Trophic interactions determine the effects of drought on an aquatic ecosystem
Bibliographic record
Abstract
Species interactions can be important mediators of community and ecosystem responses to environmental stressors. However, we still lack a mechanistic understanding of the indirect ecological effects of stress that arise via altered species interactions. To understand how species interactions will be altered by environmental stressors, we need to know if the species that are vulnerable to such stressors also have large impacts on the ecosystem. As predators often exhibit certain traits that are linked to a high vulnerability to stress (e.g., large body size, long generation time), as well as having large effects on communities (e.g., top-down trophic effects), predators may be particularly likely to mediate ecological effects of environmental stress. Other functional groups, like facilitators, are known to have large impacts on communities, but their vulnerability to perturbations remains undocumented. Here, we use aquatic insect communities in bromeliads to examine the indirect effects of an important stressor (drought) on community and ecosystem responses. In a microcosm experiment, we manipulated predatory and facilitative taxa under a range of experimental droughts, and quantified effects on community structure and ecosystem function. Drought, by adversely affecting the top predator, had indirect cascading effects on the entire food web, altering community composition and decomposition. We identified the likely pathway of how drought cascaded through the food web from the top-down as drought -->predator --> shredder --> decomposition. This stress-induced cascade depended on predators exhibiting both a strong vulnerability to drought and large impacts on prey (especially shredders), as well as shredders exhibiting high functional importance as decomposers.
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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 | 0.000 |
| 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".