Kin recognition: conceptual issues, mechanisms and evolutionary theory 3. BOX 3.1. Kin biases. There are many ways that organisms treat kin differentially from ...
Chapter 3
Kin recognition: an overview of conceptual issues, mechanisms and evolutionary theory DUSTIN J. PENN AND JOACHIM G. FROMMEN
‘All good kumrads you can tell by their altruistic smell.’ (E.E. Cummings)
ABSTRACT Kin recognition (KR) is the ability to identify or distinguish kin from nonkin, and it is thought to be an important driving force in the evolution of social and sexual behaviour. Here, we provide an introduction to KR, including an overview of the main debates, the underlying mechanisms and evolutionary analyses. First, we examine the many evolving definitions for KR, as these have caused some confusion and debate. We explain why retaining both broad and narrow definitions can be instructive for thinking about the problem. Second, we provide examples of the different types of KR from empirical studies, ranging from the use of spatial cues to for selfinspection and green-beard genes. We also suggest a classification scheme of the different mechanisms based on whether they are considered to be KR in the broad or in the narrow sense. Third, we consider the key components necessary for most or all KR mechanisms, and explain why the central problem for any recognition mechanism is to balance the risk of acceptance versus rejection errors. Fourth, we summarise theoretical analyses addressing the evolution of nepotism through kin recognition, and the maintenance of genetic polymorphisms controlling KR. Fifth, we examine evolutionary analyses of apparent KR failures, errors, and mistakes. Finally, we suggest some of the main problems that need to be addressed in future KR research.
3.1 Introduction Individuals in many social species behave altruistically, and in extreme cases may even sacrifice their own reproduction for the group, as with
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eusocial insects. To explain the remarkable altruism found in some species, W.D. Hamilton (1964) suggested his theory of inclusive fitness which clarifies the conditions under which altruism is expected to evolve: ‘The social behaviour of a species evolves in such a way that in each distinct behaviour-evoking situation the individual will seem to value his neighbors’ fitness against his own according to the coefficients of relationship appropriate to that situation’ (p. 19). This principle, known as Hamilton’s rule shows that genetic relatedness is one of the keys to understanding altruism. This insight provided an important new theoretical approach to studying cooperation and other social behaviours (genes’-eye view of evolution; Dawkins 1976), and inspired the development of sociobiology (Wilson 1975). Inclusive fitness theory is arguably one of the most important advance in our understanding of natural selection since the Modern Evolutionary Synthesis (Griffin and West 2002). Additionally, Hamilton (1964) suggested that when selection favours helping kin, mechanisms may evolve that allow individuals to discriminate kin from non-kin. To understand how, Hamilton (1964:25) proposed a thought experiment in which a gene evolves that enables ‘the perception of the presence of like genes in other individuals’ and it also helps other individuals carrying the genes, and in this way, it helps copies of itself. He acknowledged that such a ‘super gene’, or what is now known as a green-beard gene (Dawkins 1976), is highly improbable, but nevertheless it is instructive for obtaining insights into how altruism evolves. Hamilton’s ideas sparked much interest in testing whether and how animals recognise kin (see Holmes 2004) and the role that kin recognition plays in cooperation, inbreeding avoidance, and other kin biases (BOX 3.1). Before Hamilton, kin recognition research had previously focused on parent-offspring recognition, but inclusive fitness theory broadened interest in social interactions among collateral kin (e.g., siblings, nieces, nephews, aunts and uncles). Subsequent work has shown that organisms in a wide variety of taxa – from single-celled organisms to humans – are able to distinguish kin from non-kin (e.g. Fletcher and Michener 1987, Waldman et al. 1988, Hepper 1991a). Kin recognition may also influence the behaviour of gametes, the haploid phase of the life cycle (i.e., spermegg and sperm-sperm interactions; Moore and Moore 2002), and fetalplacental interactions (Haig 1996, Summers and Crespi 2005). The trouble is that kin recognition research has been plagued with terminological, conceptual, and methodological issues, including debates over the meaning of the term kin recognition (Waldman et al. 1988, Gamboa et al. 1991). These debates came to a head when Grafen (1990:45) evaluated the field, and made several controversial objections. He argued that there is a paucity of evidence for ‘true kin recognition’,
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BOX 3.1 Kin biases There are many ways that organisms treat kin differentially from non-kin. Such kin biases can be developmental, physiological, or behavioural responses and may include either helping or avoiding kin. Many species display parental care, which can enhance offspring fitness under certain conditions (see Trillmich, this volume). Furthermore, conditional helping for kin is common, and such nepotism results in kin selection. The most extreme case of altruistic helping is the evolution of sterile workers in eusocial insects (Hughes et al. 2008). Kin biases also include kin aggregations and discriminating admittance to social groups. In addition to helping kin, some species avoid competition with kin (West et al. 2002), or show conditional aggression toward non-kin (cannibalism and infanticide) (Pfennig et al. 1993, Manica 2002). Many species show inbreeding avoidance, which most likely functions to avoid the deleterious consequences of inbreeding (inbreeding depression) (Crnokrak and Roff 1999). However, more studies are needed to determine whether natural selection favours intermediate levels of outbreeding due to harmful consequences of extreme outbreeding (optimal outbreeding). Kin biases do not require KR. For example, sex-biased dispersal may function to avoid inbreeding, and it does not require an ability to distinguish kin versus non-kin. It has been suggested that kin biases that do not involve KR should be called ancillary kin bias (Halpin 1991, Tang-Martinez 2001) or non-discriminatory kin bias (Barnard et al. 1991). However, the term ancillary implies a bias of secondary importance, which is not the case, and non-discriminatory kin bias may be confusing since non-discriminatory implies no bias (see BOX 3.2). We suggest that such biases are instead referred to as kin biases without kin recognition.
which he defined as systems ‘whose use and function is to assess the kinship of conspecifics’. Grafen concluded that there was only one convincing example of true kin recognition (i.e., Grosberg and Quinn 1986) because previous studies failed to rule out possible artifacts or incidental biases arising from individual, group, and species recognition abilities. Still, Grafen described a verbal model for how a true kin recognition system might evolve and maintain itself. His paper triggered a flurry of criticism (Blaustein et al. 1991, Byers and Bekoff 1991, Stuart 1991) and replies (Barnard et al. 1991, Grafen 1991a,b,c). There is still no consensus over these issues, even after 20 years, though there have been many important advances. In this chapter, we provide an overview of kin recognition, and focus particularly on the following issues. First, we consider the various defini-
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tions for kin recognition (and kin discrimination), and the terminological debates that have created much controversy and confusion. Second, we examine the proximate mechanisms controlling kin recognition, and we suggest a novel classification of the mechanisms. Third, we consider how kin recognition evolves, and summarise results from theoretical analyses aimed to understand the origins and maintenance of nepotism through kin recognition. Fourth, we summarise evolutionary ideas proposed to explain apparent kin recognition failures. Finally, we suggest some of the central problems that need to be addressed in future research on kin recognition.
