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Mammal Research

, Volume 64, Issue 1, pp 147–154 | Cite as

DNA from scats combined with capture–recapture modeling: a promising tool for estimating the density of red foxes—a pilot study in a boreal forest in southeast Norway

  • Per WeggeEmail author
  • Beate Banken Bakke
  • Morten Odden
  • Jørund Rolstad
Methods Paper

Abstract

In spite of its important role as predator of small game species, estimating the density of red fox Vulpes vulpes has been hampered by the species’ highly variable ranging pattern and elusive behavior. DNA analysis from scats combined with spatially explicit capture–recapture (SECR) modeling might remedy this. In a 50-km2 coniferous forest in southeast Norway, we collected scats on logging roads in late winter. DNA was extracted, amplified, and genotyped using 11 microsatellite markers. Of 184 samples collected, 126 were genotyped successfully, of which 46 (36.5%) produced individual genetic profiles. Twenty-five of these were different individuals: 13 females and 12 males. Nine of them were identified in multiple scats; mean recapture rate among all was 1.8/animal. Applying a conventional capture–recapture model (CAPWIRE) to the genotyped samples, 36 (95% CI 26–52) different individuals were estimated to have been present in the area during the sampling period. For estimating population density, we constructed three differently sized occupancy areas based on distances between recaptures, viz. ½ and 1/1 mean maximum distance moved (MMDM) and the local convex hull home range method (LoCoH). Areas varied from 60 km2 (½MMDM) to 112 km2 (MMDM), producing density estimates of 0.60 and 0.32 foxes/km2, respectively; the 95% LoCoH range method produced an estimate of 0.44 animals/km2. Based on SECR modeling, the density was estimated at 0.38 (95% CI 0.21–0.70) animals/km2. Smaller confidence intervals are expected with more appropriate sampling design than used in this pilot study.

Keywords

Density estimation Genetic sampling Meso-predator Scatology Red fox SECR analysis 

Notes

Acknowledgements

We thank the laboratory staff of The Norwegian Institute of Bioeconomy Research (NIBIO) at Svanhovd for conducting the genetic analysis of the scats.

Funding information

The central office of NIBIO at Ås funded the study.

Supplementary material

13364_2018_408_MOESM1_ESM.docx (34 kb)
ESM 1 (DOCX 33 kb)

