Advertisement

Evaluating the effects of landscape structure on the recovery of an invasive vertebrate after population control

  • Pablo García-DíazEmail author
  • Dean P. Anderson
  • Miguel Lurgi
Research Article

Abstract

Context

Effective landscape control of invasive species is context-dependent due to the interplay between the landscape structure, local population dynamics, and metapopulation processes. We use a modelling approach incorporating these three elements to explore the drivers of recovery of populations of invasive species after control.

Objectives

We aim to improve our understanding of the factors influencing the landscape-level control of invasive species.

Methods

We focus on the case study of invasive brushtail possum (Trichosurus vulpecula) control in New Zealand. We assess how 13 covariates describing the landscape, patch, and population features influence the time of population recovery to a management density threshold of two possums/ha. We demonstrate the effects of those covariates on population recovery under three scenarios of population growth: logistic growth, strong Allee effects, and weak Allee effects.

Results

Recovery times were rapid regardless of the simulated population dynamics (average recovery time < 2 years), although populations experiencing Allee effects took longer to recover than those growing logistically. Our results indicate that habitat availability and patch area play a key role in reducing times to recovery after control, and this relationship is consistent across the three simulated scenarios.

Conclusions

The control of invasive possum populations in patchy landscapes would benefit from a patch-level management approach (considering each patch as an independent management unit), whereas simple landscapes would be better controlled by taking a landscape-level view (the landscape as the management unit). Future research should test the predictions of our models with empirical data to refine control operations.

Keywords

Allee effects Brushtail possum Habitat availability Landscape and patch metrics New Zealand 

Notes

Acknowledgements

We thank G. Nugent and R. Pech (Manaaki Whenua—Landcare Research) for their insightful comments on possum biology and the management of invasive species. M. Barron (Manaaki Whenua—Landcare Research) read a previous version of this manuscript and provided important feedback that helped improve the manuscript. Three reviewers provided constructive comments that helped improve previous versions of this manuscript. ML is supported by the French ANR through LabEx TULIP (ANR-10-LABX-41; ANR-11-IDEX-002-02) by a Region Midi-Pyrénées Project (CNRS 121090), and by the FRAGCLIM Consolidator Grant, funded by the European Research Council under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement Number 726176).

Supplementary material

10980_2019_796_MOESM1_ESM.docx (31 kb)
Supplementary material 1 (DOCX 30 kb)
10980_2019_796_MOESM2_ESM.docx (19 kb)
Supplementary material 2 (DOCX 18 kb)
10980_2019_796_MOESM3_ESM.r (3 kb)
Supplementary material 3 (R 3 kb)
10980_2019_796_MOESM4_ESM.r (9 kb)
Supplementary material 4 (R 9 kb)

