The Biology and Ecology of Feral Alfalfa <i>(Medicago sativa</i> L.) and Its Implications for Novel Trait Confinement in North America
Bibliographic record
Abstract
Alfalfa (Medicago sativa) is an important forage crop worldwide. Apart from cultivated fields, alfalfa is also found along roadsides and in natural and semi-natural habitats. However, little information is available on the establishment capabilities of alfalfa in noncultivated areas and the potential of these founding populations to become feral. Some crop species have not lost all their wild characteristics during the domestication process and with several inherent traits favoring weediness, alfalfa could be one among those that can become feral. There is great interest in the feral potential of alfalfa, particularly due to the concerns that feral plants could act as genetic bridges and facilitate novel trait movement at the landscape level. Alfalfa is the first perennial, insect-pollinated crop to be genetically engineered and approved for unconfined release into the environment. This review investigates and compiles information in the literature that reveals the life history components that can influence ferality in alfalfa. Characteristics that can contribute to ferality in alfalfa include high genetic diversity, perenniality, quick regrowth potential, persistence, symbiotic nitrogen fixation, deep tap root system, drought and cold tolerance, and seed dormancy. With these traits, alfalfa is equipped to invade and dominate unmanaged habitats. Feral alfalfa populations can and will act as bridges for long-distance gene flow and facilitate the adventitious presence of novel traits in the environment. As such, feral populations will become a potential barrier for achieving coexistence of transgenic and nontransgenic alfalfa fields. Implications of ferality, including gene flow and hybridization with compatible wild relatives are also discussed in detail. This review serves as a resource for environmental risk assessment for the release of alfalfa containing novel traits.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".