3.2 What is kin recognition? (Sorting out terminological confusion) Determining whether animals recognise their kin or not, depends on how one defines kin recognition. In the broad sense, kin recognition refers to the ability to identify, distinguish or classify kin from non-kin, regardless of the mechanism or evolutionary functions (descriptive definition). However, the problem is that there are several other definitions (Table 3.1), and these have caused much confusion and debates. For example, kin recognition is also defined as an ability to distinguish and the differential treatment of kin versus non-kin (Sherman and Holmes 1985, Waldman 1987). This operational definition is practical, but it muddles two potentially distinct processes, recognition – which is a proximate mechanism – versus kin-biased actions (Byers and Bekoff 1986). Recognition does not necessarily lead to differential responses toward kin, ‘just as recognising a fruit as an orange does not necessarily lead us to eating it’ (Barnard 1991), and kin biases are not necessarily due to kin recognition (e.g., animals may avoid mating with kin through sex-biased dispersal). The problem is that different researchers use different definitions, not only for kin recognition (KR), but also for kin discrimination (KD) and kin bias (KB), and some use different definitions, even in the same paper. Therefore, it is useful to examine how these terms cause confusion, and particularly the word discrimination (BOX 3.2). To try to reduce the ambiguity and confusion, some researchers propose using more strict or narrow definitions for KR (Table 3.1). However, the problem is that few seem to agree on a definition, and which definition a researcher uses depends upon whether they emphasise a particular mechanism, adaptive function, or evolutionary history. For example, some suggest restricting the term KR to particular mechanisms, such as direct recognition of conspecific phenotypes (Halpin 1991, Tang-Martinez 2001),
Kin recognition: conceptual issues, mechanisms and evolutionary theory Table 3.1. Evolving definitions for kin recognition (KR).
Definitions for kin recognition 1. Descriptive = ability to identify or distinguish kin versus non-kin, regardless of mechanisms or functions 2. Operational = ‘…differential treatment of conspecifics differing in genetic relatedness’ (Sherman and Holmes 1985; considered ‘KB’ here) 3. Mechanistic = ability to distinguish kin versus non-kin using genetic similarity or any cues that are correlated with kinship (Holmes 2004) = ‘the process by which individuals assess the genetic relatedness of conspecifics to themselves or others based on their perception of traits expressed by or associated with these individuals’ (Waldman et al. 1988) = ability to distinguish kin versus non-kin among conspecifics, including familiarity, but excluding spatial and temporal cues (Halpin 1991, TangMartinez 2001) = unobservable neural process of classifying individuals as kin (Byers and Bekoff 1986, Barnard 1991, Tang-Martinez 2001) = ability to distinguish and respond differentially to kin (Hepper 1991a; called ‘KD’ here) 4. Cognitive Mechanism = ‘the (externally, at least) unobservable neural process of classing individuals as kin’ (Barnard 1991, Barnard et al. 1991, Tang-Martinez 2001, Griffin and West 2002) 5. Adaptive Function = any mechanism that functions to recognise kin, regardless of the underlying mechanisms 6. Mechanism and Adaptive Function = ability to distinguish genetic similarity in conspecifics, which currently functions for this purpose (so-called true kin recognition; Grafen 1990) 7. Mechanism, Origins and Adaptive Function = ability to distinguish kin versus non-kin among conspecifics, originally evolved and currently functions for this purpose (Tang-Martinez 2001)
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Dustin J. Penn and Joachim G. Frommen BOX 3.2 Coming to terms with kin recognition, kin discrimination, and kin bias There are several definitions for kin recognition (KR), kin discrimination (KD), and kin biases (KB), which cause much confusion and debate. The word recognition refers to the ability to recall and identify someone from past experience or knowledge (from the Latin recognoscere, or to know again). Thus, Halpin (1986) suggested that strictly speaking this term should only be used for the ability to identify or distinguish familiar or previously known individuals, as the recognition of a stranger is ‘a logical impossibility’. Halpin points out that recognition is often used synonymously with discrimination (from the Latin discriminare or to divide), and suggests that discrimination is a preferable term for the ability to distinguish individual conspecifics. The problem, however, is that the word discrimination has three different definitions in English: (1) perceptive abilities to distinguish or make fine distinctions; (2) biased treatment of individuals based on their membership to a group; (3) or both. This ambiguity explains why KD is defined in different ways: (1) the ability to distinguish kin from non-kin (which we call KR); (2) differential treatment of kin versus non-kin (which we call KB, but it is also used as an operational definition for KR; Hepper 1991b); (3) both an ability to distinguish and differential treatment of kin versus non-kin. i.e., some use all three interchangeably (Holmes and Sherman 1983); (4) kin biases due to KR (Barnard 1991, Barnard et al. 1991). It is little wonder that KD causes so much confusion, especially since authors often slip back and forth among the common usages. The figure below summarises the relationships between the various definitions and terms, and how we define these terms in this paper (see the Glossary). (1) The ability to identify or distinguish kin versus non-kin = KR (but also called KD)
(4)
(2) differential treatment of kin versus non-kin = KB (but also called KR, KD)
(3) the ability to distinguish and the differential treatment of kin versus non-kin = KR (but also called KD) (4) differential treatment of kin versus non-kin due to the ability to distinguish them = KR (but also called KD)
neural and cognitive mechanisms (Barnard 1991, Tang-Martinez 2001), or the ability to detect genetic similarity (Grafen 1990). Narrowly defining KR with a particular mechanism is unnecessarily restrictive, however. Restricting KR to mechanisms that rely on individual phenotypic cues, for example, might rule out other interesting possibilities, such as KR based
