An inventory of crop wild relatives and wild‐utilized plants in Canada
Bibliographic record
Abstract
Abstract In the face of global pressures of change and biodiversity loss, crop wild relatives (CWR) and wild‐utilized species (WUS) urgently require conservation attention. To advance conservation, we assembled a national inventory of CWR and WUS in Canada. To assess current ex situ conservation of these plant species, we gathered a virtual metacollection of accession data from botanical gardens and national genebanks. The inventory includes 779 CWR and WUS taxa (658 distinct species), with 263 (222 distinct species) that are related to food crops of national and global importance such as blueberry (Vaccinium corymbosum L.), apple (Malus domestica (Suckow) Borkh.), sunflower (Helianthus annuus L.), and saskatoon (Amelanchier spp.). Sixty‐one food crop relatives are prioritized for breeding potential, and sixteen due to conservation threats. Although most food crop CWR are represented in ex situ collections (91% of species), representation of within‐species diversity is low (median = 5% of Canadian ecogeographic types represented per species). Poor representation of within‐species diversity demands an integrative conservation strategy that emphasizes in situ protection, especially focusing on wild populations in Canada's southern ecoregions where diversity is concentrated. While genebank collections represent higher accession counts per species, botanical gardens include living collections of fruit crop relatives and other woody perennials that are well situated to raise broader awareness of CWR and WUS. To promote further conservation action, we present a web application that enables conservation planners and practitioners to identify local CWR and WUS and to identify within‐species ecogeographic types that are underrepresented in ex situ conservation systems.
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 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 | 0.006 | 0.012 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".