Predicting pest outbreak patterns in response to global climate change: An overview

AbstractThis study provides a comprehensive overview of how variations in climate, including temperature fluctuations, altered rainfall patterns, and catastrophic events, impact insect populations. Using statistical approaches and machine learning, among other predictive modelling tools, we demonstrate a range of hypothetical spread scenarios including several pest species and global locations. Data from remote sensing, GIS systems, and citizen science initiatives forms the foundation of these models. This emphasises the need of making forecasts more accurate by using data from several sources. Predictive insights in farming will help legislators and other interested parties reduce the consequences of insect assaults on agricultural yield and food security.