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Estimating density of an elusive carnivore in urban areas: use of spatially explicit capture-recapture models for city-dwelling bobcats

  • Julie K. YoungEmail author
  • Julie M. Golla
  • Derek Broman
  • Terry Blankenship
  • Richard Heilbrun
Article

Abstract

An important first step in managing urban carnivores or the habitat in which they live to reduce risk of conflicts with humans is to understand their basic ecology and population dynamics. Traditional density estimators may be inappropriate in urban areas because of extensive areas of impermeable development but new techniques that include spatial structure could be useful within large urban metropolitan areas. Yet to date, these techniques have largely remained untested. We evaluated whether spatially explicit capture-recapture models (SECR) could provide a reliable density estimate of bobcats (Lynx rufus) in the Dallas Fort-Worth metroplex, Texas, USA. We obtained 1003 photographs of bobcats in an urbanized landscape from June–November 2014, using 41 double camera stations spaced approximately 1.05 km apart. We individually identified bobcats from their distinct pelage patterns and used SECR to predict density throughout the study area. The overall density was at least one bobcat per km2, which calculated to approximately 43 independent-aged bobcats across the entire camera grid, an estimate higher than documented bobcat densities in both rural and peri-urban studies in Texas. Our study revealed a high density of bobcats in an urban landscape despite most assumptions that bobcats require large areas of habitat and are sensitive to fragmentation.

Keywords

Camera trap Carnivore ecology Lynx rufus Population estimate SECR model 

Notes

Acknowledgements

We thank the many technicians and volunteers who helped collect data and J. Draper for assistance with statistics and figures. We thank the editor and two anonymous reviewers for comments on earlier drafts. This study was funded by USDA-National Wildlife Research Center, Utah State University, the Welder Wildlife Foundation, Texas Parks & Wildlife Department, and in part, by USFWS Wildlife Restoration Grant W139 T2-4 and by in-kind contributions of Texas Parks & Wildlife Department volunteers. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US government.

Compliance with ethical standards

Ethical approval

This study was conducted in accordance with the USDA’s National Wildlife Research Center’s Institutional Animal Care and Use Committee (IACUC) regulations (QA-2211).

Conflict of interest

The authors have no conflict of interest.

