Canadian Forest Service Publications

Cross‐scale effects of spruce budworm outbreaks on boreal warblers in eastern Canada. 2018. Drever, M.C.; Smith, A.C.; Venier, L.A.; Sleep, D.J.H.; MacLean, D.A. Ecology and Evolution 8(15): 7334-7345.

Year: 2018

Available from: Great Lakes Forestry Centre

Catalog ID: 39362

Language: English

CFS Availability: PDF (download)

Available from the Journal's Web site.
DOI: 10.1002/ece3.4244

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Plain Language Summary

Insect outbreaks are major natural disturbance events that affect communities of forest birds, either directly by affecting the food supply or indirectly by changing the vegetation composition of forest canopies. An examination of correlations between measures of bird and insect abundance across different spatial scales and over varying time lag effects may provide insight into underlying mechanisms. We developed a hierarchical Bayesian model to assess correlations between counts of eight warbler species from the Breeding Bird Survey in eastern Canada, 1966 to 2009, with the presence of spruce budworm (Choristoneura fumiferana Clem.) at immediate local scales and time‐lagged regional scales, as measured by extent of defoliation on host tree species. Budworm‐associated species Cape May warbler (Setophaga tigrina), bay‐breasted warbler (Setophaga castanea), and Tennessee warbler (Oreothlypis peregrina) responded strongly and positively to both local and regional effects. In contrast, non‐budworm‐associated species, Blackburnian warbler (Setophaga fusca), magnolia warbler (Setophaga magnolia), Canada warbler (Cardellina canadensis), black‐throated blue warbler (Setophaga caerulescens), and black‐throated green warbler (Setophaga virens), only responded to regional effects in a manner that varied across eastern Canada. The complex responses by forest birds to insect outbreaks involve both increased numerical responses to food supply and to longer term responses to changes in forest structure and composition. These effects can vary across spatial scales and be captured in hierarchical population models, which can serve to disentangle common trends from data when examining drivers of population dynamics like forest management or climate change.

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