Low genetic diversity, moderate local adaptation, and phylogeographic insights in <i>Cornus nuttallii</i> (Cornaceae)
Bibliographic record
Abstract
PREMISE OF THE STUDY: Genetic knowledge is completely lacking for Pacific dogwood (Cornus nuttallii), a western North American temperate tree that is pollinated and dispersed by biological vectors. We investigated how history, geography, and climate have affected population genetic structure, local adaptation, and the phylogeography of this species. METHODS: We examined patterns and levels of diversity in nuclear microsatellites (SSRs) and cpDNA haplotypes in populations from across the species range. We compared these results to population differentiation and genetic clines in phenotypic traits in a common garden. KEY RESULTS: Genetic diversity was low for both nuclear SSRs and cpDNA. There was a lack of population structure (F(ST) = 0.090) in the coastal portion of the species range, with estimates of population genetic diversity in microsatellite markers decreasing with latitude from California to British Columbia. A disjunct interior population in Idaho 450 km from the coastal range had the lowest diversity but the highest divergence of all populations studied. Only a single nucleotide polymorphism was discovered after sequencing 5547 base pairs in seven noncoding regions of cpDNA. Both cpDNA haplotypes were widely distributed throughout the species range. Quantitative variation among populations was moderate (0.11 ≤ Q(ST) ≤ 0.63), and weak but significant adaptive clines were found between quantitative traits and population climatic variables (0.09 ≤ R(2) ≤ 0.34). CONCLUSIONS: Cornus nuttallii likely faced a population bottleneck in a single southern refugium during the Last Glacial Maximum. Despite low genetic diversity, it is weakly to moderately locally adapted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".