Genome-wide SNP diversity in natural and cultivated populations informs restoration ecology with three <i>Calamagrostis</i> species from the Northwest Territories of Canada
Bibliographic record
Abstract
There is growing demand for data-driven frameworks to guide robust plant restoration strategies in response to anthropogenic disturbances. Several seed-sourcing (i.e., provenancing) strategies have been proposed, which balance the use of locally adapted genotypes against mixed genotypes to reduce mutation load or assist migration to anticipate future climate scenarios. However, taxonomic uncertainty and lack of data characterizing genetic differentiation and gene flow have hindered provenancing strategies for many ecologically important non-model plant species, especially those in remote but vulnerable regions like the boreal forests of northern Canada. To guide provenancing strategies following anthropogenic disturbance in Canada's Northwest Territories, we characterize species-specific markers, population structure and hybridization among three Calamagrostis species. Double digest RAD sequencing (ddRAD) resulted in 2951 polymorphic loci across 27 individuals, which we used to design loci for genotyping in thousands by sequencing (GT-seq), a cost-efficient target loci approach resulting in 256 polymorphic loci across 93 individuals from wild C. canadensis, C. stricta ssp. inexpansa and C. purpurascens seed accessions. To help define the scale of 'local' populations for seed sourcing, we characterized geographic variation and population structure among 57 field-collected seed accessions. We also assessed genetic relationships of wild C. canadensis to 69 individuals across eight commercially maintained cultivars used in restoration projects. We found that GT-seq yields similar genetic differentiation patterns as common neutral molecular marker approaches like ddRAD-seq. Specifically, we resolve morphologically misidentified individuals, identify genetic hybrids and characterize the scale of genetic isolation-by-distance. Finally, we determined that three cultivar seed sources were genetically similar to southern wild individuals, whereas five cultivars aligned with northern wild individuals of C. canadensis in the Northwest Territories of Canada. Overall, our results highlight the benefits of cost-effective methods for genome-wide multi-locus genotyping to inform provenancing best-practices and support more effective and sustainable restoration efforts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".