MétaCan
Menu
← Back to cohort
Record W7133274848

Cumulative effects assessment for West Coast Transient (Bigg’s) Killer Whales

2025· other· en· W7133274848 on OpenAlexaboutno aff
Fisheries and Oceans Canada, Pêches et Océans Canada

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsFecundityDisturbance (geology)Cumulative effectsPopulationThreatened speciesVital ratesClimate changePredation
DOInot available

Abstract

fetched live from OpenAlex

The West Coast Transient (WCT) population of the Bigg’s Killer Whale (BKW) ecotype was listed as Threatened under the Species at Risk Act (SARA) in 2001. The SARA Recovery Strategy was completed in 2007 (DFO 2007) and is currently being amended. The SARA Recovery Strategy outlined the most pressing anthropogenic threats to WCT as chemical contaminants, and physical and acoustic disturbance (DFO 2007); and also described other threats: biological pollutants, trace metals, toxic spills, collision with vessels, and decline in prey availability or quality. Based on the Recovery Strategy, the current study focused on four identified threats: disturbance (acoustic); disturbance (physical); reduced prey availability; and contaminants. The current analysis uses an established cumulative effects framework that combines a Pathways of Effects (PoE) conceptual model with a Population Viability Analysis (PVA) to assess the cumulative effects of the four identified threats on killer whale vital rates. The study area focused on the Canadian portion of the Salish Sea (CSS) and the subset of WCT observed there during the years 2005 to 2022, to provide optimal overlap between knowledge of threats and population observations. Current knowledge of how threats affect mortality and fecundity rates of WCT in the CSS were synthesised into the overall PoE model consisting of 16 evidence-based linkages from identified threats to effects, eight from single threats and eight mediated through threat interactions. Future changes in anthropogenic activities and their potential threats, including those linked to climate change, were not included. The PoE linkages with sufficient knowledge to be quantified were retained to form a PVA specific PoE model consisting of six evidence-based linkages, four from single threats, and two from threat interactions, these quantifiable threats informed the inputs and structure of the PVA model. The PVA model explored the sensitivity and relative importance of quantifiable threats (vessel strikes, PCBs, vessel noise, reduced prey availability), threat interactions (between PCBs and prey, and vessel noise and prey), and cumulative effects on the population trajectories of the WCT in the CSS. In the PVA, each quantifiable threat and interaction was modelled individually and also together in a cumulative effects scenario. The cumulative effects model included impacts of prey availability on the population carrying capacity, masking of prey sounds by vessel noise, vessel strike mortality, and PCB contamination on calf mortality. The cumulative model, including all four threats, replicates the observed population trend closely with the CSS population size contained within the 90% distribution of the model estimates indicating good model fit. Reduced prey availability had the most influence on abundance trends for WCT in the CSS. The cumulative effects PVA model can be used to explore the impacts of different mitigation and management options for individual threats on the population trajectory, noting that it is sensitive to the value for carrying capacity (i.e., the maximum CSS abundance that the environment can sustain as a result of prey availability). Future projections showed a steady increase in the CSS population over the initial ten to twenty years and then stable population size through the rest of the simulation. The carrying capacity had the biggest effect on the simulated population trends, while the modeled prey trends had relatively small effects. The cumulative effects assessment framework used here, which combines a PoE with a PVA model, is an established approach that explicitly identifies and quantifies threat linkage pathways and associated uncertainties, with the potential for use in other populations and species.

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)0.011
metaresearch head score (Gemma)0.022
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 score0.953
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0050.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.010
GPT teacher head0.268
Teacher spread0.259 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada→French-language works237,207→