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Cheaters Must Prosper: Reconciling Theoretical and Empirical Perspectives on Cheating in Mutualism

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Cheaters Must Prosper: Reconciling Theoretical and Empirical Perspectives on Cheating in Mutualism Ecology Letters, (2015) 18: 1270–1284 doi: 10.1111/ele.12507 REVIEW AND SYNTHESIS Cheaters must prosper: reconciling theoretical and empirical perspectives on cheating in mutualism Abstract Emily I. Jones,1,2,3† Cheating is a focal concept in the study of mutualism, with the majority of researchers considering Michelle E. Afkhami,4 Erol Akßcay,5 cheating to be both prevalent and highly damaging. However, current definitions of cheating do Judith L. Bronstein,6 Redouan not reliably capture the evolutionary threat that has been a central motivation for the study of Bshary,7 Megan E. Frederickson,4 cheating. We describe the development of the cheating concept and distill a relative-fitness-based Katy D. Heath,8 Jason D. definition of cheating that encapsulates the evolutionary threat posed by cheating, i.e. that chea- Hoeksema,9 Joshua H. Ness,10 ters will spread and erode the benefits of mutualism. We then describe experiments required to 11 conclude that cheating is occurring and to quantify fitness conflict more generally. Next, we dis- M. Sabrina Pankey, Stephanie S. ‡ cuss how our definition and methods can generate comparability and integration of theory and Porter,12 Joel L. Sachs,12 Klara experiments, which are currently divided by their respective prioritisations of fitness consequences Scharnagl13 and Maren L. and traits. To evaluate the current empirical evidence for cheating, we review the literature on sev- Friesen13*,† eral 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 con- flict in mutualisms, including novel research avenues opened by a relative-fitness-based definition of cheating. Keywords Ant–plant, cleaner fish–client, cooperation, fig–fig wasp, fitness conflict, legume–rhizobia, nectar larceny, partner quality, plant–mycorrhizae, yucca–yucca moth. Ecology Letters (2015) 18: 1270–1284 (Ghoul et al. 2014; Box 1, Fig. 1). There has been disagreement INTRODUCTION over what needs to be measured in order to determine whether Mutualisms are defined by the reciprocal net benefit that cheating is happening, as well as which partner is the focus of heterospecific partners receive through the exchange of such measurements. The literature also contains varying defini- resources and services. Although the outcome of mutualism is tions regarding how distinct cheaters are from other partners mutually beneficial, the underlying actions are self-interested – and whether phylogenetic restrictions should be imposed on individuals are expected to maximise their own net benefits who can be considered a cheater (Table 1). These differing defi- without regard to the consequences for their partners. Thus, nitions have led to inconsistency over how cheating is identified unless the interests of partners are perfectly aligned, there and modelled, hampering our ability to determine how common should be an incentive to ‘cheat’ (Trivers 1971; Soberon & cheating is and to predict how mutualisms will evolve. Martinez del Rio 1985). Adoption of a fitness-based definition of cheating has great However, while there is widespread agreement that cheating promise to promote comparability across studies and systems. is a fundamental concept in the study of mutualism, there has Yet, the definition that has been proposed – that cheating been very little consensus on the definition of cheating itself increases individual fitness and reduces partner fitness (Ghoul 1Department of BioSciences, Rice University, Houston, TX 77005, USA 8Department of Biology, University of Illinois, Urbana, IL 61801, USA 2Wissenschaftskolleg zu Berlin, Institute for Advanced Study, 14193 Berlin, 9Department of Biology, University of Mississippi, University, MS 38677, USA Germany 10Department of Biology, Skidmore College, Saratoga Springs, NY 12866, USA 3Department of Entomology, Washington State University, Pullman, WA 11Department of Molecular, Cell and Biomedical Sciences, University of New 99164, USA Hampshire, Durham, NH 08624, USA 4Department of Ecology & Evolutionary Biology, University of Toronto, 12Department of Biology, University of California, Riverside, CA 92521, USA Toronto, Ontario M5S 3G5, Canada 13Department of Plant Biology, Michigan State University, East Lansing, MI 5Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, 48824, USA USA *Correspondence: E-mail: [email protected] † 6Department of Ecology & Evolutionary Biology, University of Arizona, These authors contributed