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Why are no animal communication systems simple languages.

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Commentary: Why Are No Animal Communication Systems Simple Languages?

• 1 Department of Psychology, University of Washington, Seattle, WA, United States
• 2 Department of Biology, University of Washington, Seattle, WA, United States

Individuals of some animal species have been taught simple versions of human language despite their natural communication systems failing to rise to the level of a simple language. How is it, then, that some animals can master a version of language, yet none of them deploy this capacity in their own communication system? I first examine the key design features that are often used to evaluate language-like properties of natural animal communication systems. I then consider one candidate animal system, bird song, because it has several of the key design features or their precursors, including social learning and cultural transmission of their vocal signals. I conclude that although bird song communication is nuanced and complex, and has the acoustic potential for productivity, it is not productive – it cannot be used to say many different things. Finally, I discuss the debate over whether animal communication should be viewed as a cooperative information transmission process, as we typically view human language, or as a competitive process where signaler and receiver vie for control. The debate points to a necessary condition for the evolution of a simple language that has generally been overlooked: the degree of to which the interests of the signaler and receiver align. While strong cognitive and signal production mechanisms are necessary pre-adaptations for a simple language, they are not sufficient. Also necessary is the existence of identical or near-identical interests of signaler and receiver and a socio-ecology that requires high-level cooperation across a range of contexts. In the case of our hominid ancestors, these contexts included hunting, gathering, child care and, perhaps, warfare. I argue that the key condition for the evolution of human language was the extreme interdependency that existed among unrelated individuals in the hunter-gatherer societies of our hominid ancestors. This extreme interdependency produced multiple prosocial adaptations for effective intragroup cooperation, which in partnership with advanced cognitive abilities, set the stage for the evolution of language.

Introduction

Research programs on animal communication systems in nature have proceeded essentially independently of research programs endeavoring to teach language to animals. This is surprising in light of the early, well-known efforts to relate these two research streams, especially by Hockett (1960) and Marler (1961) . These efforts spurred two questions. First, can animals be taught human language, even a simplified version? Second, do the natural communication systems of any animals rise to the level of simple language? Research since then has indicated that these two questions may have different answers: I would suggest a provisional yes to the first, and a provisional no to the second. If this view is correct, it raises a further question: why, then, if some animals can master a version of language, don’t they use this capacity in their natural communication system? In this paper I address this paradox, and make some suggestions toward its resolution.

My paper is divided into four parts. First I consider the main “design features” of language proposed by Hockett as a basis for evaluating language-like properties of animal communication systems. Hockett concluded that some animal communication systems have some of these design features, but none of them have all the design features, especially the key ones. I will designate an animal communication system as a ‘simple language’ system using a variation on the definition of Hewes (1973) : “language [is] any system of animal communication which exhibits most of the design features set forth by Hockett” ( Hewes, 1973 , p. 5). I narrow this definition by identifying four design features – semanticity, arbitrariness, learnability and cultural transmission, and productivity – as necessary for the system to be classified as a simple language. Second, I discuss bird song, a case where several but not all of the key design features are present. I will focus on one specific case of a song-based communication system that is clearly complex and nuanced, but nevertheless lacks three key design features, semanticity, arbitrariness and productivity. Third, I consider the debate, not yet fully concluded, over whether animal communication should be conceived of as a process of information transfer or as manipulation of receiver by the signaler. The debate is germane to our more specific question because it provides a clue as to why we find no simple languages among animals despite the apparent capacity for it in at least some of them. Finally, I suggest that although there appear to be at least some animals with the cognitive capacity for a language-like communication system, none of them have a social system with extreme interdependency among individuals on the scale of that which existed in the hominid hunter-gatherer system. I argue that this extreme interdependency was a necessary condition for the evolution of human language.

Design Features of Language

In this section I consider the extent to which the most important design features of human language are found in animal communication systems. I use Hockett’s (1960) design features as a basis for comparison of natural animal communication systems with human language. Although Hockett’s design features may have limited use as a theoretical framework for modern evolutionary linguistics ( Wacewicz and Żywiczyński, 2015 ), it is a useful starting point for the comparative analysis of this paper. I have winnowed Hockett’s original design features down to the few I consider the most fundamental ones that can be used to directly compare human language with animal communication systems.

Specialization: The Purpose of Linguistic Signals Is Communication and Not Some Other Biological Function

Specialization, in Hockett’s sense, is the first defining feature of a communication system, no matter how simple or complex it might be. Otte (1974) defines communication signals as traits “fashioned or maintained by natural selection because they convey information to other organisms”( Otte, 1974 , p. 385). I discuss the vigorous debate over the ‘information’ aspect of this definition in Section “Communication: Information or Influence? Mutual Benefit or Manipulation?”, but debaters on both sides would agree that this definition captures the key difference between true communication signals on the one hand, and tactical behaviors or inadvertent cues on the other. For example, while we might describe an individual delivering a blow to a potential opponent as ‘sending a message,’ we mean this only in a metaphorical sense. This behavior is primarily tactical, that is, the individual delivering the blow will directly benefit it if its opponent responds by backing down. If instead of delivering a blow the individual had said “I’m going to kill you,” or growled, or barked, or hissed, we would recognize these as true communication signals, having been shaped by natural selection for the purpose of (literally) sending a message, and requiring adaptations in the receiver as well.

Hockett listed prevarication – the ability to transmit misinformation, i.e., to lie or deceive – as one of his many design features, albeit a minor one, a corollary almost. In Section “Communication: Information or Influence? Mutual Benefit or Manipulation?”, I will argue that we should consider prevarication to be a fundamental, indeed foundational feature of animal communication systems: communication in animals is shaped by the tension between the sender’s and receiver’s interests, and truth in communication is not a given, but rather, when it occurs, hard won.

Semanticity: Specific Signals Are Directly Tied to Certain Meanings

To say that a communication system is semantic is to say that it uses signals to represent particular things or actions. A well-known example in animals are alarm signals given in response to different predators. We can say in such cases that each of these signals represents one of several different predators, or more precisely, the appearance on the scene of one of these predators. For example, vervet monkeys have three different alarm calls for three different classes of predators: raptors, terrestrial mammals and snakes, predators which depend on an element of surprise to capture the monkey. In response to an aerial predator, such as a martial eagle, a monkey emits ‘cough’ calls and sender and receivers take shelter in dense bushes or near the core of a tree. In response to leopards, a monkey emits a ‘bark’ call and the monkeys climb up to the tip of tree branches where leopards cannot safely go. Finally, if a monkey spots a dangerous snake, such as a python, it emits a ‘chutter’ call and the group gathers around the snake, standing upright and harassing it until it leaves the area. Although the vervets use these same signals in other contexts (e.g., intergroup fights) to represent different things, the modification of signal meaning in different contexts occurs in human language as well, and does not negatively impact the representational quality of these signals ( Seyfarth et al., 1990 ; Price et al., 2015 ). Indeed, it is not unusual for an animal to use a particular signal to mean different things in different contexts ( Smith, 1997 ), similar to some words meaning totally different things within different sentences.

Nevertheless, I will argue later in this paper that the semanticity of animal communication systems is limited: although some things are represented by animal signals, the number of things is generally small. Attempts to catalog the number of different things signaled in animal communication systems typically top out at 25 or so (vervet monkeys, Struhsaker, 1967 ; Japanese macaques, Green, 1975 ; review in Hauser, 2000 ). The limitation does not appear to be due to production constraints (the ability to produce enough distinct signals or to recombine enough of them to enlarge the signal set) or to perceptual-cognitive constraints.

Arbitrariness: Languages Are Made Up of Arbitrary Symbols Which Have No Intrinsic or Logical Connection to What They Represent

A distinctive feature of human language is that not only are words semantic, they are arbitrarily so. We could equally well call dogs ‘cats’ and cats ‘dogs,’ or any other two words, so long as sender and receiver knew the convention, a point illustrated by the existence of the many different languages of the world. These signals seem totally arbitrary with respect to what they signify, and in theory they could be interchanged without problems, so long as senders and receivers were both aware of the convention. How about animal signals? It appears that in theory we could interchange the vervet alarm signals without problems, provided of course that the receivers were aware of the ‘convention’ (i.e., were hard-wired appropriately). Identity signals – indicating species or individual identity, and occasionally group or kinship – are perhaps the most common animals signals that unequivocally have the arbitrariness feature.

But many, perhaps most, animal signals are not arbitrary. Signals used in agonistic and mate attraction contexts are typically “more of” signals, i.e., more effective signals are louder, longer, bigger, brighter, flashier, designed to impress or to shock and awe. I am unaware of any clear example where the reverse is true, where the more effective signal is the one that is less conspicuous, for example, a softer sound, a more subdued color, a less vigorous display. An apparent exception might be the ‘quiet song’ sung by many songbirds in intense conflict situations, but this typically happens only when the bird is close to its opponent so that the quiet song is audible to the receiver ( Searcy et al., 2014 ); ‘normal’ song is loud because it is a long-distance signal. Moreover, quiet song is typically different in other respects besides loudness, for example, having some elements seen only in quiet song, such as very high frequency elements.

Other animal signals are simple extensions or slight modifications of tactical behaviors, e.g., of attack behavior in agonistic situations. For example, a threat signal in many mammals is the open mouth display, where the teeth, the canines notably, are prominently displayed. Ethologists called this a ‘ritualized’ display ( Lorenz, 1966 ), i.e., one that has been modified by natural selection to be a display, since the mouth is held open, and attack withheld, rather than being the beginning of an actual attack. Another common threat signal is the raising of the hair or feathers, making the animal appear larger. Again, while these actions are plausibly considered ritualized displays, they are not arbitrary signals. If they were, you would also find cases where animals threaten by closing their mouths, or by making themselves appear small. In short, animal signals functioning to impress an opponent or potential mating partner are usually inherently impressive, not arbitrarily selected to represent threat or desirability. Any naïve observer viewing a ritualized dominance interaction between two wolves (or dogs) would have no difficulty determining which animal was dominant and which was subordinate. An upright animal, with its hair raised, its tail raised, and staring at its opponent inherently appears dominant, whereas one with a flattened, slinking body, hair down, tail down, and looking away from the opponent, inherently appears subordinate.

