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Record W1978101295 · doi:10.1139/z04-153

Why are there so many empty lakes? Food limits survival of mallard ducklings

2004· article· en· W1978101295 on OpenAlexvenueno aff
Gunnar Gunnarsson, Johan Elmberg, Kjell Sjöberg, Hannu Pöysä, Petri Nummi

Bibliographic record

VenueCanadian Journal of Zoology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsPrecocialBiologyAnasAnatidaeBroodEcologyHolarcticReproductionWaterfowlReproductive successPredatorZoologyAnimal sciencePredationHabitatDemographyPopulation

Abstract

fetched live from OpenAlex

Food is an important factor affecting survival in many bird species, but this relationship has rarely been explored experimentally with respect to reproductive output of precocial birds. In a field experiment we tested the hypothesis that food abundance limits reproductive output in breeding dabbling ducks. Onto 10 oligotrophic lakes in northern Sweden we introduced one wing-clipped female mallard (Anas platyrhynchos L., 1758) and a brood of 10 newly hatched ducklings, and survival was monitored for 24 days. Food was added ad libitum at five of the lakes, but not at the other five. Duckling survival was best modelled to include a treatment effect, with higher survival on lakes with food added, and a negative effect of harsh weather. As expected, duckling survival increased nonlinearly with age. Only one female remained on control lakes after 24 days, whereas four remained on lakes with food added. This is the first experimental demonstration that food may limit survival and reproductive output in breeding precocial birds. We argue that food limitation may be one reason why duckling mortality is high and why many lakes throughout the Holarctic have no breeding dabbling ducks.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
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)0.0030.000

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 head0.016
GPT teacher head0.213
Teacher spread0.197 · 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.

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

Citations59
Published2004
Admission routes1
Has abstractyes

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