Trophic island biogeography drives spatial divergence of community establishment
Bibliographic record
Abstract
Food webs assemble via the interacting constraints of dispersal limitation and bottom‐up trophic dependencies where consumers can only establish after their resources have arrived. These factors can affect assembly by influencing the expression of the regional species pool in local patches, but how this unfolds mechanistically remains unclear. Here, we use a large‐scale grassland meta‐community experiment to demonstrate how the independent influences of spatial factors and bottom‐up constraints on insect trophic guilds interact to create divergent local insect communities. Bottom‐up trophic dependencies tightly controlled the composition and abundance of specialist trophic guilds, resulting in different communities among islands because producer communities were mainly determined by patch size contingencies. Spatial isolation controlled the composition and abundance of generalist trophic guilds, resulting in different insect communities among islands based on distance from mainland. These results demonstrate that neither diet‐based constraints nor the spatial characteristics of islands can predict the early structure of locally assembling food webs, with their establishment deriving instead from interactions between both 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 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".