Risk-taking incentives predict aggression heuristics in female gorillas

In the wild, animals frequently compete for access to resources critical for survival and reproduction, such as food. Competition among members of a social group often leads to social hierarchies, with higher-ranking individuals typically acting as aggressors, and conflicts occurring mostly between individuals of similar rank. While patterns of aggression are often considered species-specific, social, ecological, and physiological factors may also play important roles in shaping them.

To better understand the dynamics underlying aggressive interactions in animals, Smit and Robbins analysed long-term data sets of five groups of wild gorillas, dating back to the late 1990s. These included one group of wild western gorillas and four groups of wild mountain gorillas. They recorded aggressive interactions among females and assigned each a ‘risk score’. Interactions were considered riskier when lower-ranking females targeted higher-ranking opponents.

The analyses revealed that females with greater energetic needs – such as pregnant and lactating females – were more likely to engage in risky aggression, targeting more powerful opponents. Females also directed aggression toward more powerful opponents when more males were present, which could protect them from retaliation. Conversely, females chose weaker opponents when more females were present, suggesting that when females have more options, they choose among the less risky ones.

These results suggest that animals can adapt their behaviour based on both their social environment and individual needs. As a result, aggression tactics and social dynamics can vary significantly even within the same species – driven by the circumstances that individuals experience at different times.

Studying competition in animal societies and aggression among individuals of different ranks offers valuable insights into the evolution of more egalitarian or despotic structures – including in humans. This research can also help us better understand the behaviour of individuals experiencing resource scarcity or desperation, and how these can motivate individuals to navigate their social landscape and challenge their social hierarchies.

Animals that live in groups often compete for access to resources such as food and mates (Carel, 1989; Koenig, 2002). The potential costs of this competition can drive the formation of hierarchies that determine priority of access to resources without superfluous conflicts (Rowell, 1974; Boone, 2017). Accordingly, individuals may choose strategically who they compete with in order to minimize costs and maximize gains. Previous research suggests that individuals primarily compete with those closest in the hierarchy, to attain (against close higher-ranking) or maintain (against close lower-ranking individuals) their ranks (‘rank-dependent aggression’; Vogel et al., 2007; Hobson and DeDeo, 2015; Wright et al., 2019; Hobson et al., 2021; Dehnen et al., 2022b; Dehnen et al., 2022a). Aggression, probably the most straightforward proxy of competition, commonly increases in frequency when resource availability is lower, and it is most often directed towards lower-ranking individuals (Hobson et al., 2021; Smit and Robbins, 2024). Yet, recent research has demonstrated that the rules that animals use to guide their aggressive interactions (‘aggression heuristics’) towards groupmates of different ranks vary even within species (Hobson and DeDeo, 2015; Hobson et al., 2021). In this study, we test the hypothesis that this variation arises due to the different conditions that (individual) animals experience, and specifically that the social environment and individual energetic needs shape competitive incentives and aggression towards individuals of different ranks.

Regarding the social environment, larger group sizes may entail a larger number of low-ranking individuals which are cumulatively targeted, as competition and aggression are preferentially directed towards the lowest-ranking groupmates (see also ‘bullying’ in Hobson et al., 2021). When individuals have access to a larger pool of competitors, they may preferentially target less powerful ones, consistent with risk-sensitivity theory, which posits that individuals tend to minimize risks when they have the option (Caraco, 1981; Barclay et al., 2018). Conversely, larger group sizes might entail a larger number of allies (e.g. kin for spotted hyaenas, Crocuta crocuta, Vullioud et al., 2019) or protectors (e.g. adult males for female gorillas, Watts, 1997; Smit and Robbins, 2024), which can increase social support and, eventually, minimize any risk-related costs of aggression towards higher-ranking competitors. Hence, group size, the overall number of individuals in the group, might be a poor predictor of aggression because it conflates opposing effects of different kinds of individuals (e.g. see Smit and Robbins, 2024 for an example of opposing effects of the number of females and number of males on female gorilla aggression). Finally, if larger group sizes promote within-group competition increasing overall aggression rates (Slotow, 1996; Koenig, 2002; Smit and Robbins, 2024), they might simultaneously promote high-ranking individuals to reinforce their status by targeting lower-ranking groupmates and lower-ranking individuals to direct aggression against higher-ranking groupmates if this can allow them access to precious resources.

