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Record W4392656666 · doi:10.3389/fmars.2024.1283231

Biologically Important Areas II for cetaceans within U.S. and adjacent waters - West Coast Region

2024· article· en· W4392656666 on OpenAlexaboutno aff
John Calambokidis, Michaela A. Kratofil, Daniel M. Palacios, Barbara A. Lagerquist, Gregory S. Schorr, M. Bradley Hanson, Robin W. Baird, Karin A. Forney, Elizabeth A. Becker, R. Cotton Rockwood, Elliott L. Hazen

Bibliographic record

VenueFrontiers in Marine Science · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersNational Marine Fisheries ServiceOffice of Naval ResearchBureau of Ocean Energy ManagementU.S. NavyNational Oceanic and Atmospheric Administration
KeywordsGeographyFisheryOceanographyWest coastBiologyGeology

Abstract

fetched live from OpenAlex

Here we update U.S. West Coast Biologically Important Areas (BIAs) that were published in 2015 using new data and approaches. Additionally, BIAs were delineated for two species that were not delineated in the 2015 BIAs: fin whales and Southern Resident killer whales (SRKW). While harbor porpoise BIAs remained the same, substantial changes were made for other species including identifying both larger overall areas (parent BIAs) and smaller core areas (child BIAs). For blue, fin, and humpback whales we identified, delineated, and scored BIAs using the overlap between the distribution and relative density from three data sources, leveraging the strengths and weaknesses of these approaches: 1) habitat density models based on Southwest Fisheries Science Center (SWFSC) line-transect data from systematic ship surveys conducted through 2018, 2) satellite tag data from deployments conducted by three research groups, and 3) sightings of feeding behavior from non-systematic effort mostly associated with small-boat surveys for photo-identification conducted by Cascadia Research Collective. While the previous BIAs were based solely on a more subjective assignment from only the small boat sightings, here we incorporate the other two data sources and use a more rigorous, quantitative approach to identify higher density areas and integrate the data types. This resulted in larger, better-supported, objective BIAs compared to the previous effort. Our methods are also more consistent with the delineation of BIAs in other regions. For SRKWs, the parent BIA was based on a modification of the Critical Habitat boundaries defined by the National Oceanographic and Atmospheric Administration (NOAA) and the Department of Fisheries and Oceans (DFO) Canada; a core BIA highlighting areas of intensified use was identified using both NOAA’s Critical Habitat and kernel density analyses of satellite tag data. Gray whale BIAs were re-evaluated for the migratory corridor of Eastern North Pacific gray whales, for Pacific Coast Feeding Group feeding areas, and for gray whales that feed regularly in Puget Sound.

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 score0.066
Threshold uncertainty score0.583

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.002
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 head0.014
GPT teacher head0.229
Teacher spread0.215 · 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

Citations13
Published2024
Admission routes1
Has abstractyes

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