Code from: Metrics for conservation success: using the bird‐friendliness index to evaluate grassland and aridland bird community resilience across the Northern Great Plains ecosystem
Bibliographic record
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 imperilled 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 of North America. Methods: We developed a novel metric to evaluate grassland and aridland bird community response to habitat management, 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 identify ecologically significant areas for grassland and aridland birds and compared them with other prioritizations. Then, we used the BFI to evaluate the effects of simulated habitat management on grassland and aridland bird communities. Results: The most resilient bird communities were found in the Prairie Potholes region of Alberta, Saskatchewan and North Dakota and the lowest BFI values in the southern and western regions of the Northern Great Plains. BFI values were significantly greater in areas included in one or more prioritization, and increased with the number of prioritizations an area was included within. BFI values increased in response to simulated bird‐friendly habitat management. Main conclusions: Our findings suggest 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 that bird community responses to management will be detected using the BFI. The BFI is a tool by which conservationists and managers can carry out adaptive management and accountable conservation now and into the future.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.062 | 0.021 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".