PosterPDF Available

Modelling the foraging behaviour of bumblebees using private or social information (PhD Project)



Plant-pollinator interaction is a strong evolutive force, and bumblebees are model organisms that have shaped much of our current knowledge. Past researches on bumblebees foraging strategies have shown that their efficiency depends on the environmental conditions, like the flower spatial distribution, with bumblebees being able to follow routines while visiting flowers, a behaviour is known as traplining. Moreover, the presence of the conspecifics may also impact foraging decisions, namely the decision on whether to visit a given flower. We propose to use an individual-based model to examine the impact of floral resources distribution and diversity on bumblebees foraging behaviour. The model simulates the equivalent of a day of bumblebee foraging. We follow the journey of pollinators across a simulated floral landscape. We are particularly interested in their foraging efficiency measured by the difference between the energy obtained during the feeding and the cost of moving in the environment. The agent can make decisions at two different levels: while moving between flowers, and while probing (or not) a flower. We will focus on the information used to make those decisions. We will focus on two types of information: the bumblebees can use either personal information (e.g. as in trapline foraging) or social information (e.g. the presence of a conspecific or the scent mark left by other pollinators on the corolla).
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The capacity to find resources is crucial for individuals fitness. To locate them, they can
use two types of information: personal and social.1
Our biological model, bumblebees, can use both types.
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The IBM models pollinators’ daily foraging in a given environment. Pollinators face a partially unknown
environment and compete with conspecifics. Their ability to use different types of information will
change their movement and their foraging efficiency.
The resource is described by the abundance and the aggregation of flowers.
The success of each pollinator is measured at
the end of the simulation by:
Nectar quantity collected
Number of flowers visited%: success (ie, the
bumblebee gets some nectar) & fails (ie, the
bumblebee probe a flower without nectar)
Distance covered
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The temporal variation, agregation and the diversity of the flowers will favor the individuals with a high use social information
"''+'%; BAUDRY, Emmanuelle%; BESSA-GOMES, Carmen
Laboratoire Écologie, Systématique et Évolution%; Université Paris Saclay (France)
Contact%: @EliseVerrier
Personal information%:
Physical habitat
Resources location
Social Information%:
Localisation cues
Signals communication
Public information (Performance)
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Learning capacity to the Bumblebees, which can change their trap-line
More flowers species, with different nectar capacity and regeneration
Possibility to copy the fellows (social information)
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Invariable Trap-line, a
localisations' sequence
Nectar quantity
Nectar quantity
Presence or not of pollinator's sent
mark on the corolla
Localisation on the map
Probability to do some exploration,
make a random move (Wrandom)
Probability to move to a detected
flower, using visual information
Probability to avoid a fellow,
move to opposite direction than
fellow (Wsocial)
Probability to follow its trap-line,
using private information (Wprivate)
1Danchin, E., Giraldeau, L. A., Valone, T. J., & Wagner, R. H.
(2004). Public information: from nosy neighbors to cultural
evolution. Science, 305(5683), 487-491.
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Full-text available
Psychologists, economists, and advertising moguls have long known that human decision-making is strongly influenced by the behavior of others. A rapidly accumulating body of evidence suggests that the same is true in animals. Individuals can use information arising from cues inadvertently produced by the behavior of other individuals with similar requirements. Many of these cues provide public information about the quality of alternatives. The use of public information is taxonomically widespread and can enhance fitness. Public information can lead to cultural evolution, which we suggest may then affect biological evolution.