the complexity of social complexity: a quantitative

The Complexity of Social Complexity: A Quantitative Multidimensional Approach for Studies of Social Organizationvol . 1 96 , no . 5 the amer ican natural i st november 2020
Synthes is
Jacob G. Holland*,† and Guy Bloch*
Department of Ecology, Evolution, and Behavior, Alexander Silberman Institute of Life Sciences, Hebrew University of Jerusalem, Jerusalem, Israel
Submitted August 15, 2019; Accepted June 9, 2020; Electronically published September 11, 2020
Dryad data: https://doi.org/10.5061/dryad.x3ffbg7g6.
abstract: The rapid increase in “big data” during the postgeno- mic era makes it crucial to appropriately measure the level of social complexity in comparative studies. We argue that commonly used qualitative classifications lump together species showing a broad range of social complexity and falsely imply that social evolution always progresses along a single linear stepwise trajectory that can be deduced from comparing extant species. To illustrate this point, we compared widely used social complexity measures in “primitively eusocial” bumble bees with “advanced eusocial” stingless bees, honey bees, and attine ants. We find that a single species can have both higher and lower levels of complexity compared with other taxa, depending on the social trait measured. We propose that mea- suring the complexity of individual social traits switches focus from semantic discussions and offers several directions for progress. First, quantitative social traits can be correlated with molecular, developmental, and physiological processes within and across lineages of social animals. This approach is particularly promising for identifying processes that influence or have been affected by social evolution. Second, key social complexity traits can be combined into multidimensional lineage-specific quantitative indices, enabling fine-scale comparison across species that are currently bundled within the same level of social complexity.
Keywords: social complexity, social evolution, primitive eusociality, social insects, bumble bees.
Introduction
What Is Social Complexity?
Although there is no universal definition of “complexity,” in biological systems functional complexity commonly
* Corresponding authors; email: [email protected], guy.bloch@mail .huji.ac.il. † Present address: Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom. ORCIDs: Holland, https://orcid.org/0000-0002-4064-0630; Bloch, https://
orcid.org/0000-0003-1624-4926.
Am. Nat. 2020. Vol. 196, pp. 000–000. q 2020 by The University of Chicago. 0003-0147/2020/19605-59421$15.00. All rights reserved. DOI: 10.1086/710957
implies that a system is made from many specialized and interacting parts that together contribute to a function (e.g., a complex tissue is composed of more cell types than a simple tissue, and a complex organism has more tissue and cell types than a simple organism; Valentine et al. 1994; McShea 2000). Studies of insect sociality have typi- callyusedadifferent approach that is basedona small number of qualitatively defined social traits, including reproductive division of labor within a colony, cooperative brood care, and an overlap of multiple adult generations (table 1). This approach has been central to defining the “eusocial” (truly social) insects (Wilson 1971;Michener 1974; Batra 1966) as well as other classifications and subdivisions. Within an evolutionary framework, social complexity is typically used as a proxy for the degree of social group transformation, de- scribing how groups of formerly independent entities (such as cells or multicellular organisms) become new organism- like units (Maynard Smith and Szathmáry 1995; Keller 1999; Bonner and Brainerd 2004; Bourke 2011; Szathmary 2015; West et al. 2015). The richness and diversity of social insects have provided fertile grounds for cultivating ideas on the evolution of complexity and sociality. Social insects have formed the primary examples of the major evolutionary transition from a multicellular organism to a society of multicellular organisms and for the kin and multilevel selection theories (Hamilton1964;Maynard Smith and Szath- máry 1995; Keller 1999; Bourke 2011).
Limitations with the Common Classifications of Social Complexity in Social Insects
The framework in which we assess social complexity is critical for the interpretation of comparative studies. Well- resolved phylogenies and the rapid increase in sequencing the genomes, transcriptomes, and epigenomes of an increasing number of social and solitary animals has set the stage for a new wave of studies comparing molecular,
Table 1: Common qualitative classifications of social complexity
Least complex
Most complex
Eusociality: Behavioral division of labor and cooperative brood care between monomorphic parents and offspring.
Hypersociality: Queen and worker castes differ in morphology, physiology, and behavior. Colony reproduction by swarming.
Wilson 1971
Quasisociality: Cooper- ative brood care in nest of same-generation individuals.
Semisociality: Repro- ductive division of labor and cooperative brood care in nest of same-generation individuals.
Eusociality: Reproduc- tive division of labor and cooperative brood care between parents and offspring.
Michener 1974 (social bees)
Subsociality: Lone foundress mother provisions and protects brood until emergence of adults or foundress death.
Primitive eusociality: Queens found alone and morphologically similar to worker caste. Some reproductive and behavioral division of labor. Col- ony size typically in tens to hundreds.
High eusociality: Queen and worker castes differ in morphology, physiology, and behavior. Colony reproduction by swarming. Colony size typically in thousands or higher.
Crespi and Yanega 1995
Quasisociality: Some temporary reproductive division of labor, but lifetime reproductive success is unimodal. All individuals remain totipotent.
Semisociality: Tempo- rary reproductive division of labor with bimodal lifetime reproductive success. All individuals remain totipotent.
Facultative eusociality: The worker caste (but not the reproductive caste) has lost behavioral totipotency.
Obligate eusociality: Both worker and reproductive castes have lost behavioral totipotency.
Toth et al. 2016 (vespid wasps; also see Jandt and Toth 2015)
Subsociality: Foundress mother builds and inhabits nest alone. Shows extended maternal care.
Facultative sociality: Some foundresses in a population may nest with worker daughters.
Primitive eusociality: Founding by lone or small groups of females. Queen and worker castes highly flexible.
Advanced eusociality: Lone foundress. High queen-worker differentiation. Possible colony reproduction by swarming.
Boomsma and Gawne 2018
Cooperative breeding: No castes. All individuals can mate.
Eusociality: Some caste distinction. Mating chance correlated with age or body size. Queens maintain dominance hierarchies.
Superorganismality: All individuals belong to permanent castes lacking totipotency, with no mating for the worker caste.
Richards 2019 (social bees)
Sociality: Nest with social interactions between adult conspecifics, with no castes.
Eusociality: Behavioral division of labor and cooperative brood care between monomorphic parents and offspring (after Batra).
Hypersociality: Colo- nies with discrete castes, with no mating in the worker caste.
Note: Shown is a summary of criteria and traits suggested by some key studies for classifying the level of sociality. The term used for each level is highlighted in boldface. The solitary and aggregate levels are omitted. Where studies have primarily focused on certain taxa, this is shown in parentheses in the leftmost column.
Quantitative Social Complexity 000
organismal, and ecological data across different levels of social complexity (e.g., Cardinal and Danforth 2011; Kap- heimetal. 2015;RehanandToth2015;Tothet al. 2016;Glastad et al. 2017; Wittwer et al. 2017; Shell and Rehan 2018; Sum- ner et al. 2018). These comparative studies can drive the understanding of which traits and mechanisms influence, or are influenced by, the evolution of social complexity (Fischman et al. 2011). For example, molecular signatures of caste differentiation, an important component of social complexity, have already begun to be identified in diverse taxa (Sumner et al. 2018). However, the array of terms used to describe the levels of social complexity, such as “primitively eusocial,” “advanced eusocial,” “hypersocial,” and “superorganism,” are not always consistently used in the literature or across social lineages (table 1), leading to difficulties in comparisons across studies and in evolutionary interpretation of the data (Boomsma and Gawne 2018; Richards 2019 and references therein). We argue that a re- assessment of theway social complexity is defined andmea- sured is especially timely in the current genomic and post- genomic (“-omics”) era in which new molecular data open unprecedented opportunities for understanding the evolutionof sociality.We argue that in order tomeet this goal, the field needs to move from inconsistently defined and some- times unclear qualitative classifications into approaches that account for multiple quantitative traits as components of social complexity. The common qualitative classifications of social insects
(table 1) are built on the presumption of a single axis of social complexity, which is assumed to be supported by evidence for correlations between a number of social traits (Bourke 1999, 2011; Anderson and McShea 2001). For example, multiple social traits have been shown to be associated with colony size (Thomas and Elgar 2003; Holbrook et al. 2011; Kramer and Schaible 2013; Ferguson-Gow et al. 2014;Amador-Vargas et al. 2015) or thedegree of caste dimorphism (e.g., Fergusson-Gow et al. 2014; Sumner et al. 2018). Thus, while some classifications may consider multiple traits, the assumption of strong correlationmeans that only a single axis of variation is considered. By using a single scale, these classifications implicitly assume that the important traits underlying social complexity always evolve in synchrony with each other in a single narrow trajectory and faithfully reproduce specific stages along a ladderlike evolutionary pathway progressing from solitary to intermediate sociality (commonly termed “primitive eusociality”) to elaborated societies (e.g., defined as “highly eusocial,” “superorganismal,” or “hypersocial”; see examples above and in table 1). We herein term this approach the “linear stepwise model.” This common view also asserts, intention- ally or otherwise, that extant solitary species or species with simple societies faithfully represent the ancestors (i.e., lower rungs on a ladder) of species with more complex societies.
