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Biological Invasions

, Volume 19, Issue 1, pp 209–221 | Cite as

Optimizing control programmes by integrating data from fine-scale space use by introduced predators

  • Mariano R. Recio
  • Richard F. Maloney
  • Renaud Mathieu
  • Emilio Virgós
  • Antoni B. Moore
  • Philip J. Seddon
Original Paper

Abstract

The control of introduced mammalian predators (IMP) through trapping campaigns relies on operator experience to deploy traps in sites with an expected high probability of IMP presence, where the maximum number of captures is anticipated. We tested the limitations of available information on fine-scale spatial use by feral cats modelled from remote data collection methods (small-resolution satellite imagery and GPS-telemetry) in an intensive control campaign conducted over 8 years in an ecologically sensitive area of New Zealand. We calculated dichotomous optimal/sub-optimal areas for cats and found that operators placed traps in or close to optimal areas. Over a continuous range of probabilities of cat use, trap sites were not principally placed in hot spots of cat use. Logistic regression revealed that the probability of cat use was significantly associated with the probability of capture. However, regressing catch-effort against the probability of cat use showed no association between sites of high probability of cat use and higher capture rates. The incorporation in the models of bait, trap type, and habitat suitability for rabbits, as variables of operator’s choice showed that rabbit suitability, and the combination of baits/traps were significant. Results suggest that trapping feral cats is a complex process that likely relies on variables of space, time, and individual cognition. However, control programmes could improve trap deployment by identifying sites of high probability of cat use to maximize capture probability, while traps in sub-optimal areas could be removed (cost reduction), reallocated to optimal areas, or used to “fence” core conservation areas.

Keywords

Introduced mammalian predators Fine-scale Space use Control programmes Trapping Feral cats 

Notes

Acknowledgments

The authors acknowledge the Department of Conservation in Twizel for assisting in this research based on their predator control work in the Tasman River Valley and for providing the trapping database. To Simon Stevenson for his invaluable contribution to fieldwork in the Godley Valley. This research was funded by University of Otago PBRF allocations from the School of Surveying and Department of Zoology.

Supplementary material

10530_2016_1274_MOESM1_ESM.pdf (146 kb)
Supplementary material 1 (PDF 145 kb)

