The dual role of detritus as resource and habitat: integrating non-trophic processes to ecosystem dynamics
Bibliographic record
Abstract
The diversity of ecological interactions, trophic and non-trophic, is central to understand the assembly of communities. However, we have yet to integrate non-trophic to ecosystem-level processes such as recycling or habitat provisioning. Here we study a simple ecosystem model where the dual role of detritus as both resource and habitat allows defining ecosystem engineering from non-trophic processes interacting with the cycling of matter at the ecosystem level. Our results show how habitat and resource limitation of consumer growth from detritus can affect ecosystem stability. We further predict that non-trophic processes can stabilize ecosystems via (i) asynchrony between trophic and non-trophic interactions, (ii) weak trophic interactions emerging from non-trophic feedbacks, and (iii) coupling between non-trophic and recycling processes that control top-down vs bottom-up trophic regulation. Our results show ecosystem dynamics provides the relevant context to study the interplay between trophic and non-trophic processes
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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".