References

  1. Adams LW (2005) Urban wildlife ecology and conservation: a brief history of the discipline. Urb Ecosyst 8:139–156CrossRefGoogle Scholar
  2. Alexander JS, Gopalaswamy AM, Shi K, Riordan P (2015) Face value: towards robust estimates of snow leopard densities. PLoS One 10:e0134815CrossRefGoogle Scholar
  3. Alonso RS (2012) The effects of urbanization and road development on carnivores in Southern California. Dissertation, Colorado State UniversityGoogle Scholar
  4. Athreya V, Odden M, Linnell JDC, Krishnaswamy J, Karanth U (2013) Big cats in our backyards: persistence of large carnivores in a human dominated landscape in India. PLoS One 8:e57872CrossRefGoogle Scholar
  5. Bashir T, Bhattacharya T, Poudyal K, Sathyakumar S, Qureshi Q (2013) Estimating leopard cat Prionailurus bengalensis densities using photographic captures and recaptures. Wild Biol 19:462–472CrossRefGoogle Scholar
  6. Bateman PW, Fleming PA (2012) Big city life: carnivores in urban environments. J Zool 287:1–23CrossRefGoogle Scholar
  7. Beier P (1995) Dispersal of juvenile cougars in fragmented habitat. J Wildl Manag 59:228–237CrossRefGoogle Scholar
  8. Bhatia S, Athreya V, Grenyer R, MacDonald DW (2013) Understanding the role of representations of human-leopard conflict in Mumbai through media-content analysis. Cons Biol 27:588–594CrossRefGoogle Scholar
  9. Blanc L, Marboutin E, Gatti S, Gimenez O (2013) Abundance of rare and elusive species: empirical investigation of closed versus spatially explicit capture–recapture models with lynx as a case study. J Wildl Manag 77:372–378CrossRefGoogle Scholar
  10. Borchers DL, Efford M (2008) Spatially explicit maximum likelihood methods for capture–recapture studies. Biometrics 64:377–385CrossRefGoogle Scholar
  11. Braczkowski AR, O'Bryan CJ, Stringer MJ, Watson JE, Possingham HP, Beyer HL (2018) Leopards provide public health benefits in Mumbai, India. Frontiers Ecol Environ 16:176–182CrossRefGoogle Scholar
  12. Carbone C, Gittleman JL (2002) A common rule for the scaling of carnivore density. Science 295(5563):2273–2276.  https://doi.org/10.1126/science.1067994 CrossRefPubMedGoogle Scholar
  13. Clare JD, Anderson EM, MacFarland DM (2015a) Predicting bobcat abundance at a landscape scale and evaluating occupancy as a density index in Central Wisconsin. J Wild Manage 79:469–480CrossRefGoogle Scholar
  14. Clare JD, Anderson EM, MacFarland DM, Sloss BL (2015b) Comparing the costs and detectability of bobcat using scat-detecting dog and remote camera surveys in Central Wisconsin. Wild Soc Bull 39:210–217CrossRefGoogle Scholar
  15. Crooks KR (2002) Relative sensitivities of mammalian carnivores to habitat fragmentation. Cons Biol 16:488–502.  https://doi.org/10.1046/j.1523-1739.2002.00386.x CrossRefGoogle Scholar
  16. Crooks KR, Burdett CL, Theobald DM, Rondinini C, Boitani L (2011) Global patterns of fragmentation and connectivity of mammalian carnivore habitat. Phil Trans R Soc London B Biol Sci 366:2642–2651CrossRefGoogle Scholar
  17. Don Carlos AW, Bright AD, Teel TL, Vaske JJ (2009) Human–black bear conflict in urban areas: an integrated approach to management response. Human Dimens Wildl 14:174–184CrossRefGoogle Scholar
  18. Efford MG (2011) SECR-spatially explicit capture-recapture in R. University of Otago, Dunedin Google ScholarGoogle Scholar
  19. Efford MG, Fewster RM (2013) Estimating population size by spatially explicit capture–recapture. Oikos 122:918–928CrossRefGoogle Scholar
  20. Golla JM (2017) Urban bobcat (Lynx rufus) ecology in the Dallas-Fort Worth, Texas Metroplex. Thesis, Utah State UniversityGoogle Scholar
  21. Gould FW (1975) The grasses of Texas. Texas A&M University, Texas Agricultural Experiment StationGoogle Scholar
  22. Heilbrun RD, Silvy NJ, Tewes ME, Peterson MJ (2003) Using automatically-triggered cameras to individually identify bobcats. Wild Soc Bull 31:748–755Google Scholar
  23. Heilbrun RD, Silvy NJ, Peterson MJ, Tewes ME (2006) Estimating bobcat abundance using automatically triggered cameras. Wild Soc Bull 34:69–73CrossRefGoogle Scholar
  24. Homer CG, Dewitz JA, Yang L, Jin S, Danielson P, Xian G, Coulston J, Herold ND, Wickham JD, Megown K (2015) Completion of the 2011 national land cover database for the conterminous United States - representing a decade of land cover change information. Photogram Eng Remote Sens 81:345–354Google Scholar
  25. Ivan JS, Newkirk ES (2016) CPW photo warehouse: a custom database to facilitate archiving, identifying, summarizing and managing photo data collected from camera traps. Methods Ecol Evol 7:499–504CrossRefGoogle Scholar
  26. Kalle R, Ramesh T, Qureshi Q, Sankar K (2011) Density of tiger and leopard in a tropical deciduous forest of Mudumalai Tiger Reserve, southern India, as estimated using photographic capture–recapture sampling. Acta Theriol 56:335–342.  https://doi.org/10.1007/s13364-011-0038-9 CrossRefGoogle Scholar
  27. Kane MD, Morin DJ, Kelly MJ (2015) Potential for camera-traps and spatial mark-resight models to improve monitoring of the critically endangered west African lion (Panthera leo). Biodivers Conserv 24:3527–3541CrossRefGoogle Scholar
  28. Karanth KU, Nichols JD (1998) Estimation of tiger densities in India using photographic captures and recaptures. Ecology 79:2852–2862CrossRefGoogle Scholar