References

  1. Atterby H, Allnutt TR, MacNicoll AD, Jones EP, Smith GC (2015) Population genetic structure of the red fox (Vulpes vulpes) in the UK. Mamm Res 60:9–19CrossRefGoogle Scholar
  2. Baines D, Aebischer N, Maclead A, Woods J (2013) Pine marten Martes martes and red fox Vulpes vulpes sign indices in Scottish forests: population change and reliability of field identification of scats. Wildl Biol 19:490–495CrossRefGoogle Scholar
  3. Brittas R, Marcström V, Kenward RE, Karlbom M (1992) Survival and breeding success of reared and wild ring-necked pheasants in Sweden. J Wildl Manag 56:368–376CrossRefGoogle Scholar
  4. Brownstein MJ, Carpten JD, Smith JR (1996) Modulation of non-templated nucleotide addition by Taq DNA polymerase: primer modifications that facilitate genotyping. Biotechniques 20:1004–1010CrossRefGoogle Scholar
  5. Cagnacci F, Boitani L, Powell RA, Boyce MS (2010) Animal ecology meets GPS-based radiotelemetry: a perfect storm of opportunities and challenges. Philos Trans R Soc Lond Ser B Biol Sci 365:2157–2162CrossRefGoogle Scholar
  6. Cavallini P (1994) Faeces count as an index of fox abundance. Acta Theriol 39:417–424CrossRefGoogle Scholar
  7. Dell-Arte GL, Laaksonen T, Norrdahl K, Korpimaki E (2007) Variation in the diet composition of a generalist predator, the red fox, in relation to season and density of main prey. Acta Oecol 31:276–281CrossRefGoogle Scholar
  8. Efford M (2018) Spatially Explicit Capture-Recapture, Version 3.17 (in R)Google Scholar
  9. Foster RJ, Harmsen BJ (2012) A critique of density estimation from camera-trap data. J Wildl Manag 76:224–236.  https://doi.org/10.1002/jwmg.275 CrossRefGoogle Scholar
  10. Galov A, Sindicic M, Andreanszky T, Curkovic S, Dezdek D, Slavica A, Hartl GB, Krueger B (2014) High genetic diversity and low population structure in red foxes (Vulpes vulpes) from Croatia. Mamm Biol 79:77–80CrossRefGoogle Scholar
  11. Getz WM, Fortmann-Roe S, Cross PC, Lyons AJ, Ryan SJ, Wilmers CC (2007) LoCoH: nonparametric kernel methods for constructing home ranges and utilization distributions. PLoS One.  https://doi.org/10.1371/journal.pone.00di00207
  12. Gopalaswamy AM, Royle JA, Hines JE, Singh P, Jathanna D, Kumar NS, Karanth KU (2012) Program SPACECAP: software for estimating animal density using spatially explicit capture–recapture models. Methods Ecol Evol 3:1067–1072CrossRefGoogle Scholar
  13. Güthlin D, Storch I, Küchenhoff H (2014) Is it possible to individually identify red foxes from photographs? Wildl Soc Bull 38:205–210CrossRefGoogle Scholar
  14. Janečka JE, Munkhtsog B, Jackson RM, Naranbataar G, Mallon DP, Murphy WJ (2011) Comparison of noninvasive genetic and camera-trapping techniques for surveying snow leopards. J Mammal 92:771–783.  https://doi.org/10.1644/10-MAMM-A-036.1 CrossRefGoogle Scholar
  15. Jarnemo A (2004) Predation processes: behavioural interactions between red fox and roe deer during the fawning season. J Ethol 22:167–173CrossRefGoogle Scholar
  16. Karanth KU, Nichols JD (1998) Estimation of tiger densities in India using photographic captures and recaptures. Ecology 79:2852–2862CrossRefGoogle Scholar
  17. Kauhala K, Helle P, Helle E (2000) Predator control and the density and reproductive success of grouse populations in Finland. Ecography 23:161–168CrossRefGoogle Scholar
  18. Kawanishi K, Sunquist ME (2004) Conservation status of tigers in a primary rainforest of peninsular Malaysia. Biol Conserv 120:329–344CrossRefGoogle Scholar
  19. Kery M, Gardner B, Stoeckle T, Weber D, Royle JA (2011) Use of spatial capture-recapture modeling and DNA data to estimate densities of elusive animals. Conserv Biol 25:356–364Google Scholar
  20. Lindström, ER (1982) Population ecology of the red fox (Vulpes vulpes L.) in relation to food supply. PhD dissertation, University StockholmGoogle Scholar
  21. Lindström ER (1989) Food limitation and social regulation in a red fox population. Holarct Ecol 12:70–79Google Scholar
  22. Lindström ER, Andren H, Angelstam P, Cederlund G, Hörnfeldt B, Jäderberg L, Lemnell P-A, Martinsson B, Sköld K, Swenson JE (1994) Disease reveals the predator: sarcoptic mange, red fox predation, and prey populations. Ecology 75:1042–1049CrossRefGoogle Scholar
  23. MacDonald DW (1977) On food preference in the red fox. Mammal Rev 7:7–23CrossRefGoogle Scholar
  24. Maffei L, Noss AJ (2008) How small is too small? Camera trap survey areas and density estimates for ocelots in the Bolivian Chaco. Biotropica 40:71–75Google Scholar
  25. Manivannan A (2013) Population genetic analysis of red foxes (Vulpes vulpes) in Hedmark County, Norway—a pilot study. MSc thesis, Hedmark University College, NorwayGoogle Scholar
  26. 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.  https://doi.org/10.1111/j.1365-294X.2005.02577 CrossRefGoogle Scholar
  27. Mondol S, Karanth KU, Kumar NS, Gopalaswamy AM, Andheria A, Ramakrishnan U (2009) Evaluation of non-invasive genetic sampling methods for estimating tiger population size. Biol Conserv 142:2350–2360CrossRefGoogle Scholar
