Landscape Ecology

, Volume 26, Issue 10, pp 1447–1461 | Cite as

Modeling invasive species spread in complex landscapes: the case of potato moth in Ecuador

  • Verónica Crespo-Pérez
  • François Rebaudo
  • Jean-François Silvain
  • Olivier Dangles
Research Article


Tropical mountains have a long history of human occupation, and although vulnerable to biological invasions, have received minimal attention in the literature. Understanding invasive pest dynamics in socio-ecological, agricultural landscapes, like the tropical Andes, is a challenging but timely issue for ecologists as it may provide developing countries with new tools to face increasing threats posed by these organisms. In this work, road rehabilitation into a remote valley of the Ecuadorian Andes constituted a natural experiment to study the spatial propagation of an invasive potato tuber moth into a previously non-infested agricultural landscape. We used a cellular automaton to model moth spatio-temporal dynamics. Integrating real-world variables in the model allowed us to examine the relative influence of environmental versus social landscape heterogeneity on moth propagation. We focused on two types of anthropogenic activities: (1) the presence and spatial distribution of traditional crop storage structures that modify local microclimate, and (2) long-distance dispersal (LDD) of moths by human-induced transportation. Data from participatory monitoring of pest invasion into the valley and from a larger-scale field survey on the Ecuadorian Andes allowed us to validate our model against actual presence/absence records. Our simulations revealed that high density and a clumped distribution of storage structures had a positive effect on moth invasion by modifying the temperature of the landscape, and that passive, LDD enhanced moth invasion. Model validation showed that including human influence produced more precise and realistic simulations. We provide a powerful and widely applicable methodological framework that stresses the crucial importance of integrating the social landscape to develop accurate invasion models of pest dynamics in complex, agricultural systems.


Boosted regression tree Cellular automata Crop storage structures Gravity model Invasive species Long-distance dispersal Mountainous landscapes Tecia solanivora Tropical Andes 



This work was part of the research conducted within the project Innovative Approaches for integrated Pest Management in changing Andes (C09-031) funded by the McKnight Foundation. We are grateful to Jérôme Casas and Isabelle Chuine for their helpful comments on previous versions of the manuscript. We also thank Carlos Carpio and Mario Hererra for their technical support during moth monitoring in the field, and Frederick Saltre for insightful discussions regarding models’ validation. We would also like to thank the editor, Kirk Maloney, and two anonymous reviewers whose constructive suggestions greatly improved the quality of our contribution. VCP was financed by grants from the French Embassy in Ecuador and from the Département Soutien et Formation des communautés scientifiques du Sud (DSF) of the IRD.

Supplementary material

10980_2011_9649_MOESM1_ESM.docx (499 kb)
Supplementary material 1 (DOCX 499 kb)


