Landscape Ecology

, 26:1097 | Cite as

Incoming! Association of landscape features with dispersing mountain pine beetle populations during a range expansion event in western Canada

  • Honey-Marie C. de la GirodayEmail author
  • Allan L. Carroll
  • B. Staffan Lindgren
  • Brian H. Aukema
Research Article


Mountain pine beetle, Dendroctonus ponderosae Hopkins (Coleoptera: Curculionidae, Scolytinae), is a forest insect that undergoes intermittent population eruptions, causing landscape-level mortality to mature pines. Currently, an outbreak covers over 16.3 million ha of British Columbia and Alberta in western Canada. Recent incursion into the jack pine (Pinus banksiana Lamb.) of northwestern Alberta threatens further range expansion through the boreal forest to central and eastern Canada. The spread from British Columbia into northwestern Alberta has been facilitated by above-canopy dispersal of the insect by meso-scale atmospheric currents. At these scales, dispersing D. ponderosae may behave like inert particles, causing terrain-induced tropospheric convective and advective currents to influence population dispersal and establishment. We use spatial point process regression models to examine the association of meso-scale variables, including landscape features and their orientations, habitat suitability, elevation and treatment efforts, with occurrence of D. ponderosae infestations in 2004, 2005, and 2006. Infestations of D. ponderosae primarily established in canyons and valleys, before moving into more open-sloped areas. Southwestern slopes of midslope ridges and small hills, southwest facing open slopes, and valleys that run in a northeast–southwest cardinal direction were positively associated with higher intensities of infestation. This study provides insight into the influences of complex terrain on landscape disturbance by a forest insect, and can be used to prioritize areas for potential management.


Dendroctonus ponderosae Dispersal Jack pine Landscape features Lodgepole pine Mountain pine beetle Mountains Boreal forest Valleys 



Funding for this study was provided by the TRIA project of Genome British Columbia, Genome Alberta, and Genome Canada. MPB Initiative—Natural Resources Canada and NSERC Discovery grants to BHA and Pacific Forestry Centre Graduate Student and Association of Professional Biologists awards to HMdlG. We thank B. Pate (West Fraser Timber Ltd.), C. Johnson (Canadian Forest Products Ltd.), G. Thandi (Canadian Forest Service), A. McGill (Alberta Sustainable Resource Development), and P. Bai (UNBC) for logistical and technical support. T. Shore and B. Riel (Canadian Forest Service), provided stand susceptibility index data. A. Baddeley (University of Western Australia) and J. Zhu (Department of Statistics, UW-Madison), provided statistical advice on model implementation. J. Jenness (Jenness Enterprises Ltd.) provided the Topographic Position Index tool v. 1.3a for Arcview 3.2. The authors also thank the assistance and support of M. Duthie-Holt, M. Klingenberg, F. McKee, S. Allen, S. Wesche, and D. Linton. Thesis external examiner T. Nelson (U Victoria), associate editor T. Wiegand (Helmholtz Centre for Environmental Research, Germany), and two anonymous reviewers provided valuable comments on an earlier draft.

Supplementary material

10980_2011_9628_MOESM1_ESM.doc (48 kb)
Supplementary material 1 (DOC 48 kb)
10980_2011_9628_MOESM2_ESM.doc (48 kb)
Supplementary material 2 (DOC 47 kb)
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Supplementary material 3 (DOC 91 kb)


