Long-term changes in river–floodplain dynamics: implications for salmonid habitat in the Interior Columbia Basin, USA
Bibliographic record
Abstract
Rivers and their associated floodplains are among the world's most highly altered ecosystems, resulting in billions of dollars in restoration expenditures. Successful restoration of these systems requires information at multiple spatial scales (from localized reaches to broader-scale watersheds), as well as information spanning long time frames. Here, we develop a suite of historical landscape indicators of riverine status, primarily from the perspective of salmonid management, using a case study in the Interior Columbia Basin, Washington, USA. We use a combination of historical and modern aerial photography to quantify changes in land cover and reach type, as well as potential fish habitat within channel and off-channel floodplain areas. As of 1949, 55% of the Wenatchee River floodplain had been converted to agriculture. By 2006, 62% had been modified by anthropogenic development, of which 20% was due to urban expansion. The historical percentage of agricultural land in the watershed and the contemporary percentage of urban area surpass thresholds in land cover associated with deleterious impacts on river systems. In addition, the abundance of reach types associated with the highest quality salmonid habitat (island braided and meandering reaches) has declined due to conversion to straight reach types. The area occupied by fish habitats associated with channel migration (slow/stagnant channels and dry channels) has declined approximately 25-30%. Along highly modified rivers, these habitats have also become increasingly fragmented. Caveats related to visual quality and seasonal timing of historical photographs were important considerations in the interpretation of changes witnessed for headwater island braided systems, as well as for floodplain ponds. Development of rigorous, long-term, multi-scale monitoring techniques is necessary to guide the management and restoration of river-floodplain systems for the diversity of ecosystem services they provide.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".