Many epigamic signals – signals designed to attract a mate and induce her to mate – are bright, striking ornaments, often ones that function like supernormal stimuli (e.g., the tail of the long-tailed widowbird, Andersson, 1982 ). Many epigamic signals are energetically expensive and highly skilled behaviors, such as the complex male courtship dances of wolf spiders and jumping spiders ( Hebets and Uetz, 1999 ; Elias et al., 2012 ). The motor performance revealed in these sorts of displays likely reflect whole-organism performance relating to survival, and thus should be good indicators of individual signaler quality. There is considerable evidence that females choose mates in nature based upon their evaluations of male motor performance (reviewed in Byers et al., 2010 ). The relevant point here is that these signals are not arbitrary, but inherently reflect the trait signaled: signaler quality.

Even in the example par excellence of communication of information about the external world – the honeybee dance language – the signals are not quite so arbitrary as generally assumed. For example, if the dance is done outside the hive, where the sun is visible, the bee dances with respect to the actual position of the sun, rather than with respect to the vertical ( Gould, 1975 ). That is, outside the hive, the symbology is not truly arbitrary. Moreover, the distance to the target is represented by the duration of the straight run – the further the distance, the longer the run – so this is at least partially non-arbitrary as well.

Although the words in human language are arbitrary – the existence of different languages is the clearest evidence on this point – they may be expressed in such a way to amplify or otherwise modify their meaning, as for example a loudly shouted “no” indicating stronger conviction. But what would be considered an extra-linguistic feature for humans is often the primary message in animals. For example, the initial stage of a battle between two male red deer consists of a roaring contest ( Clutton-Brock and Albon, 1979 ). This vocal signaling duel does far more than simply establish that each animal is a male conspecific ready to defend or fight for the harem – this undoubtedly was perceived by both parties before the contest began – rather, how loud and how long an individual roars establishes how motivated and formidable he is, and is used by the receiver to decide whether to continue the fight or depart. Similarly, the plumage ornaments and courtship dance of a male golden-collared manakin do far more than simply identify species and sex – that is simply the necessary first step – the brightness of the ornament and the skill of the dance determine whether the receiver, the female, will choose to mate with this particular male or continue her search for the best possible mate ( Stein and Uy, 2006 ; Barske et al., 2011 ).

In summary, although we have examples of animal signals that are totally arbitrary, many others – perhaps most? – are not. I would add that to date we have found nothing comparable to the many different human languages, which are a consequence of the arbitrariness feature. We do find geographical dialects in animals (e.g., Marler and Tamura, 1964 ; Wright and Dahlin, 2018 ), but as the name implies, these are relatively minor variations on the basic signal set, nothing like the wholesale variation seen in human languages.

Learnability and Cultural Transmission

Human language is both learned and taught. Most animal communication systems are neither. A well-known exception to this generalization are the learned vocal communication signals of several taxa, most notably the oscine passerines (songbirds), hummingbirds and parrots among birds, and cetaceans and at least some bat species among mammals (reviews in Janik, 2014 ; Knornschild, 2014 ; Nowicki and Searcy, 2014 ). Evidence for vocal learning and cultural transmission in some other birds and mammals as well ( Walcott et al., 2006 ; Kroodsma et al., 2013 ; Stoeger and Manger, 2014 ; Garland and McGregor, 2020 ; Barker et al., 2021 ) suggests that this ability may lie closer to the surface than is generally assumed, but at least at the present time, vocal learning is thought to be rare in animals. Later in this paper I return to the best-studied example of vocal learning, song learning in songbirds.

Where the communication signals are learned, we should expect to find dialects, geographical variation in the signals. The occurrence of dialects is one criterion for identifying the occurrence of learning and potentially evidence for the arbitrariness design feature. An example that may illustrate the arbitrary nature of dialects is the recently-discovered modification of the song in eastern white-throated sparrows to resemble the typical song of western white-throated sparrows. Investigators have traced this change to eastern birds learning the western version of the song on the migration grounds, where individuals of the two populations mix ( Otter et al., 2020 ). Most eastern birds now sing the ‘western’ version of the song on the breeding grounds, illustrating that the details of the song structure are not crucial for its function. Although Otter et al. (2020) suggest that this change might have been driven by a preference on the part of eastern females, they give no evidence for this hypothesis, nor plausible basis for it.

Perhaps even rarer in animal communication systems than learning is teaching. The commonly accepted criteria for demonstrating teaching in non-human animals are that (1) teachers should modify their behavior in the presence of the learner, (2) this change in behavior should result in no immediate benefit to the teacher, and (3) the learner should acquire a behavior quicker or better as a result ( Caro and Hauser, 1992 ). In song-learning studies the birds from whom the young bird learns its song are conventionally referred to as ‘tutors,’ and although live birds are invariably more effective song tutors than recorded song (review in Beecher, 2017 ), the term ‘tutor’ is used purely as matter of convenience. In fact, in the most common context for song learning in nature, young birds learn from older birds who are or will be their territorial rivals, a very different context from language learning in young humans, where ‘tutors’ are typically relatives or other interested parties who ultimately (but not immediately) benefit from tutoring. Nevertheless, even in the common songbird case where the young bird learns from territorial rivals, bird song tutoring would fit all three criteria for teaching if in fact the older bird reduces his usual aggression when a young bird appears on his territory, increases his counter-singing with the young bird in such a way as to facilitate learning, and benefits down the road from this tutoring (for example, the two cooperate in mutual defense of their territories, or against predators, or refrain from extra-pair mating with one another’s mates). We have indirect evidence for song learning/teaching in song sparrows: mutual survival is greater in young birds and their primary tutor-neighbor (the one from whom they learn most of their songs) the more songs the two of them ultimately share, i.e., the more songs the tutee learned from the tutor, or the tutor taught the tutee ( Beecher et al., 2020 ).

Productivity: By Combining a Small Number of Meaningless Units Into Larger Meaningful Signals, a Sender Is Capable of Producing Meaningful Statements About Virtually Anything

The sense in which I am using this term is captured by Hauser (2000 , p. 448): “the power of [human] language comes from our capacity to take meaningless syllables and combine them into an unbounded number of meaningful words, and then take these words and combine them into an unbounded number of meaningful expressions ( Chomsky, 1986 ; Studdert-Kennedy, 1998 ).” I will define productivity as recombining a smaller number of basic signal units to produce a larger number of signals, and thus, messages. Indeed, semanticity (representation) and productivity are probably the two central features of human language: by combining basic phonetic units into larger meaningful units, and combining these units further via syntactical rules, we can say almost anything.

Animal communication systems are not productive in this sense, and this is the primary reason we do not refer to them as languages. We would be impressed if a vervet could say something like “Grab your infant and run from the leopard coming from the west but watch out for the python who likes to hide in the bushes just to the east of you.” A human can say this kind of thing easily, combining a relatively small number of atomic units (phonemes) into very large number of basic signals (words) and combining these into a very large set of possible communications. I note that while there is some controversy in phonetics about exactly what are the units of productive combination, there is agreement that all natural languages (including sign language) are made up of meaningless atomic units that are combined into larger meaningful wholes ( Zuidema and de Boer, 2009 ).

Instead of productivity, we could describe the communication system in terms of information capacity. The information capacity of human language is essentially infinite, in the sense that, in theory, we can communicate virtually anything. Our motor, sensory and cognitive capacities obviously will reduce how much information actually gets transmitted and received. But still, the fact is that we can transmit an enormous amount of information with language. Attempts to measure information capacity or information transmission in animals, on the other hand, have given rather modest results. Two estimates of the information about distance and direction in the honeybee dance language have given a high value of 14.9 bits ( Gould, 1975 ) and a low value of 7.4 bits ( Schürch and Ratnieks, 2015 ). My group has estimated the information capacity of the call signature system that parents of the colonial cliff swallow use to find their offspring in their large breeding colonies ( Medvin et al., 1993 ). We estimated the capacity as 8.76 bits, and the estimate would be somewhat larger if we included information that can be derived from visual differences among cliff swallow chicks ( Stoddard and Beecher, 1983 ). The information capacity of human language of course is orders of magnitude larger than this.

We certainly find the potential for productivity in bird song. For example, most songbirds have multiple songs (song ‘repertoires’), and the different songs are made up of different syllables or notes in different orders, and these smaller units can be used in more than one song. Still, although the units are there, and although songbirds may possess the cognitive capacity to comprehend hierarchical structuring in vocal signals ( Gentner et al., 2006 ; but see van Heijningen et al., 2009 ), they do not use these capacities to form different songs representing different things. As Hauser (2000 , p. 450) puts it, “in contrast to the recombination of words into sentences by humans, the output of songbird recombination does not change its meaning.” A minor exception are some songbirds who use some song types in a territorial defense context and others in a mate attraction context (e.g., Byers, 1996 ). As discussed in the next section, theories on the function of song repertoires abound, but they all agree that the different songs function simply to provide diversity, rather than to represent different things.

Table 1 summarizes the conclusions of this section. The natural communication systems of animals fall short of human language on a number of the key design features of language. They come closest on semanticity, where signals sometimes represent things in the external world or within the signaler, and the signals are sometimes truly arbitrary. However, more commonly animal signals are not arbitrary but inherently meaningful, e.g., an animal making itself appear large is more frightening than an animal making itself appear small. Most animal communication signals and responses are neither learned nor culturally transmitted. And, so far as we know, no animal communication has the sine qua non of language: productivity.

Table 1. Key design features of communication systems (after Hockett, 1960 , pruned and combined).

