Controlled temperature contrasts of three native and one highly invasive annual plant species in California
Bibliographic record
Abstract
Plant responses to changes in temperature can be a key factor in predicting the presence and managing invasive plant species while conserving resident native plant species in dryland ecosystems. Climate can influence germination, establishment, and seedling biomass of both native and invasive plant species. We tested the hypothesis that common and widely distributed native and an invasive plant species in dryland ecosystems in California respond differently to increasing temperatures. To test this, we examined the effects of temperature variation on germination, establishment, and per capita seedling biomass of three native and one invasive plant species (Bromus rubens) in independent 6 week growth trial experiments in a controlled greenhouse. Higher relative temperatures reduced the germination and establishment of the tested invasive species and two tested native species, however, per capita biomass was not significantly affected. Specifically, germination and establishment of the invasive species B. rubens and the native species Phacelia tanacetifolia was significantly reduced. This invasive species can often outcompete natives, but increasing temperature could potentially shift the balance between the germination and establishment of natives. A warming climate will likely have negative impacts on native annual plant species in California tested here because increasing temperatures can co-occur with drought. This study shows that our tested native annual plant species tested here have some resilience to relatively significant increases in temperature, and this can favor at least one native species relative to at least one highly noxious invasive plant species.
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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 | 0.001 |
| 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".