Assessment during Intergroup Contests
Authors: P.A. Green, M. Briffa, M.A. Cant
Journal: Trends in Ecology & Evolution (2020)

The dyadic assessment framework – studying the strategies animals use to gather information during one-on-one contests, and how this assessment drives contest behaviors and outcomes – can be fruitfully adapted to intergroup contests: those between stable social-living groups.Heterogeneity among group members and how groups cohere to make effective decisions are unique features of social living that add complexity to intergroup contest assessment.Understanding intergroup contest assessment can inform research in social evolution and ecology, for example, by revealing selective pressures on group size evolution and drivers of population dynamics. Research on how competitors assess (i.e., gather information on) fighting ability and contested resources, as well as how assessment impacts on contest processes and outcomes, has been fundamental to the field of dyadic (one-on-one) contests. Despite recent growth in studies of contests between social-living groups, there is limited understanding of assessment during these intergroup contests. We adapt current knowledge of dyadic contest assessment to the intergroup case, describing what traits of groups, group members, and resources are assessed, and how assessment is manifested in contest processes (e.g., behaviors) and outcomes. This synthesis helps to explain the role of individual heterogeneity in assessment and how groups are shaped by the selective pressure of contests. Research on how competitors assess (i.e., gather information on) fighting ability and contested resources, as well as how assessment impacts on contest processes and outcomes, has been fundamental to the field of dyadic (one-on-one) contests. Despite recent growth in studies of contests between social-living groups, there is limited understanding of assessment during these intergroup contests. We adapt current knowledge of dyadic contest assessment to the intergroup case, describing what traits of groups, group members, and resources are assessed, and how assessment is manifested in contest processes (e.g., behaviors) and outcomes. This synthesis helps to explain the role of individual heterogeneity in assessment and how groups are shaped by the selective pressure of contests. Animal contests determine access to crucial resources such as territory, food, and mates. Because contest outcomes result in the unequal distribution of resources (e.g., mating opportunities [1.Jennings D.J. Contest behaviour varies in relation to reproductive opportunities and reproductive success in the fallow deer.Anim. Beh. 2020; 163: 95-103Crossref Scopus (2) Google Scholar]), contests influence resource ecology. In addition, traits such as dynamic displays [2.Searcy W.A. Nowicki S. The Evolution of Animal Communication: Reliability and Deception in Signaling Systems. Princeton University Press, 2005Google Scholar] and exaggerated weapons [3.Emlen D.J. The evolution of animal weapons.Annu. Rev. Ecol. Evol. Syst. 2008; 39: 387-413Crossref Scopus (423) Google Scholar] are thought to evolve, in part, under the selective pressure of contests. Much of our knowledge of contests has come from studies of assessment (see Glossary), or information-gathering, during dyadic contests between individuals. Models of dyadic contests, which have usually been validated using evolutionary game theory [4.Maynard Smith J. Price G.R. The logic of animal conflict.Nature. 1973; 246: 15-18Crossref Scopus (3669) Google Scholar], and experimental tests of these models (reviewed in [5.Hardy I.C.W. Briffa M. Animal Contests. Cambridge University Press, 2013Crossref Google Scholar]), show how individuals assess intrinsic traits (behavioral, morphological, physiological) of themselves and/or their competitors, as well as extrinsic factors (e.g., resources). In turn, this assessment influences strategic decision-making such as the decision to give up a contest (Box 1). We term this suite of models and corresponding approaches for experimental tests the dyadic contest assessment framework.Box 1Dyadic and Intergroup Contest Assessment TheoryBoth dyadic and intergroup contests are associated with specific theories that make predictions regarding how contests should proceed. However, the focus of those predictions differs between the two types of contest. Dyadic contest theory usually generates predictions about within-contest changes in the intensity of fighting, based on assumptions regarding the adaptive value (that is in some but not all cases verified as an evolutionarily stable solution) of various assessment strategies. By contrast, intergroup theory makes predictions about attrition rates experienced by the weaker side, based on assumptions about the effect of using a numerical advantage in two distinct ways (see below).Dyadic contest theory has a long history at the core of behavioral ecology [38.Kokko H. Dyadic contests: modelling fights between two individuals.in: Hardy I.C.W. Briffa M. Animal Contests. Cambridge University Press, 2013: 5-32Crossref Google Scholar]. Empirical work has focused on directly testing the assumptions, and sometimes the predictions, of three models: the sequential assessment model (SAM) [66.Enquist M. Leimar O. Evolution of fighting behaviour: decision rules and assessment of relative strength.J. Theor. Biol. 1983; 102: 387-410Crossref Scopus (611) Google Scholar], the energetic war of attrition (EWOA) model [50.Payne R.J.H. Pagel M. Escalation and time costs in displays of endurance.J. Theor. Biol. 1996; 183: 185-193Crossref Scopus (133) Google Scholar], and the cumulative assessment model (CAM) [82.Payne R.J.H. Gradually escalating fights and displays: the cumulative assessment model.Anim. Behav. 