Bird Song: Complexity Without Productivity

The oscine passerines (songbirds) are one of the rare animal taxa in which individuals learn their vocal communication signals. In most animals, these vocal signals are ‘hard-wired,’ that is, they develop normally whether or not the animal is exposed to them early in life. It has long been noted that vocal learning in songbirds has many similarities to language learning in humans ( Marler, 1970 ; Doupe and Kuhl, 1999 ). These similarities include the following. (1) The young bird needs to be exposed to normal species vocal signals in order to produce them as an adult. (2) The sensory phase of song learning precedes the motor phase. (3) Auditory feedback (which can be abolished by deafening) is necessary for the translation of memorized sensory input into motor production. (4) Vocal learning is most efficient in (and sometimes restricted to) a sensitive period early in life. (5) There are specialized parts of the brain dedicated to the vocal control system. (6) Song is socially learned and culturally transmitted, and in at least some cases it may be actively taught (e.g., Carouso-Peck and Goldstein, 2019 ; Beecher et al., 2020 ). While notable differences exist among songbird species with regard to the normal progression of song learning ( Beecher and Brenowitz, 2005 ), these six features are essentially true for all of the many songbirds that have been studied to date.

Despite the notable parallels between bird song learning and human language learning, none of the many studies endeavoring to teach a version of human language to animals have focused on songbirds. This is all the more surprising given the language learning shown by Alex the African Gray Parrot, a member of another avian taxon with vocal learning, the psittacines ( Pepperberg, 1981 , 1987 ). Moreover, songbirds have strong cognitive capacities, a highly-developed vocal production mechanism, and a vocabulary of basic sound units in their song that rivals or exceeds the basic sound units of human language. There are even songbird species that can mimic human speech sounds (e.g., Hill Mynah birds). On the face of it, all the requisites would seem to be there to support a simple language in a songbird.

What Is the Function of a Song Repertoire?

In contrast to well-studied white-crowned sparrows and zebra finches, in most songbird species an individual bird will sing multiple songs (has a song ‘repertoire’). For example, song sparrows typically have nine (plus or minus two or so) very different songs. Each of these songs is made up of 5 or 6 distinct elements, and the order of these elements is important ( Horning et al., 1993 ). The songs do not have individual signatures and the nine or so songs in a song sparrow’s repertoire are as different among themselves as would be a collection of songs taken at random one from each of nine or so different birds ( Beecher et al., 1994 ). Song sparrows are somewhere on the middle of the song repertoire complexity scale: many species have larger and even more complex song repertoires. The key point for this discussion is that song repertoires provide clear potential for productivity, as song sparrows and many other songbirds have as many or more distinct units in their vocal communication systems (e.g., about 100 in indigo buntings, Thompson, 1970 ; and in swamp sparrows, Marler and Pickert, 1984 ) as there are in human language (a typical language has 40–45 phonemes).

The most popular hypothesis about song repertoires for north temperate zone songbirds – where only males sing – is that they are an epigamic signal produced by males to attract females and that larger repertoires are more attractive than smaller ones ( Catchpole, 1987 ; Searcy and Yasukawa, 1996 ; MacDougall-Shackleton, 1997 ; Collins, 2004 ). Focusing on just the well-studied song sparrow, the evidence for this hypothesis is mixed ( Searcy, 1984 ; Reid et al., 2004 ; Hill C. E. et al., 2011 ). The handicap principle, discussed in the next section, would suggest that if large song repertoires are preferred, it is because they are an indicator of some aspect of male quality. Reid et al. (2005) found support for this idea: song repertoire size in male song sparrows correlated with enhanced cell-mediated immune response (CMI) and relative heterozygosity. Anderson et al. (2017) hypothesized that female song sparrows might prefer large-repertoire males because this feature is an indicator the overall learning ability of the male. However, they found no correlations between repertoire size (or two other measures of song learning ability) with an overall measure of learning ability (based on five different learning tasks). I should note, however, that a correlation of vocal learning ability with both overall learning ability and mating success has been found in another songbird, the Satin Bowerbird, a vocal mimic: in this case the vocal learning ability is the ability of males to mimic the calls of other local bird species, both the number of species mimicked, and the accuracy of the mimicry ( Coleman et al., 2007 ; Keagy et al., 2009 ).

According to another hypothesis, song repertoires play a role in territorial competition, which in north temperate zone songbirds, where only males sing, is largely male-male competition, but outside the north temperate zone where both sexes sing, is pair-pair competition (e.g., Levin, 1996 ; Langmore, 1998 ; Logue and Gammon, 2004 ). There are several hypotheses as to how repertoires might work in the territorial competition context. Song is used by most territorial songbirds at least in part as a keep-out signal, to ‘post’ their territory. Kroodsma (1988) argues that the vocal diversity provided by a repertoire functions to hold the attention of territorial competitors by dishabituating them to the territory owner’s singing, i.e., by holding their attention. As one piece of evidence, he points to a positive correlation between repertoire size and population density in marsh wren populations, and also to the finding that birds in denser populations cycle through their songs faster, again a behavior that should reduce habituation ( Kroodsma, 1977 ). In contrast, song sparrows sing their much smaller repertoires with eventual variety, i.e., singing each one of their song types many times before switching to another type, and this would seem to argue against the dishabituation hypothesis. In western, resident populations of song sparrows, song repertoires may function primarily to provide a bird with songs matching all (or most) of his neighbors, and thus potential individualized replies to each one of them ( Beecher et al., 1997 ; and see next section).

Although as this brief discussion indicates, the theoretical debate has not yet concluded, the take-away point is that none of these hypotheses view song repertoires as a form of semantic communication. Rather they view repertoires as having a direct effect on the receiver (dishabituation), or as permitting individualized replies to multiple neighbors, or as quantitative signals with inherent rather than semantic meaning, that is, more songs (or more song syllables) are simply more effective.

I should add that most single-song species appear to have the potential to develop song repertoires yet do not tap into this potential. For example, when examined over an entire population, indigo buntings have a repertoire of over a 100 distinct song syllables, yet a given individual uses just 6–8 of these in the single song it develops ( Rice and Thompson, 1968 ; Thompson, 1969 ; Baker and Boylan, 1995 ).

An Example: Communication in a Negotiation Context

Although the different songs in a bird’s repertoire do not have different meanings, a bird having a song repertoire can still use the different songs to communicate in more subtle, nuanced ways than might at first be suspected. In this section I describe one such case: how song sparrows use the songs in their song repertoire to negotiate territorial disputes. The general point I will make is that their communication system is surprisingly complex and versatile, despite being neither semantic nor productive. Although I will not attempt to generalize to all songbirds given the incredible diversity of the song communication systems seen in this group ( Beecher and Brenowitz, 2005 ), I suspect that this conclusion – complexity without productivity – applies broadly to songbirds, and perhaps to all animals.

Song sparrows have a territorial system like that found in many animals and typical of many songbirds. An individual carves out a territory where the mated pair will nest and raise their young, doing most of their feeding on the territory. Suitable habitat is typically densely occupied by conspecifics, so territorial disputes can arise during both the establishment and maintenance stages. The relationship between territorial neighbors can become relatively non-hostile once established, however, on the principle that the enemy you know is better than the enemy you don’t know, generally referred to as the ‘Dear Enemy’ relationship ( Fisher, 1954 ; Akçay et al., 2009 , 2010 ; Beecher and Akçay, 2014 ). Because in territorial animals, neighbors have no fences, neighbors need to renegotiate territory boundaries from time to time. Negotiation can progress into fighting but avoiding fighting may benefit both parties and this common interest favors reliable signaling. Therefore, as I will discuss in Section “Communication: Information or Influence? Mutual Benefit or Manipulation?”, we should expect to find some degree of honest communication concerning not only fighting ability (resource-holding potential) but also motivation to fight (e.g., at a particular point in time, one party may have more to lose than the other).

Song sparrows in western, resident populations use their repertoires in a complex way to carry out territory negotiations. Although they will engage in serious fights, established neighbors use their signaling system to avoid fighting if possible. Before fighting they typically give their high-level threat signals, wing waves and soft song ( Searcy and Beecher, 2009 ; Searcy et al., 2014 ; Akçay et al., 2015a ). But before reaching this stage, they use the songs in their repertoires to escalate or de-escalate the dispute following a set of ‘conventions’ predicated on which songs the two birds happen to share ( Beecher et al., 1996 , 2000 ; Burt et al., 2001 , 2002 ; Beecher and Campbell, 2005 ; Akçay et al., 2011 ; Templeton et al., 2012 ; Akçay et al., 2013 , 2015b ). Because western song sparrows learn songs from their neighbors in the area to which they disperse after fledging, a bird typically shares some of his songs with each of his immediate neighbors. The set of songs he shares with one neighbor is typically different from the set he shares with another. A partial example is shown in Figure 1 . For example, if we represent the different songs of a bird with different capital letters, and the shared songs of neighbors with the same capital letter, then Bird 1 might share his song types A, B, and C with his neighbor Bird 2, his song types C, D, and E with another neighbor, his song types E and F with a third neighbor, and finally G, H, and I with no neighbors (e.g., the bird he learned these songs from may have died). A typical territorial negotiation might occur as follows. Suppose Bird 1’s mate finds an ideal place to build her nest just over the previously-established boundary with Bird 2. Bird 1, aiming to establish this new boundary, moves to that point and sings at his neighbor. Typically the two birds would still be a considerable distance apart at this point and out of sight of one another (territories are large and song is a long-distance signal). Although Bird 1 could sing any one of his 9 songs to Bird 2, in this circumstance he would typically ‘address’ Bird 2 by singing one of their shared types, A, B, or C. Let us say bird 1 sings B. Bird 2 can escalate by replying with his B’ (i.e., his most similar song to Bird 1’s B). This ‘type match’ is a low-level threat signal and would be the first step in escalation. Alternatively, he could ‘confirm’ without escalating by replying with A’ or C’ (‘repertoire matches’, Beecher et al., 1996 ). Note that this type of reply is only possible if Bird 2 knows Bird 1 well enough to know which songs they share and which songs they don’t. Finally, rather than type-matching or repertoire-matching, Bird 2 can de-escalate by singing one of his unshared types, e.g., D, E, F, G, H or I. Singing an unshared type is better than not singing at all because it signals that although the singer is not engaging, he is on territory and has heard his neighbor; it is a signal likely used for example when the bird is busy feeding recently-fledged young. If Bird 2 does type match bird 1 (sings B’), Bird 1 in turn can continue to sing that song type (‘stay on type’), or he can de-escalate by switching to another shared song (A or C, ‘repertoire match’), or de-escalate further by switching to an unshared type (e.g., D or E), or disengage totally by stopping singing.

