Small to large-scale patterns of ground-dwelling spider (Araneae) diversity across northern Canada
Bibliographic record
Abstract
We examined how Arctic spider (Araneae) biodiversity is distributed at multiple spatial scales in northern Canada using a standardized hierarchical sampling design. We investigated which drivers, environmental or spatial, influence the patterns observed. Spatial patterns of Arctic spider species richness and composition were assessed in 12 sites located in arctic, subarctic, and north boreal ecoclimatic regions, spanning 30 degrees of latitude and 80 degrees of longitude. Variation in diversity was partitioned in relation to multiple environmental and spatial drivers of diversity patterns. Over 23 000 adult spiders, representing 306 species in 14 families, were collected in northern Canada, with 107 species (35% of the total species collected) representing new territorial or provincial records. Spider diversity was structured at the regional scale across ecoclimatic regions but was not structured with latitude. Longitudinal patterns of spider diversity across Canada may be explained by post-glacial dispersal. At local scales, diversity was non-randomly distributed and possibly limited by biotic interactions. We recommend the use of ecoclimatic regions as a framework for conservation of biodiversity in northern Canada and spiders as useful bioindicators that can help us understand the effects of climate change across ecoclimatic regions of northern Canada.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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".