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Insect pests and climate change: progress, trends, and challenges

Climate change and extreme weather events have major impacts on crop production and agricultural pests. As generally adaptable organisms, insect pests respond differently to various causes of climate change. Because temperature is the most important environmental factor affecting insect population dynamics, it is expected that global climate warming could trigger an expansion of their geographic range, increased overwintering survival, increased number of generations, increased risk of invasive insect species and insect-borne plant diseases, and changes in their interactions with host plants and natural enemies. The effects of climate change on insects are complex because climate change favours some insects and inhibits others while affecting their distribution, diversity, abundance, development, growth, and phenology. Insects would likely expand their geographic distribution. Due to higher overwintering survival rates and the ability to develop more generations, the abundance of some pests will increase. Invasive pest species will likely establish more readily in new areas. As climate change exacerbates the pest problem, there is a great need for future pest management strategies. These include monitoring climate and pest populations, modified integrated pest management, and the use of predictive models. A proactive and scientific approach is needed to address this problem. From 2020, the European Regional Development Fund has supported the project "AgroSPARC- Advanced and predictive agriculture for resilience to climate change", which will be implemented by the Nikola Tesla Innovation Centre, the Faculty of Electrical Engineering and Computing and the Faculty of Agriculture at the University of Zagreb in Croatia. The goal of this project is to use artificial intelligence to develop mathematical models for different stages of wheat development and use these models to predict yields and plant growth. Artificial neural networks will be developed to classify and select data on climatic conditions, weather forecasts, and indicators of plant development. These neural networks will learn and validate numerical models for different stages of plant development based on large experimental data sets. The models will be used publicly and interactively through an internet application to predict different stages of wheat development under real and hypothetical climatic conditions.

climate change, insects, progress, trends, challenges

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