ArticlePloS one2024
Predicting potential distribution of the Rhinoncus sibiricus under climatic in China using MaxEnt.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 8 citations in OpenAlex.
- Suitability prediction of potential arable land in southeast coastal area of China.Scientific reports · 2025Article
- Predicting the Distribution ofInsects · 2024Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, buckwheat (Fagopyrum spp.) is being increasingly damaged by the Siberian tortoise beetle (Rhinoncus sibiricus Faust). Adults and nymphs feed on leaf tissues and caulicles, thus damaging its stems and leaves. In this study, we investigated the habits, distribution, and environmental impact of R. sibiricus using MaxEnt, an ecological niche model. Geographic information about the infestation site from previous field surveys and climatic data from 2013 to 2018 were organized and optimized using R. The impact factors were calculated using MaxEnt software. The results indicate that population fluctuations in R. sibiricus are related to changes in temperature, humidity, and their spatial distribution. Under current climatic conditions, R. sibiricus is mainly distributed in northern China, with sporadic distribution in south-western China. The values for a survival probability threshold > 0.3 were: precipitation during the wettest month (bio13), 70.31-137.56 mm; mean temperature of the coldest quarter (bio11), -15.00-0.85°C; mean temperature of the warmest quarter (bio10), 11.88-23.16°C; precipitation during the coldest quarter (biol9), 0-24.39 mm. The main factors contributing > 70% to the models were precipitation during the wettest month and coldest quarter, and mean temperature during the warmest and coldest quarters. Under both future climate models, the center of the fitness zone moves northward. Our results will be useful in guiding administrative decisions and support farmers interested in establishing control and management strategies for R. sibiricus. This study could also serve as a reference for future research on other invasive pests.
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Registered trials
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