Figure 3.

How kin and similarity targeting can evolve persistently high altruism levels. A thought experiment illustration showing how (a) kin-based altruism naturally thwarts kin-cheaters (kc) and (b) enables enduring increases in altruism levels. (a(i)) Consider a group of related organisms that are altruistic to each other (blue and light blue). One organism may mutate to be less altruistic, becoming a kin-cheater (red), but since only its closest relatives (light blue) will consider it kin, only they will be altruistic towards it. (a(ii)) The kin-cheater will tend to supplant its kin because it receives more donations from them than it gives. (a(iii)) Once the kin-cheater has replaced those that considered it kin, the kin-cheater is left receiving donations only from other kin-cheaters. This group (red) will have a lower altruism level than their distant kin (blue) and will come to be replaced by them. (b(i)) Now consider an organism (orange) that mutates to have a higher level of altruism (ha) than its ancestors (blue). Initially, it will be selected against because it gives more donations to those that it considers kin (pink) than it receives from them. (b(ii)) If the less-altruistic kin of the higher level altruist are killed off by drift, then the higher level altruist and its offspring (orange) will have a competitive advantage over their distant ancestors (blue). (b(iii)) While chance is required to start the process, once it has occurred, there will be selection for the higher level of altruism. There are additional factors that complicate all of these fitness comparisons, but for clarity, we have sketched these scenarios only in broad strokes. kc, kin cheater; kkc, kin of kin cheater; dkkc, distant kin of kin cheater; ha, higher-level altruist; kha, kin of higher-level altruist; dkhla, distant kin of higher-level altruist.