Population Ecology

, Volume 54, Issue 1, pp 43–54 | Cite as

Evaluating the potential biases in carnivore capture–recapture studies associated with the use of lure and varying density estimation techniques using photographic-sampling data of the Malagasy civet

  • Brian D. GerberEmail author
  • Sarah M. Karpanty
  • Marcella J. Kelly
Original Article


Estimating density of elusive carnivores with capture–recapture analyses is increasingly common. However, providing unbiased and precise estimates is still a challenge due to uncertainties arising from the use of (1) bait or lure to attract animals to the detection device and (2) ad hoc boundary-strip methods to compensate for edge effects in area estimation. We used photographic-sampling data of the Malagasy civet Fossa fossana collected with and without lure to assess the effects of lure and to compare the use of four density estimators which varied in methods of area estimation. The use of lure did not affect permanent immigration or emigration, abundance and density estimation, maximum movement distances, or temporal activity patterns of Malagasy civets, but did provide more precise population estimates by increasing the number of recaptures. The spatially-explicit capture–recapture (SECR) model density estimates ±SE were the least precise as they incorporate spatial variation, but consistent with each other (Maximum likelihood-SECR = 1.38 ± 0.18, Bayesian-SECR = 1.24 ± 0.17 civets/km2), whereas estimates relying on boundary-strip methods to estimate effective trapping area did not incorporate spatial variation, varied greatly and were generally larger than SECR model estimates. Estimating carnivore density with ad hoc boundary-strip methods can lead to overestimation and/or increased uncertainty as they do not incorporate spatial variation. This may lead to inaction or poor management decisions which may jeopardize at-risk populations. In contrast, SECR models free researchers from making subjective decisions associated with boundary-strip methods and they estimate density directly, providing more comparable and valuable population estimates.


Baiting Buffer Luring MMDM Population Spatially-explicit 



Funding was provided by Virginia Tech, National Geographic Society Committee on Research and Exploration, National Science Foundation Graduate Research Fellowship Program, Sigma Xi Master’s Degree and Grants-in-Aid Awards, and the Burd Sheldon McGinnes Graduate Fellowship. We thank Madagascar National Parks and Direction des Eaux et Forêts for permission to conduct this research. We were assisted by ICTE/MICET, Centre ValBio, J. Randrianantenaina, D. Andrianoely, B. Marine, M. Kotschwar, C. Latimer, J.C. Razafimahaimodison, K. Bannar-Martin, D. Stauffer, J. Cohen, Z. Farris and J. Ivan. We thank M. Ridout for providing the R code to analyze temporal activity. Comments from two anonymous reviewers and M. Efford helped us greatly improve upon earlier drafts.