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on extended phenotypes (e.g., acquired commensal microbes or the shape of a birds’ nest, etc.). Limiting KR to cognitive or neural mechanisms excludes bacteria, plants, unicellular social amoebae, and colonial marine invertebrates (unless cognition is broadly defined to include these taxa). Restricting KR to genetic similarity detection (Grafen 1990) could unnecessarily define the topic out of existence. Also, in many circumstances, environmentally determined cues may provide even better indicators of kinship than genetic ones (Gamboa et al. 1991). As Hamilton (1975) pointed out, ‘kinship should be considered just one way of getting this positive regression of genotype in the recipient, and that it is this positive regression that is vitally necessary for altruism’. If a species has parent, offspring, or sibling recognition, then it is difficult to understand why such behaviours should not be considered KR (after all, offspring are kin) just because they use mechanisms other then genetic similarity detection. Grafen (1990) also proposed that the term KR should be restricted to mechanisms that specifically function to recognise kin. Testing the consequences of KR is necessary to distinguish between adaptive versus incidental KR. However, some ethologists caution against labeling behaviours by their presumed functions or proximate causes, as these assumptions may later turn out to be incorrect (and a behaviour may have more than one function), and instead recommend using descriptive terms. TangMartinez (2001) goes further and proposes reserving the term KR only for mechanisms that originally evolved as well as currently function to recognise kin. This idea follows from the suggestion that the term adaptation should be reserved for traits that are shaped by natural selection for their current role, and the term exaptation for traits that originally evolved for something other (Gould and Vrba 1982). However, history-laden definitions for adaptation are impractical and misleading for several reasons (Reeve and Sherman 2001). For example, it is impossible to discern where an adaptation ends and an exaptation begins. How much of the current function of a trait must differ from its original role for it to be considered to be an exaptation? Adaptations generally evolve by modifying or coopting existing traits, and therefore, all traits are exaptations if we go back far enough in time. So, while more work is needed on the functions (Blaustein et al. 1991) and phylogenetic origins of KR (Crampton and Hurst 1994), there are practical reasons to advocate descriptive over mechanistic, functional or history-laden definitions. The main problem is that to demonstrate KR, some researchers insist that in addition to showing an ability to distinguish kin versus non-kin, one must also work out the mechanism (though there is no consensus about which mechanism, as we address further in the next section), its adaptive functions, and its evolutionary origins. This is hardly practical. A number
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of definitions for KR have been proposed, and there are advantages in retaining both broad and narrow definitions (as is the case for many terms in biology, such as heritability). We suggest that strict definitions of KR should be treated as hypotheses about the underlying mechanisms and functions. It is instructive to note that similar terminological problems plagued the study of social learning, as Galef pointed out over 30 years ago: ‘Some investigators prefer purely descriptive terms even though these can obscure differences in the mechanisms underlying surface similarities in behavioural interaction.… Others utilise terminology reflecting hypothesised underlying mechanisms mediating observed behavioural interaction…, and there are those who employ operationally defined categories…’. He lamented that the explosion of new definitions and labels has added nothing to our understanding of the mechanisms or the adaptive functions for social learning. This is probably why Hamilton (1975) suggested that ‘it seems on the whole preferable to retain a more flexible use of terms’.
3.3 How do organisms recognise kin? (Proximate mechanisms) In this section, we provide an overview and examples of the various mechanisms through which organisms identify or distinguish kin versus non-kin. We also suggest a classification scheme for these mechanisms based on the broad and narrow definitions for KR. Then, we consider a general model describing the key components that are thought to comprise all KR mechanisms. 3.3.1 Types of kin recognition mechanisms There are several different mechanisms that enable animals to distinguish kin versus non-kin, and several classifications of KR mechanisms have been proposed. The most widely cited scheme (e.g. Sherman and Holmes 1985, Waldman 1987) proposes four categories: (1) recognition alleles; (2) familiarity (associative learning); (3) phenotype matching; and (4) spatially-based mechanisms. These categories are criticised because they are not based on consistent criteria, and some mechanisms (2 and 4) are not considered to be KR by researchers who reject the broad definition for KR. The alternative proposals, however, are rather complicated (Barnard et al. 1991, Tang-Martinez 2001) or too simple (e.g., it has been suggested to exclude spatially-based mechanisms, and combine the rest into two catego-
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ries, recognition alleles and learning; Barnard et al. 1991, Tang-Martinez 2001). Thus, the proposed classifications of KR mechanisms vary depending upon how researchers define kin recognition. Therefore, we propose a classification of the types of KR based on broad or narrow-sense definitions (Table 3.2). We first examine examples of KR in the broad-sense (spatially-based mechanisms and familiarity), and then in the narrow-sense (indirect familiarity, self-inspection, and green-beard genes). Another distinction used for classifying KR mechanisms is based on the types of cues, which can be divided into two categories: indirect, contextual cues versus direct, phenotypic cues (Waldman 1988). This distinction may be somewhat confusing since direct, phenotypic cues are further divided into direct versus indirect familiarity (see below; Wyatt 2004), but it is useful nevertheless. Table 3.2. Kin recognition mechanisms can be classified according the matching rules (i.e., the referents used for recognition).
