Image scoring, often called eavesdropping, is the occurrence where by information pertaining to interacting individuals is derived by a separate bystander (Bshary and Grutter, 2006). The information is utilized by the bystander to optimize its behaviour in future interactions with either of the presently interacting individuals (Bshary and Grutter, 2006). Image scoring is commonly observed during agonistic interactions. This is because image sourcing allows bystanders to optimize fighting strategies in potential future conflict with the presently interacting individuals (Johnstone, 2001). Meanwhile, image scoring, despite its ambiguity, has a possible role in the evolution of cooperation (Nowak and Sigmund, 1998).
Cooperation crucial for the Evolution of Social Animals
Cooperation is defined as the process by which numerous individuals mutually interact to increase fitness and reproductive success. (Gardner, et al. 2016).Often, the actor may forgo immediate fitness benefits for the reproductive success of the recipient. For this reason, the evolution of cooperation may seem counterintuitive. Nonetheless, the phenomena can be justified through both, indirect and direct, reciprocal altruism. (Gardner, et al. 2016). Through direct reciprocity, an actor will cooperate with the recipient in hope that the latter with reciprocate the altruistic act. This is possible when there are repeated interactions between individuals. However, it is not always possible for repeated interactions to occur (Gardner, et al. 2016).
On the contrary, indirect reciprocate provides a mechanism for cooperation to evolve without repetitive cooperation between the same individuals. Through image scoring, donors often direct altruist acts towards recipients with a history of altruism towards other individuals. Despite its short-term costs, cooperation is beneficial for the donor because it enhances its reputation, which hence increases the chances of receiving altruism in the future. This allows the donor to overcome the costs of the initial altruistic act (Nowak and Sigmund, 1998). Furthermore, an individual who regularly does not provide altruist acts, will have a low image score, hence receive a lower degree of altruism (Nowak and Sigmund, 1998).
Eavsedropping allowed for the Evolution of Reciprocal Altruism
Indirect reciprocity based on image scoring is ubiquitous amongst humans. For example, a study, which utilized an image scoring method, found that people, who had provided more generous donations in earlier interactions, received larger and more frequent donations from other individuals (Wedekind and Milinski, 2000).
Another example of such phenomena is that of the cleaner fish (Labroides dimidiatus) and its client fish. Mutualistic interactions occur when the cleaner fish removes ectoparasites from its client fish. However, the cleaner fish has an incentive to cheat, as they prefer the consumption of the client mucus over ectoparasites (Bshary and Grutter, 2006). Client fish utilize image scoring to effectively prevent cleaners from cheating.
Specifically, clients were more likely to invite cleaner fish for inspection when the former observed mutualistic interactions between the latter and its previous client (Bshary and Grutter, 2006). Furthermore, client fish were less welcoming without knowledge of the cleaner fish’s previous interactions. Meanwhile, cleaner fish were observed to more cooperative in the presence of bystander clients (Bshary and Grutter, 2006).
Individual Variation in Image Scoring
This an example of the audience effect, where the presence or absence of a bystander forces interacting individuals to adjust behaviour accordingly (Bshary and Grutter, 2006). This is because the degree of cooperation in current interactions influences whether a bystander will cooperate with the donor in the future (Sugden, 1986). Unsurprisingly, attempts of an individual to alter its image score requires an understanding of how other members responds to a specific image score (Sugden, 1986).
As such, a donor’s image score can only be perceived by the recipient and surrounding bystanders. For this reason, the perception of an individual’s image score will vary significantly across the population (Nowak and Sigmund, 1998). Additionally, the ability of an individual to estimate the image score of a potential partner also influences the possibility of cooperation (Bshary and Grutter, 2006). The individual variance in the degree of cooperation is thought to promote image scoring. Cooperation will utilize image scoring when bystanders benefit from the acquisition of information and the donors benefit from access to the bystander (Bshary and Grutter, 2006).
“And” and “Or” Strategy
Numerous models have been stimulated to explain the process of reciprocity through image strategy. One prominent example is the “And” and “Or” strategies. Here cooperation occurs when the image score of recipients is greater than a certain value while the image score of the donor is less than a certain value (Nowak and Sigmund, 1998). In such scenarios, the recipient does not benefit from trying to increase its already high score (Nowak and Sigmund, 1998).
Meanwhile, in the “Or” Strategy, cooperation occurs when either of the two scenarios are met. In such strategies, it is highly advantageous for the donor to increase its image scoring, regardless of how low the score of the recipient is (Nowak and Sigmund, 1998). The same simulations found that cooperation did not evolve when donors only considered their own image and not that of the recipient (Nowak and Sigmund, 1998).
Can this strategy counter cheaters?
As such, there are numerous fallacies in the idea the indirect reciprocity is driven by image scoring. Given that the acquisition of future altruistic benefits is dependent on the individual’s own image score (Brandt and Sigmund, 2004), it may be counterintuitive to base decisions on the image scores of the patterner (Sugden, 1986). This exposes the system to more selfish exploitation than in direct reciprocation. Furthermore, in during direct reciprocation, repeated interactions can foster retaliatory strategies in response to cheating.
