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Source and spread dynamics of mountain pine beetle in central Alberta, Canada

Published online by Cambridge University Press:  24 February 2021

Victor A. Shegelski Open the ORCID record for Victor A. Shegelski [Opens in a new window] ,
Erin O. Campbell Open the ORCID record for Erin O. Campbell [Opens in a new window] ,
Kirsten M. Thompson Open the ORCID record for Kirsten M. Thompson [Opens in a new window] ,
Caroline M. Whitehouse Open the ORCID record for Caroline M. Whitehouse [Opens in a new window]  and
Felix A.H. Sperling Open the ORCID record for Felix A.H. Sperling [Opens in a new window]
Victor A. Shegelski*
Affiliation:
Department of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9, Canada
Erin O. Campbell
Affiliation:
Department of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9, Canada
Kirsten M. Thompson
Affiliation:
Department of Ecosystem Science and Management, University of Northern British Columbia, Prince George, British Columbia, V2N 4Z9, Canada
Caroline M. Whitehouse
Affiliation:
Alberta Agriculture and Forestry, Government of Alberta, Edmonton, Alberta, T5K 2M4, Canada
Felix A.H. Sperling
Affiliation:
Department of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9, Canada
*
*Corresponding author. Email: [email protected]
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Abstract

The mountain pine beetle (Dendroctonus ponderosae Hopkins) (Coleoptera: Curculionidae) is a significant destructive force in the pine forests of western Canada and has the capacity to spread east into a novel host tree species, jack pine (Pinaceae). New populations have been documented in central Alberta, Canada, but the source populations for these outbreaks have yet to be identified. In this study, we use genetic data to identify parent populations for recent outbreak sites near Slave Lake, Lac La Biche, and Hinton, Alberta. We found the northern population cluster that entered Alberta near Grande Prairie was the source of the most eastern established population near Lac La Biche, and the range expansion to this leading-edge population has been too rapid to establish evidence of population structure. However, some dispersal from a population in the Jasper and Hinton area has been detected as far north and east as Slave Lake, Alberta. We also identified two potential source populations for the current outbreak in Hinton: most beetles appear to be from Jasper National Park, Alberta, but some also originated from the northern population cluster. These findings demonstrate the dynamic dispersal capabilities of mountain pine beetle across the Alberta landscape and the potential hazard of increased dispersal to newly established leading-edge populations.

Type
Research Papers
Information
The Canadian Entomologist , Volume 153 , Issue 3 , June 2021 , pp. 314 - 326
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Copyright
© The authors and the Government of Alberta, 2021. Published by Cambridge University Press on behalf of the Entomological Society of Canada

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Footnotes

Subject editor: Barbara Bentz

References

Abdellaoui, A., Hottenga, J., de Knijff, P., Nivard, M.G., Xiao, X., Scheet, P., et al. 2013. Population structure, migration, and diversifying selection in the Netherlands. European Journal of Human Genetics, 21: 1277–1285. https://doi.org/10.1038/ejhg.2013.48.CrossRefGoogle ScholarPubMed
Alhusain, L. and Hafez, A.M. 2018. Nonparametric approaches for population structure analysis. Human Genomics, 12: 25. https://doi.org/10.1186/s40246-018-0156-4.CrossRefGoogle ScholarPubMed
