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Record W2740471276 · doi:10.1002/wsb.794

Relationships between abundances of breeding ducks and attributes of Canadian prairie wetlands

2017· article· en· W2740471276 on OpenAlexafffundabout
Blake A. Bartzen, Kevin W. Dufour, Mark T. Bidwell, Michael D. Watmough, Robert G. Clark

Bibliographic record

VenueWildlife Society Bulletin · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Saskatchewan
FundersEnvironment and Climate Change CanadaInstitute for Wetland and Waterfowl Research, Ducks Unlimited Canada
KeywordsAbundance (ecology)WetlandHabitatEcologyWildlifeWaterfowlRange (aeronautics)Environmental scienceBiologyGeography

Abstract

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ABSTRACT Understanding how animals respond to changing habitat conditions can improve predictions about effects of environmental change and also inform conservation planning. We examined relationships between abundances of 5 common dabbling duck species breeding in the Canadian Prairie Pothole Region and basic wetland metrics. Pond area was a well‐supported predictor of duck abundance at the local scale of pond. Relationships for all 5 species varied with their respective regional duck and pond densities. In regions where duck densities were high, there were more ducks per pond; conversely, there were fewer ducks per pond in regions where pond densities were high, indicating that mechanisms influencing local habitat use were, in part, mediated by processes occurring at larger spatial scales. Although models explained small amounts of variation of duck abundance on a per pond basis, these models explained more variation when results were aggregated to the level of survey segment, indicating reasonable performance of models for estimating duck abundance over specific areas with known pond areas. Our results also indicated that the greatest increase in duck abundance with increasing pond size occurs at the low end of the range of pond sizes. It is relatively small wetlands that face the greatest threat of loss and degradation on the prairies; therefore, protection and conservation efforts need to focus on these wetlands if the objective is to increase or maintain populations of the duck species studied. © 2017 The Wildlife Society.

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)0.001
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 score0.047
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.036
GPT teacher head0.234
Teacher spread0.198 · 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

Citations12
Published2017
Admission routes3
Has abstractyes

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