Reporting Australia’s forest biodiversity I: forest-dwelling and forest-dependent native species
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it