Abstract

Grassland locusts harm a large amount of grassland every year. Grassland locusts have caused devastating disasters across grassland resources and have greatly impacted the lives of herdsmen. Due to the impacts of climate change and human activity, the distribution of grassland locust habitats changes constantly. The monitoring and identification of locust habitats is of great significance for the production and utilization of grassland resources. In order to further understand the behavior of these grassland pests and carry out precise prevention and control strategies, researchers have often used survey points to reveal the distribution of habitat-suitability areas or establish the high density of locusts (more than 15 locusts/m2) to identify the different risk levels of habitat-suitability areas for grassland locusts. However, the results of these two methods have often been too large, which is not conducive to the precise control of grassland locusts in large areas. Starting from the sample points of our locust investigation, we conducted a hierarchical prediction of the density of locusts and used the probability value of locust occurrence, as predicted by a maximum entropy model, to categorize the habitat-suitability areas according to the probability thresholds of suitable species growth. The results were in good agreement with the actual situation and there was little difference between the prediction results for locust densities greater than 15 locusts/m2 in the middle- and high-density habitat-suitability areas and those for all survey points, while there was a big difference between the prediction results for densities in the middle- and low-density habitat-suitability areas and those for all survey points. These results could provide a basis for the efficient and accurate control of grassland locusts and could have practical significance for future guidance.

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