Two cytotype niche shifts are of different magnitude in <i>Solidago gigantea</i>
Bibliographic record
Abstract
PREMISE: Polyploidy may serve to contribute to range size if autopolyploid cytotypes are adapted to differing ecological conditions. This study aims to establish the geographic distribution of cytotypes within the giant goldenrod (Solidago gigantea), and to assess whether cytotypes exhibit differing ecological tolerances and morphology. METHODS: A range-wide set of 629 Solidago gigantea individuals was obtained through field collecting, sampling from herbarium specimens, and incorporating existing chromosome counts. Cytotype of each unknown sample was estimated by observing allele numbers at twelve microsatellite loci, a strategy that was assessed by comparing estimated to known cytotype in 20 chromosome-counted samples. Abiotic ecological differentiation was assessed for two transitions: diploid-tetraploid and tetraploid-hexaploid. Morphological differentiation among cytotypes was assessed. RESULTS: Microsatellite repeat variation accurately estimated cytotype in 85% of samples for which ploidy was known. Applying this approach to samples of unknown ploidy established that the three cytotypes are non-randomly distributed. Although niche modeling and MANOVA approaches identified significant differences in macro-climatic conditions for both cytotype transitions, the tetraploid to hexaploid transition was more substantial. Leaf length and width did not differ among cytotypes. Although leaf vestiture exhibited strong trends, no absolute differences were observed among cytotypes. CONCLUSIONS: With the largest such study to date, we established niche transitions among giant goldenrod cytotypes of differing magnitudes. Collectively, this suggests that whole-genome duplication has contributed to Solidago gigantea's large range.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".