Leaf‐trait responses to environmental gradients in moorland communities: contribution of intraspecific variation, species replacement and functional group replacement
Bibliographic record
Abstract
Abstract The values of many important traits of plants in a community change along environmental gradients. Such changes may involve intraspecific variation and replacement by species that have different trait values. We hypothesized that they also involve the variation within and among functional groups (FGs) to the environmental dependence of trait values at the community level. We studied environmental dependence of trait values in 27 moorlands at various scales and analyzed to what extent intraspecific variation, species replacement within FGs and FG replacement contribute to the gradient of community trait values. The community structure in moorlands was influenced mainly by two environmental factors: temperature and water condition. Plants inhabiting sites with low temperature and low‐pH generally tended to have lower maximum leaf height, greater leaf mass per area, and smaller leaf size. At the community level, site‐mean of maximum leaf height and leaf size generally increased with increasing temperature and water pH. Our analysis demonstrated that the relative contributions of intraspecific variation, species replacement within FGs and FG replacement differed depending on combinations of the traits and environments. The contribution of FG replacement varied considerably among cases (0.6–34.5 %). Species replacement within FGs, which has received little attention in previous studies, was most responsible for the community‐level changes (31.6–65.3 %) and intraspecific variation also made a large contribution (22.9–57.9 %). Understanding such various mechanisms involving intraspecific variation and species replacement should help us better predict how the structure and functioning of moorland plant communities will respond to climate change.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".