Response of ground-dwelling spider assemblages to prescribed fire following stand structure manipulation in the southern Cascade RangeThis article is one of a selection of papers from the Special Forum on Ecological Studies in Interior Ponderosa Pine — First Findings from Blacks Mountain Interdisciplinary Research.
Bibliographic record
Abstract
We assessed spider (Arachnida: Araneae) responses to prescribed fire following stand structure treatments in ponderosa pine ( Pinus ponderosa Dougl. ex P. & C. Laws.) stands in the Cascade Range of California. Stands were logged or left untreated to create three levels of structural diversity. We logged one treatment to minimize old-growth characteristics (low diversity) and one to enhance old-growth characteristics (high diversity) and we used unlogged Research Natural Areas (RNAs) as old-growth, highest-diversity reference stands. We conducted low-intensity prescribed fire on half of each plot following harvest. Spider assemblages in unburned, logged stands were similar to one another but diverged from those in RNAs, with increased abundance, species richness, and diversity in more structurally diverse stands. Prescribed fire, which altered habitat in the organic soil layer where many spiders forage, resulted in altered spider assemblages and population declines in most plots. Fire generally reduced spider species richness, evenness, and diversity. Several taxa were potential indicators of fire and old-growth structure, and we discovered one species and one genus that were previously unknown. There was evidence that old-growth characteristics intensified the effects of fire on spider abundance. This outcome probably results from the deep litter layers in high-diversity stands and RNAs, which constituted greater fuel loads than low-diversity 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".