Figure 1. Partial song repertoires of two neighboring birds. Shared songs are shown in the top three rows, and four of their unshared songs in the bottom two rows (they are arbitrarily paired). Frequency scale: 0–10 kHz. Songs are 2–3 s long.

Each ‘convention’ – type matching, repertoire matching, staying on type, switching to an unshared type – has a distinct signaling function in this graded signaling system, with both type matching and staying on type when type-matched signaling a readiness to escalate, repertoire matching signaling recognition of the sender and engagement but stopping short of escalation, and switching to an unshared type signaling de-escalation. The system while not in itself resolving anything, does give the neighbors time to defuse the situation or work out a compromise. Note, however, that the semantic content is limited. No particular song in the repertoire means a particular thing. A song’s meaning is defined entirely by the context of who the receiver is, and even then there are essentially only three meanings, roughly ‘back off,’ ‘I hear you and know who you are,’ and ‘I’m busy now.’

Songbirds check several of the design feature boxes and they would appear to have the potential to use their songs in a productive way, i.e., to use their signaling system to say many things. However, despite considerable debate concerning the function of song repertoires, the different repertoire hypotheses all agree on one point: that the function of the vocal diversity is diversity per se , not the transmission of different messages with different songs. Perhaps even more surprising, many single-song species have large song syllable repertoires an individual could tap into, but instead each individual uses just several of these syllables to develop its single song. No songbird rearranges its multiple song syllables into different songs that signal different things. I echo here the conclusion of Fitch and Jarvis (2013 , p. 502): although songbirds (and parrots) have vocal learning and a complex vocal repertoire, they do not “use their songs to communicate combinatorial propositional meanings, i.e., semantics.”. Songbirds may use their repertoires in subtle, nuanced ways, as with the song sparrow hierarchical signaling system I described above, but what the system achieves seems better described as the management of behavioral conflict than as an impressive transmission of information. That is, the system may function well, but it does not function like a language.

Communication: Information or Influence? Mutual Benefit or Manipulation?

In this section I discuss the debate within the field about the fundamental nature of animal communication. I believe this debate has provided us with a key to understanding why we find no examples of a simple language among the many communication systems of non-human animals, and true language only in the human animal.

We can trace the real beginning of the field of animal communication to the classical ethologists (e.g., Tinbergen, 1952 ). The ethologists provided detailed descriptions of animal signaling systems in nature, developed theories about the underlying proximate causes (e.g., sign stimuli, innate release mechanisms, and fixed action patterns) and evolutionary processes (e.g., ritualization), and most relevant here, established the view of animal communication as – like human language – an information transfer process. On the question of the function of animal signaling systems, they took a group-selectionist perspective: the benefit that a signaling system provided went not to signaler or receiver per se , but to the species (see Tinbergen, 1964 definition in Table 2 ).

Table 2. Definitions.

Following the revolution of the 1960’s and 1970’s first known as sociobiology ( Wilson, 1975 ) and subsequently as behavioral ecology ( Krebs and Davies, 1978 ), natural selection came to be viewed as acting on individuals, rather than species or groups ( Williams, 1966 ). For some researchers, the shift from naïve group selection to individual selection did not entail a significant change in view: it was simply assumed that signaler and receiver both benefited from the transmission of information, and so this basic parallel with human language was maintained (see Table 2 definitions of Marler, 1968 ; Otte, 1974 ). The assumption of mutual benefit seemed natural in cases where sender and receiver have a strong common interest, e.g., the honeybee ‘dance language’ where scout and recruit are both working toward the same end, to provide food for their relatives in the hive. But as investigators began considering the many cases where signaler and receiver have conflicting interests, such as in agonistic encounters over an indivisible resource, they began to question the mutual-benefit, information transmission view. They asked two questions about such cases. First, do both parties have to benefit? Second, do we need to even talk about ‘information transmission’? Isn’t the signaler simply selected to manipulate (or influence) the behavior of the receiver to its advantage? The manipulation viewpoint was famously developed by Dawkins and Krebs (1978) who argued that rather than expecting signalers to signal honestly, we should expect them to manipulate the receiver to their own advantage, e.g., to convince opponents to retreat, or potential partners to mate with them.

Since the Dawkins and Krebs (1978) paper, the debate has continued as to whether it is justified or productive to conceptualize animal signaling as an information transmission process in which both parties benefit. Simplifying somewhat, I will distinguish between the Information Transmission and Manipulation approaches to animal communication. Strong arguments on the manipulation side since Dawkins and Krebs (1978) include Krebs and Dawkins (1984) , Owings and Morton (1998) , Scott-Phillips (2008) , Rendall et al. (2009) , and Owren et al. (2010) . Strong arguments on the information side over this same period include Green and Marler (1979) , Smith (1997) , Bradbury and Vehrencamp (1998) , Searcy and Nowicki (2005) , Carazo and Font (2010) , Seyfarth et al. (2010) , and Wiley (2013) . Definitions from some of these sources are included in Table 2 .

In conceiving of signaling as manipulation, Dawkins and Krebs (1978) essentially treated the communication interaction like a zero-sum game. This seems reasonable in cases like disputes over an indivisible resource (a food item, a territory, and a mate), and also in epigamic selection, where a male tries to persuade a female to mate with him now rather than to continue searching for a possibly better male. Although the manipulation view was enlightening in many respects, as originally presented it had a serious weakness: it gave no agency to the receiver. While it was sensible to expect signalers to signal for their own benefit, why should we expect receivers to be passive in these evolutionary scenarios, especially if being manipulated by the signaler is costly? Rather, we should expect receivers to show ‘sales resistance’ to signals that carry misinformation or are pure propaganda (“I am the best,” “I will fight you to death”). Indeed, receivers can do more than simply ignore signals that do not benefit them: they can require signals that do benefit them, even if those signals are costly to the sender. For example, in many species males must sing or call to attract a female for mating. If the male does not vocalize, potential female receivers will simply not engage. Moreover, these vocal signals may attract predators, a cost borne by the signaler but not the receiver. Indeed, the most effective or most-preferred signals may be the most costly, e.g., most conspicuous not just to the intended receiver but to predators as well. This is the case for a male túngara frog ( Ryan and Rand, 1990 ). Males attract females to mate with a ‘whine’ call or a ‘whine-chuck’ call. When a male adds chucks to his calls, he not only attracts more females, but also predators: frog-eating bats that home in specifically on the chucks. Similarly, a calling male field cricket attracts more females than does a silent male, but he also attracts more parasitoid flies, and louder calls attract both more females and more parasitoid flies ( Cade, 1975 ). In some populations the rate of fly parasitism is so high that males have lost the ability to sing ( Zuk et al., 2006 ). As another example, territorial animals often vocalize as a “keep-out” signal. When a territorial songbird is deprived of its voice, however, potential rivals show up and proceed to take over its territory (e.g., McDonald, 1989 ).

If we reframe our view of the communication system as beginning with the implicit requirement that the receiver imposes on the signaler—to signal—rather than with the signal itself, it is apparent that receivers can be conceived of as manipulating signalers, and in the ‘receiver manipulation’ view, the potential costs to the sender are secondary to the potential benefits to the receiver. A possible benefit for the female túngara frog – the receiver in our example – might be a shorter search time in navigating to the male who adds the more localizable chucks to his calls, perhaps lessening her vulnerability to predation.

The receiver manipulation view prompts us to consider how the receiver might demand a more honest signal. There are two related possibilities. First, the receiver can selectively attend to signals that are inherently honest due to physical constraints. For example, in many frogs and toads, size is the most important weapon in male battles over mating opportunities and size is reliably predicted by the pitch of the animal’s vocalization: larger animals give lower-pitched calls. Davies and Halliday (1978) showed that playback of low-pitched calls was sufficient to discourage smaller males from entering into battle with an apparently larger male. A second way to require a more reliable signal has generally been discussed under the rubric of the ‘handicap’ principle. This principle was first proposed by Zahavi (1975) , modified and formalized by Grafen (1990) , given the intuitively pleasing graphical formulation by Johnstone (1997) shown in Figure 2 , and is still being subjected to further modification and clarification (e.g., Penn and Számadó, 2018 ). But the basic principle is straight-forward, and can be verbalized as follows: signals whose degree of expression is dependent on the health, general condition or vigor of the signaler are inherently honest expressions of that individual’s quality. For a high-quality signaler, a ‘bigger’ signal is a smaller handicap (less costly, or more affordable) than it is for a low-quality signaler, thus ‘big’ signals are reliable signals of signaler quality. One of the clearest demonstrations of honesty in an epigamic signal was carried out by Petrie and her colleagues on that poster animal for epigamic signaling, the peacock. Petrie and colleagues demonstrated that in their peacock population, females preferred a mate with more eyespots in his feather train (whether the difference was natural, or produced by experimental manipulation), and that females mated with males with more eyespots had more young surviving to a year of age than females mated to males with fewer eyespots ( Petrie et al., 1991 ; Petrie, 1994 ; Petrie and Halliday, 1994 ). Although the generality of these results has been questioned by studies on other populations ( Takahashi et al., 2008 ; Dakin and Montgomerie, 2011 ), the example provides a clear illustration of the predictions generated by the handicap principle, and how they should be tested.

