DataSheet_1_Quantifying the effects of extreme events and oceanographic variability on the spatiotemporal biomass and distribution of two key euphausiid prey species.docx
Bibliographic record
Abstract
<p>Euphausiids form a critical component of oceanic food chains and individual species vary in their responses to perturbation events. We aimed to establish if patterns of fine scale oceanographic variability and larger-scale climate events such as marine heatwaves (MHWs) could be linked with spring variability in the biomass of two key forage species in the northeast Pacific Ocean, Euphausia pacifica and Thysanoessa spinifera. To achieve this, we used long-term datasets from the west coast of Vancouver Island Canada, an important commercial fishing area, to first quantify interannual signals of variability in fine-scale oceanographic conditions using multivariate analysis. We then used geostatistical spatiotemporal modelling to quantify the effects on species-specific euphausiid biomass. Oceanographic data showed that the effects of warm events are not always observable, and effects vary across small spatial scales. Warming due to the 2014-2016 MHW was relatively mild on the continental shelf during spring (<1°C above climatology). Spring biomass of euphausiids, particularly E. pacifica, peaked in 2015, and all euphausiid groups analysed (E. pacifica, T. spinifera and total euphausiids) exhibited significant correlations with positive phases of the Pacific Decadal Oscillation. These results have implications for marine predators as euphausiids may act as system stabilisers in the northeast Pacific, thereby potentially increasing ecosystem resilience during extreme events.</p>
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".