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Forecasting the future of Fall armyworm Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae) in India using ecological niche model.

Karuppannasamy AshokAbdelmutalab G A AzragGeethalakshmi VellingiriJohn Samuel KennedyPatil Santosh GanapatiSubramanian SevganBalasubramani Venkatasamy
Published in: International journal of biometeorology (2024)
The Fall armyworm, Spodoptera frugiperda is the most notorious invasive pest species on maize, recently reported in India. The continuous spread of Fall armyworms to new ecological niches raises global concern. The current study is the first in India to forecast the suitability of a habitat for S. frugiperda using a maximum entropy algorithm. Predictions were made based on an analysis of the relationship between 109 occurrence records of S. frugiperda and pertinent historical, current, and predicted climatic data for the study area. The model indicated that S. frugiperda could thrive in different habitats under the current environmental circumstances, particularly in the west and south Indian states like Maharashtra, Tamil Nadu, and Karnataka. The model predicted that areas with higher latitudes, particularly in Uttar Pradesh, Odisha, West Bengal, and some portions of Telangana, Rajasthan, Chhattisgarh, and Madhya Pradesh, as well as some tracts of northeastern states like Assam and Arunachal Pradesh, would have highly climate-suitable conditions for S. frugiperda to occur in the future. The average AUC value was 0.852, which indicates excellent accuracy of the prediction. A Jackknife test of variables indicated that isothermality with the highest gain value was determining the potential geographic distribution of S. frugiperda. Our results will be useful for serving as an early warning tool to guide decision-making and prevent further spread toward new areas in India.
Keyphrases
  • climate change
  • human health
  • decision making
  • risk assessment
  • machine learning
  • current status
  • artificial intelligence
  • electronic health record
  • life cycle