Effects of Native Plant Species, Mycorrhizal Inoculum, and Mulch on Restoration of Reservoir Sediment Following Dam Removal, Elwha River, Olympic Peninsula, Washington
Bibliographic record
Abstract
As dams across the country continue to age, successful restoration of dewatered reservoirs remains a critical factor in decisions regarding dam removal. Freshly exposed reservoir sediment may not support rapid reestablishment of native plant species due to poor fertility or absence of arbuscular mycorrhizal fungi propagules. This field study evaluated treatment effects involving combinations of native plants, mycorrhizal inoculum, and mulch on restoration of dewatered reservoir sediment over 20 months. Most plants, even those uninoculated, became mycorrhizal. In all treatments, sediment pH decreased, as did nitrogen and organic matter, compared to original reservoir sediment, while aggregate stability doubled from original anaerobic sediment. Revegetated plots with mulch had significantly greater vegetation cover and more native volunteer species compared to plots without mulch. The planted mulch treatment also decreased plot runoff tenfold, reducing erosion to the same degree. Indicators suggest that the primary benefit of mulch resulted in increased moisture retention making the planted mulch treatment most successful for restoration of reservoir sediment due to extensive native plant growth, improved soil characteristics, and reduced runoff and erosion compared to nonmulched plots. While results from this plot‐scale study suggest commercial mycorrhizal inoculum is unnecessary since natural inoculum sources sufficiently colonized plants, reservoir‐scale restoration may require creation of additional source areas to encourage rapid reestablishment of native plants and mycorrhizal fungi.
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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".