Determinants of ground-dwelling spider assemblages at a regional scale in the Yukon Territory, Canada
Bibliographic record
Abstract
Arctic fauna is undergoing significant alteration in response to global climate change, yet we know little regarding the factors that determine species assemblages at northern latitudes. We used a latitudinal transect to assess environmental determinants of ground-dwelling spider assemblages across the boreal forest-tundra transition at a regional scale. Using multivariate techniques, we tested 3 complementary hypotheses regarding the factors that best explain patterns of assemblage structure. We predicted that spider assemblages would respond most strongly to vegetation composition and structure and that climate and spatial variables would explain less of the variation in the data. We sampled ground dwelling spiders using pitfall traps placed at 36 sites along the latitudinal transect. We constructed 3 separate matrices of spatial, climate, and vegetation variables, with each matrix representing a hypothesis. We used redundancy analysis with variation partitioning to determine which matrix of environmental variables best explained patterns in a matrix of spider abundances. We then used a separate redundancy analysis to determine which environmental variables best explained the variation in measures of species richness and activity density. We collected a total of 2890 individual spiders representing 103 species, 58 genera, and 13 families. Our analysis supports the hypothesis that vegetation composition and its related structure best explain patterns in northern spider assemblages at a regional scale.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".