However, theoretical considerations and empirical studies suggest that social evolution (or other complex evolutionary traits) is not constrained in such a way that a pre- dictable and stepwise trajectory is consistently followed across independent lineages (reviewed in Linksvayer and Johnson 2019). Instead, studies with diverse social insects point to distinct, lineage-specific trajectories that may have been shaped bydifferent costs or benefits of eusociality (e.g., Fischman et al. 2011; Sumner 2014; Shell and Rehan 2018). There is evidence that key traits of “primitive eusociality” have been maintained for millions of years and so likely represent successful evolutionary strategies (Linksvayer and Johnson 2019 and references therein). Moreover, the assumption of a linear stepwise progression of traits is not consistent with species having different levels of social complexity across their social traits in a multidimensional mosaic fashion (fig. 1)—for example, if species A is more socially complex than species B in trait X but is less socially complex than species B in trait Y. Such a phenomenon, where different lineages vary in the level of complexity for different social traits, could result from selection pressures that are specific to certain ecological niches, preadap- tions, or life-history traits (e.g., predation pressure, latitudi- nal clines, habitat selection, nesting biology, or diapause; Rehan et al. 2012; Kocher et al. 2014). In this case, a more nuanced understanding of social evolution would be nec- essary, where different components of social complexity can evolve at different rates across, or even within, distinct phylogenetic lineages. We refer to this as the “multidimensional model.”
A Test Case: Are Bumble Bees Primitively Eusocial?
Bumble bees (tribe Bombini) form an especially useful focal lineage because there ismuch research on bumble bee physiology and sociobiology as well as that for other apid bees to which they are often compared. Bumble bees are commonly considered an intermediate stage of social complexity between the orchid bees, which are considered solitary, “primitively social,” or “facultatively eusocial” (Andrade et al. 2016), and the “advanced eusocial” honey bees and stingless bees. Indeed, Apidae are the most commonly used lineage for comparative studies of social complexity (Kocher et al. 2014; Richards 2019). However, it is not clear how well bumble bees really fit this assumed posi- tion. Bumble bees are also a good taxon with which to demonstrate inconsistency in the field because their level of social complexity has been variously described as “eusocial” (Wilson 1971), “primitively eusocial” (Michener 1974), “highly social” (Kocher et al. 2014), “superorganismal” (BoomsmaandGawne2018),or “hypersocial” (Rich- ards 2019), among other terms. Below, we use published
000 The American Naturalist
and new data to compare social traits of bumble bees with other social insect taxa (see the appendix for a description of our methods).
Queen-Worker Variation
Morphological differentiation between queens and workers has been often used as a key criterion for the highest level of social complexity (table 1). In bumble bees, queens are typically much larger than workers, and in many species the size ranges of workers and queens do not overlap (Cumber 1949; Michener 1974; Goulson 2010; Prs-Jones and Corbet 2011). We quantified the size ratio of bumble bee queens to workers and compared these ratios with those of the honey bee Apis mellifera, stingless bees, and attine ants (fig. 2; see the appendix for methodological details). These ratios were higher than those in the honey bee (although not statistically significant, probably as a result of the small sample size; t-test assuming equal variance,
t p 1:36, n p 7, P p :23) and comparable to those of many stingless bees (Wilcoxon rank sum test, W p 55, n p 27, P p :46), the “advanced eusocial” close relatives of bumble bees (Cardinal and Danforth 2011; Bossert et al. 2019). Notably, bumble bee queen-worker size dimorphism was significantly larger than that of attine ant species taken together (Wilcoxon rank sum test, W p 151, n p 36, P p :008); the degree of bumble bee dimorphism was actually numerically similar to that of the most extreme attines, Atta and Acromyrmex (the leaf-cutting ants), which have been used to exemplify an extremedegree of social complexity (e.g., Holldobler and Wilson 1990). Bumble bee queens and workers apparently differ in a few additional morphological traits (such as color patterns and possibly ommatidia number and the density of anten- nal sensilla; Goulson 2010; Chole et al. 2019) but do not show the strong allometric variation typical to queens of some “highly” social species (Wilson 1971; Michener 1974). Queens of many ants, honey bees, and stingless bees show more substantial morphological variation, reflecting
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Figure 1: Models for the evolution of increasing social complexity, represented by hypothetical social insect phylogenies. Different shapes refer to different social traits (e.g., queen-worker dimorphism, across-worker differentiation, or colony size). The common ancestor in each model is assumed to have the least socially complex traits (pale colors), whereas darker colors represent an evolutionary increase in quantitative (or qualitative) complexity for specific traits (see the main text for details). For simplicity, these models assume that traits cannot become less complex. At the tip of each branch, a present-day species is represented by a letter and its complement set of traits. In the linear stepwise model, the tree can be arranged so that social traits evolve increasing complexity in tandem (e.g., increase in colony size and in worker-queen differentiation), as depicted by the arrow. Under this model, it may be tempting to conclude that species A approximates the ancestral traits of species B, C, and D. Note that lineages that branched early in evolution share many features with the ancestor of the other lineages but themselves are not ancestral or more “primitive” to the other lineages. Moreover, given that nodes in phylogenetic trees can be freely rotated, arrow-like evolutionary inferences are arbitrary. In the multidimensional model, different social traits do not necessarily evolve synchronously along a single trajectory, meaning that species B may be more socially complex than species A in several traits but not in others (e.g., as a result of differing selection pressures). In the multidimensional model, there is no way to rearrange the tree such that it is consistent with a stepwise linear increase in social complexity.
selection on the same genome to produce two distinct developmental trajectories. Allometric or other morphological variability may be used for characterizing the degree of caste differentiation (Wilson 1971; Michener 1974), but it has not been precisely quantified and currently cannot be used in our analysis. Division of labor in reproduction is a hallmark of insect
sociality, and various measures of reproductive skew have been used as proxies for social complexity (e.g., the proportion of reproductive females, the proportion of queen- derived males, and worker ability to mate; e.g., Sherman et al. 1995; Rubenstein et al. 2016). In bumble bees, queens and workers have a similar number of ovarioles, but the queen has larger ovaries with a higher maximal number of mature oocytes, and she is significantly more fertile. Only queens attract and copulate with males and are physiologi- cally capable of diapause (Röseler and Röseler 1986; Am- salem et al. 2015). Nevertheless, in sharp contrast to honey bees, a large proportion of bumble bee workers activate their ovaries and attempt to reproduce at later stages of col-
ony development, even though relatively few worker offspring seem tomake it to adulthood in queenright colonies (Owen and Plowright 1982; Bloch et al. 1996; Bloch and Hefetz 1999; Brownet al. 2003; Takahashi et al. 2008).How- ever, worker egg laying may be similarly (and even more) substantial in many species of the “highly social” stingless bees. In some species workers lay numerous “trophic” eggs for the queen diet (Michener 1974), and in other species workers lay many male eggs (Toth et al. 2004). Thus, the highly eusocial stingless bees and the “primitively eusocial” bumble bees cannot be clearly separated on the basis of the degree of worker egg laying or the proportion of reproductive workers. Morphological differences between adult queens and
workers (including in overall body size) are determined by developmental processes during the embryo (egg), larva, or pupa stages. In particular, early differentiation is typically associatedwithmore distinct queen-worker phenotypes (Wheeler 1986) and has been suggested as a component of social complexity (Bourke 2011). In Bombus terrestris, the
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Figure 2: Queen-worker body size dimorphism in selected social insect genera. Bumble bees (red) are compared with 11 attine ants (black), 10 stingless bees (blue), and Apis mellifera (green). Each point represents queen-worker size ratio (mean queen size/mean worker size) for a single species of the genus indicated on the X-axis. Bombus data are from Cumber (1949; raw data) and from I. Medici de Mattos and G. Bloch (unpublished data). Bombus terrestris is highlighted with a black outline. Stingless bee and attine ant data are from Toth et al. (2004) and Ferguson-Gow et al. (2014), respectively. A phylogeny is shown to highlight relationships. Additional details on our methods are provided in the appendix.
known critical period for caste determination occurs early in development, a few days after larval hatching (Cnaani et al. 2000; Bortolotti et al. 2001). The paragraphs above indicate that bumble bees show
substantial queen-worker body size polymorphism, few worker-produced adults, caste-specific physiology, and early caste determination, which are comparable to those found in some “highly eusocial” species.On the other hand, they do not show caste-specific structures or significant allometric differences, and compared with honey bees (but notmany stingless bees) reproductive bias is relatively small in terms of the number of eggs laid by workers and the proportion of reproductive females.
