Plains rough fescue grassland restoration using natural regeneration after pipeline disturbances
Bibliographic record
Abstract
Plains rough fescue (Festuca hallii), once a dominant grassland in the Northern Great Plains, has been reduced to a fraction of its original extent by agricultural intensification and energy sector disturbances and has become a threatened community type. Despite thousands of kilometers of pipelines in grasslands, little is documented about long‐term restoration outcomes. This research assessed recovery of rough fescue grassland 6–21 years after pipeline construction with topsoil stripping and natural regeneration relative to undisturbed reference sites in south‐central Canada. Soil properties varied between pipelines and undisturbed prairie, although most were within theoretical values to support plant growth and development. Vegetation cover, species richness and Shannon diversity and evenness did not differ significantly between pipelines and undisturbed prairie. Multivariate analysis (multi‐response permutation procedure) showed plant community composition, and its dominant species differed significantly between pipelines and undisturbed prairie. Bray–Curtis dissimilarity indices showed dominant species and functional species groups on pipelines were more similar to undisturbed prairie than the undesirable species group. Presence of early‐ to late‐successional species and increasing F. hallii with pipeline age indicate restoration was possible with topsoil salvage and replacement, using natural regeneration as a revegetation method, but requires time to develop and restore a typical rough fescue grassland ecosystem.
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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 | 0.000 | 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".