Evaluating Strategies for the Restoration and Reestablishment of Native Grasslands in the Foothills Fescue Subregion in Southern Alberta
Bibliographic record
Abstract
Removal of invasive species within the Canadian shortgrass prairie is one of the greatest challenges to native grassland restoration. Invasive grass species are successful in this ecosystem because they are typically adapted to high grazing and trampling pressures, do not require fire for regeneration, and tolerate a wide range of climatic conditions. In the southern Alberta Foothills Fescue subregion, the common exotic species, Bromus inermis (smooth brome) and Poa pratensis (Kentucky bluegrass), are aggressive colonizers that spread quickly through rhizomes and are difficult to eradicate once established, allowing them to displace native grasses. Success of invasive species in this subregion is exacerbated by anthropogenic impacts, which include the alteration of fire regimes, extirpation of native grazers, and climate change. I investigated strategies for restoring a disturbed grassland by employing several restoration strategies in isolation and combination: mowing, plowing, herbicide application, carbon addition, and native seed addition. The experimental plots were monitored throughout the 2019 growing season. Within each plot, the total number of species, number of individuals per species, bare ground percentage, and aboveground biomass were quantified for each plot. At the end of the sampling period, soil samples were collected from each plot to test for differences in carbon, nitrates, pH, and salinity between treatments and control plots. The results showed the dominance of invasive species within the Foothills Fescue subregion with a majority presence of Kentucky bluegrass, smooth brome, and timothy (Phleum pratense). Through the application of the restoration treatment methods, plots that were plowed and seeded demonstrated the highest level of restorative success. However, low germination rates of planted seeds and seed predation from animals impacted overall biomass in some of the treatment types, suggesting that additional observation years are required for further assessment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".