Multi‐trophic metacommunity interactions mediate asynchrony and stability in fluctuating environments
Bibliographic record
Abstract
Abstract Environmental fluctuations influence patterns of synchrony and stability in species abundances. Most of our understanding of synchrony and stability stems from competitive community and metacommunity ecology, when in reality species interact in more complex ways. Therefore, there is a mounting need for the integration of multi‐trophic interactions into metacommunity ecology. In particular, knowledge is lacking on: (1) whether synchrony and stability respond to environmental fluctuations similarly under competitive and multi‐trophic metacommunities; (2) how synchrony and stability change across the hierarchical levels of a metacommunity; and (3) whether trophic groups differ in their contributions to synchrony and stability. Here, we address these questions through a complementary approach, using model simulations to derive theoretical expectations for the effects of environmental fluctuations on synchrony and stability, and a microcosm experiment to test observations against these expectations. We created spatially heterogeneous metacommunities populated by eight protist and one rotifer species organized in a multi‐trophic food‐web. We controlled environmental fluctuations so that they were spatially uncorrelated and species were assumed to respond differently to environmental conditions. We contrasted the control of constant environmental conditions to the effects of periodic environmental fluctuations. We show that environmental fluctuations can reduce synchrony between patches and increase stability, but can also decouple asynchrony between species and increase population and metapopulation variability. We discuss how some of these findings apply to both competitive and multi‐trophic metacommunities but changes are stronger in multi‐trophic metacommunities, and how trophic groups differ in their contributions to synchrony and variability.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".