Batista, P.D., Janes, J.K., Boone, C.K., Murray, B.W., and Sperling, F.A.H. 2016. Adaptive and neutral markers both show continent-wide population structure of mountain pine beetle (Dendroctonus ponderosae). Ecology and Evolution, 6: 6292–6300. https://doi.org/10.1002/ece3.2367.CrossRefGoogle Scholar
Bleiker, K.P. 2019. Risk assessment of the threat of mountain pine beetle to Canada’s boreal and eastern pine forests [online]. Canadian Council of Forest Ministers Forest Pest Working Group, Natural Resources Canada. Available from http://cfs.nrcan.gc.ca/publications [accessed 23 October 2019].Google Scholar
Bleiker, K.P., Heron, R.J., Braithwaite, E.C., and Smith, G.D. 2013. Pre-emergence mating in the mass-attacking bark beetle, Dendroctonus ponderosae (Coleoptera: Curculionidae). The Canadian Entomologist, 145: 1–8. https://doi.org/10.4039/tce.2012.102.CrossRefGoogle Scholar
Bleiker, K.P., O’Brien, M.R., Smith, G.D., and Carroll, A.L. 2014. Characterisation of attacks made by the mountain pine beetle (Coleoptera: Curculionidae) during its endemic population phase. The Canadian Entomologist, 146: 271–284. https://doi.org/10.4039/tce.2013.71.CrossRefGoogle Scholar
Blomquist, G.J., Figueroa-Teran, R., Aw, M., Song, M., Gorzalski, A., Abbott, N.L., et al. 2010. Pheromone production in bark beetles. Insect Biochemistry and Molecular Biology, 40: 699–712. https://doi.org/10.1016/j.ibmb.2010.07.013.CrossRefGoogle ScholarPubMed
Butts, C.T. 2016. SNA: tools for social network analysis. R package. Version 2.4 [online]. Available from https://CRAN.R-project.org/package=sna [accessed 16 August 2019].Google Scholar
Campbell, E.O., Davis, C.S., Dupuis, J.R., Muirhead, K., and Sperling, F.A.H. 2017. Cross-platform compatibility of de novo-aligned SNPs in a nonmodel butterfly genus. Molecular Ecology Resources, 17: e84–e93. https://doi.org/10.1111/1755-0998.12695.CrossRefGoogle Scholar
Catchen, J.M., Amores, A., Hohenlohe, P., Cresko, W., and Postlethwait, J.H. 2011. Stacks: building and genotyping loci de novo from short-read sequences. G3: Genes, Genomes, Genetics, 1: 171–182. https://doi.org/10.1534/g3.111.000240.CrossRefGoogle ScholarPubMed
Cullingham, C.I., Cooke, J.E.K., Dang, S., Cooke, B.J., and Coltman, D.W. 2011. Mountain pine beetle host-range expansion threatens the boreal forest. Molecular Ecology, 20: 2157–2171. https://doi.org/10.1111/j.1365-294X.2011.05086.x.CrossRefGoogle ScholarPubMed
Cullingham, C.I., Roe, A.D., Sperling, F.A.H., and Coltman, D.W. 2012. Phylogeographic insights into an irruptive pest outbreak. Ecology and Evolution, 2: 908–919. https://doi.org/10.1002/ece3.102.CrossRefGoogle ScholarPubMed
Danecek, P., Auton, A., Abecasis, G., Albers, C.A., Banks, E., DePristo, M.A., et al. 2011. The variant call format and VCFtools. Bioinformatics, 27: 2156–2158.CrossRefGoogle ScholarPubMed
Evanno, G., Regnaut, S., and Goudet, J. 2005. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology, 14: 2611–2620. https://doi.org/10.1111/j.1365-294X.2005.02553.x.CrossRefGoogle ScholarPubMed
Falush, D., Stephens, M., and Pritchard, J.K. 2003. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics, 164: 1567–1587.CrossRefGoogle ScholarPubMed
Falush, D., Stephens, M., and Pritchard, J.K. 2007. Inference of population structure using multilocus genotype data: dominant markers and null alleles. Molecular Ecology Notes, 7: 574–578. https://doi.org/10.1111/j.1471-8286.2007.01758.x.CrossRefGoogle ScholarPubMed
Gruber, B. and Georges, A. 2019. dartR: Importing and analysing SNP and silicodart data generated by genome-wide restriction fragment analysis. R package. Version 1.1.11 [online]. Available from https://CRAN.R-project.org/package=dartR [accessed 27 November 2019].Google Scholar