1998; 56: 651-662Crossref PubMed Scopus (205) Google Scholar]. The SAM assumes that each rival compares its own resource holding potential (RHP) with that of the opponent, and losers give up when they know they are weaker ('mutual assessment'). The EWOA and CAM assume that losers give up when the accumulated costs cross a threshold ('self-assessment'). A correlational approach described by Taylor and Elwood [78.Taylor P.W. Elwood R.W. The mismeasure of animal contests.Anim. Behav. 2003; 65: 1195-1202Crossref Scopus (238) Google Scholar], as well as analyses of contest behavioral progressions [83.Briffa M. Elwood R.W. Difficulties remain in distinguishing between mutual and self-assessment in animal contests.Anim. Behav. 2009; 77: 759-762Crossref Scopus (85) Google Scholar], are often used to distinguish between these two assessment rules (Figure I), although many contests may fall outside this dichotomy [72.Chapin K.J. et al.Further mismeasures of animal contests: a new framework for assessment strategies.Behav. Ecol. 2019; 30: 1177-1185Crossref Scopus (19) Google Scholar,77.Briffa M. et al.Using ternary plots to investigate continuous variation in animal contest strategies.Anim. Behav. 2020; 167: 85-99Crossref Scopus (4) Google Scholar].Intergroup contests are considered by a body of theory spanning third-party interventions up to conflicts between larger groups (reviewed in [13.Rusch H. Gavrilets S. The logic of animal intergroup conflict: a review.J. Econ. Behav. Org. 2017; 178: 1014-1030Crossref Scopus (26) Google Scholar,17.Sherratt T.N. et al.Models of group or multi-party contests.in: Hardy I.C.W. Briffa M. Animal Contests. Cambridge University Press, 2013: 33-46Crossref Google Scholar]). In the latter case, key ideas come from Lanchester's attrition laws developed during World War I. These models consider how superior numbers could be best utilized when armies have access to ranged weapons. If extra numbers on the more numerous side are held in reserve until needed (i.e., the more numerous side matches the number of combatants and/or materiel allocated by the less numerous side), then Lanchester's linear law should be followed (Figure I). Lanchester's square law would be followed if the more numerous side commit their extra numbers to the fray, such that members of that side can concentrate their attacks on the outnumbered members of the weaker side (Figure I). Both dyadic and intergroup contests are associated with specific theories that make predictions regarding how contests should proceed. However, the focus of those predictions differs between the two types of contest. Dyadic contest theory usually generates predictions about within-contest changes in the intensity of fighting, based on assumptions regarding the adaptive value (that is in some but not all cases verified as an evolutionarily stable solution) of various assessment strategies. By contrast, intergroup theory makes predictions about attrition rates experienced by the weaker side, based on assumptions about the effect of using a numerical advantage in two distinct ways (see below). Dyadic contest theory has a long history at the core of behavioral ecology [38.Kokko H. Dyadic contests: modelling fights between two individuals.in: Hardy I.C.W. Briffa M. Animal Contests. Cambridge University Press, 2013: 5-32Crossref Google Scholar]. Empirical work has focused on directly testing the assumptions, and sometimes the predictions, of three models: the sequential assessment model (SAM) [66.Enquist M. Leimar O. Evolution of fighting behaviour: decision rules and assessment of relative strength.J. Theor. Biol. 1983; 102: 387-410Crossref Scopus (611) Google Scholar], the energetic war of attrition (EWOA) model [50.Payne R.J.H. Pagel M. Escalation and time costs in displays of endurance.J. Theor. Biol. 1996; 183: 185-193Crossref Scopus (133) Google Scholar], and the cumulative assessment model (CAM) [82.Payne R.J.H. Gradually escalating fights and displays: the cumulative assessment model.Anim. Behav. 1998; 56: 651-662Crossref PubMed Scopus (205) Google Scholar]. The SAM assumes that each rival compares its own resource holding potential (RHP) with that of the opponent, and losers give up when they know they are weaker ('mutual assessment'). The EWOA and CAM assume that losers give up when the accumulated costs cross a threshold ('self-assessment'). A correlational approach described by Taylor and Elwood [78.Taylor P.W. Elwood R.W. The mismeasure of animal contests.Anim. Behav. 