  1. Anderson KL, Deveson TE, Sallam N, Congdon BC (2010) Wind-assisted migration potential of the island sugarcane planthopper Eumetopina flavipes (Hemiptera: Delphacidae): implications for managing incursions across an Australian quarantine frontline. J Appl Ecol 47:1310–1319CrossRefGoogle Scholar
  2. Baddeley A, Turner R (2005) Spatstat: an R package for analyzing spatial point patterns. J Stat Softw 12:1–42Google Scholar
  3. Bonabeau E (2002) Agent-based modeling: methods and techniques for simulating human systems. Proc Natl Acad Sci USA 99:7280–7287PubMedCrossRefGoogle Scholar
  4. Bossenbroek JM, Kraft CE, Nekola JC (2001) Prediction of long-distance dispersal using gravity models: Zebra mussel invasion of inland lakes. Ecol Appl 11:1778–1788CrossRefGoogle Scholar
  5. Briggs CJ, Godfray HCJ (1996) The dynamics of insect-pathogen interactions in seasonal environments. Theor Popul Biol 50:149–177PubMedCrossRefGoogle Scholar
  6. Buchan LAJ, Padilla DK (1999) Estimating the probability of long-distance overland dispersal of invading aquatic species. Ecol Appl 9:254–265CrossRefGoogle Scholar
  7. Buston PM, Elith J (2011) Determinants of reproductive success in dominant pairs of clownfish: a boosted regression tree analysis. J Anim Ecol 80:528–538PubMedCrossRefGoogle Scholar
  8. Cacho OJ, Spring D, Hester S, Mac Nally R (2010) Allocating surveillance effort in the management of invasive species: a spatially-explicit model. Environ Model Softw 25:444–454CrossRefGoogle Scholar
  9. Cadotte M, McMahon S, Fukami T (2006) Conceptual ecology and invasion biology: reciprocal approaches to nature. Springer, DordrechtCrossRefGoogle Scholar
  10. Cameron PJ, Walker GP, Penny GM, Wigley PJ (2002) Movement of potato tuberworm (Lepidoptera: Gelechiidae) within and between crops, and some comparisons with diamondback moth (Lepidoptera: Plutellidae). Environ Entomol 31:65–75CrossRefGoogle Scholar
  11. Cameron PJ, Wigley PJ, Elliott S, Madhusudhan VV, Wallace AR, Anderson JAD, Walker GP (2009) Dispersal of potato tuber moth estimated using field application of Bt for mark-capture techniques. Entomol Exp Appl 132:99–109CrossRefGoogle Scholar
  12. Carrasco LR, Mumford JD, MacLeod A, Harwood T, Grabenweger G, Leach AW, Knight JD, Baker RHA (2010) Unveiling human-assisted dispersal mechanisms in invasive alien insects: integration of spatial stochastic simulation and phenology models. Ecol Model 221:2068–2075CrossRefGoogle Scholar
  13. Dangles O, Carpio C, Barragan AR, Zeddam JL, Silvain JF (2008) Temperature as a key driver of ecological sorting among invasive pest species in the tropical Andes. Ecol Appl 18:1795–1809PubMedCrossRefGoogle Scholar
  14. Dangles O, Mesias V, Crespo-Perez V, Silvain JF (2009) Crop damage increases with pest species diversity: evidence from potato tuber moths in the tropical Andes. J Appl Ecol 46:1115–1121CrossRefGoogle Scholar
  15. Dangles O, Carpio C, Villares M, Yumisaca F, Liger B, Rebaudo F, Silvain JF (2010) Community-based participatory research helps farmers and scientists to manage invasive pests in the Ecuadorian Andes. Ambio 39:325–335PubMedCrossRefGoogle Scholar
  16. Davies KF, Chesson P, Harrison S, Inouye BD, Melbourne BA, Rice KJ (2005) Spatial heterogeneity explains the scale dependence of the native–exotic diversity relationship. Ecology 86:1602–1610CrossRefGoogle Scholar
  17. Diggle PJ (2003) Statistical analysis of spatial point patterns, 2nd edn. Arnold/Hodder Headline Group, LondonGoogle Scholar
  18. Elith J, Leathwick JR, Hastie T (2008) A working guide to boosted regression trees. J Anim Ecol 77:802–813PubMedCrossRefGoogle Scholar
  19. Ellenberg H (1979) Man’s influence on tropical mountain ecosystems in South America—2nd Tansley Lecture. J Ecol 67:401–416CrossRefGoogle Scholar
