Humans and urban development mediate the sympatry of competing carnivores

  • Remington J. Moll
  • Jonathon D. Cepek
  • Patrick D. Lorch
  • Patricia M. Dennis
  • Terry Robison
  • Joshua J. Millspaugh
  • Robert A. Montgomery
Article

Abstract

Humans can profoundly shape animal community dynamics, but such effects have rarely been evaluated for terrestrial carnivores. Humans affect carnivores in both spatial and temporal dimensions via the chance of human encounter and alteration of the landscape through urban development. We investigated three hypotheses regarding how humans mediate the sympatry of larger, dominant carnivores with their smaller, subordinate counterparts. We tested these hypotheses by examining the spatio-temporal dynamics of a dominant carnivore (coyote Canis latrans) and its subordinate competitor (red fox Vulpes vulpes) across an extensive urban park system. We found that dominant and subordinate carnivores exhibited strong and often opposing spatio-temporal responses to the probability of human encounter and urban development. Spatially, coyotes visited more highly developed sites less frequently while red foxes exhibited an opposing response. Temporally, both species avoided humans via nocturnal activity. Spatio-temporally, red foxes avoided coyotes at all sites and avoided humans at highly developed sites, whereas coyotes showed a positive association with humans at such sites. Our analysis indicates that areas with higher urban development might act as spatial refugia for some subordinate carnivores against interference from larger, dominant carnivores (a “human shield” effect). Our findings also reveal that broad-scale spatial avoidance is likely a crucial component of coexistence between larger, dominant carnivores and humans, whereas finer-scale spatio-temporal avoidance is likely a key feature of coexistence between humans and smaller, subordinate carnivores. Overall, our study underscores the complex and pervasive nature of human influence over the sympatry of competing carnivores inhabiting urban systems.

Keywords

Carnivore Development Interference competition Risk effects Spatio-temporal dynamics Sympatry 

Notes

Acknowledgements

We are grateful to Cleveland Metroparks and Michigan State University staff, students, and volunteers who contributed to field work and data preparation, especially E. Clingman, T. Krynak, J. Krock, T. Kraft, G. Woodard, W. Ortiz, C. Lepard, and members of the RECaP laboratory. R.J.M. was supported by a National Science Foundation Graduate Research Fellowship. We thank the associate editor and two anonymous reviewers for comments that improved the manuscript.

Supplementary material

11252_2018_758_MOESM1_ESM.docx (58 kb)
ESM 1 (DOCX 57 kb)

