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Record W4390607579 · doi:10.33265/polar.v43.9756

Garbage consumption by Arctic terrestrial predators in one of the most pristine land areas on Earth

2024· article· en· W4390607579 on OpenAlexaff
Araceli Gort‐Esteve, Muzit Abrham, Christian Carøe, Johannes Måsviken, Susana E. Freire, Nicolas Lecomte, Patrícia Pečnerová, Anders Angerbjörn, Jordi Bartolomé, Karin Norén, Fredrik Dalerum

Bibliographic record

VenuePolar Research · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsUniversité de Moncton
FundersConsejo Superior de Investigaciones CientíficasMinisterio de Ciencia e InnovaciónMinisterio de Economía y CompetitividadPolarforskningssekretariatet
KeywordsArcticGarbageWildlifeLagopusPredationVulpesEcologyApex predatorTerrestrial ecosystemArctic foxEcosystemGeographyEnvironmental scienceTrophic levelBiology

Abstract

fetched live from OpenAlex

Garbage may cause substantial environmental perturbations, in part because of its consumption by wildlife. Such consumption may have direct health implications for animals and may also influence trophic relationships. Even in pristine Arctic ecosystems, wildlife feeding in marine environments consume garbage in the form of plastic debris transported by ocean currents. We show that Arctic wildlife in pristine terrestrial environments may also ingest garbage or food items derived from abandoned camp sites. We found the remains of a chocolate wrapper and a milk powder bag in two Arctic fox (Vulpes lagopus) scats and a piece of cloth in an Arctic wolf (Canis lupus arctos) scat collected near Nares Strait, northern Greenland, one of the most pristine terrestrial wilderness regions on Earth. Found on Washington Land and associated with long-abandoned camp sites, these three scats were among 657 Arctic fox scats and 92 wolf scats collected as part of a larger study. Our study demonstrates that these two highly opportunistic predators managed to consume garbage despite the almost complete lack of human activity in this High-Arctic region. Our results highlight that abandoned anthropogenic material in the High Arctic may function as a source of garbage for local terrestrial wildlife over extended time periods, and that garbage consumption may become a potential issue if human activity in remote Arctic regions increases.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.296
Teacher spread0.251 · 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.

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

Citations2
Published2024
Admission routes1
Has abstractyes

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