Production and ecosystem structure in cold‐core vs. warm‐core eddies: Implications for the zooplankton isoscape and rock lobster larvae
Bibliographic record
Abstract
Abstract Anticyclonic (warm‐core) mesoscale eddies (WCEs) in the Eastern Indian Ocean carry higher surface chlorophyll signatures than cyclonic (cold‐core) eddies (CCEs). Paradoxically, WCEs host rock lobster larvae (phyllosomas) with lower lipid stores and protein reserves than phyllosomas in CCEs, suggesting a poorer nutritional status. We assess primary productivity and zooplankton isotopic data from eight eddies across four research voyages (2003–2011) to determine how this contradiction might occur. We find that WCEs and CCEs are equally productive per unit chlorophyll a, but depth‐integrated primary production (PP) is greater in eddies with shallower mixed layers (MLs), especially in CCEs. MLs tend to be shallower in CCEs than in WCEs because the pycnocline is closer to the surface. This, in combination with stronger stratification in CCE euphotic zones than those of WCEs, supports greater flagellate and dinoflagellate populations in CCEs. These phytoplankton provide high‐quality nutrition for zooplankton, which feed on average ~ 0.6 trophic level lower in CCEs with the shallowest MLs, accumulating high lipid stores. Conversely, WCEs have, on average, ~ 70 m deeper MLs than CCEs, and host a phytoplankton community with more diatoms. Diatoms provide lower quality food for zooplankton, and zooplankton lipid stores in WCEs decline with trophic level, and possibly, with time after initial (or seasonal) nutrient injection. As a result, phyllosomas in CCEs have higher energy and lipid content than those in warm‐core eddies. The resolution of the paradox, therefore, is that the higher surface chlorophyll signatures of WCEs are not representative of the nutritional value of the prey field of the phyllosoma. We also conclude that interannual variations of mixed layer depth occur at a regional scale, controlling PP.
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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 | 0.001 | 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) | 0.001 | 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".