Food‐web composition affects cross‐ecosystem interactions and subsidies
Bibliographic record
Abstract
1. Ecosystems may affect each other through trophic interactions that cross ecosystem boundaries as well as via the transfer of subsidies, but these effects can vary depending on the identity of species involved in the interaction. 2. In this study, we manipulated two terrestrial bromeliad-living spider species (Aglaoctenus castaneus, Corinna gr. rubripes) that have variable hunting modes, to test their individual and combined effects on aquatic invertebrate community structure and ecosystem processes (i.e. decomposition rate and nitrogen cycling). We predicted that these terrestrial predators can affect aquatic invertebrates and nutrient dynamics within water-filled bromeliads. 3. Aglaoctenus spiders reduced the richness, abundance and biomass of aquatic insect larvae via consumptive or non-consumptive effects on ovipositing terrestrial adults, but effects of the two spider species in combination were usually the linear average of their monoculture effects. In contrast, invertebrates with entirely aquatic life cycles were unaffected or facilitated by spiders. Spiders did not affect either net detritivore biomass or the flux of detrital nitrogen to the bromeliad. Instead, Corinna spiders contributed allochthonous nitrogen to bromeliads. 4. Our results provide the novel observations that predators in one ecosystem not only directly reduce taxa whose life cycles cross-ecosystem boundaries, but also indirectly facilitate taxa whose life cycles are entirely within the second ecosystem. This compensatory response between cross-ecosystem and within-ecosystem taxa may have led to an attenuation of top-down effects across ecosystem boundaries. In addition, our results add to a growing consensus that species identity is an important determinant of community structure and ecosystem functioning. Thus, the composition of both terrestrial and aquatic food webs may affect the strength of cross-ecosystem interactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".