Seed traits and germination of native grasses and invasive forbs are largely insensitive to parental temperature and CO<sub>2</sub>concentration
Bibliographic record
Abstract
Abstract The structure and function of grassland ecosystems can be altered by a changing climate, including higher temperature and elevated atmospheric CO 2 concentration. Previous studies suggest that there is no consistent trend in seed germination and seedling recruitment as affected by these conditions. We collected seeds of two native and two invasive species over 6 years from a field study with elevated CO 2 (600 p.p.m.) and temperature (1.5/3.0°C day/night) on the mixed-grass prairie of Wyoming, USA. Seed fill, viability and mass were evaluated and germination tests were conducted under alternating temperatures in growth chambers. Thermal time requirements to reach 50% germination (θ 50 ) and base temperatures ( T b ) for germination were determined using thermal time models. Climate change conditions had limited effects on seed fill, viability and mass. The combination of CO 2 enrichment and warming increased germination of Bouteloua gracilis . Centaurea diffusa and Linaria dalmatica , two invasive species in this study, had the lowest θ 50 and T b required for germination among all the species studied. Although final germination percentages of these invasive species were not affected by treatments, previous studies reported increased seed production under future climate conditions, indicating that they could be more invasive at the regeneration stage in the future. We conclude that projected future temperature increases will have little effect on seed reproductive traits of native species. In addition, the distribution and abundance of B. gracilis and invasive species may be favoured by global climate change due to enhanced germination or seed production traits caused by elevated parental CO 2 and temperature conditions.
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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 | 0.000 | 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 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".