2003; 65: 1195-1202Crossref Scopus (238) Google Scholar], as well as analyses of contest behavioral progressions [83.Briffa M. Elwood R.W. Difficulties remain in distinguishing between mutual and self-assessment in animal contests.Anim. Behav. 2009; 77: 759-762Crossref Scopus (85) Google Scholar], are often used to distinguish between these two assessment rules (Figure I), although many contests may fall outside this dichotomy [72.Chapin K.J. et al.Further mismeasures of animal contests: a new framework for assessment strategies.Behav. Ecol. 2019; 30: 1177-1185Crossref Scopus (19) Google Scholar,77.Briffa M. et al.Using ternary plots to investigate continuous variation in animal contest strategies.Anim. Behav. 2020; 167: 85-99Crossref Scopus (4) Google Scholar]. Intergroup contests are considered by a body of theory spanning third-party interventions up to conflicts between larger groups (reviewed in [13.Rusch H. Gavrilets S. The logic of animal intergroup conflict: a review.J. Econ. Behav. Org. 2017; 178: 1014-1030Crossref Scopus (26) Google Scholar,17.Sherratt T.N. et al.Models of group or multi-party contests.in: Hardy I.C.W. Briffa M. Animal Contests. Cambridge University Press, 2013: 33-46Crossref Google Scholar]). In the latter case, key ideas come from Lanchester's attrition laws developed during World War I. These models consider how superior numbers could be best utilized when armies have access to ranged weapons. If extra numbers on the more numerous side are held in reserve until needed (i.e., the more numerous side matches the number of combatants and/or materiel allocated by the less numerous side), then Lanchester's linear law should be followed (Figure I). Lanchester's square law would be followed if the more numerous side commit their extra numbers to the fray, such that members of that side can concentrate their attacks on the outnumbered members of the weaker side (Figure I). More recently, there has been rapid growth in the field of intergroup contests – contests between groups of social-living organisms. This work has been driven, in part, by attempts to understand human conflict [6.Riddihough G. et al.Human conflict: winning the peace.Science. 2012; 336: 818-819Crossref PubMed Scopus (11) Google Scholar,7.Henriques G.J. et al.Acculturation drives the evolution of intergroup conflict.Proc. Natl. Acad. Sci. U. S. A. 2019; 116: 14089-14097Crossref PubMed Scopus (3) Google Scholar]. Intergroup contests are also widespread in non-human organisms, including bacteria (multiple species) [8.Granato E.T. et al.The evolution and ecology of bacterial warfare.Curr. Biol. 2019; 29: R521-R537Abstract Full Text Full Text PDF PubMed Scopus (116) Google Scholar], ants (e.g., harvester ants Messor barbarus) [9.Birch G. et al.Behavioural response of workers to repeated intergroup encounters in the harvester ant Messor barbarus.Insect. 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Org. 2017; 178: 1014-1030Crossref Scopus (26) Google Scholar, 14.Reeve H.K. Holldobler B. The emergence of a superorganism through intergroup competition.Proc. Natl Acad. Sci. USA. 2007; 104: 9736-9740Crossref PubMed Scopus (132) Google Scholar, 15.Choi J.K. Bowles S. The coevolution of parochial altruism and war.Science. 2007; 318: 636-640Crossref PubMed Scopus (608) Google Scholar, 16.Gavrilets S. Fortunato L. A solution to the collective action problem in between-group conflict with within-group inequality.Nat. Comm. 2014; 5: 3526Crossref PubMed Scopus (85) Google Scholar]. Our understanding of assessment during intergroup contests – how groups gather information on themselves, each other, and/or contested resources, and how that information is used to make group-level decisions – is still underdeveloped [17.Sherratt T.N. et al.Models of group or multi-party contests.in: Hardy I.C.W. Briffa M. Animal Contests. Cambridge University Press, 2013: 33-46Crossref Google Scholar]. The power of a rich history of dyadic contest research is the availability of a well-established framework that can be readily adapted to intergroup contests. The dyadic contest assessment framework can be studied through theoretical and empirical exploration of its individual components (Figure 1, Key Figure). These components include how competitors assess fighting ability and the ownership and value of contested resources, and how assessment is modified by prior experience. The framework shows how these components integrate to affect contest costs, behaviors, and outcomes, with impacts on ecology and trait evolution (Figure 1). Before a boxing match, commentators describe the 'tale of the tape' for both competitors, outlining size-based metrics such as weight, height, and reach that are thought to be associated with fighting success. In dyadic contest research, similar metrics describe what Parker [18.Parker G.A. Assessment strategy and the evolution of fighting