Seasonal shifts between autochthonous and allochthonous carbon contributions to zooplankton diets in a subarctic lake
Bibliographic record
Abstract
We addressed the extent to which autochthonous and allochthonous carbon sources contribute to zooplankton diet throughout the year in oligotrophic subarctic Lake Saanajärvi. Optical measures of dissolved organic matter (DOM) indicated high water discharge and associated terrestrial DOM during winter and low inputs in summer. Bulk particulate organic matter (POM) showed δ13C values consistent with allochthonous inputs of DOM. The most positive POM δ13C values (−27‰) occurred during winter, when heterotrophic bacteria and nanoflagellates peaked in abundance; the isotopically lighter autotrophic phytoplankton shifted the POM δ13C to −29‰ in summer. The δ13C values of zooplankton were up to 4‰ more negative than those of POM, most likely because detritus and other nonliving material with higher δ13C values comprised 45–90% of POM. The δ13C of the cladoceran Daphnia umbra mirrored the trend of POM δ13C, indicating a dietary shift from heavy dependence on autochthonous carbon in summer to allochthonous or heterotrophic food in winter. The δ13C of the most abundant zooplankton in Lake Saanajärvi, Eudiaptomus graciloides and Cyclops abyssorum, remained low and constant in winter, suggestive of little or no food intake during the 8 months of winter. There are significant differences in the zooplankton utilization of nonphytoplankton carbon in different seasons and among species. Although autochthonous carbon seemed to be mainly responsible for the growth of zooplankton, the ability to utilize allochthonous carbon‐fueled microorganisms explains the survival of Daphnia through winter in northern lakes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".