Regional variability of resource use, trophic position and habitat coupling within Lake Superior
Bibliographic record
Abstract
Food web characterizations of large lakes have rarely considered spatial variation in resource use or trophic connections among species. This is also true of Lake Superior, the world’s second largest freshwater lake. While instances of habitat coupling in Lake Superior have been documented, the extent to which coupling or resource specialization in this system varies spatially, particularly within a species, remains unknown. To address this, stable isotopes of common fish species and prey were collected and analyzed along a depth gradient at four geographically and bathymetrically distinct regions of Lake Superior; 1099 fish and 60 composite invertebrate samples (separately for zooplankton and benthos) were collected from both deeper regions (Keweenaw and Western Arm) and shallower regions (Nipigon Bay and Whitefish Bay). Benthic and pelagic species of fish and invertebrates were collected to characterize different energy pathways. Within regions and taxa, benthic reliance and trophic position differences across depth strata were large and comparable to those previously observed among species lake wide. Across regions, large within-taxa differences in resource use patterns and trophic position existed at similar depth strata, as well as among taxa. Generally, there was a high reliance on pelagic resources across all fish species with greater benthic resource use observed at medium and deep strata. As expected, higher trophic organisms tended to have greater evidence of benthic-pelagic coupling. Our findings reinforce the need to consider regional variation in resource use and trophic position in large lake systems over broad approaches that can overgeneralize patterns of energy flow.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".