Predation efficiency of praying mantises as important natural enemies of spotted lanternfly, <scp> <i>Lycorma delicatula</i> </scp>
Bibliographic record
Abstract
BACKGROUND: The spotted lanternfly, Lycorma delicatula (White) (Hemiptera: Fulgoridae), has emerged as a globally important invasive insect pest, causing extensive damage to grapevines and ornamental plants in its invasive range. Praying mantises are commonly found in many native habitats of the spotted lanternfly in China. However, the role of predatory natural enemies such as mantises and their predatory efficiency as biological control agents for spotted lanternfly in this region is unknown. The predation efficiency of the five most common praying mantis species in northern China-Hierodula petellifera, Mantis religiosa, Statilia maculata, Tenodera angustipennis, and Tenodera sinensis (Mantodea: Mantidae) were evaluated-by measuring their functional responses to adult spotted lanternflies under controlled conditions. In addition, the intraspecific interference in predators were also examined by exposing a fixed ratio of mantis to prey densities. RESULTS: Both final instars and adults of all five species of mantis were found to readily prey upon spotted lanternfly adults, and their feeding rates increased linearly with prey abundance within the tested spotted lanternfly densities. Mutual interference by all tested mantid species was observed with increased predator density. Overall, T. sinensis, the largest-bodied mantis tested, consumed more spotted lanternflies than other species, and T. sinensis adults were more efficient predators than their final instars. CONCLUSION: Our results show that praying mantises are important natural enemies of spotted lanternfly adults in their native range in China. These findings also provide insights into the potential efficacy of different mantis species as biocontrol agents for the spotted lanternfly and could be incorporated into future integrated pest management programs against this invasive pest. © 2025 Society of Chemical Industry.
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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".