References

  1. Anderson DP, Ramsey DSL, de Lisle GW, Bosson M, Cross ML, Nugent G (2015) Development of integrated surveillance systems for the management of tuberculosis in New Zealand wildlife. N Z Vet J 63:89–97CrossRefPubMedPubMedCentralGoogle Scholar
  2. Anderson DP, Gormley AM, Ramsey DSL, Nugent G, Martin PAJ, Bosson M, Livingstone P, Byrom AE (2017) Bio-economic optimisation of surveillance to confirm broadscale eradications of invasive pests and diseases. Biol Invasions 19:2869–2884CrossRefGoogle Scholar
  3. Baker CM (2017) Target the source: optimal spatiotemporal resource allocation for invasive species control. Conserv Lett 10:41–48CrossRefGoogle Scholar
  4. Bellard C, Cassey P, Blackburn TM (2016) Alien species as a driver of recent extinctions. Biol Let 12:20150623CrossRefGoogle Scholar
  5. Berec L, Angulo E, Courchamp F (2007) Multiple Allee effects and population management. Trends Ecol Evol 22:185–191CrossRefPubMedGoogle Scholar
  6. Bomford M, O’Brien P (1995) Eradication or control for vertebrate pests? Wildl Soc Bull 23:249–255Google Scholar
  7. Boukal DS, Berec L (2002) Single-species models of the Allee effect: extinction boundaries, sex ratios and mate encounters. J Theor Biol 218:375–394CrossRefPubMedGoogle Scholar
  8. Braysher M (2017) Managing Australia’s pest animals. CSIRO, CanberraGoogle Scholar
  9. Byrom AE, Innes J, Binny RN (2016) A review of biodiversity outcomes from possum-focused pest control in New Zealand. Wildl Res 43:228–253CrossRefGoogle Scholar
  10. Chadès I, Martin TG, Nicol S, Burgman MA, Possingham HP, Buckley YM (2011) General rules for managing and surveying networks of pests, diseases, and endangered species. Proc Natl Acad Sci 108:8323–8328CrossRefPubMedGoogle Scholar
  11. Clout MN, Efford MG (1984) Sex differences in the dispersal and settlement of brushtail possums (Trichosurus vulpecula). J Anim Ecol 53:737–749CrossRefGoogle Scholar
  12. Conroy MJ, Peterson JT (2013) Decision making in natural resource management: a structured, adaptive approach. Wiley, West SussexCrossRefGoogle Scholar
  13. Courchamp F, Berec L, Gascoigne J (2008) Allee effects in ecology and conservation. Oxford University Press, OxfordCrossRefGoogle Scholar
  14. Cowan PE (2001) Advances in New Zealand mammalogy 1990–2000: brushtail possum. J R Soc N Z 31:15–29CrossRefGoogle Scholar
  15. Cowan PE, Brockie RE, Smith RN, Hearfield ME (1997) Dispersal of juvenile brushtail possums, Trichosurus vulpecula, after a control operation. Wildl Res 24:279–288CrossRefGoogle Scholar
  16. de Valpine P, Turek D, Paciorek CJ, Anderson-Bergman C, Lang DT, Bodik R (2017) Programming with models: writing statistical algorithms for general model structures with NIMBLE. J Comput Graph Stat 26:403–413CrossRefGoogle Scholar
  17. Dietze MC (2017) Ecological forecasting. Princeton University Press, PrincetonCrossRefGoogle Scholar
  18. Dietze MC, Fox A, Beck-Johnson LM, Betancourt JL, Hooten MB, Jarnevich CS, Keitt TH, Kenney MA, Laney CM, Larsen LG, Loescher HW (2018) Iterative near-term ecological forecasting: Needs, opportunities, and challenges. Proc Natl Acad Sci 115(7):1424–1432CrossRefPubMedGoogle Scholar
  19. Driscoll DA, Lindenmayer DB (2012) Framework to improve the application of theory in ecology and conservation. Ecol Monogr 82:129–147.CrossRefGoogle Scholar
  20. Etherington TR, Perry GLW, Cowan PE, Clout MN (2014) Quantifying the direct transfer costs of common brushtail possum dispersal using least-cost modelling: a combined cost-surface and accumulated-cost dispersal kernel approach. PLoS ONE 9:e88293CrossRefPubMedPubMedCentralGoogle Scholar
  21. Fahrig L (2017) Ecological responses to habitat fragmentation per se. Annu Rev Ecol Evol Syst 48:1–23CrossRefGoogle Scholar
  22. Forsyth DM, Ramsey DS, Perry M, McKay M, Wright EF (2018) Control history, longitude and multiple abiotic and biotic variables predict the abundances of invasive brushtail possums in New Zealand forests. Biol Invasions 20(8):2209–2225CrossRefGoogle Scholar