Figure 2. Johnstone’s graphical model of the Handicap principle. The basic assumption is that it costs a high-quality signaler less to signal at its optimum level than it costs a low-quality signaler to signal at that level. The optimum or equilibrium level (where the difference between the costs and benefits of signaling are greatest) for the low quality signaler is lower (opt low) than that for the high-quality signaler (opt high). Thus the signaling level is a reliable indicator of signaler quality.

The handicap principle should maintain some degree of honesty in any signaling system where signaler and receiver have non-identical interests, such as virtually all mating and agonistic contexts. A low-quality individual can only ‘lie’ by diverting energy into signal development and expression that it needs for maintenance, and so as Searcy and Nowicki (2005) succinctly put it, lying becomes more costly than signaling honestly. Searcy and Nowicki suggest that ‘reliable’ is a better word here than ‘honest,’ for several reasons. First, as with reliability testing in science and elsewhere, we understand that although perfect reliability is unattainable, partial reliability may be good enough. In contrast, ‘honesty’ is generally taken to mean absolute honesty. Second, reliability of a signal is empirically measurable. Thus instead of debating whether an animal signal is informative or not, we can measure if it predicts something important about the present state of affairs or future events. Thus for example, in an agonistic situation a ‘threat signal’ should predict subsequent escalation, and the strongest ‘threat’ signal should predict attack ( Searcy and Beecher, 2009 ).

Summing Up: Two Perspectives

Historically, the Information Transmission and Manipulation views of animal communication systems have been presented as in opposition. I suggest that in fact they are simply different perspectives on the same process. Once we give the receiver agency, and accept that manipulation is a two-way or reciprocal process in animal communication, we see that the two views have more in common than was at first thought. This rapprochement is nicely captured in the evolution of Dawkins and Krebs’s papers on the topic. In their original paper, Dawkins and Krebs (1978) focused on signalers and argued that “natural selection favors [signalers] who successfully manipulate [receivers] whether or not this is to the advantage of the manipulated individuals.” However, 6 years later in a follow-up paper ( Krebs and Dawkins, 1984 ) they expanded their view to include receiver interests, noting that receivers would be favored to resist manipulation and to attempt to “read the minds” of signalers. Finally, Krebs (1991) , discussing Zahavi’s handicap principle, concluded that the manipulation and honest signaling views are probably not incompatible: “ Dawkins and Krebs (1978) discussed a coevolutionary process without specifying an end point, whereas Zahavi was concerned mainly with the end-point itself, so it is possible to imagine an evolutionary arms race of manipulation and sales resistance which end up with honest signaling” ( Krebs, 1991 , p. 67).

Figure 3 is a schematic representation of what I will call the Reciprocal Manipulation view. It shows communication taking place on a battleground in which signaler and receiver are each selected to manipulate the other, the battle being settled in the long run with the compromise of mostly-honest (reliable) signals. The “management-assessment” theory of Owings and Morton (1997 , 1998) is quite similar to the Reciprocal Manipulation view. Their theory captures the dynamics of signalers attempting to manage receivers and receivers assessing signalers. In their words “the process of assessment is more active than has been generally recognized, and is responsible for the ‘informational’ couplings between individuals” (1997, p. 359). However, receivers do more than just assess signalers, they manipulate them as well, requiring them to signal in the first place, and requiring a relatively honest signal as a prerequisite for responding to the signal. The Reliable Signaling view of Searcy and Nowicki (2005) is essentially identical to the Reciprocal Manipulation view, with the superficial difference that the former focuses on the information transmission aspect (reliable signaling) while the latter focuses on the manipulation aspect (the conflicting motivations of signaler and receiver).

Figure 3. Schematic suggesting the opposing pressures favoring signaler over receiver or vice-versa. Where interests of signaler and receiver are coincident or nearly so (light gray to white) reliable communication will occur. At the extremes of the space (darker), where interests of one or the other of the two parties predominates, signaling will be disfavored. In the intermediate (gray) region, one party may benefit more than the other, but signaling may still be ‘reliable enough.’

The Reciprocal Manipulation and Information Transmission views each seem most helpful in different circumstances ( Table 3 ). Where the interests and thus motivations of the two parties differ, the Reciprocal Manipulation highlights the clash. In contrast, where the interests and motivations of the two parties are more in line, the Information Transmission viewpoint focuses on the essence of the interaction. Indeed, where the overlap of sender and receiver interests is considerable, as for example between related individuals, or mates caring for offspring, or individuals in a social group where individuals are strongly interdependent, reliable, mutually beneficial signals will be favored. But even where the interests of sender and receiver are partially opposed, selection acting on both parties will move them to the region where both parties benefit on average, and signals will still be reliable, if less so. This game theory dynamic has been clearly laid out elsewhere ( Maynard Smith and Harper, 2003 ; Godfrey-Smith, 2013 ).

Table 3. Differences between reciprocal manipulation and information transmission perspectives.

I believe that the clash between these views of animal communication has ultimately led us to a clearer view of animal communication systems than the original human-oriented information transmission view. Most animal communication systems are somewhere on the continuum from pure manipulation to pure communication, from arms race (where sender and receiver have different interests, each selected to behave so as to benefit themselves) to pure information transmission (where sender and receiver have identical interests, and where signals benefit or cost both parties in the same way or to the same degree). A fuller development of these ideas can be found in Beecher (2020) .

In conclusion, I have argued that we should expect that natural communication systems will generally be reliable, even if not perfectly honest, with signaler and receiver both benefiting on average. However, returning to the main theme of this paper, there is no reason to expect such systems to blossom into simple languages unless signalers and receivers have identical or near-identical interests, and if the ecological selective context requires strong cooperation. There are cognitive prerequisites as well – otherwise one might predict that honeybees should have a simple language – but the brake on the evolution to language-like signaling systems in species with the requisite cognitive capacity is provided by the generally divergent interests of signaler and receiver. Otherwise, bonobos, dolphins and some other vertebrates who seem to have the necessary cognitive prerequisites would have a more language-like natural communication systems than they do.

Why Are There No Natural Language Systems in Animals?

Research on teaching animals simple human language indicate that at least some animals appear to have the cognitive capacity to decode language or language-like expressions. Herman’s dolphins could comprehend a sign language command such as “take the ball to the hoop” and to distinguish it from a similar but syntactically different command like “take the hoop to the ball” ( Herman, 2010 ). Kanzi the bonobo could respond correctly to novel verbal commands such as “Can you put the pine needles in the refrigerator?” ( Savage-Rumbaugh et al., 1993 ). Pepperberg (1981 , 1987) and Pailian et al. (2020) have shown that African gray parrots can follow verbal directions to solve difficult problems, including some that challenge humans. Yet despite having the apparent capacities, at least to some extent, no non-human animal uses even a rudimentary language in its day-to-day existence. This includes groups like the songbirds that seem to have a crucial design feature, the learning and cultural transmission of a complex set of vocal signals. Some animals appear to be smart enough, or capable enough to handle a simple language, but we have yet to discover an animal communication system – in nature – that rises to this level. Thus it appears that some missing element other than cognitive or motor limitations has blocked language evolution in non-human animals. Although it is possible that yet some other cognitive limitation has not been clearly identified ( Hauser et al., 2002 ; Pinker and Jackendoff, 2005 ), I focus in this final section on a candidate for the missing element that is not purely a cognitive mechanism.

A clue as to the missing element comes from the honeybee ‘dance language.’ Despite a relatively simple nervous system, honeybees are able not only to transmit precise information about events in the external world, but also to use this system in two very different contexts (when talking about the location of desirable food sources or about the location of suitable hive sites). The key ingredient for the evolution of this system, I would argue, is zero conflict of interest between sender and receiver. Both scout and recruit are sister sterile workers and they are both working to feed sisters and brothers slated to be future reproductives. Humans also evolved in a social system featuring extraordinary levels of cooperation, but significantly this cooperation was not restricted to close relatives, as it is in the honeybees and other social insects, ruling out kin selection as a sufficient explanation (but see Fitch, 2004 ).

I will reframe the question from “why not them?” to the question of “why us” (phrasing suggested by Hrdy, 2009 )? How did the human animal become the one species to evolve language? As I argued in the previous section, the field has arrived at a consensus concerning the factors that shape animal communication systems: the pressure for sender and receiver each to shape the interaction to its benefit inevitably both stimulates and constrains the evolution of the communication system. Very unusual circumstances are required for a true language system to evolve. Three essential conditions have to be met. First, the species must have the underlying cognitive capacity. Honeybees may lack this, but some other animals may have it. Second, and this is the clue provided by honeybees, sender and receiver must have identical or near identical interests. Third, individuals must have a compelling need to transmit information across multiple contexts. These are precisely the conditions that existed in pre-human and early human hunter-gatherer societies, the context in which humans and our hominid precursors spent some 95% of our evolutionary history. The description of the prototypical hunter-gatherer society that follows is based on information from a number of sources (including Boehm, 1999 ; Bowles, 2006 ; Hrdy, 2009 ; Hill K. et al., 2011 ; Knight and Power, 2011 ; Lee, 2018 ).

Our hunter-gather ancestors lived in small social groups where individuals were strongly interdependent, and cooperation across multiple contexts was essential for survival. Most highly cooperative animal societies such as the eusocial insects are typically just very large families, but the human hunter-gatherer societies we know – and which we assume to be typical of the ancestral type – consisted of members of several kin lines. Thus human societies then – and now as well – required extensive cooperation among unrelated individuals. Humans are the supreme cooperators in the animal world, but because this cooperation is not supported by high kin relatedness, it has to withstand a strong undercurrent of individual competition. We sometimes lose sight of the human affinity for within-group cooperation because of its paradoxical coexistence with intense between-group competition and tribalism. Irreconcilable conflicts within ancestral hunter-gatherer groups surely occurred, but were often resolved by individuals leaving one group for another (hunter-gatherer societies being classic examples of fission-fusion societies).

