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Record W3217220977 · doi:10.1111/csp2.594

Differential population trends align with migratory connectivity in an endangered shorebird

2021· article· en· W3217220977 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueConservation Science and Practice · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersAustralian Research CouncilCharles Darwin UniversityThreatened Species Recovery HubUniversity of QueenslandNatural Sciences and Engineering Research Council of CanadaBirds Queensland
KeywordsGeographyEndangered speciesPopulationEcologyPopulation declineCritically endangeredHabitatBiologyDemography

Abstract

fetched live from OpenAlex

Abstract Migratory connectivity describes the extent to which migratory species' populations are connected throughout the annual cycle. While recognized as critical for understanding the population dynamics of migratory species and conserving them, empirical evidence of links between migratory connectivity and population dynamics are uncommon. We analyzed associations between spatiotemporal connectivity and differential population trends in a declining and endangered migratory shorebird, the far eastern curlew ( Numenius madagascariensis ), with multiyear tracking data from across the Australian nonbreeding grounds. We found evidence of temporal and spatial segregation during migration and breeding: curlew from southeast Australia initiated northward migration earlier, arrived at breeding sites earlier, and bred at lower latitudes than curlew from northwest Australia. Analysis of land modification intensity revealed that populations from southeast Australia face greater human impacts compared to those from northwest Australia at both the breeding and nonbreeding grounds, a pattern that aligns with steeper population declines in southeast Australia. This alignment between migratory connectivity, human impacts, and differential population change highlights the importance of a full annual cycle approach to conservation that includes mitigating threats on the breeding grounds and better protecting nonbreeding habitats in Australia where far eastern curlew spend over half of each year.

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)0.001
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 score0.029
Threshold uncertainty score0.635

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.036
GPT teacher head0.311
Teacher spread0.275 · 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