Regional-scale changes in diatom distribution in the Humboldt upwelling system as revealed by remote sensing: implications for fisheries
Bibliographic record
Abstract
Abstract Jackson, T., Bouman, H. A., Sathyendranath, S., and Devred, E. 2011. Regional-scale changes in diatom distribution in the Humboldt upwelling system as revealed by remote sensing: implications for fisheries. – ICES Journal of Marine Science, 68: 729–736. A diatom-detection algorithm was parametrized for the Humboldt upwelling system using local cruise data that were first validated, then used to create monthly composites of diatom distribution from 0 to 40°S and 90 to 70°W for both normal and El Niño conditions. There was a 50% reduction in the areal extent of diatom-dominated waters during the peak of the 1997 El Niño. The extent of the coastward contraction in the diatom-dominated area varied along the South American coastline. These regional shifts in phyto- and zooplankton communities would have increased food stress on local anchovy (Engraulis ringens) populations and could have contributed to diminished larval survival and landings the following year. A region of strong upwelling over the wide Peruvian continental shelf around 15°S was the only area that maintained a strong diatom population throughout the El Niño; the area may require special protection from fishing pressure in years following an El Niño event.
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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 | 0.000 |
| 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".