Between-Worker Morphological Variation
Highly eusocial societies typically show clear division of labor between workers specializing in different tasks, and in some highly social ants and termites this is associated with morphological worker caste differentiation (Wilson 1971). At intermediate levels of social complexity (e.g., “primitive eusociality”), division of labor between workers is assumed to be less structured and morphological variation is expected to be absent or weak (table 1). It is then perplexing to note that bumble bees exhibit profound variation in worker size, with up to eightfold variability inmass in B. terrestris (Goulson 2010), tenfold variability in B. lucorum (Cumber 1949) and B. impatiens (Mares et al. 2005), and probably even more in “pocket- making” species such as B. pascorum and B. hortorum (Alford 1975; Pouvreau 1989; Prs-Jones and Corbet 2011). This variation is mediated by juvenile hormone and social inhibition, among other factors (reviewed in Chole et al. 2019). To investigate differences in this component of social complexity, we compared variation in worker body size between bumble bees and “highly eusocial” honey bees, stingless bees, and attine ants (see the appendix for details). Following previous studies, we used the coefficient of variation as a simple way to compare all genera (including those with morphological worker castes, such as Atta and Acromyrmex). We found that bumble bee colonies have a significantly larger variation in worker body size compared with their close relatives, the stingless bees (Wilcoxon rank sum test, W p 280, n p 47, P ! :0001; fig. 3). Bumble bee size variation was also larger than that in A. mellifera (although not quite statistically significant, probably as a result of the small sample size; t-test assuming equal variance, W p 2:39, n p 8, P p :054) and overall was comparable to that in attine ants (Wilcoxon rank sum test,W p 125, n p 43, P p :98). In fact, bumble bees show higher variation than all attine ant genera studied except the leafcutter ants.
Variation in body size by itself is not necessarily linked to social complexity because itmay not relate to functional variation in behavior. However, the profound worker body size variation in bumble bees has been repeatedly shown to relate to the propensity of workers to perform different tasks (reviewed in Michener 1974; Alford 1975; Goulson 2010; Chole et al. 2019). Specifically, many studies have shown that small workers disproportionately perform in-nest tasks, such as brood care, whereas larger workers disproportionately perform foraging activities. This behavioral variability is associated with a range of size-related morphological and physiological features (summarized in Chole et al. 2019) that apparently make larger workers more efficient foragers than smaller workers (Goulson et al. 2002; Spaethe and Weidenmuller 2002). There is also evidence consistent with a reduction in the performance of free-foraging B. terrestris colonies when the largest and smallest workers are replaced with middle-sized workers, at least under some conditions (Holland et al. 2020). This association with task performance links body size variation to social complexity because division of labor is a key organizational principle of insect societies. Other social insect taxa also exhibit an association between worker size variation and task specialization, which can be functionally significant even without allometric distinctions (Trible and Kronauer 2017). Thus, the high degree of between-worker body size variation coupled with its associated task specialization is not consistent with most definitions of primitive eusociality. Instead, it bears some similarity to the morphological worker castes found in highly eusocial societies of some ants and termites, despite having a monomorphic rather than polymorphic body size distribution, as in some ants. It should be appreciated, however, that division of labor can also be efficient without morphological variation, as seen in many other taxa.
Colony Size
Colony size (i.e., the total number of individuals, or only workers, in a colony) is broadly correlated with various indices of social complexity and has been commonly used as a proxy for the degree of social complexity (Wilson 1971; Bourke 1999; Bonner and Brainerd 2004). Social bumble bees meet the upper range of Michener’s description stating that primitively eusocial bees typically have!20 workers and no more than a few hundred (Michener 1974). These numbers contrast with “advanced eusocial” colonies of honey bees and many stingless bees that can be two orders of magnitude larger (Michener 1974, 2007); ant and termite societies can be even larger still (Wilson 1971). Nota- bly, however, other stingless bee or ant species may have
smaller colonies than bumble bees, indicating the colony size does not always separate “advanced” from “primitively” eusocial species (e.g., Wille 1983; Holldobler and Wilson 1990).
Multidimensional Patterns of Social Complexity in Other Social Insects
Our analyses show that social bumble bees, compared with some honey bees, stingless bees, and attine ants, in some traits are less socially complex (generally smaller colony size, less extreme reproductive division of labor between queens and workers) but in other traits are comparable or even more socially complex (similar or larger queen-worker body size ratio, similar or larger between-
worker morphological variation and specialization, larger colony size than some stingless bee and ant species, lower proportion of egg-laying workers than some stingless bees; fig. 4A). No matter how trait variables are rescaled or classifications repositioned, these taxa will not neatly fit into a classification system that assumes that all social traits evolve in synchrony and in which one taxon is more socially complex than another in all traits. The literature suggests that a multidimensional mosaic
combination of social traits is not unique to comparative studies within the Apidae. Examples are implied in An- derson and McShea’s (2001) classification of social complexity among ants, in which they categorized some species as having an overall higher level of social complexity than others on the basis of such factors as greater polymorphism, complex division of labor, and large colony size. One such
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Figure 3: Log10 coefficient of variation of worker body size in selected social insect genera. Bumble bees (red) are compared with 12 attine ants (black), 16 stingless bees (blue), and the honey bee Apis mellifera (green). Each point represents the coefficient of variation for a single species of the genus indicated on the X-axis (using the sample-size-weighted mean of study populations). Workers in each case included both in-nest and foraging workers. The Bombus terrestris data represent more than 6,000 workers from three studies (Cumber 1949; Goulson et al. 2002; Holland et al. 2020) and are highlighted with a black outline. Additional Bombus data (five more species) are from Cumber (1949) and Couvillon et al. (2010). Attine ant data and methods are from Ferguson-Gow et al. (2014). Stingless bee data are from Waddington et al. (1986) and Grüter et al. (2017). A phylogeny is shown to highlight relationships. Additional details on our methods are provided in the appendix.
example is the genus Cataglyphis, which they classify as having a lower level of social complexity because of its au- tonomous individuals and a lack of complex recruitment behavior in foraging but which has a larger colony size (es-
timated at 5,000) than many species they classify as more socially complex. The inverse is true for another species, Acromyrmex landoli, which they classify as having a higher level of social complexity because of fungus farming and
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Figure 4: Possible strategies for using quantitative multidimensional approaches for social complexity. We used real data in five social traits from six species of bees and ants. A, Separately comparing social traits across all six species. Colony size p number of workers at peak colony size; colony longevity p estimated lifespan of colony; reproductive skew p the proportion of males produced by the queen/ foundress in queenright colonies; queen-worker dimorphism p mean queen size/mean worker size; worker size variation p coefficient of variation in worker size. Log10 values are used for worker size variation and colony size. All values are rescaled so that the minimum and maximum across species are 0 and 1, respectively. Each symbol represents a different species, as shown at the bottom of B and C. The social complexity rank of the species differs for each measured social trait. B, C, Example of combining the traits in A into a single social complexity index, with traits weighted equally and rescaled separately for ants (B) and for bees (C). Illustrations are by Guy Bloch. Additional details on our methods are provided in the appendix.
worker polymorphism but which has a colony size of only about 1,000 workers. Consistent with this evidence, some studies with ants have failed to find any relationship between colony size and worker reproduction (Hammond and Keller 2004; Helantera and Sundstrom 2007), despite both being considered important measures of social complexity. In vespine wasps, worker-queen differentiation is restricted, since queens establish nests alone and workers can lay eggs (Evans and West-Eberhard 1973), but colony sizes can be very large, including the production of nearly 10,000 larvae in Vespula colonies (Donovan et al. 1992). By contrast, the paper wasp Ropalidia ignobilis forms small colonies of 100 or fewer adults and yet has female castes differing in size, wing length, coloration, and allometric relationships among body parts (Wenzel 1992). Lower termites live in complex societies but still show little, if any, brood care, which is one of the defining characters of eusociality. This lack of brood care probably relates to their wood-dwelling lifestyle (Korb et al. 2012). The multidimensional model of social evolution is also
congruent with findings of substantial variation in molecular mechanisms regulating social traits in different taxa, even within the same lineages (Sumner 2014; Shell and Rehan 2018). For example, there is evidence that various bee species differ in whether queen-biased genes or worker-biased genes undergo higher levels of selection (Harpur et al. 2017) and in the microRNAs associated with caste determination (Collins et al. 2017), while some caste-related genes in wasps also appear to be taxon specific (Ferreira et al. 2013). In other studies, a mixture of shared and lineage-specific pathways and genes are associated with social regulation across taxa (e.g., Woodard et al. 2011; Berens et al. 2015; Kapheim et al. 2015;Warner et al. 2019), suggesting that it may be fruitful to test correlations of these patterns with different components of social complexity rather than with the common qualitative stages along the social ladder. To test whether these correlations hold over broad taxa, such comparisons should also be phylogenetically corrected to control for pseudo- replication of clades.
