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Record W3213761995 · doi:10.14430/arctic73845

The Long-Term Monitoring of Bird Populations on Kolguev Island in the Barents Sea

2021· article· en· W3213761995 on OpenAlexvenueno aff
П.М. Глазов, Julia Loshchagina, Alexander Kondratyev, Elmira Zaynagutdinova, Helmut Kruckenberg, Ivan Pokrovsky

Bibliographic record

VenueARCTIC · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsnot available
FundersRussian Foundation for Basic Research
KeywordsLagopusVulpesEcologyPloverWaderCalidrisBiologyPopulationNest (protein structural motif)SandpiperBuzzardGeographyPredationArcticFisheryHabitat

Abstract

fetched live from OpenAlex

Kolguev Island (69˚05′ N 49˚15′ E) is located in the Pechora Sea, the southeastern part of the Barents Sea. The island’s ecosystem is unusual due to the total absence of rodents and specialized predators such as weasels, while non-specialized predators such as Arctic (Vulpes lagopus) and red (V. vulpes) foxes and Rough-legged Hawk (Buteo lagopus) are common. Currently, 111 bird species have been registered here, of which 58 are nesting. The absence of rodents and the relatively stable predation pressure have resulted in the high abundance of many bird species: Willow Ptarmigan (Lagopus lagopus), several goose species, some waders, and passerines. Over the 125-year history of ornithological studies on Kolguev, the island avifauna has changed significantly. The trend of an increase in the proportion of widespread and Siberian species together with a decrease in the proportion of Arctic species was observed. Since 2006, a thorough monitoring of Kolguev avifauna has been carried out, during which the dynamics of the bird population densities have been traced. The abundance of Black-bellied Plover (Pluvialis squatarola) and Dunlin (Calidris alpina) decreased, while the numbers of Barnacle Goose (Branta leucopsis) have increased sharply since the 1980s. The breeding density of Rough-legged Hawk has also increased in recent years. The long-term monitoring of Kolguev ecosystems has indicated the high international conservation value of the island due to the high breeding density of many bird species. Our study, covering more than a century of avifaunal studies with almost annual monitoring over the past three decades, provides an unusually long and detailed time-series for an Arctic island.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.975

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 head0.065
GPT teacher head0.264
Teacher spread0.199 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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