From science to practice: genetic estimate of brown bear population size in Slovenia and how it influenced bear management

  • Tomaž SkrbinšekEmail author
  • Roman LuštrikEmail author
  • Aleksandra Majić-Skrbinšek
  • Hubert Potočnik
  • Franc Kljun
  • Maja Jelenčič
  • Ivan Kos
  • Peter Trontelj
Original Article


Rapid development of molecular genetics has provided ecologists and wildlife managers with a powerful set of tools for studying and monitoring wildlife. We applied these tools to estimate the size of the brown bear population in Slovenia in 2007. In the years after the estimate was made public, we followed how this estimate affected policy and management actions in Slovenian bear management. We designed and executed a large-scale noninvasive genetic sampling across the range of this species in the country with a network of volunteers and estimated the size of the brown bear population in Slovenia using mark-recapture modeling. In a highly intensive 3-month sampling in autumn 2007, we collected 1057 samples. A total of 931 samples were successfully genotyped, yielding 354 different genotypes. Using mark-recapture and correcting for the edge effect caused by bears moving in and out of the sampling area across the Slovenian-Croatian border, and accounting for detected mortality, we estimated “winter” population size (after annual mortality, before reproduction) at 424 (95% confidence interval 383–458). We also observed an uneven male and female ratio of 0.405 and 0.595, respectively. Using “citizen science,” we managed to conduct a highly intensive large-scale sampling with modest financial resources, something that would be impossible to do otherwise. We produced the first robust, scientifically defensible estimate of the brown bear population size in Slovenia. Although at first reluctantly considered by managers as equivalent to other “traditional” population monitoring data, awareness of the importance of the estimate grew with time. It became the first reference point for understanding population dynamics, a basis to which current and future development of the population is being compared to. As such, we can expect it will profoundly affect Slovenian bear management in the years to come.


Noninvasive genetics Mark-recapture Brown bear Ursus arctos Wildlife management Population size Science and policy Citizen science 



Our first and greatest thanks goes to all volunteers—hunters, foresters, and all other people who love nature and bears and were willing to lend a helping hand for a greater cause. Special thanks go to the Hunters’ Association of Slovenia and the Slovenia Forest Service for their full and unconditional support. We must personally thank Marko Jonozovič and Tone Marinčič for helping us organize the sampling within the Slovenia Forest Service, and Mateja Blažič for the support and encouragement. Another essential person who helped make all this happen and supported us every step of the way was Blaž Krže, to whom we must unfortunately give our thanks posthumously. Last but not the least, we must thank the Slovenian Environment Agency which funded this research.


The study was funded by the Slovenian Environment Agency (Project “Analiza medvedov odvzetih iz narave in genetsko-molekularne raziskave populacije medveda v Sloveniji”). The follow-up regarding the effects of the results on management was funded by the Slovenian Research Agency, project J4-7362, and by the European Commission through the project LIFE DINALP BEAR (LIFE13 NAT/SI/000550).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. Genetic material from bear mortality was obtained according to the annual decree by the Ministry of the Environment of the Republic of Slovenia through the official institution in charge of brown bear monitoring, Slovenia Forest Service. No live animals were handled or harmed for the purpose of this research.