equally to this work. ‡ Tucson, AZ 85721, USA School of Biological Sciences, Washington State University, Vancouver WA 7Institute of Biology, University of Neuchatel,^ CH-2000 Neuchatel,^ Switzerland 98686 USA . © 2015 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. Review and Synthesis Cheating in mutualism 1271 Table 1 Variation in the concept of cheating. Major aspects of the defini- Box 1 Current opinions about cheating tion of cheating and the alternate perspectives that appear in the empirical and theoretical literatures on cheating in mutualism (for a review of alter- As studies of cheating in mutualism have accumulated, so native definitions see Ghoul et al. 2014, table A1). have definitions of cheating (Table 1, Fig. 2). To evaluate current perspectives in the community, we conducted an Aspect of the cheating definition Alternate perspectives anonymous survey of professional ecologists and evolution- What needs to be measured • Mutualist rewards ary biologists (Supporting Information S1). Of the respon- • Specific antagonistic dents who self-identified as working on mutualism, 30% behaviours also identified that they work on cheating. The average • Net fitness effects response to ‘How common is cheating in mutualisms?’ was Who needs to be measured • The putative cheater alone 2.476, with answers ranging from 1 to 4 on a scale of 1 • Multiple individuals for (nonexistent) to 5 (ubiquitous). The average response to comparison ‘How much of a threat does cheating pose for the persis- • Both the putative cheater tence of mutualisms?’ was 2.825, with answers ranging and its partner from 1 to 5 on a scale of 1 (no threat) to 5 (extreme • Multiple partner threat). Individuals rated the threat of cheating to be combinations higher than its prevalence (paired t-test, P = 0.0351). How different cheaters • Discretely different are from non-cheaters Respondents were asked to evaluate seven potential defini- • Quantitatively different tions of cheating from the literature on a scale of 1 (com- Phylogenetic restrictions • None pletely disagree) to 5 (completely agree). Of the potential • Only members of definitions, only ‘a cheater provides no reward’ was dis- (previously) mutualistic lineages can be considered agreed with on average. The potential definition that cheaters received the most agreement was ‘a cheater has a higher reward taken: reward given ratio than other prospective The perspectives that correspond with our definition (a cheater must have partners’. The level of agreement for each of the seven higher than average relative fitness and cause its partner to have lower than average relative fitness) are given in bold. potential definitions is shown in Fig. 1. BD F A BRIEF HISTORY OF THE CHEATING CONCEPT A C E G Individuals and species that are associated with mutualisms –0.5 –0.25 0 0.25 0.5 but do not confer benefits have been noted since biologists Disagree Neutral Agree first began studying mutualisms. For example, in 1878 Kerner wrote an entire book entitled ‘Flowers and their Unbidden Figure 1 Survey responses on the definition of cheating. Respondents were Guests’, a product of his years of studying pollination biology asked to evaluate seven potential definitions of cheating from the under the influence of Charles Darwin. Many early examples literature on a scale of 1 (completely disagree) to 5 (completely agree); we were summarised in ‘Parasitism and Symbiosis’, published by re-scaled these responses to calculate the overall extent of agreement ranging from À1to+1. Ordered from least to most agreement, the Caullery in 1952. Through at least the mid-1980s, the ecologi- definitions were (A) a cheater provides no reward, (B) a cheater takes cal literature used a wide diversity of terms to describe these more reward than other potential partners, (C) a cheater takes a benefit phenomena. For instance, ants that occupied acacias without but does not provide a reward, (D) a cheater takes more than its fair defending their hosts were termed ‘parasites’ (Janzen 1975), share, (E) a cheater provides less than its fair share, (F) a cheater the phenomenon in which orchids lured pollinators to non-re- provides less reward than other potential partners and (G) a cheater has a warding flowers was called ‘deception’ (Vogel 1978), and floral higher reward taken: reward given ratio than other prospective partners. visitors that collected nectar without pollinating were defined et al. 2014) – implies a comparison without specifying what as ‘robbers’ or ‘thieves’ depending on their mode of entry to needs to be compared. Here, we provide a brief history of the the flower (Inouye 1980). By the time the first
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