Assessing the current and future biological control potential of <i>Trichogramma ostriniae</i> on its hosts <i>Ostrinia furnacalis</i> and <scp> <i>Ostrinia nubilalis</i> </scp>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Understanding interactions between biocontrol agents and their pest hosts under climate change should assist implementation of biocontrol strategies, by identifying appropriate biocontrol agents for release or determining the optimal timing of releases. Species distribution models (SDMs) were applied to evaluate the distributions of Trichogramma ostriniae and its native host, Ostrinia furnacalis, in southeastern Asia, and a non-native host, Ostrinia nubilalis, in a novel range, North America, using MAXENT and CLIMEX modelling approaches. RESULTS: The models led to similar predictions about the expected distribution of the two species in Asia, and emphasized likely mismatches between host and natural enemy. Trichogramma ostriniae was predicted to occur in the summer corn region of China, with distribution limits linked to its sensitivity to cold, seasonality of radiation and precipitation. The modelled Ostrinia nubilalis distribution overlapped with the main corn production areas of the northeastern USA and Canada; temporary/seasonal suitable habitat was also predicted across the southeastern USA. Climate change scenarios are predicted to favour T. ostriniae over its hosts in northeastern China and North America. CONCLUSION: The modelling approaches used here proved useful for assessing environmental factors linked to an egg parasitoid and its lepidopteran hosts and identifying areas potentially suitable for inundative releases. © 2017 Society of Chemical Industry.
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.
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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 it