Contrastingly, in indirect reciprocity, individuals are unlikely to meet more than once, reducing the opportunities to punish cheaters. (Brandt and Sigmund, 2004). Additionally, punishing defaulters in an image scoring system is costly. By refusing to aid individuals with low image scores, the discriminator’s own image score is hindered. Image scoring does not provide a mechanism to punish defaulters (Sugden, 1986).
Good Standing Strategy
An alternate strategy has been suggested to counter the issue of defaulters. This is the good standing strategy, where all individuals are initially in good standing. Here an individual loses good standing by failing to provide altruistic acts to a recipient with good standing (Sugden, 1986). However, the individual does not lose good standing for not being altruistic towards individuals lacking good standing (Sugden, 1986). Meanwhile, Individuals can regain a good standing by providing altruistic acts towards other individuals (Sugden, 1986).
Not only does this provide a mechanism to counter defaulters, it also highlights the relevance of the image score of potential recipients in cooperation. As such, numerous stimulations have found that the standing strategy is superior to scoring (Brandt and Sigmund, 2004) and is potentially an evolutionary stable strategy (Leimar and Hammerstein, 2001).
Are animals smart enough for the Good Standing Strategy?
However, there are two primary issues with this strategy. Firstly, elaborate cognitive abilities are required to account for “justifiable” defections. As most cooperative organisms lack such elaborate neurological adaptations, the evolution of this strategy may not be feasible. (Brandt and Sigmund, 2004). Additionally, despite its theoretical soundness, practical evidence supports the evolution of image scoring over the standing strategy.
For example, a study found that the scoring mechanism was more prevalent in real life human interactions than its standing counterpart (Milinski et al., 2001). Furthermore, the study found that justifiable defection is compensated for by increased generosity in subsequent altruistic interactions. This highlights the existence of a possible mechanism to punish defaulters without hampering the individual’s own image score (Milinski et al., 2001).
Conclusion
To conclude, more research is certainly required to truly understand the mechanisms of indirect reciprocity. Nonetheless, despite its ambiguity, the role of image scoring in the evolution of cooperation cannot be ignored. It provides a mechanism for reciprocity to occur indirectly, when direct reciprocity is limited by the lack of repeated interactions. Understanding how image scoring selects against defaulters will provide more clarity on the evolution of cooperation.
Help us Help Them! Think Wildlife Foundation is a non profit organization with various conservation initiatives. Our most prominent campaign is our Caring for Pari intiative. Pari is a rehabilitated elephant at the Wildlife SoS Hospital. 25% of the profits from our store are donated to the elephant hospital for Pari. Other than buying our wonderful merchandise, you could donate directly to our Caring For Pari fundraiser.
Reference List
Brandt, H. and Sigmund, K., 2004. The logic of reprobation: assessment and action rules for indirect reciprocation. Journal of Theoretical Biology, [online] 231(4), pp.475-486. Available at: <https://www.sciencedirect.com/science/article/pii/S0022519304002784> [Accessed 28 January 2022].
Bshary, R. and Grutter, A., 2006. Image scoring and cooperation in a cleaner fish mutualism. Nature, [online] 441(7096), pp.975-978. Available at: <https://www.nature.com/articles/nature04755> [Accessed 28 January 2022].
Gardner, A., Griffin, A. and West, S., 2016. Theory of Cooperation. eLS, [online] pp.1-8. Available at: <https://www.researchgate.net/publication/228018300_Theory_of_Cooperation> [Accessed 28 January 2022].
Johnstone, R., 2001. Eavesdropping and animal conflict. Proceedings of the National Academy of Sciences, [online] 98(16), pp.9177-9180. Available at: <https://www.pnas.org/content/98/16/9177> [Accessed 28 January 2022].
Leimar, O. and Hammerstein, P., 2001. Evolution of cooperation through indirect reciprocity. Proceedings of the Royal Society of London. Series B: Biological Sciences, [online] 268(1468), pp.745-753. Available at: <https://royalsocietypublishing.org/doi/abs/10.1098/rspb.2000.1573> [Accessed 28 January 2022].
Milinski, M., Semmann, D., Bakker, T. and Krambeck, H., 2001. Cooperation through indirect reciprocity: image scoring or standing strategy?. Proceedings of the Royal Society of London. Series B: Biological Sciences, [online] 268(1484), pp.2495-2501. Available at: <https://pubmed.ncbi.nlm.nih.gov/11747570/#:~:text=Theorists%20have%20only%20recently%20shown,a%20mechanism%20called%20image%20scoring.&text=The%20new%20theoretical%20study%20confirmed,and%20easily%20beats%20image%20scoring.> [Accessed 28 January 2022].
Nowak, M. and Sigmund, K., 1998. Evolution of indirect reciprocity by image scoring. Nature, [online] 393(6685), pp.573-577. Available at: <https://www.researchgate.net/publication/13650819_Evolution_of_Indirect_Reciprocity_by_Image_Scoring> [Accessed 28 January 2022].
Sugden, R., 1986. The Economics of Rights, Co-operation and Welfare. 1st ed. London: Palgrave Macmillan.
Wedekind, C. and Milinski, M., 2000. Cooperation Through Image Scoring in Humans. Science, [online] 288(5467), pp.850-852. Available at: <https://www.science.org/doi/abs/10.1126/science.288.5467.850> [Accessed 28 January 2022].