Phosphorus nutrition of phosphorus-sensitive Australian native plants: threats to plant communities in a global biodiversity hotspot
Why this work is in the frame
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Bibliographic record
Abstract
South-western Australia harbours a global biodiversity hotspot on the world's most phosphorus (P)-impoverished soils. The greatest biodiversity occurs on the most severely nutrient-impoverished soils, where non-mycorrhizal species are a prominent component of the flora. Mycorrhizal species dominate where soils contain slightly more phosphorus. In addition to habitat loss and dryland salinity, a major threat to plant biodiversity in this region is eutrophication due to enrichment with P. Many plant species in the south-western Australian biodiversity hotspot are extremely sensitive to P, due to a low capability to down-regulate their phosphate-uptake capacity. Species from the most P-impoverished soils are also very poor competitors at higher P availability, giving way to more competitive species when soil P concentrations are increased. Sources of increased soil P concentrations include increased fire frequency, run-off from agricultural land, and urban activities. Another P source is the P-fertilizing effect of spraying natural environments on a landscape scale with phosphite to reduce the impacts of the introduced plant pathogen Phytophthora cinnamomi, which itself is a serious threat to biodiversity. We argue that alternatives to phosphite for P. cinnamomi management are needed urgently, and propose a strategy to work towards such alternatives, based on a sound understanding of the physiological and molecular mechanisms of the action of phosphite in plants that are susceptible to P. cinnamomi. The threats we describe for the south-western Australian biodiversity hotspot are likely to be very similar for other P-impoverished environments, including the fynbos in South Africa and the cerrado in Brazil.
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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 | 0.000 | 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) | 0.000 | 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 it