotaling, S. et al. Species discovery and validation in a cryptic radiation of endangered primates: Coalescent-based species delimitation in madagascar’s mouse lemurs. Mol. Ecol. 25, 2029–2045 (2016).

    Google Scholar 

  9. Pozzi, L. et al. Species boundaries within morphologically cryptic galagos: evidence from acoustic and genetic data. Folia Primatol. 90, 279–299 (2019).

    Google Scholar 

  10. C McGregor, D. et al. Genetic evidence supports three previously described species of greater glider, petauroides volans, P. minor, and P. armillatus. Sci. Rep. 10 (19284). https://doi.org/10.1038/s41598-020-76364-z (2020).

  11. Umbrello, L. S. et al. Hiding in plain sight: two new species of diminutive marsupial (Dasyuridae: Planigale) from the Pilbara, Australia. Zootaxa 5330, 1–46 (2023).

    Google Scholar 

  12. Zimmermann, E. Differentiation of vocalizations in bushbabies (Galaginae, Prosimiae, Primates) and the significance for assessing phylogenetic relationships. J. Zool. Syst. Evol. Res. 28, 217–239 (1990).

    Google Scholar 

  13. Esser, D., Schehka, S. & Zimmermann, E. Species-specificity in communication calls of tree shrews (Tupaia: Scandentia). J. Mammal. 89, 1456–1463 (2008).

    Google Scholar 

  14. Bettridge, C. M., Kenworthy, S. P., Butynski, T. M., de Jong, Y. A. & de Kort, S. R. Vocal repertoire and intraspecific variation within two loud calls of the small-eared greater Galago (Otolemur garnettii) in Tanzania and Kenya. Folia Primatol. 90, 319–335 (2019).

    Google Scholar 

  15. Oates, J. F. et al. A new species of tree hyrax (Procaviidae: Dendrohyrax) from West Africa and the significance of the Niger-Volta interfluvium in mammalian biogeography. Zool. J. Linn. Soc. 194, 527–552 (2022).

    Google Scholar 

  16. Mittermeier, R. A. et al. Lemurs of Madagascar (Conservation International, 2010).

  17. Baldwin, H. J. et al. Concordant patterns of genetic, acoustic, and morphological divergence in the West African old world leaf-nosed bats of the Hipposideros caffer complex. J. Zool. Syst. Evol. Res. 59, 1390–1407 (2021).

    Google Scholar 

  18. McCowan, B. & Hooper, S. L. Individual acoustic variation in belding’s ground squirrel alarm chirps in the high Sierra Nevada. J. Acoust. Soc. Am. 111, 1157–1160 (2002).

    Google Scholar 

  19. Teixeira, D., Maron, M. & van Rensburg, B. J. Bioacoustic monitoring of animal vocal behavior for conservation. Conserv. Sci. Pract. 1, e72. https://doi.org/10.1111/csp2.72 (2019).

    Google Scholar 

  20. Hasiniaina, A. F. et al. Evolutionary significance of the variation in acoustic communication of a cryptic nocturnal primate radiation (Microcebus spp). Ecol. Evol. 10, 3784–3797 (2020).

    Google Scholar 

  21. Hale, A. M., Hein, C. D. & Straw, B. R. Acoustic and genetic data can reduce uncertainty regarding populations of migratory tree-roosting bats impacted by wind energy. Animals 12, 81. https://doi.org/10.3390/ani12010081 (2022).

    Google Scholar 

  22. Malekian, M., Cooper, S. J. B., Norman, J. A., Christidis, L. & Carthew, S. M. Molecular systematics and evolutionary origins of the genus Petaurus (Marsupialia: Petauridae) in Australia and new Guinea. Mol. Phylogenet Evol. 54, 122–135 (2010).

    Google Scholar 

  23. Burnett, S., Winter, J. & Martin, R. Petaurus gracilis. IUCN Red List. Threatened Species. e.T16727A21959531 https://doi.org/10.2305/IUCN.UK.2016-2.RLTS.T16727A21959531.en (2016). (2016).

  24. Leary, T. et al. Petaurus biacensis. IUCN Red List of Threatened Species 2016: e.T16732A21959734. (2016). https://doi.org/10.2305/IUCN.UK.2016-2.RLTS.T16732A21959734.en

  25. Leary, T. et al. Petaurus abidi. IUCN Red List of Threatened Species 2016: e.T16726A21959298. (2016). https://doi.org/10.2305/IUCN.UK.2016-2.RLTS.T16726A21959298.en

  26. Salas, L. et al. Petaurus Breviceps. IUCN Red List. Threatened Species. e.T16731A21959798 https://doi.org/10.2305/IUCN.UK.2016-2.RLTS.T16731A21959798.en (2016). (2016).