  1. Albignac R (1984) The carnivores. In: Jolly A, Oberle P, Albignac R (eds) Key environments: Madagascar. Pergamon Press, Oxford, pp 167–182Google Scholar
  2. Balme GA, Hunter LTB, Slotow R (2009) Evaluating methods for counting cryptic carnivores. J Wildl Manage 73:433–441CrossRefGoogle Scholar
  3. Batschelet E (1981) Circular statistics in biology. Academic Press, New YorkGoogle Scholar
  4. Bondrup-Nielsen S (1983) Density estimation as a function of live-trapping grid and home range size. Can J Zool 61:2361–2365CrossRefGoogle Scholar
  5. Boulanger J, McLellan BN (2001) Closure violation bias in DNA based mark-recapture population estimates of grizzly bears. Can J Zool 79:642–651CrossRefGoogle Scholar
  6. Boulanger J, McLellan BN, Woods JG, Proctor MF, Strobeck C (2004a) Sampling design and bias in DNA-based capture-mark-recapture population and density estimates of grizzly bears. J Wildl Manage 68:457–469CrossRefGoogle Scholar
  7. Boulanger J, Stenhouse G, Munro R (2004b) Sources of heterogeneity bias when DNA mark-recapture sampling methods are applied to grizzly bear (Ursus arctos) populations. J Mammal 85:618–624CrossRefGoogle Scholar
  8. Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach, 2nd edn. Springer, New YorkGoogle Scholar
  9. Cumming G, Finch S (2005) Inference by eye: confidence intervals and how to read pictures of data. Am J Psychol 60:170–180CrossRefGoogle Scholar
  10. Dillon A, Kelly MJ (2007) Ocelot Leopardus pardalis in Belize: the impact of trap spacing and distance moved on density estimates. Oryx 41:469–477CrossRefGoogle Scholar
  11. Dillon A, Kelly MJ (2008) Ocelot home range, overlap and density: comparing radio telemetry with camera trapping. J Zool 275:391–398CrossRefGoogle Scholar
  12. Efford MG (2009) Density 4.4: software for spatially explicit capture–recapture. Available at: Accessed 19 April 2011
  13. Efford MG, Borchers DL, Byrom AE (2009a) Density estimation by spatially explicit capture–recapture: likelihood-based methods. In: Thomson DL, Cooch EG, Conroy MJ (eds) Modeling demographic processes in marked populations. Springer, New York, pp 255–269CrossRefGoogle Scholar
  14. Efford MG, Dawson DK, Borchers DL (2009b) Population density estimated from locations of individuals on a passive detector array. Ecology 90:2676–2682PubMedCrossRefGoogle Scholar
  15. Gardner B, Reppucci J, Lucherini M, Royle JA (2010a) Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies. Ecology 91:3376–3383PubMedCrossRefGoogle Scholar
  16. Gardner B, Royle JA, Wegan MT, Rainbolt RE, Curtis PD (2010b) Estimating black bear density using DNA data from hair snares. J Wildl Manage 74:318–325CrossRefGoogle Scholar
  17. Garshelis D (1992) Estimating bear population size. In: McCullough DR, Barrett RH (eds) Wildlife 2001: populations. Elsevier Applied Science, London, pp 1098–1111CrossRefGoogle Scholar
  18. Gerber B, Karpanty SM, Crawford C, Kotschwar M, Randrianantenaina J (2010) An assessment of carnivore relative abundance and density in the eastern rainforests of Madagascar using remotely-triggered camera traps. Oryx 44:219–222CrossRefGoogle Scholar
  19. Goodman SM, Kerridge FJ, Ralisoamalala RC (2003) A note on the diet of Fossa fossana (Carnivora) in the central eastern humid forests of Madagascar. Mammalia 67:595–598Google Scholar
  20. Gopal R, Qureshi Q, Bhardwaj M, Jagadish Singh RK, Jhala YV (2010) Evaluating the status of the endangered tiger Panthera tigris and its prey in Panna Tiger Reserve, Madhya Pradesh, India. Oryx 44:383–389CrossRefGoogle Scholar
  21. Grassman LI, Haines AM, Janečka JE, Tewes ME (2006) Activity periods of photo-captured mammals in north central Thailand. Mammalia 70:306–309CrossRefGoogle Scholar
  22. Greenwood RJ, Sargeant AB, Johnson DH (1985) Evaluation of mark-recapture for estimating striped skunk abundance. J Wildl Manage 49:332–340CrossRefGoogle Scholar
