Linking geomorphic change due to floods to spatial hydraulic habitat dynamics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Large flood events have the capacity to induce geomorphic restructuring that can impact riverine ecosystems. However, the detailed morphodynamics associated with infrequent, high‐magnitude floods are variable and difficult to capture, and more research is needed into potential relationships between geomorphic change, flow organization, and aquatic habitat dynamics. In this study, we focus on the reach‐scale response of a gravel bed river to a large flood, employing a combined remote sensing, field measurement, and numerical modelling approach to measure and interpret conditions bracketing the flood. Documented geomorphic turnover was extensive, reworking low‐flow channel patterns and causing widespread bank erosion and sediment deposition. This resulted in a shift to wide, shallow flow conditions in the post‐flood morphology and a loss of hydraulic diversity, particularly in ecologically important pool and riffle units identified using a fuzzy statistical classification method. These impacts are most evident at low flows; higher discharges display relatively similar hydraulic conditions despite geomorphic change. Smaller‐scale adjustments in the year following the flood appear to be driving the reintroduction of hydraulic diversity, which is interpreted as beneficial for in‐stream brown trout. Results from this study highlight the utility of applying flexible and objective remote sensing and modelling methods to measure fluvial change and provide a real‐world example that can inform broader theoretical understanding of large flood ecohydrology.
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.
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) | 0.005 | 0.011 |
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 it