The fate of salp blooms: decomposition and sinking of salp carcasses
Bibliographic record
Abstract
Abstract Gelatinous zooplankton (GZ) biomass is an important, yet often overlooked, vector of the particulate organic matter downward export and a nutritional prey source for the mesopelagic and benthic communities. To better quantify the potential impact of their blooms on biogeochemistry and food webs, we performed decomposition and sinking experiments under two different temperature regimes, 6 and 12 °C using 260 Salpa aspera, sampled in the Northeast Pacific (48.39°-50.40°N, 126.40°-145.00°W) during May 2021. Salp decay was exponential and occurred ~1.5 times faster under warmer conditions. Comparison of the published GZ decay rates supported their strong temperature dependence (Q10 = 3.46) and revealed that S. aspera decayed slower than most GZ taxa. Carcass sinking rates were higher than previously reported for this species and slowed after a prolonged decay. Biochemical (proteins, carbohydrates, lipids) and elemental (C: carbon, N: nitrogen) compositions were determined for salps at various decomposition stages. The high water content (~97%) and low organic content (27.8 ± 7.1 % dry weight) was typical of other thaliaceans. The high C:N ratio (6.61 ± 1.14) of S. aspera, compared to many thaliaceans, suggested that their carcasses are valuable sources of carbon beyond the euphotic zone.
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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".