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Conservation genomics of an endangered arboreal mammal following the 2019–2020 Australian megafire

  • Ward, M. et al. Impact of 2019–2020 mega-fires on Australian fauna habitat. Nat. Ecol. Evol. 4(10), 1321–1326. https://doi.org/10.1038/s41559-020-1251-1 (2020).

    Article 

    Google Scholar 

  • Legge, S. et al. Estimates of the impacts of the 2019–20 fires on populations of native animal species, Brisbane (2021).

  • Yibo, H. et al. Genomic evidence for two phylogenetic species and long-term population bottlenecks in red pandas. Sci. Adv. 6(9), eaax5751. https://doi.org/10.1126/sciadv.aax5751 (2022).

    Article 

    Google Scholar 

  • Grossen, C., Guillaume, F., Keller, L. F. & Croll, D. Purging of highly deleterious mutations through severe bottlenecks in Alpine ibex. Nat. Commun. 11(1), 1001. https://doi.org/10.1038/s41467-020-14803-1 (2020).

    Article 
    ADS 

    Google Scholar 

  • van Aalst, M. K. The impacts of climate change on the risk of natural disasters. Disasters 30(1), 5–18. https://doi.org/10.1111/j.1467-9523.2006.00303.x (2006).

    Article 

    Google Scholar 

  • Banholzer, S., Kossin, J. & Donner, S. The impact of climate change on natural disasters. In Reducing Disaster: Early Warning Systems For Climate Change (eds Singh, A. & Zommers, Z.) 21–49 (Springer Netherlands, 2014). https://doi.org/10.1007/978-94-017-8598-3_2.

    Chapter 

    Google Scholar 

  • Frankham, R., Ballou, J. D. & Briscoe, D. A. Introduction to Conservation Genetics 2nd edn. (Cambridge University Press, 2010).

    Book 

    Google Scholar 

  • Bouzat, J. L. Conservation genetics of population bottlenecks: The role of chance, selection, and history. Conserv. Genet. 11(2), 463–478. https://doi.org/10.1007/s10592-010-0049-0 (2010).

    Article 

    Google Scholar 

  • Leigh, D. M., Hendry, A. P., Vázquez-Domínguez, E. & Friesen, V. L. Estimated six per cent loss of genetic variation in wild populations since the industrial revolution. Evol. Appl. 12(8), 1505–1512. https://doi.org/10.1111/eva.12810 (2019).

    Article 

    Google Scholar 

  • Willi, Y., Van Buskirk, J. & Hoffmann, A. A. Limits to the adaptive potential of small populations. Annu. Rev. Ecol. Evol. Syst. 37(1), 433–458 (2006).

    Article 

    Google Scholar 

  • Tanaka, M. M., Wahl, L. M. & Wahl, L. M. Surviving environmental change: When increasing population size can increase extinction risk. Proc. R. Soc. B 289, 20220439. https://doi.org/10.1098/rspb.2022.0439 (2022).

    Article 

    Google Scholar 

  • Gomulkiewicz, R. & Holt, R. D. When does evolution by natural selection prevent extinction?. Evolution 49(1), 201–207. https://doi.org/10.1111/j.1558-5646.1995.tb05971.x (1995).

    Article 

    Google Scholar 

  • Bell, G. Evolutionary rescue. Annu. Rev. Ecol. Evol. Syst. 48(1), 605–627. https://doi.org/10.1146/annurev-ecolsys-110316-023011 (2017).

    Article 

    Google Scholar 

  • Wood, J. L. A., Yates, M. C. & Fraser, D. J. Are heritability and selection related to population size in nature? Meta-analysis and conservation implications. Evol. Appl. 9(5), 640–657. https://doi.org/10.1111/eva.12375 (2016).

    Article 

    Google Scholar 

  • Sgrò, C. M., Lowe, A. J. & Hoffmann, A. A. Building evolutionary resilience for conserving biodiversity under climate change. Evol. Appl. 4(2), 326–337 (2011).