Regarding the energetic needs, greater needs for resources may boost the incentives of higher-ranking individuals to reinforce their status by strategically directing their competitive efforts towards lower-ranking groupmates (Hobson et al., 2021; Dehnen et al., 2022b; Strauss and Shizuka, 2022). Contrarily, greater individual needs may also prompt low-ranking individuals, who struggle more to access resources and experience a lower risk-reward ratio (more to gain, less to lose), to show greater aggression rates even against higher-ranking groupmates (Parker and Rubenstein, 1981; Sapolsky, 1993; Sapolsky, 2005). This aggression may help individuals to improve their ranks but it might be risky if it can incite retaliation from high-ranking, powerful, recipients. Yet, the benefits related to status improvement (long-term benefit) or resource acquisition (short-term benefit) might counterbalance any risk-related costs. Various empirical examples support the latter hypothesis: hunger-driven payoff asymmetries can increase aggression from lower- to higher-ranking individuals (noble crayfish, Astacus astacus; Gruber et al., 2016), reproductive suppression of low-ranking females can promote conflict escalation against high-ranking ones (paper wasps, Polistes dominulus; Cant et al., 2006), and the energetic/nutritional needs of pregnancy (due to support of fetal growth) or lactation (due to milk production) can increase female aggression that reverses hierarchical relationships (Murie and Harris, 1988; Lu et al., 2013; Lu et al., 2016).

Studies investigating the influence of social, ecological, or physiological factors on aggression patterns across species usually focus on aggression frequency/rate (Vogel and Janson, 2011; Nie et al., 2013); in this study, we build on this literature to test how relevant factors influence ‘aggression direction’ in terms of power differentials, aiming to unravel another evolutionary aspect of competitive strategies. Gorillas represent an intriguing case for this endeavour because females of both species form surprisingly stable hierarchical relationships, usually maintained over their whole co-residence in a group, but they often direct aggression towards higher-ranking groupmates (Smit and Robbins, 2025; Watts, 1994; Robbins, 2008). Female–female aggression rates towards both higher- and lower-ranking rivals decrease with the number of adult males/protectors in the group but increase with the number of females/competitors in the group (Watts, 1994; Robbins, 2008; Wright and Robbins, 2014; Smit and Robbins, 2024). Additionally, aggression rates are greater in pregnant females (Smit and Robbins, 2024), which, like lactating females, spend more time feeding (Watts, 1983), highlighting the greater energetic needs of females in these reproductive states – similar to humans and other apes (Dufour and Sauther, 2002).

We use behavioural observations on one wild western (Gorilla gorilla gorilla) and four wild mountain (Gorilla beringei beringei) gorilla groups, starting in 1998 in one of the mountain gorilla groups, to test if the social environment or energetic needs influence female aggression towards more or less powerful females. Specifically, we test whether females direct aggression of lower or higher score (score = recipient-aggressor rank difference) depending on (i) the number of males in their group who may support or protect females, (ii) the number of females in the group representing competitors over resources, and (iii) female reproductive state (cycling, pregnant, or lactating) which is an indirect proxy of energetic needs. We compare our results on the direction of aggression to previous results examining the effects of the same variables on aggression frequency/rates.

We analysed 6871 aggressive interactions among a total of 31 adult female gorillas in the five social groups (Table 2). The average percentage of aggressive interactions directed from lower- to higher-ranking females across groups was 41.8 ± 6.7% (± SD; ATA: 47.2%; BIT: 46.3%; KYA: 36.5%; MUK: 46.1%; ORU: 32.7%). For comparison, only 16.4 ± 4.1% of displacement/avoidance interactions that we used to infer the highly stable hierarchies (details in Smit and Robbins, 2025) were directed from lower- to higher-ranking females (± SD; ATA: 15.4%; BIT: 19.2%; KYA: 12.8%; MUK: 22.1%; ORU: 12.5%). This result confirms previous evidence that aggression may not be a reliable proxy of power in gorillas or other species (Watts, 1994; Robbins, 2008; Smit, 2024).

Aggression from lower- to higher-ranking females was 85% mild, 9% moderate, and 6% severe while aggression from higher- to lower-ranking females was 82% mild, 10% moderate, and 8% severe. Generally, aggression of different intensity showed similar distributions and all aggression was most common from higher- to lower-ranking females close in rank (–0.5>score>0; Figure 2). The interactions of mild aggression were of greater score (recipient-aggressor rank difference) than the interactions of moderate aggression, meaning that females were more likely to use mild rather than moderate aggression against more powerful rivals, but the score difference between interactions of severe and moderate or mild aggression was not significant (Table 2).