  1. Ainslie B, Jackson PL (2011) Investigation into mountain pine beetle above-canopy dispersion using weather radar and an atmospheric dispersion model. Aerobiologia 27:51–65CrossRefGoogle Scholar
  2. Akaike H (1973) Information theory and an extension of the maximum likelihood principle. In: Petrov BN, Csaki F (eds) The second international symposium on information theory, Tsahkadsor, Armenia, USSR, 2–8 September 1971Google Scholar
  3. Amman GD (1973) Population changes of the mountain pine beetle in relation to elevation. Environ Entomol 2:541–547Google Scholar
  4. Antor RJ (1994) Arthropod fallout on high alpine snow patches of the central Pyrenees, northeastern Spain. Arctic Alpine Res 26:72–76CrossRefGoogle Scholar
  5. Arnold TW (2010) Uninformative parameters and model selection using Akaike’s Information Criterion. J Wildl Manag 74:1175–1178CrossRefGoogle Scholar
  6. Ashmole NP, Nelson JM, Shaw MR, Garside A (1983) Insects and spiders on snowfields in the Cairngorms, Scotland. J Nat Hist 17:599–613CrossRefGoogle Scholar
  7. Aukema BH, Carroll AL, Zhu J, Raffa KF, Sickley TA, Taylor SW (2006) Landscape level analysis of mountain pine beetle in British Columbia, Canada: spatiotemporal development and spatial synchrony within the present outbreak. Ecography 29:427–441Google Scholar
  8. Baddeley A, Turner R (2000) Practical maximum pseudolikelihood for spatial point patterns. Aust N Z J Stat 42:283–322CrossRefGoogle Scholar
  9. Baddeley A, Turner R (2005) Spatstat: an R package for analyzing spatial point patterns. J Stat Softw 12:1–42Google Scholar
  10. Bentz BJ, Mullins DE (1999) Ecology of mountain pine beetle (Coleoptera: Scolytidae) cold hardening in the intermountain west. Environ Entomol 28:577–587Google Scholar
  11. Bentz BJ, Munson AS (2000) Spruce beetle population suppression in northern Utah. West J Appl For 15:122–128Google Scholar
  12. Bentz BJ, Logan JA, Amman GD (1991) Temperature-dependent development of the mountain pine beetle (Coleoptera: Scolytidae) and simulation of its phenology. Can Entomol 123:1083–1094CrossRefGoogle Scholar
  13. Bjørnstad ON, Peltonen M, Liebhold AM, Baltensweiler W (2002) Waves of larch budmoth outbreaks in the European Alps. Science 298:1020–1023PubMedCrossRefGoogle Scholar
  14. Bullard JE, Wiggs GFS, Nash DJ (2000) Experimental study of wind directional variability in the vicinity of a model valley. Geomorphology 35:127–143CrossRefGoogle Scholar
  15. Carroll AL, Taylor SW, Régniere J, Safranyik L (2004) Effects of climate change on range expansion by the mountain pine beetle in British Columbia. In: Shore TL, Brooks JE, Stone JE (eds) Challenges and solutions: proceedings of the mountain pine beetle symposium, Kelowna, British Columbia, Canada, 30–31 October 2003Google Scholar
  16. Cerezke HF (1995) Egg gallery, brood production, and adult characteristics of mountain pine beetle, Dendroctonus ponderosae Hopkins (Coleoptera: Scolytidae), in three pine hosts. Can Entomol 127:955–965CrossRefGoogle Scholar
  17. Chapman JA (1962) Field studies on attack flight and log selection by ambrosia beetle Trypodendron lineatum (oliv.) (Coleoptera: Scolytidae). Can Entomol 94:74–92CrossRefGoogle Scholar
  18. de la Giroday H-MC (2009) Spatial associations between infestations of mountain pine beetle and landscape features in the Peace River region of British Columbia. M.Sc. thesis, University of Northern British ColumbiaGoogle Scholar
  19. Defant F (1951) Local winds. In: Malone TF (ed) Compendium of meteorology. American Meteorological Society, Boston, pp 655–672Google Scholar
  20. Elith J, Leathwick JR (2009) Species distribution models: ecological explanation and prediction across space and time. Annu Rev Ecol Evol Syst 40:677–697CrossRefGoogle Scholar
  21. Environment Canada (2002) Canadian daily climatic data 2000. Environment Canada Meteorological Services, DownsviewGoogle Scholar
  22. Fettig CJ, McMillin JD, Anhold JA, Hamud SM, Borys RR, Dabney CP, Seybold SJ (2006) The effects of mechanical fuel reduction treatments on the activity of bark beetles (Coleoptera: Scolytidae) infesting ponderosa pine. For Ecol Manag 230:55–68Google Scholar
  23. Fettig CJ, Klepzig KD, Billings RF, Munson AS, Nebeker TE, Negron JF, Nowak JT (2007) The effectiveness of vegetation management practices for prevention and control of bark beetle infestations in coniferous forests of the western and southern United States. For Ecol Manag 238:24–53Google Scholar
