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<p>This study employs the MaxEnt species distribution model (SDM) to predict the potential habitat distribution of <i>Vatiga illudens</i>, a newly emerging pest threatening cassava production in Indonesia. The model identifies key environmental factors influencing the species' spread, such as precipitation during the coldest quarter (BIO19), contributing 66.2%, and temperature during the wettest quarter (BIO8), contributing 18.3%. The results show that high habitat suitability zones, with a probability ranging from 0.60 to 0.99, are concentrated in southern Indonesia, particularly in Java, Bali, and Nusa Tenggara, which account for 73.33% to 56.74% of the highest suitability classes. In contrast, regions such as Sumatra, Kalimantan, and Sulawesi show suitability values below 0.30, indicating low habitat suitability. The model’s accuracy, with an average AUC of 0.925 (± 0.021), demonstrates excellent discriminatory ability. The findings support a risk-based management approach, focusing on routine monitoring in high-risk areas and strengthening biosecurity measures. This study underscores the need to integrate climate forecasting with pest management strategies to mitigate the impact of pest invasions and safeguard Indonesia's food security in the face of climate change.</p>

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Spatial prediction of Vatiga illudens (Hemiptera: Tingidae) on cassava crops: a newly invasive pest in Indonesia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月6日

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  • Ahmad Ziyadul Haq Al Fisal,
  • Muhammad Faiz Muzhaffar,
  • Pebra Heriansyah

摘要

This study employs the MaxEnt species distribution model (SDM) to predict the potential habitat distribution of Vatiga illudens, a newly emerging pest threatening cassava production in Indonesia. The model identifies key environmental factors influencing the species' spread, such as precipitation during the coldest quarter (BIO19), contributing 66.2%, and temperature during the wettest quarter (BIO8), contributing 18.3%. The results show that high habitat suitability zones, with a probability ranging from 0.60 to 0.99, are concentrated in southern Indonesia, particularly in Java, Bali, and Nusa Tenggara, which account for 73.33% to 56.74% of the highest suitability classes. In contrast, regions such as Sumatra, Kalimantan, and Sulawesi show suitability values below 0.30, indicating low habitat suitability. The model’s accuracy, with an average AUC of 0.925 (± 0.021), demonstrates excellent discriminatory ability. The findings support a risk-based management approach, focusing on routine monitoring in high-risk areas and strengthening biosecurity measures. This study underscores the need to integrate climate forecasting with pest management strategies to mitigate the impact of pest invasions and safeguard Indonesia's food security in the face of climate change.