  23. Huggins RM (1991) Some practical aspects of a conditional likelihood approach to capture experiments. Biometrics 47:725–732CrossRefGoogle Scholar
  24. IUCN (2011) IUCN red list of threatened species. Available at: Accessed 19 April, 2011
  25. Ivan JS (2011) Density, demography and movement of snowshoe hares in central Colorado. PhD dissertation. Colorado State University, Fort CollinsGoogle Scholar
  26. Jennings AP, Seymour AS, Dunstone N (2006) Ranging behaviour, spatial organization and activity of the Malay civet (Viverra tangalunga) on Buton Island, Sulawesi. J Zool 268:63–71CrossRefGoogle Scholar
  27. Jett DA, Nichols JD (1987) A field comparison of nested grid and trapping web density estimators. J Mammal 68:888–892CrossRefGoogle Scholar
  28. Karanth KU, Nichols JD (2002) Monitoring tigers and their prey: a manual for researchers managers and conservationists in tropical Asia. Centre for Wildlife Studies, BanglamoreGoogle Scholar
  29. Karanth KU, Nichols JD, Kumar NS, Hines JE (2006) Assessing tiger population dynamics using photographic capture–recapture sampling. Ecology 87:2925–2937PubMedCrossRefGoogle Scholar
  30. Kendall WL (1999) Robustness of closed capture–recapture methods to violations of the closure assumption. Ecology 80:2517–2525Google Scholar
  31. Kerridge FJ, Ralisoamalala RC, Goodman SM, Pasnick SD (2003) Fossa fossana, Malagasy striped civet, fanaloka. In: Goodman SM, Benstead JP (eds) Natural history of Madagascar. The University of Chicago Press, Chicago, pp 1363–1365Google Scholar
  32. Kolowski JM, Alonso A (2010) Density and activity patterns of ocelots (Leopardus pardalis) in northern Peru and the impact of oil exploration activities. Biol Conserv 143:917–925CrossRefGoogle Scholar
  33. Long R, MacKay P, Ray J, Zielinski W (2008) Noninvasive survey methods for carnivores. Island Press, Washington, DCGoogle Scholar
  34. Mace RD, Minta SC, Manley TL, Aune KE (1994) Estimating grizzly bear population size using camera sightings. Wildl Soc Bull 22:74–83Google Scholar
  35. 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
  36. Maffei L, Cuéllar E, Noss A (2004) One thousand jaguars (Panthera onca) in Bolivia’s Chaco? Camera trapping in the Kaa-Iya National Park. J Zool 262:295–304CrossRefGoogle Scholar
  37. Mowat G, Strobeck C (2000) Estimating population size of grizzly bears using hair capture, DNA profiling, and mark-recapture analysis. J Wildl Manage 64:183–193CrossRefGoogle Scholar
  38. Negrões N, Sarmento P, Cruz J, Eira C, Revilla E, Fonseca C, Sollmann R, Tôrres NM, Furtado MM, Jácomo ATA, Silveira L (2010) Use of camera-trapping to estimate puma density and influencing factors in central Brazil. J Wildl Manage 74:1195–1203Google Scholar
  39. Noyce KV, Garshelis DL, Coy PL (2001) Differential vulnerability of black bears to trap and camera sampling and resulting biases in mark-recapture estimates. Ursus 12:211–225Google Scholar
  40. Obbard ME, Howe EJ, Kyle CJ (2010) Empirical comparison of density estimators for large carnivores. J Appl Ecol 47:76–84CrossRefGoogle Scholar
  41. O’Brien T, Kinnaird M, Wibisono H (2003) Crouching tigers, hidden prey: Sumatran tiger and prey populations in a tropical forest landscape. Anim Conserv 6:131–139CrossRefGoogle Scholar
  42. Otis DL, Burnham KP, White GC, Anderson DR (1978) Statistical inference from capture data on closed animal populations. Wildl Monogr 62:3–135Google Scholar
  43. Parmenter RR, Yates TL, Anderson DR, Burnham KP, Dunnum JL, Franklin AB, Friggens MT, Lubow BC, Miller M, Olson GS, Parmenter CA, Pollard J, Rexstad E, Shenk TM, Stanley TR, White GC (2003) Small-mammal density estimation: a field comparison of grid-based vs. web-based density estimators. Ecol Monogr 73:1–26CrossRefGoogle Scholar