Definitions for kin recognition 1. Contextual cues non-conspecific cues (spatial, temporal, and state-dependent cues) 2. Phenotypic cues A. Familiarity dependent recognition R compares S at time 1 to S at time 2 (e.g., associative learning of individually-distinctive cues) B. Familiarity-independent recognition (i) Indirect familiarity R compares S to K (e.g., associative learning’ of familialdistinctive cues) (ii) Self inspection R compares S with R (e.g., compare individually-distinctive cues through habituation/dishabituation) (iii) Green-beard genes R compares S with R (no prior experience necessary) R = receiver making the evaluation, S = sender being evaluated, and K = likely kin to R
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3.3.1.1 Indirect, contextual cues (spatial, temporal and other non-phenotypic mechanisms) Many species rely on spatial, temporal, or other contextual cues to distinguish kin versus non-kin (see Table 3.3). For example, many birds, mammals and fish rely on location to recognise offspring, and use the rule: ‘any young in my nest are mine’. For example, male house mice normally kill pups, but after mating with a female, they no longer attack her pups (Elwood and Ostermeyer 1984). They thus use mating as a contextual cue to assess the probability of being related to the pups (state-mediated recognition). Female moorhens (Gallinula chloropus) destroy any eggs they find in their nest if they have not begun to lay eggs, and they apparently use their knowledge of their own egg-laying to bias investment into their own offspring (McRae 1996). Such decision rules are not necessarily all-ornone. In dunnocks (Prunella modularis), males allocate parental care based on the amount of sexual access they had to a mate, which correlates Table 3.3 Kin recognition has been found in a wide variety of species, and these are some arbitrarily chosen examples from different taxa. Kin recognition 1. Contextual cues Burying beetles (Necrophorus vespilloides)
Mothers kill larvae that hatch too early to be own young
Müller and Eggert 1990
Bird
Bank swallows (Riparia riparia)
Treat all chicks in their nest as their own, as long as chicks are younger than 14 days
Beecher et al. 1981
2. Phenotypic cues a. Familiarity-dependent recognition Predatory mites (Phytoseiulus persimilis)
Cannibalise non-kin and unfamiliar kin, but not familiar kin
Schausberger 2007
Bird
Barnacle geese (Branta leucopsis)
Breed near sister, but only when they were born in the same year
van der Jeugd et al. 2002
Mammal
Barbary macaques (Macaca sylvanus)
Avoid mating with individuals with whom they were familiarised during early life
Kuester et al. 1994
Broad sense KR
Insect
Broadest sense KR
Insect
Kin recognition: conceptual issues, mechanisms and evolutionary theory
Broadest sense KR
b. Familiarity-independent recognition (i) Indirect familiarity Prefer to shoal with unfamiliar kin, based on learning of sibling’s cues
Frommen et al. 2007a,b
Fish
Pelvicachromis taeniatus
Both sexes prefer familiar as well as unfamiliar kin as mates
Thünken et al. 2007a,b
Mammal
House mice (Mus musculus)
Males prefer to mate with females carrying MHC genes of the family with which they are reared
Yamazaki et al. 1988
(ii) Self inspection Plant
Sea rockets (Cakile edentula)
Grow additional roots when share soil with non-kin
Dudley and File 2007
Bird
Peafowl (Pavo cristatus)
Peacocks, raised with non-kin, lek with relatives
Petrie et al. 1999
Amphibian
Clawed frogs (Xenopus leavis)
Preferred to group with siblings with which they shared MHC haplotypes to those with no MHC haplotypes in common
Villinger and Waldman 2008
Prefer forming chimeras with related cells
Queller et al. 2003
Broad sense KR
Three-spined stickleback (Gasterosteus aculeatus)
Narrow sense KR
Fish
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(iii) Green-beard genes Social amoeba
Dictyostelium purpureum
with offspring paternity (Davies et al. 1992, Hartley et al. 1995). Some contextual cues may be easily exploited by cheaters, but there may be no cheat-proof mechanisms. Extreme examples are birds that care for a cuckoo’s chick in their nest. Furthermore, contextual cues may not allow recognising kin outside the respective context. Because direct conspecific phenotypic cues are not involved, and mistakes are possible, some researchers argue that species that utilise contextual mechanisms do so because they lack the ability to recognise kin (Barnard et al. 1991, Tang-Martinez 2001). Indeed, classifying indirect, contextual cues as KR seems an odd use of the term recognition, but perhaps such cues are commonly utilised in most other types of recognition
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systems. Contextual mechanisms are KR in the broadest sense of the term, and some may prefer to consider them as kin bias without kin recognition (see BOX 3.1). 3.3.1.2 Direct, phenotypic cues Some suggest that the term KR should be restricted for mechanisms that rely on direct cues from conspecifics, including chemical, acoustic, visual, behavioural or other phenotypes (Barnard et al. 1991, Tang-Martinez 2001). These may be features of individuals or groups (e.g., colony odours). The first type of phenotypic recognition we address is another example of KR in the broad sense. A. Familiarity-dependent recognition (also called prior association). There is a great deal of evidence that animals rely on direct familiarity of cues from conspecifics to recognise kin (e.g., Table 3.3). This mechanism can be found in many species where young stay together during the first days of their life. Here, the phenotypes of individuals who are kin – or likely to be kin – are individually learned, classified and later on treated as related or not. Close kin are often more familiar than non-kin, and a wide variety of species use previous association to recognise kin (e.g. Westermarck 1891, Porter et al. 1981, Dewsbury 1982, Holmes and Sherman 1982). They follow a rule: ‘treat familiar individuals as kin because they are likely to be kin’. Individuals may become classified as kin if they become familiar at particularly sensitive times during ontogeny. For example, humans and other mammals negatively imprint on individuals with which they are reared, and subsequently avoid mating as adults. They follow the rule: ‘avoid mating with individuals I grow up with in my family’. This so-called Westermarck effect was the first mechanism discovered to control kin discrimination in humans (BOX 3.3). Tang-Martinez (2001) suggests that kin biases based on familiarity should be regarded as individual rather than kin recognition. These are not mutually exclusive alternatives, however, and it seems moot to debate whether to call such behaviours kin biases based on individual recognition or kin recognition based on individual familiarity. As familiarity is not considered to be KR by some researchers (but instead, it is seen as something that must be controlled to test KR), we consider it to be KR in the broad sense. Regardless, determining how animals distinguish kin versus non-kin among unfamiliar individuals is clearly one of the more challenging problems in this field. There are at least two types of mechanisms that do not require familiarity, and we consider these to be KR in the narrow sense.
