Dog days are just starting: the ecology invasion of free-ranging dogs (Canis familiaris) in a protected area of the Atlantic Forest

  • Marina ZaninEmail author
  • Christyan Lemos Bergamaschi
  • Juliana Rodrigues Ferreira
  • Sérgio Lucena Mendes
  • Danielle Oliveira Moreira
Original Article


Free-ranging dogs (Canis familiaris, Linnaeus, 1758) are highly invasive exotic species because of their ecological flexibility and adaptability and their close relationship with humans. They have occupied many protected areas around the world, threatening natural ecosystems and causing environmental damage. To understand the potential pressures of free-ranging dogs, we investigated three main aspects of their population ecology by placing camera traps in ecologically distinct locations of the Augusto Ruschi Biological Reserve (ARBR), southeastern Brazil. In this study, we assessed (i) the daily activity patterns according to circular kernel density function, (ii) the habitat selection according to occupancy models, and (iii) the population density according to spatial capture-recapture models. Free-ranging dogs in the ARBR are active irregularly (cathemeral behavior), display multiple daily activity peaks, and use approximately 73% of the study area. Our results suggest that free-ranging dogs exhibit broad temporal and spatial plasticity, so they can potentially harm a broad array of native species through competition or predation. The high temporal and spatial use range of free-ranging dogs is possibly a consequence of their high population density (0.55 ± SD 0.18 individuals/km2), representing one of the highest such estimates for the Atlantic Forest, and one that is higher than several estimates for ocelots, an ecologically similar native mesocarnivore. Our results suggest that the free-ranging dog population in the ARBR likely comprises a mix of domestic, stray, and feral individuals, with consequent management challenges that should focus on prevention, control, and perhaps eradication strategies.


Temporal utilization Daily activity pattern Spatial utilization Occupancy model Population density 



We thank Evanildo José Volpi (in memoriam) and Rogério Ribeiro for helping with fieldwork.

Funding information

This study was authorized by Brazilian environmental authorities (Instituto Chico Mendes de Conservação da Biodiversidade—ICMBio; Number: 54003-1). It was supported by the Research Support Foundation of the state of Espírito Santo (Fundação de Amparo à Pesquisa do Espírito Santo) through project number 0833/2015. MZ was supported by a CNPq DCR fellowship (number 312627/2015-7). DOM is supported by a Capes PNPD fellowship. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001.