    Article 

    Google Scholar 

  • Hohenlohe, P. A., Funk, W. C. & Rajora, O. P. Population genomics for wildlife conservation and management. Mol. Ecol. 30(1), 62–82. https://doi.org/10.1111/mec.15720 (2021).

    Article 

    Google Scholar 

  • Walters, A. D. & Schwartz, M. K. Population genomics for the management of wild vertebrate populations. In Population Genomics: Wildlife 419–436 (Springer, 2020).

    Chapter 

    Google Scholar 

  • Willi, Y. et al. Conservation genetics as a management tool: The five best-supported paradigms to assist the management of threatened species. Proc. Natl. Acad. Sci. USA 119(1), 1–10. https://doi.org/10.1073/pnas.2105076119 (2022).

    Article 

    Google Scholar 

  • Moore, J. F. et al. The potential and practice of arboreal camera trapping. Methods Ecol. Evol. https://doi.org/10.1111/2041-210X.13666 (2021).

    Article 

    Google Scholar 

  • Frankham, R. Challenges and opportunities of genetic approaches to biological conservation. Biol. Conserv. 143(9), 1919–1927. https://doi.org/10.1016/j.biocon.2010.05.011 (2010).

    Article 

    Google Scholar 

  • Allendorf, F. W., Luikart, G. H. & Aitken, S. N. Conservation and the Genetics of Populations 2nd edn. (Wiley, 2012).

    Google Scholar 

  • Franklin, I. Evolutionary change in small populations. In Conservation Biology—An Evolutionary-Ecological Perspective 135–149 (Sinauer Associates, 1980).

    Google Scholar 

  • Soulé, M. E. Thresholds for survival: maintaining fitness and evolutionary potential. In Conservation Biology: An Evolutionary-Ecological Perspective 151–169 (Sinauer, 1980).

    Google Scholar 

  • Hoban, S. et al. Genetic diversity targets and indicators in the CBD post-2020 Global Biodiversity Framework must be improved. Biol. Conserv. https://doi.org/10.1016/J.BIOCON.2020.108654 (2020).

    Article 

    Google Scholar 

  • McGregor, D. C. et al. Genetic evidence supports three previously described species of greater glider, Petauroides volans, P. minor, and P. armillatus. Sci. Rep. 10(1), 1–11. https://doi.org/10.1038/s41598-020-76364-z (2020).

    Article 

    Google Scholar 

  • Hogg, C. J. et al. Threatened species initiative: Empowering conservation action using genomic resources. Proc. Natl. Acad. Sci. USA 119(4), e2115643118. https://doi.org/10.1073/pnas.2115643118 (2022).

    Article 

    Google Scholar 

  • Pierson, J. C. et al. Genetic factors in threatened species recovery plans on three continents. Front. Ecol. Environ. 14(8), 433–440. https://doi.org/10.1002/fee.1323 (2016).

    Article 

    Google Scholar 

  • Harris, J. M. & Maloney, K. S. S. Petauroides volans (Diprotodontia: Pseudocheiridae). Mamm. Species 42(866), 207–219. https://doi.org/10.1644/866.1 (2010).

    Article 

    Google Scholar 

  • Kavanagh, R. P. & Lambert, M. J. Food selection by the greater glider, Petauroides volans: Is foliar nitrogen a determinant of habitat quality?. Austral. Wildl. Res. 17(3), 285–299 (1990).

    Article 

    Google Scholar 

  • Youngentob, K. N. et al. Foliage chemistry influences tree choice and landscape use of a gliding marsupial folivore. J. Chem. Ecol. 37(1), 71–84. https://doi.org/10.1007/s10886-010-9889-9 (2011).

    Article 

    Google Scholar 

  • Jensen, L. M., Wallis, I. R. & Foley, W. J. The relative concentrations of nutrients and toxins dictate feeding by a vertebrate browser, the greater glider Petauroides volans. PLoS ONE 10(5), 1–12. https://doi.org/10.1371/journal.pone.0121584 (2015).