behavior.J. Theor. Biol. 1974; 47: 223-243Crossref PubMed Scopus (1561) Google Scholar] termed resource holding potential (RHP), defined as 'absolute fighting ability'. RHP is a theoretical concept that is often measured by proxy as the single variable that best predicts contest success [19.Briffa M. et al.Analysis of animal contest data.in: Hardy I.C.W. Briffa M. Animal Contests. Cambridge University Press, 2013: 47-85Crossref Google Scholar] (Table 1). Most commonly this is body mass [19.Briffa M. et al.Analysis of animal contest data.in: Hardy I.C.W. Briffa M. Animal Contests. Cambridge University Press, 2013: 47-85Crossref Google Scholar]; other proxies include weapon size [20.Rink A.N. et al.Contest dynamics and assessment strategies in combatant monkey beetles (Scarabaeidae: Hopliini).Behav. Ecol. 2019; 30: 713-723Crossref Scopus (6) Google Scholar] and physiological capacity [21.Boisseau R.P. et al.The metabolic costs of fighting and host exploitation in a seed-drilling parasitic wasp.J. Exp. Biol. 2017; 220: 3955-3966Crossref PubMed Scopus (9) Google Scholar]. The behaviors important to a given contest system have been thought to drive RHP proxies; for example, systems where contests involve frequent physical contact might find force output the best RHP proxy, whereas systems where competitors avoid contact might find endurance-based RHP proxies, such as fat or glycogen reserves, more important [22.Lailvaux S.P. Irschick D.J. A functional perspective on sexual selection: insights and future prospects.Anim. Behav. 2006; 72: 263-273Crossref Scopus (183) Google Scholar]. A recent meta-analysis, however, found no support for this functional approach in arthropods [23.Vieira M.C. Peixoto P.E.C. Winners and losers: a meta-analysis of functional determinants of fighting ability in arthropod contests.Funct. Ecol. 2013; 27: 305-313Crossref Scopus (43) Google Scholar]. Though often measured as a single trait, RHP may instead be a composite of many morphological, physiological, and/or behavioral traits. For example, boxing success is not determined by reach alone, but likely by a combination of weight, height, reach, skill in delivering punches, and other factors. The best-supported single RHP proxy in intergroup contests is group size: the number of members in each group. A recent meta-analysis affirmed this in primates [12.Majolo B. et al.Effect of group size and individual characteristics on intergroup encounters in primates.Int. J. Primatol. 2020; 41: 325-341Crossref Scopus (14) Google Scholar], and group size is relevant in other taxa from ants (e.g., wood ants Formica rufa) [24.Batchelor T.P. Briffa M. Influences on resource-holding potential during dangerous group contests between wood ants.Anim. Beh. 2010; 80: 443-449Crossref Scopus (23) Google Scholar], to lions (Panthera leo) [25.Mosser A. Packer C. Group territoriality and the benefits of sociality in the African lion, Panthera leo.Anim. Behav. 2009; 78: 359-370Crossref Scopus (201) Google Scholar], to birds (green woodhoopoes Phoeniculus purpureus) ([26.Radford A.N. du Plessis M.A. Territorial vocal rallying in the green woodhoopoe: factors affecting contest length and outcome.Anim. Behav. 2004; 68: 803-810Crossref Scopus (50) Google Scholar]; cf [27.Strong M.J. et al.Home field advantage, not group size, predicts outcomes of intergroup conflicts in a social bird.Anim. Behav. 2018; 143: 205-213Crossref Scopus (14) Google Scholar] where group size does not predict outcomes in greater anis Crotophaga major). However, proxies other than absolute numbers might be important. A functional approach might predict that total group mass is a better RHP proxy than group size in contests that involve high levels of physical contact. Other metrics of intergroup contest RHP reveal the importance of within-group heterogeneity (Box 2). For example, although group size was an RHP proxy in grey wolf (Canis lupus) intergroup contests, groups with more males could overcome a group size disadvantage [28.Cassidy K.A. et al.Group composition effects on aggressive interpack interactions of gray wolves in Yellowstone National Park.Behav. Ecol. 2015; 26: 1352-1360Crossref Scopus (95) Google Scholar]. Males are larger and more aggressive than females, suggesting a functional reason for the impact of group heterogeneity on RHP. Finally, group social cohesion could also be a proxy of intergroup contest RHP – groups that execute contest behaviors in a more coordinated fashion may be more likely to win. Exactly as for dyadic contests, RHP for intergroup contests is likely a suite of traits comprising – within and among group members – morphology, physiology, and behavior. Intergroup contests are characterized by two features, heterogeneity and social cohesion, that play no role in dyadic contests. Unlike individuals, groups are inherently heterogeneous, being composed of individuals that vary in size, strength, genetic relatedness, and the value they place on contested resources. Group resource holding potential (RHP) is thus determined by both individual attributes and social cohesion – that is, the degree to which group members act together. Heterogeneity is the source of the collective action problem (CAP), where group success depends on collective effort, but the costs of effort are borne by the individual [84.Olson M. The Logic of Collective Action: Public Goods and the Theory of Groups, Second Printing with a New Preface and Appendix. Harvard University Press, 2009Crossref Google Scholar]. Individuals that are weaker or place lower value on a contested resource are predicted to free-ride on the effort of their stronger or more incentivized group mates [85.Ostrom E. Collective action and the evolution of social norms.J. Econ. 