Supplementary material

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  1. Agostinelli C, Lund U (2017) circular: circular statistics. R package version 0.4–93.
  2. Agostinelli C. (2012) ‘CircStats’: circular statistic R package version 0.2–4. CircStats
  3. Aschoff J (1966) Circadian activity patterns with two peaks. Ecology 47:657–662Google Scholar
  4. Bartón K (2018) MuMIn: Multi-Model Inference. R package version 1.40.4.
  5. Bögel K, Frucht K, Drysdale G, Remfry J (1990) Guidelines for dog population management. GenevaGoogle Scholar
  6. Brasil (2000) SNUC - Sistema Nacional de Unidades de Conservação. BrasilGoogle Scholar
  7. Brasil (2017) Lei N° 13.426. BrasilGoogle Scholar
  8. Burnham KP, Anderson DR (2004) Multimodel inference: understanding AIC and BIC in model selection. Sociol Methods Res 33:261–304Google Scholar
  9. Calhoun JB, Casby JU (1958) Calculation of home range and density of small mammals. Public Health Monogr 73:1143–1145Google Scholar
  10. Chape S, Harrison J, Spalding M, Lysenko I (2005) Measuring the extent and effectiveness of protected areas as an indicator for meeting global biodiversity targets. Philos Trans R Soc B Biol Sci 360:443–455Google Scholar
  11. Cove MV, Spinola RM, Jackson VL, Saenz J (2014) Camera trapping ocelots: an evaluation of felid attractants. Hystrix 25:1–4Google Scholar
  12. Di Bitetti MS, De Angelo CD, Di Blanco YE, Paviolo A (2010) Niche partitioning and species coexistence in a Neotropical felid assemblage. Acta Oecol 36:403–412Google Scholar
  13. Di Bitetti MS, Paviolo A, De Angelo C (2006) Density, habitat use and activity patterns of ocelots (Leopardus pardalis) in the Atlantic Forest of Misiones, Argentina. J Zool 270:153–163Google Scholar
  14. Dray S, Dufour AB (2007) The ade4 package: implementing the duality diagram for ecologists. J Stat Softw 22:1–20Google Scholar
  15. Efford M (2017) secr: spatially explicit capture-recapture in R. R package version 3.1.3.
  16. Efford MG, Borchers DL, Byrom AE (2009) Density estimation by spatially explicit capture-recapture: likelihood-based methods. In: Modeling demographic processes in marked populations, pp 255–269Google Scholar
  17. Efford MG (2004) Density estimation in live-trapping studies. Oikos 106:598–610Google Scholar
  18. Ferreira JP, Leitão I, Santos-Reis M, Revilla E (2011) Human-related factors regulate the spatial ecology of domestic cats in sensitive areas for conservation (ed Y. Ropert-Coudert). PLoS One 6:e25970PubMedPubMedCentralGoogle Scholar
  19. Fiske I, Chandler R, Miller D et al (2015) Package ‘unmarked’: models for data from unmarked animalsGoogle Scholar
  20. Frigeri E, Cassano CR, Pardini R (2014) Domestic dog invasion in an agroforestry mosaic in Southern Bahia, Brazil. Trop Conserv Sci 7:508–528Google Scholar
  21. Galetti M, Sazima I (2006) Impacto de cães ferais em um fragmento urbano de Floresta Atlântica no sudeste do Brasil. Nat Conserv 4:58–63Google Scholar
  22. Gatti A, Seibert JB, Moreira DO (2018) A predation event by free-ranging dogs on the lowland tapir in the Brazilian Atlantic Forest. Anim Biodivers Conserv 41:311–314Google Scholar
  23. Goulart F, Graipel ME, Tortato M, Ghizoni-Jr I, Oliveira-Santos LG, Cáceres N (2009) Ecology of the ocelot (Leopardus pardalis) in the Atlantic Forest of southern Brazil. Neotrop Biol Conserv 4:137–143Google Scholar
  24. Huete A, Didan K, Miura T, Rodriguez E, Gao X, Ferreira L (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens Environ 83:195–213Google Scholar
  25. Hughes J, Macdonald DW (2013) A review of the interactions between free-roaming domestic dogs and wildlife. Biol Conserv 157:341–351. CrossRefGoogle Scholar
  26. Huguenin J, Ferreira JF, Moreira DO, Gatti A, Mendes SL, Zanin M (2018) An updated species list of medium and large-sized mammals of the Augusto Ruschi Biological Reserve, Atlantic Forest of Brazil, using a novel sampling design. Oecologia Australis 23(1):66–77Google Scholar
  27. Hutchinson GE (1948) Circular causal systems in ecology. Ann N Y Acad Sci 50:221–246PubMedGoogle Scholar
  28. IBAMA (2004) Plano de manejo da Reserva Biológica Augusto Ruschi. Vitória, BrasilGoogle Scholar
