Simple Physical Interactions Yield Social Self-Organization in Honeybees

Abstract

Social insect colonies show all characteristics of complex adaptive systems (CAS). Their complex behavioral patterns arise from social interactions that are based on the individuals’ reactions to and interactions with environmental stimuli. We study here how social and environmental factors modulate and bias the collective thermotaxis of young honeybees. Therefore, we record their collective decision-making in a series of laboratory experiments and derived a mathematical model of the collective decision-making in young bees from our empirical observations. This model uses only one free parameter that combines the ultimate effects of several aspects of the microscopic individual behavioral mechanisms, such as motion behavior, sensory range, or contact detection, into one single coefficient. We call this coefficient the “social factor.” Our model is capable of capturing the observed aggregation patterns from our empiric experiments with static environments and of predicting the emergent swarm-intelligent behavior of the system in dynamic environments. Besides the fundamental research aspect in studying CAS, our model enables us to predict the effects of a physical stimulus onto the macroscopic collective decision-making that affects several crucial prerequisites for efficient and effective brood production and population growth in honeybee colonies.

Emergence and retention of a collective memory in cockroaches

“…Similar networks of feedbacks than those highlighted in this paper have been described to be present in other social systems [22,73,74]. A body of works devoted to such social systems where positive feedbacks are in competition highlights the emergence of multistable patterns…”

“…Similar networks of feedbacks than those highlighted in this paper have been described to be present in other social systems [ 22 , 73 , 74 ]. A body of works devoted to such social systems where positive feedbacks are in competition highlights the emergence of multistable patterns of organization that depends on different elements such as the size of the system, the environmental parameters and the strength of the interactions/interattractions [ 58 , 75 ].…”

“…degradation of a site), depending on the properties of the system and on its feedbacks’ network, two very different outcomes are observed. If the adopted outcome only depends on the parameters, whatever the level stochasticity is, the system is monostable [ 22 , 23 ]. In multistable systems, the settlement in a particular state (the outcome) does not depend only on the new environmental parameters but also on the state it has been settled previously.…”

A Minimally Invasive Approach Towards “Ecosystem Hacking” With Honeybees

“…It was found that such complex processes can be modeled well by multi-agent models in a bottom-up way if the mechanisms of agents employ threshold-based behavior triggers and modulators. The simplest types of such models have fixed stimulus-threshold mechanisms, these models have been for example developed for modeling ants ( Bonabeau et al, 1996 , 1998 ), honeybees ( Schmickl et al, 2012 ; Szopek et al, 2021a ) and termites ( Feltell et al, 2008 ). Often, and also for our needs here, such fixed thresholds are not powerful enough to capture the observed dynamics in the system.…”