  27. Winter, J., Lunney, D., Denny, M., Burnett, S. & Menkhorst, P. Petaurus norfolcensis. IUCN Red List. Threatened Species. e.T16728A21959402 https://doi.org/10.2305/IUCN.UK.2016-2.RLTS.T16728A21959402.en (2016). (2016).

  28. Johnson, C. N., Woinarski, J. C. Z. & Burbidge, A. A. Petaurus australis. The IUCN Red List of Threatened Species 2025: e.T16730A258670618 (2025).

  29. Cremona, T. et al. Integrative taxonomic investigation of Petaurus Breviceps (Marsupialia: Petauridae) reveals three distinct species. Zool. J. Linn. Soc. 191, 503–527 (2021).

    Google Scholar 

  30. Smith, M. J. Petaurus Breviceps. Mamm. Species. 30, 1–5 (1973).

    Google Scholar 

  31. Goldingay, R. L. Loud calls of the yellow-bellied glider, Petaurus australis: territorial behaviour by an arboreal marsupial? Aust J. Zool. 42, 279–293 (1994).

    Google Scholar 

  32. Raftery, A. Sugar gliders (Petaurus breviceps). Companion Anim. 20, 422–426 (2015).

    Google Scholar 

  33. Powley, M. & Mikac, K. Comparative analysis of Petaurus cryptic species of ‘sugar glider’ from Australia and new Guinea using 3D geometric morphometrics. Animals 14, 3680. https://doi.org/10.3390/ani14243680 (2024).

    Google Scholar 

  34. Campbell, C. D., Pecon-Slattery, J., Pollak, R., Joseph, L. & Holleley, C. E. The origin of exotic pet sugar gliders (Petaurus breviceps) kept in the united States of America. PeerJ 7, e6180. https://doi.org/10.7717/peerj.6180 (2019).

    Google Scholar 

  35. Franke, F. A. et al. Genetic differentiation of the African Dwarf crocodile Osteolaemus tetraspis Cope, 1861 (Crocodylia: Crocodylidae) and consequences for European zoos. Org. Divers. Evol. 13, 255–266 (2013).

    Google Scholar 

  36. Schmidt, F., Franke, F. A., Shirley, M. H., Vliet, K. A. & Villanova, V. L. The importance of genetic research in zoo breeding programmes for threatened species: the African Dwarf crocodiles (genus Osteolaemus) as a case study. Int. Zoo Yearb. 49, 125–136 (2015).

    Google Scholar 

  37. Shirley, M. H., Villanova, V. L., Vliet, K. A. & Austin, J. D. Genetic barcoding facilitates captive and wild management of three cryptic African crocodile species complexes. Anim. Conserv. 18, 322–330 (2015).

    Google Scholar 

  38. Palmer, A., Sommer, V. & Msindai, J. N. Hybrid apes in the anthropocene: burden or asset for conservation? People Nat. 3, 573–586 (2021).

    Google Scholar 

  39. Sievers, F. & Higgins, D. G. Clustal Omega for making accurate alignments of many protein sequences. Protein Sci. 27, 135–145 (2018).

    Google Scholar 

  40. Sievers, F. et al. Fast, scalable generation of high-quality protein multiple sequence alignments using clustal Omega. Mol. Syst. Biol. 7, 539. https://doi.org/10.1038/msb.2011.75 (2011).

    Google Scholar 

  41. Sievers, F., Barton, G. J. & Higgins, D. G. Multiple sequence alignments. In Bioinformatics (eds Baxevanis, A. D., Bader, G. D. & Wishart, D. S.) 227–250 (Wiley, (2020).

  42. Huelsenbeck, J. P. & Ronquist, F. Bayesian inference of phylogenetic trees. Bioinformatics 17, 754–755 (2001).

    Google Scholar 

  43. Guindon, S. & Gascuel, O. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52, 696–704. https://doi.org/10.1080/10635150390235520 (2003).

    Google Scholar 

  44. Darriba, D., Taboada, G. L., Doallo, R. & Posada, D. JModelTest 2: more models, new heuristics and parallel computing. Nat. Methods. 9, 772. https://doi.org/10.1038/nmeth.2109 (2012).

