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Record W2090794812 · doi:10.1071/mu09096

Nesting habitat of Chubut Steamer Ducks in Patagonia, Argentina

2010· article· en· W2090794812 on OpenAlexaff
María Laura Agüero, Jorge Pablo Garcia Borboroglu, Dan Esler

Bibliographic record

VenueEmu - Austral Ornithology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsSimon Fraser University
FundersConsejo Nacional de Investigaciones Científicas y TécnicasRufford FoundationWildlife Conservation SocietyOak Foundation
KeywordsHabitatEcologyNest (protein structural motif)PredationRange (aeronautics)GeographyBiologyNesting seasonFishery

Abstract

fetched live from OpenAlex

We studied nest-site selection of the flightless Chubut Steamer Duck (Tachyeres leucocephalus) along 292 km of continental coastline and 59 km of island coastline in Patagonia, Argentina, between 2004 and 2006. This area encompasses the main breeding range of the species. Almost all nests were on islands and islets, which ranged in area from 0.5 to 54.4 ha and were 0.01-5.6 km from the mainland. Nesting sites were within bays and inlets with shallow waters and protected from waves, winds and strong currents. Using logistic regression analyses in an information-theoretic framework to compare habitat characteristics between nesting sites and randomly chosen sites, we found that Chubut Steamer Duck nesting sites were strongly and positively associated with higher proportions of shrub vegetation cover. To a lesser degree, the percentage of silt—clay sediment was also positively associated with nesting sites. Nest-site selection is thought to be associated with concealment from aerial predators and protection from weather. This is the first study of breeding habitat and nest-site selection of Chubut Steamer Ducks, and will contribute to management and habitat conservation for this rare flightless duck through identification of both general and specific habitat features that should be preserved or enhanced.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score1.000

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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; both teacher heads agree on what is shown here.

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
Published2010
Admission routes1
Has abstractyes

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