Cheaters must prosper: reconciling theoretical and empirical perspectives on cheating in mutualism

Abstract

Cheating is a focal concept in the study of mutualism, with the majority of researchers considering cheating to be both prevalent and highly damaging. However, current definitions of cheating do not reliably capture the evolutionary threat that has been a central motivation for the study of cheating. We describe the development of the cheating concept and distill a relative-fitness-based definition of cheating that encapsulates the evolutionary threat posed by cheating, i.e. that cheaters will spread and erode the benefits of mutualism. We then describe experiments required to conclude that cheating is occurring and to quantify fitness conflict more generally. Next, we discuss how our definition and methods can generate comparability and integration of theory and experiments, which are currently divided by their respective prioritisations of fitness consequences and traits. To evaluate the current empirical evidence for cheating, we review the literature on several of the best-studied mutualisms. We find that although there are numerous observations of low-quality partners, there is currently very little support from fitness data that any of these meet our criteria to be considered cheaters. Finally, we highlight future directions for research on conflict in mutualisms, including novel research avenues opened by a relative-fitness-based definition of cheating.

Using niche breadth theory to explain generalization in mutualisms

“…There is a widespread expectation that mutualisms are undermined by "cheating," or taking benefits from a mutualist without (fully) reciprocating (Ghoul et al 2014, Jones et al 2015. The anticipated, though seldom demonstrated (Frederickson 2017), cheating in mutualisms has led to the prediction that selection should favor ever more specialized interactions (Frank 1996, Thompson 2005, Thrall et al 2007, Poisot et al 2011, as mutualists limit their associations to or preferentially reward only highly cooperative partners (Bull andRice 1991, reviewed in Frederickson 2013).…”

“…A focus on cheaters and phylogenetically unrelated exploiters is common in many well-known mutualisms, including ant-fungus, cleaner-client-fish, legume-rhizobium, plantarbuscular-mycorrhizal-fungi, and squid-Vibrio interactions (Ghoul et al 2014, Jones et al 2015. To explain why mutualisms are evolutionarily stable despite the potential for cheating, research has emphasized mechanisms that couple partner (Heleno et al 2013), and (C) plant-pollinator (Olesen et al 2002) systems.…”

“…Reprinted from Bl€ uthgen et al (2007) with permission from Elsevier. However, recent studies have questioned whether cheating is as widespread in mutualisms as is often assumed (Friesen 2012, Jones et al 2015, Frederickson 2017, and thus whether mutualists are really under selection to specialize on high-quality partners to avoid associating with cheaters (Frederickson 2013). Asterisks show significant differences between network types.…”

Bacterial Quorum Sensing Stabilizes Cooperation by Optimizing Growth Strategies

“…In the context of PG, individuals that contribute by producing the good are defined as cooperators, while nonproducers are defined as defectors. Importantly, defectors are not always inherently cheaters but are capable of cheating if they reap fitness advantages by exploiting social behaviors (8)(9)(10). Conditional participation through phenotypic plasticity driven by communication could provide a potential solution to this dilemma (11).…”

Information in the Biosphere: Biological and Digital Worlds

“…This scenario raises the question of how such an organic-digital fusion might become a symbiosis that co-evolves through natural and artificial selection. In all symbioses, there is potential for exploitation and cheating [75], and this possibility has to be examined for the biological-technological fusion. Science fiction has frequently examined conflicts that either end in the extinction or parasitism of the human species, and intellectuals from Stephen Hawking and Noam Chomsky to Bill Gates and Elon Musk have all warned about the existential threat posed by Artificial Intelligence [76,77].…”