Students of human evolution, while differing as to what were the key selective contexts, or the key adaptations, all agree that human evolution has been characterized by remarkable levels of within-group cooperation among unrelated individuals, on a scale not seen in any non-human animal. Several contexts stand out as crucial for the high level of cooperation found in hunter-gather societies. They begin, of course, with hunting and gathering. Effective group hunting (usually done by men) requires sharing of information about distant prey and discussion of strategies for capturing prey. In essentially the same way, gathering of plants and fruits (usually done by women) requires the ability to track the growing schedules and locations of many plants and fruits in the area and the ability to discuss and coordinate foraging activities efficiently. Furthermore, hunter-gatherer societies periodically have to pick up and move to a new, more abundant locale. These moves require discussion and group consensus, with input from all parties, especially older, more experienced men and women.

A second, equally important axis of cooperation is child-raising. Humans are unique among primates in the time and cost required to raise an offspring. Humans solved this problem by involving the whole group in the process. Hrdy (2009) has pointed out that this pattern of cooperative breeding sets humans apart from the exclusive mother-centered parenting of our closest relatives, the great apes. In these early human societies, many individuals played a role in the cooperative care. For starters, the whole group participated in that food brought back to the camp was typically shared among all individuals, without reference to their role in procuring the food. Then unlike most mammals, the father participated in child care alongside the mother. Other relatives were routinely involved in direct child care, especially older siblings and grandparents, often aunts and uncles too, and sometimes non-relatives as well.

Finally, within-group cooperation is essential for success in between-group competition, warfare in particular. This aspect of our hunter-gather heritage is strongly debated in anthropology. Using the terms of Lee (2018) , the Peaceful school views significant inter-group competition as not beginning until the Agricultural era, when property gave humans something to fight over. The Bellicose school (e.g., Kelly, 2000 ; Gat, 2015 ) believes inter-group competition dates further back in our evolutionary past. But whenever it started, warfare would certainly promote adaptations for within-group cooperation.

In recent years various investigators have proposed key adaptations that may have allowed human societies to achieve this high level of cooperation in the absence of the glue of a very high level of kinship. Although there is not complete agreement as to which of these adaptations were most crucial, taken together they coalesce into a suite of psychological adaptations that promote prosocial within-group interactions within a context of near-complete interdependence. Indeed, Tomasello et al. (2012) have dubbed this the Interdependence hypothesis. The specific adaptations include: shared intentionality ( Tomasello et al., 2005 ), egalitarianism ( Boehm, 1999 ), social learning and communication ( Herrmann et al., 2007 ), intersubjectivity and empathy ( Hrdy, 2009 ), moral intuitions ( Haidt, 2012 ), adaptations for teaching and receiving teaching, and thus cultural transmission ( Sterelny, 2012 ; Henrich, 2016 ; Whiten, 2017 ), proactive aggression ( Wrangham, 2018 ) and self-domestication ( Wrangham, 2019 ). These adaptations of our social mind appear to be what set us apart from the other great apes, who it has been argued are otherwise just as cognitively advanced ( Herrmann et al., 2007 ). This suite of adaptations has enabled us to live in complex, cooperative societies. Despite our equally extraordinary proactive (deliberate and planned) aggressive tendencies, directed typically at out-groups, as in wars, pogroms, crusades and the like ( Wrangham, 2018 ), no other social animal has achieved the level of within-group docility and cooperation without high within-group relatedness that is found in the human species. I note that Knight (2018) has an advanced an argument similar to the one I have presented here.

Language unquestionably represents the pinnacle of evolved animal communication systems, and as noted at the beginning of this section, attempts to teach language to animals have not significantly changed this view. Language is often given pride of place in human evolution. In this view the other adaptations mentioned above came only after some form of language was in place. I favor the view of Hrdy (2009) , that this may well reverse cause and effect. The evolution of language may have only become possible when the posited unique suite of prosocial, communicative and mind-reading adaptations were in place. The crucial importance of communication in the strongly interdependent social system of early humans would have created this prosocial suite of adaptations, and would have laid the groundwork for evolving a true language.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

Many thanks to editor IP, three reviewers, John Byers, Doug Mock, Trish Schwagmeyer, and Bill Searcy for their very thoughtful reviews of the manuscript.

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Keywords : animal communication, language evolution, animal cognition, animal language studies, information

Citation: Beecher MD (2021) Why Are No Animal Communication Systems Simple Languages? Front. Psychol. 12:602635. doi: 10.3389/fpsyg.2021.602635

Received: 03 September 2020; Accepted: 18 February 2021; Published: 19 March 2021.

Reviewed by:

Copyright © 2021 Beecher. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Michael D. Beecher, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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An Introduction to Animal Communication

The ability to communicate effectively with other individuals plays a critical role in the lives of all animals. Whether we are examining how moths attract a mate, ground squirrels convey information about nearby predators, or chimpanzees maintain positions in a dominance hierarchy, communication systems are involved. Here, I provide a primer about the types of communication signals used by animals and the variety of functions they serve. Animal communication is classically defined as occurring when “...the action of or cue given by one organism [the sender] is perceived by and thus alters the probability pattern of behavior in another organism [the receiver] in a fashion adaptive to either one both of the participants” (Wilson 1975). While both a sender and receiver must be involved for communication to occur (Figure 1), in some cases only one player benefits from the interaction. For example, female Photuris fireflies manipulate smaller, male Photinus fireflies by mimicking the flash signals produced by Photinus females. When males investigate the signal, they are voraciously consumed by the larger firefly (Lloyd 1975; Figure 2). This is clearly a case where the sender benefits and the receiver does not. Alternatively, in the case of fringe-lipped bats, Trachops cirrhosus , and tungara frogs, Physalaemus pustulosus , the receiver is the only player that benefits from the interaction. Male tungara frogs produce advertisement calls to attract females to their location; while the signal is designed to be received by females, eavesdropping fringe-lipped bats also detect the calls, and use that information to locate and capture frogs (Ryan et al . 1982). Despite these examples, there are many cases in which both the sender and receiver benefit from exchanging information. Greater sage grouse nicely illustrate such “true communication”; during the mating season, males produce strutting displays that are energetically expensive, and females use this honest information about male quality to choose which individuals to mate with (Vehrencamp et al . 1989).

Figure 1 A model of animal communication.

Figure 2:  Photinus fireflies. Courtesy of Tom Eisner.

Signal Modalities

Animals use a variety of sensory channels, or signal modalities, for communication. Visual signals are very effective for animals that are active during the day. Some visual signals are permanent advertisements; for example, the bright red epaulets of male red-winged blackbirds, Agelaius phoeniceus, which are always displayed, are important for territory defense. When researchers experimentally blackened epaulets, males were subject to much higher rates of intrusion by other males (Smith 1972). Alternatively, some visual signals are actively produced by an individual only under appropriate conditions. Male green anoles, Anolis carolinensis, bob their head and extend a brightly colored throat fan (dewlap) when signaling territory ownership. Acoustic communication is also exceedingly abundant in nature, likely because sound can be adapted to a wide variety of environmental conditions and behavioral situations. Sounds can vary substantially in amplitude, duration, and frequency structure, all of which impact how far the sound will travel in the environment and how easily the receiver can localize the position of the sender. For example, many passerine birds emit pure-tone alarm calls that make localization difficult, while the same species produce more complex, broadband mate attraction songs that allow conspecifics to easily find the sender (Marler 1955). A particularly specialized form of acoustic communication is seen in microchiropteran bats and cetaceans that use high-frequency sounds to detect and localize prey. After sound emission, the returning echo is detected and processed, ultimately allowing the animal to build a picture of their surrounding environment and make very accurate assessments of prey location. Compared to visual and acoustic modalities, chemical signals travel much more slowly through the environment since they must diffuse from the point source of production. Yet, these signals can be transmitted over long distances and fade slowly once produced. In many moth species, females produce chemical cues and males follow the trail to the female’s location. Researchers attempted to tease apart the role of visual and chemical signaling in silkmoths, Bombyx mori , by giving males the choice between a female in a transparent airtight box and a piece of filter paper soaked in chemicals produced by a sexually receptive female. Invariably, males were drawn to the source of the chemical signal and did not respond to the sight of the isolated female (Schneider 1974; Figure 3). Chemical communication also plays a critical role in the lives of other animals, some of which have a specialized vomeronasal organ that is used exclusively to detect chemical cues. For example, male Asian elephants, Elaphus maximus , use the vomeronasal organ to process chemical cues in female’s urine and detect if she is sexually receptive (Rasmussen et al . 1982).

Figure 3 Male silkmoths are more strongly attracted to the pheromones produced by females (chemical signal) than the sight of a female in an airtight box (visual signal). Tactile signals, in which physical contact occurs between the sender and the receiver, can only be transmitted over very short distances. Tactile communication is often very important in building and maintaining relationship among social animals. For example, chimpanzees that regularly groom other individuals are rewarded with greater levels of cooperation and food sharing (de Waal 1989). For aquatic animals living in murky waters, electrical signaling is an ideal mode of communication. Several species of mormyrid fish produce species-specific electrical pulses, which are primarily used for locating prey via electrolocation, but also allow individuals searching for mates to distinguish conspecifics from heterospecifics. Foraging sharks have the ability to detect electrical signals using specialized electroreceptor cells in the head region, which are used for eavesdropping on the weak bioelectric fields of prey (von der Emde 1998).