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BOX 3.3 Kin recognition in Homo sapiens
In his autobiography, Hamilton (1996:3) commented that he ‘did not anticipate the degree of relevance to humans that the findings eventually proved to have’. However, he surely realised that incest avoidance is a topic that has puzzled thinkers since ancient times (Porter 1991). Like other animals, humans show kin biases in a wide array of contexts, including incest avoidance, parental care, and cooperative behaviour. The mechanisms they use are multifarious, too. Maybe the best known is direct familiarity (also known as the Westermarck effect). Westermarck (1981) described that small children are negatively imprinted on their age mates, avoiding them as partners when reaching adulthood. Similar results were found by Lieberman et al. (2007) who showed that kinship is estimated by the perinatal association of the proposed sibling with the individual’s genetic mother as well as through the duration of time siblings live together. Many studies show that human offspring are able to recognise their mothers through volatile scent cues, and vice versa (Porter 1991). There is suggestive evidence that humans are also capable of recognising unfamiliar kin as well, and self-reference may play a role. For example, DeBruine (2002) found people trust a stranger’s face more when it has been morphed with their own than when it was left unchanged. Familiarity was ruled out by using morphs of celebrities; only selfresemblance mattered. The use of self-reference in human KR was further supported by a study that found that dizygotic as well as monozygotic twins preferred pictures of faces that were merged with their own over faces that were merged with the face of the twin (Bressan and Zucchi 2009). B. Familiarity-independent recognition. (1) Indirect familiarity (also called ‘phenotype matching’) Individuals can potentially recognise kin even among unfamiliar individuals by comparing the phenotypes of putative kin with those of known kin: individuals who resemble their own kin are treated as related. There are examples of this KR mechanism in many species in which the young stay together during the first days of their life (Table 3.3). For example, in brood-caring fish, fry have ample opportunities to learn cues (e.g., smell) of their siblings or parents before they leave the nest or cave. Later on in life they use these cues to recognise not
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only their nest mates, but also relatives raised in other broods. This mechanism not only allows recognising unfamiliar siblings, but also more distantly related kin like half-siblings or cousins (see BOX 3.4). Its weakness is that in species with close contact between kin and nonkin during maturation (e.g., in colonial species) or with high amount BOX 3.4 MHC genes: candidate genetic loci for kin recognition cues The genes of the major histocompatibility complex (MHC) are a multigene family of highly polymorphic loci that control immunological self/nonself recognition, and are suspected to play a role in KR (Brown and Eklund 1994). MHC genes influence odour and mating preferences in a variety of species, including mice, humans, fish, and frogs (Yamazaki et al. 1988, Penn and Potts 1998, Milinski 2006). MHC-dependent mating preferences may function to increase or optimise offspring MHC-heterozygosity (e.g., Penn and Potts 1998, Penn et al. 2002), avoid inbreeding, or both (Penn 2002). Female mice prefer to nest communally with sisters, or MHC-identical individuals when sisters are unavailable (Manning et al. 1992). Also, female mice are more likely to retrieve pups if the pups are MHC-identical to the dam (Yamazaki et al. 2000). It is unclear how MHC genes influence odour, though several candidate volatiles have been identified (Willse et al. 2005, 2006, Novotny et al. 2007), and MHC-derived peptides have been shown to be detected through the vomeronasal organ (Leinders-Zufall et al. 2004). Interestingly, house mice avoid mating with individuals carrying MHC genes that are identical to the foster family with which they are reared (familial imprinting; Yamazaki et al. 1988, Penn and Potts 1998). This behaviour may provide a more effective mechanism for avoiding sib matings than self-inspection. For example, consider the MHC-genotypes of closely related mice, shown below (most individuals are heterozygous since MHC genes are polymorphic). If ac relies entirely on self-inspection, she will risk mating with 0.25 of her siblings (bd) and 0.5 of her half-siblings (de and df). In contrast, by using familial imprinting, ac can avoid mating with all full-siblings (bc, ad, bd), all half-siblings (ce, cf, de, df), and half of all cousins (Penn and Potts 1999). By imprinting on a variety of phenotypic cues of family members, this may provide a highly effective mechanism to avoid inbreeding (i.e., indirect familiarity). ab
ac
bc
cd
ad
ef
bd
ce
cf
de
df
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of stolen fertilisations, individuals may learn the cues of relatives as well as non-relatives and treat all individuals bearing these cues similarly. This mechanism is often called phenotype matching, and is seen categorically distinct from familiarity, but the crucial difference is that with phenotype matching the animal learns self- or familial- rather than individually-distinctive cues (Porter 1988, Barnard et al. 1991, Tang-Martinez 2001). (2) Self-inspection (also called’ self-referent phenotype matching’ and the ‘armpit effect’) It has been suggested that to recognise kin, animals might inspect their own scent, voice or other phenotypic cues and compare how well they match with other individuals, and use the similarity to recognise kin (armpit effect, Dawkins 1976). There are some, though still surprisingly few candidates for KR through self-inspection (Table 3.3), and these are often found in unicellular organisms, fungi and plants, rather than animals (reviewed in Tsutsui 2004; Table 3.3). Mateo and Johnston (2000) reported evidence for self-referent phenotype matching in golden hamsters (Mesocricetus auratus). However, their study is criticised for several reasons, e.g., not ruling out post-partum and earlylife familiarisation with close kin through fetal olfaction (e.g., Heth and Todrank 2001, Mateo and Johnston 2001, Hare et al. 2002, Mateo and Johnston 2003). Self-inspection may evolve when the opportunity to learn relative’s cues is limited or unreliable due to a lack of family members to use for comparison, or due to the presence of unrelated individuals in the same nest or burrow. Self-inspection is often viewed as categorically distinct from other learning mechanisms, yet it is arguably a type of phenotype matching, in which the cues used for comparison are not learned from conspecifics but from self. Self-inspection might also be considered to be a type of familiarity (associative learning) (though if it involves habituation to one’s own cues, this is non-associative rather than associative learning). Oddly, self-reference matching is widely considered a form of genetic KR in the strict sense (recognition alleles, see below) even though genetically determined cues may or may not be involved. A problem with the self-inspection hypothesis is that it is unclear how it might be empirically distinguished from green-beard effects. (3) Green-beard genes (also called ‘recognition alleles’, and ‘genetic kin recognition’) As mentioned in the introduction, when speculating on how animals might evolve mechanisms to recognise their kin, Hamilton (1964) postulated the evolution of a supergene that is able to recognise and help