References

  1. Adkins CA, Stott P (1998) Home ranges, movements and habitat associations of red foxes Vulpes vulpes in suburban Toronto, Ontario, Canada. J Zool 244:335–346CrossRefGoogle Scholar
  2. Barbieri MM, Berger JO (2004) Optimal predictive model selection. Ann Stat 32:870–897CrossRefGoogle Scholar
  3. Bejder L, Samuels A, Whitehead H, Gales N (2006) Interpreting short-term behavioral responses to disturbance within a longitudinal perspective. Anim Behav 72:1149–1158CrossRefGoogle Scholar
  4. Berger J (2007) Fear, human shields and the redistribution of prey and predators in protected areas. Biol Lett 3:620–623CrossRefPubMedPubMedCentralGoogle Scholar
  5. Burton AC, Neilson E, Moreira D, Ladle A, Steenweg R, Fisher JT, Bayne E, Boutin S (2015) Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes. J Appl Ecol 52:675–685CrossRefGoogle Scholar
  6. Cleveland Metroparks. (2017) Cleveland Metroparks by the numbers. In: Clevel. Metroparks.com. https://www.clevelandmetroparks.com/about/cleveland-metroparks-organization/by-the-numbers. Accessed 6 Dec 2017
  7. Crooks KR, Riley SPD, Gehrt SD et al (2010) Community ecology of urban carnivores. In: Gehrt SD, Riley SPD, Cypher BL (eds) Urban carnivores: ecology, conflict, and conservation. The Johns Hopkins University Press, Baltimore, Maryland, USA, pp 185–200Google Scholar
  8. Crooks KR, Soulé ME (1999) Mesopredator release and avifaunal extinctions in a fragmented system. Nature 400:563–566CrossRefGoogle Scholar
  9. Darimont CT, Carlson SM, Kinnison MT et al (2009) Human predators outpace other agents of trait change in the wild. Proc Natl Acad Sci 106:8–10CrossRefGoogle Scholar
  10. Darimont CT, Fox CH, Bryan HM, Reimchen TE (2015) The unique ecology of human predators. Science 80(349):858–861CrossRefGoogle Scholar
  11. Dirzo R, Young HS, Galetti M et al (2014) Defaunation in the Anthropocene. Science 80(345):401–406CrossRefGoogle Scholar
  12. Dorresteijn I, Schultner J, Nimmo DG, Fischer J, Hanspach J, Kuemmerle T, Kehoe L, Ritchie EG (2015) Incorporating anthropogenic effects into trophic ecology: predator–prey interactions in a human-dominated landscape. Proc R Soc B Biol Sci 282:20151602CrossRefGoogle Scholar
  13. Dröge E, Creel S, Becker MS, M’soka J (2017) Risky times and risky places interact to affect prey behaviour. Nat Ecol Evol 1:1123–1128CrossRefPubMedGoogle Scholar
  14. Ellis EC (2011) Anthropogenic transformation of the terrestrial biosphere. Philos Trans R Soc A Math Phys Eng Sci 369:1010–1035CrossRefGoogle Scholar
  15. Fischer JD, Cleeton SH, Lyons TP, Miller JR (2012) Urbanization and the predation paradox: the role of trophic dynamics in structuring vertebrate communities. Bioscience 62:809–818CrossRefGoogle Scholar
  16. Forman RTT (2016) Urban ecology principles: are urban ecology and natural area ecology really different? Landsc Ecol 31:1653–1662CrossRefGoogle Scholar
  17. Frey S, Fisher JT, Burton AC, Volpe JP (2017) Investigating animal activity patterns and temporal niche partitioning using camera-trap data: challenges and opportunities. Remote Sens. Ecol Conserv:1–10Google Scholar
  18. Frid A, Dill L (2002) Human-caused disturbance stimuli as a form of predation risk. Ecol Soc 6:11Google Scholar
  19. Gallo T, Fidino M, Lehrer EW, Magle SB (2017) Mammal diversity and metacommunity dynamics in urban green spaces: implications for urban wildlife conservation. Ecol Appl 0:1–12Google Scholar
  20. Gehr B, Hofer EJ, Muff S et al (2017) A landscape of coexistence for a large predator in a human dominated landscape. Oikos:1–11Google Scholar
  21. Gehrt SD, Anchor C, White LA (2009) Home range and landscape use of coyotes in a metropolitan landscape: conflict or coexistence? J Mammal 90:1045–1057CrossRefGoogle Scholar
  22. Gehrt SD, Brown JL, Anchor C (2011) Is the urban coyote a misantrhopic synanthrope? The case from Chicago. Cities Environ 4:3CrossRefGoogle Scholar