Figure 2

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Female gorillas directed aggression of greater score when there were more males in the group and when there were fewer females in the group (Figure 3, Table 2). When we ran our analysis testing for group size (number of weaned individuals in the group), instead of the numbers of males and females, its influence on interaction score was not significant (estimate=−0.001, p-value=0.682). Females in the third trimester of pregnancy directed the aggression of the greatest score, females in any pregnancy stage directed aggression of greater score than lactating and cycling females, and lactating females directed aggression of greater score than cycling females, likely highlighting an effect of energetic needs on aggression heuristics (Figure 3, Table 2). Post hoc pairwise comparisons showed significant differences between all reproductive states, apart from the difference of the first and the other two trimesters of pregnancy (Table 3, Figure 3). When we ran our analysis merging pregnancy trimesters into one category, we found pregnant females to direct aggression of significantly greater score than lactating and cycling females, and lactating females to direct aggression of significantly greater score than cycling females (not shown). Finally, our results did not show any significant difference between aggression score of western (only one group) and mountain gorillas groups.

Figure 3

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Notably, a positive (or negative) correlation of a predictor with the interaction score does not necessarily represent a shift from aggression towards females lower-ranking than the aggressor to aggression towards females higher-ranking than the aggressor (or vice versa) – but, more generally, it represents a shift of aggression towards more (or less) powerful females independently of the rank relationship to the aggressor. For example, females in the second trimester of pregnancy direct most aggression towards rivals higher-ranking than themselves; yet they direct aggression of significantly lower score than females in the third trimester of pregnancy, that is, the latter direct more aggression to females even more higher-ranking than those during the second trimester (Figure 3, Table 2).

Most aggression was directed from higher to lower-ranking females, usually close in rank, supporting the hypothesis that individuals commonly use aggression to reinforce their status. However, approximately 42% of aggression was directed from lower- to higher-ranking females, which is even greater than previous estimations in gorillas (34% [Watts, 1994] and 25% [Robbins, 2008]) and also greater than in many other animals (Hobson et al., 2021). Our results suggest that such aggression towards more powerful rivals reflects competitive incentives influenced by the social environment and driven by circumstantial needs. This interpretation is in line with previous observations showing that female gorillas are usually unable to improve their ranks through active competition, as they form highly stable hierarchical relationships (Smit and Robbins, 2025), that is, aggression is unlikely to be used for challenging the hierarchy. Importantly, female gorillas are more likely to respond aggressively (‘retaliate’) than submissively to aggression from other females (Watts, 1994), meaning that aggression involves some risk for the aggressor, especially when it targets more powerful groupmates. Thus, greater interaction scores reflect greater risks (the greater the relative rank of the recipient, the greater the risk for the aggressor), and our results suggest that the social environment and circumstantial needs may influence individual decisions to engage in risky behaviours.

Female gorillas appeared to direct aggression of greater score when there were more males in the group, potentially supporting our interpretation that male support or protection (Watts, 1994; Watts, 1997) provides females with an environment to take greater risks. Males may support lower-ranking females in order to decrease competitive inequities among females (e.g. to prevent low-ranking female emigration from their group; Sicotte, 2002) and high-ranking females might hesitate to retaliate to aggressors and escalate a contest if more males are adjacent to the aggressors or are simply present in the group and can intervene. Interestingly, when females have access to fewer males, they generally exhibit greater aggression rates towards other females (Smit and Robbins, 2024; Table 2, column ‘Aggression rates’), potentially competing for male protection per se; but once they have access to more males (and male protection), they appear to direct more aggression to more powerful female rivals.

In contrast to the number of adult males, the number of adult females in the group was negatively correlated with interaction score, that is, female gorillas directed aggression to lower-ranking, less powerful, females when there were more females in the group. Hence, the previously observed increase in aggression rates in groups with more females (Smit and Robbins, 2024; Table 2, column ‘Aggression rates’) likely pertains predominantly to aggression from more to less powerful rivals. Our result may reflect that females preferably target less powerful rivals when they have access to a larger pool of competitors to choose from, similar to humans (Savage et al., 2020; see also risk-sensitivity theory in introduction). Alternatively, the increased competition due to a larger number of competitors may prompt higher-ranking females to reinforce their status more than it prompts lower-ranking females to target higher-ranking ones in order to access resources. Overall, the combination of our present and previous results (Smit and Robbins, 2024) showing the influence of the number of males and females on both female aggression rates and aggression direction confirms that non-human animals can adapt their aggression patterns according to the social context or the available social information (see also Haux et al., 2021).

