Conservation prioritization based on past cascading climatic effects on genetic diversity and population size dynamics: Insights from a temperate tree species
Bibliographic record
Abstract
Abstract Aim The biogeographic history affects adaptive evolution by altering the pattern of genetic variation and provides the background upon which other evolutionary processes are operating. Assessment of the consequence of such eco‐evolutionary interactions is crucial to population's genetic diversity maintenance. Yet, considering how biogeographic and multiple evolutionary processes interact in complex environments to alter genetic diversity in conservation planning remains unresolved. Location The Pacific Northwest. Methods Herein I document the impact of geographic landscapes and past climatic fluctuations on the evolutionary processes that drive population divergence of Populus trichocarpa by assembling genomic, climatic and species occurrence data. Results Based on inferences of demographic history of the species and tests for niche divergence, results show that the British Columbia (BC)‐North and BC‐South populations are ancestral and subject to more recent bottlenecks than the Oregon population. Consistently, ecological niche modelling illustrates that compared to the Last Glacial Maximum (~21 Ka), the present niche suitability of the BC‐North and ‐South populations is overall marginally inferior to that of the Oregon population. However, genomic analysis demonstrates that the Oregon harbours the lowest genetic diversity, possibly due to an extended bottleneck experienced by the population. Model prediction indicates that in the 2050s, the impact of climate change is minor compared to the niche suitability of the species as a whole, but climate change will likely result in considerable genetic shifts over two generations especially in the Oregon and BC‐South populations, which will attenuate along a northward gradient. Main conclusions This study underpins the long‐lasting impact of demographic histories and natural selection on genetic diversity, rather than highlighting the consequence of recent demographic events (e.g. bottleneck in the Holocene epoch; ~12 Ka) potentially cascading to eroding genetic diversity and yielding conservation urgency.
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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 | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".