Genotyping‐by‐sequencing informs conservation of Andean palms sources of non‐timber forest products
Bibliographic record
Abstract
Abstract Conservation and sustainable management of lineages providing non‐timber forest products are imperative under the current global biodiversity loss. Most non‐timber forest species, however, lack genomic studies that characterize their intraspecific variation and evolutionary history, which inform species' conservation practices. Contrary to many lineages in the Andean biodiversity hotspot that exhibit high diversification, the genus Parajubaea (Arecaceae) has only three species despite the genus' origin 22 million years ago. Two of the three palm species, P. torallyi and P. sunkha , are non‐timber forest species endemic to the Andes of Bolivia and are listed as IUCN endangered. The third species, P. cocoides , is a vulnerable species with unknown wild populations. We investigated the evolutionary relationships of Parajubaea species and the genetic diversity and structure of wild Bolivian populations. Sequencing of five low‐copy nuclear genes (3753 bp) challenged the hypothesis that P. cocoides is a cultigen that originated from the wild Bolivian species. We further obtained up to 15,134 de novo single‐nucleotide polymorphism markers by genotyping‐by‐sequencing of 194 wild Parajubaea individuals. Our total DNA sequencing effort rejected the taxonomic separation of the two Bolivian species. As expected for narrow endemic species, we observed low genetic diversity, but no inbreeding signal. We found three genetic clusters shaped by geographic distance, which we use to propose three management units. Different percentages of missing genotypic data did not impact the genetic structure of populations. We use the management units to recommend in situ conservation by creating new protected areas, and ex situ conservation through seed collection.
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".