Review on mathematical modeling of honeybee population dynamics

Jun Chen, Gloria DeGrandi-Hoffman, Vardayani Ratti, Yun Kang

Research output: Contribution to journalReview articlepeer-review

Abstract

Honeybees have an irreplaceable position in agricultural production and the stabilization of natural ecosystems. Unfortunately, honeybee populations have been declining globally. Parasites, diseases, poor nutrition, pesticides, and climate changes contribute greatly to the global crisis of honeybee colony losses. Mathematical models have been used to provide useful insights on potential factors and important processes for improving the survival rate of colonies. In this review, we present various mathematical tractable models from different aspects: 1) simple bee-only models with features such as age segmentation, food collection, and nutrient absorption; 2) models of bees with other species such as parasites and/or pathogens; and 3) models of bees affected by pesticide exposure. We aim to review those mathematical models to emphasize the power of mathematical modeling in helping us understand honeybee population dynamics and its related ecological communities. We also provide a review of computational models such as VARROAPOP and BEEHAVE that describe the bee population dynamics in environments that include factors such as temperature, rainfall, light, distance and quality of food, and their effects on colony growth and survival. In addition, we propose a future outlook on important directions regarding mathematical modeling of honeybees. We particularly encourage collaborations between mathematicians and biologists so that mathematical models could be more useful through validation with experimental data.

Original languageEnglish (US)
Pages (from-to)9606-9650
Number of pages45
JournalMathematical Biosciences and Engineering
Volume18
Issue number6
DOIs
StatePublished - 2021

Keywords

  • Dynamical systems
  • Honeybee
  • Mathematical models
  • Parasites
  • Pathogens
  • Pesticides
  • Seasonality

ASJC Scopus subject areas

  • Modeling and Simulation
  • Agricultural and Biological Sciences(all)
  • Computational Mathematics
  • Applied Mathematics

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