A hypothesis for the assessment of the importance of microbial food web linkages in nearshore and offshore habitats of the Laurentian Great Lakes
Bibliographic record
Abstract
Our work in the Laurentian Great Lakes of North America indicates that significant fluxes of carbon and phosphorus can pass through the microbial food webs (MFW) of these lakes. Here we present a synthesis of our recent investigations conducted largely along a trophic axis from the heavily eutrophic coastal Sandusky Bay to offshore communities near the international boundary in the central basin of Lake Erie. We find that the significance of the MFW in transporting C and P to higher trophic levels differs along a trophic gradient. In relatively eutrophic nearshore communities, most C and P are fixed into phytoplankton, transport of materials is largely dependent on grazing by cladocerans, and transport through the MFW is relatively insignificant. In contrast, in relatively oligotrophic offshore communities bacterial biomass often exceeds phytoplankton biomass, the majority of P is fixed into bacteria, bacterivorous grazers (e.g. rotifers and protozoa) dominate, copepods are the dominant microcrustacean, and transport of C and P through the MFW represents a major pathway. We suggest that the management of large-lake ecosystems is largely based on relatively eutrophic “nearshore” views of the base of the food web and needs to be modified to include considerations of the MFW in the more oligotrophic offshore regions of these lakes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".