Spatial trophic cascades in communities connected by dispersal and foraging
Bibliographic record
Abstract
Pairwise interactions between species have both direct and indirect consequences that reverberate throughout the whole ecosystem. In particular, interaction effects may propagate in a spatial dimension, to localities connected by organismal movement. Here we study the propagation of interaction effects with a spatially explicit metacommunity model, where local sites are connected by dispersal, foraging, or by both types of movement. We show that indirect pairwise effects are, in most cases, of the same sign as direct effects if localities are connected by dispersing species. However, if foraging is prevalent, this correspondence is broken, and indirect effects between species often have a different sign than direct effects. This highlights the importance of indirect interactions across space and their inherent unpredictability in complex settings with species foraging across local patches. Further, the effect of a species over another in a local patch does not necessarily correspond to its effect at the metacommunity scale; this correspondence is again mediated by the type of movement across localities. Every species, despite their trophic position or spatial range, displays a non-zero net effect over every other species in our model metacommunities. Thus we show that local dynamics and local interactions between species can trigger indirect effects all across the set of connected patches, and these effects have a distinct signature depending on whether the prevalent connection between patches is via dispersal or via foraging. However, the magnitude of this effect between any two species strongly decays with the distance between them. These theoretical results strengthen the importance of considering indirect effects across species at both the community and metacommunity levels, highlight the differences between types of movement across locations, and thus open novel avenues for the study of interaction effects in spatially explicit settings.
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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) | 0.006 | 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".