Aggression score was also influenced by energetic needs: female gorillas in the most energetically demanding reproductive states directed aggression to more powerful females (greater aggression score = greaterrecipient-aggressor rank difference). Females in the last and most energetically demanding stage of pregnancy directed aggression of greater score than all other females (this difference was significant for all reproductive states except for females in the first trimester of pregnancy), females in any stage of pregnancy directed aggression of greater score than lactating and cycling females, and lactating females directed aggression of greater score than cycling females. While lactating females can have greater energetic needs than pregnant females, they might direct aggression of lower score than pregnant females because they have lower risk tolerance in aggression, especially towards higher-ranking groupmates, in order to protect their dependent infants, reminiscent of risk-avoidance behaviours of lactating female African wild dogs (Lycaon pictus; Marneweck et al., 2021) and black bears (Ursus americanus; Gantchoff et al., 2019). This interpretation is consistent with previous results showing that lactating females show the lowest aggression rates (Smit and Robbins, 2024; see also column ‘Aggression rates’ in Table 2). Yet, lactating females directed aggression of greater score than cycling females, despite the fact that they exhibit lower aggression rates than cycling females (Smit and Robbins, 2024; Table 2, column ‘Aggression rates’). Lactating females have greater proximity to alpha males (Harcourt, 1979; Rosenbaum et al., 2016), that potentially offers them greater access to resources with no need for direct female-female competition (low aggression rates), but it might also buffer female–female aggression risk if males mediate/intervene in female aggressive interactions (Watts, 1994; Watts, 1997), allowing lactating females to direct aggression to generally more powerful rivals (high aggression score), even if this aggression is infrequent.

Our study suggests that aggression heuristics depend on the social environment and individual needs, meaning that the variation in heuristics observed within or between species (Hobson et al., 2021) at least partially reflects differences in the conditions that specific animal populations or individuals experience at different time points. Our study also adds to behavioural observations from several species suggesting that individuals with greater needs might engage in more risky behaviours (Verdolin, 2006; Bruyneel et al., 2009; Jordan et al., 2011), including inter-individual competition (Garamszegi et al., 2009; Rosati and Hare, 2012; Bertram et al., 2016). Accordingly, it improves our understanding of the evolution of risk-taking in hominids, including (aggressive) competition in humans where individuals unsuccessful in economic or mating competition may exhibit risky aggressive behaviours (Wilson and Daly, 1985; Campbell, 1995; Mishra and Lalumière, 2008; Hill and Buss, 2010; Wohl et al., 2014). Finally, our results may provide some insights regarding the evolution of more egalitarian or despotic societies of other species: if certain social factors or individual conditions can drive shifts in aggression up or down the hierarchy, then they have the potential to flatten or reinforce the hierarchy, respectively.

The data and code necessary to replicate this study are available at GitLab, copy archived at Smit, 2025.

1. 1. Albers PCH
   2. de Vries H

   (2001) Elo-rating as a tool in the sequential estimation of dominance strengths

   Animal Behaviour 61:489–495.

   https://doi.org/10.1006/anbe.2000.1571

   • Google Scholar
2. 1. Barclay P
   2. Mishra S
   3. Sparks AM

   (2018) State-dependent risk-taking

   Proceedings. Biological Sciences 285:20180180.

   https://doi.org/10.1098/rspb.2018.0180

   • PubMed
   • Google Scholar
3. 1. Bertram SM
   2. Healy C
   3. Hogge J
   4. Kritikos Z
   5. Pipitone J
   6. Kolluru GR

   (2016) Positive relationship between risk-taking behaviour and aggression in subordinate but not dominant males of a Cuban poeciliid fish

   Behaviour 153:1489–1507.

   https://doi.org/10.1163/1568539X-00003392

   • Google Scholar
4. Book

   1. Boone JL

   (2017)

   Competition, conflict, and the development of social hierarchies

   In: Boone JL, editors. Evolutionary Ecology and Human Behavior. Routledge. pp. 301–338.

   • Google Scholar
5. 1. Brooks ME
   2. Kristensen K
   3. van Benthem KJ
   4. Berg CW
   5. Nielsen A
   6. Skaug HJ
   7. Mächler M
   8. Bolker BM

   (2017) glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling

   The R Journal 9:378.

   https://doi.org/10.32614/RJ-2017-066

   • Google Scholar
6. 1. Bruyneel SD
   2. Dewitte S
   3. Franses PH
   4. Dekimpe MG

   (2009) I felt low and my purse feels light: depleting mood regulation attempts affect risk decision making

   Journal of Behavioral Decision Making 22:153–170.

   https://doi.org/10.1002/bdm.619

   • Google Scholar
7. 1. Butte NF
   2. King JC

   (2005) Energy requirements during pregnancy and lactation

   Public Health Nutrition 8:1010–1027.

