Factors controlling plankton productivity, particulate matter stoichiometry, and export fluxin the coastal upwelling system off Peru
Bibliographic record
Abstract
Abstract. Eastern boundary upwelling systems (EBUS) are among the most productive marine ecosystems on Earth. The high productivity in surface waters is facilitated by upwelling of nutrient-rich deep waters, with high light availability enabling fast phytoplankton growth and nutrient utilization. However, there are numerous biotic and abiotic factors modifying productivity and biogeochemical processes. Determining these factors is important because EBUS are considered hotspots of climate change, and reliable predictions on their future functioning requires understanding of the mechanisms driving biogeochemical cycles therein. In this study, we used in situ mesocosms to obtain mechanistic understanding of processes controlling productivity, organic matter export, and particulate matter stoichiometry in the coastal Peruvian upwelling system. Therefore, eight mesocosm units with a volume of ~50 m3 were deployed for 50 days ~6 km off Callao during austral summer 2017, coinciding with a coastal El Niño event. To compare how upwelling of different water bodies influences plankton succession patterns, we collected two subsurface waters at different locations in the regional oxygen minimum zone (OMZ) and injected these into four replicate mesocosms, respectively (mixing ratio ≈ 1.5:1 mesocosm: OMZ water). The differences in nutrient concentrations between the collected water bodies were relatively small, and therefore we do not consider treatment differences in the present paper. The phytoplankton communities were initially dominated by diatoms but shifted towards a pronounced dominance of the mixotrophic harmful dinoflagellate (Akashiwo sanguinea) when inorganic nitrogen was exhausted in surface layers. The community shift resulted in a major short-term increase in productivity during A. sanguinea growth which left a pronounced imprint on organic matter C:N:P stoichiometry. However, C, N, and P export fluxes were not affected by this ecological regime shift because A. sanguinea persisted in the water column and did not sink out during the experiment. Accordingly, ongoing export fluxes during the study were maintained mainly by a remaining “background” plankton community. Overall, biogeochemical pools and fluxes were surprisingly constant in between the ecological regime shifts. We explain this constancy by light limitation through self-shading by phytoplankton and inorganic nitrogen limitation which constrained phytoplankton growth. Thus, gain and loss processes seemed to be relatively well balanced and there was little opportunity for blooms, which represents an event where the system becomes unbalanced. The mesocosm study revealed key links between ecological and biogeochemical processes for one of the economically most important regions in the oceans.
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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 | 0.001 |
| 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) | 0.001 | 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".