title: Manipulated into giving: when parasitism drives apparent or incidental altruism.
abstract: Altruistic acts involve the actor donating fitness to beneficiaries at net cost to itself. In contrast, parasitic acts involve the actor extracting benefit from others at net cost to the donors. Both behaviours may have the same direct net-cost transferral of fitness from donor to beneficiary; the key difference between parasitism and altruism is thus who drives the interaction. Identifying the evolutionary driver is not always straightforward in practice, yet it is crucial in determining the conditions necessary to sustain such fitness exchange. Here, we put classical ecological competition into a novel game-theoretic framework in order to distinguish altruism from parasitism. The distinction depends on the type of interaction that beneficiaries have among themselves. When this is not costly, net-cost transferrals of fitness from the donor are strongly altruistic, and sustained only by indirect benefits to the donor from assortative mixing. When the interaction among beneficiaries is costly, however, net-cost transferrals of fitness from the donor are sustainable without assortative mixing. The donor is then forced into apparent or incidental altruism driven by parasitism from the beneficiary. We consider various scenarios in which direct and indirect fitness consequences of strong altruism may have different evolutionary drivers.
authors.affiliation: Centre for Biological Sciences, Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, UK. cpd@soton.ac.uk
authors.forename: C Patrick
authors.initials: CP
authors.lastname: Doncaster
authors.forename: Adam
authors.initials: A
authors.lastname: Jackson
authors.forename: Richard A
authors.initials: RA
authors.lastname: Watson
mesh_terms: D000533:Altruism; D000818:Animals; D005075:Biological Evolution; D003163:Competitive Behavior; D003299:Cooperative Behavior; D005716:Game Theory; D056084:Genetic Fitness; D006790:Host-Parasite Interactions; D008954:Models, Biological