Germination sensitivities to water potential among co-existing C3 and C4 grasses of cool semi-arid prairie grasslands
Bibliographic record
Abstract
An untested theory states that C4 grass seeds could germinate under lower water potentials (Ψ) than C3 seeds. We used hydrotime modelling to study seed water relations of C4 and C3 Canadian prairies grasses to address both Ψ divergent sensitivities and germination strategies along a risk-spreading continuum of responses to limited water. C4 grasses were Bouteloua gracilis, Calamovilfa longifolia and Schizachyrium scoparium; C3 grasses were Bromus carinatus, Elymus trachycaulus, Festuca hallii and Koeleria macrantha. Hydrotime parameters were obtained after incubation of non-dormant seeds under different Ψ PEG 6000 solutions. A t-test between C3 and C4 grasses did not find statistical differences in population mean base Ψ (Ψb(50)). We found idiosyncratic responses of C4 grasses along the risk-spreading continuum. B. gracilis showed a risk-takers strategy of a species able to quickly germinate in a dry soil due to its low Ψb(50) and hydrotime (θH). The high Ψb(50) of S. scoparium indicates it follows the risk-averse strategy so it can only germinate in wet soils. C. longifolia showed an intermediate strategy: the lowest Ψb(50) yet the highest θH. K. macrantha which thrives in the driest habitats showed the highest Ψb(50) suggesting a risk-averse strategy for a C3 species. Other C3 species showed intermediate germination patterns in response to Ψ relative to C4 species. Our results indicate that grasses display germination sensitivities to Ψ across the risk-spreading continuum of responses. Then seed water relations may be poor predictors to explain C3-C4 grasses differential recruitment and distribution in the Canadian prairies.
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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 | 0.000 | 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 | 0.001 | 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) | 0.001 | 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".