Hijmans, R.J. 2019. Geosphere: spherical trigonometry. R package. Version 1.5–10 [online]. Available from https://CRAN.R-project.org/package=geosphere [accessed 16 August 2019].Google Scholar
Hopping, G.R. and Mathers, W.G. 1945. Observations on outbreaks and control of the mountain pine beetle in the lodge-pole pine stands of Western Canada. The Forestry Chronicle, 21: 98–108. https://doi.org/10.5558/tfc21098-2.CrossRefGoogle Scholar
Hubisz, M.J., Falush, D., Stephens, M., and Pritchard, J.K. 2009. Inferring weak population structure with the assistance of sample group information. Molecular Ecology Resources, 9: 1322–1332. https://doi.org/10.1111/j.1755-0998.2009.02591.x.CrossRefGoogle ScholarPubMed
Jackson, P.L., Straussfogel, D., Lindgren, B.S., Mitchell, S., and Murphy, B. 2008. Radar observation and aerial capture of mountain pine beetle, Dendroctonus ponderosae Hopk. (Coleoptera: Scolytidae) in flight above the forest canopy. Canadian Journal of Forest Research, 38: 2313–2327. https://doi.org/10.1139/X08-066.CrossRefGoogle Scholar
James, P.M.A., Janes, J.K., Roe, A.D., and Cooke, B.J. 2016. Modelling landscape-level spatial variation in sex ratio skew in the mountain pine beetle (Coleoptera: Curculionidae). Environmental Entomology, 45: 790–801. https://doi.org/10.1093/ee/nvw048.CrossRefGoogle Scholar
Janes, J.K., Roe, A.D., Rice, A.V., Gorrell, J.C., Coltman, D.W., Langor, D.W., and Sperling, F.A.H. 2016. Polygamy and an absence of fine-scale structure in Dendroctonus ponderosae (Hopk.) (Coleoptera: Curcilionidae) confirmed using molecular markers. Heredity, 116: 68–74. https://doi.org/10.1038/hdy.2015.71.CrossRefGoogle Scholar
Janes, J.K., Li, Y., Keeling, C.I., Yuen, M.M.S., Boone, C.K., Cooke, J.E.K., et al. 2014. How the mountain pine beetle (Dendroctonus ponderosae) breached the Canadian Rocky Mountains. Molecular Biology and Evolution, 31: 1803–1815. https://doi.org/10.1093/molbev/msu135.CrossRefGoogle ScholarPubMed
Janes, J.K., Worth, J.R.P., Batista, P.D., and Sperling, F.A.H. 2018. Inferring ancestry and divergence events in a forest pest using low-density single-nucleotide polymorphisms. Insect Systematics and Diversity, 2: 1–9. https://doi.org/10.1093/isd/ixy019.CrossRefGoogle Scholar
Jombart, T. 2008. adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics, 24: 1403–1405. https://doi.org/10.1093/bioinformatics/btn129.CrossRefGoogle Scholar
Jombart, T. and Ahmed, I. 2011. adegenet 1.3–1: new tools for the analysis of genome-wide SNP data. Bioinformatics 27: 3070–3071. https://doi.org/10.1093/bioinformatics/btr521.CrossRefGoogle ScholarPubMed
Jombart, T., Devillard, S., and Balloux, F. 2010. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genetics 11: 94. https://doi.org/10.1186/1471-2156-11-94.CrossRefGoogle ScholarPubMed
Keeling, C.I., Yuen, M.M., Liao, N.Y., Docking, T.R., Chan, S.K., Taylor, G.A., et al. 2013. Draft genome of the mountain pine beetle, Dendroctonus ponderosae Hopkins, a major forest pest. Genome Biology, 14: R27. https://doi.org/10.1186/gb-2013-14-3-r27.CrossRefGoogle ScholarPubMed
Klutsch, J.G., Najar, A., Cale, J.A., and Erbilgin, N. 2016. Direction of interaction between mountain pine beetle (Dendroctonus ponderosae) and resource-sharing wood-boring beetles depends on plant parasite infection. Oecologia, 182: 1–12. https://doi.org/10.1007/s00442-016-3559-8.CrossRefGoogle ScholarPubMed
Kopelman, N.M., Mayzel, J., Jakobsson, M., Rosenberg, N.A., and Mayrose, I. 2015. CLUMPAK: a program for identifying clustering models and packaging population structure inferences across K . Molecular Ecology Resources, 15: 1179–1191. https://doi.org/10.1111/1755-0998.12387.CrossRefGoogle ScholarPubMed
