First Nations’ interactions with underground storage organs in southwestern Australia, a Mediterranean climate Global Biodiversity Hotspot
Bibliographic record
Abstract
Abstract Aims and background Underground storage organs (USOs) have long featured prominently in human diets. They are reliable year-round resources, especially valuable in seasonal climates. We review a significant but scattered literature and oral recounts of USOs utilised by Noongar people of the Southwest Australian Floristic Region (SWAFR). USOs are important to First Nations cultures in other geophyte-rich regions with Mediterranean climate, with specialist knowledge employed, and productive parts of the landscape targeted for harvest, with likely ecological interactions and consequences. Methods We have gathered Noongar knowledge of USOs in the SWAFR to better understand the ecological role of Noongar-USO relationships that have existed for millennia. Results We estimate that 418 USO taxa across 25 families have Noongar names and/or uses. Additionally, three USO taxa in the SWAFR weed flora are consumed by Noongar people. We found parallels in employment of specific knowledge and targeted ecological disturbance with First Nations’ practice in other geophyte-rich floristic regions. We found that only in 20% of cases could we identify the original source of recorded USO knowledge to an acknowledged Noongar person. Conclusion This review identified that traditional Noongar access to USOs is taxonomically and geographically extensive, employing specific knowledge and technology to target and maintain resource rich locations. However, we also found a general practice of ‘extractive’ documentation of Noongar plant knowledge. We identify negative implications of such practice forNoongar people and SWAFR conservation outcomes and assert ways to avoid this going forward, reviving Noongar agency to care for traditional Country.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".