  24. Gamarra JGP, He F (2008) Spatial scaling of mountain pine beetle infestations. J Anim Ecol 77:796–801PubMedCrossRefGoogle Scholar
  25. GeoBase (2007) Digital elevation data. Canadian Council on Geomatics. Accessed July 2007
  26. Goossens D (1996) Wind tunnel experiments of aeolian dust deposition along ranges of hills. Earth Surf Proc Land 21:205–216CrossRefGoogle Scholar
  27. Graham MH (2003) Confronting multicollinearity in ecological multiple regression. Ecology 84:2809–2815CrossRefGoogle Scholar
  28. Guisan A, Zimmerman NE (2000) Predictive habitat distribution models in ecology. Ecol Model 135:147–186CrossRefGoogle Scholar
  29. Holt J, Eaton D (2008) Assessment of the energy potential and estimated costs of wind energy of British Columbia. British Columbia Hydro and Power Authority, VictoriaGoogle Scholar
  30. Ihaka R, Gentleman R (1996) R: a language for data analysis and graphics. J Comput Graph Stat 5:299–314CrossRefGoogle Scholar
  31. Ims RAL, Hans P, Coulson S (2004) Spatial and temporal variation in patch occupancy and population density in a model system of an arctic Collembola species assemblage. Oikos 105:89–100CrossRefGoogle Scholar
  32. Jackson PL, Straussfogel D, Lindgren BS, Mitchell S, Murphy B (2008) Radar observation and aerial capture of mountain pine beetle, Dendroctonus ponderosae Hopk. (Coleoptera: Scolytidae) in flight above the forest canopy. Can J For Res 38:2313–2327CrossRefGoogle Scholar
  33. Jenness J (2006) Topographic position index (tpi_jen.Avx) extension for arcview 3.X, v. 1.3a. Jenness EnterprisesGoogle Scholar
  34. Lewis T, Dibley G (1970) Air movement near windbreaks and a hypothesis on the mechanism of the accumulation of airborne insects. Ann Appl Biol 66:477–484CrossRefGoogle Scholar
  35. Mason CJ, McManus ML (1981) Larval dispersal of the gypsy moth. In: Doane CC, McManus ML (eds) The gypsy moth: research toward integrated pest management U.S. Department of Agriculture, Washington, pp 161–202Google Scholar
  36. Mattson WJ, Haack RA (1987) The role of drought in outbreaks of plant-eating insects. Bioscience 37:110–119CrossRefGoogle Scholar
  37. Nelson T, Boots B, White K, Smith A (2006) The impact of treatment on mountain pine beetle infestation rates. B C J Ecosyst Manag 7:20–36Google Scholar
  38. Powell J, Bentz B (2009) Connecting phenological predictions with population growth rates for mountain pine beetle, an outbreak insect. Landscape Ecol 24:657–672CrossRefGoogle Scholar
  39. Powers JS, Sollins P, Harmon ME, Jone JA (1999) Plant–pest interactions in time and space: a Douglas-fir bark beetle outbreak as a case study. Landscape Ecol 14:105–120CrossRefGoogle Scholar
  40. Preisler H, Mitchell R (1993) Colonization patterns of the mountain pine beetle in thinned and unthinned lodgepole pine stands. For Sci 39:528–545Google Scholar
  41. R Development Core Team (2009) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Accessed July 2010
  42. Raffa KF, Berryman AA (1983) The role of host plant resistance in the colonization behavior and ecology of bark beetles (Coleoptera: Scolytidae). Ecol Monogr 53:27–49CrossRefGoogle Scholar
  43. Raffa KF, Aukema BH, Bentz BJ, Carroll AL, Hicke JA, Turner MG, Romme WH (2008) Cross-scale drivers of natural disturbances prone to anthropogenic amplification: the dynamics of bark beetle eruptions. Bioscience 58:501–517Google Scholar
  44. Reid RW (1962) Biology of the mountain pine beetle, Dendroctonus monticolae Hopkins, in the east Kootenay region of British Columbia. I. Life cycle, brood development, and flight periods. Can Entomol 94:531–538CrossRefGoogle Scholar
  45. Robertson C, Nelson T, Jelinski D, Wulder MA, Boots B (2009) Spatial–temporal analysis of species range expansion: the case of the mountain pine beetle, Dendroctonus ponderosae. J Biogeogr 36:1446–1458CrossRefGoogle Scholar
  46. Ruel J-C, Pin D, Cooper K (2001) Windthrow in riparian buffer strips: effect of wind exposure, thinning and strip width. For Ecol Manag 143:105–113CrossRefGoogle Scholar
  47. Safranyik L (1978) Effects of climate and weather on mountain pine beetle populations. In: Berryman AA, Amman GD, Stark RW, Kibbee D, Hieb S (eds) Theory and practice of mountain pine beetle management in lodgepole pine forests, Moscow, Idaho, 25–27 April 1978Google Scholar
  48. Safranyik L, Carroll AL (2006) The biology and epidemiology of the mountain pine beetle in lodgepole pine forests. In: Safranyik L, Wilson B (eds) The mountain pine beetle: a synthesis of biology, management, and impacts on lodgepole pine. Natural Resources Canada, Victoria, pp 3–66Google Scholar
