FeCycle: Attempting an iron biogeochemical budget from a mesoscale SF<sub>6</sub> tracer experiment in unperturbed low iron waters
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Bibliographic record
Abstract
An improved knowledge of iron biogeochemistry is needed to better understand key controls on the functioning of high‐nitrate low‐chlorophyll (HNLC) oceanic regions. Iron budgets for HNLC waters have been constructed using data from disparate sources ranging from laboratory algal cultures to ocean physics. In summer 2003 we conducted FeCycle, a 10‐day mesoscale tracer release in HNLC waters SE of New Zealand, and measured concurrently all sources (with the exception of aerosol deposition) to, sinks of iron from, and rates of iron recycling within, the surface mixed layer. A pelagic iron budget (timescale of days) indicated that oceanic supply terms (lateral advection and vertical diffusion) were relatively small compared to the main sink (downward particulate export). Remote sensing and terrestrial monitoring reveal 13 dust or wildfire events in Australia, prior to and during FeCycle, one of which may have deposited iron at the study location. However, iron deposition rates cannot be derived from such observations, illustrating the difficulties in closing iron budgets without quantification of episodic atmospheric supply. Despite the threefold uncertainties reported for rates of aerosol deposition (Duce et al., 1991), published atmospheric iron supply for the New Zealand region is ∼50‐fold (i.e., 7‐ to 150‐fold) greater than the oceanic iron supply measured in our budget, and thus was comparable (i.e., a third to threefold) to our estimates of downward export of particulate iron. During FeCycle, the fluxes due to short term (hours) biological iron uptake and regeneration were indicative of rapid recycling and were tenfold greater than for new iron (i.e. estimated atmospheric and measured oceanic supply), giving an “ f e” ratio (uptake of new iron/uptake of new + regenerated iron) of 0.17 (i.e., a range of 0.06 to 0.51 due to uncertainties on aerosol iron supply), and an “F e ” ratio (biogenic Fe export/uptake of new + regenerated iron) of 0.09 (i.e., 0.03 to 0.24).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it