Influence of balsam fir stand condition on the abundance and diversity of eastern hemlock looper, Lambdina fiscellaria fiscellaria (Guen.) (Lepidoptera: Geometridae) natural enemies
Bibliographic record
Abstract
To assess the impact of natural enemies on the distribution of eastern hemlock looper various balsam fir stands were examined at Black Pond, in central Newfoundland. In 1995, 1996 and 1997 insects were collected using Malaise traps suspended into the balsam fir canopy. First, natural enemy abundance was assessed based on balsam fir stand vigour. A non-continuous vigour gradient was established using three silvicultural methods (root pruning, thinning, and fertilizing) and control treatments. Natural enemy abundance, in general and known eastern hemlock looper natural enemy abundance and diversity was higher in balsam fir stands that were more vigourous. These more vigorous stands provided natural enemies with more alternate hosts or prey. Second, natural enemy abundance was estimated based on the time since thinning and vegetation diversity of balsam fir stands. Natural enemy presence in stands that were unthinned, thinned one year prior to the study and thinned 16 years prior to the study were examined. Natural enemy abundance, in general and known eastern hemlock looper natural enemy abundance and diversity was higher in balsam fir stands that had had vigour increased by thinning 16 years prior to the study. The diversity of vegetation in these stands was higher due to the length of time since thinning. This increased vegetation diversity resulted in more resources available to natural enemies: more alternative feeding sites for adults, more shelter and overwintering sites. Balsam fir stands that have low vigour and have little or no understory vegetation seem to provide looper with enemy free space.
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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".