Host-parasitoid network in extreme conditions: the case of cereal aphids in wheat crops in Saskatchewan, Canada
Bibliographic record
Abstract
In agricultural areas, the climatic conditions at the northern limit of crop cultures could impact pest regulation. In this paper, we study the aphid-parasitoid-hyperparasitoid network in cereal fields around Saskatoon (SK, Canada), one of the most harsh climatic conditions for cereal crops in the world, with an extremely short growing season. We have inves- tigated the aphid-parasitoid-hyperparasitoid species relative abundances over two consecutive years. In 2014, a cold spring year, aphids were only found late in the growing season, and their arrival probably corresponded to late Southern winds. In 2015, aphids, parasitoids and hyperparasitoids arrived in the cereal fields in July and August, whereas the cereal harvest is typically complete by the end of the month of August. Three species of primary parasitoids were found for a total parasitism rate of 7.62%, and four genera of hyperparasitoids, with a hyperparasitism rate of 20.1%. There were 87.4% apterous aphids, and the proportion of apterous and winged (alate) aphids did not differ among the 3 aphid species, or among use by parasitoid species and hyperparasitoid species. The sex ratio of parasitoids in the complex was biased towards females for most of the species. In areas with extreme weather conditions and short growing seasons, effective biocontrol through para- sitism is limited, although the synchronization level of parasitoids to their aphid hosts is high. We discuss the consequences of the limited length of the growing season on the provision of ecosystem services and on the seasonal ecology of insects of agronomic interest. We also provide information about morphological criteria for identification of parasitoids from the genus Aphidius.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".