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Record W3035206089 · doi:10.1126/science.aay5342

Cascading social-ecological costs and benefits triggered by a recovering keystone predator

2020· article· en· W3035206089 on OpenAlex
Edward J. Gregr, Villy Christensen, Linda M. Nichol, Rebecca Martone, Russell W. Markel, Jane C. Watson, Christopher D. G. Harley, Evgeny A. Pakhomov, Jonathan B. Shurin, Kai M. A. Chan

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueScience · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsTula FoundationVancouver Island UniversityFisheries and Oceans CanadaSciencetech (Canada)University of British Columbia
FundersHakai Institute
KeywordsTrophic cascadeKeystone speciesTrophic levelKelp forestEcosystemEcosystem servicesEcologyBiomass (ecology)Food webApex predatorFisheryMesopredator release hypothesisPredationBenthic zoneEnvironmental scienceGeographyBiology

Abstract

fetched live from OpenAlex

Predator recovery often leads to ecosystem change that can trigger conflicts with more recently established human activities. In the eastern North Pacific, recovering sea otters are transforming coastal systems by reducing populations of benthic invertebrates and releasing kelp forests from grazing pressure. These changes threaten established shellfish fisheries and modify a variety of other ecosystem services. The diverse social and economic consequences of this trophic cascade are unknown, particularly across large regions. We developed and applied a trophic model to predict these impacts on four ecosystem services. Results suggest that sea otter presence yields 37% more total ecosystem biomass annually, increasing the value of finfish [+9.4 million Canadian dollars (CA$)], carbon sequestration (+2.2 million CA$), and ecotourism (+42.0 million CA$). To the extent that these benefits are realized, they will exceed the annual loss to invertebrate fisheries (-$7.3 million CA$). Recovery of keystone predators thus not only restores ecosystems but can also affect a range of social, economic, and ecological benefits for associated communities.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.024
GPT teacher head0.215
Teacher spread0.191 · 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