SELECTION ON LEAF ECOPHYSIOLOGICAL TRAITS IN A DESERT HYBRID HELIANTHUS SPECIES AND EARLY-GENERATION HYBRIDS
Bibliographic record
Abstract
Leaf ecophysiological traits related to carbon gain and resource use are expected to be under strong selection in desert annuals. We used comparative and phenotypic selection approaches to investigate the importance of leaf ecophysiological traits for Helianthus anomalus, a diploid annual sunflower species of hybrid origin that is endemic to active desert dunes. Comparisons were made within and among five genotypic classes: H. anomalus, its ancestral parent species (H. annuus and H. petiolaris), and two backcrossed populations of the parental species (designated BC2ann and BC2pet) representing putative ancestors of H. anomalus. Seedlings were transplanted into H. anomalus habitat at Little Sahara Dunes, Utah, and followed through a summer growing season for leaf ecophysiological traits, phenology, and fitness estimated as vegetative biomass. Helianthus anomalus had a unique combination of traits when compared to its ancestral parent species, suggesting that lower leaf nitrogen and greater leaf succulence might be adaptive. However, selection on leaf traits in H. anomalus favored larger leaf area and greater nitrogen, which was not consistent with the extreme traits of H. anomalus relative to its ancestral parents. Also contrary to expectation, current selection on the leaf traits in the backcross populations was not consistently similar to, or resulting in evolution toward, the current H. anomalus phenotype. Only the selection for greater leaf succulence in BC2ann and greater water-use efficiency in BC2pet would result in evolution toward the current H. anomalus phenotype. It was surprising that the action of phenotypic selection depended greatly on the genotypic class for these closely related sunflower hybrids grown in a common environment. We speculate that this may be due to either phenotypic correlations between measured and unmeasured but functionally related traits or due to the three genotypic classes experiencing the environment differently as a result of their differing morphology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".