   https://doi.org/10.1079/phn2005793

   • PubMed
   • Google Scholar
8. 1. Campbell A

   (1995) A few good men: Evolutionary psychology and female adolescent aggression

   Ethology and Sociobiology 16:99–123.

   https://doi.org/10.1016/0162-3095(94)00072-F

   • Google Scholar
9. 1. Cant MA
   2. English S
   3. Reeve HK
   4. Field J

   (2006) Escalated conflict in a social hierarchy

   Proceedings of the Royal Society B 273:2977–2984.

   https://doi.org/10.1098/rspb.2006.3669

   • Google Scholar
10. 1. Caraco T

    (1981) Risk-Sensitivity and Foraging Groups

    Ecology 62:527–531.

    https://doi.org/10.2307/1937716

    • Google Scholar
11. Book

    1. Carel PVS

    (1989)

    Comparative Socioecology: The Behavioural Ecology of Humans and Other Mammals

    Blackwell.

    • Google Scholar
12. 1. Czekala N
    2. Sicotte P

    (2000) Reproductive monitoring of free-ranging female mountain gorillas by urinary hormone analysis

    American Journal of Primatology 51:209–215.

    https://doi.org/10.1002/1098-2345(200007)51:3<209::AID-AJP6>3.0.CO;2-6

    • PubMed
    • Google Scholar
13. 1. Dehnen T
    2. Arbon JJ
    3. Farine DR
    4. Boogert NJ

    (2022a) How feedback and feed-forward mechanisms link determinants of social dominance

    Biological Reviews of the Cambridge Philosophical Society 97:1210–1230.

    https://doi.org/10.1111/brv.12838

    • PubMed
    • Google Scholar
14. 1. Dehnen T
    2. Papageorgiou D
    3. Nyaguthii B
    4. Cherono W
    5. Penndorf J
    6. Boogert NJ
    7. Farine DR

    (2022b) Costs dictate strategic investment in dominance interactions

    Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 377:20200447.

    https://doi.org/10.1098/rstb.2020.0447

    • PubMed
    • Google Scholar
15. 1. Dufour DL
    2. Sauther ML

    (2002) Comparative and evolutionary dimensions of the energetics of human pregnancy and lactation

    American Journal of Human Biology 14:584–602.

    https://doi.org/10.1002/ajhb.10071

    • PubMed
    • Google Scholar
16. 1. Eckardt W
    2. Fawcett K
    3. Fletcher AW

    (2016) Weaned age variation in the Virunga mountain gorillas (Gorilla beringei beringei): influential factors

    Behavioral Ecology and Sociobiology 70:493–507.

    https://doi.org/10.1007/s00265-016-2066-6

    • Google Scholar
17. Book

    1. Elo AE

    (1978)

    The Rating of Chessplayers, Past and Present

    Arco Pub.

    • Google Scholar
18. Book

    1. Fox J
    2. Weisberg S

    (2019)

    An R Companion to Applied Regression

    Sage.

    • Google Scholar
19. Software

    1. Fox J
    2. Weisberg S
    3. Price B
    4. Friendly M
    5. Hong J
    6. Andersen R
    7. Firth D
    8. Taylor S
    9. Team RC

    (2022) Effects: effect displays for linear, generalized linear, and other models, version 4.2-2

    CRAN.

    https://cran.r-project.org/package=effects
20. 1. Gantchoff MG
    2. Beyer D
    3. Belant JL

    (2019) Reproductive class influences risk tolerance during denning and spring for American black bears ( Ursus americanus )

    Ecosphere 10:e02705.

    https://doi.org/10.1002/ecs2.2705

    • Google Scholar
21. 1. Garamszegi LZ
    2. Eens M
    3. Török J

    (2009) Behavioural syndromes and trappability in free-living collared flycatchers, Ficedula albicollis

    Animal Behaviour 77:803–812.

    https://doi.org/10.1016/j.anbehav.2008.12.012

    • Google Scholar
22. 1. Gruber C
    2. Tulonen J
    3. Kortet R
    4. Hirvonen H

    (2016) Resource availability and predation risk influence contest behavior and dominance hierarchies in crayfish

    Behavioral Ecology and Sociobiology 70:1305–1317.

    https://doi.org/10.1007/s00265-016-2139-6

    • Google Scholar
23. 1. Harcourt AH

    (1979) Social relationships between adult male and female mountain gorillas in the wild

    Animal Behaviour 27:325–342.

    https://doi.org/10.1016/0003-3472(79)90166-0

    • Google Scholar
24. Software

    1. Hartig F

    (2022) DHARMa: residual diagnostics for hierarchical (multi-level / mixed) regression models, version 0.4.6