A New Approach for Comparative Studies of Social Complexity
A Need to Move from Stepwise Qualitative Definitions to Quantitative Multidimensional Approaches
The “-omic” era presents an unprecedented opportunity to study social evolution in molecular terms as a wealth of new studies using large amounts of data become available (e.g., transcriptomics, genomics, proteomics, and epigenomics). Many of these studies rely on the comparative approach in which behavioral, physiological, or mo-
lecular features are compared for species differing in their level of social complexity. As illustrated above, the commonly used linear stepwise qualitative classification suffers from several important limitations. First, there is inconsistency in the way different studies label qualitatively defined levels of social complexity for the same taxon (table 1). Sec- ond, much of this classification is very crude and limits the resolution of the analyses. For example, small Halicitinae, Euglossini, and Xylocopinae societies composed of few individuals are frequently placed at the same level of social complexity as bumble bee societies numbering several hundred individual workers and showing substantial caste and between-worker variability. Similarly, ant societies showing orders of magnitude variability in colony size and consider- able variation in the degree of queen-worker and worker- worker differentiation are all classified as having the same level of sociality (e.g., “advanced eusocial”). Third, social complexity is commonly treated as a single trajectory passing through similar stages that bundles multiple social traits together, but in reality these traits are not always tightly correlated (fig. 4A). There is currently no convincing theoretical or empirical support for the notion that social complexity evolves along the same narrow restrictive stepwise trajectory in different social lineages (Linksvayer and John- son 2019). Fourth, low social complexity in one or more traits should be seen as a successful evolutionary strategy (adaptation) rather than a transitional or “primitive” stage representing a low rung in the ladder of social evolution. Fifth, the current approach may advocate focus on species that neatly fit the common classifications, potentially ob- scuring important natural variation among species. For some studies, such as those specifically focusing on
a “point of no return” to eusociality (e.g., Holldobler and Wilson1990; Boomsma2009), on the initial transition from solitary to social life, or on species differing greatly in several social complexity components, using broad qualitative classifications may be useful. Nonetheless, we argue that for many studies, particularly those using molecular and physiological variables, it will be more fruitful to measure social complexity on a trait-by-trait basis. The logic is that molecular, developmental, and physiological processes affect specific organismal traits, such as behavior, communication systems (e.g., pheromonal or odorant receptor repertoire), body size, morphology, or reproductive potential. Many of these traits underlie key components of social complexity, and it is important to know whether they are regulated by similar or different processes across different lineages of social insects and how this regulation is modified through evolution. For example, the developmental processes that determine body size underlie the variability between queens and workers and among workers. The number of enzymes that are involved in pheromone biosynthesis and the number of odorant receptors may determine communication
complexity. Likewise, the molecular processes that control ovary size and oogenesis influence fertility and the degree of reproductive skew. Therefore, molecular processes such as the expression of genes in certain pathways or the degree of epigenetic methylation are likely to show clearer associations, within and across taxa, with such quantitative components of social complexity thanwith the commonbroadly defined qualitative states that may stem from diverse com- binationsof social traits. Indeed, studies that have attempted to link molecular processes to the commonly used levels of social complexity revealed weak associations at best (e.g., Woodard et al. 2011; Kapheim et al. 2015; Glastad et al. 2017).
Can Components of Social Complexity Be Reliably Quantified?
Previous studies have already compiled and compared commonly used quantitative traits that are components of social complexity (Michener 1974; Anderson and McShea 2001; Gardner et al. 2007; Aviles and Harwood 2012). These include reproductive skew, variation in body size, colony size, behavioral repertoires, behavioral specialization (i.e., division of labor), the number of genes differentially expressed between queen- and worker- destined larvae, the richness of communication signals (e.g., pheromones, antennation, trophallaxis, “dances” etc.), the fraction of the life cycle that individuals remain in their social group, and the efficacy of nest homeostasis (e.g., Sherman et al. 1995; Gorelick and Bertram 2007; Avilés and Harwood 2012; Sumner et al. 2018). However, to realize the full potential of the multidimensional approach it is important to develop quantitative and stan- dardized measures for additional components of social complexity, such as the degree of morphological differentiation other than body size (including allometry and other morphological differences among workers and between queens and workers).
What Are the Best Quantitative Measures of Social Complexity?
The selection of the most appropriate indices of social complexity—and in some cases also the best ways to quantify them—is not always easy andmay differ between lineages of social insects. There is good agreement and much literature supporting the importance of several commonly used metrics. For example, the degree of reproductive skew is considered in many studies to be particularly important for determining social complexity overall (Sher- man et al. 1995; Crespi and Yanega 1995; Hughes et al. 2008; Boomsma 2009; Boomsma andGawne 2018). Similar arguments have been made for the causal importance of
colony size, termed the “size-complexity hypothesis” (Bon- ner and Brainerd 2004; Bourke 2011). There is less agreement concerning other metrics. For example, some researchers may argue that size variation among workers is not a good proxy of social complexity if it is not associated with discrete (polymorphic) size distribution or that morphological/allometric differences between queens and workers should receive more weight than mere differences in body size or physiology. Likewise, variation in behavioral repertoire (as seen in honey bees) may be seen as a better proxy for social complexity than morphological variability (as seen in some ants, termites, and bumble bees). Deciding between these conflicting opinions requires good understanding of the social biology, natural history, and life history of the studied species. The value of different traits probably differs between lineages of social insects. Thus, further development of our proposed approaches requires additional discussion that is based on a deep understanding of the natural history and life history of the different social lineages. There is also an obvious need for more empirical and theoretical studies that are beyond the scope of the current article.
How to Use Quantitative Multidimensional Approaches?
As an illustrative example of a quantitative multidimensional approach, we have used data available from the literature to compare the relative levels of five commonly used quantitative components of social complexity in six species of bees and ants (fig. 4A; see the appendix for details). This approach reveals the uncorrelated nature of social traits, showing that the order of relative complexity between species is different for each trait, which em- phasizes the multidimensional pattern and highlights the need to take multiple quantitative traits into account. To this end, we suggest two approaches for using quan-
titative multidimensional data on social complexity to un- derstand the causes and consequences of social evolution. The first approach, which explicitly recognizes the multidimensional pattern of social complexity, is to separately focus on individual components of social complexity. In the ideal case, this involves comparing species that vary in one focal social trait but not in others (e.g., where colony size varies but queen-worker differentiation is comparable), which allows the importance of the focal trait to be assessed empirically. A clear separation of social complexity components facilitates the recognition of alternative preadapta- tions ormodifications thatmay be important for social evolution. For example, the annual colony life histories of some bees andwasps restrict increases in colony size andmay also restrict queen-worker differentiation (because the queen needs to care for the brood and forage effectively during colony foundation), but they do not appear to constrain the
complexity of other social traits, such as between-worker differentiation (as seen in bumble bees). In addition, it will also help in the recognition of different selection pressures in different lineages. For example, most bumble bee species are principally adapted to cold climates, whereas stingless bees and honey bees are mostly tropical. This may account for some of the differences they show in social traits, such as queen-worker variation, which may be related to diapause in bumble bees but not in honey bees or stingless bees. The same logic has been used to assess the effect of abiotic factors (variation in temperature and precipitation) on colony size, queen-worker dimorphism, and worker size variation in attine ants (Fergusson-Gow et al. 2014). This approach, for example, sets the stage for asking questions such as whether similar processes (e.g., molecular) are associated with colony size in meliponine stingless bees and attine ants or whether the degree of caste differentiation is regulated by similar molecular pathways in bees and wasps. This approach will be particularly powerful with molecular data, such as the level of DNA methylation or differential gene expression. Rather than correlating the molecular variableswith qualitatively defined stagesof social complexity (e.g., Kapheim et al. 2015; Glastad et al. 2017; Sumner 2018), the same data could be separately correlated to each relevant component of social complexity (e.g., reproductive skew, queen-worker size variation, colony size). A second approach is to combine multiple components
of social complexity into a single quantitative measure of social complexity and use this multidimensional index to identify new features and processes correlated with social complexity. This would be similar to the approach of previous comparative studies (see the introduction) but using a quantitative and less ambiguous measure of social complexity. An important advantage of this approach over qualitatively defined levels of sociality is that it allows finer analyses and distinctions between species that are currently bundled within the same level of sociality. A first move in this direction was suggested by Avilés and Har- wood (2012), who combinedmultiple quantitative indices of social complexity into a single value to compare social spiders. We used a similar approach to demonstrate another example using several species of bees and ants (see the appendix for details on our methods). As in Avilés andHarwood (2012), we assigned the sameweight to each of the social complexity components in figure 4A to gen- erate a social complexity metric (fig. 4B, 4C). Such overall social complexity metrics could use a complement of different social traits that are tailored to the study in question but would be most reliable if they explain as much variation as possible. Our example demonstrates an important advantage of this approach, which is the ability to separate the level of social complexity for species that are commonly considered to have the same level of social com-
plexity (e.g., under some classifications, all of these species except Euglossa viridissima would be considered hypersocial or superorganismal; table 1). Another advantage is for lineages, such as spiders, in which there are no accepted classifications for the overall level of social complexity (Avilés and Harwood 2012). However, studies using this approach should acknowledge the intrinsic limitations of assuming a linear stepwise model that we discuss above aswell as the need to carefully consider theweighting of different social traits according to the biology and natural history of the studied lineages. Our example in figure 4 demonstrates some of these difficulties—for example, by showing bumble bees as more similar to stingless bees and honey bees than is commonly accepted. We propose that this approach is especially powerful for comparing species within the same lineage (e.g., Attini, Halictinae, Vespidae) by allowing for a finer resolution that can be later used to identifymolecular or other processes that have been important in the evolutionof social complexity. For this reason,we separately compared our basic “social complexity” metric for ants and bees as a simple form of phylogenetic control. Using this metric to compare bees, in which all five traits were equally weighted, Apis mellifera, Bombus terrestris, andMelipona fasciata all showed very similar levels of complexity, with E. viridissima having a relative complexity of zero.
