Evidence for a decline in the population density of Antarctic krill Euphausia superba Dana, 1850 still stands. A comment on Cox et al
Bibliographic record
Abstract
Antarctic krill (Euphausia superba Dana, 1850) exemplifies the key role of marine crustaceans in fisheries, foodwebs, and biogeochemical cycles. Ecological understanding and policy decisions require information on population trends. We have therefore worked with international colleagues to publish KRILLBASE, a database of fishery-independent krill population information for every decade since the 1970s. These data were used by Cox et al. (2018) who dispute the evidence for a late twentieth-century decline in krill density (number per unit area) in the Southwest Atlantic sector of the Southern Ocean and claim to overturn “much of recent thinking about climate-driven change in krill populations.” They support this claim with an analysis which reaffirms one non-significant result from an earlier paper but does not challenge the five significant results from that paper or those of other studies which support a decline. In this comment we examine the methods which led Cox and coauthors to conclude that krill density has been stable over the last 40 years. Although these authors provide a potentially useful approach, we show that their analysis was biased by the exclusion of usable net types, the inclusion of negatively biased data and down-weighting of high densities in the early part of the analysis period, the absence of recent data from the north of the sector, and a lack of statistical hypothesis testing. These factors maximise the chances of failure to detect a real decline. To aid future analyses we provide recommendations to supplement those which accompany KRILLBASE. We also suggest the need for consensus scientific advice on krill population dynamics based on agreed standards of evidence, evaluation of uncertainty, and a thorough understanding of the data. This will be more useful to policy makers and other stakeholders than polarised opinions. Meanwhile, the evidence for a decline in krill density still stands.
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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 | 0.011 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.023 | 0.030 |
| Insufficient payload (model declined to judge) | 0.008 | 0.009 |
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".