Langor, D.W. and Spence, J.R. 1991. Host effects on allozyme and morphological variation of the mountain pine beetle, Dendroctonus ponderosae Hopkins (Coleoptera: Scolytidae). The Canadian Entomologist, 123: 395–410. https://doi.org/10.4039/Ent123395–2.CrossRefGoogle Scholar
Larroque, J., Johns, R., Canape, J., Morin, B., and James, P.M.A. 2020. Spatial genetic structure at the leading edge of a spruce budworm outbreak: the role of dispersal in outbreak spread. Forest Ecology and Management, 461: 117965. https://doi.org/10.1016/j.foreco.2020.117965.CrossRefGoogle Scholar
Lenormand, T. 2002. Gene flow and the limits to natural selection. Trends in Ecology & Evolution, 17: 183–189. https://doi.org/10.1016/S0169-5347(02)02497-7.CrossRefGoogle Scholar
Li, H. and Durbin, R. 2009. Fast and accurate short read alignment with Burrows-Wheeler Transform. Bioinformatics, 25: 1754–1760. https://doi.org/10.1093/bioinformatics/btp324.CrossRefGoogle ScholarPubMed
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., et al. 2009. The Sequence Alignment/Map format and SAMtools. Bioinformatics, 25: 2078–2079. https://doi.org/10.1093/bioinformatics/btp352.CrossRefGoogle ScholarPubMed
MacCormick, J. 2020. Spread management action collaborative. Bugs and Diseases, 31: 6.Google Scholar
Martin, M. 2011. Cutadapt removed adapter sequences from high-throughput sequencing reads. EMBnet.journal, 17: 10–11.CrossRefGoogle Scholar
Miller, D.R., Lindgren, B.S., and Borden, J.H. 2005. Dose-dependent pheromone responses of mountain pine beetle in stands of lodgepole pine. Environmental Entomology, 34: 1019–1027. https://doi.org/10.1093/ee/34.5.1019.CrossRefGoogle Scholar
Mock, K.E., Bentz, B.J., O’Neill, E.M., Chong, J.P., Orwin, J., and Pfrender, M.E. 2007. Landscape-scale genetic variation in a forest outbreak species, the mountain pine beetle (Dendroctonus ponderosae). Molecular Ecology, 16: 553–568. https://doi.org/10.1111/j.1365-294X.2006.03158.x.CrossRefGoogle Scholar
Natural Resources Canada. 2017. Mountain pine beetle (factsheet) [online]. Canadian Forest Service, Natural Resources Canada. Available from http://www.nrcan.gc.ca/forests/fire-insects-disturbances/top-insects/13397 [accessed 16 October 2019].Google Scholar
Paris, J.R., Stevens, J.R., and Catchen, J.M. 2017. Lost in parameter space: a road map for STACKS. Methods in Ecology and Evolution, 8: 1360–1373.CrossRefGoogle Scholar
Peterson, B.K., Weber, J.N., Kay, E.H., Fisher, H.S., and Hoekstra, H.E. 2012. Double Digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PLOS One, 7: e37135. https://doi.org/10.1371/journal.pone.0037135.CrossRefGoogle Scholar
Poland, J.A., Brown, P.J., Sorrells, M.E., and Jannink, J.L. 2012. Development of high-density genetic maps for barley and wheat using a novel two-enzyme genotyping-by-sequencing approach. PLOS One, 7: e32253. https://doi.org/10.1371/journal.pone.0032253.CrossRefGoogle ScholarPubMed
Price, A.L., Zaitlen, N.A., Reich, D., and Patterson, N. 2010. New approaches to population stratification in genome-wide association studies. Nature Reviews Genetics, 11: 459–463. https://doi.org/10.1038/nrg2813.CrossRefGoogle ScholarPubMed
Pritchard, J.K., Stephens, M., and Donnelly, P. 2000. Inference of population structure using multilocus genotype data. Genetics, 155: 945–959.CrossRefGoogle ScholarPubMed
Puechmaille, S.J. 2016. The program STRUCTURE does not reliably recover the correct population structure when sampling is uneven: sub-sampling and new estimator alleviate the problem. Molecular Ecology Resources, 16: 608–627. https://doi.org/10.1111/1755-0998.12512.CrossRefGoogle ScholarPubMed
R Core Team. 2018. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria [online]. Available from https://www.R-project.org/ [accessed 13 September 2018].Google Scholar
