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Effects of small mammal cycles on productivity of boreal ducks

2005· article· en· W2173540659 on OpenAlexafffundabout
Rodney W. Brook, David C. Duncan, James E. Hines, Suzanne Carrière, Robert G. Clark

Bibliographic record

VenueWildlife Biology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsEnvironment and Climate Change CanadaGovernment of Northwest TerritoriesUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPredationBiologyAbundance (ecology)AnasProductivityGrouseEcologyWaterfowlSnowshoe hareNumerical responsePredatorHabitatFunctional response

Abstract

fetched live from OpenAlex

North American boreal nesting waterfowl (and their eggs and ducklings) share a number of generalist predators with small mammals and non-migratory birds that could indirectly link fluctuations in these coexisting prey. We surveyed pairs and broods to determine an index of productivity for lesser scaup Aythya affinis breeding near Yellowknife, Northwest Territories, Canada. We also calculated a mallard Anas platyrhynchos productivity index for birds from northern Saskatchewan, Canada. Small mammal abundance was estimated by snap trapping rodents and by counting pellets of snowshoe hares Lepus americanus in the Yellowknife area. Because small mammal data were not available for the same area as mallard harvest survey data, correlation with an estimate of ruffed grouse Bonasa umbellus harvest was used because small mammal abundance and grouse are known to correlate positively. We found a positive correlation between the abundance of rodents and lesser scaup productivity suggesting a prey switching relationship for predators between their main prey (rodents) and alternative prey (lesser scaup, eggs and ducklings). A negative correlation between snowshoe hare abundance and lesser scaup productivity was also found as well as a negative correlation between ruffed grouse abundance and mallard productivity. Negative correlations suggest a possible shared predation relationship, where changes in main prey abundance (hares) may cause a numerical response in predators that influences predation rates of shared alternative prey (ducks, eggs and ducklings). Although our conclusions are based on correlations, they indicate that a great deal of variation in boreal duck productivity might be explained by the indirect effects of coexisting prey abundance. Further work is needed to determine causal mechanisms contributing to these relationships, the effect of cycles in small mammal populations and the overall importance of top-down predator regulation for regulating duck productivity in boreal forest.

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 score0.017
Threshold uncertainty score0.296

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)0.0000.000

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 head0.012
GPT teacher head0.244
Teacher spread0.233 · 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

Citations25
Published2005
Admission routes3
Has abstractyes

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