Conclusions and Future Perspectives
The remarkable increase in the number of species for which “-omics” data are available, coupled with improved phylogenies and steadily growing knowledge on the social biology of species showing diverse forms of social lifestyles, calls for new methods and strategies for studies of the evolution of social complexity.We suggest thatmultidimensional arrays of quantitative metrics more precisely describe the diverse forms of social complexity than the broad and inconsistent qualitative classifications that are currently used. Moving the field into a quantitativemultidimensional approachwill enablefiner-scale analyseswithin lineages and a better comparison of processes influencing or influenced by different components of social complexity across lineages, recogniz- ing that social evolution is not always strictly linear and stepwise. The proposed approach is particularly appropriate for linking molecular or physiological processes, pre- adaptations, selection pressures, and regulatory processes to specific phenotypic social traits, such as colony size, reproductive skew, or the degree of caste differentiation. The various quantitative measures of complexity can potentially be further combined into unifiedmultidimensional indices or models for overall social complexity. Although we believe that some previous and current comparative studies can already significantly benefit from relating
molecular (or other) data to individual indices of social complexity (fig. 4A), we advocate that additional theoretical and empirical work is needed in order to realize the full potential of quantitative multidimensional approaches. Some of the most pressing challenges are to identify the most important components of social complexity and find the best ways to quantify them.Developing social complexity indices, while potentially useful, is challenging because it requires deciding not only which traits to include but also how much weight to assign to each social trait. These de- cisions will require deep knowledge on the biology, behavior, natural history, and life history of the studied species and will likely depend on the specific lineages and questions in focus. The value of a quantitative multidimensional approach will increase as more data are collected for more species along gradients of social complexity. This will allow for better resolution in comparative studies and for better understanding of the interactions between different components of complexity.We hope that our contribution will encourage additional researchers to contendwith these challenges.
Acknowledgments
We thank Jenny Jandt and Igor Medici de Mattos for sharing unpublished data used for the analyses. We also thank Daniel Bolnick, Timothy Linksvayer, and two anon- ymous reviewers for detailed and helpful comments on the manuscript. Financial support was provided by grants from the US-Israel Binational Agricultural Research and Development Fund (BARD; project IS-4418-11 and IS- 5077-18) and the US-Israel Binational Science Founda- tion (BSF) to G.B. as well as a Lady Davis Postdoctoral Fellowship to J.G.H. Finally, we thank Eamonn Mallon’s group for hosting J.G.H. during much of the development of this article.
Statement of Authorship
The ideas in this piece were conceived and developed by J.G.H. and G.B., data gathering and analyses were performed by J.G.H., and the manuscript was written by J.G.H. and G.B.
Data and Code Availability
Data in support of this publication have been deposited in the Dryad Digital Repository (https://doi.org/10.5061 /dryad.x3ffbg7g6; Holland and Bloch 2020).
APPENDIX
Methods
To quantify bumble bee queen-worker size differentiation, we used data from Cumber (1949) and new data.
In Cumber’s publication, wing lengths of females (n p 944) present in nine nests of six species were provided without distinguishing between workers and queens. However, all colonies were stated to contain queens and the size distribution was clearly bimodal in each colony, which we assumed to represent worker and queen modes. In the pollen-storing species (Bombus lapidarius, Bombus lucorum, Bombus terrestris, Bombus pratorum), there was clear separation of worker and queen distributions. For the pocket-making species (Bombus agrorum, Bombus hortorum), where queen-worker size distinction is less obvious, the sizemeasurement with theminimum amount of records between the worker and queen modes (a clear trough in all three colonies) was assumed to consist of workers and queens equally, with all values smaller and larger than this assumed to be workers and queens, respectively. Additional size data using thorax width were taken from all emerging workers (n p 434) and gynes (n p 26) in five B. terrestris colonies kept enclosed in standard laboratory conditions from incipient colonies to queen death (I. Medici de Mattos and G. Bloch, unpublished data). A B. terrestris value was calculated from both studies using ameanweighted by sample size.Queenworker size ratio (queen mean size/worker mean size) was calculated for comparison with stingless bee data from Toth et al. (2004) and attine ant data from Fergusson-Gow et al. (2014). Additionally, a value for Apis mellifera was calculated using thorax size and taking a mean of values from European and African strains in DeGrandi-Hoffman et al. (2004). To statistically compare bumble bees to stingless bees and (separately) to attine ants, we used species-level Wilcoxon rank sum tests (given the nonnormality of the data). For comparing bumble bees and A. mellifera (single value only), aWilcoxon rank sum test does not provide sufficient power to allow such comparisons; thus, we assumed a normal distribution and equal variances in a t-test.
To quantify bumble bee among-worker size differentiation, we used the following: B. terrestris data obtained from (i) wing marginal cell length of all workers (n p 1,832) produced by nine freely foraging colonies over themajority of colony growth (Holland et al. 2020), (ii) thorax width of all workers (n p 4,492) found in28 freely foraging colonies around the peakof colony growth (Goulson et al. 2002), and (iii) wing length of workers (n p 139) found in wild colonies (Cumber 1949). Bombus impatiens data were obtained from thorax width of all workers (n p 1,133) produced by 12 enclosed colonies over the later stages of colony growth (Couvillon et al. 2010; J. Jandt, personal communication). Other Bombus spp. data were obtained from wing lengths of workers (n p 570) found in seven wild colonies of five species (Cumber 1949). For the data from Cumber’s (1949) study, workers were determined as described above. The coefficient of variation, 100 # (worker head width
standard deviation/worker head width mean), was calculated for comparison with attine ant data from the meta- study of Fergusson Gow et al. (2014). In addition, stingless bee data from Waddington et al. (1986) and Grüter et al. (2017) were also used to calculate coefficients of variation (there was no overlap in the species covered by each study). A value for A. mellifera was obtained from Roulston and Cane (2000). Although size in bumble bees was measured as thoraxwidth orwingmarginal cell length,we assume this to be comparable to head width (which was used for ants and stingless bees) because both of these measures are strongly correlated with head width across the full size range of B. terrestris workers (Pearson correlation, thorax width-head width, r p 0:92, R2 p 0:85; wing cell length- head width, r p 0:95, R2 p 0:90; n p 69; J. G. Holland, unpublished data). To statistically compare bumble bee species to stingless bees and (separately) to attine ants, we used species-level Wilcoxon rank sum tests (given the nonnormality of the data). As with the queen-worker comparison, for comparing bumble bees and A. mellifera (single value only), a Wilcoxon rank sum test does not provide sufficient power to allow such comparisons; thus, we assumed a normal distribution and equal variances in a t-test.
We produced a genus-level phylogenetic tree for graph- ical comparison using relationships from the following studies: within Attini, Fergusson-Gow et al. (2014); within Meliponini, Rasmussen and Cameron (2009); amongMeli- ponini, Bombini, andApini, Cardinal andDanforth (2011); and between Apidae and Formicidae, numerous studies (e.g., Johnson et al. 2013). The trees were produced, without differences in branch length, using TreeGraph2.
