Inter- and intra-population variation in seedling performance of Rio Grande cottonwood under low and high salinity
Bibliographic record
Abstract
The Rio Grande watershed ecosystem has been increasingly threatened since the construction of dams and severe channelization in the past century. Rio Grande cottonwood (Populus deltoides var. wislizenii (S. Wats.) Eckenw.) has been suffering stress and high mortality rates with decreased water availability and increased salinity levels. Genetic variation in salt tolerance has been documented in adult cottonwoods, and we hypothesized that these traits might be heritable. This potential heritable genetic variation in seedling offspring might be advantageous in reforestation efforts along the Rio Grande. We screened four New Mexican Rio Grande populations for seedling genotypes that might be salt tolerant and correlated seedling performance under both high- and low-salt treatments with the physiological performance of their open-pollinated family. For all populations, we found significant stunting effects of high salinity on mean leaf size, plant height, total plant mass, root mass, and shoot mass, with no effects on chlorophyll content (as measured by a Minolta SPAD-502 meter) or root/shoot ratio. Although there were no significant differences between the four populations, there were highly significant differences between open-pollinated families within each site. In addition, at one site (San Antonio), genetically based open-pollinated family physiology, as measured in a common garden, was significantly correlated with seedling performance, especially under low-salt conditions. This indicates these traits are heritable, and adult salt tolerance may convey an advantage in offspring establishment under high-salt 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) | 0.001 | 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".