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Establishing climate–growth relationships for yelloweye rockfish (<i>Sebastes ruberrimus</i>) in the northeast Pacific using a dendrochronological approach

2008· article· en· W2163645101 on OpenAlexaboutno aff
Bryan A. Black, George W. Boehlert, Mary M. Yoklavich

Bibliographic record

VenueFisheries Oceanography · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersNational Marine Fisheries ServiceOregon State University
KeywordsDendrochronologyChronologyPacific decadal oscillationOceanographyClimatologySebastesGeologyRockfishSea surface temperatureMultivariate ENSO indexCurrent (fluid)DendroclimatologyUpwellingClimate changeLa NiñaEl Niño Southern OscillationFish <Actinopterygii>Fishery

Abstract

fetched live from OpenAlex

Abstract We applied dendrochronology (tree‐ring) methods to develop multidecadal growth chronologies from the increment widths of yelloweye rockfish ( Sebastes ruberrimus ) otoliths. Chronologies were developed for the central California coast, a site just north of Vancouver Island, British Columbia, and at Bowie Seamount west of the Queen Charlotte Islands, British Columbia. At each site, synchronous growth patterns were matched among otoliths via the process of cross‐dating, ensuring that the correct calendar year was assigned to all increments. Each time series of growth‐increment measurements was divided by the values predicted by a best‐fit negative exponential function, thereby removing age‐related trends. These detrended time series were averaged into a master chronology for each site, and chronologies were correlated with monthly averages of sea surface temperatures, upwelling, the Northern Oscillation Index, and the Pacific Decadal Oscillation. The two northern growth chronologies positively correlated with indices of warm ocean conditions, especially from the prior summer through the spring of the current year. During the same period, the California chronology positively correlated with indices of cool ocean conditions, indicating an opposing productivity regime for yelloweye rockfish between the California Current and the Gulf of Alaska. Overall, this study demonstrates how tree‐ring techniques can be applied to quickly develop annually resolved chronologies and establish climate–growth relationships across various temporal and spatial scales.

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)0.001
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 score0.099
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

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

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 head0.057
GPT teacher head0.222
Teacher spread0.165 · 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

Citations73
Published2008
Admission routes1
Has abstractyes

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