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Predictive Modeling and Integrated Management Systems for Climate-Induced Shifts in Agricultural Insect Pest Populations

DOI https://doi.org/10.55640/corr-v04i04-02
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Dr. Liang Wei Zhang 1 , Prof. Yuhan Liu 1 ,
4 East Asia Institute of Digital Research, Beijing, China
4 Shanghai Institute of Advanced Studies, Shanghai, China

Abstract

Climate change has emerged as a dominant driver of ecological instability, significantly altering the spatial distribution, phenology, and population dynamics of agricultural insect pests. Rising global temperatures, altered precipitation regimes, and increased frequency of extreme weather events are reshaping pest–crop interactions, leading to heightened risks for global food security. This paper develops a predictive modeling and integrated management framework for understanding and mitigating climate-induced shifts in insect pest populations. Drawing on ecological theory, physiological insect responses, and agroecosystem modeling, the study synthesizes existing scientific evidence to construct a structured analytical approach combining climate variables, pest population dynamics, and crop vulnerability indices. The findings highlight that temperature-dependent developmental acceleration, range expansion, and disrupted trophic interactions are central mechanisms driving pest outbreaks. Integrating predictive analytics with adaptive pest management strategies enables early warning systems and targeted interventions. The study concludes that a multi-layered modeling approach, coupled with ecosystem-based management, is essential for resilient agricultural systems under climate change scenarios.

Keywords

Climate change, insect pests, predictive modeling, agroecosystem

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