Not just for the birds: Spiders as natural enemies of spruce budworm (Choristoneura fumiferana, Clem.)
Bibliographic record
Abstract
The eastern spruce budworm (Choristoneura fumiferana, Clem.) is a native irruptive forest pest that defoliates spruce-fir forests throughout North America’s boreal zone. Past studies suggest that successful spruce budworm population control requires high natural mortality from a variety of sources, including predators, especially from parasitoids and birds. While well represented in many different ecosystems, the role of generalist predatory spiders in these boreal systems remains largely unstudied. To determine the identity and percentage of spiders that predate on spruce budworm, we hand collected spiders from balsam fir (Abies balsamea) in stands with relatively high spruce budworm densities from forests in insular Newfoundland and Labrador, Canada. Using a spruce budworm specific TaqMan real time PCR assay we successfully amplified spruce budworm DNA in 32% of collected spiders. After spider molecular barcoding we found the web-builders Grammonota angusta Dondale, Pityohyphantes (aff. subarcticus), Dictyna brevitarsa Emerton, and Estrandia grandaeva (Keyserling) represented 58% of the spiders feeding on spruce budworm, and the wandering hunter Philodromus rufus vibrans Dondale represented 11.8%. Our molecular approach was an effective means with which to identify recently consumed prey and natural enemies in this boreal system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 0.000 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".