  20. EPPO (2005) Data sheets on quarantined pests, Tecia solanivora. Bull OEPP/EPPO 35:399–401Google Scholar
  21. Fenemore PG (1988) Host-plant location and selection by adult potato moth, Phthorimaea operculella (Lepidoptera, Gelechiidae)—a review. J Insect Phys 34:175–177CrossRefGoogle Scholar
  22. Fleiss JL (1971) Measuring nominal scale agreement among many raters. Psychol Bull 76:378–382CrossRefGoogle Scholar
  23. Foley DH (1985) Tethered flight of the potato moth, Phthorimaea operculella. Physiol Entomol 10:45–51CrossRefGoogle Scholar
  24. Gilbert M, Gregoire JC, Freise JF, Heitland W (2004) Long-distance dispersal and human population density allow the prediction of invasive patterns in the horse chestnut leafminer Cameraria ohridella. J Anim Ecol 73:459–468CrossRefGoogle Scholar
  25. Goslee SC, Peters DPC, Beck KG (2006) Spatial prediction of invasion success across heterogeneous landscapes using an individual-based model. Biol Invasions 8:193–200CrossRefGoogle Scholar
  26. Hanafi A (1999) Integrated pest management of potato tuber moth in field and storage. Potato Res 42:373–380CrossRefGoogle Scholar
  27. Hanski I, Gaggiotti OE (2004) Ecology, genetics, and evolutions of metapopulations. Elsevier, AmsterdamGoogle Scholar
  28. Hanski I, Alho J, Moilanen A (2000) Estimating the parameters of survival and migration of individuals in metapopulations. Ecology 81:239–251CrossRefGoogle Scholar
  29. Harris CM, Park KJ, Atkinson R, Edwards C, Travis JMJ (2009) Invasive species control: incorporating demographic data and seed dispersal into a management model for Rhododendron ponticum. Ecol Inform 4:226–233CrossRefGoogle Scholar
  30. Hastings A, Cuddington K, Davies KF, Dugaw CJ, Elmendorf S, Freestone A, Harrison S, Holland M, Lambrinos J, Malvadkar U, Melbourne BA, Moore K, Taylor C, Thomson D (2005) The spatial spread of invasions: new developments in theory and evidence. Ecol Lett 8:91–101CrossRefGoogle Scholar
  31. Herben T, Munzbergova Z, Milden M, Ehrlen J, Cousins SAO, Eriksson O (2006) Long-term spatial dynamics of Succisa pratensis in a changing rural landscape: linking dynamical modelling with historical maps. J Ecol 94:131–143CrossRefGoogle Scholar
  32. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978CrossRefGoogle Scholar
  33. Hufkens K, Ceulemans R, Scheunders P (2008) Estimating the ecotone width in patchy ecotones using a sigmoid wave approach. Ecol Inform 3:97–104Google Scholar
  34. Hutchings MJ, John EA, Stewart AJA (eds) (2000) The ecological consequences of environmental heterogeneity. Blackwell, OxfordGoogle Scholar
  35. Jongejans E, Skarpaas O, Shea K (2008) Dispersal, demography and spatial population models for conservation and control management. Perspect Plant Ecol Evol Syst 9:153–170CrossRefGoogle Scholar
  36. Keasar T, Kalish A, Becher O, Steinberg S (2005) Spatial and temporal dynamics of potato tuberworm (Lepidoptera: Gelechiidae) infestation in field-stored potatoes. J Econ Entomol 98:222–228PubMedCrossRefGoogle Scholar
  37. Keller S (2003) Integrated pest management of the potato tuber moth in cropping systems of different agroecological zones. Margraf Publishers, GermanyGoogle Scholar
  38. Körner C (2007) The use of ‘altitude’ in ecological research. Trends Ecol Evol 22:569–574PubMedCrossRefGoogle Scholar
  39. Lewis MA, Pacala S (2000) Modeling and analysis of stochastic invasion processes. J Math Biol 41:387–429PubMedCrossRefGoogle Scholar
  40. Liebhold AM, Tobin PC (2008) Population ecology of insect invasions and their management. Annu Rev Entomol 53:387–408PubMedCrossRefGoogle Scholar
  41. MA (2003) Ecosystems and human well-being: a framework for assessment. Island Press, WashingtonGoogle Scholar
  42. MAE, EcoCiencia (2005) Proyecto Indicadores de Biodiversidad para Uso Nacional y el Programa de Biodiversidad, Páramos y otros Ecosistemas Frágiles. Project Coordinators: Ángel Onofa (MAE) and Malki Sáenz (EcoCiencia): Quito, EcuadorGoogle Scholar
