Germination rates of weedy radish populations (<i><scp>R</scp>aphanus</i> spp.) altered by crop‐wild hybridisation, not human‐mediated changes to soil moisture
Why this work is in the frame
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Bibliographic record
Abstract
Summary Cultivated plants are known to readily hybridise with their wild relatives, sometimes forming populations with weedier life‐history strategies than their progenitors. Due to altered precipitation patterns from human‐induced global climate change, crop‐wild hybrid populations may have new and unpredictable environmental tolerances relative to parental populations, which would further challenge farming and land‐management weed control strategies. To recognise the role of seed dormancy variation in weed invasion, we compared seedbank dynamics of two cross‐type populations (wild radish, Raphanus raphanistrum , and crop‐wild hybrid radish, R. raphanistrum × R. sativus ) across a soil moisture gradient. In a seed‐burial experiment, we assessed relative rates of seed germination, dormancy and seed mortality over two years across cross types (crop‐wild hybrid or wild) and watering treatments (where water was withheld, equal to annual rainfall, or double annual rainfall). Weekly population censuses in 2012 and 2013 assessed the frequency and timing of seedling emergence within a growing season. Generally, germination rates were two times higher and seed dormancy was 58% lower in hybrid versus wild populations. Surprisingly, experimental soil moisture conditions did not determine seedbank dynamics over time. Yet, seed bank dynamics changed between years, potentially related to different amounts of annual rainfall. Thus, variation in seedbank dynamics may be driven by crop‐wild hybridisation rates and, potentially, annual variation in soil moisture conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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