    Google Scholar 

  45. Rambaut, A. FigTree Ver 1.4.4 (Institute of Evolutionary Biology, University of Edinburgh, 2018).

  46. Kumar, S. et al. MEGA12: molecular evolutionary genetic analysis version 12 for adaptive and green computing. Mol. Biol. Evol. 41, 1–9 (2024).

    Google Scholar 

  47. Leigh, J. W. & Bryant, D. P. O. P. A. R. T. Full-feature software for haplotype network construction. Methods Ecol. Evol. 6, 1110–1116 (2015).

    Google Scholar 

  48. Clement, M., Snell, Q., Walke, P., Posada, D. & Crandall, K. TCS: estimating gene genealogies. In Proceedings 16th International Parallel and Distributed Processing Symposium, 7 ppIEEE Computer Society,. (2002).

  49. Rozas, J. et al. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol. Biol. Evol. 34, 3299–3302 (2017).

    Google Scholar 

  50. R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, (2025). https://www.R-project.org/

  51. Mazerolle, M. J. AICcmodavg: Model selection and multimodel inference based on (Q)AIC(c). R package version 2.3.3 (2023). https://cran.r-project.org/package=AICcmodavg

  52. Robinson, D., Hayes, A. & Couch, S. broom: Convert statistical objects into tidy tibbles. R package version 1.0.7 (2024). https://CRAN.R-project.org/package=broom

  53. Fox, J. & Weisberg, S. An R companion to applied regression, Third edition. (Sage, (2019). https://www.john-fox.ca/Companion/

  54. Fox, J., Weisberg, S. & Price, B. CarData: companion to applied regression data sets. R Package Version 3 0–5. https://CRAN.R-project.org/package=carData (2022).

  55. Wei, T. & Simko, V. R package ‘corrplot’: Visualization of a correlation matrix (Version 0.95). (2021). Available from https://github.com/taiyun/corrplot

  56. Kassambara, A. & Mundt, F. factoextra: Extract and visualize the results of multivariate data analyses. R package version 1.0.7 (2020). https://CRAN.R-project.org/package=factoextra

  57. Kassambara, A. ggcorrplot: Visualization of a Correlation Matrix using ‘ggplot2’. R package version 0.1.4.1 (2023). https://CRAN.R-project.org/package=ggcorrplot

  58. Tang, Y., Horikoshi, M., Li, W. & ggfortify Unified interface to visualize statistical result of popular R packages. R J. 8, 474–485. https://doi.org/10.32614/RJ-2016-060 (2016).

    Google Scholar 

  59. Horikoshi, M. & Tang, Y. ggfortify: Data visualization tools for statistical analysis results (2018). https://CRAN.R-project.org/package=ggfortify

  60. Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-, 2016).

  61. Kassambara, A. ggpubr: ‘ggplot2’ based publication ready plots. R package version 0.6.0 (2023). https://CRAN.R-project.org/package=ggpubr

  62. Yamamoto, H. loadings: Loadings for principal component analysis and partial least squares. R package version 0.5.1 (2024). https://CRAN.R-project.org/package=loadings

  63. Bache, S. & Wickham, H. magrittr: A Forward-pipe operator for R. R package version 2.0.3 (2022). https://CRAN.R-project.org/package=magrittr

  64. Wickham, H. & Bryan, J. readxl: Read excel files. R package version 1.4.5 (2025). https://CRAN.R-project.org/package=readxl

  65. Kassambara, A. rstatix: Pipe-friendly framework for basic statistical tests. R package version 0.7.2 (2023). https://CRAN.R-project.org/package=rstatix

  66. Wickham, H. et al. Welcome to the tidyverse. J. Open. Source Softw. 4, 1686. https://doi.org/10.21105/joss.01686 (2019).

    Google Scholar 

  67. Knief, U. & Forstmeier, W. Violating the normality assumption May be the lesser of two evils. Behav. Res. Methods. 53, 2576–2590 (2021).

    Google Scholar 

  68. Nijman, V. An overview of international wildlife trade from Southeast Asia. Biodivers. Conserv. 19, 1101–1114 (2010).

    Google Scholar 

  69. Witzenberger, K. A. & Hochkirch, A. Ex situ conservation genetics: A review of molecular studies on the genetic consequences of captive breeding programmes for endangered animal species. Biodivers. Conserv. 20, 1843–1861 (2011).

