Climate or migration: what limited <scp>E</scp>uropean beech post‐glacial colonization?
Bibliographic record
Abstract
Abstract Aim Despite the recent improvements made in species distribution models ( SDMs ), assessing species' ability to migrate fast enough to track their climate optimum remains a challenge. This study achieves this goal and demonstrates the reliability of a process‐based SDM to provide accurate projections by simulating the post‐glacial colonization of E uropean beech. Location E urope. Methods We simulated the post‐glacial colonization of European beech over the last 12,000 years by coupling a process‐based SDM ( PHENOFIT ) and a new migration model based on G ibbs point processes, both parameterized with modern ecological data. Simulations were compared with palaeoarchives and phylogeographic data on E uropean beech. Results Model predictions are consistent with palaeoarchives and phylogeographic data over the Holocene. The results suggest that post‐glacial expansion of E uropean beech was limited by climate on its north‐eastern leading edge, while limited by its migration abilities on its north‐western leading edge. The results show a mean migration rate of beech varying from 270 m yr −1 to 280 m yr −1 and a maximum migration rate varying from 560 m yr −1 to 630 m yr −1 , when limited and not limited by climate, respectively. They also highlight the relative contribution of known and suspected glacial refugia in present beech distribution and confirm the results of phylogeographic studies. Main conclusions For the first time, we were able to reproduce accurately the colonization dynamics of E uropean beech during the last 12 kyr using a process‐based SDM and a migration model, both parameterized with modern ecological data. Our methodology has allowed us to identify the different factors that affected European beech migration during its post‐glaciation expansion in different parts of its range. This method shows great potential to help palaeobotanists and phylogeographers locate putative glacial refugia, and to provide accurate projections of beech distribution change in the future.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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; both teacher heads agree on what is shown here.
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".