Forest migration outpaces tree species range shift across North America
Bibliographic record
Abstract
Abstract Mounting evidence suggests that geographic ranges of tree species worldwide are shifting under global environmental change, but little is known about forest migration—the shift in the geographic ranges of forest types—and how it differs from individual tree species migration. Here, based on in situ records of more than 9 million trees from 596,282 sample plots, we quantified and compared the migration patterns of forests and tree species across North America between 1970 and 2019. On average, forests migrated at a mean velocity of 205.2 km per decade, which is twice as fast as species-level migration (95.6 km per decade), and 12 times faster than the average of previous estimates (16.3 km per decade). Our findings suggest that as subtle perturbations in species abundance can aggregate to change an entire forest from one type to another, failing to see the forest for the trees may result in a gross underestimation of the impacts of global change on forest ecosystem functioning and services. With the first forest classification and quantification of forest migration patterns at a continental level, this study provides an urgently needed scientific basis for a new paradigm of adaptive forest management and conservation under a rapid forest migration.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".