Eco‐evolutionary contributions to community trait change in floating aquatic plants
Bibliographic record
Abstract
An entire community of organisms may become modified when its environment changes. These modifications can happen through physiological processes (plasticity), evolutionary processes (adaptation) or shifts in species composition (sorting). The outcome of these three sources of change constitutes the community's phenotypic response, but how they combine to drive community trait dynamics is not currently well understood. We have conducted a community selection experiment in which communities of short-lived floating aquatic plants were grown in a range of stressful conditions, and measured changes in their body size. Determinants of phenotypic change were assessed with a full community reciprocal transplant which led to estimates of the contributions of plasticity, adaptation, and sorting. Species were modified during the experiment by both plasticity and adaptation, but in either case the magnitude and direction of change differed among species. Sorting and adaptation were of equal magnitude but tended to act in opposite directions: in conditions where species with large fronds prevailed, each species evolved smaller fronds, and vice versa. We conclude that community trait dynamics cannot be understood simply by extrapolating the adaptive response of any single species to the whole community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 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".