Detritivore diversity promotes a relative contribution rate of detritus to the diet of predators in ponds
Bibliographic record
Abstract
Abstract Theory suggests that bottom‐up effects of resource diversity to upper trophic levels increases ecosystem functioning. In particular, energy flux from the detritus to other organisms in an ecosystem affects food web dynamics. To our knowledge, no empirical studies have examined how detritivore diversity alters the energy flux to upper trophic levels in a food web. Here we test the hypothesis that the greater diversity of litter‐consuming detritivores promotes energy flow between the resource and top predators in agricultural ponds using stable isotope analysis. We found that the diversity and abundance of detritivores had a significant positive effect on the relative contribution rate of detritus to the diet of predators, even after confounding effects were controlled for. In addition, the number of functional feeding groups of detritivores was significantly correlated with the contribution of detritus to the diet of predators, and particularly, high functional diversity of detritivores increased the energy flow from the detritus to the detritivores compared to the flow from the detritivores to the predators. It is likely that high functional diversity within species induces complementarity effects on decomposition and this may be a potential mechanism leading to diversity effects on the energy flow in detritus‐based food web. Our study is the first to demonstrate bottom‐up effects of detritivore diversity on energy flow in food webs.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".