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Spatial Evaluation of Salurnis marginella Occurrence According to Climate Change Using Multiple Species Distribution Models

Author

Listed:
  • Jae-Woo Song

    (Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of Korea)

  • Jaho Seo

    (Department of Automotive and Mechatronics Engineering, Ontario Tech University, Oshawa, ON L1G 0C5, Canada)

  • Wang-Hee Lee

    (Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of Korea
    Department of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Republic of Korea)

Abstract

Salurnis marginella causes agricultural and forest damage in various Asian environments. However, considering the environmental adaptability of pests and the active international trade, it may invade other regions in the future. As the damage to local communities caused by pests becomes difficult to control after invasion, it is essential to establish measures to minimize losses through pre-emptive monitoring and identification of high-risk areas, which can be achieved through model-based predictions. The aim of this study was to evaluate the potential distribution of S . marginella by developing multiple species distribution modeling (SDM) algorithms. Specifically, we developed the CLIMEX model and three machine learning-based models (MaxEnt, random forest, and multi-layer perceptron), integrated them to conservatively assess pest occurrence under current and future climates, and overlaid the host distribution with climatically suitable areas of S. marginella to identify high-risk areas vulnerable to the spread and invasion of the pest. The developed model, demonstrating a true skill statistic >0.8, predicted the potential continuous distribution of the species across the southeastern United States, South America, and Central Africa. This distribution currently covers approximately 9.53% of the global land area; however, the model predicted this distribution would decrease to 6.85%. Possible areas of spread were identified in Asia and the southwestern United States, considering the host distribution. This study provides data for the proactive monitoring of pests by identifying areas where S. marginella can spread.

Suggested Citation

  • Jae-Woo Song & Jaho Seo & Wang-Hee Lee, 2025. "Spatial Evaluation of Salurnis marginella Occurrence According to Climate Change Using Multiple Species Distribution Models," Agriculture, MDPI, vol. 15(3), pages 1-18, January.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:3:p:297-:d:1580049
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    References listed on IDEAS

    as
    1. Peterson, A. Townsend & Papeş, Monica & Soberón, Jorge, 2008. "Rethinking receiver operating characteristic analysis applications in ecological niche modeling," Ecological Modelling, Elsevier, vol. 213(1), pages 63-72.
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