As an example of comparing social complexity between species, we chose six species (A. mellifera, Atta sexdens, B. terrestris, Euglossa viridissima, Melipona fasciata, and Trachymyrmex septentrionalis) for which quantitative data were available in five social traits. The traits were quantified as follows: (1) worker size variationp log10 coefficient of variation in worker head width (A. melliferap Roulston and Cane 2000; A. sexdens, T. septentrionalisp Fergusson-Gow et al. 2014; B. terrestris p see above; M. fasciata p Waddington et al. 1986; E. viridissima p variation among females, Eltz et al. 2011); (2) queen-worker body size dimorphism p mean queen size/mean worker size (A. mellifera p DeGrandi-Hoffman et al. 2004, see above; A. sexdens, T. septentrionalis p Fergusson-Gow et al. 2014;B. terrestrisp see above;E. viridissimap equal size assumed since all females can mate and disperse; M. fasciata p Toth et al. 2004); (3) reproductive skew p the proportion of adult males that are queen produced rather than worker produced in queenright colonies (A. mellifera, B. terrestris, Trachymyrmex spp. p Wenseleers and Ratneiks 2006; A. sexdensp 1 implied given no viable
worker-laid eggs in Dijkstra et al. 2005; E. viridissima p the mean proportion of eggs laid by dominant mother, Cocom Pech 2008;M. fasciatap Toth et al. 2004); (4) colony size p log10 number of workers at peak colony size (A. mellifera p approximated at 10,000 workers; A. sexdens, T. septentrionalis p Fergusson-Gow et al. 2014; B. terrestris p approximated at 200 workers; E. viridissima p Cocom Pech 2008; M. fasciata p Toth et al. 2004); and (5) colony longevity p best estimate of lifespan in colonies surviving foundation (A. melliferapmean of feral colonies, Seeley 1978; A. sexdensp Keller 1998; B. terrestrisp approximated at 0.5 years; E. viridissima p longevity of adults, Skov and Wiley 2005; M. fasciata p Roubik 1983; T. septentrionalisp approximated at 2 years, on the basis of comments in Beshers and Traniello 1996 and Weber 1966). For plotting, traits were rescaled across species so that the minimum was set to 0 and the maximum was set to 1. This rescaling was performed both for all species together (presented in fig. 4A) and for ants and bees separately (fig. 4B, 4C). To produce the combined indices (fig. 4B, 4C), unweighted means of the six scaled trait values were then calculated. This is not an exclusive list of traits that could be quantified as components of social complexity, and several of these traits could be quantified by alternative or complementary methods. These comparisons are obviously limited by the amount of comparable data available.
Literature Cited
Alford, D. V. 1975. Bumblebees. Davis-Poynter, London. Amador-Vargas, S., W. Gronenberg, W. T. Wcislo, and U. Mueller.
2015. Specialization and group size: brain and behavioural cor- relates of colony size in ants lacking morphological castes. Pro- ceedings of the Royal Society B 282:20142502. https://doi.org /10.1098/rspb.2014.2502.
Amsalem, E., D. A. Galbraith, J. Cnaani, P. E. A. Teal, and C. M. Grozinger. 2015. Conservation and modification of genetic and physiological toolkits underpinning diapause in bumble bee queens. Molecular Ecology 24:5596–5615. https://doi.org/10.1111 /mec.13410.
Anderson, C., and D. W. McShea. 2001. Individual versus social complexity, with particular reference to ant colonies. Biological Reviews 76:211–237. https://doi.org/10.1017/s1464793101005656.
Andrade, A. C. R., E. A. Miranda, M. A. Del Lama, and F. S. Nascimento. 2016. Reproductive concessions between related and unrelated members promote eusociality in bees. Scientific Reports 6:26635. https://doi.org/10.1038/srep26635.
Avilés, L., and G. Harwood. 2012. A quantitative index of sociality and its application to group-living spiders and other social organisms. Ethology 118:1219–1229. https://doi.org/10.1111/eth.12028.
Batra, S. 1966. Nests and social behavior of halictine bees of India (Hymenoptera: Halicidae). Indian Journal of Entomology 28:375– 393.
———. 1977. Bees of India (Apoidea), their behavior, manage- ment, and a key to the genera. Oriental Insects 11:289–324. https:// doi.org/10.1080/00305316.1977.10433811.
Berens, A. J., J. H. Hunt, and A. L. Toth. 2015. Comparative transcriptomics of convergent evolution: different genes but con- served pathways underlie caste phenotypes across lineages of eusocial insects. Molecular Biology and Evolution 32:690–703. https://doi.org/10.1093/molbev/msu330.
Beshers, S. N., and J. F. A. Traniello. 1996. Polyethism and the adaptiveness of worker size variation in the attine ant Trachy- myrmex septentrionalis. Journal of Insect Behavior 9:61–83. https://doi.org/10.1007/bf02213724.
Bloch, G., B. W. Borst, Z. Y. Huang, G. E. Robinson, and A. Hefetz. 1996. Effects of social conditions on juvenile hormone mediated reproductive development in Bombus terrestris workers. Physio- logical Entomology 21:257–267. https://doi.org/10.1111/j.1365-3032 .1996.tb00863.x.
Bloch, G., and A. Hefetz. 1999. Regulation of reproduction by dominant workers in bumblebee (Bombus terrestris) queenright colonies. Behavioral Ecology and Sociobiology 45:125–135. https:// doi.org/10.1007/s002650050546.
Bonner, J. T., and E. Brainerd. 2004. Perspective: the size-complexity rule. Evolution 58:1883–1890. https://doi.org/10.1554/04-146.
Boomsma, J. J. 2009. Lifetime monogamy and the evolution of eusociality. Philosophical Transactions of the Royal Society B 364:3191–3207. https://doi.org/10.1098/rstb.2009.0101.
Boomsma, J. J., and R. Gawne. 2018. Superorganismality and caste differentiation as points of no return: how the major evolutionary transitions were lost in translation. Biological Reviews 93:28– 54. https://doi.org/10.1111/brv.12330.
Bortolotti, L., M. J. Duchateau, and G. Sbrenna. 2001. Effect of juvenile hormone on caste determination and colony processes in the bumblebee Bombus terrestris. Entomologia Experimentalis et Applicata 101:143–158. https://doi.org/10.1046/j.1570-7458.2001 .00899.x
Bossert, S., E. A. Murray, E. A. B. Almeida, S. G. Brady, B. B. Blaimer, and B. N. Danforth. 2019. Combining transcriptomes and ultraconserved elements to illuminate the phylogeny of Apidae. Molecular Phylogenetics and Evolution 130:121–131. https://doi .org/10.1016/j.ympev.2018.10.012.
Bourke, A. F. G. 1999. Colony size, social complexity and reproductive conflict in social insects. Journal of Evolutionary Biology 12:245–257.
———. 2011. Principles of social evolution. Oxford University Press, Oxford.
Brown, M. J. F., R. Schmid-Hempel, and P. Schmid-Hempel. 2003. Queen-controlled sex ratios and worker reproduction in the bumble bee Bombus hypnorum, as revealed by microsatellites. Molec- ular Ecology 12:1599–1605. https://doi.org/10.1046/j.1365-294X.2003 .01840.x.
Cardinal, S., and B. N. Danforth. 2011. The antiquity and evolutionary history of social behavior in Bees. PLoS ONE 6:e21086. https://doi.org/e21086 10.1371/journal.pone.0021086.
Chole, H., S. H. Woodard, and G. Bloch. 2019. Body size variation in bees: regulation, mechanisms, and relationship to social organization. Current Opinion in Insect Science 35:77–87. https:// doi.org/0.1016/j.cois.2019.07.006.
Cnaani, J., G. E. Robinson, G. Bloch, D. Borst, and A. Hefetz. 2000. The effect of queen-worker conflict on caste determination in the bumblebee Bombus terrestris. Behavioral Ecology and Socio- biology 47:346–352. https://doi.org/10.1007/s002650050675.
Cocom Pech, M. E., W. D. May-Itza, L. A. M. Medina, and J. J. G. Quezada-Euan. 2008. Sociality in Euglossa (Euglossa) viridissima
Friese (Hymenoptera, Apidae, Euglossini). Insectes Sociaux 55:428–433. https://doi.org/10.1007/s00040-008-1023-4.
Collins, D. H., I. Mohorianu, M. Beckers, V. Moulton, T. Dalmay, and A. F. G. Bourke. 2017. MicroRNAs associated with caste determination and differentiation in a primitively eusocial insect. Scientific Reports 7:45674. https://doi.org/10.1038/srep45674.
Couvillon, M. J., J. M. Jandt, N. Duong, and A. Dornhaus. 2010. Ontogeny of worker body size distribution in bumble bee (Bom- bus impatiens) colonies. Ecological Entomology 35:424–435. https://doi.org/10.1111/j.1365-2311.2010.01198.x.
