Seed-based approach for identifying flora at risk from climate warming
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
In obligate seeding species, the germination niche is crucial for colonization and population survival. It is a high-risk phase in a plant's life cycle, and is directly regulated by temperature. Seeds germinate over a range of temperatures within which there is an optimum temperature, with thresholds above and below which no germination occurs. We suggest that abrupt changes in temperature associated with a warming climate may cause a disconnect between temperatures seeds experience and temperatures over which germination is able to occur, rendering obligate seeding species vulnerable to decline and extinction. Using a bidirectional temperature gradient system, we examined the thermal constraints in the germination niche of some geographically restricted species from the low altitude mountains of the Stirling Range, southern Western Australia, including seedlots from lowland populations of four of these species. We demonstrated that high temperatures are not a limiting factor for germination in some restricted species, signifying a lack of relationship between geographic range size and breadth of the germination niche. In contrast, we identified other restricted species, in particular Sphenotoma drummondii, as being at risk of recruitment failure as a consequence of warming: seeds of this species showed a strong negative relationship between percentage germination and increasing temperature above a relatively low optimum constant temperature (13°C). We found some ecotypic differences in the temperature profiles between seeds collected from montane or lowland populations of Andersonia echinocephala, and while specific populations may become more restricted, they are perhaps at less risk of extinction from climate warming. This seed-based approach for identifying extinction risk will contribute tangibly to efforts to predict plant responses to environmental change and will assist in prioritizing species for management actions, directing limited resources towards further investigations and can supplement bioclimatic modelling.
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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) | 0.049 | 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