MétaCan
Menu
Back to cohort

Marine mammal culling programs: review of effects on predator and prey populations

2012· article· en· W1559403838 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMammal Review · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsDalhousie UniversityBedford Institute of Oceanography
Fundersnot available
KeywordsCullingPredationMarine mammalPredatorBiologyMammalEcologyPopulationEndangered speciesAbundance (ecology)FisheryHabitatHerdDemography

Abstract

fetched live from OpenAlex

Abstract Culling is widely practised as a means to reduce predation effects of terrestrial carnivores, birds and marine mammals in many parts of the world. Of marine mammals, coastal pinniped species have usually been the target of culling programs, but dolphins and a large odontocete have also been culled. We reviewed the published literature on marine mammal culling programs to evaluate the extent of their efficacy as a fisheries management measure. Changes in species' distributions and abundance demonstrate that culling programs can be very effective at reducing predator density. Several conclusions from experimental studies of terrestrial mammals and birds may also apply to marine mammal control. Firstly, predator removal generally increases productivity and population size of target prey populations, but not always. Secondly, culling programs typically involve a large proportional reduction (>50%) in predator populations. Thirdly, the effects of culling are typically dependent on continued control, and in the absence of control the population rapidly returns to pre‐culling density. This underscores the need for predator removal to be a long‐term management strategy. Fourthly, culling predators often has non‐intuitive and unintended consequences for target species and for other predator and prey species. Marine mammal culling programs rarely have measurable objectives with respect to prey populations, and their success has not been evaluated. Culling marine mammals is controversial because of the following: (i) they are high‐profile charismatic megafauna; (ii) many populations are recovering from a period of over‐exploitation while others remain threatened or endangered; and (iii) the scientific evidence needed to justify a cull is usually highly uncertain. Marine mammal culling programs should be based on scientific analysis with stated and measurable objectives to be evaluated during planned follow‐up monitoring.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.561
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.035
GPT teacher head0.289
Teacher spread0.254 · 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