Crespi, B. J., and D. Yanega. 1995. The definition of eusociality. Behavioral Ecology 6:109–115. https://doi.org/10.1093/beheco /6.1.109.
Cumber, R. A. 1949. The biology of humble-bees, with special reference to the production of the worker caste. Transactions of the Royal Entomological Society of London 100:1–45. https:// doi.org/10.1111/j.1365-2311.1949.tb01420.x.
DeGrandi-Hoffman, G., M. Chambers, J. E. Hooper, and S. S. Schneider. 2004. Description of an intermorph between a worker and queen in African honey beesApis mellifera scutellata (Hyme- noptera: Apidae). Annals of the Entomological Society of Amer- ica 97:1299–1305. https://doi.org/10.1603/0013-8746(2004)097 [1299:doaiba]2.0.co;2.
Dijkstra, M. B., D. R. Nash, and J. J. Boomsma. 2005. Self-restraint and sterility in workers of Acromyrmex and Atta leafcutter ants. Insectes Sociaux 52:67–76. https://doi.org/10.1007/s00040-004 -0775-8.
Donovan, B., A. Howie, and N. Schroeder. 1992. Comparative characteristics of nests of Vespula germanica (F.) and Vespula vulgaris (L.) (Hymenoptera: Vespinae) from Christchurch City, New Zealand. New Zealand Journal of Zoology 19:61–71. https:// doi.org/10.1080/03014223.1992.10423252.
Eltz, T., F. Fritzsch, J. R. Pech, Y. Zimmermann, S. R. Ramirez, J. J. G. Quezada-Euan, and B. Bembe. 2011. Characterization of the orchid bee Euglossa viridissima (Apidae: Euglossini) and a novel cryptic sibling species, by morphological, chemical, and genetic characters. Zoological Journal of the Linnean Society 163:1064– 1076. https://doi.org/10.1111/j.1096-3642.2011.00740.x.
Evans, H. E., and M. J. West-Eberhard. 1973. The wasps. David & Charles, Newton Abbot.
Ferguson-Gow, H., S. Sumner, A. F. G. Bourke, and K. E. Jones. 2014. Colony size predicts division of labour in attine ants. Proceedings of the Royal Society B 281:20141411. https://doi.org/10.1098/rspb .2014.1411.
Ferreira, P. G., S. Patalano, R. Chauhan, R. Ffrench-Constant, T. Gabaldón, R. Guigó, and S. Sumner. 2013. Transcriptome analyses of primitively eusocial wasps reveal novel insights into the evolution of sociality and the origin of alternative phenotypes. Genome Biology 14:1–15. https://doi.org/10.1186/gb-2013-14-2-r20.
Fischman, B. J., S. H. Woodard, and G. E. Robinson. 2011. Molec- ular evolutionary analyses of insect societies. Proceedings of the National Academy of Sciences of the USA 108:10847–10854. https://doi.org/10.1073/pnas.1100301108.
Gardner, K. E., R. L. Foster, and S. O’Donnell. 2007. Experimental analysis of worker division of labor in bumblebee nest thermo- regulation (Bombus huntii, Hymenoptera: Apidae). Behavioral Ecology and Sociobiology 61:783–792. https://doi.org/10.1007 /s00265-006-0309-7.
Glastad, K. M., S. V. Arsenault, K. L. Vertacnik, S. M. Geib, S. Kay, B. N. Danforth, S. M. Rehan, C. R. Linnen, S. D. Kocher, and
B. G. Hunt. 2017. Variation in DNA methylation is not consistently reflected by sociality in Hymenoptera. Genome Biology and Evolution 9:1687–1698. https://doi.org/10.1093/gbe/evx128.
Gorelick, R., and S. M. Bertram. 2007. Quantifying division of labor: borrowing tools from sociology, sociobiology, information theory, landscape ecology, and biogeography. Insectes Sociaux 54:105–112. https://doi.org/10.1007/s00040-007-0923-z.
Goulson, D. 2010. Bumblebees: behaviour, ecology and evolution. Oxford University Press, Oxford.
Goulson, D., J. Peat, J. C. Stout, J. Tucker, B. Darvill, L. C. Derwent, and W. O. H. Hughes. 2002. Can alloethism in workers of the bumblebee, Bombus terrestris, be explained in terms of foraging efficiency? Animal Behaviour 64:123–130. https://doi.org/10.1006/anbe.2002.3041.
Grüter, C., F. H. I. D. Segers, C. Menezes, A. Vollet-Neto, T. Fal- cón, L. von Zuben, M. M. G. Bitondi, F. S. Nascimento, and E. A. B. Almeida. 2017. Repeated evolution of soldier sub-castes suggests parasitism drives social complexity in stingless bees. Nature Communications 8:4. https://doi.org/10.1038/s41467-016 -0012-y.
Hamilton, W. D. 1964. Genetical evolution of social behaviour. I, II. Journal of Theoretical Biology 7:1–16, 17–52. https://doi.org /10.1016/0022-5193(64)90039-6.
Hammond, R. L., and L. Keller. 2004. Conflict over male parentage in social insects. PLoS Biology 2:e248. https://doi.org/10.1371 /journal.pbio.0020248.
Harpur, B. A., A. Dey, J. R. Albert, N. Patel, H. M. Hines, M. Hasselmann, L. Packer, and A. Zayed. 2017. Queens and workers contribute differently to adaptive evolution in bumble bees and honey bees. Genome Biology and Evolution 9:2395–2402. https:// doi.org/10.1093/gbe/evx182.
Helantera, H., and L. Sundstrom. 2007. Worker policing and nest mate recognition in the ant Formica fusca. Behavioral Ecology and Sociobiology 61:1143–1149. https://doi.org/10.1007/s00265-006 -0327-5.
Holbrook, C. T., P. M. Barden, and J. H. Fewell. 2011. Division of labor increases with colony size in the harvester ant Pogono- myrmex californicus. Behavioral Ecology 22:960–966. https:// doi.org/10.1093/beheco/arr075.
Holland, J. G., and G. Bloch. 2020. Data from: The complexity of social complexity: a quantitative multidimensional approach for studies of social organization. American Naturalist, Dryad Dig- ital Repository, https://doi.org/10.5061/dryad.x3ffbg7g6.
Holland, J. G., S. Nakayama, M. Porfiri, O. Nov, and G. Bloch. 2020. Is diversity in worker body size important for the performance of bumble bee colonies? bioRxiv, https://doi.org/10.1101 /2020.05.06.079525.
Holldobler, B., and E. O. Wilson. 1990. The ants. Harvard Univer- sity Press, Cambridge, MA.
Hughes, W. O. H., B. P. Oldroyd, M. Beekman, and F. L. W. Ratnieks. 2008. Ancestral monogamy shows kin selection is key to the evolution of eusociality. Science 230:1213–1216. https:// doi.org/10.1126/science.1156108.
Jandt, J. M., and A. Toth. 2015. Chapter three—physiological and genomic mechanisms of social organization in wasps (family: Vespidae). Advances in Insect Physiology 48:95–130. https:// doi.org/10.1016/bs.aiip.2015.01.003.
Johnson, B., M. L. Boroweic, J. C. Chiu, E. K. Lee, J. Atallah, and P. S. Ward. 2013. Phylogenomics resolves evolutionary relationships among ants, bees, and wasps. Current Biology 23:2058–2062.
Kapheim, K. M., H. Pan, C. Li, S. L. Salzberg, D. Puiu, T. Magoc, H. M. Robertson, M. E. Hudson, et al. 2015. Genomic signatures of evolutionary transitions from solitary to group living. Science 348:1139–1143. https://doi.org/10.1126/science.aaa4788.
Keller, L. 1998. Lifespan and colony characteristics in ants and termites. Insectes Sociaux 45:235–246. https://doi.org/10.1007 /s000400050084.
———. 1999. Levels of selection in evolution. Princeton Univer- sity Press, Princeton, NJ.
Kocher, S. D., L. Pellissier, C. Veller, J. Purcell, M. A. Nowak, M. Chapuisat, and N. E. Pierce. 2014. Transitions in social complexity along elevational gradients reveal a combined impact of season length and development time on social evolution. Proceedings of the Royal Society B 281:20140627. https://doi.org/10.1098 /rspb.2014.0627.
Korb, J., M. Buschmann, S. Schafberg, J. Liebig, and A. G. Bag- neres. 2012. Brood care and social evolution in termites. Pro- ceedings of the Royal Society B 279:2662–2671. https://doi.org /10.1098/rspb.2011.2639.
Kramer, B. H., and R. Schaible. 2013. Colony size explains the lifespan differences between queens and workers in eusocial Hy- menoptera. Biological Journal of the Linnean Society 109:710– 724. https://doi.org/10.1111/bij.12072.
