Baseline matters: Challenges and implications of different marine heatwave baselines
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
• Marine Heatwaves (MHW) can be defined relative to different baselines. • The baselines determine whether long term warming is included or excluded. • Different baselines convey different levels of changing risk for marine species. • The choice of baseline should be carefully considered to best fit the application. Marine heatwaves (MHWs), prolonged periods of unusually high ocean temperatures, significantly impact global ecosystems. However, there is ongoing debate regarding the definition of these extreme events, which is crucial for effective research and communication among marine scientists, decision-makers, and the broader public. Fundamental to all MHW analyses is a clearly defined background oceanic climate – i.e., a temperature ‘baseline’ against which the MHW is defined. While a single approach to implementing a baseline may not be suitable for all MHW research applications, the choice of a baseline for analysing MHWs must be intentional as it affects research outcomes. This perspective examines baseline choices and discuss their implications for marine organism and ecosystem risks, and their relevance in communicating MHW characteristics and metrics to stakeholders, policymakers, and the public. In particular we analyses five different baseline approaches for computing MHW statistics, assesses their technical differences, and discusses their ecological implications. Different baselines suggest widely different trends in MHW characteristics in a warming world. This would, for example, imply differences in future risk, reflective of marine organisms with different adaptive potential, thereby affecting recommendations for management strategies. We also examine the consequences of different baseline choices on ease of implementation and communication with wider audiences. Our analyses highlight the need to clearly specify a chosen baseline in MHW studies, and to be mindful of its implications for MHW statistics, practical considerations, and interpretations concerning the adaptive capacities of marine organisms, ecosystems and human systems. The challenges and implications of different MHW baselines highlighted here have similar relevance in research and communication for other branches of climate extremes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it