(444e) Agent-Based Modeling of the Effects of Colony Size and Neonicotinoid Exposure on Bumblebee Behavior within Nests | AIChE

(444e) Agent-Based Modeling of the Effects of Colony Size and Neonicotinoid Exposure on Bumblebee Behavior within Nests


Ford Versypt, A. N. - Presenter, Oklahoma State University
Crall, J. D., Harvard University
de Bivort, B. L., Harvard University
Dey, B., Princeton University
Neonicotinoids are a widely used class of pesticides that were designed to be harmless to pollinating insects and have been incorporated into many plants via seed coatings. However, even at sublethal exposures, neonicotinoids have been shown to negatively impact bees and their pollination services [1-9]. While there is evidence suggesting that colony size may play a role in mitigating neonicotinoid exposure in bumblebees, mechanisms underlying these effects are not well understood. We developed an agent-based computational model of the spatiotemporal distribution of bumblebees in nests that considers the stochastic interactions between and movements of individual bees within a nest and the nest-related disruptions that occur due to pesticide exposure. The dynamic states of the bees are stored in a matrix, the default data structure of MATLAB. Agent-based modeling allows for building understanding of the colony scale impacts of multiple interacting factors that affect numerous individuals in close proximity and how these change upon pesticide exposure. The scientific significance is that the model focuses on the effects of pesticides that occur in bumblebees over short time scales (hours to days) inside a single nest. These temporal and spatial scales are appropriate for modeling the effects of neonicitinoid pesticides that account for colony size and interactions between exposed and unexposed individuals. The short and local scales allow the model to explicitly consider neighbor interactions and individual bee interactions with structures inside an isolated environment without confounding external factors. Emergent phenomena can be tracked during simulations using the model.

We validated our model with our recently published empirical results before and after sublethal dosing of a common neonicotinoid called imidacloprid [10]. Additionally, we have made our agent-based model available as free open-source software called BeeNestABM [11]. The software and its documentation has been peer-reviewed [12]. We used the model to elucidate the mechanisms underlying the effects of neonicotinoid exposure on worker behavior within bumblebee nests and how these effects are modulated by colony size [13]. In this presentation, we will summarize how the agent-based model works and analyze in silico simulation results for several emergent behaviors within nests for treated and untreated bumblebees in colonies of different sizes (population and spatial dimensions). Our results suggest that changes in both number of workers and nest architecture may contribute to making larger colonies less sensitive to pesticide exposure.


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[11] Ford Versypt, A. N., Crall, J. D., and Dey, B. (2018) BeeNestABM, http://github.com/ashleefv/BeeNestABM DOI: 10.5281/zenodo.1148830.

[12] Ford Versypt, A. N., Crall, J. D., and Dey, B. (2018). BeeNestABM: An open-source agent-based model of spatiotemporal distribution of bumblebees in nests. JOSS 3, 718. doi:10.21105/joss.00718.

[13] Crall, J. D., de Bivort, B. L., Dey, B., Ford Versypt, A. N. (2019) Social buffering of pesticides in bumblebees: agent-based modeling of the effects of colony size and neonicotinoid exposure on behavior within nests,” Frontiers in Ecology and Evolution, 7, 51. DOI: 10.3389/fevo.2019.00051