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Skip to Search Results- 36Mountain pine beetle
- 8Lodgepole pine
- 5Curculionidae
- 5Jack pine
- 5Reproductive success
- 4Dendroctonus ponderoae
- 4Cullingham, Catherine I.
- 4Erbilgin, Nadir
- 4Evenden, Maya L.
- 3Coltman, David W.
- 3Pitt, Caitlin
- 2Bohlmann, Jörg
- 17The NSERC TRIA Network (TRIA-Net)
- 17The NSERC TRIA Network (TRIA-Net)/Journal Articles (TRIA-Net)
- 16Graduate and Postdoctoral Studies (GPS), Faculty of
- 16Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 13Biological Sciences, Department of
- 13Biological Sciences, Department of/Journal Articles (Biological Sciences)
- 4Erbilgin, Nadir (Renewable Resources)
- 2Evenden, Maya (Biological Sciences)
- 1Comeau, Phil (Renewable Resources)
- 1Cooke, Janice (Biological Sciences)
- 1Cárcamo, Hector (Agriculture and Agrifood Canada)
- 1Cárcamo, Héctor (Agriculture and AgriFood Canada, Lethbridge Research and Development Center)
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2020-06-01
Jones, Kelsey L., Rajabzadeh, Rahmatollah, Ishangulyyeva, Guncha, Erbilgin, Nadir, Evenden, Maya L.
Flight polyphenisms naturally occur as discrete or continuous traits in insects. Discrete flight polyphenisms include winged and wingless morphs, whereas continuous flight polyphenisms can take the form of short- or long-distance fliers. The mountain pine beetle (Dendroctonus ponderosae) exhibits...
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Molecular analysis of lodgepole and jack pine seedlings response to inoculation by mountain pine beetle fungal associate Grosmannia clavigera under well watered and water deficit
DownloadFall 2016
To date mountain pine beetle (MPB) has affected more than 19 million ha. of pine forests in Canada. The primary species affected by the current outbreak has been lodgepole pine (Pinus contorta), however as MPB range expands eastward beyond its historical habitat, the bark beetle has encountered a...
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Fall 2020
Dispersal by flight is a complex life history phase in many insects that is essential to gene flow and range expansion. Many elements contribute to realized dispersal, including biotic and abiotic environmental conditions, as well as intrinsic factors such as morphology, physiology and behavior....
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Optimization of semiochemical monitoring for pea leaf weevil, Sitona lineatus (Coleoptera: Curculionidae), in the Prairie Provinces
DownloadFall 2017
The pea leaf weevil, Sitona lineatus Linnaeus (Coleoptera: Curculionidae) is an invasive pest of increasing concern to pulse producers in the Canadian Prairie Provinces. Pea leaf weevil larvae cause damage to field pea (Pisum sativum) and faba bean (Vicia faba) crops by feeding on root nodules...
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2012-01-01
Cullingham, Catherine I., Sperling, Felix A. H., Coltman, David W., Roe, Amanda D.
Irruptive forest insect pests cause considerable ecological and economic damage, and their outbreaks have been increasing in frequency and severity. We use a phylogeographic approach to understand the location and progression of an outbreak by the MPB (Dendroctonus ponderosae Hopkins), an...
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Physiological, ecological and environmental factors that predispose trees, stands and landscapes to infestation by tree-killing Dendroctonus beetles
DownloadSpring 2013
In the last century the frequency and severity of outbreaks of tree-killing Dendroctonus beetles (Coleoptera: Curculionidae) have increased. Small-scale drivers within trees likely drive outbreak dynamics across landscapes. At a small scale, variation in carbohydrate availability within the stems...
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PLANT FATTY ACIDS INFLUENCE BROOD DEVELOPMENT OF MOUNTAIN PINE BEETLE AND GROWTH OF ITS SYMBIOTIC FUNGUS: IMPLICATIONS TO HOST-RANGE EXPANSION OF AN HERBIVOROUS INSECT
DownloadSpring 2015
Nutritional composition of plants can affect the performance of insect herbivores and their associated microbial symbionts. Mountain pine beetle (Dendroctonus ponderosae) is an important bark beetle species that colonizes many species of Pinus within its historical range and encounter host...
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2021-10-01
Pouria Ramazi, Mélodie Kunegel-Lion, Russell Greiner, Mark A. Lewis
Planning forest management relies on predicting insect outbreaks such as mountain pine beetle, particularly in the intermediate‐term future, e.g., 5‐year. Machine‐learning algorithms are potential solutions to this challenging problem due to their many successes across a variety of prediction...