PESTICIDE TREATMENTS AFFECT MOUNTAIN PINE BEETLE ABUNDANCE AND WOODPECKER FORAGING BEHAVIOR
Bibliographic record
Abstract
In British Columbia, Canada, management efforts used to control mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreaks have included treatment of infested trees with an organic arsenic pesticide, monosodium methanearsonate (MSMA). Cumulative pesticide applications over a large geographic area have generated concerns about arsenic loading in the environment and potential toxicity to nontarget wildlife. We investigated woodpecker foraging patterns in infested stands with and without MSMA treatment using a combination of tree debarking indices, point count surveys, and radiotelemetry methods in addition to insect flight traps to measure mountain pine beetle emergence. Debarking indices indicated woodpecker foraging of MSMA-treated trees was significantly lower than nontreated trees in all sampling years. However, approximately 40% of MSMA trees had some evidence of foraging. Focal observations of foraging woodpeckers and point count surveys in MSMA treatment areas further confirmed that several species of woodpeckers regularly used MSMA stands during the breeding season. Radio-tagged Hairy (Picoides villosus) and Three-toed (Picoides dorsalis) Woodpeckers spent on average 13% and 23% (range 0-66%) of their time, respectively, in treated stands, despite the fact that these areas only comprised on average 1-2% of their core home range (1 km2). MSMA strongly reduced the emergence of several bark beetle (Coleoptera, Scolytidae) species including the mountain pine beetle, and there was a highly significant positive relationship between Dendroctonus beetle abundance and Three-toed Woodpecker abundance. This study identifies the potential negative impact that forest management practices using pesticides can have on woodpecker populations that depend on bark beetles and their host trees.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".