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Volume 52 Issue 9
Sep.  2025
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Article Contents

Genomic predictions of invasiveness and adaptability of the cotton bollworm in response to climate change

doi: 10.1016/j.jgg.2025.01.016
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This project was funded by the National Natural Science Foundation of China (32372546), Shenzhen Science and Technology Program (KQTD20180411143628272), the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences and STI 2030-Major Projects (2022ZD04021), and the National Key Research and Development Program of China (2023YFD2200700).

  • Received Date: 2024-08-14
  • Accepted Date: 2025-01-23
  • Rev Recd Date: 2025-01-22
  • Publish Date: 2025-01-30
  • Agricultural pests cause enormous losses in annual agricultural production. Understanding the evolutionary responses and adaptive capacity of agricultural pests under climate change is crucial for establishing sustainable and environmentally friendly agricultural pest management. In this study, we integrate climate modeling and landscape genomics to investigate the distributional dynamics of the cotton bollworm (Helicoverpa armigera) in the adaptation to local environments and resilience to future climate change. Notably, the predicted inhabitable areas with higher suitability for the cotton bollworm could be eight times larger in the coming decades. Climate change is one of the factors driving the dynamics of distribution and population differentiation of the cotton bollworm. Approximately 19,000 years ago, the cotton bollworm expanded from its ancestral African population, followed by gradual occupations of the European, Asian, Oceanian, and American continents. Furthermore, we identify seven subpopulations with high dispersal and adaptability which may have an increased risk of invasion potential. Additionally, a large number of candidate genes and SNPs linked to climatic adaptation were mapped. These findings could inform sustainable pest management strategies in the face of climate change, aiding future pest forecasting and management planning.
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