Assisted species migration and hybridization to conserve cold‐adapted plants under climate change
Bibliographic record
Abstract
Temperature rise due to climate change is putting many arctic and alpine plants at risk of extinction because their ability to react is outpaced by the speed of climate change. We considered assisted species migration (ASM) and hybridization as methods to conserve cold-adapted species (or the genes thereof) and to minimize the potential perturbation of ecosystems due to climate change. Assisted species migration is the deliberate movement of individuals from their current location to where the species' ecological requirements will be matched under climate projections. Hybridization refers to crossbreeding of closely related species, where for arctic and alpine plants, 1 parent is the threatened cold-adapted and the other its reproductively compatible, warm-adapted sibling. Traditionally, hybridization is viewed as negative and leading to a loss of biodiversity, even though hybridization has increased biodiversity over geological times. Furthermore, the incorporation of warm-adapted genes into a hybrid may be the only means for the persistence of increasingly more maladapted, cold-adapted species. If approached with thorough consideration of fitness-related parameters of the source population and acknowledgement of the important role hybridization has played in shaping current biodiversity, ASM and hybridization could help save partial or whole genomes of key cold-adapted species at risk due to climate change with minimal negative effects on ecosystem functioning.
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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) | 0.006 | 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 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".