References

  1. Baker PJ, Harris S (2006) Does culling reduce fox (Vulpes vulpes) density in commercial forests in Wales? Eur J Wildl Res 52:99–108CrossRefGoogle Scholar
  2. Baldwin RA (2009) Use of maximum entropy modeling in wildlife research. Entropy 11:854–866CrossRefGoogle Scholar
  3. Bateman JA (1979) Trapping: a practical guide. Coch-y-bonddu books, BathGoogle Scholar
  4. Beauvais GP, Buskirk SW (1999) Modifying estimates of sampling effort to account for sprung traps. Wildl Soc B 27:39–43Google Scholar
  5. Bengsen AJ, Butlet JA, Masters P (2012) Applying home range and landscape-use data to design effective feral-cat control programs. Wildl Res 39:258–265CrossRefGoogle Scholar
  6. Birkhofer K, Diehl E, Andersson J, Ekroos J, Früh-Müller A, Machnikowski F, Mader VL, Nilsson L, Sasaki K, Rundlöf M, Wolters V, Smith HG (2015) Ecosystem services—current challenges and opportunities for ecological research. Front Ecol Evol 2:87CrossRefGoogle Scholar
  7. Blackie HM, MacKay JWB, Allen WJ, Smith DHS, Barret B, Whyte BI, Murphy EC, Ross J, Shapiro L, Ogilvie S, Sam S, MacMorran D, Inder S, Eason CT (2014) Innovative developments for long-term mammalian pest control. Pest Manag Sci. doi: 10.1002/ps.3627 PubMedGoogle Scholar
  8. Boitani L, Ciucci P, Mortelliti A (2012) Designing carnivore surveys. In: Boitani L, Powell RA (eds) Carnivore ecology and conservation. Oxford University Press, New York, pp 8–30CrossRefGoogle Scholar
  9. Boyce MS, McDonald LL (1999) Relating populations to habitats using resource selection functions. Trends Ecol Evol 14:268–272CrossRefPubMedGoogle Scholar
  10. Brook BW, Sodhi NS, Bradshaw CJA (2008) Synergies among extinction drivers under global change. Trends Ecol Evol 23:453–460CrossRefPubMedGoogle Scholar
  11. Burnham KP, Overton WS (1978) Estimation of the size of a closed population when capture probabilities vary among animals. Biometrika 65:625–636CrossRefGoogle Scholar
  12. 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 B 365:2157–2162CrossRefGoogle Scholar
  13. Cameron BG, van Heezik Y, Maloney RF, Seddon PJ, Harraway JA (2005) Improving predator capture rates: analysis of river margin trap site data in the Waitaki Basin, New Zealand. NZ J Ecol 29:117–128Google Scholar
  14. Carstensen B, Plummer M, Laara E, Hills M (2016) Epi: a package for statistical analysis in epidemiology. R package version 2.0. http://CRAN.R-project.org/package=Epi
  15. Caut S, Casanovas JG, Virgos E, Lozano J, Whitmer GW, Courchamp F (2007) Rats dying for mice: modelling the competitor release effect. Austral Ecol 32:858–868CrossRefGoogle Scholar
  16. Clapperton BK, Eason CT, Weston RJ, Woolhouse AD, Morgan DR (1994) Development and testing of attractants for feral cats, Felis catus L. Wildl Res 21:389–399CrossRefGoogle Scholar
  17. Clayton R, Cowan P (2010) Management of animal and plant pests in New Zealand—patterns of control and monitoring by regional agencies. Wildl Res 37:360–371CrossRefGoogle Scholar
  18. Courchamp F, Langlais M, Sugihara M (1999) Cats protecting birds: modelling the mesopredator release effect. J Anim Ecol 68:282–292CrossRefGoogle Scholar
  19. Courchamp F, Chapuis JL, Pascal M (2003) Mammal invaders on islands: impact, control and control impact. Biol Rev 78:347–383CrossRefPubMedGoogle Scholar
  20. Cowan PE, Tyndale-Biscoe CH (1997) Australian and New Zealand mammal species considered to be pests or problems. Reprod Fertil Dev 9:27–37CrossRefPubMedGoogle Scholar
  21. Crowl TA, Crist TO, Parmenter RR, Belovsky G, Lugo AE (2008) The spread of invasive species and infectious disease as drivers of ecosystem change. Front Ecol Environ 6:238–246CrossRefGoogle Scholar
  22. Efford MG, Fewster RM (2013) Estimating population size by spatially explicit capture–recapture. Oikos 122:918–928CrossRefGoogle Scholar
  23. Fletcher D, Mackenzie D, Villouta E (2005) Modelling skewed data with many zeros: a simple approach combining ordinary and logistic regression. Environ Ecol Stat 12:45–54CrossRefGoogle Scholar
  24. Howlin S, Erickson W, Nielson R (2004) A validation technique for assessing predictive abilities of resource selection functions. In: Proceedings first international conference resource selection. Ecosystem Technologies Inc, Laramie, Wyoming, pp 40–51Google Scholar
  25. IUCN (2015) Red list of threatened species. www.iucnredlist.org. Accessed 10 Feb 2016
  26. Kays R, Croofot MC, Jetz W, Wikelski M (2015) Terrestrial animal tracking as an eye on life and planet. Science 348:6240. doi: 10.1126/science.aaa2478 CrossRefGoogle Scholar
  27. King CM (2005) Editor’s introduction. In: King CM (ed) The handbook of New Zealand mammals. Oxford University Press, Melbourne, pp 1–25Google Scholar
  28. Liberg O, Sandel M (1988) Spatial organisation and reproductive tactics in the domestic cat and other felids. In: Turner DC, Bateson P (eds) The domestic cat: the biology of its behaviour. Cambridge University Press, Cambridge, pp 83–98Google Scholar
  29. Liu C, White M, Newell G (2013) Selecting thresholds for the prediction of species occurrence with presence-only data. J Biogeogr 40:778–789CrossRefGoogle Scholar
  30. Loss SR, Will T, Marra PP (2012) The impact of free-ranging domestic cats on wildlife in the United States. Nat Commun 4:1396. doi: 10.1038/ncomms2380 CrossRefGoogle Scholar
  31. Lowe S, Browne M, Boudjelas S, De Poorter M (2000) 100 of the World’s worst invasive alien species a selection from the global invasive species database. Published by The Invasive Species Specialist Group (ISSG) a specialist group of the Species Survival Commission (SSC) of the World Conservation Union (IUCN)Google Scholar