    CRAN.

    https://cran.r-project.org/package=DHARMa
25. 1. Haux LM
    2. Engelmann JM
    3. Herrmann E
    4. Hertwig R

    (2021) How chimpanzees decide in the face of social and nonsocial uncertainty

    Animal Behaviour 173:177–189.

    https://doi.org/10.1016/j.anbehav.2021.01.015

    • Google Scholar
26. 1. Hill SE
    2. Buss DM

    (2010) Risk and relative social rank: positional concerns and risky shifts in probabilistic decision-making

    Evolution and Human Behavior 31:219–226.

    https://doi.org/10.1016/j.evolhumbehav.2010.01.002

    • Google Scholar
27. 1. Hobson EA
    2. DeDeo S

    (2015) Social feedback and the emergence of rank in animal society

    PLOS Computational Biology 11:e1004411.

    https://doi.org/10.1371/journal.pcbi.1004411

    • PubMed
    • Google Scholar
28. 1. Hobson EA
    2. Mønster D
    3. DeDeo S

    (2021) Aggression heuristics underlie animal dominance hierarchies and provide evidence of group-level social information

    PNAS 118:e2022912118.

    https://doi.org/10.1073/pnas.2022912118

    • PubMed
    • Google Scholar
29. Software

    1. Hothorn T
    2. Bretz F
    3. Westfall P
    4. Heiberger RM
    5. Schuetzenmeister A
    6. Scheibe S

    (2025) Multcomp: simultaneous inference in general parametric models, version 1.4-28

    CRAN.

    https://cran.r-project.org/package=multcomp
30. 1. Jordan J
    2. Sivanathan N
    3. Galinsky AD

    (2011) Something to lose and nothing to gain: the role of stress in the interactive effect of power and stability on risk taking

    Administrative Science 56.4:530–558.

    https://doi.org/10.1177/0001839212441928

    • Google Scholar
31. 1. Koenig A

    (2002) Competition for resources and its behavioral consequences among female primates

    International Journal of Primatology 23:759–783.

    https://doi.org/10.1023/A:1015524931226

    • Google Scholar
32. 1. Lu A
    2. Borries C
    3. Caselli A
    4. Koenig A

    (2013) Effects of age, reproductive state, and the number of competitors on the dominance dynamics of wild female Hanuman langurs

    Behaviour 150:485–523.

    https://doi.org/10.1163/1568539X-00003064

    • Google Scholar
33. 1. Lu A
    2. Borries C
    3. Gustison ML
    4. Larney E
    5. Koenig A

    (2016) Age and reproductive status influence dominance in wild female Phayre’s leaf monkeys

    Animal Behaviour 117:145–153.

    https://doi.org/10.1016/j.anbehav.2016.04.020

    • Google Scholar
34. 1. Marneweck CJ
    2. van Schalkwyk OL
    3. Marneweck DG
    4. Beverley G
    5. Davies-Mostert HT
    6. Parker DM

    (2021) Reproductive state influences the degree of risk tolerance for a seasonally breeding mesopredator

    Behavioral Ecology 32:717–727.

    https://doi.org/10.1093/beheco/arab018

    • Google Scholar
35. Book

    1. Mishra S
    2. Lalumière ML

    (2008) Risk-taking, antisocial behavior, and life histories

    In: Duntley J, Shackelford TK, editors. Evolutionary Forensic Psychology. Oxford University Press. pp. 139–159.

    https://doi.org/10.1093/acprof:oso/9780195325188.003.0008

    • Google Scholar
36. 1. Murie JO
    2. Harris MA

    (1988) Social interactions and dominance relationships between female and male Columbian ground squirrels

    Canadian Journal of Zoology 66:1414–1420.

    https://doi.org/10.1139/z88-207

    • Google Scholar
37. 1. Neumann C
    2. Duboscq J
    3. Dubuc C
    4. Ginting A
    5. Irwan AM
    6. Agil M
    7. Widdig A
    8. Engelhardt A

    (2011) Assessing dominance hierarchies: validation and advantages of progressive evaluation with Elo-rating

    Animal Behaviour 82:911–921.

    https://doi.org/10.1016/j.anbehav.2011.07.016

    • Google Scholar
38. 1. Nie H
    2. Yao M
    3. Liu J

    (2013) Factors influencing aggression levels in root vole populations under the effect of food supply and predation

    ISRN Ecology 2013:1–6.

