Plant Identity Influences Decomposition through More Than One Mechanism
Bibliographic record
Abstract
Plant litter decomposition is a critical ecosystem process representing a major pathway for carbon flux, but little is known about how it is affected by changes in plant composition and diversity. Single plant functional groups (graminoids, legumes, non-leguminous forbs) were removed from a grassland in northern Canada to examine the impacts of functional group identity on decomposition. Removals were conducted within two different environmental contexts (fertilization and fungicide application) to examine the context-dependency of these identity effects. We examined two different mechanisms by which the loss of plant functional groups may impact decomposition: effects of the living plant community on the decomposition microenvironment, and changes in the species composition of the decomposing litter, as well as the interaction between these mechanisms. We show that the identity of the plant functional group removed affects decomposition through both mechanisms. Removal of both graminoids and forbs slowed decomposition through changes in the decomposition microenvironment. We found non-additive effects of litter mixing, with both the direction and identity of the functional group responsible depending on year; in 2004 graminoids positively influenced decomposition whereas in 2006 forbs negatively influenced decomposition rate. Although these two mechanisms act independently, their effects may be additive if both mechanisms are considered simultaneously. It is essential to understand the variety of mechanisms through which even a single ecosystem property is affected if we are to predict the future consequences of biodiversity loss.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".