A multi‐trait approach reveals the structure and the relative importance of intra‐ vs. interspecific variability in plant traits
Bibliographic record
Abstract
Summary 1. Functional traits have been extensively used to describe, group and rank species according to their functions. There is now growing evidence that intraspecific functional variability, as well as interspecific variability, can have significant effects on community dynamics and ecosystem functioning. A core hypothesis for the use of functional traits expressed as species means, that their intraspecific variability is negligible compared with their interspecific variability, has however been too rarely tested empirically. We then addressed four questions: Is intraspecific functional variability across species ranges negligible compared with interspecific variability? Are the major resource economics trade‐off and functional strategies robust to individual trait variability? Are species rankings or ordination robust across species ranges once considering intraspecific variability? Can species be discriminated by their leaf traits? 2. Using an environmentally stratified sampling design within an alpine catchment, we collected five functional traits for 13 common plant species with contrasting life histories and traits. Several populations from a range of environmental conditions were then sampled for each species across their ranges. 3. With an original combination of single‐trait and multi‐trait analyses, we highlighted a non‐negligible contribution of intraspecific variability to overall functional trait variability (∼30%). Although not affecting general and well‐known functional trade‐offs and strategies, intraspecific functional variability had the potential to alter species ordination and produced a functional continuum rather than a clear‐cut species classification. 4. Deciding whether intraspecific functional variability can be considered as negligible – species being represented by mean trait values –, or not – species being represented by multivariate trait distributions –, is an essential question for multiple ecological issues. However, this decision cannot be generic, but will depend on the studied system and selected traits and species, as well as on study objectives.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| 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".