Understanding context dependence in the contribution of intraspecific variation to community trait–environment matching
Bibliographic record
Abstract
Intraspecific trait variation (ITV) plays a potentially important role in determining functional community composition across environmental gradients. However, the importance of ITV varies greatly among studies, and we lack a coherent understanding of the contexts under which to expect a high vs. low contribution of ITV to trait-environment matching among communities. Here we first elaborate a novel conceptual framework posing specific hypotheses and predictions about the environmental and ecological contexts underlying the contribution of ITV to community trait turnover. We then empirically test these predictions in understory herbaceous plant communities in a montane environment, for three functional traits (flowering phenology, specific leaf area, and height). We found that different components of trait variation mapped onto different environmental axes, specifically reporting a greater contribution of ITV along non-climatic axes (e.g., soil properties, light) than along the main climatic axis (i.e., elevation), as predicted by the hypothesis that phenotypic plasticity (a major source of ITV) is greatest in response to conditions varying at a small spatial scale. Based on a variant of the niche-variation hypothesis, we predicted that the importance of ITV would be greatest in the lowest-diversity portion of the elevational gradient (i.e., at high elevation), but this prediction was not supported. Finally, the generally strong intraspecific responses to the gradient observed across species did not necessarily give rise to a high contribution of ITV (or vice versa) given (1) an especially weak or strong response of a dominant species driving the community-level trend, (2) differences among species in the direction of trait-environment response cancelling out, or (3) relatively narrow portions of the gradient where individual species abundances were high enough to have an important impact on community-level trait means. Our research identifies contexts in which we can predict that local adaptation and phenotypic plasticity will play a relatively large role in mediating community-level trait responses to environmental 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".