Assessing risks to ecosystems within biodiversity hotspots: a case study from southwestern <scp>A</scp>ustralia
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
Abstract The south west of W estern A ustralia is a global biodiversity hotspot that contains a suite of highly restricted and threatened ecosystems. In common with some other global hotspots, this region has high levels of alpha, beta and gamma diversity characterized by local endemism and spatial turnover of species. The region therefore includes a suite of highly localized species assemblages in complex mosaics across the landscape. Such landscapes pose particular challenges for assessing risks to biodiversity because the status of the most extensive species assemblages within broad scale assessment units tends to mask the status of those that are most restricted. Hence, risk assessments at different thematic scales may sometimes reveal different outcomes and salient threats. We examined these expectations by applying the IUCN R ed L ist criteria for ecosystems at a fine thematic scale to assess risks to shrublands on southern S wan C oastal P lain ironstones, one of the most restricted ecosystems in the region, distinguished by its component suite of endemic flora. The ecosystem was found to be critically endangered due to its declining distribution and restricted current extent in combination with threats, particularly weed invasion. These outcomes suggest two scaling effects when a broader suite of assemblages in the region are considered; the perceived levels of risk may be less extreme; and the main threatening processes that influence risk assessment outcomes rank differently in importance. Both effects are critical to future management to promote persistence of ecosystems, as the priorities and actions will vary between local and regional scales, as will their conservation outcomes. In this case the major needs are to limit vegetation clearing and water extraction and mitigate the invasion of weeds and impacts of disease. The relative emphasis on these strategies varies between local and regional scales.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it