Tall grass prairie ecosystem management—a gastropod perspective
Bibliographic record
Abstract
Less than 5% of the original tall grass prairie in North America remains. A portion of this remnant, composed of wetland, grassland and forest, is protected by the Nature Conservancy of Canada (NCC) in southern Manitoba. This heterogeneous ecosystem has rich biodiversity; however, gastropods have not been surveyed in Canada’s tall grass prairie. We studied gastropods in Prairie, Wet Meadow, Forest, and Wet Forest habitats of the Manitoba Tall Grass Prairie Preserve that vary with respect to land management practices (prescribed burning, grazing by cattle). Gastropod community composition was unique in the Prairie where mounds of grass litter form permanently moist cavities harbouring aquatic species, while dry-habitat species colonized the upper parts of these mounds. Gastropod communities in Prairie habitats were negatively affected by grazing and burning that occurred in the five years prior to our survey. Unburned Forest patches included both forest gastropod species and edge effect influenced open-habitat species and harboured the most diverse gastropod communities. These unburned Forest patches potentially provide a species pool for post-burn prairie recolonization. The gastropod community of Wet Meadows was not affected by grazing and was composed mainly of aquatic species. In this gastropod survey five species were recorded from Manitoba for the first time. The rare Blade Vertigo (Vertigo milium) is also reported.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".