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Climatic conditions during outward migration affect apparent survival of an arctic top predator, the peregrine falcon <i>Falco peregrinus</i>

2011· article· en· W2125972640 on OpenAlexafffundabout
Alastair Franke, Jean‐François Therrien, Sébastien Descamps, Joël Bêty

Bibliographic record

VenueJournal of Avian Biology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaNunavut Wildlife Management BoardArcticNet
KeywordsBiologyPeregrinusFalconPredatorArcticZoologyPredationEcology

Abstract

fetched live from OpenAlex

In long‐lived species, population growth rate is highly sensitive to changes in adult survival. Despite the growing concerns regarding recent climate changes, few studies have investigated the effect of climatic conditions on survival in long‐lived wildlife that are either resident or breed in the Arctic. In this study, we evaluated the effect of climate across the annual life cycle (breeding, outward migration, wintering, and inward migration) on apparent annual survival of arctic‐breeding peregrine falcons. From 1982 to 2008, peregrine falcons breeding near Rankin Inlet, Nunavut, Canada were monitored, in part, to assess apparent annual survival (the product of true survival and site fidelity) using re‐observations of marked individuals. Our study indicated that apparent annual survival of adult peregrine falcons was correlated with indices of climatic conditions during outward migration (i.e., flight from the Arctic breeding grounds). These climatic indices (fall NAO of the current year and fall NAO with a lag of one year) explained 35% of the temporal variation in apparent annual survival of peregrine falcons. Our results suggest that this top‐predator is vulnerable to weather‐related environmental conditions encountered during fall migration.

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)0.000
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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.028
GPT teacher head0.269
Teacher spread0.241 · 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

Citations36
Published2011
Admission routes3
Has abstractyes

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