Population dynamics and seasonal migration patterns of Spodoptera exigua in northern China based on 11 years of monitoring data

PeerJ. 2024 Apr 10:12:e17223. doi: 10.7717/peerj.17223. eCollection 2024.

Abstract

Background: The beet armyworm, Spodoptera exigua (Hübner), is an important agricultural pest worldwide that has caused serious economic losses in the main crop-producing areas of China. To effectively monitor and control this pest, it is crucial to investigate its population dynamics and seasonal migration patterns in northern China.

Methods: In this study, we monitored the population dynamics of S. exigua using sex pheromone traps in Shenyang, Liaoning Province from 2012 to 2022, combining these data with amigration trajectory simulation approach and synoptic weather analysis.

Results: There were significant interannual and seasonal variations in the capture number of S. exigua, and the total number of S. exigua exceeded 2,000 individuals in 2018 and 2020. The highest and lowest numbers of S. exigua were trapped in September and May, accounting for 34.65% ± 6.81% and 0.11% ± 0.04% of the annual totals, respectively. The average occurrence period was 140.9 ± 9.34 days during 2012-2022. In addition, the biomass of S. exigua also increased significantly during these years. The simulated seasonal migration trajectories also revealed varying source regions in different months, primarily originated from Northeast China and East China. These unique insights into the migration patterns of S. exigua will contribute to a deeper understanding of its occurrence in northern China and provide a theoretical basis for regional monitoring, early warning, and the development of effective management strategies for long-range migratory pests.

Keywords: Integrated pest management; Migration trajectory; Population dynamics; Sex pheromone trap; Spodoptera exigua.

MeSH terms

  • Agriculture*
  • Animals
  • China / epidemiology
  • Humans
  • Population Dynamics
  • Seasons
  • Spodoptera

Grants and funding

This research was supported by the Natural Science Foundation of Liaoning Province of China (No. 2023-MS-209); The National Key R & D Program of China (2021YFD1400200) and the National Natural Science Foundation of China (No. 31871950). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.