    Article 

    Google Scholar 

  • Kehl, J. & Borsboom, A. Home range, den tree use and activity patterns in the greater glider, Petauroides volans. Possums Gliders 229–236 (1984).

  • Goldingay, R. L. Characteristics of tree hollows used by Australian arboreal and scansorial mammals. Aust. J. Zool. 59(5), 277–294 (2012).

    Article 

    Google Scholar 

  • Eyre, T. J. Regional habitat selection of large gliding possums at forest stand and landscape scales in southern Queensland, Australia: I. Greater glider (Petauroides volans). For. Ecol. Manag 235(1–3), 270–282. https://doi.org/10.1016/j.foreco.2006.08.338 (2006).

    Article 

    Google Scholar 

  • Kavanagh, R. P. & Bamkin, K. L. Distribution of nocturnal forest birds and mammals in relation to the logging mosaic in south-eastern New South Wales, Australia. Biol. Conserv. 71(1), 41–53. https://doi.org/10.1016/0006-3207(94)00019-M (1995).

    Article 

    Google Scholar 

  • Lindenmayer, D. B. et al. Fire severity and landscape context effects on arboreal marsupials. Biol. Conserv. 167, 137–148 (2013).

    Article 

    Google Scholar 

  • May-Stubbles, J. C., Gracanin, A. & Mikac, K. M. Increasing fire severity negatively affects greater glider density. Wildl. Res. https://doi.org/10.1071/wr21091 (2022).

    Article 

    Google Scholar 

  • Smith, P. & Smith, J. Decline of the greater glider (Petauroides volans) in the lower Blue Mountains, New South Wales. Aust. J. Zool. 66(2), 103–114. https://doi.org/10.1071/ZO18021 (2019).

    Article 

    Google Scholar 

  • Kearney, M. R., Wintle, B. A. & Porter, W. P. Correlative and mechanistic models of species distribution provide congruent forecasts under climate change. Conserv. Lett. 3(3), 203–213. https://doi.org/10.1111/j.1755-263X.2010.00097.x (2010).

    Article 

    Google Scholar 

  • Wagner, B. et al. Climate change drives habitat contraction of a nocturnal arboreal marsupial at its physiological limits. Ecosphere 11(10), e03262 (2020).

    Article 

    Google Scholar 

  • McLean, C. M., Kavanagh, R. P., Penman, T. & Bradstock, R. The threatened status of the hollow dependent arboreal marsupial, the greater glider (Petauroides volans), can be explained by impacts from wildfire and selective logging. For. Ecol. Manag. 415, 19–25 (2018).

    Article 

    Google Scholar 

  • Lindenmayer, D. B. et al. Conservation conundrums and the challenges of managing unexplained declines of multiple species. Biol. Conserv. 221, 279–292. https://doi.org/10.1016/j.biocon.2018.03.007 (2018).

    Article 

    Google Scholar 

  • Lindenmayer, D. B. B. et al. How to make a common species rare: a case against conservation complacency. Biol. Conserv. 144(5), 1663–1672. https://doi.org/10.1016/j.biocon.2011.02.022 (2011).

    Article 

    Google Scholar 

  • IUCN. The IUCN Red List of Threatened Species (2022) https://www.iucnredlist.org (Accessed 17 Nov 2022).

  • Rübsamen, K., Hume, I. D., Foley, W. J. & Rübsamen, U. Implications of the large surface area to body mass ratio on the heat balance of the greater glider (Petauroides volans: Marsupialia). J. Comp. Physiol. B. 154(1), 105–111. https://doi.org/10.1007/BF00683223 (1984).

    Article 

    Google Scholar 

  • Wintle, B. A., Legge, S. & Woinarski, J. C. Z. After the megafires: What next for Australian wildlife?. Trends Ecol. Evol. 35(9), 753–757. https://doi.org/10.1016/j.tree.2020.06.009 (2020).

    Article 

    Google Scholar 

  • Legge, S. et al. Estimates of the impacts of the 2019–2020 fires on populations of native animal species, Brisbane (2021).

