The ecological equivalence of quarry floors to alvars
Bibliographic record
Abstract
Abstract Question:Are the biophysical conditions of abandoned limestone quarry floors and natural alvars sufficiently similar to each other for alvars to be used as a model for quarry floor restoration? Location:Ontario, Canada. Methods:We measured plant species frequency and environmental and soil variables in 13 abandoned limestone quarries and used ANOVA to compare them with data previously collected from seven natural alvars. We used multivariate ordinations on the quarry floor data alone and on the combined quarry floor and alvar data to determine how plant community structure was controlled by the abiotic environment in both habitats. Results:Except for higher levels of many nutrients, the physical characteristics were similar between quarry floors and alvars. 246 plant species were found on quarry floors as compared to 283 on alvars, with 79 species in common between the two habitat types. While quarry floors supported fewer bryophytes and more exotic vascular plants compared with alvars, five alvar endemics and 24 characteristic alvar species were found to grow there. The age of the site, nutrient levels, and presence of standing water and bare rock were important factors influencing species composition in both habitats. Conclusions:Through natural revegetation alone, the abandoned quarry floors surveyed in this study have already taken on many physical and vegetation characteristics of natural alvars. This makes alvars very suitable as the restoration goal for abandoned limestone quarries.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".