  49. Safranyik L, Linton DA (1983) Brood production by three spp. of Dendroctonus (Coleoptera: Scolytidae) in bolts from host and nonhost trees. J Entomol Soc B C 80:10–13Google Scholar
  50. Safranyik L, Shrimpton DM, Whitney HS (1974) Management of lodgepole pine to reduce losses from the mountain pine beetle. Natural Resources Canada, VictoriaGoogle Scholar
  51. Safranyik L, Shrimpton DM, Whitney HS (1975) An interpretation of the interaction between lodgepole pine, the mountain pine beetle and its associated blue stain fungi in western Canada. In: Baumgartner D (ed) Management of lodgepole pine ecosystems. Washington State University Cooperative Extension Service, Pullman, pp 406–428Google Scholar
  52. Safranyik L, Silversides R, McMullen LH, Linton DA (1989) An empirical approach to modeling the local dispersal of the mountain pine beetle (Dendroctonus ponderosae Hopk.) (Col., Scolytidae) in relation to sources of attraction, wind direction, and speed. J Appl Entomol 108:498–511CrossRefGoogle Scholar
  53. Safranyik L, Carroll AL, Regniere J, Langor DW, Riel WG, Shore TL, Peter B, Cooke BJ, Nealis VG, Taylor SW (2010) Potential for range expansion of mountain pine beetle into the boreal forest of North America. Can Entomol 142:415–442Google Scholar
  54. Shepherd RF (1966) Factors influencing the orientation and rates of activity of Dendroctonus ponderosae Hopkins (Coleoptera: Scolytidae). Can Entomol 97:207–215CrossRefGoogle Scholar
  55. Shore TL, Safranyik L (1992) Susceptibility and risk rating systems for mountain pine beetle in lodgepole pine stands. Natural Resources Canada, VictoriaGoogle Scholar
  56. Shore TL, Safranyik L, Lemieux JP (2000) Susceptibility of lodgepole pine stands to the mountain pine beetle: testing of a rating system. Can J For Res 30:44–49CrossRefGoogle Scholar
  57. Shore TL, Riel WG, Fall A (2008) Incorporating present and future climatic suitability into decision support tools to predict geographic spread of the mountain pine beetle. Mountain pine beetle working paper 2008-10, MPBI Project #2.03, Natural Resources Canada, Canadian Forest Service, Victoria, BC, Canada. ISBN 978-0-662-48890-3Google Scholar
  58. Stahl K, Moore RD, McKendry IG (2006) Climatology of winter cold spells in relation to mountain pine beetle outbreaks in British Columbia, Canada. Clim Res 32:13–23CrossRefGoogle Scholar
  59. Taylor LR (1974) Insect migration, flight periodicity and the boundary layer. J Anim Ecol 43:225–238CrossRefGoogle Scholar
  60. Trzcinski MK, Reid ML (2008) Effect of management on the spatial spread of mountain pine beetle (Dendroctonus ponderosae) in Banff national park. For Ecol Manag 256:418–1426CrossRefGoogle Scholar
  61. Waring RH, Pitman GB (1985) Modifying lodgepole pine stands to change susceptibility to mountain pine beetle attack. Ecology 66:889–897CrossRefGoogle Scholar
  62. Weiss A (2001) Topographic position and landforms analysis. Paper presented at the 21st ESRI user conference, San Diego, 9–13 July 2001Google Scholar
  63. Westbrook JK, Isard SA (1999) Atmospheric scales of biotic dispersal. Agric For Meteorol 97:263–274CrossRefGoogle Scholar
  64. Wulder MA, Dymond CC, White JC, Erikson B (2006) Detection, mapping, and monitoring of the mountain pine beetle. In: Safranyik L, Wilson B (eds) The mountain pine beetle: a synthesis of biology, management, and impacts on lodgepole pine. Natural Resources Canada, Victoria, pp 123–154Google Scholar
  65. Wygant ND (1940) Effects of low temperatures on the black hills beetle (Dendroctonus ponderosae Hopk.). Dissertation, New York State College of ForestryGoogle Scholar
  66. Zhang Q-B, Alfaro RI (2003) Spatial synchrony of the two-year cycle budworm outbreaks in central British Columbia, Canada. Oikos 102:146–154CrossRefGoogle Scholar
  67. Zheng Y, Aukema BH (2010) Hierarchical dynamic modeling of spatial–temporal binary data. Environmetrics 21:801–816CrossRefGoogle Scholar

Copyright information

© Her Majesty the Queen in Right of Canada as represented by the Canadian Forest Service  2011

Authors and Affiliations

  • Honey-Marie C. de la Giroday
    • 1
    Email author
  • Allan L. Carroll
    • 2
  • B. Staffan Lindgren
    • 1
  • Brian H. Aukema
    • 1
    • 3
  1. 1.University of Northern British ColumbiaPrince GeorgeCanada
  2. 2.Department of Forest SciencesUniversity of British ColumbiaVancouverCanada
  3. 3.Department of EntomologyUniversity of MinnesotaSt. PaulUSA

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