Journal of Entomological Research
SCOPUSWeb of Science
  • Year: 2025
  • Volume: 49
  • Issue: 3

Modeling the impact of global warming on insect population dynamics and pest pressure

  • Author:
  • Pratiksha Singh1, Subrat Kumar Mahapatra2, Shirish Inamdar*, B. Harinathan3, Roma Tandel4
  • Total Page Count: 8
  • Published Online: Sep 26, 2025
  • Page Number: 749 to 756

1Department of Agriculture, Noida International University, Greater Noida, Gautam Budhha Nagar - 201 310, Uttar Pradesh, India, pratiksha.singh@niu.edu.in

2Department of Agricultural Statistics, Institute of Agricultural Sciences, Siksha ‘O’ Anusandhan (Deemed to be University), Bhubaneswar - 751 030, Odisha, India, E-mail: subratmahapatra@soa.ac.in

3Krishna Institute of Science and Technology, Krishna Vishwa Vidyapeeth “Deemed to be University”, Karad, Satara - 415 539, Maharashtra, India, E-mail: hariinvisible@gmail.com

4Department of Entomology, College of Agriculture, Parul University, Vadodara - 391 760, Gujarat, India, E-mail: roma.tandel33728@paruluniversity.ac.in

Department of Pharmacy Practice, Krishna Institute of Pharmacy, Krishna Vishwa Vidyapeeth “Deemed to be University”, Karad, Satara -415 539, Maharashtra, India

*Corresponding authors' E-mail: shirish2124@yahoo.co.in

Online published on 26 September, 2025.

Abstract

Global warming profoundly affects insect population dynamics, therefore changing their physiology, behaviour, and ecological function. The significant consequences of growing temperatures, altering precipitation patterns, and changing climatic circumstances on insect metabolism, development, and life cycles are investigated in this work. The interaction of these elements disturbs the ecological equilibrium and increases the stresses on agricultural systems by pests. This work investigates three main modelling techniques: mechanistic models, statistical models, and agent-based models in order to grasp and forecast these effects: While statistical models find patterns and connections from vast datasets, mechanistic models offer thorough understanding of physiological processes. Providing a geographically and temporally explicit viewpoint, agent-based models replicate individual-level behaviours and interactions within dynamic contexts. Combining these approaches will help us to grasp how global warming affects insect numbers, therefore facilitating the creation of adaptive management plans.

Keywords

Adaptation, Agriculture, Biodiversity, Climate, Ecology, Global warming, Insect, Modeling, Pest, Pressure, Predictions management, Resilience