Evaluation of floodplain restoration projects in the interior Columbia River basin using a combination of remote sensing and field data
Bibliographic record
Abstract
Floodplain habitat restoration has become a common component of river restoration throughout the Pacific Northwest and is critical to the recovery of Pacific salmon ( Oncorhynchus spp.) and steelhead ( Oncorhynchus mykiss), yet little information exists on the physical or biological response to these habitat restoration efforts. Using an extensive post-treatment design and a combination of remote sensing and field surveys, we sampled 17 floodplain projects designed to benefit anadromous fish in the Columbia River Basin. We detected significant increases in side channel metrics (area, length, and the ratio of bankfull side-channel to main channel length), sinuosity, pool frequency, large wood, and the morphological quality index. On average, juvenile Chinook ( Oncorhynchus tshawytsch), coho ( Oncorhynchus kisutch), steelhead, and salmonid combined abundance was 1.17, 4.62, 1.62, and 1.65 times higher, respectively, in treatment reaches compared to control reaches, though these increases were only significant for steelhead and all salmonids combined. Our study demonstrated that a combination of remote sensing and field data can be used to monitor floodplain and instream habitat and detect fish response to floodplain restoration projects.
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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 | 0.002 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".