Four decades of plant community change along a continental gradient of warming
Bibliographic record
Abstract
Many studies of individual sites have revealed biotic changes consistent with climate warming (e.g., upward elevational distribution shifts), but our understanding of the tremendous variation among studies in the magnitude of such biotic changes is minimal. In this study, we resurveyed forest vegetation plots 40 years after the initial surveys in three protected areas along a west-to-east gradient of increasingly steep recent warming trends in eastern Canada (Québec). Consistent with the hypothesis that climate warming has been an important driver of vegetation change, we found an increasing magnitude of changes in species richness and composition from west to east among the three parks. For the two mountainous parks, we found no significant changes in elevational species' distributions in the easternmost park (raw mean = +11.4 m at Forillon Park) where warming has been minimal, and significant upward distribution shifts in the centrally located park (+38.9 m at Mont-Mégantic), where the recent warming trend has been marked. Community Temperature Indices (CTI), reflecting the average affinities of locally co-occurring species to temperature conditions across their geographic ranges ("Species Temperature Indices"), did not change over time as predicted. However, close examination of the underpinnings of CTI values suggested a high sensitivity to uncertainty in individual species' temperature indices, and so a potentially limited responsiveness to warming. Overall, by testing a priori predictions concerning variation among parks in the direction and magnitude of vegetation changes, we have provided stronger evidence for a link between climate warming and biotic responses than otherwise possible and provided a potential explanation for large variation among studies in warming-related biotic changes.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".