  44. Pledger S (2000) Unified maximum likelihood estimates for closed capture–recapture models using mixtures. Biometrics 56:434–442PubMedCrossRefGoogle Scholar
  45. Pradel R (1996) Utilization of capture-mark-recapture for the study of recruitment and population growth rate. Biometrics 52:703–709CrossRefGoogle Scholar
  46. Ridout MS, Linkie M (2009) Estimating overlap of daily activity patterns from camera trap data. J Agr Biol Environ Stat 14:322–337CrossRefGoogle Scholar
  47. Royle JA, Karanth KU, Gopalaswamy AM, Kumar NS (2009) Bayesian inference in camera trapping studies for a class of spatial capture–recapture models. Ecology 90:3233–3244PubMedCrossRefGoogle Scholar
  48. Sarmento P, Cruz J, Eira C, Fonseca C (2009) Evaluation of camera trapping for estimating red fox abundance. J Wildl Manage 73:1207–1212CrossRefGoogle Scholar
  49. Sarmento P, Cruz J, Eira C, Fonseca C (2010) Habitat selection and abundance of common genets Genetta genetta; using camera capture-mark-recapture data. Eur J Wildlife Res 56:59–66CrossRefGoogle Scholar
  50. Schlexer FV (2008) Attracting animals to detection devices. In: Long RA, MacKay P, Zielinski WJ, Ray JC (eds) Noninvasive survey methods for carnivores. Island Press, Washington, pp 263–326Google Scholar
  51. Soisalo MK, Cavalcanti SMC (2006) Estimating the density of a jaguar population in the Brazilian Pantanal using camera-traps and capture–recapture sampling in combination with GPS radio-telemetry. Biol Conserv 129:487–496CrossRefGoogle Scholar
  52. Stanley TR, Burnham KP (1999a) A closure test for time-specific capture–recapture data. Environ Ecol Stat 6:197–209CrossRefGoogle Scholar
  53. Stanley TR, Burnham KP (1999b) A goodness-of-fit test for capture–recapture model M t under closure. Biometrics 55:366–375PubMedCrossRefGoogle Scholar
  54. Tanaka R (1972) Investigation into the edge effect by use of capture–recapture data in a vole population. Res Popul Ecol 13:127–151CrossRefGoogle Scholar
  55. Trolle M, Noss AJ, Lima EDS, Dalponte JC (2007) Camera-trap studies of maned wolf density in the Cerrado and the Pantanal of Brazil. Biodivers Conserv 16:1197–1204CrossRefGoogle Scholar
  56. Turk RD (1997) Survey and species-screening trials of indigenous trees from the vicinity of Ranomafana National Park, Madagascar. PhD dissertation. North Carolina State University, RaleighGoogle Scholar
  57. Weinberg SL, Abramowitz SK (2008) Statistics using SPSS: an integrative approach. Cambridge University Press, CambridgeGoogle Scholar
  58. White GC (2008) Closed population estimation models and their extensions in program MARK. Environ Ecol Stat 15:89–99CrossRefGoogle Scholar
  59. White GC, Shenk TM (2001) Population estimation with radio-marked animals. In: Millspaugh JJ, Marzluff JM (eds) Radio tracking and animal populations. Academic Press, San Diego, pp 329–350CrossRefGoogle Scholar
  60. White GC, Anderson DR, Burnham KP, Otis DL (1982) Capture–recapture and removal methods for sampling closed populations. Los Alamos National Laboratory, Los AlamosGoogle Scholar
  61. Wilson KR, Anderson DR (1985) Evaluation of two density estimators of small mammal population size. J Mammal 66:13–21CrossRefGoogle Scholar
  62. Zar JH (1998) Biostatistical analysis. Prentice Hall, Upper Saddle RiverGoogle Scholar
  63. Zielinski WJ, Kucera TE (1995) American marten, fisher, lynx, and wolverine: survey methods for their detection. USDA Forest Service, Pacific Southwest Research Station, General Technical Report PSW-GTR-157, AlbanyGoogle Scholar

Copyright information

© The Society of Population Ecology and Springer 2011

Authors and Affiliations

  • Brian D. Gerber
    • 1
    Email author
  • Sarah M. Karpanty
    • 1
  • Marcella J. Kelly
    • 1
  1. 1.Department of Fish and Wildlife ConservationVirginia Polytechnic Institute and State UniversityBlacksburgUSA

Personalised recommendations