  • Hoffmann, A. A. & Sgró, C. M. Climate change and evolutionary adaptation. Nature 470(7335), 479–485. https://doi.org/10.1038/nature09670 (2011).

    Article 
    ADS 

    Google Scholar 

  • Hoffmann, A. A., Sgrò, C. M. & Kristensen, T. N. Revisiting adaptive potential, population size, and conservation. Trends Ecol. Evol. 32(7), 506–517. https://doi.org/10.1016/j.tree.2017.03.012 (2017).

    Article 

    Google Scholar 

  • Rossetto, M. et al. A conservation genomics workflow to guide practical management actions. Glob. Ecol. Conserv. 26, e01492. https://doi.org/10.1016/j.gecco.2021.e01492 (2021).

    Article 

    Google Scholar 

  • Mcmahon, B. J., Teeling, E. C. & Höglund, J. How and why should we implement genomics into conservation?. Evol. Appl. 7(9), 999–1007. https://doi.org/10.1111/eva.12193 (2014).

    Article 

    Google Scholar 

  • Hoffmann, A. et al. A framework for incorporating evolutionary genomics into biodiversity conservation and management. Clim. Change Responses https://doi.org/10.1186/s40665-014-0009-x (2015).

    Article 

    Google Scholar 

  • Lindenmayer, D. B. et al. Integrating demographic and genetic studies of the greater glider Petauroides volans in fragmented forests: predicting movement patterns and rates for future testing. Pac. Conserv. Biol. 5(1), 2–8 (1999).

    Article 

    Google Scholar 

  • Taylor, A. C., Kraaijeveld, K. & Lindenmayer, D. B. Microsatellites for the greater glider, Petauroides volans. Mol. Ecol. Notes 2(1), 57–59. https://doi.org/10.1046/j.1471-8286.2002.00148.x (2002).

    Article 

    Google Scholar 

  • Taylor, A. C., Tyndale-Biscoe, H. & Lindenmayer, D. B. Unexpected persistence on habitat islands: Genetic signatures reveal dispersal of a eucalypt-dependent marsupial through a hostile pine matrix. Mol. Ecol. 16(13), 2655–2666. https://doi.org/10.1111/j.1365-294X.2007.03331.x (2007).

    Article 

    Google Scholar 

  • NSW Scientific Committee. Greater glider population in the Mount Gibraltar Reserve area” endangered population listing. Final Determination to list an endangered ecological community under the Threatened Species Conservation Act 1995 (2015).

  • NSW Scientific Committee. Greater glider, Petauroides volans, in the Eurobodalla local government area endangered population listing. Final Determination to list an endangered ecological community under the Threatened Species Conservation Act 1995. (2007).

  • NSW Scientific Committee. Greater Glider population at Seven Mile Beach National Park Endangered population listing. Final Determination to list an endangered ecological community under the Threatened Species Conservation Act 1995 (2016).

  • Woinarski, J. C. Z., Burbidge, A. A. & Harrison, P. L. The Action Plan for Australian Mammals 2012 (CSIRO Publishing, 2014).

    Book 

    Google Scholar 

  • W. and the E. Department of Agriculture. Conservation advice for Petauroides volans (Greater Glider (southern)), Canberra (2021).

  • Gracanin, A., Pearce, A., Hofman, M., Knipler, M. & Mikac, K. Greater glider (Petauroides volans) live capture methods. Austral. Mammal. 44(2), 280–286 (2021).

    Article 

    Google Scholar 

  • Comport, S. S., Ward, S. J. & Foley, W. J. Home ranges, time budgets and food-tree use in a high-density tropical population of greater gliders, Petauroides volans minor (Pseudocheiridae: Marsupialia). Wildl. Res. 23(4), 401–419. https://doi.org/10.1071/WR9960401 (1996).

    Article 

    Google Scholar 

  • Henry, S. R. Social organisation of the greater glider (Petauroides volans) in Victoria. In Possums and Gliders (eds Smith, A. P. & Hume, I. D.) 221–228 (1984).

