Fatty acid composition as a function of latitude in barnacle cyprid larvae
Bibliographic record
Abstract
Abstract Broadly distributed species need to perform well in a range of environmental conditions, but knowledge of how wide‐ranging marine larvae perform along latitudinal gradients remains limited. The fatty acid composition of larvae is important for their physiological responses to changing conditions. Here, we investigated the fatty acid composition of the last, non‐feeding stage of barnacle larvae (cyprids) using an integrative (larvae–environment) and comparative (latitudinal) approach. We measured fatty acids in the pelagic particulate matter and cyprids from Chthamalus bisinuatus, Chthamalus proteus, and Semibalanus balanoides from tropical to polar (Arctic) latitudes to identify potential food sources during the feeding larval stages (nauplius) that precede the cyprids and to ascertain larval capacity to integrate neutral (energetic) and polar (structural) fatty acids. We demonstrate that particulate matter in tropical waters mainly consisted of low‐quality saturated fatty acids derived from detrital pathways, while particulate matter from polar waters was rich in polyunsaturated fatty acids originating from living microalgae. Across the studied regions, neutral fatty acids were assimilated from various food sources including diatoms, dinoflagellates, detritus, and microeukaryotes. Cyprids consistently retained higher essential fatty acid levels than the relative share in the particulate matter. Particularly, the essential docosahexaenoic acid (22:6ω3), which was scarce in the particulate matter, was highly retained across all species but highest for the tropical cyprids. We argue that this latitudinal pattern in fatty acid retention is related to periods of reduced nutrient intake, increased energetic and/or synthetic requirements, and responses to physical large‐scale differences in environmental conditions.
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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 | 0.000 | 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".