Non‐random food‐web assembly at habitat edges increases connectivity and functional redundancy
Bibliographic record
Abstract
Habitat fragmentation dramatically alters the spatial configuration of landscapes, with the creation of artificial edges affecting community structure and dynamics. Despite this, it is not known how the different food webs in adjacent habitats assemble at their boundaries. Here we demonstrate that the composition and structure of herbivore-parasitoid food webs across edges between native and plantation forests are not randomly assembled from those of the adjacent communities. Rather, elevated proportions of abundant, interaction-generalist parasitoid species at habitat edges allowed considerable interaction rewiring, which led to higher linkage density and less modular networks, with higher parasitoid functional redundancy. This was despite high overlap in host composition between edges and interiors. We also provide testable hypotheses for how food webs may assemble between habitats with lower species overlap. In an increasingly fragmented world, non-random assembly of food webs at edges may increasingly affect community dynamics at the landscape level.
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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".