Reclamation of an eroded lakeshore slope using small vegetation islands and terraces
Bibliographic record
Abstract
Bioengineering approaches to slope stabilization involve biological and mechanical methods with low impact on the environment and landscape. Slope stabilization using vegetation patches or islands can greatly decrease runoff and soil erosion on an eroded lake shore. While vegetation islands showed promise for forest and grassland reclamation, they have rarely been used on eroded lake shores. A study was conducted to determine whether bioengineering using native vegetation islands and terraces could successfully revegetate and stabilize a severely eroded lake shore slope in the central aspen parkland, Alberta, Canada. Three gullies and three slopes were terraced using pressure treated planks, then transplanted with non-dormant (mid-August) and dormant (mid-October) 20 cm diameter vegetation islands in a soil amended with 25% (by volume) compost. Volumetric water content was significantly less in lower slope positions than upper slope positions, and sediment transport to lower slope positions was much reduced. After one year, both non-dormant and dormant transplanted islands survived and established on the terraced slope, under relatively inhospitable growing conditions. Although non-dormant islands had significantly lower vegetation mortality (10% or less) than dormant islands on both slopes and gullies, no differences in health and vigour were found by the end of the study. Overall plant species number on the site increased during the study. Graminoid species densities increased, while those of forbs, shrub and tree species declined in the transplanted vegetation islands. Non-dormant islands had greater graminoid density than dormant islands, where Poa pratensis was the dominant species in the islands. Bioengineering with vegetation islands and terraces can assist in trapping runoff and sediment, and accelerate establishment of a diversity of plant species and groups relative to traditional revegetation methods. • Eroded lakeshore slopes can be reclaimed with terraces and small vegetation islands. • Non-dormant and dormant transplanted islands survived on terraced lakeshore slopes. • Vegetation mortality was significantly lower with non-dormant than dormant islands. • Non-dormant islands had greater graminoid density than dormant islands. • Vegetation islands can trap runoff and sediment, and accelerate plant establishment.
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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) | 0.001 | 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".