No selection for greater size in an introduced grass invading semiarid grassland
Bibliographic record
Abstract
Exotic species are often planted for restoration or to enhance production. Populations that expand from plantings may undergo selection in directions that differ from those produced by artificial selection prior to planting. Here, we test whether a highly productive grass, Agropyron cristatum (L.) Gaertn., introduced to the semiarid Great Plains of North America, evolves during invasion from seeded fields into native grassland. We grew individuals of A. cristatum from six seeded populations and 12 invading populations in 12 common gardens separated by 0.5–12 km for two growing seasons. Contrary to expectations, individuals from invading populations did not have significantly greater tiller number or growth (increase in tiller number) than did individuals from seeded populations, suggesting that they have not undergone evolution towards increased invasion ability through increased size or growth. Instead, there was a general trend for individuals from invading populations to have lower growth rates and fewer tillers when grown without neighbours. Large size or high growth rates arising from artificial selection prior to introduction may be disadvantageous to populations invading semiarid grassland on dry, nutrient-poor soils. In this case, evolution may have resulted in convergence between the relatively large planted species and the smaller native species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| 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".