  • Kilian, A. et al. Diversity arrays technology: A generic genome profiling technology on open platforms. Methods Mol. Biol. 888, 67–89. https://doi.org/10.1007/978-1-61779-870-2_5 (2012).

    Article 

    Google Scholar 

  • Gruber, B., Unmack, P. J., Berry, O. F. & Georges, A. dartr: An r package to facilitate analysis of SNP data generated from reduced representation genome sequencing. Mol. Ecol. Resour. 18(3), 691–699. https://doi.org/10.1111/1755-0998.12745 (2018).

    Article 

    Google Scholar 

  • R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).

    Google Scholar 

  • Privé, F., Luu, K., Vilhjálmsson, B. J. & Blum, M. G. B. Performing highly efficient genome scans for local adaptation with R package pcadapt version 4. Mol. Biol. Evol. 37(7), 2153–2154. https://doi.org/10.1093/molbev/msaa053 (2020).

    Article 

    Google Scholar 

  • Luu, K., Bazin, E. & Blum, M. G. B. pcadapt: An R package to perform genome scans for selection based on principal component analysis. Mol. Ecol. Resour. 17(1), 67–77. https://doi.org/10.1111/1755-0998.12592 (2017).

    Article 

    Google Scholar 

  • Dabney, A., Storey, J. D. & Warnes, G. R. qvalue: Q-value estimation for false discovery rate control. R package version, vol. 1, no. 0 (2010).

  • Oksanen, J. et al. Package “vegan”. Community ecology package, version, vol. 2, no. 9, 1–295 (2013).

  • Pratt, E. A. L. et al. Seascape genomics of coastal bottlenose dolphins along strong gradients of temperature and salinity. Mol. Ecol. 31(8), 2223–2241 (2022).

    Article 

    Google Scholar 

  • Forester, B. R., Lasky, J. R., Wagner, H. H. & Urban, D. L. Comparing methods for detecting multilocus adaptation with multivariate genotype–environment associations. Mol. Ecol. 27(9), 2215–2233 (2018).

    Article 

    Google Scholar 

  • Zimmerman, S. J. et al. Environmental gradients of selection for an alpine-obligate bird, the white-tailed ptarmigan (Lagopus leucura). Heredity 126(1), 117–131 (2021).

    Article 

    Google Scholar 

  • Lott, M. J. et al. Future‐proofing the koala: Synergising genomic and environmental data for effective species management. Mol. Ecol. (2022).

  • Fick, S. E. & Hijmans, R. J. WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37(12), 4302–4315 (2017).

    Article 

    Google Scholar 

  • Goudet, J. HIERFSTAT, a package for R to compute and test hierarchical F-statistics. Mol. Ecol. Notes 5(1), 184–186. https://doi.org/10.1111/J.1471-8286.2004.00828.X (2005).

    Article 

    Google Scholar 

  • Nei, M. Molecular Evolutionary Genetics (Columbia University Press, 1987).

    Book 

    Google Scholar 

  • Meirmans, P. G. & Hedrick, P. W. Assessing population structure: FST and related measures. Mol. Ecol. Resour. 11(1), 5–18. https://doi.org/10.1111/J.1755-0998.2010.02927.X (2011).

    Article 

    Google Scholar 

  • Frankham, R., Ballou, J. D. & Briscoe, D. A. Introduction to Conservation Genetics (Cambridge University Press, 2002). https://doi.org/10.1016/j.foreco.2003.12.001.

    Book 

    Google Scholar 

  • Weir, B. S. & Cockerham, C. C. Estimating F-statistics for the analysis of population structure. Evolution 38(6), 1358. https://doi.org/10.2307/2408641 (1984).

    Article 

    Google Scholar 

  • Pembleton, L. W., Cogan, N. O. I. & Forster, J. W. StAMPP: An R package for calculation of genetic differentiation and structure of mixed-ploidy level populations. Mol. Ecol. Resour. 13(5), 946–952. https://doi.org/10.1111/1755-0998.12129 (2013).

    Article 

    Google Scholar 

  • Bonferroni, S. Teoria statistica delle classi e calcolo delle probabilita. cir.nii.ac.jp, vol. 8, 3–62 (1936).

