Massive circumpolar biomass of Southern Ocean zooplankton: Implications for food web structure, carbon export, and marine spatial planning
Bibliographic record
Abstract
Abstract With rapid, sector‐specific climatic changes impacting the Southern Ocean, we need circumpolar‐scale biomass data of its plankton taxa to improve food web models, blue carbon budgets and resource management. Here, we provide a new dataset on mesozooplankton biomass with 2909 records spanning the last 90 yr, and describe, in comparable carbon units, their circumpolar distribution alongside those of phytoplankton, Antarctic krill, and salps. With our datasets, we estimate total summer carbon biomasses for phytoplankton (36 MT), mesozooplankton (67 MT), krill (30 MT), and salps (1.7 MT). The mesozooplankton value is much higher than previously reported and, added to that of krill and salps, points to an enormous overall biomass of zooplankton in the Southern Ocean. This means that the pyramids of biomass are often inverted, with higher biomass of zooplankton than of phytoplankton. Such high biomasses suggest key roles of grazers in nutrient cycling and we estimate an export of ~ 50 Mt C yr−1, solely from mortality of overwintering zooplankton that typically reside at depth. Deep lipid respiration (the lipid pump), for example, would increase this export even further. While inverted biomass pyramids prevailed at mid latitudes (50°–70°S), the balance of taxa differed regionally: for example, with biomass dominance by phytoplankton (highest latitudes and Pacific sector), mesozooplankton (Kerguelen Plateau), krill (north and east Scotia Sea), and salps (Crozet area). In light of contrasting climate change impacts between these sectors, we provide data that will underpin biogeochemical and food web models, blue carbon budgets, and the planning of marine protected areas.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".