Linksvayer, T. A., and B. R. Johnson. 2019. Re-thinking the social ladder approach for elucidating the evolution and molecular basis of insect societies. Current Opinion in Insect Science 34:123– 129. https://doi.org/10.1016/j.cois.2019.07.003.
Mares, S., L. Ash, and W. Gronenberg. 2005. Brain allometry in bumblebee and honey bee workers. Brain, Behavior and Evolu- tion 66:50–61. https://doi.org/10.1159/000085047.
Maynard Smith, J., and E. Szathmáry. 1995. The major transitions in evolution. Oxford University Press, Oxford.
McShea, D. W. 2000. Functional complexity in organisms: parts as proxies. Biology and Philosophy 15:641–668. https://doi.org /10.1023/A:1006695908715.
Michener, C. 1974. The social behavior of the bees. Belknap, Cambridge, MA.
———. 2007. The bees of the world. 2nd ed. Johns Hopkins Uni- versity Press, Baltimore.
Owen, R. E., and R. C. Plowright. 1982. Worker-queen conflict and male parentage in bumble bees. Behavioral Ecology and So- ciobiology 11:91–99. https://doi.org/10.1007/BF00300097.
Pouvreau, A. 1989. Contribution à l’étude du polyéthisme chez les bourdons, Bombus Latr. (Hymenoptera, Apidae). Apidologie 20:229– 244.
Prs-Jones, O. E., and S. A. Corbet. 2011. Bumblebees. 3rd ed. Pe- lagic, Exeter.
Rasmussen, C., and S. Cameron. 2009. Global stingless bee phylogeny supports ancient divergence, vicariance, and long dis- tance dispersal. Biological Journal of the Linnean Society 99:206– 232.
Rehan, S. M., R. Leys, and M. P. Schwarz. 2012. A mid-Cretaceous origin of sociality in xylocopine bees with only two origins of true worker castes indicates severe barriers to eusociality. PLoS ONE 7:e34690. https://doi.org/10.1371/journal.pone.0034690.
Rehan, S. M., and A. L. Toth. 2015. Climbing the social ladder: the molecular evolution of sociality. Trends in Ecology and Evolu- tion 30:426–433. https://doi.org/10.1016/j.tree.2015.05.004.
Richards, M. H. 2019. Social trait definitions influence evolutionary inferences: a phylogenetic approach to improving social
terminology for bees. Current Opinion in Insect Science 34:97– 104. https://doi.org/10.1016/j.cois.2019.04.006.
Röseler, P. F., and I. Röseler. 1986. Caste specific differences in fat- body glycogen-metabolism of the bumblebee, Bombus-terrestris. Insect Biochemistry 16:501–508. https://doi.org/10.1016/0020 -1790(86)90027-2.
Roubik, D. W. 1983. Nest and colony characteristics of stingless bees from Panamá (Hymenoptera: Apidae). Journal of the Kan- sas Entomological Society 56:327–355.
Roulston, T. A. H., and J. H. Cane. 2000. The effect of diet breadth and nesting ecology on body size variation in bees (Apiformes). Journal of the Kansas Entomological Society 73:129–142.
Rubenstein, D. R., C. A. Botero, and E. A. Lacey. 2016. Discrete but variable structure of animal societies leads to the false perception of a social continuum. Royal Society Open Science 3:160147. https://doi.org/10.1098/rsos.160147.
Seeley, T.D. 1978. Life history strategy of the honey bee,Apismellifera. Oecologia 32:109–118. https://doi.org/10.1007/bf00344695.
Shell, W. A., and S. M. Rehan. 2018. Behavioral and genetic mechanisms of social evolution: insights from incipiently and facultatively social bees. Apidologie 49:13–30. https://doi.org/10.1007 /s13592-017-0527-1.
Sherman, P. W., E. A. Lacey, H. K. Reeve, and L. Keller. 1995. Fo- rum: the eusociality continuum. Behavioral Ecology 6:102–108. https://doi.org/10.1093/beheco/6.1.102.
Skov, C., and J. Wiley. 2005. Establishment of the neotropical orchid bee Euglossa viridissima (Hymenoptera: Apidae) in Florida. Flor- ida Entomologist 88:225–227. https://doi.org/10.1653/0015-4040 (2005)088[0225:eotnob]2.0.co;2.
Spaethe, J., and A. Weidenmuller, 2002. Size variation and foraging rate in bumblebees (Bombus terrestris). Insectes Sociaux 49:142–146. https://doi.org/10.1007/s00040-002-8293-z.
Sumner, S. 2014. The importance of genomic novelty in social evolution. Molecular Ecology 23:26–28. https://doi.org/10.1111/mec .12580.
Sumner, S., E. Bell, and D. Taylor. 2018. A molecular concept of caste in insect societies. Current Opinion in Insect Science 25:42–50. https://doi.org/10.1016/j.cois.2017.11.010.
Szathmary, E. 2015. Towardmajor evolutionary transitions theory 2.0. Proceedings of the National Academy of Sciences of the USA 112:10104–10111. https://doi.org/10.1073/pnas.1421398112.
Takahashi, J., M. Itoh, I. Shimizu, and M. Ono. 2008. Male parentage and queen mating frequency in the bumblebee Bombus ignitus (Hy- menoptera: bombinae). Ecological Research 23:937–942. https:// doi.org/10.1007/s11284-007-0456-y.
Thomas, M. L., and M. A. Elgar. 2003. Colony size affects division of labour in the ponerine ant Rhytidoponera metallica. Naturwis- senschaften 90:88–92. https://doi.org/10.1007/s00114-002-0396-x.
Toth, A. L., S. Sumner, and R. L. Jeanne. 2016. Patterns of longevity across a sociality gradient in vespid wasps. Current Opinion in Insect Science 16:28–35. https://doi.org/10.1016/j.cois.2016.05.006.
Toth, E., D. C. Queller, A. Dollin, and J. E. Strassmann, 2004. Con- flict over male parentage in stingless bees. Insectes Sociaux 51:1–11. https://doi.org/10.1007/s00040-003-0707-z.
Trible, W., and D. J. Kronauer. 2017. Caste development and evolution in ants: it’s all about size. Journal of Experimental Biology 220:53–62. https://doi.org/10.1242/jeb.145292.
Valentine, J. W., A. G. Collins, and C. P. Meyer. 1994. Morpholog- ical complexity increase in metazoans. Paleobiology 20:131–142. https://doi.org/10.1017/S0094837300012641.
Waddington, K. D., L. H. Herbst, and D. W. Roubik. 1986. Re- lationship between recruitment systems of stingless bees and within-nest worker size variation. Journal of the Kansas Ento- mological Society 59:95–102.
Warner, M. R., A. S. Mikheyev, and T. A. Linksvayer. 2019. Transcriptomic basis and evolution of the ant nurse-larval social interactome. PLoS Genetics 15:20. https://doi.org/10.1371 /journal.pgen.1008156.
Weber, N. A. 1966. Fungus-growing ants. Science 153:587–604. https://doi.org/10.1126/science.153.3736.587.
Wenseleers, T., and F. L. W. Ratnieks. 2006. Comparative analysis of worker reproduction and policing in eusocial hymenoptera supports relatedness theory. American Naturalist 168:E163– E179. https://doi.org/10.1086/508619.
Wenzel, J. W. 1992. Extreme queen-worker dimorphism in Ropalidia ignobilis, a small-colony wasp (Hymenoptera: Vespidae). Insectes Sociaux 39:31–43. https://doi.org/10.1007/bf01240529.
West, S. A., R. M. Fisher, A. Gardner, and E. T. Kiers. 2015. Major evolutionary transitions in individuality. Proceedings of the National Academy of Sciences of the USA 112:10112–10119. https://doi.org/10.1073/pnas.1421402112.
Wheeler, D. E. 1986. Developmental and physiological deter- minants of caste in social hymenoptera: evolutionary implica- tions. American Naturalist 128:13–34. https://doi.org/10.1086 /284536.
Wille, A. 1983. Biology of the stingless bees. Annual Review of En- tomology 28:41–64.
Wilson, E. O. 1971. The insect societies. Belknap, Cambridge, MA. Wittwer, B., A. Hefetz, T. Simon, L. E. K. Murphy, M. A. Elgar,
N. E. Pierce, and S. D. Kocher. 2017. Solitary bees reduce invest- ment in communication compared with their social relatives. Proceedings of the National Academy of Sciences of the USA 114:6569–6574. https://doi.org/10.1073/pnas.1620780114.
Woodard, S. H., B. J. Fischman, A. Venkat, M. E. Hudson, K. Varala, S. A. Cameron, A. G. Clark, and G. E. Robinson. 2011. Genes involved in convergent evolution of eusociality in bees. Proceedings of the National Academy of Sciences of the USA 108:7472–7477. https://doi.org/10.1073/pnas.1103457108.
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