  • Pritchard, J. K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155(2), 945–959 (2000).

    Article 

    Google Scholar 

  • Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal components: A new method for the analysis of genetically structured populations. BMC Genet. 11(1), 1–15. https://doi.org/10.1186/1471-2156-11-94/FIGURES/9 (2010).

    Article 

    Google Scholar 

  • Janes, J. K. et al. The K = 2 conundrum. Mol. Ecol. 26(14), 3594–3602. https://doi.org/10.1111/MEC.14187 (2017).

    Article 

    Google Scholar 

  • Miller, J. M., Cullingham, C. I. & Peery, R. M. The influence of a priori grouping on inference of genetic clusters: Simulation study and literature review of the DAPC method. Heredity 125, 269–280. https://doi.org/10.1038/s41437-020-0348-2 (2020).

    Article 

    Google Scholar 

  • Cullingham, C. I. et al. Confidently identifying the correct K value using the ΔK method: When does K = 2?. Mol. Ecol. 29(5), 862–869. https://doi.org/10.1111/mec.15374 (2020).

    Article 

    Google Scholar 

  • Pritchard, J., Wen, X. & Falush, D. Documentation for STRUCTURE software: version 2.3|Request PDF (2003).

  • Earl, D. A. & VonHoldt, B. M. STRUCTURE HARVESTER: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4(2), 359–361. https://doi.org/10.1007/s12686-011-9548-7 (2012).

    Article 

    Google Scholar 

  • Stankiewicz, K. H., Vasquez Kuntz, K. L. & Baums, I. B. The impact of estimator choice: Disagreement in clustering solutions across K estimators for Bayesian analysis of population genetic structure across a wide range of empirical data sets. Mol. Ecol. Resour. 22(3), 1135–1148. https://doi.org/10.1111/1755-0998.13522 (2022).

    Article 

    Google Scholar 

  • Jombart, T. Adegenet: A R package for the multivariate analysis of genetic markers. Bioinformatics 24(11), 1403–1405. https://doi.org/10.1093/bioinformatics/btn129 (2008).

    Article 

    Google Scholar 

  • Harmon, L. J. & Braude, S. Conservation of small populations: effective population sizes, inbreeding, and the 50/500 rule. In An Introduction to Methods and Models in Ecology, Evolution, and Conservation Biology 125–138 (Princeton University Press, 2010).

    Chapter 

    Google Scholar 

  • Do, C. et al. NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne ) from genetic data. Mol. Ecol. Resour. 14(1), 209–214. https://doi.org/10.1111/1755-0998.12157 (2014).

    Article 

    Google Scholar 

  • Waples, R. S. & Do, C. LDNE: A program for estimating effective population size from data on linkage disequilibrium. Mol. Ecol. Resour. 8(4), 753–756. https://doi.org/10.1111/J.1755-0998.2007.02061.X (2008).

    Article 

    Google Scholar 

  • Potvin, D. A. et al. Genetic erosion and escalating extinction risk in frogs with increasing wildfire frequency. J. Appl. Ecol. 54(3), 945–954. https://doi.org/10.1111/1365-2664.12809 (2017).

    Article 

    Google Scholar 

  • Catullo, R. A. et al. Benchmarking taxonomic and genetic diversity after the fact: Lessons learned from the catastrophic 2019–2020 Australian bushfires. Front. Ecol. Evol. 9, 292. https://doi.org/10.3389/FEVO.2021.645820/BIBTEX (2021).

    Article 
    ADS 

    Google Scholar 

  • DPIE. Fire Extent and Severity Mapping (FESM) 2019/20 (2021) https://datasets.seed.nsw.gov.au/dataset/fire-extent-and-severity-mapping-fesm-2019-20 (Accessed 23 June 2021).

  • Banks, S. C. et al. Fire severity and landscape context effects on arboreal marsupials. Biol. Conserv. 167, 137–148. https://doi.org/10.1016/j.biocon.2013.07.028 (2013).

