Physical barriers and corridors in urban habitats affect colonisation and parasitism rates of a specialist leaf miner
Bibliographic record
Abstract
1. Urban environments are fragmented habitats characterised by the presence of physical barriers, which may negatively affect dispersal and colonisation by insect herbivores and their natural enemies. Conversely, plants growing along pavements may function as dispersal corridors, helping to moderate the harmful effects of resource patch isolation on organism movement and population persistence. 2. We experimentally tested the effects of walls as physical barriers to the dispersal of the leaf miner Liriomyza commelinae Frost and colonisation of its host plant, Commelina erecta L., in urban habitats. We also evaluated whether plants along pavements could act as corridors for this species. 3. We exposed experimental host plants to the leaf miner in houses with front gardens and back yards, the latter being completely surrounded by walls. The front gardens had walls but none separating them from the pavement. Previously mined plants were also exposed to parasitoids in the yards to determine parasitoid attack. 4. Liriomyza commelinae took longer to colonise back yards with higher walls, and the abundance of mined plants along pavements reduced the colonisation time. Leaf‐miner abundance was marginally affected by the yard type, and was lower in back yards. Cumulative parasitism rates decreased with increasing distance at which mined plants were placed from pavements. 5. Constructions act as physical barriers, having a negative impact on colonisation of host plants by leaf miners. The function of pavements as corridors seems to depend on the abundance of mined plants. Parasitism may be affected by distance from the corridor rather than physical barriers or other potential hosts.
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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 | 0.000 |
| 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) | 0.001 | 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".