Diversity, species richness, and abundance of spiders (Araneae) in different strata of boreal white spruce stands
Bibliographic record
Abstract
Abstract Spiders (Araneae) were sampled in white spruce (Picea glauca(Moench) Voss (Pinaceae)) dominated stands from the ground and shrub layers, and from several overstorey strata to assess patterns in species composition and diversity (alpha and beta) along the vertical gradient (0–12 m above ground). Overall, 3070 adult spiders in 15 families and 76 species were collected, with the ground layer accounting for the highest species richness (40 species) followed by the mid-overstorey (36 spp.) and the shrub layers (33 species). Vertical stratification was apparent in the samples: richness clearly decreased with height, and species turnover between the ground, shrub, and mid-overstorey levels was evident, suggesting that species composition in each layer was highly distinctive. Within the mid-overstorey stratification was less obvious but both species richness and spider abundance were predicted significantly by height from the ground and branch size. Given the role of late-seral conifer stands for maintaining old-growth species, understanding diversity patterns across strata provides basic knowledge to support forest management decisions that effectively conserve spider species and assemblages. It is clearly important to include higher canopy layers in considering impacts of forestry on biodiversity in the boreal mixedwood.
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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 | 0.001 | 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".