HOW TO MODEL HONEYBEE POPULATION DYNAMICS: STAGE STRUCTURE AND SEASONALITY

Jun Chen, Komi Messan, Marisabel Rodriguez Messan, Gloria Degrandi-Hoffman, Dingyong Bai, Yun Kang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Western honeybees (Apis Mellifera) serve extremely important roles in our ecosystem and economics as they are responsible for pollinating $ 215 billion dollars annually over the world. Unfortunately, honeybee population and their colonies have been declined dramatically. The purpose of this article is to explore how we should model honeybee population with age structure and validate the model using empirical data so that we can identify different factors that lead to the survival and healthy of the honeybee colony. Our theoretical study combined with simulations and data validation suggests that the proper age structure incorporated in the model and seasonality are important for modeling honeybee population. Specifically, our work implies that the model assuming that (1) the adult bees are survived from the egg population rather than the brood population; and (2) seasonality in the queen egg laying rate, give the better fit than other honeybee models. The related theoretical and numerical analysis of the most fit model indicate that (a) the survival of honeybee colonies requires a large queen egg-laying rate and smaller values of the other life history parameter values in addition to proper initial condition; (b) both brood and adult bee populations are increasing with respect to the increase in the egg-laying rate and the decreasing in other parameter values; and (c) seasonality may promote/suppress the survival of the honeybee colony.

Original languageEnglish (US)
Pages (from-to)91-125
Number of pages35
JournalMathematics in Applied Sciences and Engineering
Volume1
Issue number2
DOIs
StatePublished - Jun 30 2020
Externally publishedYes

Keywords

  • age structure
  • delay differential equations
  • Honeybees
  • mortality
  • seasonality

ASJC Scopus subject areas

  • Applied Mathematics
  • Modeling and Simulation

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