Succession of boreal forest spider assemblages following wildfire and harvesting
Bibliographic record
Abstract
To test whether spider succession following harvest differed from succession following wildfire, spiders were collected by pitfall trapping and sweep netting over two years in aspen‐dominated boreal forests. Over 8400 individuals from 127 species of spiders were identified from 12 stands representing three age‐classes (stand origin in 1995, 1982, and 1968) and two disturbance types (wildfire and harvesting). The diversity of spider assemblages tended to be higher in fire‐origin stands than in harvest‐origin stands; the youngest fire‐origin stands also supported more even distributions of spider species. Spider assemblages responded quickly to wildfire and harvesting as open habitat specialists colonized stands within one year after disturbance. Many web‐building species common to older forests either survived harvesting, or re‐colonized harvest‐origin stands more rapidly than they re‐colonized fire‐origin stands. Cluster analyses and DCA ordination show faunal convergence by ca 30 years after wildfire and harvesting; trajectories in re‐colonization, however, differed by disturbance type as the succession of spider assemblages from fire‐origin stands lagged behind spider succession in harvest‐origin stands. Comparison with cluster analyses using vegetation data and abiotic site conditions suggests spider assemblages recover from harvesting and fire more rapidly than do a variety of other site characteristics. Several spider species (e.g. Gnaphosa borea Kulezyński, Pirata bryantae Kurata, Arctosa alpigena (Doleschall)) appear dependent on some of the conditions associated with wildfires as they were absent or rarely collected in harvest‐origin stands.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".