Signal Functions

Some of the most extravagant communication signals play important roles in sexual advertisement and mate attraction. Successful reproduction requires identifying a mate of the appropriate species and sex, as well as assessing indicators of mate quality. Male satin bowerbirds, Ptilonorhynchus violaceus , use visual signals to attract females by building elaborate bowers decorated with brightly colored objects. When a female approaches the bower, the male produces an elaborate dance, which may or may not end with the female allowing the male to copulate with her (Borgia 1985). Males that do not produce such visual signals have little chance of securing a mate. While females are generally the choosy sex due to greater reproductive investment, there are species in which sexual roles are reversed and females produce signals to attract males. For example, in the deep-snouted pipefish, Syngnathus typhle , females that produce a temporary striped pattern during the mating period are more attractive to males than unornamented females (Berglund et al . 1997). Communication signals also play an important role in conflict resolution, including territory defense. When males are competing for access to females, the costs of engaging in physical combat can be very high; hence natural selection has favored the evolution of communication systems that allow males to honestly assess the fighting ability of their opponents without engaging in combat. Red deer, Cervus elaphus , exhibit such a complex signaling system. During the mating season, males strongly defend a group of females, yet fighting among males is relatively uncommon. Instead, males exchange signals indicative of fighting ability, including roaring and parallel walks. An altercation between two males most often escalates to a physical fight when individuals are closely matched in size, and the exchange of visual and acoustic signals is insufficient for determining which animal is most likely to win a fight (Clutton-Brock et al . 1979). Communication signals are often critical for allowing animals to relocate and accurately identify their own young. In species that produce altricial young, adults regularly leave their offspring at refugia, such as a nest, to forage and gather resources. Upon returning, adults must identify their own offspring, which can be especially difficult in highly colonial species. Brazilian free-tailed bats, Tadarida brasiliensis , form cave colonies containing millions of bats; when females leave the cave each night to forage, they place their pup in a crèche that contains thousands of other young. When females return to the roost, they face the challenge of locating their own pups among thousands of others. Researchers originally thought that such a discriminatory task was impossible, and that females simply fed any pups that approached them, yet further work revealed that females find and nurse their own pup 83% of the time (McCracken 1984, Balcombe 1990). Females are able to make such fantastic discriminations using a combination of spatial memory, acoustic signaling, and chemical signaling. Specifically, pups produce individually-distinct “isolation calls”, which the mother can recognize and detect from a moderate distance. Upon closer inspection of a pup, females use scent to further confirm the pup’s identity. Many animals rely heavily on communication systems to convey information about the environment to conspecifics, especially close relatives. A fantastic illustration comes from vervet monkeys, Chlorocebus pygerythrus , in which adults give alarm calls to warn colony members about the presence of a specific type of predator. This is especially valuable as it conveys the information needed to take appropriate actions given the characteristics of the predator (Figure 4). For example, emitting a “cough” call indicates the presence of an aerial predator, such as an eagle; colony members respond by seeking cover amongst vegetation on the ground (Seyfarth & Cheney 1980). Such an evasive reaction would not be appropriate if a terrestrial predator, such as a leopard, were approaching.

Figure 4 Vervet monkeys. Many animals have sophisticated communication signals for facilitating integration of individuals into a group and maintaining group cohesion. In group-living species that form dominance hierarchies, communication is critical for maintaining ameliorative relationships between dominants and subordinates. In chimpanzees, lower-ranking individuals produce submissive displays toward higher-ranking individuals, such as crouching and emitting “pant-grunt” vocalizations. In turn, dominants produce reconciliatory signals that are indicative of low aggression. Communication systems also are important for coordinating group movements. Contact calls, which inform individuals about the location of groupmates that are not in visual range, are used by a wide variety of birds and mammals. Overall, studying communication not only gives us insight into the inner worlds of animals, but also allows us to better answer important evolutionary questions. As an example, when two isolated populations exhibit divergence over time in the structure of signals use to attract mates, reproductive isolation can occur. This means that even if the populations converge again in the future, the distinct differences in critical communication signals may cause individuals to only select mates from their own population. For example, three species of lacewings that are closely related and look identical are actually reproductively isolated due to differences in the low-frequency songs produced by males; females respond much more readily to songs from their own species compared to songs from other species (Martinez, Wells & Henry 1992). A thorough understanding of animal communication systems can also be critical for making effective decisions about conservation of threatened and endangered species. As an example, recent research has focused on understanding how human-generated noise (from cars, trains, etc) can impact communication in a variety of animals (Rabin et al . 2003). As the field of animal communication continues to expand, we will learn more about information exchange in a wide variety of species and better understand the fantastic variety of signals we see animals produce in nature.

Vomeronasal organ – auxiliary olfactory organ that detects chemosensory cues

Altricial – the state of being born in an immature state and relying exclusively on parental care for survival during early development

Refugia – areas that provide concealment from predators and/or protection from harsh environmental conditions

Conspecifics – organisms of the same species

References and Recommended Reading

Balcombe, J.P. Vocal recognition of pups by mother Mexican free-tailed bats, Tadarida brasiliensis mexicana . Animal Behaviour 39 , 960-966 (1990). Berglund, J., Rosenqvist G. and Bernet P. Ornamentation predicts reproductive success in female pipefish. Behavioral Ecology and Sociobiology 40 , 145-150 (1997). Clutton-Brock, T., Albon S., Gibson S. & Guinness F. The logical stag: Adaptive aspects of fighing in the red deer. Animal Behaviour 27 , 211-225 (1979). de Waal F.B.M. Food sharing and reciprocal obligations among chimpanzees. Journal of Human Evolution 18 , 433–459 (1989).

Hauser, M. 1997. The Evolution of Communication . Cambridge, MA: MIT Press. Lloyd, J.E. Aggressive mimicry in Photuris: signal repertoires by femmes fatales. Science 197 , 452-453 (1975).

Marler, P. Characteristics of some animal calls. Nature 176 , 6-8 (1955). Martinez Well, M. & Henry C.S. The role of courtship songs in reproductive isolation among populations of green lacewings of the genus Chrysoperla . Evolution 46 , 31-43 (1992). McCracken, G.F. Communal nursing in Mexican free-tailed bat maternity colonies. Science 223 , 1090-1091(1984).

Rabin, L.A., McCowan B., Hooper S.L & Owings D.H. Anthropogenic noise and its effect on animal communication: an interface between comparative psychology and conservation biology. International Journal of Comparative Psychology 16 , 172-192 (2003). Ryan M.J., Tuttle M.D., & Rand A.S. Sexual advertisement and bat predation in a neotropical frog. American Naturalist 119 , 136–139 (1982). Schneider, D. The sex attractant receptors of moths. Scientific American 231 , 28-35 (1974). Seyfarth, R.M., Cheney D.L. & Marler P. Monkey responses to three different alarm calls: Evidence for predator classification and semantic communication. Science 210 , 801-803 (1980). Smith, D. The role of the epaulets in the red-winged blackbird, ( Agelaius phoeniceus ) social system. Behaviour 41 , 251-268 (1972).

Vehrencamp, S.L., Bradbury J.W., & Gibson R.M. The energetic cost of display in male sage grouse. Animal Behaviour 38 , 885-896 (1989). von der Emde, G. Electroreception. In D. H. Evans (ed.). The Physiology of Fishes , pp. 313-343. Boca Raton, FL: CRC Press (1998). Wilson, E.O. Sociobiology: The New Synthesis . Cambridge, MA: Harvard University Press (1975).

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• v.375(1789); 2020 Jan 6

Animal cognition and the evolution of human language: why we cannot focus solely on communication

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Studies of animal communication are often assumed to provide the ‘royal road’ to understanding the evolution of human language. After all, language is the pre-eminent system of human communication: doesn't it make sense to search for its precursors in animal communication systems? From this viewpoint, if some characteristic feature of human language is lacking in systems of animal communication, it represents a crucial gap in evolution, and evidence for an evolutionary discontinuity. Here I argue that we should reverse this logic: because a defining feature of human language is its ability to flexibly represent and recombine concepts, precursors for many important components of language should be sought in animal cognition rather than animal communication. Animal communication systems typically only permit expression of a small subset of the concepts that can be represented and manipulated by that species. Thus, if a particular concept is not expressed in a species' communication system this is not evidence that it lacks that concept. I conclude that if we focus exclusively on communicative signals, we sell the comparative analysis of language evolution short. Therefore, animal cognition provides a crucial (and often neglected) source of evidence regarding the biology and evolution of human language.

This article is part of the theme issue ‘What can animal communication teach us about human language?’

1. Introduction

I have not, to my knowledge, spoken the word ‘octopus’ today or indeed in the past week, but no one would therefore conclude that I lack the concept OCTOPUS (here I follow the philosopher's convention, when necessary, of denoting conceptual representations in capital letters). Indeed, I have spent many hours observing these creatures and read books about them but, like most of my mental concepts, OCTOPUS goes unexpressed in my speech most of the time. This is not only true of concepts captured by single words (like ‘octopus’, ‘chartreuse’, ‘quasar’ or ‘exponent’) but for more complex cognitive constructs that I possess (like how to walk from the Jardin de Luxembourg to the Place Stravinsky in Paris, via Notre Dame) but have never spoken at all. Humans possess many concepts, within individual minds, that go unexpressed via their language output for long periods of time (and some may never be expressed verbally). However, my assumption in what follows is that pretty much any human concept could be expressed in language, with perhaps hours or days of effort, and with varying degrees of accuracy, difficulty and concision. This capability to express any concept goes far beyond what any other species can do.

In what follows, I will take the basic observation that most concepts go unexpressed as axiomatic and argue that the same is true regarding animal communication, only more so (using ‘animal’ as shorthand for ‘non-human animal’ hereafter). For at least in principle, I might, under some circumstances, exclaim ‘Octopus!’ (e.g. when seeing one unexpectedly) or tell you the way to the Place Stravinsky (if you asked me), providing evidence that I indeed possess these concepts. By contrast, it is the nature of all known animal communication systems that they allow their bearers to express only a small subset of the concepts they can remember, represent and manipulate productively (cf. [ 1 ]). For example, honeybees have excellent colour vision and can remember the colours of the flowers they visit, but the honeybee dance ‘language’ allows a forager to communicate only the spatial location of the flower and has no provision for expressing colour information. I will provide evidence for this below and review similar evidence for other species, including non-human primates. I conclude that animal communication systems appear to be intrinsically limited to a smallish set of fitness-relevant messages that relate to such factors as food, danger, aggression, appeasement or personal prowess. But a substantial literature in animal cognition reveals that they know much more than this, even if they have no way of saying it [ 2 ].