  23. Gelman A, Carlin JB, Stern HS, Rubin DB (2013) Bayesian data analysis, 3rd edn. CRC Press, Boca RatonGoogle Scholar
  24. Glen AS, Pech RP, Byrom AE (2013) Connectivity and invasive species management: towards an integrated landscape approach. Biol Invasions 15:2127–2138CrossRefGoogle Scholar
  25. Glen AS, Latham MC, Anderson D, Leckie C, Niemiec R, Pech RP, Byrom AE (2017) Landholder participation in regional-scale control of invasive predators: an adaptable landscape model. Biol invasions 19(1):329–338CrossRefGoogle Scholar
  26. Gormley AM, Holland EP, Barron MC, Anderson DP, Nugent G (2016) A modelling framework for predicting the optimal balance between control and surveillance effort in the local eradication of tuberculosis in New Zealand wildlife. Prev Vet Med 125:10–18CrossRefPubMedGoogle Scholar
  27. Gormley AM, Anderson DP, Nugent G (2017) Cost-based optimization of the stopping threshold for local disease surveillance during progressive eradication of tuberculosis from New Zealand wildlife. Transbound Emerg Dis 65:186–196CrossRefPubMedGoogle Scholar
  28. Hanski I (1998) Metapopulation dynamics. Nature 396:41–49CrossRefGoogle Scholar
  29. Hanski I, Gaggiotti OE (2004) Ecology, genetics, and evolution of metapopulations. Academic Press, BurlingtonGoogle Scholar
  30. Hanski I, Ovaskainen O (2003) Metapopulation theory for fragmented landscapes. Theor Pop Ecol 64:119–127CrossRefGoogle Scholar
  31. Hickling GJ, Pekelharing CJ (1989) Intrinsic rate of increase for a brushtail possum population in rata/kamahi forest, Westland. N Z J Ecol 12:117–120Google Scholar
  32. Holden MH, Ellner SP (2016) Human judgment vs. quantitative models for the management of ecological resources. Ecol Appl 26:1553–1565.CrossRefPubMedGoogle Scholar
  33. Hone J, Duncan RP, Forsyth DM (2010) Estimates of maximum annual population growth rates (rm) of mammals and their application in wildlife management. J Appl Ecol 47:507–514.CrossRefGoogle Scholar
  34. Hooten MB, Hobbs NT (2015) A guide to Bayesian model selection for ecologists. Ecol Monogr 85:3–28.CrossRefGoogle Scholar
  35. Hui C, Richardson DM (2017) Invasion dynamics. Oxford University Press, OxfordCrossRefGoogle Scholar
  36. Kéry M, Royle AJ (2016) Applied hierarchical modeling in ecology. Analysis of distribution, abundance and species richness in R and BUGS. Academic Press, LondonGoogle Scholar
  37. Kopf RK, Nimmo DG, Humphries P, Baumgartner LJ, Bod M, Bond NR, Byrom AE, Cucherousset J, Keller RP, King AJ, McGinness HM (2017) Confronting the risks of large-scale invasive species control. Nat Ecol Evol 1:0172CrossRefGoogle Scholar
  38. Livingstone PG, Hancox N, Nugent G, de Lisle GW (2015) Toward eradication: the effect of Mycobacterium bovis infection in wildlife on the evolution and future direction of bovine tuberculosis management in New Zealand. N Z Vet J 63:4–18.CrossRefPubMedPubMedCentralGoogle Scholar
  39. Long J (2003) Introduced mammals of the world: their history, distribution and influence. CSIRO Publishing, MelbourneCrossRefGoogle Scholar
  40. Lurgi M, Wells K, Kennedy M, Campbell S, Fordham DA (2016) A landscape approach to invasive species management. PLoS ONE 11(7):e0160417CrossRefPubMedPubMedCentralGoogle Scholar
  41. Montague TL (2000) The brushtail possum: biology, impact and management of an introduced marsupial. Manaaki Whenua Press, LincolnGoogle Scholar
  42. Nathan R, Klein E, Robledo-Arnuncio JJ, Revilla E (2012) Dispersal kernels: review. In: Clobert J, Baguette M, Benton TG, Bullock JM (eds) Dispersal ecology and evolution. Oxford University Press, Oxford, pp 187–210Google Scholar
  43. Norbury GL, Pech RP, Byrom AE, Innes J (2015) Density-impact functions for terrestrial vertebrate pests and indigenous biota: guidelines for conservation managers. Biol Conserv 191:409–420CrossRefGoogle Scholar