  1. Adams JR, Waits LP (2007) An efficient method for screening faecal DNA genotypes and detecting new individuals and hybrids in the red wolf (Canis rufus) experimental population area. Conserv Genet 8:123–131. CrossRefGoogle Scholar
  2. Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716–723. CrossRefGoogle Scholar
  3. Bellemain E, Swenson JE, Tallmon DA, Brunberg S, Taberlet P (2004) Estimating population size of elusive animals with DNA from hunter-collected feces: comparing four methods for brown bears. Conserv Biol 19:150–161. CrossRefGoogle Scholar
  4. Boulanger J, White GC, McLellan BN, Woods J, Proctor M, Himmer S (2002) A meta-analysis of grizzly bear DNA mark-recapture projects in British Columbia, Canada. Ursus 13:137–152Google Scholar
  5. Broquet T, Petit E (2004) Quantifying genotyping errors in noninvasive population genetics. Mol Ecol 13:3601–3608. CrossRefPubMedGoogle Scholar
  6. Brown bear (Ursus arctos) management strategy in Slovenia (2002). Accessed August 20, 2018
  7. Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach. Springer-Verlag, New YorkGoogle Scholar
  8. Chao A, Lee SM, Jeng SL (1992) Estimating population size for capture-recapture data when capture probabilities vary by time and individual animal. Biometrics 48:201–216. CrossRefPubMedGoogle Scholar
  9. Clark JD, Huber D, Servheen C (2002) Bear reintroductions: lessons and challenges. Ursus 13:335–345Google Scholar
  10. Cooch E, White G (2007) Program MARK, “a gentle introduction”. Accessed 5 May 2007
  11. De Barba M, Miquel C, Lobréaux S, Quenette PY, Swenson JE, Taberlet P (2016) High-throughput microsatellite genotyping in ecology: improved accuracy, efficiency, standardization and success with low-quantity and degraded DNA. Mol Ecol Resour 17:1–16. CrossRefGoogle Scholar
  12. Deyoung RW, Brennan LA (2005) Molecular genetics in wildlife science, conservation, and management. J Wildl Manag 69:1360–1361.[1360:MGIWSC]2.0.CO;2CrossRefGoogle Scholar
  13. Deyoung RW, Honeycutt RL, Brennan (2005) The molecular toolbox: genetic techniques in wildlife ecology and management. J Wildl Manag 69:1362–1384.[1362:TMTGTI]2.0.CO;2CrossRefGoogle Scholar
  14. Guertin DA, Ben-David M, Harestad AS, Elliott JE (2012) Fecal genotyping reveals demographic variation in river otters inhabiting a contaminated environment. J Wildl Manag 76:1540–1550. CrossRefGoogle Scholar
  15. Herrero S (2018) Bear attacks: their causes and avoidance. Rowman & Littlefield, LanhamGoogle Scholar
  16. Huber D, Kusak J, Majić-Skrbinšek A, Majnarić D, Sindičić M (2008) A multidimensional approach to managing the European brown bear in Croatia. Ursus 19:22–32.[22:AMATMT]2.0.CO;2CrossRefGoogle Scholar
  17. Huggins RM (1989) On the statistical analysis of capture experiments. Biometrika 76:133–140. CrossRefGoogle Scholar
  18. Humm JM, McCown JW, Scheick BK, Clark JD (2017) Spatially explicit population estimates for black bears based on cluster sampling. J Wildl Manag 81:1187–1201. CrossRefGoogle Scholar
  19. Jerina K, Jonozovič M, Krofel M, Skrbinšek T (2013) Range and local population densities of brown bear Ursus arctos in Slovenia. Eur J Wildl Res 59:459–467. CrossRefGoogle Scholar
  20. Karamanlidis AA, Drosopoulou E, de Gabriel Hernando M et al (2010) Noninvasive genetic studies of brown bears using power poles. Eur J Wildl Res 56:693–702. CrossRefGoogle Scholar
  21. Karamanlidis AA, de Gabriel Hernando M, Krambokoukis L, Gimenez O (2015) Evidence of a large carnivore population recovery: counting bears in Greece. J Nat Conserv 27:10–17. CrossRefGoogle Scholar
  22. Kellert SR (1997) The value of life: biological diversity and human society, Reprint edn. Island Press, WashingtonGoogle Scholar
  23. Kindberg J, Swenson JE, Ericsson G, Bellemain E, Miquel C, Taberlet P (2011) Estimating population size and trends of the Swedish brown bear Ursus arctos population. Wildl Biol 17:114–123. CrossRefGoogle Scholar
  24. Kokalj B (2016) Protection and management of brown bear (Ursus arctos) in Slovenia through media reports-media content analysis from year 2002 to year 2016. University of Ljubljana, Graduation thesisGoogle Scholar
  25. Kryštufek B, Flajšman B, Griffiths HI (2003) Living with bears: a large European carnivore in a shrinking. Ecological Forum of the Liberal Democracy of Slovenia, LjubljanaGoogle Scholar
  26. Lescureux N, Linnell JDC, Mustafa S, Melovski D, Stojanov A, Ivanov G, Avukatov V (2011) The king of the forest: local knowledge about European brown bears (Ursus arctos) and implications for their conservation in contemporary Western Macedonia. Conserv Soc 9:189–201. CrossRefGoogle Scholar
