The role of metabolism in modulating CO<sub>2</sub> fluxes in boreal lakes
Bibliographic record
Abstract
Abstract Lake CO2 emissions are increasingly recognized as an important component of the global CO2 cycle, yet the origin of these emissions is not clear, as specific contributions from metabolism and in‐lake cycling, versus external inputs, are not well defined. To assess the coupling of lake metabolism with CO2 concentrations and fluxes, we estimated steady state ratios of gross primary production to respiration (GPP:R) and rates of net ecosystem production (NEP = GPP‐R) from surface water O2 dynamics (concentration and stable isotopes) in 187 boreal lakes spanning long environmental gradients. Our findings suggest that internal metabolism plays a dominant role in regulating CO2 fluxes in most lakes, but this pattern only emerges when examined at a resolution that accounts for the vastly differing relationships between lake metabolism and CO2 fluxes. Fluxes of CO2 exceeded those from NEP in over half the lakes, but unexpectedly, these effects were most common and typically largest in a subset (~30% of total) of net autotrophic lakes that nevertheless emitted CO2. Equally surprising, we found no environmental characteristics that distinguished this category from the more common net heterotrophic, CO2 outgassing lakes. Excess CO2 fluxes relative to NEP were best predicted by catchment structure and hydrologic properties, and we infer from a combination of methods that both catchment inputs and internal anaerobic processes may have contributed this excess CO2. Together, our findings show that the link between lake metabolism and CO2 fluxes is often strong but can vary widely across the boreal biome, having important implications for catchment‐wide C budgets.
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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 | 0.001 | 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 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".