    https://doi.org/10.1155/2013/948915

    • Google Scholar
39. 1. Noren SR
    2. Udevitz MS
    3. Jay CV

    (2014) Energy demands for maintenance, growth, pregnancy, and lactation of female Pacific walruses (Odobenus rosmarus divergens)

    Physiological and Biochemical Zoology 87:837–854.

    https://doi.org/10.1086/678237

    • PubMed
    • Google Scholar
40. 1. Parker GA
    2. Rubenstein DI

    (1981) Role assessment, reserve strategy, and acquisition of information in asymmetric animal conflicts

    Animal Behaviour 29:221–240.

    https://doi.org/10.1016/S0003-3472(81)80170-4

    • Google Scholar
41. 1. Robbins MM

    (1996) Male‐male Interactions in heterosexual and all‐male wild mountain Gorilla groups

    Ethology 102:942–965.

    https://doi.org/10.1111/j.1439-0310.1996.tb01172.x

    • Google Scholar
42. 1. Robbins MM

    (2008) Feeding competition and agonistic relationships among Bwindi Gorilla beringei

    International Journal of Primatology 29:999–1018.

    https://doi.org/10.1007/s10764-008-9275-4

    • Google Scholar
43. 1. Robbins MM
    2. Robbins AM

    (2021) Variability of weaning age in mountain gorillas (Gorilla beringei beringei)

    American Journal of Physical Anthropology 174:776–784.

    https://doi.org/10.1002/ajpa.24237

    • PubMed
    • Google Scholar
44. 1. Rosati AG
    2. Hare B

    (2012) Decision making across social contexts: competition increases preferences for risk in chimpanzees and bonobos

    Animal Behaviour 84:869–879.

    https://doi.org/10.1016/j.anbehav.2012.07.010

    • Google Scholar
45. 1. Rosenbaum S
    2. Hirwa JP
    3. Silk JB
    4. Vigilant L
    5. Stoinski TS

    (2016) Infant mortality risk and paternity certainty are associated with postnatal maternal behavior toward adult male Mountain Gorillas (Gorilla beringei beringei)

    PLOS ONE 11:e0147441.

    https://doi.org/10.1371/journal.pone.0147441

    • PubMed
    • Google Scholar
46. 1. Rowell TE

    (1974) The concept of social dominance

    Behavioral Biology 11:131–154.

    https://doi.org/10.1016/s0091-6773(74)90289-2

    • PubMed
    • Google Scholar
47. Book

    1. Sapolsky RM

    (1993)

    The physiology of dominance in stable versus unstable social hierarchies

    In: Sapolsky RM, editors. Primate Social Conflict. State University of New York Press. pp. 171–204.

    • Google Scholar
48. 1. Sapolsky RM

    (2005) The influence of social hierarchy on primate health

    Science 308:648–652.

    https://doi.org/10.1126/science.1106477

    • PubMed
    • Google Scholar
49. 1. Savage SV
    2. Dippong J
    3. Melamed D

    (2020) Status and competitive choice

    Social Science Research 88–89:102430.

    https://doi.org/10.1016/j.ssresearch.2020.102430

    • PubMed
    • Google Scholar
50. 1. Sicotte P

    (2002) The function of male aggressive displays towards females in mountain gorillas

    Primates; Journal of Primatology 43:277–289.

    https://doi.org/10.1007/BF02629603

    • PubMed
    • Google Scholar
51. 1. Slotow R

    (1996) Aggression in white-crowned sparrows: effects of distance from cover and group size

    The Condor 98:245–252.

    https://doi.org/10.2307/1369142

    • Google Scholar
52. 1. Smit N

    (2024) Hierarchies inferred from different agonistic behaviours are not always comparable

    The Journal of Animal Ecology 93:1947–1959.

    https://doi.org/10.1111/1365-2656.14203

    • PubMed
    • Google Scholar
53. 1. Smit N
    2. Robbins MM

    (2024) Female gorillas compete for food and males

    Evolution and Human Behavior 45:106611.

    https://doi.org/10.1016/j.evolhumbehav.2024.106611

    • Google Scholar
54. Software

    1. Smit N

    (2025) Risk-taking incentives predict aggression heuristics in female gorillas, version swh:1:rev:f50b87c7972699535528f2b175df6ebfe53638f2

    Software Heritage.

    https://archive.softwareheritage.org/swh:1:dir:2f65f6b5889344f5502a93bc28b334c7872e4400;origin=https://gitlab.com/nksmt/GorillaHeuristics;visit=swh:1:snp:ef6845382afdc8f19d885176f6535ed1aeb588a8;anchor=swh:1:rev:f50b87c7972699535528f2b175df6ebfe53638f2
55. 1. Smit N
    2. Robbins MM