  27. Linnell JDC, Salvatori V, Boitani L (2008) Guidelines for population level management plans for large carnivores in Europe. A Large Carnivore Initiative for Europe report prepared for the European Commission (contract 070501/2005/424162/MAR/B2) Accessed 3 September 2018
  28. Lukacs PM, Burnham KP (2005) Estimating population size from DNA-based closed capture–recapture data incorporating genotyping error. J Wildl Manag 69:396–403.<0396:EPSFDC>2.0.CO;2 CrossRefGoogle Scholar
  29. Majić A, Marino Taussig de Bodonia A, Huber Đ, Bunnefeld N (2011) Dynamics of public attitudes toward bears and the role of bear hunting in Croatia. Biol Conserv 144:3018–3027. CrossRefGoogle Scholar
  30. Miller CR, Joyce P, Waits LP (2005) A new method for estimating the size of small populations from genetic mark-recapture data. Mol Ecol 14:1991–2005. CrossRefPubMedGoogle Scholar
  31. Moqanaki EM, Jiménez J, Bensch S, López-Bao JV (2018) Counting bears in the Iranian Caucasus: remarkable mismatch between scientifically-sound population estimates and perceptions. Biol Conserv 220:182–191. CrossRefGoogle Scholar
  32. Morin DJ, Kelly MJ, Waits LP (2016) Monitoring coyote population dynamics with fecal DNA and spatial capture-recapture. J Wildl Manag 80:824–836. CrossRefGoogle Scholar
  33. Mueller A-K, Chakarov N, Krüger O, Hoffman JI (2016) Long-term effective population size dynamics of an intensively monitored vertebrate population. Heredity 117:290–299. CrossRefPubMedPubMedCentralGoogle Scholar
  34. Paetkau D (2004) The optimal number of markers in genetic capture–mark–recapture studies. J Wildl Manag 68:449–452.[0449:TONOMI]2.0.CO;2CrossRefGoogle Scholar
  35. Pennell MW, Stansbury CR, Waits LP, Miller CR (2013) Capwire: a R package for estimating population census size from non-invasive genetic sampling. Mol Ecol Resour 13:154–157. CrossRefPubMedGoogle Scholar
  36. Petit E, Valiere N (2006) Estimating population size with noninvasive capture-mark-recapture data. Conserv Biol 20:1062–1073. CrossRefPubMedGoogle Scholar
  37. Poole KG, Reynolds DM, Mowat G, Paetkau D (2011) Estimating mountain goat abundance using DNA from fecal pellets. J Wildl Manag 75:1527–1534. CrossRefGoogle Scholar
  38. Pradel R (1996) Utilization of capture-mark-recapture for the study of recruitment and population growth rate. Biometrics 52:703–709. CrossRefGoogle Scholar
  39. R Core Team (2010) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
  40. Rehnus M, Bollmann K (2016) Non-invasive genetic population density estimation of mountain hares (Lepus timidus) in the Alps: systematic or opportunistic sampling? Eur J Wildl Res 62:737–747. CrossRefGoogle Scholar
  41. Reynolds H (2002) Brown Bear Management in Slovenia-2002; A letter from the president of the International Bear Association to Slovenian Minister of EnvironmentGoogle Scholar
  42. Roon DA, Waits LP, Kendall KC (2005) A simulation test of the effectiveness of several methods for error-checking non-invasive genetic data. Anim Conserv 8:203–215. CrossRefGoogle Scholar
  43. Schwartz MK, Luikart G, Waples RS (2007) Genetic monitoring as a promising tool for conservation and management. Trends Ecol Evol 22:25–33. CrossRefPubMedGoogle Scholar
  44. Scriven JJ, Woodall LC, Goulson D (2013) Nondestructive DNA sampling from bumblebee faeces. Mol Ecol Resour 13:225–229. CrossRefPubMedGoogle Scholar
  45. Slovenia Forest Service (2006). Odgovor ZGS k pisnemu stališču ZRSVN o strokovnem mnenju o odstrelu velikih zveri za leto 2006. Accessed 6 October 2016
  46. Slovenia Forest Service (2010) Strokovno mnenje za odstrel velikih zveri v letu 2010 Accessed 10 October 2016
  47. Slovenia Forest Service (2016). Strokovno mnenje za odstrel velikih zveri za obdobje 01.10.2016–30.09.2017 Accessed 3 August 2018
  48. Skrbinšek T, Jelenčič M, Waits L, Kos I, Jerina K, Trontelj P (2012a) Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches. Mol Ecol 21:862–875. CrossRefPubMedGoogle Scholar
  49. Skrbinšek T, Jelenčič M, Waits L, Kos I, Trontelj P (2010) Highly efficient multiplex PCR of noninvasive DNA does not require pre-amplification. Mol Ecol Resour 10:495–501. CrossRefPubMedGoogle Scholar
  50. Skrbinšek T, Jelenčič M, Waits LP, Potočnik H, Kos I, Trontelj P (2012b) Using a reference population yardstick to calibrate and compare genetic diversity reported in different studies: an example from the brown bear. Heredity 109:299–305. CrossRefPubMedPubMedCentralGoogle Scholar
