Essential fatty acid concentrations of different seston sizes and zooplankton: a field study of monomictic coastal lakes
Bibliographic record
Abstract
Plankton particle size is a central issue for aquatic ecologists. In this field study, we examined essential fatty acids (EFAs) in different plankton particle sizes and obtained initial estimates of how EFA concentrations, and thus high dietary lipid quality for consumers, vary with seston size. We measured EFA concentrations in three seston size classes (i.e. micro = 0.7–35 μm; meso = 35–64 μm and macroseston = 64–100 μm) and in cladocerans and calanoid copepods of monomictic, coastal lakes. Algal pigment analysis identified a mixture of Chlorophyta, Cryptophyta, diatoms and Cyanophyta in all seston size classes. Total EFA concentrations did not vary with increasing seston size. There was no difference in linoleic (LIN), eicosapentaenoic (EPA) and docosahexaenoic (DHA) acid concentrations among the three seston size classes; however, α-linolenic (ALA) and arachidonic (ARA) acid concentrations were significantly higher in microseston. For herbivorous zooplankton, concentrations of LIN, ALA and EPA did not differ significantly between cladocerans and calanoid copepods; however, ARA concentrations were significantly higher in cladocerans and DHA concentrations were significantly higher in calanoid copepods. Our results indicate that microseston represents the most nutritious dietary component, per unit biomass, with respect to ALA and ARA and that seston size alone does not predict EFA concentrations, i.e. dietary access to larger seston particle sizes is not necessarily associated with access to particles with higher EFA concentrations.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".