Survival & growth of sandbar willow, Salix interior, in bioengineering projects, and the implications for use in erosion control in Manitoba
Bibliographic record
Abstract
Willow bioengineering is an alternative erosion management technique that includes the use of living and inert willow material. It is successfully used across North America, Europe and Asia but, due to lack of public awareness of the technique or concerns about its effectiveness, it is currently used only occasionally in southern Manitoba. To provide insight into possible biological limitations upon the use of willows to prevent erosion a combination of field experiments and observational studies of new bioengineering sites was carried out across southern Manitoba. \nThe results indicate that first year willow cutting survival is likely to be below 50% unless planted within 100cm of fall low water level. Using taller cuttings may improve survival as they develop greater numbers of shoots early in the growing season, but taller cuttings have a greater chance of being cut down or even pulled from the ground by beaver. Flooding had a negative effect of shoot numbers during the first year after planting, although it did not impact survival. In 2012 flood levels were lower at the majority of sites than the long term mean; more extensive flooding may have a more negative effect upon the cuttings. Maximum shoot length was reduced by high water levels, but was improved by cutting proximity to low water later in the summer. More research is needed to better understand the effect of high water levels on long term survival. \nCombining live willow with erosion blanket helps reduced substrate loss during establishment and also prevented willow bundles from being removed by beaver reducing the potential of project failure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".