Biomass compensation and plant responses to 7 years of plant functional group removals
Bibliographic record
Abstract
Question: What is the role of functional group identity in determining community composition and dynamics? Location: A natural grassland in Yukon Territory, Canada. Methods: We selectively removed single plant functional groups (graminoids, forbs, legumes) to examine their effects on biomass compensation, the distribution of biomass among common and rare colonizing species, and plant species richness and diversity. Removals were conducted across two environmental treatments (fertilization and fungicide) to test if biomass compensation was context-dependent. Biomass was estimated non-destructively using point-intercept sampling. Results: When graminoids or legumes were continuously removed, there was full biomass compensation by the remaining functional groups after 5 years, but only partial compensation when forbs were removed. Biomass compensation depended on the colonizing functional group; forbs showed no increase in biomass until 5 years after the removal of any functional group, but graminoids colonized quickly after removals. After any removal, the dominant species within each remaining functional group showed no compensatory growth, whereas the first subdominant forb and graminoid both increased in biomass. Rare species had a delayed response to removals; rare species biomass only increased beginning 5 years after removals. Context dependence was observed only in the response of subdominant species to removals, and these responses did not translate into context-dependent effects on total estimated biomass. Conclusion: We show that the effects of losing a plant functional group depends both on the identity of the group removed and on the species remaining. In this northern grassland, most compensatory growth was by the subdominant species, which may determine the direction of community development in the long term.
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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 | 0.000 | 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 | 0.000 |
| 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".