  51. Skrbinšek T, Potočnik H, Kos I, Trontelj P (2007a) Varstvena genetika medveda, končno poročilo. pp. 1–52. Accessed 3 September 2018
  52. Skrbinšek T, Potočnik H, Kos I, Trontelj P (2007b) Z genetskimi metodami in sodelovanjem do natančnejše ocene številčnosti medvedov! Lovec, pp. 363–365. Accessed 3 September 2018
  53. Skrbinšek T, Potočnik H, Trontelj P, Kos I (2007c) Genetika v službi medveda. Lovec, pp. 425–429. Accessed 3 September 2018
  54. Skrbinšek T, Potočnik H, Trontelj P, Kos I (2007d) Vabilo k sodelovanju pri raziskavi slovenskih medvedov s pomočjo neinvazivnega genetskega vzorčenja. Lovec, pp. 430–431. Accessed 3 September 2018
  55. Skrbinšek T, Jelenčič M, Luštrik R, Konec M, Boljte B, Jerina K, Černe R, Jonozovič M, Bartol M, Huber Đ, Huber J, Reljić S, Kos I (2017) Genetic estimates of census and effective population sizes of brown bears in Northern Dinaric Mountains and South-eastern Alps. Report. Life Dinalp Bear, 50.
  56. Støen O-G, Ordiz A, Sahlén V, Arnemo JM, Sæbø S, Mattsing G, Kristofferson M, Brunberg S, Kindberg J, Swenson JE (2018) Brown bear (Ursus arctos) attacks resulting in human casualties in Scandinavia 1977–2016; management implications and recommendations. PLoS One 13:e0196876. CrossRefPubMedPubMedCentralGoogle Scholar
  57. Sugiura N (1978) Further analysis of the data by Akaike’s information criterion and the finite corrections. Commun Stat Theory Methods 7:13–26. CrossRefGoogle Scholar
  58. Swenson JE, Taberlet P, Bellemain E (2011) Genetics and conservation of European brown bears Ursus arctos: bear conservation genetics. Mammal Rev 41:87–98. CrossRefGoogle Scholar
  59. Swenson JE, Schneider M, Zedrosser A, Söderberg A, Franzén R, Kindberg J (2017) Challenges of managing a European brown bear population; lessons from Sweden, 1943-2013. Wildl Biol 2017:wlb.00251. CrossRefGoogle Scholar
  60. Taberlet P, Griffin S, Goossens B, Questiau S, Manceau V, Escaravage N, Waits LP, Bouvet J (1996) Reliable genotyping of samples with very low DNA quantities using PCR. Nucleic Acids Res 24:3189–3194. CrossRefPubMedPubMedCentralGoogle Scholar
  61. Taberlet P, Luikart G, Waits LP (1999) Noninvasive genetic sampling: look before you leap. Trends Ecol Evol 14:323–327. CrossRefPubMedGoogle Scholar
  62. Waits LP (2004) Using noninvasive genetic sampling to detect and estimate abundance of rare wildlife species. In: Thompson W (ed) Sampling rare or elusive species: concepts, designs, and techniques for estimating population parameters. Island Press, Washington DC, pp 211–228Google Scholar
  63. Waits LP, Luikart G, Taberlet P (2001) Estimating the probability of identity among genotypes in natural populations: cautions and guidelines. Mol Ecol 10:249–256. CrossRefPubMedGoogle Scholar
  64. Waits LP, Paetkau D (2005) Noninvasive genetic sampling tools for wildlife biologists: a review of applications and recommendations for accurate data collection. J Wildl Manag 69:1419–1433.[1419:NGSTFW]2.0.CO;2CrossRefGoogle Scholar
  65. White GC, Burnham KP (1999) Program MARK: survival estimation from populations of marked animals. Bird Study 46:120–139. CrossRefGoogle Scholar
  66. Wilson KR, Anderson DR (1985) Evaluation of two density estimators of small mammal population size. J Mammal 66:13–21. CrossRefGoogle Scholar
  67. Wilton CM, Beringer J, Puckett EE, Eggert LS, Belant JL (2016) Spatiotemporal factors affecting detection of black bears during noninvasive capture–recapture surveys. J Mammal 97:266–273. CrossRefGoogle Scholar
  68. Wultsch C, Waits LP, Kelly MJ (2014) Noninvasive individual and species identification of jaguars (Panthera onca), pumas (Puma concolor) and ocelots (Leopardus pardalis) in Belize, Central America using cross-species microsatellites and faecal DNA. Mol Ecol Resour 14:1171–1182. CrossRefPubMedGoogle Scholar
  69. Zedrosser A, Dahle B, Swenson JE, Gerstl N (2001) Status and management of the brown bear in Europe. Ursus 12:9–20Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Tomaž Skrbinšek
    • 1
    Email author
  • Roman Luštrik
    • 1
    Email author
  • Aleksandra Majić-Skrbinšek
    • 1
  • Hubert Potočnik
    • 1
  • Franc Kljun
    • 1
  • Maja Jelenčič
    • 1
  • Ivan Kos
    • 1
  • Peter Trontelj
    • 1
  1. 1.Biotechnical Faculty, Department of BiologyUniversity of LjubljanaLjubljanaSlovenia

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