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Record W4385473262 · doi:10.1016/j.rama.2023.07.002

Review of Conservation Challenges and Possible Solutions for Grassland Birds of the North American Great Plains

2023· article· en· W4385473262 on OpenAlexaff
Jacy Bernath‐Plaisted, Maureen D. Correll, Scott G. Somershoe, Angela M. Dwyer, Andy Bankert, Adam Beh, Humberto Berlanga, W. Alice Boyle, Lizardo Cruz‐Romo, T. Luke George, James R. Herkert, Nicola Koper, Alberto Macías‐Duarte, Arvind O. Panjabi, Oscar M. Ramírez-Flores, Barry G. Robinson, Irene Ruvalcaba-Ortega, Julie Sibbing, Erin H. Strasser, Mieke Titulaer, William E. Van Pelt, Tammy VerCauteren

Bibliographic record

VenueRangeland Ecology & Management · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Manitoba
FundersNatural Resources Conservation ServiceBobolink FoundationU.S. Department of AgricultureNational Science Foundation
KeywordsGrasslandHabitatEcologyGeographyAgroforestrySet-asidePopulationEnvironmental resource managementBiologyEnvironmental science

Abstract

fetched live from OpenAlex

North America's grassland birds remain in crisis despite decades of conservation efforts. This review provides an overview of factors contributing to these declines, as well as strategies and resources available to a diversity of stakeholders to help conserve grassland bird communities with an emphasis on the Great Plains—a grassland region of global ecological significance and a habitat stronghold for grassland birds. Grassland bird declines are driven by historical and continuing threats across the full annual cycle including grassland habitat loss, agriculture intensification, woody encroachment, and disruption of fire and grazing regimes. More recently, energy development activities, the use of neonicotinoid pesticides, and anthropogenic climate change have emerged as additional threats. While threats to grassland birds are numerous and often synergistic, possibilities for conservation are also diverse and multifaceted. Land set-aside programs, incentives and voluntary practices for producers, improved environmental management by energy and utility companies, and policy and regulation can all contribute to the conservation of these unique species. We suggest that future grassland bird research should focus on poorly studied aspects of the annual cycle, such as overwinter survival and habitat use, and the migratory period, which remains completely unexplored for many species. Filling these knowledge gaps may facilitate more sophisticated population modeling that can identify limiting factors and more effectively guide investment in conservation.

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 score0.037
Threshold uncertainty score0.480

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)0.0000.000

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 head0.031
GPT teacher head0.256
Teacher spread0.225 · 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
Published2023
Admission routes1
Has abstractyes

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