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Record W2796813226 · doi:10.1139/as-2017-0054

Phenology of hatching and food in low Arctic passerines and shorebirds: is there a mismatch?

2018· article· en· W2796813226 on OpenAlexaffvenueabout
Maria C.-Y. Leung, Élise Bolduc, Frank I. Doyle, Donald G. Reid, Benjamin Gilbert, Alice J. Kenney, Charles J. Krebs, Joël Bêty

Bibliographic record

VenueArctic Science · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of British ColumbiaYukon UniversityWildlife Conservation Society CanadaUniversité du Québec à Rimouski
Fundersnot available
KeywordsTundraEcologyPhenologyBiologyPredationAbundance (ecology)Biomass (ecology)ChironomidaeWaderArcticEcosystemLarva

Abstract

fetched live from OpenAlex

The warming climate is driving earlier spring snow melt and longer growing seasons in tundra regions of northwestern North America, thereby changing the timing of ecological processes. On Herschel Island, Yukon, Canada, we investigated changes in the migratory bird community, and the potential for phenological mismatch of egg hatching with the pulses in abundance of arthropod prey on which young birds depend for growth. We found an apparent reduction in abundance or loss of some species dependent on freshwater ponds or sparsely vegetated upland tundra. Tracking hatch dates of passerines and shorebirds along with the changes in biomass of mobile life history stages of arthropods (principally Araneae, Tipulidae, Carabidae, Muscidae, Chironomidae, Mycetophilidae, and Ichneumonidae), we found no evidence for phenological mismatch in the 2007–2009 time period. Most nests hatched, and the period of most rapid chick growth occurred, in advance of the highest availability of arthropod biomass. Shorebirds hatched significantly later than passerines, less in advance of the peak abundances of arthropods. They are most at risk of future mismatch, given likely trend to earlier onset of arthropod availability and longer migration routes. Herschel Island is a well-studied site warranting further monitoring to assess changes in the Arctic tundra ecosystem.

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 score0.027
Threshold uncertainty score0.998

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 studies0.0000.001
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 head0.031
GPT teacher head0.250
Teacher spread0.220 · 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

Citations15
Published2018
Admission routes3
Has abstractyes

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