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copies of itself in other individuals (Haig 1996), and this model became known as a green-beard gene (Dawkins 1976, 1982). A greenbeard gene helps copies of itself by encoding three traits: (1) influencing the expression of a rare phenotypic trait, such as a green beard; (2) enabling individuals to recognise the trait in others; and (3) acting altruistically towards individuals carrying the trait (or antagonistically towards individuals that do not). In other words, the same gene influences all these traits simultaneously through pleiotropy. Green-beard effects may be controlled by a single or multiple loci, and if their effects are controlled by multiple loci, this might be considered a genetic KR system (Grafen 1990). The distinction between green-beard effects and other types of genetic KR mechanisms is fuzzy in theoretical models (Rousset and Roze 2007). Green-beard genes are often dismissed as being far-fetched; even Hamilton recognised that it is unlikely that a single gene could ever influence all these traits. Some argue that green-beard genes are unlikely because they are genetic outlaws, as they help individuals bearing similar cues who are sometimes unrelated, this leads to intragenomic conflicts, which favours the evolution of suppressor genes (the parliament of the genome; Alexander and Borgia 1978, Helantera and Bargum 2007). Others argue that green-beard genes are not necessarily outlaws, as the rest of the genome will reap any benefits obtained by a green-beard gene (Ridley and Grafen 1981). The first report for a green-beard gene was found in a study on spiteful behaviour in fire ants (Solenopsis invicta; Keller and Ross 1998), though these findings have been challenged (Vander Meer and Alonso 2002). Subsequently, several candidate green-beard effects have been reported, including cooperation among budding yeast (Smukalla et al. 2008), social amoeba (Queller et al. 2003) and lizards (Sinervo et al. 2006), parent-offspring recognition at the placenta (Haig 1996, Summers and Crespi 2005), altruistic sperm pairing (Moore and Moore 2002), and self-incompatibility loci in plants (reviewed in Tsutsui 2004). As mentioned above, the main problem with the green-beard gene hypothesis is empirically distinguishing it from self-inspection: it requires eliminating all phenotypic cues that an organism could obtain about its own phenotypic cues, which seems difficult if not impossible. Therefore, many evolutionary researchers combine them together into tag-based kin recognition (e.g., Axelrod et al. 2004, Antal et al. 2009), as we will see in the next section. In summary, there is much evidence that many species can distinguish kin and non-kin, and some evidence to support all of the proposed mechanisms. Furthermore, the various types of KR mechanisms
Kin recognition: conceptual issues, mechanisms and evolutionary theory
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are not mutually exclusive, as they may be used by different individuals within a species, or they may change during development, age, or an individuals’ condition or context (Neff and Sherman 2002, Mateo 2004). 3.3.2 Key components of KR mechanisms Even though there are several types of KR mechanisms, it has been suggested that all KR systems must have several key components or design features to enable individuals to recognise and respond differentially to kin (e.g., Sherman and Holmes 1985, Waldman 1987; Fig. 3.1). From this perspective, KR is not a single system, but rather a device or contraption with many components. First, KR requires a sender that produces kinship cues (also known as markers, labels, signatures, and tags), which are phenotypic traits produced by the organism, such as chemical, visual, or acoustic signatures, that provide information about kinship. Kinship cues must be highly variable among individuals – and also consistent or developmentally stable within each individual, and the variability of cues must be genetic or correlated with genetic relatedness (e.g., see BOX 3.4). KR cues may function specifically to indicate relatedness, or more likely they are produced incidentally, with no special function for communicating relatedness. For example, Todrank and Heth (2003) suggest that animals produce odour signals (which are usually a blend of compounds or ‘signature mixtures’ sensu Wyatt 2004) that have a wide range of functions, from individual to kin to species recognition. The broadest definition of KR, as we have seen, also includes indirect spatial, temporal or other contextual cues associated with kinship, as well as direct phenotypic cues, though these would not be an example of kin communication (see below). Second, recognition begins with sensory detection (or perception) of kinship cues, such as through olfaction, visual, hearing, or tactile mechanisms by receivers (also called discriminators). Usually, only one type of sensory modality is studied, though a combination may be involved (multimodal processing; e.g., the sheep example (Ovis aries) in Halpin 1991). Next, recognition requires a phenotype matching mechanism: a hypothetical device that compares a sender’s cues to a template, an internal model or representation of cues from self or other referent, and evaluates the similarity between them, as necessary for classification (Lacy and Sherman 1983). A template may be learned from self (self-inspection) or from other referents, even though phenotype matching is often seen as categorically distinct from self-inspection. Recognition errors occur due to
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Sender: 1. Cues Display chemical, visual, acoustic information e.g., scent marking
Contextual information (e.g., spatial cues)
Receiver: 2. Recognition Perception (sensory detection) e.g., olfaction Phenotypic matching e.g., self-inspection
3. Decision-rules / Heuristics e.g., avoid similar smelling mates
Receiver’s physiological state and ecological context
4. Action e.g., inbreeding avoidance
Fig. 3.1 Kin recognition (or kinship communication) involves several key components, from (1) the production of cues by senders to (2) recognition, (3) decisions, and (4) actions by receivers. Recognition per se includes cue detection and phenotypic matching, which are used for making decisions regarding actions. Spatial, temporal, and other contextual cues may be used, at least for KR in the broadest sense. Self-inspection (shown above) and indirect familiarity are examples of KR mechanisms in the narrow sense. Decision rules involve acceptance thresholds and simple rules-of-thumb that enable receivers to evaluate the likely relatedness of conspecifics. Decisions may also integrate contextual information about the receivers’ own age, condition, physiological state, and ecological constraints to weigh the perceived costs and benefits (adapted from Sherman and Holmes 1985, Waldman et al. 1988; mice drawn by Shawn Meagher).
excess over-lap in cues, and one of the central problems for KR systems is to optimise the risk of acceptance errors (Type I or false positives), due to accepting undesirable recipients, with rejection errors (Type II or false
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negatives), due to rejecting ‘desirable recipients’ (Reeve 1989, Beecher 1991, Sherman et al. 1997). Third, after recognition, receivers use this information for making decisions, which are cognitive or other information processing devices that control behavioural and other responses (or store the information into memory). Adaptive decisions also integrate contextual information about the receivers’ internal state or motivation, and other relevant information. For example, plains spadefoot toad tadpoles (Spea bombifrons) cannibalise other tadpoles and they eat more non-kin than kin, except for when they are very hungry; then they become indiscriminate (Pfennig et al. 1993). The importance of the context-dependence of acceptance thresholds should not be underestimated. Fourth, receivers’ decisions enable them to take the appropriate action, which may be developmental, physiological or behavioural responses that result in differential treatment of kin (e.g., Liebert and Starks 2004). For example, this occurs when a mother rejects a foreign offspring because she detects that it has previously been licked or labeled by another female. Actions can be all-or-none, such as when there is a critical threshold above which all senders are accepted and below which they are rejected. However, whether receivers take action or not depends on the relative rates of interaction with and the fitness consequences of accepting and rejecting desirable and undesirable recipients (Reeve 1989). As we will see later, recognition does not necessarily lead to discrimination if, for example, the perceived costs outweigh the benefits. This summary of KR components differs somewhat from previous versions (Sherman and Holmes 1985, Waldman 1987). For example, we do not consider cues and actions as components of recognition per se, even though cues are necessary for recognition to occur. We divide recognition and decision-rules into separate components, because they may be mechanistically distinct. Referring to all these steps as components of recognition overlooks the communication aspects of the system, and particularly selection on the sender’s cues (Beecher 1991). Therefore, this model is more accurately described as components of kinship communication rather than a KR system, and communication is not necessarily honest. This is an important point for evolutionary analyses of KR, which we address in the next sections.
