Current Zoology, 2016, 62(3), 277–284 doi: 10.1093/cz/zow041 Advance Access Publication Date: 4 April 2016 Article Article The organization of societal conflicts by pavement ants Tetramorium caespitum: an agent-based model of amine-mediated Downloaded from https://academic.oup.com/cz/article-abstract/62/3/277/2897747 by guest on 08 December 2019 decision making a a,b a Kevin M. HOOVER , Andrew N. BUBAK , Isaac J. LAW , c c a Jazmine D. W. YAEGER , Kenneth J. RENNER , John G. SWALLOW , and a,* Michael J. GREENE aDepartment of Integrative Biology, University of Colorado Denver, Denver, CO 80217-3364, USA, bNeuroscience Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA, and cDepartment of Biology, University of South Dakota, Vermillion, South Dakota 57069, USA *Address correspondence to Michael J. Greene. E-mail: [email protected]. Received on 27 December 2015; accepted on 2 March 2016 Abstract Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant’s brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the ter- ritory that they patrol in search of energetically rich forage. When members of 2 colonies randomly interact at the territory boundary a decision to fight occurs when: 1) there is a mismatch in nest- mate recognition cues and 2) each ant has a recent history of high interaction rates with nestmate ants. Instead of fighting, some ants will decide to recruit more workers from the nest to the fighting location, and in this way a positive feedback mediates the development of colony wide wars. In ants, the monoamines serotonin (5-HT) and octopamine (OA) modulate many behaviors associated with colony organization and in particular behaviors associated with nestmate recognition and ag- gression. In this article, we develop and explore an agent-based model that conceptualizes how in- dividual changes in brain concentrations of 5-HT and OA, paired with a simple threshold-based de- cision rule, can lead to the development of colony wide warfare. Model simulations do lead to the development of warfare with 91% of ants fighting at the end of 1 h. When conducting a sensitivity analysis, we determined that uncertainty in monoamine concentration signal decay influences the behavior of the model more than uncertainty in the decision-making rule or density. We conclude that pavement ant behavior is consistent with the detection of interaction rate through a single timed interval rather than integration of multiple interactions. Key words: agent-based model, aggressive behavior, ants, decision making, monoamines, octopamine, serotonin. Despite their miniaturized and simple brains, ants are able to solve information in those cues, compare them to an inherent set of rules, complex problems when organized at the colony level. Ant colonies and make decisions to change their behavior (Greene and Gordon are regulated as non-hierarchical distributed systems (Camazine et al. 2003; Couzin et al. 2005; Arganda et al. 2012). Colony behavior 2001; Collignon and Detrain 2009; Gordon 2010; Robinson et al. changes collectively because of the cascade of individual decisions 2014). Without an authority to direct the actions of workers, it is ne- made by workers. Examples of collective decision making include cessary for each individual to assess local information cues, integrate choosing a new nest, allocating the proper number of workers to VC The Author (2016). Published by Oxford University Press. 277 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact [email protected] 278 Current Zoology, 2016, Vol. 62, No. 3 perform jobs to support colony homeostasis, forming foraging trails, pavements ants; we hypothesis that high 5-HT and OA brain con- and even tending gardens (Gordon 1986; Frederickson et al. 2005; centrations correlate to recent interactions with nestmates and may Collignon and Detrain 2009; Sumpter and Pratt 2009). Thus, we wit- prime the ant to fight (Greene MJ, unpublished data). A mismatch ness the aggregation of simple deterministic components leading to a in nestmate recognition cues preceded by elevated brain concentra- nuanced, variable system that natural selection can act on; the super- tions of 5-HT and OA thus satisfies the proposed decision rule to organism of the ant colony (Detrain and Deneubourg 2006; Gordon initiate a fight. 