Global estimate of mesopelagic mesozooplankton biomass
Bibliographic record
Abstract
The global standing stock of mesozooplankton in the mesopelagic zone was assessed using estimates of particulate organic carbon (POC) and net primary productivity (NPP). These estimates were compared to published data to establish a relationship between epipelagic and mesopelagic zooplankton biomasses. The relationship between species diversity and biomass in the mesopelagic zone was examined using scatterplots and maps with 2-dimenssional scales. The results showed that NPP and POC were important predictors of mesopelagic mesozooplankton biomass (MMB). Linear models incorporating these factors were statistically significant, explaining a moderate to high proportion of variance in the predicted MMB. The spatial patterns of MMB showed higher values in some regions of the northern hemisphere, along the west coasts of continents, and in the equatorial and 50°S bands. This study provides the first estimates of MMB using two definitions of the mesopelagic zone: standard (200-1000 m depths) and variable depth. Global MMB was estimated between 0.20 and 0.91 PgC, depending on the method. High biomass values were common in regions with intermediate rarity values and high species richness coupled with high POC stocks. Surface and mesopelagic biomass spatial patterns were consistent, and the epipelagic/mesopelagic biomass ratio depended on mesopelagic zone depth, suggesting a higher MMB than previously observed.
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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 | 0.002 | 0.001 |
| 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".