The wash zone and habitat use among three benthic fish species in stratified lakes
Bibliographic record
Abstract
Abstract Mixing processes in lakes are important in determining sedimentation zones and in setting the so‐called “wash zone”, the area of lake bottom in contact with an oscillating thermocline during wind‐driven internal seiche events. The wash zone also aligns with a sharp change in sediment roughness and hardness. Taken together, these rapid changes in temperature and sediment indicate that the wash zone is a distinctive ecotone in stratified lakes. Depth stratified randomised netting was used to develop count‐based habitat use models for three common benthic fish species as a function of depth or temperature covariates. Using data from two lakes with quite different wash zone depths, we show the wash zone to describe fish habitat for two of three benthic fish species by utilising the top 50% of estimated fish abundance as an indicator of habitat use. White sucker ( Catostomus commersoni ) habitat use was within the boundaries of the wash zone. Lake whitefish ( Coregonus clupeaformis ) habitat was adjacent and within the wash zone. Longnose sucker ( C. catostomus ) habitat use was in the deep areas of lakes dominated by sediment focusing and did not overlap white sucker. Lake whitefish habitat use overlapped both catostomids, but peak abundance of both lake whitefish and white sucker overlapped pointing to potential interactions between these species. Smaller lakes have less vigorous mixing processes and a narrower wash zone, so with a decline in lake size the likely area of the wash zone as habitat for benthic feeding fish would become smaller.
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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 | 0.001 |
| 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 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".