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Record W4406932505 · doi:10.3389/fmars.2025.1503019

Location and natural history are key to determining impact of the 2021 atmospheric heatwave on Pacific Northwest rocky intertidal communities

2025· article· en· W4406932505 on OpenAlexaboutno aff
C. Melissa Miner, Helen Berry, Heath Bohlmann, Megan N. Dethier, Steven C. Fradkin, Rani Gaddam, Wendel W. Raymond, P. Raimondi

Bibliographic record

VenueFrontiers in Marine Science · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsnot available
FundersWashington Sea Grant, University of Washington
KeywordsIntertidal zoneNatural (archaeology)GeographyKey (lock)OceanographyEnvironmental scienceEcologyEnvironmental resource managementGeologyBiologyArchaeology

Abstract

fetched live from OpenAlex

Introduction In late June 2021, the Pacific Northwest region of the United States and Canada experienced an unprecedented atmospheric heatwave that co-occurred with one of the lowest day-time tide series of the year. Several consecutive days of air temperatures 10-20°C above normal, coupled with mid-afternoon low tides proved deadly for many rocky intertidal organisms, which live at the margin of land and sea. Methods To assess short (weeks) and longer-term (1 year) impacts of the heatwave on rocky intertidal communities, we used long-term monitoring data collected annually at 16 sites throughout Washington State. Results and discussion Our findings indicate that impacts were most severe at sites within the Salish Sea region of WA, where peak low tides occurred during the hottest, mid-afternoon hours. Focal species assemblages at Olympic coast sites, where low tides occurred in the morning, were largely spared. In addition, while the heatwave was associated with substantial short-term changes in acorn barnacle, rockweed, and California mussel assemblages, lasting impacts (1 year) were only observed in the mussel assemblage at the one Salish Sea site where this species is common. These findings will aid in forecasting both short-term and longer lasting impacts of future heatwave events and help direct potential mitigation efforts to regions and species assemblages where impacts will likely be greatest.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.006
GPT teacher head0.199
Teacher spread0.192 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2025
Admission routes1
Has abstractyes

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