Conservation status of native tree species in British Columbia
Bibliographic record
Abstract
We assess the conservation status of all tree species in order to identify conservation gaps and prioritize genetic conservation efforts. A thorough assessment would consider genetic variation in each species across the species range, but for most tree species, such information is simply not available. For this reason, we used spatial variation associated with Biogeoclimatic Ecosystem Classification zones (BEC zones) representing different macroclimates as a proxy for adaptive genetic variation. We re-assessed the 2005 conservation status calculated in this manner using updated datasets collected in 2017, considered both in situ and ex situ conservation, and used an adjusted criterion for small-stature tree species. Results of our gap analysis revealed that overall, the native tree species in 89% of the conservation units (defined as species-by-biogeoclimatic-zone combinations) were well protected in situ. Of the 43 native tree species in the province, 12 species had conservation gaps in one or more biogeoclimatic zones. When in situ and ex situ conservation were considered jointly, the overall percentage of conservation units that were adequately protected improved to 91%. Needs for additional ex situ collections or in situ protection are discussed in terms of both BEC zones and individual species. In most cases, we recommend seed collection as the most feasible short-term option to cover gaps in protected area coverage.
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) | 0.010 | 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".