Rapid latitudinal range expansion at cold limits unlikely for temperate understory forest plants
Bibliographic record
Abstract
Abstract We ask whether climate warming will be likely to trigger rapid northward range expansion for understory plants in the northeastern forests of North America at the temperate–boreal forest ecotone. We answer this question through a detailed analysis of contemporary occupancy patterns at cold range edges and by looking for patterns consistent with climate or other environmental (e.g., edaphic) limitations. We first identify each species' realized growing degree‐day niche to sample zones central, at the tail, or beyond the edge of this niche. We model habitat suitability, based on 11 nonclimate variables, for each species, and compare the availability of, and occupancy on, suitable sites across zones, with the assumption that a limiting climate is likely to result in decreased occupancy or abundance on otherwise suitable sites toward the range limit. We also check for evidence of shifts to warm microclimate conditions at the range limit as a potential indication of climate limitations. Based on our habitat models, we find that the availability of suitable sites declines across these three zones for most species, while occupancy increases on suitable sites at range edge, and abundance does not vary significantly. Some species shifted to sites with warm microclimate conditions; of these, several also declined in abundance suggesting climate limitations. We conclude, however, that for most species studied, suitable site availability appears to determine the northern edges of distribution and, consequently, warming may not necessarily lead to near‐term range expansions.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".