The effects of salt, manganese, and density on life history traits in <i>Hesperis matronalis</i> L. from oldfield and roadside populations
Bibliographic record
Abstract
Plant communities in the verges of major roadways (roadsides) are similar to those of abandoned farm fields undergoing succession (oldfields). However, roadsides are subject to distinctive stresses. Here, we look at local adaptation in Hesperis matronalis L. to salinity and manganese (Mn). Plants collected from three roadside and three oldfield populations were grown in a greenhouse under controlled, high-salinity, and high-Mn conditions, and several life history traits were measured. In addition, we imposed a density treatment after vernalization. Mortality was high in both the salt (43% survival) and Mn treatments (53% survival) compared with the control (71% survival). Distinct family, population, and site variation was found in measures of plant size. There were also family-level differences in response to soil treatments. However, none of our results were consistent with local adaptation. In general, larger plants were more likely to bolt, and oldfield plants were less likely to bolt than roadside plants in all treatments (in the low-density treatment, 56% of roadside plants had bolted compared with only 16% of oldfield plants). We found that the high-density treatments resulted in earlier bolting and longer internodes, a result consistent with the shade avoidance hypothesis.Key words: biennial, salinity, phenotypic plasticity, heavy metal, local adaptation.
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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) | 0.001 | 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".