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Effective foraging for food is such a necessity for most animals it is reasonable to expect natural selection to favour individuals that optimise their nutrient intake and minimise energy expenditure. One way to achieve these goals is through the use of specific behaviours, called “foraging strategies”. Pollinators such as bees present a very interesting case of foraging optimisation. Since the nectar offered by plants is a renewable resource bees have a strong incentive to learn and memorise the positions of the flowers they have discovered. Many studies have investigated the foraging behaviour of bees, leading to the identification of two foraging strategies: the use of stable, repeated routes between subsets of flowers (“traplines”) and the development of areas of exclusion of other bees in competitive situations (“resource partitioning”). The use of these two strategies by bees has been demonstrated multiple times in different situations, but we still know very little about how such strategies develop. These two strategies have mostly been described through cognitively complex mechanisms. However, while they have been observed and characterised in controlled environments, these strategies were seldom seen in more natural environments, suggesting our current explanations of these phenomena are incomplete. This gap in knowledge leads me to question what are the behavioural rules individual bees follow to establish these strategies? My thesis focused on attempting to gain some insight on how these foraging strategies form by complementing experiments with a modelling approach. I built an agent-based model of multiple bees foraging in a wide variety of environments. With it I tried to explain the establishment of these strategies through the use of simple positive and negative reinforcement rules as bees found flowers with or without rewards, respectively. Exploration of the model showed that both traplining and partitioning strategies could emerge in simple competitive situations with two bees foraging on 10 feeding sites. I then conducted three experiments to challenge the assumptions of the model. My results suggest that the foraging strategies of bees could emerge from simple foraging rules, but more importantly that their development in natural conditions could be mostly driven from the spatial and temporal constraints of the environment which are altering the availability in resources. Bees were able to improve their foraging efficiency in most experimental conditions, but how they did so was not limited to the establishment of traplines or resource partitioning. By explaining their formation mostly through these constraints, we are able to present these foraging strategies not as cognitively intensive processes, but rather paths of least resistance to environmental constraints.

International audience; Central place foraging pollinators tend to develop multi-destination routes (traplines) to exploit several patchily distributed plant resources. While the formation of traplines by individual pollinators has been studied in details, how populations of individuals exploit resources in a common area is an open question difficult to address experimentally. Here we explored conditions for the emergence of resource partitioning among traplining bees using agent-based models built from experimental data of bumblebees foraging on artificial flowers. In the models, bees learn to develop routes as a consequence of feedback loops that change their probabilities of moving between flowers. While a positive reinforcement of route segments leading to rewarding flowers is sufficient for the emergence of resource partitioning when flowers are evenly distributed, a negative reinforcement of route segments leading to unrewarding flowers is necessary when flowers are patchily distributed. In these more complex environments, the negative experiences of individual bees favour the spatial segregation of foragers and high levels of collective foraging efficiency.