  23. Gehrt SD, Riley SPD (2010) Coyotes (Canis latrans). In: Gehrt SD, Riley SPD, Cypher BL (eds) Urban carnivores: ecology, conflict, and conservation. The Johns Hopkins University Press, Baltimore, Maryland, USA, pp 79–96Google Scholar
  24. Gelman A, Hill J (2007) Data analysis using regression and multilevel/hierarchical models. Cambridge University Press, New York, New YorkGoogle Scholar
  25. Goad EH, Pejchar L, Reed SE, Knight RL (2014) Habitat use by mammals varies along an exurban development gradient in northern Colorado. Biol Conserv 176:172–182CrossRefGoogle Scholar
  26. Gompper ME (2002) Top carnivores in the suburbs? Ecological and conservation issues raised by colonization of northeastern North America by coyotes. Bioscience 52:185CrossRefGoogle Scholar
  27. Gosselink TE, Van DTR, Warner RE, Joselyn MG (2003) Temporal habitat partitioning and spatial use of coyotes and red foxes in east-Central Illinois. J Wildl Manag 67:90–103CrossRefGoogle Scholar
  28. Gosselink TE, Van Deelen TR, Warner RE et al (2007) Survival and cause-specific mortality of red foxes in agricultural and urban areas of Illinois. J Wildl Manag 71:1862–1873CrossRefGoogle Scholar
  29. Greene W (2008) Functional forms for the negative binomial model for count data. Econ Lett 99:585–590CrossRefGoogle Scholar
  30. Harrison DJ, Bissonette JA, Sherburne JA (1989) Spatial relationships between coyotes and red foxes in eastern Maine. J Wildl Manag 53:181–185CrossRefGoogle Scholar
  31. Hartigan JA, Wong MA (1979) Algorithm AS 136: a K-means clustering algorithm. J R Stat Soc C 28:100–108Google Scholar
  32. Hooten MB, Hobbs ANT (2015) A guide to Bayesian model selection for ecologists. Ecol Monogr 85:3–28CrossRefGoogle Scholar
  33. Karanth KU, Srivathsa A, Vasudev D, Puri M, Parameshwaran R, Kumar NS (2017) Spatio-temporal interactions facilitate large carnivore sympatry across a resource gradient. Proc R Soc B Biol Sci 284:20161860CrossRefGoogle Scholar
  34. Kays R, Parsons AW, Baker MC et al (2016) Does hunting or hiking affect wildlife communities in protected areas? J Appl Ecol 54:242–252CrossRefGoogle Scholar
  35. Kays RW, Gompper ME, Ray JC (2008) Landscape ecology of eastern coyotes based on large-scale estimates of abundance. Ecol Appl 18:1014–1027CrossRefPubMedGoogle Scholar
  36. Kéry M, Royle JA (2015) Applied hierarchical modeling in ecology: analysis of distribution, abundance and species richness in R and BUGS / volume 1. Prelude and static models, Elsevier, San Diego, CaliforniaGoogle Scholar
  37. Kuijper DPJ, Bubnicki JW, Churski M, Mols B, van Hooft P (2015) Context dependence of risk effects: wolves and tree logs create patches of fear in an old-growth forest. Behav Ecol 26:1558–1568CrossRefGoogle Scholar
  38. Kuijper DPJ, Sahlén E, Elmhagen B, Chamaillé-Jammes S, Sand H, Lone K, Cromsigt JPGM (2016) Paws without claws? Ecological effects of large carnivores in anthropogenic landscapes. Proc R Soc B Biol Sci 283:20161625CrossRefGoogle Scholar
  39. Lashley MA, Cove MV, Chitwood MC et al (2018) Estimating wildlife activity curves: comparison of methods and sample size. Sci Rep:1–11Google Scholar
  40. Lesmeister DB, Nielsen CK, Schauber EM, Hellgren EC (2015) Spatial and temporal structure of a mesocarnivore guild in Midwestern North America. Wildl Monogr 191:1–61CrossRefGoogle Scholar
  41. Levi T, Wilmers C (2012) Wolves – coyotes – foxes : a cascade among carnivores. Ecology 93:921–929CrossRefPubMedGoogle Scholar
  42. Loveridge AJ, Valeix M, Elliot NB, Macdonald DW (2017) The landscape of anthropogenic mortality: how African lions respond to spatial variation in risk. J Appl Ecol 54:815–825CrossRefGoogle Scholar
  43. MacKenzie DI, Nichols JD, Lachman GB et al (2002) Estimating site occupancy rates when detection probabilities are less than one. Ecology 83:2248–2255CrossRefGoogle Scholar
  44. Magle SB, Hunt VM, Vernon M, Crooks KR (2012) Urban wildlife research: past, present, and future. Biol Conserv 155:23–32CrossRefGoogle Scholar