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3.4 Evolutionary analyses of kin recognition KR research has always been grounded on evolutionary analyses of social behaviour, and particularly Hamilton’s ideas about nepotism (see Holmes 2004). In this section, we provide an overview of theoretical analyses that have aimed to understand how KR recognition evolves, and in particular, how natural selection maintains the diversity of genes controlling KR (in the narrow sense). These analyses have only considered the evolution of KR in mediating cooperation (nepotism) so far, and not inbreeding avoidance or other kin biases, and they have only examined self-inspection (or green-beard effects), and not considered indirect familiarity. 3.4.1 Evolutionary origins and maintenance of genetic kin recognition It has been difficult to understand how KR might evolve and be maintained by natural selection. Crozier (1986) made the first mathematical model of the evolution of KR by examining its role in nepotism, and he concluded that it is unstable, and inevitably drives itself to extinction. He found that individuals bearing common phenotypic cues (markers) have more opportunities to find and engage in cooperative activities than those bearing rare markers, and therefore, they gain greater fitness. The common markers become even more common over time, and eventually all individuals have the same marker. Once a marker no longer provides an indicator of kinship, there is no benefit to KR. In short, rare alleles will be at a disadvantage in finding cooperators, which eliminates the marker diversity, and any benefits of KR. Nevertheless, Crozier (1987) suggested that genetic variation in KR cues might be maintained by piggy backing on other loci under balancing selection, such as inbreeding avoidance, parentoffspring recognition, individual recognition, or a completely different source of selection, such as parasites. Grafen (1990) pointed out that Crozier’s model assumed that social interactions are always beneficial as there are no cheats (social parasites that display a marker and exploit other’s cooperation), and therefore, there is no benefit to limiting interactions to kin. Rare markers provide better indicators of kinship, which would favour greater altruism among individuals carrying rare markers. He concluded that ‘cheating maintains genetic polymorphisms at the matching locus because common alleles are hit harder when cheating arises, because they are too trusting’. On the other hand, if the marker and conditional helping evolve independently, then cheaters, displaying the correct marker without providing help, might un-
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dermine the system. Axelrod et al. (2004) conducted a simulation in which heritable cues of relatedness, which they called tags, can coevolve with discrimination and other strategies based on these indicators. They found that conditional or discriminating altruism can be maintained in a stable equilibrium. Jansen and van Baalen (2006) made a similar simulation based on a recognisable cue (coloured beards) to study the evolutionary dynamics of beard colour polymorphism (beard chromodynamics). They found that complete linkage between the matching and conditional helping loci leads to highly unstable dynamics, and to the rapid loss of tag variation (beard colours). However, when they allowed low recombination, beard colour and conditional helping were maintained at intermediate frequency in the population. This is in contrast to the assumption that tight coupling (pleiotropy or close linkage) is necessary for green-beard effects. Thus, it appears that cooperative genes must continuously change their tags to avoid exploitation by defectors or social parasites, much like red queen dynamics in host-parasite interactions. Rousset and Roze (2007) constructed a model using two-loci that control matching and helping, and they examined how various rates of recombination and dispersal (spatial population structure) affect the maintenance of polymorphisms. They found that selection usually eliminates KR and helping due to the benefits for common markers, just as Crozier (1986) found. Yet, when they reduced dispersal and recombination between the matching and helping loci, the polymorphisms were maintained: rare markers benefit from greater levels of helping, just as Grafen (1990) suggested. Increasing mutation rates help to maintain polymorphisms at both loci, as mutations supply new alleles into the system as they go extinct, but this still requires restrictive conditions. Perhaps the most interesting finding is that adding an extrinsic selective advantage for rare alleles, such as negative-frequency dependent selection from parasites, effectively maintains KR and conditional helping (Gardner and West 2007), as Crozier (1986) also suggested. More recently, Antal et al. (2009) used an analytical approach to model the evolution of conditional cooperation based on tag-based recognition of phenotypic similarity (green-beard or self-referent effects). Unlike previous models, they found that the evolution of cooperation does not require spatial structure. They also found that cooperation is more likely to evolve if the strategy mutation rate is controlled by one or few genes, and the phenotypic tags are encoded by many loci. In summary, nepotism mediated by KR may be prone to drive itself to extinction, but not always. It can be maintained under certain conditions, namely linkage between loci and subdivided population structure, and
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from extrinsic sources of balancing selection – such as from parasites. Its red queen dynamic nature suggests that its occurrence will vary over time and space, i.e., among populations and even within populations of the same species. We should expect genetic KR driven nepotism to be found in species with low dispersal and recombination. Evolutionary analyses help explain why MHC genes, which control immunological recognition of parasites, are also implicated in KR (Gardner and West 2007; BOX 3.3). Although these models suggest that nepotism through genetic KR is unlikely to evolve without spatial structure or other restrictive conditions, a recent analysis suggests otherwise (Antal et al. 2009). 3.4.2 Apparent kin recognition failures There are many examples in which animals do not seem to recognise their kin, even when it would seem to be in their interest to do so. For example, when male birds are cuckolded, they do not eject the extra-pair offspring from the nest. It is instructive to consider apparent KR failures (Beecher 1991, Sherman et al. 1997), and the evolutionary hypotheses to explain them. First, KR (or KB) may not occur because the costs of discrimination outweigh the benefits. There are surely potential tradeoffs for any kinbiased behaviours, so that the optimal response may sometimes require taking no action or discrimination, which might be mistaken as a recognition failure. For example, it has been suggested that the benefits of rejecting extra-pair offspring by male birds may not be worth the costs of making recognition mistakes, and erroneously killing their own offspring (Kempenaers and Sheldon 1996). There may be other costs for males that discriminate against extra-pair offspring, such as risk of desertion by their mate. It is instructive to consider that the body’s immune system functions to recognise parasites; however, a lack of immune responses to a parasite is not necessarily due to a recognition failure. Mounting an immune response can help resolve an infection, but it also has costs, especially in case of autoimmunity and other forms of immunopathology. Since immune recognition has detrimental side-effects, hosts are sometimes favoured that show greater immune tolerance to infection. Similarly, just as selection favours optimal immunity and tolerance rather than maximal responsiveness, we should expect kin discrimination responses to be optimised to balance the potential fitness costs and benefits. This decision problem faced by receivers has been studied in several theoretical models (Reeve 1989, Beecher 1991), but it has not been empirically tested to our knowledge.
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Second, KR may not occur because signalers are under selection to conceal their identity to potential receivers (anti-recognition hypothesis) (Beecher 1991). For example, fathers may not recognise their own offspring because in species with high rates of extra-pair paternity, offspring may be favoured to conceal their identity so that they do not resemble their genetic fathers (also called neonatal identify deception) (Beecher 1991, Pagel 1997). Most analyses assume that signalers honestly signal their identity, even if only inadvertently, and do not consider the possibility that individuals evolve mechanisms to disguise themselves. Yet, one theoretical analysis shows that selection can favour concealment over a wide range of conditions (Johnstone 1997). Moreover, it shows that kin discrimination will not evolve just because it benefits receivers: it depends on whether honest signature cues are also beneficial to signalers. This is called the communication problem, as it involves the evolution of the sender’s cues, as well as the receiver’s KR abilities (Johnstone 1997). Similarly, the failure of the immune system to recognise invading pathogens is sometimes due to pathogens evolving mechanisms to escape immune recognition. Interestingly, such deception games may be required for selection to maintain cooperation through KR (Grafen 1990), as we previously discussed. Finally, a failure to recognise kin may be maladaptive for a variety of reasons, such as insufficient time to evolve and adapt to new environmental conditions (evolutionary lag-time hypothesis; see Dawkins 1982), or as we have seen, selection from kin-biased behaviours eroding the genetic polymorphisms required to maintain itself (Crozier 1987). Such maladaptive ideas are hypotheses of last resort however, as testing requires ruling out the functional hypotheses.
