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The outbreak of the desert locust Schistocerca gregaria Forskål, 1775, which originated from the Horn of Africa in 2019-2020 created an episodic plague under bio-geographical settings in the arid and semi-arid areas of South and Southwest Asia. In India, it happened after twenty-seven years due to the persistence of a few favourable conditions caused by its plague, resulting in hundreds of crores in crop damage. Keeping this in mind, the study aims to assess the suitability and likelihood of the desert locust epidemic occurring in India, utilizing two widely recognized statistical models: Weight-of-Evidence (WoE) and Frequency Ratio (FR). This work evaluated nine critical climatic factors for the study considering western and central parts of India. The 'Projected Locust Suitability' (PLS) was calculated by analyzing the correlation of the considered variables and the occurrence of locust swarms and bands. The significance (importance) of each variable on PLS was determined using Principal Component Analysis (PCA) and Random Forest (RF) algorithms. The PLS maps clearly show that 42.7-52.8% of the areas fall under high and very high locust suitability zones. The result suggests that the Ajmer-Gwalior-Allahabad tract is highly prone to future locust occurrences, while the Aligarh-Bareilly-Lakhimpur tract is moderately susceptible. The effectiveness of both modelled PLS maps was determined with the help of the ROC curve. The AUC results indicate that both the WoE (0.92) and the RF (0.90) models worked remarkably well in precisely predicting PLS. The RF-based IncNodePurity analysis indicates that low to moderate temperatures in the presence of cloud cover significantly impact locust occurrence and migration. The present findings are projected to direct the development of sustainable locust management strategies utilizing proper land use policies in the tropical climate.
Mitra et al. (Wed,) studied this question.