Step change in sea surface temperatures brings marine heat waves to sub-Arctic James Bay, Canada
Bibliographic record
Abstract
Marine heat waves (MHWs) are recognized as pervasive drivers of impacts on marine species and ecosystems across the world; however, sub-Arctic areas that are rapidly losing seasonal sea-ice cover remain understudied. In this research, we examine a forty-year time series of MHW characteristics in the seasonally ice-covered James Bay region of the Canadian Inland Seas in central Canada. Through the period 1982 to 2021, we document the trends and investigate past MHW occurrences with respect to their driving processes. After only two MHW events during the early portion of the record (1982-1997), five events occurred in 1998 and signaled both an anomalous year and a step change in the region’s marine climatology. The new marine climate in the region is more variable with longer and more intense MHWs. Four or more MHWs occurred in each of 2001, 2005, 2010, 2012. Events in May and October 2021 lasted over a month in duration, with the former reaching intensities of between 2.5 and 3°C. MHW intensity was correlated with ice breakup date and positive Atlantic Multi-decadal Variability, which are suggested drivers of the increasing trends in sea surface temperatures. While the impacts of MHWs on marine and coastal ecosystems in the region remain unknown because of a lack of monitoring, the 1998 MHW intensification coincides with a massive decline in the region’s seagrass Zostera marina (eelgrass) ecosystem, which has been monitored since 1982. Given projections of more extreme MHWs under global warming and the sensitivity of marine species and ecosystems to warm water events, there is an urgent need to better tracks MHWs and investigate their role in shaping northern ecosystem changes.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".