Effects of algal food quality on sexual reproduction of <i><scp>D</scp>aphnia magna</i>
Bibliographic record
Abstract
The objective of our study was to investigate sexual reproduction of Daphnia magna associated with mating behaviors and hatching rates, according to different algal food sources. Since a diatom is known to contain more abundant long-chain poly unsaturated fatty acids (PUFAs), we hypothesized that the diatom-consuming D. magna would exhibit more successful reproduction rates. Upon the hypothesis, we designed three experiments using two algal species, a green alga (Chlorella vulgaris) and a diatom (Stephanodiscus hantzschii). From the results, we found that the mating frequency and copulation duration increased in the treatment with S. hantzschii, resulting in a significant increase of hatching rates of resting eggs. In the other two repetitive mating strategies (e.g., one female vs. multiple males, and one male vs. multiple females), we found that the hatching rates of resting eggs were greater in the S. hantzschii treatment. In addition to the mating strategy, male body size significantly increased in the diatom treatment, hence average diameter of penis was also statistically different among the treatments (greater diameter in the S. hantzschii treatment). To examine the effect of algal food quality, we estimated quantity of fatty acids in the two algal species. Our result showed that S. hantzschii had a higher proportion of long-chain PUFAs than C. vulgaris. Furthermore, a stable isotope analysis revealed that carbon and nitrogen originated from S. hantzschii were more assimilated to D. magna. In summary, our study manifested that diatom consumption of D. magna leads to more successful sexual reproduction. We then discussed how the diatom consumption of zooplankton influences food web dynamics in a freshwater ecosystem.
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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 | 0.000 | 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".