    Google Scholar 

  70. McGreevy, T. J., Dabek, L., Gomez-Chiarri, M. & Husband, T. P. Genetic diversity in captive and wild matschie’s tree Kangaroo (Dendrolagus matschiei) from Huon Peninsula, Papua new Guinea, based on MtDNA control region sequences. Zoo Biol. 28, 183–196 (2009).

    Google Scholar 

  71. Ito, H., Ogden, R., Langenhorst, T. & Inoue-Murayama, M. Contrasting results from molecular and pedigree-based population diversity measures in captive zebra highlight challenges facing genetic management of zoo populations. Zoo Biol. 36, 87–94 (2017).

    Google Scholar 

  72. Atkinson, K. E., Kitchener, A. C., Tobe, S. S. & O’Donoghue, P. An assessment of the genetic diversity of the founders of the European captive population of Asian Lion (Panthera Leo Leo), using microsatellite markers and studbook analysis. Mamm. Biol. 88, 138–143 (2018).

    Google Scholar 

  73. Farré, M. et al. Novel MtDNA haplotypes represented in the European captive population of the endangered François’ langur (Trachypithecus francoisi). Int. J. Primatol. 43, 533–537 (2022).

    Google Scholar 

  74. Cetkovská, E., Brandlová, K. & Ogden, R. Černá Bolfíková, B. Evaluation of the impact of population management on the genetic parameters of selected spiral-horned antelopes. Biology 13, 104. https://doi.org/10.3390/biology13020104 (2024).

    Google Scholar 

  75. Adavoudi, R. & Pilot, M. Consequences of hybridization in mammals: A systematic review. Genes 13, 50. https://doi.org/10.3390/genes13010050 (2022).

    Google Scholar 

  76. Butynski, T. M., de Jong, Y. A., Perkin, A. W., Bearder, S. K. & Honess, P. E. Taxonomy, distribution, and conservation status of three species of Dwarf Galagos (Galagoides) in Eastern Africa. Primate Conserv. 21, 63–79 (2006).

    Google Scholar 

  77. Masters, J. C. et al. A new genus for the Eastern Dwarf Galagos (Primates: Galagidae). Zool. J. Linn. Soc. 181, 229–241 (2017).

    Google Scholar 

  78. Rosti, H. et al. Vocalization analyses of nocturnal arboreal mammals of the Taita hills, Kenya. Diversity 12, 473. https://doi.org/10.3390/d12120473 (2020).

    Google Scholar 

  79. Chang, Y., Bertola, L. V., Zenger, K. R. & Hoskin, C. J. Conservation genetics of Mahogany gliders and their complex evolutionary relationship with squirrel gliders. Conserv. Genet. 26, 731–750 (2025).

    Google Scholar 

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Acknowledgements

We thank all the ex-situ institutions that have contributed to our study, namely the Berlin Zoological Garden, Riga National Zoological Garden, Zoological and Botanical Garden Plzen, Prague Zoological Garden, and the Zoological Garden Brno. We also thank the private breeders for their contributions. The following thanks go to the iNaturalist website and mostly to all the authors of recordings from Australia. We also thank Denisa Stejskalová for her amazing drawing of Petaurus papuanus.

Funding

The research was supported by the Internal Grant Agency of FTZ CZU (IGA20253125).

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Authors and Affiliations

  1. Faculty of Tropical AgriSciences, Czech University of Life Sciences Prague, Prague, Czech Republic

    Miroslav Mulko & Barbora Černá Bolfíková

  2. Research Institute for Gene Pool Conservation, Safari Park Dvůr Králové, Dvůr Králové nad Labem, Czech Republic

    Miroslav Mulko

  3. Faculty of Science, Charles University, Prague, Czech Republic

    Irena Schneiderová

Authors

  1. Miroslav Mulko
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  2. Irena Schneiderová
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  3. Barbora Černá Bolfíková
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by M. M., I. S., and B. Č. B. The first draft of the manuscript was written by M. M., and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to
Miroslav Mulko.

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Mulko, M., Schneiderová, I. & Černá Bolfíková, B. Taxonomic reassessment of captive sugar gliders using genetic analyses and complementary acoustic data.
Sci Rep (2025). https://doi.org/10.1038/s41598-025-31262-0

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  • DOI: https://doi.org/10.1038/s41598-025-31262-0

Keywords

  • Bioacoustics
  • Captive breeding
  • Genetic diversity
  • Marsupialia
  • Pet trade
  • Petauridae

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