Genetic differentiation and precolonial Indigenous cultivation of hazelnut ( <i>Corylus cornuta</i> , Betulaceae) in western North America
Bibliographic record
Abstract
Cultivation studies evaluating land-use histories and coevolutionary dynamics between humans and plants focus predominantly on domesticated species. Traditional anthropological divisions of “foragers” and “farmers” have shaped our understanding of ancient cultivation practices but have several limitations, including how people stewarded and managed nondomesticated species. To investigate the long-term effects of plant management in the Pacific Northwest, this study focuses on beaked hazelnut ( Corylus cornuta ) which has a long, precolonial history of management, transportation, and cultivation in British Columbia (BC, Canada). In particular, isolated hazelnut populations in northwestern BC are thought to be the result of historical transplanting and management. We sampled individual hazelnuts (n = 219) representing three distinct regions in and assessed 9,650 genome-wide SNPs identified with nextRAD genotyping-by-sequencing libraries to test for population genetic structure. We used linear measurements of individuals to assess morphological phenotypes and to identify variation between individuals and lineages. These data reveal shared genetic clusters in distant and disjunct northwestern and interior regions consistent with the movement of humans across the landscape. We also find several small genetically distinct populations in the northwestern region. The Genetic structure of hazelnut in the previously labeled “disjunct” region in Gitxsan, Ts’msyen, and Nis g a’a homelands is consistent with the enduring influence of people on the distribution of purportedly “wild” plant species. Our results support the hypothesis that hazelnut was likely transplanted long distances and also managed in situ. This study highlights the often-overlooked agency of Indigenous Peoples in shaping species range distributions in North America.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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 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".