GRAZING AND SUBSTRATE INTERACT TO AFFECT NATIVE VS. EXOTIC DIVERSITY IN ROADSIDE GRASSLANDS
Bibliographic record
Abstract
We compared the native and exotic species composition of ungrazed roadside verges with that of adjacent grazed interiors in the grasslands of California's inner northern coast range (Napa and Lake Counties). We sampled 72 pairs of verge and interior quadrats at five sites representative of the region's grasslands, on both fertile (loam) and infertile (serpentine) soils, avoiding all obvious forms of roadside physical disturbance. We found that, on serpentine soils, ungrazed verges had a higher proportion of exotic species than grazed interiors; on nonserpentine soils, the reverse was true. Within serpentine soils, native species were more prevalent in quadrats with lower biomass; within nonserpentine, natives were more prevalent in quadrats receiving less radiation. Overall, the total species diversity was higher in grazed interiors than on ungrazed verges, regardless of the fertility of the substrate. Our results indicate that the ecological role of roadside verges depends on the interactive effects of community composition and history, environmental gradients, and land use practices that characterize a region.
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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 | 0.000 |
| 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".