  44. Nugent G, Fraser W, Sweetapple P (2001) Top down or bottom up? Comparing the impacts of introduced arboreal possums and ‘terrestrial’ ruminants on native forests in New Zealand. Biol Conserv 99:65–79CrossRefGoogle Scholar
  45. Nugent G, Buddle BM, Knowles G (2015) Epidemiology and control of Mycobacterium bovis infection in brushtail possums (Trichosurus vulpecula), the primary wildlife host of bovine tuberculosis in New Zealand. N Z Vet J 63:28–41CrossRefPubMedPubMedCentralGoogle Scholar
  46. O’Hara RB, Sillanpää MJ (2009) A review of Bayesian variable selection methods: what, how and which. Bayesian Anal 4:85–117CrossRefGoogle Scholar
  47. Office of the Parliamentary Commissioner for the Environment (1994) Possum management in New Zealand. Office of the Parliamentary Commissioner for the Environment, New Zealand Government, WellingtonGoogle Scholar
  48. Piaggio AJ, Segelbacher G, Seddon PJ, Alphey L, Bennett EL, Carlson RH, Friedman RM, Kanavy D, Phelan R, Redford KH, Rosales M (2017) Is it time for synthetic biodiversity conservation? Trends Ecol Evol 32(2):97–107CrossRefPubMedGoogle Scholar
  49. R Development Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  50. Ramsey DSL, Efford MG (2010) Management of bovine tuberculosis in brushtail possums in New Zealand: predictions from a spatially explicit, individual-based model. J Appl Ecol 47:911–919.CrossRefGoogle Scholar
  51. Ricciardi A, Hoopes MF, Marchetti MP, Lockwood JL (2013) Progress toward understanding the ecological impacts of nonnative species. Ecol Monogr 83:263–282.CrossRefGoogle Scholar
  52. Rouco C, Norbury GL, Smith J, Byrom AE, Pech RP (2013) Population density estimates of brushtail possums (Trichosurus vulpecula) in dry grassland in New Zealand. N Z J Ecol 37(1):12–17Google Scholar
  53. Rozenfeld AF, Arnaud-Haond S, Hernández-García E, Eguíluz VM, Serrão EA, Duarte CM (2008) Network analysis identifies weak and strong links in a metapopulation system. Proc Natl Acad Sci 105(48):18824–18829CrossRefPubMedGoogle Scholar
  54. Ruscoe WA, Ramsey DS, Pech RP, Sweetapple PJ, Yockney I, Barron MC, Perry M, Nugent G, Carran R, Warne R, Brausch C (2011) Unexpected consequences of control: competitive vs. predator release in a four-species assemblage of invasive mammals. Ecol Lett 14(10):1035–1042CrossRefPubMedGoogle Scholar
  55. Russell JC, Innes JG, Brown PH, Byrom AE (2015) Predator-free New Zealand: conservation country. Bioscience 65:520–525CrossRefPubMedPubMedCentralGoogle Scholar
  56. Salafsky N, Margoluis R, Redford KH (2016) Adaptive management: a tool for conservation practitioners. Biodiversity Support Program, Foundations of Success, Washington, DCGoogle Scholar
  57. Taylor CM, Hastings A (2005) Allee effects in biological invasions. Ecol Lett 8:895–908CrossRefGoogle Scholar
  58. Taylor PD, Fahrig L, With KA (2006) Landscape connectivity: a return to the basics. Connectivity Conservation. Conservation Series. Cambridge University Press, Cambridge, pp 29–43CrossRefGoogle Scholar
  59. Vaz AS, Kueffer C, Kull CA, Richardson DM, Schindler S, Muñoz-Pajares AJ, Vicente JR, Martins J, Hui C, Kühn I, Honrado JP (2017) The progress of interdisciplinarity in invasion science. Ambio 46(4):428–442CrossRefPubMedPubMedCentralGoogle Scholar
  60. Wilkins KE, Prowse TA, Cassey P, Thomas PQ, Ross JV (2018) Pest demography critically determines the viability of synthetic gene drives for population control. Math Biosci 305:160–169CrossRefPubMedGoogle Scholar
  61. With KA (2002) The landscape ecology of invasive spread. Conserv Biol 16:1192–1203CrossRefGoogle Scholar
  62. Yokomizo H, Possingham HP, Thomas MB, Buckley YM (2009) Managing the impact of invasive species: the value of knowing the density–impact curve. Ecol Appl 19:376–386CrossRefPubMedGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Manaaki Whenua - Landcare ResearchLincolnNew Zealand
  2. 2.Centre for Biodiversity Theory and Modelling, Theoretical and Experimental Ecology StationCNRS-Paul Sabatier UniversityMoulisFrance

Personalised recommendations