Abstract
BACKGROUND: Dioryctria is a genus of forest pests that cause long-term harm to the economy and forest ecosystems. However, due to its complex species diversity, research on the driving factors of its spread and dispersal remains insufficient. This study proposes a research framework to address the macro-level analysis of the driving factors behind the spread of multi-species pest genera. Based on long-term analysis, we delineated the spatiotemporal distribution clusters of Dioryctria in China, analyzed its population dynamics, and explored the key factors influencing its spread across the country. RESULTS: The research results indicate that from 2004 to 2023, Dioryctria infestations exhibited spatiotemporal clustering characteristics in the north-eastern, north-western, and central regions of China, with the overall trend of occurrence following a pattern of 'stable-decline after outbreak-growth-secondary outbreak.' In addition to natural climate factors, this study identified a significant impact of artificial lighting at night on Dioryctria occurrence, and its interaction with climatic factors significantly increased the risk of Dioryctria infestation. The introduction of spatiotemporal clustering detection improved the accuracy of Dioryctria spread simulation by 13.25%, validating the feasibility of the research framework. CONCLUSION: This study provides a new perspective for the macro-level research on pest genera with complex species diversity. Through the analysis of the spatiotemporal patterns of Dioryctria infestations in China and the exploration of its driving factors, this study reveals the development trends of Dioryctria over the past 20 years and into the future, offering new scientific foundations for the control of Dioryctria. © 2025 Society of Chemical Industry.
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Claims 5
Claim · model-written summary
Dioryctria infestations showed spatiotemporal clustering in north-eastern, north-western and central China.
- Taxon
- Dioryctria
_(23694661938).jpg?width=60)
Dioryctriae0 - Outcome
- spatiotemporal clustering characteristicse1
- Setting
- north-eastern, north-western, and central regions of Chinae1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
_(23694661938).jpg?width=500)
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”
Claim · model-written summary
The overall trend of Dioryctria occurrence followed a stable-decline after outbreak-growth-secondary outbreak pattern.
- Taxon
- DioryctriaDioryctriae0
- Outcome
- overall trend of occurrencee2
- Qualifier
- stable-decline after outbreak-growth-secondary outbreake2
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Dioryctria is a genus of forest pests that cause long-term harm to the economy and forest ecosystems”
e2“the overall trend of occurrence following a pattern of 'stable-decline after outbreak-growth-secondary outbreak.'”
Claim · model-written summary
Artificial lighting at night had a significant impact on Dioryctria occurrence.
- Taxon
- DioryctriaDioryctriae0
- Treatment
- artificial lighting at nighte3
- Outcome
- Dioryctria occurrencee3
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Dioryctria is a genus of forest pests that cause long-term harm to the economy and forest ecosystems”
e3“a significant impact of artificial lighting at night on Dioryctria occurrence”
Claim · model-written summary
The interaction of artificial lighting at night with climatic factors significantly increased the risk of Dioryctria infestation.
- Taxon
- DioryctriaDioryctriae0
- Treatment
- interaction with climatic factorse4
- Outcome
- risk of Dioryctria infestatione4
- Direction
- increasede4
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Dioryctria is a genus of forest pests that cause long-term harm to the economy and forest ecosystems”
e4“its interaction with climatic factors significantly increased the risk of Dioryctria infestation”
Claim · model-written summary
Spatiotemporal clustering detection improved the accuracy of Dioryctria spread simulation by 13.25%.
- Taxon
- DioryctriaDioryctriae0
- Outcome
- accuracy of Dioryctria spread simulatione5
- Direction
- improvede5
- Value
- 13.25%e5
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Dioryctria is a genus of forest pests that cause long-term harm to the economy and forest ecosystems”
e5“The introduction of spatiotemporal clustering detection improved the accuracy of Dioryctria spread simulation by 13.25%”