  29. IBGE – Instituto Brasileiro de Geografia e Estatística (2011) Censo demográfico 2010: característica da população e dos domicílios. Rio de JaneiroGoogle Scholar
  30. Junaedi DI (2018) Why people may like invasive species: investigating biophilia in botanical gardens adjacent to natural forest ecosystems. J Trop For Sci 30:216–223Google Scholar
  31. Kasper CB, Mazim FD, Soares JBG, de Oliveira TG (2015) Density estimates and conservation of Leopardus pardalis southernmost population of the Atlantic Forest. Iheringia, Série Zool 105:367–371Google Scholar
  32. Kavanau JL (1969) Influences of light on activity of small mammals. Ecology 50:548–557Google Scholar
  33. Krauze-Gryz D, Gryz JB, Goszczyński J, Chylarecki P, ̇Zmihorski M. (2012) The good, the bad, and the ugly: space use and intraguild interactions among three opportunistic predators-cat (Felis catus), dog (Canis lupus familiaris ), and red fox (Vulpes vulpes ) under human pressure. Can J Zool 90:1402–1413Google Scholar
  34. Laake J, Rexstad E (2008) Appendix C. RMark - an alternative approach to building linear models in MARK. In: Cooch E, White G (eds) Program MARK: A Gentle Introduction, 6th edn Google Scholar
  35. Lamigueiro OP (2016) SolaR: radiation and photovoltaic systems version, pp 1–92Google Scholar
  36. Lee A (2010) Circular data. Wiley Interdiscip Rev Comput Stat 2:477–486Google Scholar
  37. Legendre P, Legendre L (1998) Numerical ecology, 2nd edn. Elsevier Science, AmsterdamGoogle Scholar
  38. Lessa I, Corrêa Seabra Guimarães T, de Godoy Bergallo H, Cunha A, M. Vieira E. (2016) Domestic dogs in protected areas: a threat to Brazilian mammals? Nat Conserv 14:46–56Google Scholar
  39. Mack RN, Simberloff D, Lonsdale WM, Evans H, Clout M, Bazzaz FA (2000) Biotic invasions: causes, epidemiology, global consequences, and control. Ecol Appl 10:689–710Google Scholar
  40. MacKenzie DI, Nichols JD, Royle JA, Pollock KH, Bailey LL, Hines JE (2006) Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Elsevier, San DiegoGoogle Scholar
  41. Massara RL, Paschoal AMO, Bailey LL, Doherty PF, Chiarello AG (2016) Ecological interactions between ocelots and sympatric mesocarnivores in protected areas of the Atlantic Forest, southeastern Brazil. J Mammal 97:1634–1644Google Scholar
  42. Meek P, Ballard G, Fleming P, Falzon G (2016) Are we getting the full picture? Animal responses to camera traps and implications for predator studies. Ecol Evol 6:3216–3225PubMedPubMedCentralGoogle Scholar
  43. Navarro CS, Palomares F (2015) Human-related factors regulate the presence of domestic dogs in protected areas. Oryx 49:254–260Google Scholar
  44. Novoa A, Shackleton R, Canavan S, Cybèle C, Davies SJ, Dehnen-Schmutz K, Fried J, Gaertner M, Geerts S, Griffiths CL, Kaplan H, Kumschick S, le Maitre DC, Measey GJ, Nunes AL, Richardson DM, Robinson TB, Touza J, Wilson JRU (2018) A framework for engaging stakeholders on the management of alien species. J Environ Manag 205:286–297. CrossRefGoogle Scholar
  45. Oksanen J, Blanchet FG, Friendly M et al (2017) Vegan: community ecology package. R package version 2.4–5.
  46. Oliveira-Santos LGR, Zucco CA, Agostinelli C (2013) Using conditional circular kernel density functions to test hypotheses on animal circadian activity. Anim Behav 85:269–280Google Scholar
  47. Otis DL, Burnham KP, White GC, Anderson DR (1978) Statistical inference from capture data on closed animal populations. Wildl Monogr 62:1–135Google Scholar
  48. Palomares F, Fernández N, Roques S, Chávez C, Silveira L, Keller C, Adrados B (2016) Fine-scale habitat segregation between two ecologically similar top predators. PLoS One 11:e0155626PubMedPubMedCentralGoogle Scholar
  49. Paschoal AMO, Massara RL, Bailey LL et al (2016) Use of Atlantic Forest protected areas by free-ranging dogs: estimating abundance and persistence of use. Ecosphere 7:1–15Google Scholar
  50. Paschoal AMO, Massara RL, Santos JL, Chiarello AG (2012) Is the domestic dog becoming an abundant species in the Atlantic forest? A study case in southeastern Brazil. Mammalia 76:67–76Google Scholar