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In general, hierarchical societies are less vulnerable to the CAP because high-ranked individuals, who gain the largest share of the fitness benefits of contests, are predicted to overcompensate for free-riding by low-ranked individuals [16.Gavrilets S. Fortunato L. A solution to the collective action problem in between-group conflict with within-group inequality.Nat. Comm. 2014; 5: 3526Crossref PubMed Scopus (85) Google Scholar]. Strong social cohesion may leave heterogeneous groups vulnerable to the emergence of 'exploitative' leaders, who may initiate conflicts that benefit themselves but not the rest of the group [96.Johnstone R.A. et al.Exploitative leaders incite intergroup warfare in a social mammal.Proc. Natl. Acad. Sci. U. S. A. 2020; 117: 29759-29766Crossref PubMed Scopus (11) Google Scholar]. Exploitative leadership is predicted when leaders gain greater benefits or suffer lower costs from conflict than other group members, but where there are strong constraints against desertion. In such circumstances, selection acting on leaders can lead to damaging levels of intergroup conflict, with negative consequences for population fitness. This model can explain violent intergroup conflict in banded mongooses, a species in which females lead groups into contact with rival groups and instigate intergroup contests in which males disproportionately bear the costs of fighting [96.Johnstone R.A. et al.Exploitative leaders incite intergroup warfare in a social mammal.Proc. Natl. Acad. Sci. U. S. A. 2020; 117: 29759-29766Crossref PubMed Scopus (11) Google Scholar]. The decoupling of leaders from the costs they incite may be one of the evolutionary causes of extreme intergroup aggression. Previous fighting experience can impact on how animals assess their own RHP and/or that of their opponent (Table 1). One well-known example in dyadic contests, with building evidence in intergroup contests, is winner and loser effects (Figure 1), in which winners of contests are more likely to win future contests, and losers to lose (reviewed for dyadic contests in [29.Hsu Y. et al.Modulation of aggressive behaviour by fighting experience: mechanisms and contest outcomes.Biol. Rev. 2006; 81: 33-74Crossref PubMed Scopus (509) Google Scholar]). Winner and loser effects are often observed in the behaviors used in subsequent contests. For example, male red-bellied woodpeckers (Melanerpes carolinus) that won simulated (via playback experiments) contests gave more territorial displays to future simulated intruders [30.Miles M.C. Fuxjager M.J. Social context modulates how the winner effect restructures territorial behaviour in free-living woodpeckers.Anim. 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Conflict between groups promotes later defense of a critical resource in a cooperatively breeding bird.Curr. Biol. 2014; 24: 2935-2939Abstract Full Text Full Text PDF PubMed Scopus (28) Google Scholar] where losers slept closer to the territory boundary). Although these behavioral changes imply a loser effect, none of these studies tested whether losing groups actually lost, or winning groups won, future contests – a key component of establishing winner or loser effects. In the same way as understanding dyadic RHP helps to develop hypotheses for how contests influence trait evolution (e.g., animal weapons [35.O'Brien D.M. et al.Muscle mass drives cost in sexually selected arthropod weapons.Proc. R. Soc. B. 2019; 28620191063Crossref PubMed Scopus (20) Google Scholar]), studies of intergroup contest RHP and its assessment can reveal selective forces that act on group living. For example, a competitive advantage of increased group size may lead to the evolution of larger groups (Figure 1). Which competitor owns a contested resource [36.Kokko H. et al.From hawks and doves to self-consistent games of territorial behavior.Am. Nat. 2006; 167: 901-912Crossref PubMed Scopus (151) Google Scholar] and the value of the resource to each competitor [37.Arnott G. Elwood R.W. Information gathering and decision making about resource value in animal contests.Anim. Beh. 2008; 76: 529-542Crossref Scopus (218) Google Scholar] is a central feature of dyadic conflict that also plays an important role in intergroup contests (Figure 1). These resource ownership (also termed 'prior residency') and resource value effects