  28. Panasci M, Ballard WB, Breck SW, Rodriguez D, Densmore LD, Western DB, Baker RJ (2011) Evaluation of fecal DNA preservation techniques and effects of sample age and diet on genotyping success. USDA National Wildlife Research Center, Staff Publication 1301Google Scholar
  29. Piggott MP (2004) Effect of sample age and season of collection on the reliability of microsatellite genotyping of faecal DNA. Wildl Res 31:485–493CrossRefGoogle Scholar
  30. Piggott MP, Taylor AC (2003) Extensive evaluation of faecal preservation and DNA extraction methods in Australian native and introduced species. Aust J Zool 51:341–355CrossRefGoogle Scholar
  31. Reynolds JC, Tapper SC (1995) The ecology of the red fox Vulpes vulpes in relation to small game in rural southern England. Wildl Biol 1:105–119CrossRefGoogle Scholar
  32. Royle JA, Karanth KU, Gopalaswamy AM, Kumar N (2009) Bayesian inference in camera trapping studies for a class of spatial capture–recapture models. Ecology 90:3233–3244CrossRefGoogle Scholar
  33. Ruette S, Stahl P, Albaret M (2003) Applying distance-sampling methods to spotlight counts of red foxes. J Appl Ecol 40:32–43CrossRefGoogle Scholar
  34. Santini A, Luccini V, Fabbri E, Randi E (2007) Ageing and environmental factors affect PCR success in wolf (Canis lupus) excremental DNA samples. Mol Ecol Notes 7:955–961Google Scholar
  35. Sarmento P, Cruz J, Eira C, Fonseca C (2009) Evaluation of camera trapping for estimating red fox abundance. J Wildl Manag 73:1207–1212.  https://doi.org/10.2193/2008-288 CrossRefGoogle Scholar
  36. Sollmann R, Gardner B, Belant JL (2012) How does spatial study design influence density estimates from spatial capture-recapture models? PLoS One 7:e34575CrossRefGoogle Scholar
  37. Stenglein JL, De Barba M, Ausband DE, Waits LP (2010) Impacts of sampling within a faeces on DNA quality in two carnivore species. Mol Ecol Resour 10:109–114CrossRefGoogle Scholar
  38. Taberlet P, Waits LP, Luikart G (1999) Noninvasive genetic sampling: look before you leap. Trends Ecol Evol 14:323–327CrossRefGoogle Scholar
  39. Thapa K, Shrestha R, Karki J, Thapa GJ, Subedi N, Pradhan NMB, Dhakal M, Khanal P, Kelly MJ (2014) Leopard Panthera pardus fusca density in the seasonally dry, subtropical forest in the Bhabhar of Terai Arc, Nepal. Adv Ecol, Article ID 286949, 12 pages.  https://doi.org/10.1155/2014/28694
  40. Travaini A, Laffitte R, Delibes M (1996) Determining the relative abundance of European red foxes by scent-station methodology. Wildl Soc Bull 24:500–504Google Scholar
  41. Vine SJ, Crowther MS, Lapidge J, Dickman CR, Mooney N, Piggott MP, English AW (2009) Comparison of methods to detect rare and cryptic species: a case study using the red fox (Vulpes vulpes). Wildl Res 36:436–446CrossRefGoogle Scholar
  42. Vynne C, Baker MR, Breuer ZK, Wasser SK (2012) Factors influencing degradation of DNA and hormones in maned wolf scat. Anim Cons  https://doi.org/10.1111/j1469-1795.2011.00503.x
  43. 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 69:1419–1433CrossRefGoogle Scholar
  44. Walton Z, Samelius G, Odden M, Willebrand T (2017) Variation in home range size of red foxes Vulpes vulpes along a gradient of productivity and human landscape alteration. PLoS One 12:e0175291.  https://doi.org/10.1371/journal.pone.0175291 CrossRefGoogle Scholar
  45. Wandeler P, Funk M (2006) Short microsatellite DNA markers for the red fox (Vulpes vulpes). Mol Ecol Notes 6:98–100CrossRefGoogle Scholar
  46. Webbon CC, Baker PJ, Harris S (2004) Faecal density counts for monitoring changes in red fox numbers in rural Britain. J Appl Ecol 41:768–779CrossRefGoogle Scholar
  47. Wegge P, Rolstad J (2011) Clearcutting forestry and Eurasian boreal forest grouse: long-term monitoring of sympatric capercaillie Tetrao urogallus and black grouse T. tetrix reveals unexpected effects on their population performances. For Ecol Manag 261:1520–1529CrossRefGoogle Scholar
  48. Wultsch C, Waits LP, Hallerman EM, Kelly MC (2015) Optimizing collection methods for noninvasive genetic sampling of neotropical felids. Wildl Soc Bull 39:403–412CrossRefGoogle Scholar
  49. Yu J-N, Chung C-U, Oh KH, Lee B-K, Lim CE (2015) Development of novel microsatellite markers for conservation genetic studies of Vulpes vulpes (Canidae) by using next-generation sequencing method. Gen Mol Res 14:3980–3983CrossRefGoogle Scholar

Copyright information

© Mammal Research Institute, Polish Academy of Sciences, Białowieża, Poland 2018

Authors and Affiliations

  1. 1.Faculty of Environmental Sciences and Natural Resource ManagementNorwegian University of Life SciencesÅsNorway
  2. 2.Norwegian Institute of Bioeconomy ResearchSvanvikNorway
  3. 3.Inland Norway University of Applied SciencesElverumNorway
  4. 4.Norwegian Institute of Bioeconomy ResearchÅsNorway

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