2010). To test the feasibility of this mechanism, we leverage the bot- A key component in the collective decision making of ants is the tom-up approach of agent-based modelling. This modelling system effect of interaction rate on behavior. Interaction rate is often used was developed as a way to explore how system level characteristics by insects as a proximate measurement of local density. It has been emerge from simple, rule-based and stochastically interacting agents shown that in red harvester ants Pogonomyrmex barbatus inter- (Bankes 2002; Hare and Deadman 2004; Grimm et al. 2006; action rate is associated with colonial task allocation in addition to Holcombe et al. 2012). Use of the bottom-up approach took off rap- the availability and dedication of reserve workers to foraging idly in the field of eusocial insect behavior (Sumpter 2006) and has Downloaded from https://academic.oup.com/cz/article-abstract/62/3/277/2897747 by guest on 08 December 2019 (Pinter-Wollman et al. 2013). In Temnothorax albipennis, inter- been used to explore the self-organization of the complex behaviors action rate is shown to modulate the process of nest emigration of ants including: aggregation (Morale et al. 2005), nest choice (Pratt 2004). Interaction rate could be measured by a spectrum of (Pratt et al. 2005), foraging (Robinson et al. 2008), task allocation methods with 2 extremes: 1) integration of all encounters in a given (Momen 2013), and intraspecific battles (Martelloni et al. 2015). time or 2) response based only on the interval before first encounter This modelling method integrates 2 key sources of variation that are (Pratt 2004). Indeed, there are examples of both occurring in insects. often ignored in analytic analyses: distributed spatial structures and Integration over multiple interactions is observed during locust individual behavioral heterogeneity (Parunak et al. 1998). Schistocerca gregaria aggregation while nest construction in Polybia Here, we build an agent-based model to conceptualize how occidentalis is a result of single interval measurement (Pratt 2004). changes in individual monoamine brain concentrations and the ap- Pavement ant Tetramorium caespitum workers perform random plication of simple decision rules lead to the development of the walks to search colony territory for foods high in sugar and fat con- observed colony behavior of fighting in pavement ant wars. In order tent (Collignon and Detrain 2009; Countryman et al. 2015). In to understand the organization of social insects, we must undertake order to secure territory, pavement ant workers organize wars an exploration of both the physiological mechanisms and contextual against neighboring colonies (Greene MJ, unpublished data; Plowes stimuli behind individual decision making, and how these decisions 2008). This organization occurs after individuals from neighboring lead to system level patterns of behavioral organization in colonies. colonies meet during the course of a random walk, touch antennae to the other’s cuticle, and assess nestmate recognition cues coded in cuticular hydrocarbon profiles (Greene MJ, unpublished data). A de- Materials and Methods cision rule to fight a non-nestmate ant is satisfied when 2 conditions Collection of ants are met: 1) there is a mismatch in the information coded in the cues Pavement ants were collected along foraging trails in urban and sub- (Greene MJ, unpublished data; Martin and Drijfhout 2009) and 2) urban areas of Denver and Aurora, Colorado, United States. Ants the ant had a recent history of interactions with nestmate ants were collected by aspiration on baited foraging trails. Collected ants (Greene MJ, unpublished data). The probability that a pavement ant were brought to the laboratory for experimental manipulations that worker will fight a non-nestmate increases with the density of nest- were conducted between 24 and 36 h after collection. Ants were mate ants as assessed by the interaction rate (Greene MJ, unpub- temporarily housed at room temperature (25C) in plastic con- lished data). Fighting among conspecifics involves a ritualized tainers and allowed to drink ad libitum from glass tubes filled with pushing of mass between dyads that are locked together by man- water and plugged with cotton. dibles and grasping appendages (Plowes 2008). The fights last for many hours during which few, if any, ants die (Plowes 2008). However, the dedication of the vast majority of available foragers to Worker density trials this behavior constitutes an opportunity cost as foraging efforts In order to study the effects of increasing interaction rate on brain lev- cease during the course of the war (Plowes 2008). Some workers do els of biogenic amines, ants were placed in petri dishes with worker 2 not fight, but instead recruit more nestmates to the war in a positive densities of 5, 20, or 100 ants per