Identifying anthropogenic and fixed influencing factors of shrub encroachment in Cypress Upland, Canada
Bibliographic record
Abstract
When shrub cover in a grassland surpasses a critical threshold, it can alter the ecosystem negatively, leading to loss of grassland species and habitat, risk of high intensity fires, and loss of available forage for grazing. Shrub expansion into grasslands is a global issue and there is no solid conclusion for what is influencing it. This study aims to i) investigate anthropogenic factors that are connected to shrub cover; and ii) apply a model that uses topo-edaphic and anthropogenic factors to define current factors of shrub presence. Shrub cover in the study area (the West Block of the Saskatchewan Cypress Hills Interprovincial Park) has significantly extended into the native fescue grassland. Within the park, anthropogenic factors, such as closeness to roads, and time since last haying were connected to high shrub cover. When using topo-edaphic and anthropogenic variables in variations of generalized least squares models, a combination of distance to roads and hydrological features, high elevation, lack of haying, and certain soil moisture regimes and landscape units were connected to high shrub cover. The topo-edaphic factors were consistent with the literature and relate to the preferences of shrubs towards moisture, which is generated in the micro-climate from soil type, topography, elevation, and aspect. These are usually stable factors. Contrarily, anthropogenic factors vary over time and have a significant influence on shrub cover in the park. This research can be the steppingstone for achieving long-term resilience and sustainability of native grassland species and their habitats by better understanding the interaction of local factors on shrub presence.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".