Climate refugia and migration requirements in complex landscapes
Bibliographic record
Abstract
All of today's species have proven their ability to cope with climate change during the glacial‐interglacial cycles of the Quaternary, but future migration requirements may be different regarding speed, direction, geographic barriers, and availability of nearby climate refugia. Here, we contribute a landscape‐level climatic analysis of postglacial vs. projected future migration requirements for 24 common western North American tree species. Using a recently developed velocity of climate change algorithm, we quantify required migration velocities for all populations of species to track climate habitat, based on projections from general circulation models for the 2080s and the last glacial maximum, 21 000 yr ago. Specifically, we ask if nearby climate refugia exist for at least some populations within species ranges and whether the current landscape position of species imply qualitatively different migration requirements in the future compared to those during glacial‐interglacial cycles. Results showed that velocities to reach the nearest climate refugia in the future still exceed the fastest reconstructed post‐glacial migration requirements, but not by orders of magnitude. Regarding landscape positions, we find a low correlation among past and future migration requirements ( r = 0.38), suggesting that qualitatively different migration patterns may emerge in the future for some species. Species identified as occupying landscape positions requiring disproportionally faster migration requirements in the future include whitebark pine, pinyon pine, and coast redwood. We discuss uncertainties of our analytical approach as well as implications for human‐assisted migration and conservation action to address climate change.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".