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Record W2745985815 · doi:10.1002/jwmg.21326

The migratory bird treaty and a century of waterfowl conservation

2017· article· en· W2745985815 on OpenAlexaffabout
Michael G. Anderson, Ray T. Alisauskas, Bruce D. J. Batt, Robert J. Blohm, Kenneth F. Higgins, Matthew C. Perry, James K. Ringelman, James S. Sedinger, Jerome R. Serie, David E. Sharp, David L. Trauger, Christopher K. Williams

Bibliographic record

VenueJournal of Wildlife Management · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsEnvironment and Climate Change CanadaDucks Unlimited Canada
FundersU.S. Fish and Wildlife Service
KeywordsWildlifeIngenuityBird conservationConventionTreatyGeographyPopulationWildlife conservationWaterfowlPoliticsHabitatEcologyPolitical scienceEnvironmental resource managementEnvironmental planningSociologyLawBiologyEconomics

Abstract

fetched live from OpenAlex

ABSTRACT In the final decades of the nineteenth century, concern was building about the status of migratory bird populations in North America. In this literature review, we describe how that concern led to a landmark conservation agreement in 1916, between the United States and Great Britain (on behalf of Canada) to conserve migratory birds shared by Canada and the United States. Drawing on published literature and our personal experience, we describe how subsequent enabling acts in both countries gave rise to efforts to better estimate population sizes and distributions, assess harvest rates and demographic impacts, design and fund landscape‐level habitat conservation initiatives, and organize necessary political and regulatory processes. Executing these steps required large‐scale thinking, unprecedented regional and international cooperation, ingenuity, and a commitment to scientific rigor and adaptive management. We applaud the conservation efforts begun 100 years ago with the Migratory Bird Treaty Convention. The agreement helped build the field of wildlife ecology and conservation in the twentieth century but only partially prepares us for the ecological and social challenges ahead. © 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 score0.045
Threshold uncertainty score0.315

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 studies0.0000.000
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 head0.009
GPT teacher head0.219
Teacher spread0.209 · 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

Citations60
Published2017
Admission routes2
Has abstractyes

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