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Record W2998884854 · doi:10.1007/s13280-019-01308-5

Status and trends of tundra birds across the circumpolar Arctic

2020· article· en· W2998884854 on OpenAlexaff
Paul A. Smith, Laura McKinnon, Hans Meltofte, Richard B. Lanctot, Anthony David Fox, James O. Leafloor, Mikhail Soloviev, Alastair Franke, Knud Falk, М. Г. Головатин, Vasiliy Sokolov, Aleksandr Sokolov, Adam C. Smith

Bibliographic record

VenueAMBIO · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of AlbertaCarleton UniversityYork UniversityEnvironment and Climate Change CanadaNatural Resources Canada
Fundersnot available
KeywordsCircumpolar starTundraArcticThe arcticGeographyPhysical geographyEnvironmental scienceEcologyOceanographyBiologyGeology

Abstract

fetched live from OpenAlex

Tundra-breeding birds face diverse conservation challenges, from accelerated rates of Arctic climate change to threats associated with highly migratory life histories. Here we summarise the status and trends of Arctic terrestrial birds (88 species, 228 subspecies or distinct flyway populations) across guilds/regions, derived from published sources, raw data or, in rare cases, expert opinion. We report long-term trends in vital rates (survival, reproduction) for the handful of species and regions for which these are available. Over half of all circumpolar Arctic wader taxa are declining (51% of 91 taxa with known trends) and almost half of all waterfowl are increasing (49% of 61 taxa); these opposing trends have fostered a shift in community composition in some locations. Declines were least prevalent in the African-Eurasian Flyway (29%), but similarly prevalent in the remaining three global flyways (44-54%). Widespread, and in some cases accelerating, declines underscore the urgent conservation needs faced by many Arctic terrestrial bird 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)0.001
metaresearch head score (Gemma)0.001
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 score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.048
GPT teacher head0.265
Teacher spread0.217 · 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

Citations90
Published2020
Admission routes1
Has abstractyes

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Same venueAMBIOSame topicClimate change and permafrostFrench-language works237,207