Truffle abundance in riparian and upland mixed-conifer forest of California's southern Sierra Nevada
Bibliographic record
Abstract
We compared the abundance, diversity, and composition of truffles in riparian and upland areas within a mixed-conifer forest of the Sierra Nevada of California. We sampled for truffles in a single watershed over two seasons (spring and summer) and 4 years to determine whether truffles were more abundant and diverse in riparian than upland sites in old-growth, mixed-conifer forest. Truffle frequency, biomass, and species richness were greater in riparian sites than in upland sites in both spring and summer samples. Species composition of truffles also was different between sites, with nine and one species found exclusively in riparian and upland sites, respectively. Distance between the center of truffle plots to logs and trees was lower and soil moisture was greater in riparian sites compared with upland sites, suggesting that log density, tree proximity, and soil moisture may influence truffle production in these habitats. Our study underscores the importance of riparian areas for truffles, a primary food source for northern flying squirrels (Glaucomys sabrinus) in the Sierra Nevada of California.Key words: truffles, riparian, Sierra Nevada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".