Trend in the Status of Breeding Bird Fauna in British Columbia, Canada, Based on the IUCN Red List Index Method
Bibliographic record
Abstract
The World Conservation Union (IUCN) Red List Index (RLI) is used to measure global trends in the status of biodiversity. We examined how the index might be used to measure the trend in the status of indigenous breeding birds in British Columbia between 1992 and 2006. We followed the RLI method described by Butchart et al. (2004, 2007) as closely as possible. Because IUCN Red List assessments at the regional level are not available in British Columbia, we used NatureServe S (subnational) ranking data. We calculated three index trend lines. The first two of these allowed us to compare an index based on our original data to one based on data that had been retrospectively corrected; the latter produced a smooth, flat line. A third trend line, based on the corrected data but excluding species new to province since 1947, produced a gently sloping downward trend. Ongoing immigration of bird species in and out of British Columbia added to the complexity of interpreting our regional RLI-type index, especially because our S-rank data did not incorporate transboundary "rescue" effects. Because the RLI is scaled so that the maximum value is based on a state in which all species are simultaneously ranked as least concern, it may exaggerate the highest potential status of intrinsically vulnerable species. A simpler, more intuitive graphic allows reporting that is less dependent on context. We believe the RLI approach holds useful innovation for an indicator of change in biodiversity within jurisdictional boundaries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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 teacher head, 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".