Dissolved organic carbon affects the occurrence of deep chlorophyll peaks and zooplankton resource use and biomass
Bibliographic record
Abstract
Abstract Concentrations of dissolved organic carbon (DOC) are increasing in many parts of the world and vary considerably among lakes. As a result, it is important to understand the effects of DOC on zooplankton, which are a key component of freshwater food webs. Deep chlorophyll maxima (DCMs) also are common in many lakes and numerous studies suggest that they may be an important resource for zooplankton. In a survey of eight boreal lakes spanning a gradient of DOC (3.5–9.2 mg/L), we assessed variations in the occurrence of DCMs, zooplankton biomass and their use of basal resources using stable isotopes of carbon (C), nitrogen (N) and hydrogen (H). DCMs occurred only in lakes with lower DOC concentrations and Bayesian stable isotope mixing models indicated that they contributed between 22% and 72% of the assimilated diet of zooplankton. Food quality as indicated by C:P and chlorophyll a : C ratios increased with depth and in DCMs. The proportion of C ultimately derived by zooplankton from terrestrial sources increased from 6% to 27% with DOC. Zooplankton biomass among lakes declined with increasing DOC concentrations, the absence of DCMs and with increasing allochthony. Our results suggest that increasing inputs of DOC may suppress zooplankton in many lakes by affecting both resource quality and the availability of metalimnetic phytoplankton resources. Because zooplankton occupy a central position in freshwater food webs, declines in their biomass may further affect phytoplankton dynamics and fish productivity.
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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 | 0.001 |
| Scholarly communication | 0.000 | 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 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".