    Article 

    Google Scholar 

  • Andrew, D., Koffel, D., Harvey, G., Griffiths, K. & Fleming, M. Rediscovery of the greater glider Petauroides volans (Marsupialia: Petauroidea) in the Royal National Park, NSW. Austral. Zool. 37(1), 23–28. https://doi.org/10.7882/AZ.2013.008 (2014).

    Article 

    Google Scholar 

  • Lindenmayer, D. et al. What 15 years of monitoring is telling us about mammals in Booderee National Park (2018).

  • Chafer, C. J. et al. The post-fire measurement of fire severity and intensity in the Christmas 2001 Sydney wildfires. Int. J. Wildland Fire 13(2), 227–240. https://doi.org/10.1071/WF03041 (2004).

    Article 

    Google Scholar 

  • Vinson, S. G., Johnson, A. P. & Mikac, K. M. Current estimates and vegetation preferences of an endangered population of the vulnerable greater glider at Seven Mile Beach National Park. Austral. Ecol. 46(2), 303–314. https://doi.org/10.1111/aec.12979 (2020).

    Article 

    Google Scholar 

  • Kavanagh, R. & Wheeler, R. Home-range of the greater glider Petauroides volans in tall montane forest of southeastern New South Wales, and changes following logging. In The Biology of Possums and Gliders (eds Goldingay, R. & Jackson, S.) 413–425 (Surrey Beatty & Sons, 2004).

    Google Scholar 

  • Fleay, D. Gliders of the Gum Trees: The Most Beautiful and Enchanting Australian Marsupials (1947).

  • Wright, S. Isolation by distance under diverse systems of mating. Genetics 31, 39–59 (1946).

    Article 

    Google Scholar 

  • McGowan, B. & Wright, C. Braidwood’s enduring Chinese heritage. Historic Environ. 23(3), 34–39 (2011).

    Google Scholar 

  • Pérez, I. et al. What is wrong with current translocations? A review and a decision-making proposal. Front. Ecol. Environ. 10(9), 494–501 (2012).

    Article 

    Google Scholar 

  • Mace, G. M. et al. Quantification of extinction risk: IUCN’s system for classifying threatened species. Conserv. Biol. 22(6), 1424–1442. https://doi.org/10.1111/j.1523-1739.2008.01044.x (2008).

    Article 

    Google Scholar 

  • Franklin, I. ‘Evolutionary change in small populations. In Conservation Biology—An Evolutionary-Ecological Perspective 135–149 (Sinauer Associates, 1980).

    Google Scholar 

  • Frankham, R., Bradshaw, C. J. A. & Brook, B. W. Genetics in conservation management: Revised recommendations for the 50/500 rules, Red List criteria and population viability analyses. Biol. Conserv. 170, 56–63. https://doi.org/10.1016/J.BIOCON.2013.12.036 (2014).

    Article 

    Google Scholar 

  • Seaborn, T. et al. Integrating genomics in population models to forecast translocation success. Restor. Ecol. 29(4), e13395. https://doi.org/10.1111/rec.13395 (2021).

    Article 

    Google Scholar 

  • Christie, M. R. & Knowles, L. L. Habitat corridors facilitate genetic resilience irrespective of species dispersal abilities or population sizes. Evol. Appl. 8(5), 454–463 (2015).

    Article 

    Google Scholar 

  • Office of Environment and Heritage. Woody extent and foliage projective cover (2016) http://data.auscover.org.au/xwiki/bin/view/Product+pages/nsw+5m+woody+extent+and+fpc (Accessed 29 Oct 2020).

  • Ashman, K. R., Watchorn, D. J., Lindenmayer, D. B. & Taylor, M. F. J. Is Australia’s environmental legislation protecting threatened species? A case study of the national listing of the greater glider. Pac. Conserv. Biol. 1980, 277–289. https://doi.org/10.1071/PC20077 (2021).

    Article 

    Google Scholar 

  • ESRI. ArcGIS 10.7.1. (Environmental Systems Research Institute, 2011).


  • Source: Ecology - nature.com

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