Saving for the future: Pre‐winter uptake of algal lipids supports copepod egg production in spring
Bibliographic record
Abstract
Abstract The freshwater copepod Leptodiaptomus minutus in boreal lakes has its main annual reproductive period at the end of winter. This follows months of ice cover and limited food production, yet the females transfer large quantities of algal‐derived carotenoids (predominantly astaxanthin) and fatty acids (FAs) to their eggs at this time, thereby providing the offspring with antioxidant protection and energy reserves. We hypothesised that this winter transfer of carotenoid pigments and FAs is based on accumulated reserves that are reinvested into reproduction (i.e. capital breeding). This strategy would allow the animals to produce offspring in time for the nauplii to feed on the spring phytoplankton bloom, thus gaining a competitive advantage. To test this hypothesis, we evaluated the seasonal production of precursor carotenoids and essential FAs by the phytoplankton, the amounts of these compounds required for egg production and the transfer rates from phytoplankton to copepod eggs. Pelagic primary production vastly outweighed the demand for copepod eggs during summer–autumn. However, the major peak of egg production in spring could not be sustained by the low phytoplankton productivity during winter, indicating reliance on previously accumulated reserves as hypothesised. High rates of lipid reserve accumulation in L. minutus in late autumn and early winter accounted for up to 128% (astaxanthin precursors) and 70% (FAs) of the daily production by the phytoplankton, further indicating the importance of pre‐winter primary production for reserve building in this copepod. During winter, the sum of carotenoid pigments as well as the sum of essential FAs stocked in copepods exceeded the concentrations in the seston. Consequently, adult copepods act as a lipid storage pool linking the biosynthesis of carotenoids and FAs by primary producers in autumn to the production of copepod eggs at the end of winter.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".