Metabolism is of minor importance for under-ice DIC dynamics in hardwater lakes
Bibliographic record
Abstract
Our knowledge of inland lakes is largely based on samples collected during the ice-free “growing” season, even though lakes in continental climates may be ice-covered for several months during winter. Studies that have characterized under-ice conditions were predominantly conducted in dilute boreal and temperate lakes, while information on hardwater lakes (>120 mg L−1 CaCO3) is still limited. Yet, hardwater lakes represent ∼50% of standing waters on earth, contain large quantities of dissolved organic and inorganic carbon (DOC, DIC) and are considered hotspots of carbon processing. Here, we present results from a 9-lake survey of Canadian hardwater lakes, conducted over 3 consecutive winters, with preceding summer conditions characterized to contrast seasonal differences. Despite their 10-fold differences in morphometry and water chemistry, hardwater lakes showed similar trajectories from fall to winter to spring: (1) physical freeze-out increased salinity and DOC; (2) metabolic activity controlled algal biomass, dissolved oxygen (DO), pH, and soluble reactive phosphorus (SRP); and (3) DIC dynamics were influenced predominantly by nonmetabolic factors such as hydrology (groundwater) and water chemistry (CaCO3 dissolution), relative to metabolic factors (aerobic/anaerobic respiration). While temporal patterns of chlorophyll a, DO, SRP, and pH were comparable to boreal and temperate lakes, DIC dynamics were starkly different. Hence, we propose that hardwater lakes should be considered separately, particularly pertaining to their role in the global carbon cycle.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".