Influence of landscape structure on the functional groups of an aphidophagous guild: Active-searching predators, furtive predators and parasitoids
Bibliographic record
Abstract
A lot of studies focusing on the effect of agricultural landscapes demonstrate that many arthropod species are influenced by landscape structure. In particular, non–crop areas and landscape diversity are often associated with a higher abundance and diversity of natural enemies in fields. Numerous studies focused on the influence of landscape structure on ground beetles, spiders and ladybeetles but few on other natural enemies or different functional groups. Thus, the objective of the present study was to determine the influence of landscape structure on the functional groups, i.e., active-searching predators, furtive predators and parasitoids of aphidophagous guilds. Natural enemies were sampled on milkweed infested with aphids, growing along the borders of ditches adjacent to cornfields. The sampling occurred weekly from June to September in 2006 and 2007, in the region of Lanaudière (Quebec, Canada). The landscapes within a radius 200 and 500 m around each site were analyzed. The abundance, richness and species composition (based on functional groups) of natural enemies were related to landscape structure. The results indicated that landscape structure explained up to 21.6% of the variation in natural enemy assemblage and confirm the positive effects of non-crop areas and landscape diversity. A lower influence of landscape structure on species composition was observed (6.4 to 8.8%) and varied greatly among the functional groups. Coccinellidae and furtive predators were the group most influenced by landscape structure. In conclusion, the influence of landscape varied greatly among the different species of the same functional group.
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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".