Diporeia site preference in Lake Superior: Food or physical factors?
Bibliographic record
Abstract
Vital to the Lake Superior food web, the amphipod Diporeia remains the dominant macroinvertebrate in Lake Superior despite drastic population declines throughout the rest of the Laurentian Great Lakes. Diporeia is most abundant in the slope region of the lake at water depths between 30 and 125 m. It has been hypothesized that this depth range is preferred because of elevated primary production and deposition within this zone. This hypothesis of food driving habitat preference has not been directly tested. Here we used 120-hour preference-avoidance trials to record Diporeia choice of sediments from different water depths, seasons, and other treatments. Most preferences were weak to absent; however, Diporeia strongly preferred sediment from 30- and 60-m water depths over deeper or shallower sites. Contrary to the hypothesis about food driving habitat choice, chemical characteristics did not explain this strong preference. Grain size variation was the only measured variable that was consistent between the sites preferred by Diporeia and different from unpreferred sites. Both the 30- and 60-meter sites contained predominantly medium silt but had a wider range in grain sizes. These results indicate that physical habitat characteristics may have a stronger bearing on Diporeia habitat preference than food availability and may account for their distribution in the lake. The results also may imply that the role of dreissenid mussels as ecosystem engineers altering sediment physical characteristics may be important where they are abundant.
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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 | 0.000 | 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) | 0.002 | 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".