Claim · model-written summary
Dioryctria infestations showed spatiotemporal clustering in north-eastern, north-western and central China.
- Taxon
- Dioryctria
Dioryctriae0 - Outcome
- spatiotemporal clustering characteristicse1
- Setting
- north-eastern, north-western, and central regions of Chinae1
Verbatim
e0“Dioryctria is a genus of forest pests that cause long-term harm to the economy and forest ecosystems”
e1“Dioryctria infestations exhibited spatiotemporal clustering characteristics in the north-eastern, north-western, and central regions of China”
Title
Spatiotemporal dynamics and driving factors of Dioryctria in China
Hongwei Zhou; Wenlu Wang; Defu Chi; et al. Pest Management Science 2025. doi:10.1002/ps.70287
Other claims from this paper (4)
- Observation The overall trend of Dioryctria occurrence followed a stable-decline after outbreak-growth-secondary outbreak pattern.
- Association Artificial lighting at night had a significant impact on Dioryctria occurrence.
- Association The interaction of artificial lighting at night with climatic factors significantly increased the risk of Dioryctria infestation.
- Method / resource Spatiotemporal clustering detection improved the accuracy of Dioryctria spread simulation by 13.25%.