Raymond, M. and Rousset, F., 1995. Genepop (version 1.2): population genetics software for exact tests and ecumenicism. Journal of Heredity, 86: 248–249. https://doi.org/10.1093/oxfordjournals.jhered.a111573.CrossRefGoogle Scholar
Reid, R.W. 1958. The behaviour of the mountain pine beetle, Dendroctonus ponderosae Hopk., during mating, egg laying, and gallery construction. The Canadian Entomologist, 90: 505–509. https://doi.org/10.4039/Ent90505-9.CrossRefGoogle Scholar
Rochette, N.C., Rivera-Colón, A.G., and Catchen, J.M. 2019. Stacks 2: Analytical methods for paired-end sequencing improve RADseq-based population genomics. Molecular Ecology, 28: 4737–4754. https://doi.org/10.1111/mec.15253.CrossRefGoogle ScholarPubMed
Rousset, F. 2008. Genepop'007: a complete reimplementation of the Genepop software for Windows and Linux. Molecular Ecology Resources, 8: 103–106. https://doi.org/10.1111/j.1471-8286.2007.01931.x.CrossRefGoogle Scholar
Royama, T. 1984. Population dynamics of the spruce budworm Choristoneura fumiferana . Ecological Monographs, 54: 429–462. https://doi.org/10.2307/1942595.CrossRefGoogle Scholar
Safranyik, L. and Carroll, A.L. 2006. The biology and epidemiology of the mountain pine beetle in lodgepole pine forests. In The mountain pine beetle, a synthesis of biology, management, and impacts on lodgepole pine. Edited by L. Safranyik and B. Wilson. Natural Resources Canada, Canadian Forest Service, Pacific Forestry Centre, Victoria, British Columbia, Canada. Pp. 3–66.Google Scholar
Safranyik, L., Carroll, A.L., Régnière, J., Langor, D.W., Riel, W.G., Shore, T.L., et al. 2010. Potential for range expansion of mountain pine beetle into the boreal forest of North America. The Canadian Entomologist, 142: 415–442. https://doi.org/10.4039/n08-CPA01.CrossRefGoogle Scholar
Samarasekera, G.D.N.G., Bartell, N.V., Lindgren, B.S., Cooke, J.E.K., Davis, C.S., James, P.M.A., et al. 2012. Spatial genetic structure of the mountain pine beetle (Dendroctonus ponderosae) outbreak in western Canada: historical patterns and contemporary dispersal. Molecular Ecology, 21: 2931–2948. https://doi.org/10.1111/j.1365-294X.2012.05587.x.CrossRefGoogle Scholar
Trevoy, S.A.L., Janes, J.K., Muirhead, K., and Sperling, F.A.H. 2019. Repurposing population genetics data to discern genomic architecture: a case study of linkage cohort detection in mountain pine beetle (Dendroctonus ponderosae). Ecology and Evolution, 9: 1147–1159. https://doi.org/10.1002/ece3.4803.CrossRefGoogle Scholar
Trevoy, S.A.L., Janes, J.K., and Sperling, F.A.H. 2018. Where did mountain pine beetle populations in Jasper Park come from? Tracking beetles with genetics. The Forestry Chronicle, 94: 20–24. https://doi.org/10.5558/tfc2018-004.CrossRefGoogle Scholar
van der Merwe, M., McPherson, H., Siow, J., and Rossetto, M. 2014. Next gen phylogeography of rainforest trees: exploring landscape-level cpDNA variation from whole-genome sequencing. Molecular Ecology Resources, 14: 199–208. https://doi.org/10.1111/1755-0998.12176.CrossRefGoogle ScholarPubMed
Weatherstats.ca. 2020. Weatherstats.ca based on Environmental and Climate Change Canada data [online]. Available from https://hinton.weatherstats.ca/metrics/wind_direction.html [accessed 3 March 2020].Google Scholar
Whittaker, P. 2018. Federal government must act on national pine beetle problem [online]. CBC News. Available from: https://www.cbc.ca/news/canada/edmonton/pine-beetle-column-alberta-forest-products-association-1.4895576 [accessed 24 February 2020].Google Scholar
Wickham, H. 2016. ggplot2: elegant graphics for data analysis [online]. Springer-Verlag New York, New York, United States of America. Available from https://CRAN.R-project.org/package=ggplot2 [accessed 13 August 2019].Google Scholar
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