Climate, currents and species traits contribute to early stages of marine species redistribution
Bibliographic record
Abstract
Anthropogenic climate change is causing a rapid redistribution of life on Earth, particularly in the ocean, with profound implications for humans. Yet warming-driven range shifts are known to be influenced by a variety of factors whose combined effects are still little understood. Here, we use scientist-verified out-of-range observations from a national citizen-science initiative to assess the combined effect of long-term warming, climate extremes (i.e., heatwaves and cold spells), ocean currents, and species traits on early stages of marine range extensions in two warming 'hotspot' regions of southern Australia. We find effects of warming to be contingent upon complex interactions with the strength of ocean currents and their mutual directional agreement, as well as species traits. Our study represents the most comprehensive account to date of factors driving early stages of marine species redistributions, providing important evidence for the assessment of the vulnerability of marine species distributions to climate change.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.020 | 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".