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Record W4230040174 · doi:10.1093/auk/120.1.107

Long-Term Productivity of Canvasbacks (Aythya Valisineria) in a Snowpack-Driven Desert Marsh

2003· article· en· W4230040174 on OpenAlexaboutno aff
Kammie L. Kruse, James R. Lovvorn, John Y. Takekawa, Jeffrey Mackay

Bibliographic record

VenueThe Auk · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAythyaNest (protein structural motif)WaterfowlEcologyAnatidaeGeographySnowpackWetlandMarshEnvironmental sciencePhysical geographyHydrology (agriculture)SnowHabitatBiologyGeology

Abstract

fetched live from OpenAlex

Abstract Ruby Lake, Nevada, is a large palustrine wetland that hosts the southern-most major breeding population of Canvasbacks (Aythya valisineria). That arid marsh, fed by springs derived from mountain snowpack, differs in climate and hydrology from glaciated potholes of the northern prairies where most Canvasbacks breed. Fourteen years of nesting data on Canvasbacks over a 31 year period (1970–2000) were analyzed to determine factors affecting breeding performance at Ruby Lake and whether they differed from those in the prairies. Long-term Mayfield nest success at Ruby Lake (50% of all nests) was in the range of that in the northern prairies (21–65%). Of all Canvasback nests, 73% were parasitized (mostly by Redheads [Aythya americana]) as compared to 83–97% in a large Manitoba marsh and 57–65% in Manitoba potholes. However, as in the northern prairies, nest parasitism generally had little or no effect on either nest success or percentage of host eggs that hatched. In Manitoba potholes, nest success was unrelated to habitat variables measured; but successful nests at Ruby Lake were over shallower water, farther from shore, in wider bands of emergent vegetation, and surrounded by lower stem densities than unsuccessful nests. Water level is the key factor in breeding performance of Canvasbacks at both Ruby Lake and the northern prairies; however, the source of water differs (mountain snowpack at Ruby Lake, direct precipitation in the prairies) and effects of water-level variations are reversed. In small prairie potholes (mostly <0.4 ha) with many mammalian predators, productivity of Canvasbacks (which build floating nests) is increased by high water that floods the emergent fringe. At Ruby Lake, a very large marsh (2,830 ha) with mostly avian predators, Canvasback productivity is decreased by high water that floods interior emergent stands too deeply. Water level at Ruby Lake was highly correlated (multiple R2 = 0.91) with mountain snowpack up to three years earlier, emphasizing the strong effect of climatic variations on wetland birds in that arid region.

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 score0.051
Threshold uncertainty score0.888

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 studies0.0000.000
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 head0.015
GPT teacher head0.233
Teacher spread0.218 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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