Species‐specific diatom dynamics shape their vertical distribution and export during bloom decline
Bibliographic record
Abstract
Abstract The Southern Ocean is a critical region for global biogeochemical cycles, particularly for carbon dioxide uptake and organic carbon export, partly driven by extensive phytoplankton blooms. In naturally iron‐fertilized regions of this otherwise iron‐limited ocean, these blooms are primarily driven by diatoms. Variability in bloom occurrences on spatiotemporal scales makes it challenging to track and understand a bloom's decline and associated carbon export. Moreover, species‐specific processes may be critical yet are typically not well resolved. Here, we use state‐of‐the‐art in situ imaging, producing high‐resolution vertical profiles of phytoplankton and particles, combined with water sampling, to resolve the decline of a Southern Ocean spring bloom. We observed significant vertical and temporal changes in particle and diatom composition and abundance. Fragilariopsis kerguelensis showed deepening abundance peaks correlating with silicic acid gradients and water density changes, while their chain lengths decreased likely due to nutrient stress and physical breakage. High downward fluxes of F. kerguelensis and concentrations below the mixed later suggest they were a key contributor to carbon export and transfer. Conversely, Eucampia antarctica exhibited a rapid decline in surface abundance with minimal vertical redistribution and low fluxes, potentially linked to changing environmental conditions. These findings highlight species‐specific responses to environmental conditions and implications for carbon processes. Measured values of the apparent photosynthetic efficiency (Fv/Fm) suggests that photosynthetically viable diatoms were a significant contributor to export and particle biomass in the upper mesopelagic zone. Our results underscore the importance of understanding individual species dynamics for oceanic carbon and nutrient cycles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".