  45. Mao JS, Boyce MS, Smith DW et al (2005) Habitat selection by elk before and after wolf reintroduction in Yellowstone National Park. J Wildl Manag 69:1691–1707CrossRefGoogle Scholar
  46. Marks CA, Bloomfield TE (2006) Home-range size and selection of natal den and diurnal shelter sites by urban red foxes (Vulpes vulpes) in Melbourne. Wildl Res 33:339–347CrossRefGoogle Scholar
  47. McKinney ML (2006) Urbanization as a major cause of biotic homogenization. Biol Conserv 127:247–260CrossRefGoogle Scholar
  48. Meredith M, Ridout M (2014) Overlap: Estimates of coefficient of overlapping for animal activity patternsGoogle Scholar
  49. Mielke PW, Berry KJ, Johnson ES (1976) Multi-response permutation procedures for a priori classifications. Commun Stat - Theory Methods 5:1409–1424CrossRefGoogle Scholar
  50. Mitchell N, Strohbach MW, Pratt R, Finn WC, Strauss EG (2015) Space use by resident and transient coyotes in an urban-rural landscape mosaic. Wildl Res 42:461–469CrossRefGoogle Scholar
  51. Moll RJ, Kilshaw K, Montgomery RA, Abade L, Campbell RD, Harrington LA, Millspaugh JJ, Birks JDS, Macdonald DW (2016) Clarifying habitat niche width using broad-scale, hierarchical occupancy models: a case study with a recovering mesocarnivore. J Zool 300:177–185CrossRefGoogle Scholar
  52. Moll RJ, Redilla KM, Mudumba T, Muneza AB, Gray SM, Abade L, Hayward MW, Millspaugh JJ, Montgomery RA (2017) The many faces of fear: a synthesis of methodological variation in characterizing predation risk. J Anim Ecol 86:749–765CrossRefPubMedGoogle Scholar
  53. Monterroso P, Alves PC, Ferreras P (2013) Catch me if you can: diel activity patterns of mammalian prey and predators. Ethology 119:1044–1056CrossRefGoogle Scholar
  54. Morey PS, Gense EM, Gehrt SD (2007) Spatial and temporal variation in the diet of coyotes in the Chicago metropolitan area. Am Midl Nat 158:147–161CrossRefGoogle Scholar
  55. Mueller MA, Drake D, Allen ML (2018) Coexistence of coyotes (Canis latrans) and red foxes (Vulpes vulpes) in an urban landscape. 1–19Google Scholar
  56. Newey S, Davidson P, Nazir S, Fairhurst G, Verdicchio F, Irvine RJ, van der Wal R (2015) Limitations of recreational camera traps for wildlife management and conservation research: a practitioner’s perspective. Ambio 44:624–635CrossRefPubMedPubMedCentralGoogle Scholar
  57. Niedballa J, Sollmann R, Courtiol A, Wilting A (2016) camtrapR: an R package for efficient camera trap data management. Methods Ecol Evol 7:1457–1462CrossRefGoogle Scholar
  58. Nouvellet P, Rasmussen GSA, MacDonald DW, Courchamp F (2012) Noisy clocks and silent sunrises: measurement methods of daily activity pattern. J Zool 286:179–184CrossRefGoogle Scholar
  59. Ordeñana MA, Crooks KR, Boydston EE, Fisher RN, Lyren LM, Siudyla S, Haas CD, Harris S, Hathaway SA, Turschak GM, Miles AK, van Vuren DH (2010) Effects of urbanization on carnivore species distribution and richness. J Mammal 91:1322–1331CrossRefGoogle Scholar
  60. 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
  61. Plummer M (2003) JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling. Proceedings of the 3rd International Workshop on Distributed Statistical Computing. p 124:1–8Google Scholar
  62. Poessel SA, Breck S, Teel TL et al (2012) Patterns of human – coyote conflicts in the Denver metropolitan area. J Wildl Manag 77:297–305CrossRefGoogle Scholar
  63. Polis GA, Holt RD (1992) Intraguild predation: the dynamics of complex trophic interactions. Trends Ecol. Evol 7:151–154CrossRefPubMedGoogle Scholar
  64. Randa LA, Yunger JA (2006) Carnivore occurrence along an urban-rural gradient: a landscape-level analysis. J Mammal 87:1154–1164CrossRefGoogle Scholar
  65. Ridout MS, Linkie M (2009) Estimating overlap of daily activity patterns from camera trap data. J Agric Biol Environ Stat 14:322–337CrossRefGoogle Scholar
