Effect of boreal forest disturbance due to logging at different spatial scales on migratory songbirds
Abstract
Boreal birds have experienced population declines that may be related to alteration of the forest
at a range of scales. Understanding how resource extraction may affect the distribution and
abundance of species is critical to address conservation policy in the boreal forest region. This
study aims to understand how habitat alteration by logging influences the abundance and habitat
choices of a migratory songbird, the Canada Warbler (CAWA; Cardellina canadensis) in its
Canadian breeding range and more specifically within the northwestern region of Ontario, where
there is little information about this species at risk. I assess whether there exists a different
response in the abundance of upland migratory songbirds to logging disturbance at different
scales. Also, I assessed the “habitat compensation hypothesis,” which states that some species
can substitute their primary habitat for other alternative and less preferred habitats on the
landscape. I conduct a meta-analysis of 21 studies to identify the effects of habitat alteration on a
relative abundance index (RAI) of 21 upland songbird species, comparing logged to unlogged
sites along the southern border of Canadian boreal forest. Using generalized linear mixed models
(GLMM), I model the RAI incorporating two scales (local- and landscape-scale effects), time
since logging, and forest type. Several species, including CAWA, are reported in decline in
Canada. They occasionally have a higher mean RAI comparing logged areas at landscape scale
than comparing at the finer local scale, suggesting that they occupy lower quality habitats in
disturbed areas. The results are consistent with other findings: birds associated with old-growth
forests are most sensitive to logging, as well as birds that nest on trees and those more associated
with a coniferous forest. I then assess how time since logging affects CAWA occurrence and
distribution in Northwestern Ontario. I use Maxent software to develop a predictive highresolution (30 m) field-validated species distribution model (SDM). [...]