  29. Lewis JS, Logan KA, Alldredge MW, Bailey LL, VandeWoude S, Crooks KR (2015) The effects of urbanization on population density, occupancy, and detection probability of wild felids. Ecol Appl 25:1880–1895CrossRefGoogle Scholar
  30. Lombardi JV, Comer CE, Scognamillo DG, Conway WC (2017) Coyote, fox, and bobcat response to anthropogenic and natural landscape features in a small urban area. Urban Ecosyst 20:1239–1248CrossRefGoogle Scholar
  31. Lowry H, Lill A, Wong BB (2013) Behavioural responses of wildlife to urban environments. Biol Rev 88(3):537–549CrossRefGoogle Scholar
  32. Magle SB, Hunt VM, Vernon M, Crooks KR (2012) Urban wildlife research: past, present, and future. Biol Conserv 155:23–32CrossRefGoogle Scholar
  33. McCleery RA (2009) Changes in fox squirrel anti-predator behaviors across the urban–rural gradient. Landsc Ecol 24:483–493CrossRefGoogle Scholar
  34. Morin DJ, Waits LP, McNitt DC, Kelly MJ (2018) Efficient single-survey estimation of carnivore density using fecal DNA and spatial capture-recapture: a bobcat case study. Pop Ecol 60:197–209CrossRefGoogle Scholar
  35. Oriol-Cotterill A, Valeix M, Frank LG, Riginos C, Macdonald DW (2015) Landscapes of coexistence for terrestrial carnivores: the ecological consequences of being downgraded from ultimate to penultimate predator by humans. Oikos 124:1263–1273CrossRefGoogle Scholar
  36. Otis D, Burnham K, White G, Anderson D (1978) Statistical inference from capture data on closed animal populations. Wild Monog 62:3–135Google Scholar
  37. Poessel SA, Burdett CL, Boydston EE, Lyren LM, Alonso RS, Fisher RN, Crooks KR (2014) Roads influence movement and home ranges of a fragmentation-sensitive carnivore, the bobcat, in an urban landscape. Biol Conserv 180:224–232CrossRefGoogle Scholar
  38. R Core Team (2013) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/
  39. Riley SP (2006) Spatial ecology of bobcats and gray foxes in urban and rural zones of a national park. J Wild Manage 70:1425–1435CrossRefGoogle Scholar
  40. Riley SPD, Sauvajot RM, Fuller TK, York EC, Kamradt DA, Bromley C, Wayne RK (2003) Effects of urbanization and habitat fragmentation on bobcats and coyotes in southern California. Conserv Biol 17:566–576CrossRefGoogle Scholar
  41. Ritchie EG, Johnson CN (2009) Predator interactions, mesopredator release and biodiversity conservation. Ecol Lett 12:982–998.  https://doi.org/10.1111/j.1461-0248.2009.01347.x CrossRefPubMedGoogle Scholar
  42. Royle JA, Karanth KU, Gopalaswamy AM, Kumar NS (2009) Bayesian inference in camera trapping studies for a class of spatial capture–recapture models. Ecology 90:3233–3244.  https://doi.org/10.1890/08-1481.1 CrossRefPubMedGoogle Scholar
  43. Ruell AEW, Riley SPD, Douglas MR, Antolin MF, Pollinger JR, Tracey JA, Lyren LM, Boydsten EE, Fisher RN, Crooks KR (2012) Urban habitat fragmentation and genetic population structure of bobcats in coastal southern California. Amer Mid Nat 168:265–280.  https://doi.org/10.1674/0003-0031-168.2.265 CrossRefGoogle Scholar
  44. Singh P, Gopalaswamy AM, Karanth KU (2010) Factors influencing densities of striped hyenas (Hyaena hyaena) in arid regions of India. J Mamm 91:1152–1159.  https://doi.org/10.1644/09-MAMM-A-wide CrossRefGoogle Scholar
  45. Sollmann R, Furtado MM, Gardner B et al (2011) Improving density estimates for elusive carnivores: accounting for sex-specific detection and movements using spatial capture–recapture models for jaguars in Central Brazil. Biol Conserv 144:1017–1024.  https://doi.org/10.1016/j.biocon.2010.12.011 CrossRefGoogle Scholar
  46. Stricker HK, Belant JL, Beyer DE Jr et al (2012) Use of modified snares to estimate bobcat abundance. Wildl Soc Bull 36:257–263CrossRefGoogle Scholar
  47. Thornton DH, Pekins CE (2015) Spatially explicit capture–recapture analysis of bobcat (Lynx rufus) density: implications for mesocarnivore monitoring. Wild Res 42:394–404CrossRefGoogle Scholar
  48. Tigas LA, Van Vuren DH, Sauvajot RM (2002) Behavioral responses of bobcats and coyotes to habitat fragmentation and corridors in an urban environment. Biol Conserv 108:299–306CrossRefGoogle Scholar
  49. US Census Bureau (2014) Current estimates data. Washington, D.C: US Census Bureau. Available at http://www.census.gov/popest/data/national/totals/2014/index.html
  50. Valeix M, Hemson G, Loveridge AJ, Mills G, Macdonald DW (2012) Behavioural adjustments of a large carnivore to access secondary prey in a human-dominated landscape. J Appl Ecol 49:73–81CrossRefGoogle Scholar
  51. Wolfe ML, Koons DN, Stoner DC, Terletzky P, Gese EM, Choate DM, Aubry LM (2015) Is anthropogenic cougar mortality compensated by changes in natural mortality in Utah? Insight from long-term studies. Biol Conserv 182:187–196CrossRefGoogle Scholar
  52. Xian G, Homer C, Dewitz J, Fry J, Hossain N, Wickham J (2011) The change of impervious surface area between 2001 and 2006 in the conterminous United States. Photogram Eng Remote Sens 77:758–762Google Scholar

Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2019

Authors and Affiliations

  1. 1.USDA National Wildlife Research Center, Predator Research Facility and Department of Wildland ResourcesUtah State UniversityLoganUSA
  2. 2.Department of Wildland ResourcesUtah State UniversityLoganUSA
  3. 3.Texas Parks and Wildlife DepartmentDallasUSA
  4. 4.Welder Wildlife FoundationSintonUSA
  5. 5.Texas Parks and Wildlife DepartmentSan AntonioUSA

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