  66. Royle JA, Dorazio RM (2008) Hierarchical modeling and inference in ecology: the analysis of data from populations, metapopulations and communities. Elsevier Academic Press, Oxford, UKGoogle Scholar
  67. RStudio Team (2015) RStudio: integrated development for R. RStudio, Inc., BostonGoogle Scholar
  68. Šálek M, Drahníková L, Tkadlec E (2015) Changes in home range sizes and population densities of carnivore species along the natural to urban habitat gradient. Mamm Rev 45:1–15Google Scholar
  69. Sargeant AB, Allen SH (1989) Observed interactions between coyotes and red foxes. J Mammal 70:631–633CrossRefGoogle Scholar
  70. Sargeant AB, Allen SH, Hastings JO (1987) Spatial relations between sympatric coyotes and red foxes in North Dakota. J Wildl Manag 51:285–293CrossRefGoogle Scholar
  71. Schmitz OJ, Miller JRB, Trainor AM, Abrahms B (2017) Toward a community ecology of landscapes: predicting multiple predator-prey interactions across geographic space. Ecology 98:2281–2292CrossRefPubMedGoogle Scholar
  72. Schoener TW (1974) Resource partitioning in ecological communities. Science 80(185):27–39CrossRefGoogle Scholar
  73. Smith JA, Suraci JP, Clinchy M, Crawford A, Roberts D, Zanette LY, Wilmers CC (2017) Fear of the human “super predator” reduces feeding time in large carnivores. Proc R Soc B Biol Sci 284:20170433CrossRefGoogle Scholar
  74. Stevens DL, Olsen AR (2003) Variance estimation for spatially balanced samples of environmental resources. Environmetrics 14:593–610CrossRefGoogle Scholar
  75. Su YS, Yajima M (2012) R2jags: a package for running jags from RGoogle Scholar
  76. Theberge JB, Wedeles CHR (1989) Prey selection and habitat partitioning in sympatric coyote and red fox populations, Southwest Yukon. Can J Zool 67:1285–1290CrossRefGoogle Scholar
  77. Treves A, Karanth KU (2003) Human-carnivore conflict and perspectives on carnivore management worldwide. Conserv Biol 17:1491–1499CrossRefGoogle Scholar
  78. Vanak AT, Fortin D, Thaker M, Ogden M, Owen C, Greatwood S, Slotow R (2013) Moving to stay in place: behavioral mechanisms for coexistence of African large carnivores. Ecology 94:2619–2631CrossRefPubMedGoogle Scholar
  79. Wang Y, Allen ML, Wilmers CC (2015) Mesopredator spatial and temporal responses to large predators and human development in the Santa Cruz Mountains of California. Biol Conserv 190:23–33CrossRefGoogle Scholar
  80. Wapenaar W, de Bie F, Johnston D, et al (2012) Population structure of harvested red foxes (Vulpes vulpes) and coyotes (Canis latrans) on Prince Edward Island, Canada. Can Field-Naturalist 126:288–294Google Scholar
  81. Werner EE, Peacor SD (2003) A review of trait-mediated indirect interactions in ecological communities. Ecology 84:1083–1100CrossRefGoogle Scholar
  82. Wilmers CC, Wang Y, Nickel B, Houghtaling P, Shakeri Y, Allen ML, Kermish-Wells J, Yovovich V, Williams T (2013) Scale dependent behavioral responses to human development by a large predator, the puma. PLoS One 8:e60590CrossRefPubMedPubMedCentralGoogle Scholar
  83. Zuur AF, Ieno EN, Elphick CS (2010) A protocol for data exploration to avoid common statistical problems. Methods Ecol Evol 1:3–14CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Remington J. Moll
    • 1
  • Jonathon D. Cepek
    • 2
  • Patrick D. Lorch
    • 3
  • Patricia M. Dennis
    • 4
    • 5
  • Terry Robison
    • 3
  • Joshua J. Millspaugh
    • 6
  • Robert A. Montgomery
    • 1
  1. 1.Department of Fisheries and WildlifeMichigan State UniversityEast LansingUSA
  2. 2.Natural ResourcesCleveland MetroparksStrongsvilleUSA
  3. 3.Natural ResourcesCleveland MetroparksParmaUSA
  4. 4.Conservation and ScienceCleveland Metroparks ZooClevelandUSA
  5. 5.Department of Veterinary Preventive MedicineThe Ohio State UniversityColumbusUSA
  6. 6.Wildlife Biology Program, W. A. Franke College of Forestry and ConservationUniversity of MontanaMissoulaUSA

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