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Record W2162186175 · doi:10.1093/icesjms/fsr195

Common large-scale responses to climate and fishing across Northwest Atlantic ecosystems

2012· article· en· W2162186175 on OpenAlexaff
Nancy L. Shackell, Alida Bundy, Janet A. Nye, Jason S. Link

Bibliographic record

VenueICES Journal of Marine Science · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsBedford Institute of Oceanography
Fundersnot available
KeywordsGroundfishFishingTrophic levelClimate changeMarine ecosystemBiomass (ecology)EcosystemNorth Atlantic oscillationEcologyEnvironmental scienceGeographyAtlantic multidecadal oscillationFisheryOceanographyFisheries managementBiology

Abstract

fetched live from OpenAlex

Abstract Shackell, N. L., Bundy, A., Nye, J. A., and Link, J. S. 2012. Common large-scale responses to climate and fishing across Northwest Atlantic ecosystems. – ICES Journal of Marine Science, 69: 151–152. Investigating whether there were common biological responses to climate and fishing across seven Northwest Atlantic ecosystems, a minimum/maximum autocorrelation factor analysis of biological indicators for each region revealed a common primary multivariate trend of a rapid change during the 1980s and early 1990s. There was a strong common pattern in the biological indicators responsible for the primary multivariate temporal trend in the five more northerly regions: an increase in the abundance of phytoplankton, an increase in biomass at mid-trophic levels, and a decline in predatory groundfish size. The common associations between patterns and drivers were fishing indices and the Atlantic Multidecadal Oscillation, but all associations weakened when co-varying drivers were held constant. The results are consistent with known long-term effects of intense fishing, such as a decline in average fish size and changes in species composition. Less fishing pressure has allowed some regions to recover to former predatory biomass levels since the late 1990s, but the bulk of the biomass consists of fewer species. However, fishing was not the only driver, and a more mechanistic understanding of how the climate affects lower trophic levels is needed to contextualize climate effects in heavily fished ecosystems.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.052
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.300
Teacher spread0.282 · 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 teacher head, 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

Citations53
Published2012
Admission routes1
Has abstractyes

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