MétaCan
Menu
Back to cohort
Record W2107325771 · doi:10.1016/j.icesjms.2005.05.007

On distributional responses of North Atlantic fish to climate change

2005· article· en· W2107325771 on OpenAlexaff
George A. Rose

Bibliographic record

VenueICES Journal of Marine Science · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCapelinClupeaGadusSpawn (biology)FisheryAtlantic herringOceanographyHerringGroundfishPacific herringBiologyPorpoisePopulationArcticClimate changeGadidaeAtlantic codEcologyFisheries managementFish <Actinopterygii>GeologyFishing

Abstract

fetched live from OpenAlex

Abstract Changes in fish distribution and climate in the North Atlantic have been observed for millennia by seafaring peoples, chronicled in many historical anecdotes, and recently studied systematically. For temperate to Arctic North Atlantic fish, a literature compendium of limits of temperature, salinity, and depth during feeding and spawning was used to investigate factors that influence distribution. Latitude and depth were negatively correlated with species number and density. Peak numbers of species feed at 0–4°C, but spawn at 2–7°C and salinities of 32.5–33.5. Principal components of feeding depths and temperatures suggested four groups of species: (i) small pelagics characterized by shallow habitat and cooler temperatures; (ii) most groundfish in deeper and warmer waters; (iii) warm-water large pelagics; and (iv) deepwater species. Spawning temperatures, salinities, depths, and timing produced groupings consistent with feeding components for pelagics, but differing for distant migrants such as tunas. Principal components (PCA) of spawning characteristics explained 56% of the variance in species resilience (doubling time), while PCA of feeding characteristics explained only 23%. We infer that the small pelagics capelin (Mallotus villosus) and herring (Clupea harengus) react strongly and quickly to climate change because of their physiological limits and potential for fast population growth. Verification comes from Icelandic and Greenland waters, which warmed considerably during 1920–1940, and where capelin, herring, cod (Gadus morhua), and other species shifted north very quickly.

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)0.001
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 score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.288
Teacher spread0.263 · 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

Citations234
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueICES Journal of Marine ScienceSame topicMarine and fisheries researchFrench-language works237,207