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Record W2993556344 · doi:10.1101/868356

Metrics for conservation success: using the ‘Bird-Friendliness Index’ to evaluate grassland and aridland bird community resilience across the Northern Great Plains ecosystem

2019· preprint· en· W2993556344 on OpenAlexaboutno aff
Nicole L. Michel, Curtis Burkhalter, Chad B. Wilsey, Matt Holloran, Alison G. Holloran, Gary Langham

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGrasslandHabitatGeographyEcologyBird conservationGrassland ecosystemEnvironmental resource managementAgroforestryEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Abstract Aim Evaluating conservation effectiveness is essential to protect at-risk species and to maximize the limited resources available to land managers. Over 60% of North American grassland and aridlands have been lost since the 1800s. Birds in these habitats are among the most imperiled in North America, yet most remaining habitats are unprotected. Despite the need to measure impact, conservation efforts on private and working lands are rarely evaluated, due in part to limited availability of suitable methods. Location Northern Great Plains Methods We developed a novel metric to evaluate grassland and aridland bird community response to habitat management practices, the Bird-Friendliness Index (BFI), consisting of density estimates of grassland and aridland birds weighted by conservation need and a functional diversity metric to incorporate resiliency. We used the BFI to inform three assessments: 1) a spatial prioritization to identify ecologically significant areas for grassland and aridland birds, 2) estimation of temporal trends in grassland and aridland bird community resilience, and 3) evaluation of the effects of land management practices on grassland and aridland bird communities. Results The most resilient bird communities were found in the Prairie Potholes region of Alberta, Saskatchewan, northern Montana, and North Dakota, and the lowest BFI values in the southern and western regions of the Northern Great Plains. BFI values varied little over time on average, but trends varied regionally, largely in response to interannual relative variability in grassland and aridland bird densities. Main conclusions BFI values increased in response to simulated habitat management, suggesting that practices recommended for use in bird-friendly grassland habitat management plans will increase the abundance and resilience of the grassland and aridland bird community, and will be detected using the BFI. The BFI is a tool by which conservationists and managers can carry out accountable conservation now and into the future.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.270
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2019
Admission routes1
Has abstractyes

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