  43. Manel S, Williams HC, Ormerod S (2001) Evaluating presence–absence models in ecology: the need to account for prevalence. J Appl Ecol 38:921–931CrossRefGoogle Scholar
  44. Melbourne BA, Cornell HV, Davies KF, Dugaw CJ, Elmendorf S, Freestone AL, Hall RJ, Harrison S, Hastings A, Holland M, Holyoak M, Lambrinos J, Moore K, Yokomizo H (2007) Invasion in a heterogeneous world: resistance, coexistence or hostile takeover? Ecol Lett 10:77–94PubMedCrossRefGoogle Scholar
  45. Miller TEX (2007) Demographic models reveal the shape of density dependence for a specialist insect herbivore on variable host plants. J Anim Ecol 76:722–729PubMedCrossRefGoogle Scholar
  46. Miller TEX, Tenhumberg B (2010) Contributions of demography and dispersal parameters to the spatial spread of a stage-structured insect invasion. Ecol Appl 20:620–633PubMedCrossRefGoogle Scholar
  47. Moilanen A (1999) Patch occupancy models of metapopulation dynamics: efficient parameter estimation using implicit statistical inference. Ecology 80:1031–1043CrossRefGoogle Scholar
  48. Moilanen A (2004) SPOMSIM: software for stochastic patch occupancy models of metapopulation dynamics. Ecol Model 179:533–550CrossRefGoogle Scholar
  49. Muirhead JR, Leung B, van Overdijk C, Kelly DW, Nandakumar K, Marchant KR, MacIsaac HJ (2006) Modelling local and long-distance dispersal of invasive emerald ash borer Agrilus planipennis (Coleoptera) in North America. Divers Distrib 12:71–79CrossRefGoogle Scholar
  50. Munkemuller T, Travis JMJ, Burton OJ, Schiffers K, Johst K (2011) Density-regulated population dynamics and conditional dispersal alter the fate of mutations occurring at the front of an expanding population. Heredity 106:678–689PubMedCrossRefGoogle Scholar
  51. Nehrbass N, Winkler E (2007) Is the Giant Hogweed still a threat? An individual-based modelling approach for local invasion dynamics of Heracleum mantegazzianum. Ecol Model 201:377–384CrossRefGoogle Scholar
  52. Nehrbass N, Winkler E, Mullerova J, Pergl J, Pysek P, Perglova I (2007) A simulation model of plant invasion: long-distance dispersal determines the pattern of spread. Biol Invasions 9:383–395CrossRefGoogle Scholar
  53. Nyssen J, Poesen J, Deckers J (2009) Land degradation and soil and water conservation in tropical highlands. Soil Tillage Res 103:197–202CrossRefGoogle Scholar
  54. Pauchard A, Kueffer C, Dietz H, Daehler CC, Alexander J, Edwards PJ, Arevalo JR, Cavieres LA, Guisan A, Haider S, Jakobs G, McDougall K, Millar CI, Naylor BJ, Parks CG, Rew LJ, Seipel T (2009) Ain’t no mountain high enough: plant invasions reaching new elevations. Front Ecol Environ 7:479–486CrossRefGoogle Scholar
  55. Perry GLW (2004) SpPack: spatial point pattern analysis in Excel using Visual Basic for Applications (VBA). Environ Model Softw 19:559–569CrossRefGoogle Scholar
  56. Pitt JPW, Worner SP, Suarez AV (2009) Predicting Argentine ant spread over the heterogeneous landscape using a spatially explicit stochastic model. Ecol Appl 19:1176–1186PubMedCrossRefGoogle Scholar
  57. Prasad A, Iverson L, Peters M, Bossenbroek J, Matthews S, Davis Sydnor T, Schwartz M (2010) Modeling the invasive emerald ash borer risk of spread using a spatially explicit cellular model. Landscape Ecol 25:353–369CrossRefGoogle Scholar
  58. Puillandre N, Dupas S, Dangles O, Zeddam JL, Capdevielle-Dulac C, Barbin K, Torres-Leguizamon M, Silvain JF (2008) Genetic bottleneck in invasive species: the potato tuber moth adds to the list. Biol Invasions 10:319–333CrossRefGoogle Scholar
  59. R Development Core Team (2009) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0,
  60. R Development Core Team (2010) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0,