  32. Maloney R (1999) Bird populations in nine braided rivers of the Upper Waitaki basin South Island. New Zealand: changes after 30 years. Notornis 46:243–256Google Scholar
  33. Maloney R, Murray D (2002) Kaki (Black stilt) recovery plan 2001–2011. NZ Department of Conservation, WellingtonGoogle Scholar
  34. Maloney R, Rebergen AL, Nilsson RJ, Wells NJ (1997) Bird density and diversity in braided river beds in the Upper Waitaki Basin, South Island, New Zealand. Notornis 44:219–232Google Scholar
  35. Meir E, Andelman S, Possingham HP (2004) Does conservation planning matter in a dynamic and uncertain world? Ecol Lett 7:615–622CrossRefGoogle Scholar
  36. Millenium Ecosystem Assessment (2005) Ecosystem and human well-being: synthesis. Island Press, WashingtonGoogle Scholar
  37. Murdock W, Polasky S, Wilson KA, Possingham HP, Kareiva P, Shaw R (2007) Maximizing return on investment in conservation. Biol Conserv 139:375–388CrossRefGoogle Scholar
  38. Nelson L Jr, Francis WC (1973) Calculations of trapping results. J Mammal 54:295–298CrossRefGoogle Scholar
  39. Norbury G, Mcglinchy A (1996) The impact of rabbit control on predator sightings in the semi-arid high country of the South Island, New Zealand. Wildl Res 23:93–97CrossRefGoogle Scholar
  40. Norbury GL, Norbury DC, Heyward RP (1998) Behavioral responses of two predator species to sudden declines in primary prey. J Wildl Manag 62:45–58CrossRefGoogle Scholar
  41. Pejchar L, Mooney HA (2009) Invasive species, ecosystem services and human well-being. Trends Ecol Evol 24:497–504CrossRefPubMedGoogle Scholar
  42. Poutu N, Warburton B (2005) Effectiviness of the DOC150, 200 and 250 traps for killing stoats, ferrets, Norway rats, ship rats, and hedgehogs. New Zealand Department of Conservation, WellingtonGoogle Scholar
  43. R Core Team (2016) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
  44. Recio M, Seddon P (2013) Understanding determinants of home range behaviour of feral cats as introduced apex predators in insular ecosystems: a spatial approach. Behav Ecol Sociobiol 67:1971–1981CrossRefGoogle Scholar
  45. Recio MR, Mathieu R, Maloney R, Seddon PJ (2010) First results of feral cats (Felis catus) monitored with GPS collars in New Zealand. NZ J Ecol 34:288–296Google Scholar
  46. Recio MR, Mathieu R, Denys P, Sirguey P, Seddon PJ (2011) Lightweight GPS-Tags, one giant leap for wildlife tracking? an assessment approach. PLoS ONE 6:e28225. doi: 10.1371/journal.pone.0028225 CrossRefPubMedPubMedCentralGoogle Scholar
  47. Recio MR, Mathieu R, Hall B, Moore AB, Seddon PJ (2013a) Landscape resource mapping for wildlife research using very high resolution satellite imagery. Methods Ecol Evol 4:982–992Google Scholar
  48. Recio MR, Mathieu R, Latham MC, Latham ADM, Seddon P (2013b) Quantifying fine-scale resource selection by introduced European hedgehogs Erinaceus europaeus in ecologically sensitive areas. Biol Invasions 15:1807–1818CrossRefGoogle Scholar
  49. Recio MR, Mathieu R, Virgós E, Seddon PJ (2014) Quantifying fine-scale resource selection by introduced feral cats to complement management decision-making in ecologically sensitive areas. Biol Invasions 16:1915–1927CrossRefGoogle Scholar
  50. Recio MR, Seddon PJ, Moore AB (2015) Niche and movement models identify corridors of introduced feral cats infringing ecologically sensitive areas in New Zealand. Biol Conserv 192:48–56CrossRefGoogle Scholar
  51. Reed CEM, Murray DP, Butler DJ (1993) Black stilt (Hymantopus novaezealandiae). Threatened species recovery plan 4. New Zealand Department of Conservation, WellingtonGoogle Scholar
  52. Rout TM, Moore JL, Possingham HP, McCarthy MA (2011) Allocating biosecurity resources between preventing, detecting, and eradicating island invasions. Ecol Econ 71:54–62CrossRefGoogle Scholar
  53. Rushton SP, Shirley MDF, Macdonald DW, Reynolds JC (2006) Effects of culling fox populations at the landscape scale: a spatially explicit population modeling approach. J Wildl Manag 70:1102–1110CrossRefGoogle Scholar
  54. Russell JC, Jones HP, Armstrong DP, Courchamp F, Kappes PJ, Seddon PJ, Oppel S, Rauzon MJ, Cowan PE, Rocamora G, Genovesi P, Bonnaud E, Keitt BS, Holmes ND, Bernie RT (2015) Importance of lethal control of invasive predators for island conservation. Conserv Biol. doi: 10.1111/cobi.12666 Google Scholar
  55. Spencer J (2007) Guide to trapping. Stackpole Books, MechanichsburnGoogle Scholar
  56. Thompson W (2013) Sampling rare or elusive species: concepts, designs, and techniques for estimating population parameters. Island Press, WashingtonGoogle Scholar
  57. Wallach AD, Johnson CN, Ritchie EG, O’Neill AJ (2010) Predator control promotes invasive dominated ecological states. Ecol Lett 13:1008–1018PubMedGoogle Scholar
  58. Wieber PA, Fryxell JM, Thompson ID, Börger L, Barker JA (2012) Do trappers understand marten habitat? J Wildl Manag 77:379–391CrossRefGoogle Scholar
  59. Wiens TS, Dale BC, Boyce MS, Kershaw GP (2008) Three way k-fold cross-validation of resource selection functions. Ecol Model 212:244–255CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.School of SurveyingUniversity of OtagoDunedinNew Zealand
  2. 2.Department of ConservationChristchurchNew Zealand
  3. 3.Earth Observation Research GroupCSIR-Natural Resource EnvironmentPretoriaSouth Africa
  4. 4.Department of Biology and Geology, College of Experimental Science and TechnologyUniversidad Rey Juan CarlosMóstolesSpain
  5. 5.Department of ZoologyUniversity of OtagoDunedinNew Zealand
  6. 6.Department of Geography, Geoinformatics and MeteorologyUniversity of PretoriaPretoriaSouth Africa

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