Reporting Australia’s forest biodiversity I: forest-dwelling and forest-dependent native species
Bibliographic record
Abstract
Species-level indicators based on the Montreal Process criteria and indicators framework are used to report Australia’s progress towards sustainable forest management, in national and international reporting of Australia’s forest biodiversity status and trends. This paper reviews the historical development of these indicators and related databases. A recent major development has been the establishment of a comprehensive suite of national inventory databases on Australia’s native forest-dwelling vertebrate fauna and vascular flora for reporting in the Australia’s State of the Forests Report series. Although these databases are incomplete, nearly 17 000 species records of vascular plants and over 2000 vertebrate species records have been assembled. Of the 2212 records of forest-dwelling vertebrate species, half (1101 species) are forest-dependent species that require a forest habitat for at least part of their lifecycle. Based on the frequency of habitat-use records, eucalypt open forest and eucalypt woodland forest are the most important habitat types for both forest-dwelling and forest-dependent vertebrate species. Monitoring of species varies nationally and across states and territories, with the most comprehensive approach undertaken in south-west Western Australia. Improved application of these databases to the reporting of species indicators will require improved collection of species records, inclusion of habitat data in records, and analysis of these records as time series with changing forest cover and condition. These databases also have application for informing forest-related indicators for the 2020 Aichi Biodiversity Targets of the Convention on Biological Diversity.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".