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Record W1989367910 · doi:10.1002/jwmg.351

Composite analysis of black duck breeding population surveys in eastern North America

2012· article· en· W1989367910 on OpenAlexaboutno aff
Guthrie S. Zimmerman, John R. Sauer, William A. Link, Mark C. Otto

Bibliographic record

VenueJournal of Wildlife Management · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsnot available
Fundersnot available
KeywordsAnasTransectGeographyPopulationWaterfowlBreeding bird surveySurvey methodologyAerial surveySurvey data collectionBreeding pairPhysical geographyStatisticsEcologyCartographyHabitatDemographyBiologyMathematics

Abstract

fetched live from OpenAlex

Abstract Waterfowl are monitored in eastern Canada and the northeastern United States with 2 surveys: a transect survey from fixed‐wing aircraft and a plot survey conducted from helicopters. The surveys vary in extent, but overlap exists in a core area of 9 strata covering portions of all provinces from Ontario east to Newfoundland. We estimated population change for American black ducks ( Anas rubripes ) and mallards ( Anas platyrhynchos ) from these surveys using a log‐linear hierarchical model that accommodates differences in sample design and visibility associated with these survey methods. Using a combined analysis of the surveys based on total indicated birds, we estimate the American black duck population to be 901,700 (95% CI: 715,200–1,274,000) in 2011, with 526,900 (95% CI: 357,500–852,300) mallards in the surveyed area. Precision of estimates varies widely by species and region, with transect surveys providing less precise results than plot surveys for black ducks in areas of overlap. The combined survey analysis for black ducks in the eastern survey region produced estimates with an average yearly coefficient of variation (CV) of 12.1% for the entire area and an average CV of 6.9% in the plot survey area. Mallards, which had a more limited distribution in the region, had an average yearly CV of 22.1% over the entire region, and an average CV of 27.7% in the plot survey area. Hierarchical models provide a rich framework for analyzing and combining results from complex survey designs, providing useful spatial and temporal information on population size and change in these economically important species. © 2012 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 score0.040
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.072
GPT teacher head0.234
Teacher spread0.162 · 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

Citations29
Published2012
Admission routes1
Has abstractyes

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