Seasonal changes in microbial community structure and activity imply winter production is linked to summer hypoxia in a large lake
Bibliographic record
Abstract
Carbon and nutrient cycles in large temperate lakes such as Lake Erie are primarily driven by phototrophic and heterotrophic microorganisms, although our understanding of these is often constrained to late spring through summer due to logistical constraints. During periods of > 90% ice cover in February of 2008, 2009, and 2010, we collected samples from an icebreaker for an examination of bacterial production as well as microbial community structure. In comparison with summer months (August 2002 and 2010), we tested hypotheses concerning seasonal changes in microbial community diversity and production. Bacterial production estimates were c. 2 orders of magnitude higher (volume normalized) in summer relative to winter. Our observations further demonstrate that the microbial community, including single-celled phototrophs, varied in composition between August and February. Sediment traps deployed and collected over a 3 year period (2008-2011) confirmed that carbon export was ongoing and not limiting winter production. The results support the notion that active primary producers in winter months export carbon to the sediments that is not consumed until the warmer seasons. The establishment of this linkage is a critical observation in efforts to understand the extent and severity of annual summertime formations of a zone of regional hypoxia in Lake Erie.
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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) | 0.001 | 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".