3.5 Conclusions and future directions Many species have the ability to distinguish kin from non-kin, which may function to facilitate helping kin, avoiding inbreeding, or other kin-biased behaviours. Whether a species shows KR or not depends on how one defines this term, and there is much debate over how to define it. It might be useful to replace the term KR with KD or perhaps kin detection, kin identification, or kinship communication, though these alternatives have their own problems. We suggest that it is useful to retain broad definitions for KR, and treat the strict definitions as hypotheses about the mechanisms and functions. There is also much debate about how to classify the various types of KR mechanisms, and as a pragmatic approach, we suggest classifying the mechanisms according to whether they fit the broad or narrow-
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sense definitions of KR. Finally, recent theoretical studies are helping to explain the evolution of nepotism through KR, as well as apparent KR mistakes, errors and failures. There are still many unresolved problems regarding KR, and here, we suggest a few ideas for future research on both mechanistic and evolutionary questions: (1) The proximate mechanisms through which KR affects KB’s are unclear, and more work is needed here. Efforts to find candidate genetic loci controlling KR could narrow the search by focusing on linked loci that are highly polymorphic, and control immune recognition to pathogens and parasites, and not only MHC genes (BOX 3.4). (2) The adaptive functions of KR are not well understood (Blaustein et al. 1991). KD is thought to increase the indirect fitness of the individual through cooperation; however, experimental evidence for this hypothesis is still scarce, opening ample opportunities for future studies. (3) It has been suggested that somatic incompatibility (or allorecognition) systems of colonial organisms might function for KR, and that these have multiple phylogenetic origins (Crampton and Hurst 1994). These ideas deserve further analyses. (4) It is often assumed that a species has either evolved KR or not, and when different studies report mixed results the positive evidence is treated with scepticism. Yet, theoretical models predict much intraspecific variation in KR abilities within and among populations, as well as dynamic changes over time and according to the varying ecological constrains. For example, the report of green-beard genes in fire ants (Keller and Ross 1998) was not supported in a different study (Vander Meer and Alonso 2002) perhaps due to geographic variation (also see Liebert and Starks 2004). Future studies should examine such variability, and also how mechanisms may change during development, age, condition or context (Neff and Sherman 2002, Mateo 2004). (5) There are several models on the evolution of genetic KR, but what are the conditions in which natural selection favours the evolution of KR through familiarity, indirect familiarity and other types of learning? (6) Theoretical analyses of the evolution of KR are restricted to the evolution of conditional helping (nepotism), and future models need to consider inbreeding avoidance and other potential benefits (and preferences for mating with kin to increase inclusive fitness benefits).
Kin recognition: conceptual issues, mechanisms and evolutionary theory
GLOSSARY Green-beard gene: a postulated gene that simultaneously influences the development of a characteristic phenotype (cue), the ability to recognise this cue, and also helping conspecifics bearing this cue or label (or harming those who do not). Genetic relatedness: estimated by calculating the proportion of genes shared, or the probability of alleles at a randomly chosen locus, between two individuals being shared due to common descent (Sewall Wright’s coefficient of relationship r). However, there is no single or absolute measure of relatedness among individuals, as it is relative to the population mean, which can surprisingly result in negative relatedness. Thus, relatedness is not simply a measurement of genetic similarity between individuals, as it depends on the population structure (Griffin and West 2002) Heuristic: simple rules-of-thumb for detection, recognition, making classifications or other decisions that are efficient and accurate under most circumstances, even though they can also lead to errors. These appear to be used in all KR mechanisms. Inclusive fitness: an individual’s own reproductive success (conventional fitness) plus its effects on the reproductive success of its relatives, each one weighed by the coefficient of relatedness (Dawkins 1982). Kin: individuals that are genetically related due to direct inheritance or recent shared ancestry or common descent (e.g., offspring, siblings, cousins, etc.). Kinship: a special case of genetic similarity in which the probability of individuals sharing an allele at a particular locus depends upon their distance in a path of common descent (Grafen 1990). Kin bias (KB): differential treatment of kin versus non-kin, which may be due to kin recognition or not (Barnard 1991). Kin discrimination (KD): differential treatment of kin based on the ability to recognise kin versus non-kin (Barnard 1991), unless otherwise indicated (see BOX 3.2). Kin recognition (KR): in the broad sense, it refers to the ability to identify, distinguish and classify kin versus non-kin, though there are several narrow versions (see Table 3.1). We use the term in this broad sense, unless otherwise indicated. Kin selection: natural selection due to interactions among kin, such as nepotistic helping behaviours. There are several common misunderstandings about kin selection (see Dawkins 1979 for details), which is why Hamilton disliked this term. Nepotism: a form of conditional helping, in which altruism is provided to close kin (parental care is a special case of nepotism). This behaviour is often referred to as kin selection.
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Dustin J. Penn and Joachim G. Frommen Recognition alleles: in the broad sense, genes that control KR (or at least the production of cues and ability to recognise kinship cues). In the literature this term is used for green-beard genes, self-inspection, or both.
Acknowledgements We are very grateful to Z. Tang-Martinez, who offered particularly thoughtful comments on the manuscript. We thank A. Hettyey, T. Thünken, S.A. Baldauf, S.M. Zala, an anonymous referee, as well as many students for their helpful comments on earlier versions, and S. Meagher for the illustrations of mice and R. Hengsberger for assistance with figures and tables. Finally, we thank P.M. Kappeler for editing the volume and inviting us to write a chapter.
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genetic relatedness 2, 25 green-beard gene 2, 16, 25 heuristic 25 inclusive fitness 2, 25 kin 25 kin bias 2, 3, 25
kin discrimination 25 kin recognition 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 14, 15, 20, 22, 25, 26, 27, 28, 29, 30, 31 kin selection 3, 25 kinship 25 nepotism 1, 3, 4, 20, 21, 24, 25 recognition allele 8, 15, 26
