Quantifying flood-pulse dynamics and associated wetland habitats for juvenile salmon in a large free-flowing river
Bibliographic record
Abstract
Floodplain wetlands are productive rearing habitats for juvenile salmon in large river systems, yet there can be considerable spatiotemporal variation in accessibility of these habitats. We examined flood inundation and wetland connectivity across a broad range of return periods (0.1–500 years) in the free-flowing North Thompson River, British Columbia, and overlaid coho salmon ( Oncorhynchus kisutch ) abundance data to assess habitat accessibility. The activation of floodplain wetlands depends on frequent, small flood events leading to dynamic connectivity and inundation patterns. Results showed that 80 % of wetlands become connected during flood events with return periods shorter than one year, underscoring the importance of frequent, small flood pulses for annually available rearing habitat. However, the distribution of wetlands relative to upstream coho salmon spawning populations and their juveniles reveal spatial variation in patterns of accessible habitat for juvenile rearing. In the upper watershed, abundant wetlands connect with even the smallest floods yet there are few spawners documented upstream. Mid-watershed sections have wetlands that require larger, less frequent floods to become fully accessible and are where most of fish spawn. In contrast, lower reaches have moderate spawner abundances and are without wetlands. This spatiotemporal variation in accessible wetlands for juvenile coho salmon will drive variation in the contribution of floodplain wetlands to coho salmon production. Our findings highlight that maintaining or restoring natural flow regimes, and ensuring alignment between floodplain wetland location and population distribution, are crucial for maintaining and restoring salmon productivity, particularly as climate change intensifies flow variability in large river basins. • We examine how flood dynamics effect floodplain wetlands used by juvenile salmon. • We developed a flood inundation model that includes sub annual flood frequencies. • Sub annual flood events activated the majority of floodplain wetland habitat. • Juvenile coho salmon's access to wetlands varied with location and flood return period. • Linking distributions of fish and wetlands can identify locations for protection and restoration.
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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 | 0.001 | 0.001 |
| 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".