Seeing the forest for the trees: an assessment of stand-level variation in arboreal spider (Araneae) assemblages in western Newfoundland, Canada
Bibliographic record
Abstract
Abstract Spiders (Araneae) are an abundant and diverse arthropod group that serve important ecosystem functions in boreal forests. Several hundred species across boreal Canada are prey for vertebrates and invertebrates. Spiders are also generalist predators that likely contribute to pest control. Our understanding of spider assemblages, particularly of the arboreal community, is minimal at the stand level in many habitats across Canada. Habitat-specific factors like connectivity, microclimate, and neighbour effects can substantially influence the structure of ecological communities. Well-replicated landscape-scale experimental designs enable us to better understand the structure of arboreal spider communities. Here, we employed beat-sheeting to characterise spider assemblages on balsam fir trees (Pinaceae) from the three most common stand types found in the boreal: coniferous, deciduous, and mixedwood. Fir trees in deciduous stands had greater spider abundance than did the trees in coniferous or mixedwood stands. Neither species diversity nor composition differed significantly among the three stand types. Our results suggest that spiders likely do not recognise “the forest for the trees.”
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".