Revegetation of disturbed lands: establishing native plant communities on borrow pits in northern Manitoba
Bibliographic record
Abstract
The historical occurrence of hydroelectric development in northern Manitoba has resulted in disturbed areas without vegetative cover within the boreal forest. These disturbed areas exhibit conditions detrimental to restoration, including compacted soil lacking in nutrients, and organic matter and possessing low water-holding capacities. Northern climate conditions and short growing seasons further inhibit recovery potential. The study objective was to develop a strategy for encouraging self-sustaining native plant communities on borrow areas in northern Manitoba. Using fertilizer and mycorrhizal inoculations, seeding, transplants and cuttings were carried out using locally sourced plant species. Soil nitrogen, phosphorus, organic matter content, pH and electrical conductivity were analyzed for differences among treatments and the surrounding undisturbed forest to determine the impacts of material extraction on the land. Plant number, height, leaf area, chlorophyll fluorescence, chlorophyll a + b and total proteins as a proxy for stress were used to determine plant suitability for revegetation. Additionally, the height of trees planted by Manitoba Hydro and monitoring of the natural revegetation were performed over the duration of the experiment. Results of this study show transplantation as the most effective planting method due to the lower survival of seeds and cuttings. Successful establishment of Fragaria virginiana and Rubus idaeus transplants was observed. Inorganic fertilizer application resulted in increased leaf area and height of some species. Soil nutrients were significantly higher in fertilized plots although no significant differences were identified in the number or stress of plants between treatments. Differences in soil nitrogen, phosphorus and pH were found between the borrow pits and undisturbed forested areas. Inoculation with Oidiodendron maius increased survival of transplanted Vaccinium uliginosum and Vaccinium vitis-idaea. Natural revegetation increased with additions of woody debris on site. This research provides information for recommendations of site preparation and amendments required for revegetation efforts that can be implemented across borrow areas in northern boreal ecosystems.
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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 | 0.000 | 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".