The effects of dissolved organic carbon on pathways of energy flow, resource availability, and consumer biomass in nutrient-poor boreal lakes
Bibliographic record
Abstract
Over the past few decades, terrestrially derived dissolved organic carbon (DOC) has been recognized as a fundamental driver of food web productivity in nutrient poor lakes. The mechanisms that underlie these effects remain poorly understood, particularly for higher trophic levels including zooplankton, benthic invertebrates, and fish. In a survey of eight lakes in northwestern Ontario, I determined consumer biomass and used stable isotopes of carbon, nitrogen, and hydrogen to investigate relationships between DOC and pathways of energy flow, resource and habitat availability, and consumer biomass. Using Bayesian stable isotope mixing models, I found that hypolimnetic phytoplankton were an important resource for zooplankton in low-DOC lakes. With increased DOC concentrations, light attenuation increased and chlorophyll a concentrations below the thermocline were reduced relative to epilimnetic concentrations. At higher DOC concentrations, zooplankton acquired proportionately more energy from low quality terrestrial sources. Zooplankton biomass also declined with increasing utilization of terrestrial sources (allochthony), suggesting that terrestrial organic matter suppresses zooplankton productivity through simultaneous limitations on habitat and resource availability and quality. Based on biomass, the dominant fish species across my study lakes was White Sucker (Catostomus commersonnii). Bayesian mixing models indicated that allochthony by White Suckers increased with DOC and that greater allochthony was related to lower White Sucker biomass measured as catch-per-unit-effort (bCPUE). Both White Sucker bCPUE and chironomid biomass were positively related to mean light irradiance, with the highest biomasses of fish and chironomids occurring in lakes with a higher proportion of their volume in the photic zone. White Sucker bCPUE was strongly and positively correlated with chironomid biomass, suggesting that DOC-mediated resource limitation may influence fish productivity via reduced prey availability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".