Terrestrial gastropod responses to an ecosystem-level calcium manipulation in a northern hardwood forest
Bibliographic record
Abstract
The effects of acid deposition on soil calcium (Ca), and in turn on land snail populations, have been of heightened concern for several decades. We compiled a 10 year record (1997–2006) of gastropod abundance on two small watersheds at the Hubbard Brook Experimental Forest, one of which was treated with a Ca addition in 1999. In years 3–7 post Ca addition, snail abundance in the treated watershed was 73% higher than in the reference area (p < 0.001); there was no significant difference in the 3 years prior to treatment, and no significant difference in slug abundance in any year. We analyzed relationships between snail density and microsite spatial variation in leaf-litter Ca concentration, litter-layer thickness, tree species composition, slope, dead wood, and forest-floor light level. We found that snail abundance was significantly correlated with litter Ca concentration (p < 0.001) and negatively correlated with the importance value of American beech (p = 0.05). Isotopic-tracer analysis indicated that, on average, 76% of Ca in snail shells 5 years post treatment was derived from the added Ca. However, interannual variation in snail numbers indicates that other factors beyond available Ca have a strong influence on snail abundance.
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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) | 0.000 | 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".