  61. Rebaudo F, Crespo-Pérez V, Dangles O (2010) SimPolilla© A cellular automaton to describe a pest invasion within the northern Andes. CIRAD, http://cormasciradfr/en/applica/SimPolillahtm. Accessed 4 Aug 2010
  62. Rebaudo F, Crespo-Pérez V, Silvain J-F, Dangles O (2011) Agent-based modeling of human-induced spread of invasive species in agricultural landscapes: insights from the potato moth in Ecuador. JASS 14:7Google Scholar
  63. Régnière J, Turgeon JJ (1989) Temperature-dependent development of Zeiraphera canadensis and simulation of its phenology. Entomol Exp Appl 50:185–193CrossRefGoogle Scholar
  64. Régnière J, Nealis V, Porter K (2009) Climate suitability and management of the gypsy moth invasion into Canada. Biol Invasions 11:135–148CrossRefGoogle Scholar
  65. Richardson DM, Pysek P (2006) Plant invasions: merging the concepts of species invasiveness and community invasibility. Prog Phys Geogr 30:409–431CrossRefGoogle Scholar
  66. Ridgeway G (2010) Package ‘gbm’ version 1.6-3.1. http://cranr-projectorg/web/packages/gbm/gbmpdf. Accessed 2 May 2011
  67. Rothschild GHL (ed) (1986) The potato moth—an adaptable pest of short-term cropping systems. Wiley, CanberraGoogle Scholar
  68. Roux O, Baumgartner J (1998) Evaluation of mortality factors and risk analysis for the design of an integrated pest management system. Ecol Model 109:61–75CrossRefGoogle Scholar
  69. Schreiber SJ, Lloyd-Smith JO (2009) Invasion dynamics in spatially heterogeneous environments. Am Nat 174:490–505PubMedCrossRefGoogle Scholar
  70. Sebert-Cuvillier E, Simon-Goyheneche V, Paccaut F, Chabrerie O, Goubet O, Decocq G (2008) Spatial spread of an alien tree species in a heterogeneous forest landscape: a spatially realistic simulation model. Landscape Ecol 23:787–801CrossRefGoogle Scholar
  71. Shea K, Jongejans E, Skarpaas O, Kelly D, Sheppard AW (2010) Optimal management strategies to control local population growth or population spread may not be the same. Ecol Appl 20:1148–1161PubMedCrossRefGoogle Scholar
  72. Soons MB, Messelink JH, Jongejans E, Heil GW (2005) Habitat fragmentation reduces grassland connectivity for both short-distance and long-distance wind-dispersed forbs. J Ecol 93:1214–1225CrossRefGoogle Scholar
  73. Suarez AV, Holway DA, Case TJ (2001) Patterns of spread in biological invasions dominated by long-distance jump dispersal: insights from Argentine ants. Proc Natl Acad Sci USA 98:1095–1100PubMedCrossRefGoogle Scholar
  74. Travis JMJ, Smith HS, Ranwala SMW (2010) Towards a mechanistic understanding of dispersal evolution in plants: conservation implications. Divers Distrib 16:690–702CrossRefGoogle Scholar
  75. Travis JMJ, Harris CM, Park KJ, Bullock JM (2011) Improving prediction and management of range expansions by combining analytical and individual-based modelling approaches. Methods Ecol Evol. doi:10.1111/j.2041-210X.2011.00104.x. Published Online
  76. Wu H, Malafant KWJ, Pendridge LK, Sharpe PJH, Walker J (1987) Simulation of two-dimensional point patterns. Application of a lattice framework approach. Ecol Model 38:299–308CrossRefGoogle Scholar
  77. Yathom S (1968) Phenology of the tuber moth Gnorimoschema operculella Zell. in Israel in spring. Isr J Agric Res 18:89–90Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Verónica Crespo-Pérez
    • 1
    • 2
    • 3
  • François Rebaudo
    • 1
    • 2
  • Jean-François Silvain
    • 1
    • 2
  • Olivier Dangles
    • 1
    • 2
    • 3
  1. 1.IRD, UR 072, Diversity, Ecology and Evolution of Tropical Insects Team, Evolution, Genomes and Speciation LaboratoryUPR 9034, CNRSGif-sur-Yvette CedexFrance
  2. 2.University Paris-Sud 11Orsay CedexFrance
  3. 3.Entomology Laboratory, Natural and Biological Sciences FacultyPontifical Catholic University of EcuadorQuitoEcuador

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