  51. Petrov PR, Popova ED, Zlatanova DP (2016) Niche partitioning among the red fox Vulpes vulpes (L.), stone marten Martes foina (Erxleben) and pine marten Martes martes (L.) in two mountains in Bulgaria. Acta Zool Bulg 68:375–390Google Scholar
  52. R Core Team (2016) R: A language and environment for statistical computing. Statistic program.
  53. Ridout MS, Linkie M (2009) Estimating overlap of daily activity patterns from camera trap data. J Agric Biol Environ Stat 14:322–337Google Scholar
  54. Ripple WJ, Abernethy K, Betts MG, Chapron G, Dirzo R, Galetti M, Levi T, Lindsey PA, Macdonald DW, Machovina B, Newsome TM, Peres CA, Wallach AD, Wolf C, Young H (2016) Bushmeat hunting and extinction risk to the world’s mammals. R Soc Open Sci 3:160498PubMedPubMedCentralGoogle Scholar
  55. Rowcliffe JM, Kays R, Kranstauber B, Carbone C, Jansen PA (2014) Quantifying levels of animal activity using camera trap data (ed D. Fisher). Methods Ecol Evol 5:1170–1179Google Scholar
  56. Russart KLG, Nelson RJ (2018) Artificial light at night alters behavior in laboratory and wild animals. J Exp Zool Part A Ecol Integr Physiol:1–8Google Scholar
  57. Rylands AB, Brandon K (2005) Unidades de conservação brasileiras. Megadiversidade 1:27–35Google Scholar
  58. Sakai AK, Allendorf FW, Holt JS, Lodge DM, Molofsky J, With KA, Baughman S, Cabin RJ, Cohen JE, Ellstrand NC, McCauley DE, O'Neil P, Parker IM, Thompson JN, Weller SG (2001) The population biology of invasive species. Annu Rev Ecol Syst 32:305–332Google Scholar
  59. Sepúlveda M, Pelican K, Cross P, Eguren A, Singer R (2015) Fine-scale movements of rural free-ranging dogs in conservation areas in the temperate rainforest of the coastal range of southern Chile. Mamm Biol 80:290–297Google Scholar
  60. Silva-Rodríguez EA, Sieving KE (2012) Domestic dogs shape the landscape-scale distribution of a threatened forest ungulate. Biol Conserv 150:103–110Google Scholar
  61. Slade NA, Swihart RK (1983) Home range indices for the hispid cotton rat (Sigmodon hispidus) in Northeastern Kansas. J Mammal 64:580–590Google Scholar
  62. Slater MR (2001) The role of veterinary epidemiology in the study of free-roaming dogs and cats. Prev Vet Med 48:273–286PubMedGoogle Scholar
  63. SOS Mata Atlantica & INPE (2018) Atlas dos remanescentes florestais da Mata Atlântica período 2016–2017. São PauloGoogle Scholar
  64. Soto C, Palomares F (2015) Coexistence of sympatric carnivores in relatively homogeneous Mediterranean landscapes: functional importance of habitat segregation at the fine-scale level. Oecologia 179:223–235PubMedGoogle Scholar
  65. Sparkes J, McLeod S, Ballard G, Fleming PJS, Körtner G, Brown WY (2016) Rabies disease dynamics in naïve dog populations in Australia. Prev Vet Med 131:127–136PubMedGoogle Scholar
  66. Suzán G, Ceballos G (2005) The role of feral mammals on wildlife infectious disease prevalence in two nature reserves within Mexico City limits. J Zoo Wildl Med 36:479–484PubMedGoogle Scholar
  67. Tattersall I (2006) The concept of cathemerality: history and definition. Folia Primatol 77:7–14PubMedGoogle Scholar
  68. Torres PC, Prado PI (2010) Domestic dogs in a fragmented landscape in the Brazilian Atlantic Forest: abundance, habitat use and caring by owners. Braz J Biol 70:987–994PubMedGoogle Scholar
  69. Tuck SL, Phillips HRP, Hintzen RE, Scharlemann JPW, Purvis A, Hudson LN (2014) MODISTools - downloading and processing MODIS remotely sensed data in R. Ecol Evol 4:4658–4668PubMedPubMedCentralGoogle Scholar
  70. Vanak AT, Gompper ME (2009) Dogs canis familiaris as carnivores: their role and function in intraguild competition. Mammal Rev 39:265–283Google Scholar
  71. Weber MG, Strauss SY (2016) Coexistence in close relatives: beyond competition and reproductive isolation in sister taxa. Annu Rev Ecol Evol Syst 47:359–381Google Scholar
  72. White TCR (2008) The role of food, weather and climate in limiting the abundance of animals. Biol Rev 83:227–248PubMedGoogle Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Biodiversity and Conservation Post-Graduation ProgramFederal University of MaranhãoSão LuísBrazil
  2. 2.Center of Natural and Human Sciences, Biology DepartmentFederal University of Espírito SantoVitóriaBrazil

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