Below‐ground biotic interactions moderated the postglacial range dynamics of trees
Bibliographic record
Abstract
Tree range shifts during geohistorical global change events provide a useful real-world model for how future changes in forest biomes may proceed. In North America, during the last deglaciation, the distributions of tree taxa varied significantly as regards the rate and direction of their responses for reasons that remain unclear. Local-scale processes such as establishment, growth, and resilience to environmental stress ultimately influence range dynamics. Despite the fact that interactions between trees and soil biota are known to influence local-scale processes profoundly, evidence linking below-ground interactions to distribution dynamics remains scarce. We evaluated climate velocity and plant traits related to dispersal, environmental tolerance and below-ground symbioses, as potential predictors of the geohistorical rates of expansion and contraction of the core distributions of tree genera between 16 and 7 ka bp. The receptivity of host genera towards ectomycorrhizal fungi was strongly supported as a positive predictor of poleward rates of distribution expansion, and seed mass was supported as a negative predictor. Climate velocity gained support as a positive predictor of rates of distribution contraction, but not expansion. Our findings indicate that understanding how tree distributions, and thus forest ecosystems, respond to climate change requires the simultaneous consideration of traits, biotic interactions and abiotic forcing.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".