    (2025) Female gorillas form highly stable dominance relationships

    Biology Letters 21:20240556.

    https://doi.org/10.1098/rsbl.2024.0556

    • PubMed
    • Google Scholar
56. 1. Strauss ED
    2. Shizuka D

    (2022) The dynamics of dominance: open questions, challenges and solutions

    Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 377:20200445.

    https://doi.org/10.1098/rstb.2020.0445

    • PubMed
    • Google Scholar
57. 1. Verdolin JL

    (2006) Meta-analysis of foraging and predation risk trade-offs in terrestrial systems

    Behavioral Ecology and Sociobiology 60:457–464.

    https://doi.org/10.1007/s00265-006-0172-6

    • PubMed
    • Google Scholar
58. 1. Vogel ER
    2. Munch SB
    3. Janson CH

    (2007) Understanding escalated aggression over food resources in white-faced capuchin monkeys

    Animal Behaviour 74:71–80.

    https://doi.org/10.1016/j.anbehav.2007.02.003

    • Google Scholar
59. 1. Vogel ER
    2. Janson CH

    (2011) Quantifying primate food distribution and abundance for socioecological studies: an objective consumer-centered method

    International Journal of Primatology 32:737–754.

    https://doi.org/10.1007/s10764-011-9498-7

    • Google Scholar
60. 1. Vullioud C
    2. Davidian E
    3. Wachter B
    4. Rousset F
    5. Courtiol A
    6. Höner OP

    (2019) Social support drives female dominance in the spotted hyaena

    Nature Ecology & Evolution 3:71–76.

    https://doi.org/10.1038/s41559-018-0718-9

    • PubMed
    • Google Scholar
61. Thesis

    1. Watts DP

    (1983)

    Foraging strategy and socioecology of Mountain gorillas (Pan Gorilla beringei)

    The University of Chicago.

    • Google Scholar
62. 1. Watts DP

    (1994) Agonistic relationships between female mountain gorillas (Gorilla beringei)

    Behavioral Ecology and Sociobiology 34.5:347–358.

    https://doi.org/10.1007/BF00197005

    • Google Scholar
63. 1. Watts DP

    (1997) Agonistic interventions in wild mountain Gorilla Groups

    Behaviour 134:23–57.

    https://doi.org/10.1163/156853997X00269

    • Google Scholar
64. 1. Wilson M
    2. Daly M

    (1985) Competitiveness, risk taking, and violence: the young male syndrome

    Ethology and Sociobiology 6:59–73.

    https://doi.org/10.1016/0162-3095(85)90041-X

    • Google Scholar
65. 1. Wohl MJA
    2. Branscombe NR
    3. Lister JJ

    (2014) When the going gets tough: economic threat increases financial risk taking in games of chance

    Social Psychological and Personality Science 5.2:211–217.

    https://doi.org/10.1177/1948550613490964

    • Google Scholar
66. 1. Wright E
    2. Robbins MM

    (2014) Proximate mechanisms of contest competition among female Bwindi mountain gorillas (Gorilla beringei beringei)

    Behavioral Ecology and Sociobiology 68:1785–1797.

    https://doi.org/10.1007/s00265-014-1788-6

    • Google Scholar
67. 1. Wright E
    2. Galbany J
    3. McFarlin SC
    4. Ndayishimiye E
    5. Stoinski TS
    6. Robbins MM

    (2019) Male body size, dominance rank and strategic use of aggression in a group-living mammal

    Animal Behaviour 151:87–102.

    https://doi.org/10.1016/j.anbehav.2019.03.011

    • Google Scholar
68. 1. Wright E
    2. Galbany J
    3. McFarlin SC
    4. Ndayishimiye E
    5. Stoinski TS
    6. Robbins MM

    (2020) Dominance rank but not body size influences female reproductive success in mountain gorillas

    PLOS ONE 15:e0233235.

    https://doi.org/10.1371/journal.pone.0233235

    • PubMed
    • Google Scholar
69. 1. Zuur AF
    2. Ieno EN
    3. Elphick CS

    (2010) A protocol for data exploration to avoid common statistical problems

    Methods in Ecology and Evolution 1:3–14.

    https://doi.org/10.1111/j.2041-210X.2009.00001.x

    • Google Scholar

Author details

1. Nikolaos Smit

   1. Department of Biology, University of Turku, Turku, Finland
   2. Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   For correspondence

   nismit@utu.fi

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-0440-1998

2. Martha M Robbins

   Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

   Contribution

   Data curation, Funding acquisition, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6037-7542

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