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Record W4405107167 · doi:10.1016/j.pocean.2024.103404

Baseline matters: Challenges and implications of different marine heatwave baselines

2024· article· en· W4405107167 on OpenAlexafffund
Kathryn E. Smith, Alex Sen Gupta, Dillon J. Amaya, Jessica A. Benthuysen, Michael T. Burrows, Antonietta Capotondi, Karen Filbee‐Dexter, Thomas L. Frölicher, Alistair J. Hobday, Neil J. Holbrook, Neil Malan, Pippa J. Moore, Eric C. J. Oliver, Benjamin Richaud, Julio Salcedo‐Castro, Dan A. Smale, Mads S. Thomsen, Thomas Wernberg

Bibliographic record

VenueProgress In Oceanography · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsDalhousie University
FundersNOAA ResearchAustralian Research CouncilNational Oceanic and Atmospheric AdministrationClimate ExtremesNatural Sciences and Engineering Research Council of CanadaEuropean CommissionNatural Environment Research CouncilUK Research and InnovationU.S. Department of CommerceMinistry of Business, Innovation and EmploymentEuropean Climate, Infrastructure and Environment Executive AgencyUniversity of CanterburyNational Aeronautics and Space Administration
KeywordsBaseline (sea)OceanographyEnvironmental scienceClimatologyGeographyGeology

Abstract

fetched live from OpenAlex

• 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.206
metaresearch head score (Gemma)0.383
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.206
Threshold uncertainty score0.979

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2060.383
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.006
Science and technology studies0.0060.010
Scholarly communication0.0140.019
Open science0.0060.009
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0100.003

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.

Opus teacher head0.018
GPT teacher head0.239
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations53
Published2024
Admission routes2
Has abstractyes

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