The core argument is that, just as a person's utterances reveal only a subset of what they know, animal communication signals express an intrinsically limited subset of that species' conceptual storehouse. The argument that most thoughts are not expressed is by no means new: it follows Jackendoff's (2002) model of linguistic semantics closely and is also consonant with Chomsky's model [ 3 , 4 ]. Both Hurford [ 2 ] and Bickerton [ 5 ] have explored its implications for language evolution at book length [ 2 , 5 ], as have I more briefly [ 1 ]. My aim here is simply to argue this crucial point sharply and concisely, for although these ideas should not be controversial, they are rejected by some prominent philosophers, and even when accepted, their implications are ignored in many recent discussions of language evolution (e.g. [ 6 , 7 ]).

The central implication of my thesis is that the field of animal cognition has a very important role to play in our understanding of human language evolution because the fact that animals have concepts (whether expressible via signalling or not) erases a potentially gaping evolutionary chasm that would exist if they did not. Apparent discontinuities between humans and animal cognition that ‘pose a severe challenge for evolutionary explanation’ ([ 6 ], p.3), may in fact be based on discontinuities between language and other species' communication systems. This elision between two different things—cognition and communication—is at best misleading and often pernicious. The study of animal communication is indeed important for comparative analysis of language evolution, most obviously relevant for factors involved in externalization, such as vocal learning, speech perception and gestural communication. But to get the full comparative picture, we need to embrace animal cognition as a central and in some cases the central source of information relevant to the biology and evolution of language (and human cognition more generally).

2. Words ≠ concepts

Before discussing animals, it is important to first clarify some basic issues about the nature of human concepts, and to at least dip our toes into the philosophical quagmire surrounding the term ‘concept’ (for a concise introduction see [ 8 ]). My take on concepts in this essay will be essentially that of mainstream cognitive (neuro)science today, where a concept is simply ‘a nonlinguistic psychological representation of a class of entities in the world’ (Murphy [ 9 ], p. 335).

More specifically, my perspective is mentalistic and representationalist. I assume that concepts are mind-internal entities—‘representations’—that often, but not necessarily, correspond to some entities ‘out there’ in the world. It is physicalist: conceptual representations ultimately consist of neural activity in brains (they have no platonic existence, independent of minds). Finally, it is pluralistic, meaning that it allows for different types of concepts, some best captured by definitions, others by prototypes and still others as abilities to discriminate or act. Although much ink has been shed regarding the virtues and flaws of these different interpretations, both in cognitive science [ 9 ] and philosophy [ 10 – 13 ], precisely where one stands on these philosophical issues will have little relevance to my comparative argument here.

However, one central issue, illustrated in figure 1 , cannot be ignored, concerning a long-running philosophical debate between ‘mentalists’ (virtually all modern cognitive scientists) and ‘referentialist’ philosophers like Quine or Putnam [ 12 , 13 ]. Referentialists posit a direct referential linkage between utterances and their real-world referents. The referentialist doctrine was dominant in behaviourist psychology of language, which privileged observable behaviours (such as speaking words and pointing) over invisible mental constructs. But it has fallen by the wayside in modern cognitive science—at least regarding human language [ 3 , 14 ]. The alternative mentalist perspective (also termed the ‘internalist’ or ‘conceptualist’ perspective, [ 3 , 4 ]) holds that words do not refer directly to things in the world, but rather express our (mind-internal) concepts. To paraphrase Strawson ‘words don't refer, people refer’ [ 15 ]. The concepts we express linguistically may correspond to real entities in the world, but in many cases (e.g. ‘Sherlock Holmes’, ‘the unicorn in my dream’), they do not.

Mentalist model of concepts and meaning: contemporary cognitive scientists argue that words and sentences connection to their referents is indirect, and that reference requires the intervention of a (private) mental concept. Thus, an organism can have a concept (illustrated by the thought bubbles) independently of any words, sentences or other signals that express this concept. Referential links between real-world objects or events and non-verbal mental concepts (representations) can exist even if an organism has no means in its communication system to express those concepts.

The modern mentalist perspective in cognitive science sees acts of referring (e.g. by speaking) as being indirect. That is, reference involves two separable phenomena ( figure 1 ): first a mental representation of an entity is recognized, recalled or otherwise activated, and second some utterance is produced which may, if successful, elicit a similar though not identical mental representation in the listener. For example, observing a cat walk behind a tree, I may form a mental representation of CAT BEHIND TREE. This complex concept is the first step in reference: a correspondence between real-world events (e.g. visual patterns interpreted as cats and trees) and the resulting mental representation. Generating this particular non-verbal concept is accomplished by the visual system, is private, and (I argue below) essentially the same type of cognitive processing that occurs when a dog sees a cat go behind a tree (who perhaps indicates this knowledge by straining at its leash).

The second stage of reference—externalization—is the one with a public, perceivable component: under some circumstance, I may choose to say ‘there's a cat behind that tree’ or perhaps ‘hinter dem Baum ist eine Katze’ (in German). This second step in referring links my mental representation to some signal in English, German, American sign language, etc. Crucially, my mental representation is the same for either sentence (the very idea of translation—that different sentences in different languages can refer to the very same concept—assumes some language-independent conceptual world). Again the link between the concept CAT BEHIND TREE and either of these sentences is initially an internal matter, within the speaker's mind, and dependent on their personal conceptual and linguistic competences. However, if finally I utter one of these sentences, the utterance enters the public sphere and may cause an appropriately equipped listener to form their own mental representation CAT BEHIND TREE (probably different in detail from mine). Linguistic communication—concept sharing—has occurred.

This indirect model may sound overly complicated or obscure. We have a strong intuition that words themselves ‘mean things’ and sentences ‘refer’, regardless of whether anyone reads or understands them. This intuition about direct reference is hard to shake and still taken quite seriously by some philosophers. This may be because the intuition is biologically grounded, stemming from a ‘referential drive’ to interpret words as meaningful, part of the species-typical ‘instinct to learn’ that underpins child language acquisition [ 1 ]. For the child inferring word meanings, the simple notion that words mean things provides a useful shortcut to get the semantic system up and running. This intuition persists into adulthood, leading to superstitious beliefs (the magical powers of names or ritual chants). Despite providing a concise shorthand for denoting the more circuitous process detailed above, the referentialist intuition is completely inadequate as a full description of linguistic meaning [ 3 ]. Freeing ourselves from the shackles of this prescientific intuition is the first step to insightful scientific analysis.

Embracing this indirect, two-step nature of reference, I can now state my argument more clearly: the first stage of reference—building representations that tie sensory input to conceptual representations—is built upon a chassis of cognitive processes (sensory processing, recognition, categorization, combination and inference) that has fundamental shared components between humans and other animals. These components long predated language. The second stage of ‘externalization’—the capacity to form signals representing these non-verbal concepts—represents a crucial difference in humans and was one of the key innovations in human language evolution [ 16 ]. As Jackendoff puts it ‘phonology and syntax… evolved to express meaning, which has a far longer evolutionary pedigree’ ([ 3 ], p. 428).

It was once common to take a link between concepts and language as definitional, such that a ‘true’ concept must be linked to a word [ 17 , 18 ], but this traditional notion seems unsustainable in the face of infant research, where infants can clearly represent and reason about things they have no words for [ 19 – 22 ].

3. Do animals have concepts?

The considerations above lead most cognitive scientists to assume that the meanings of words and sentences are to be cashed out in non-linguistic mental representations: ‘concepts’ hereafter. However, the cognitive revolution remains incomplete: while few today deny the existence of internal mental representations (concepts) in humans, many remain suspicious when attributing them to animals. Animal cognition researchers are typically required to reject all possible associative explanations, regardless of their complexity, before attributing mental representations to animals [ 23 ] and the discipline spends considerable energy and ingenuity refuting so-called killjoy associative explanations [ 10 , 24 ]. Fortunately, the field has matured to the point where, for many phenomena, there can be little doubt that mental representations exist in animals, and can be recalled, manipulated and themselves represented [ 25 – 27 ].

Concepts should be, in some sense, general and flexible, and might initially be equated with mental ‘categories’. It is uncontested that birds and mammals learn and recall categories [ 28 , 29 ], but some have claimed that animal categories are little more than reflexes, reactively elicited in sensory cortices by sensory inputs and lacking the flexibility and generality of human concepts [ 18 , 30 ]. However, current data demonstrate that many species form cross-modal associations, showing that their categories are flexibly multi-modal [ 31 – 33 ]. Animals can summon categorical representations in the absence of relevant triggering stimuli, for instance seeking hidden food items at particular times, or re-hiding food items a potential thief saw them hide, in the absence of that thief [ 34 ]. They can compute abstract relationships like ‘same’ and ‘different’, for example, correctly choosing novel ‘same’ pairs when presented with two matched objects, and vice versa when given unmatched pairs [ 35 , 36 ]. Many species can compute transitive inferences: knowing that if A > B and B > C, then A must be greater than C as well [ 37 – 39 ]. These data fulfil the philosophers' desideratum that (animal) concepts should be more than unimodal, reflexive, stimulus-driven dispositions to react appropriately: they have an abstract categorical and relational structure.

A sceptical philosopher might still object that however impressive these cognitive abilities are, they do not ‘really’ constitute concepts. Concepts require not just categorization (first-order representations), but a second-order representation of that knowledge: knowing that (or doubting that, or being surprised that) some perceptual object belongs to the category. Animal concepts are limited, philosophers like Davidson argue, to first-order representations [ 40 ]. The most telling evidence against this ‘first-order’ view comes from studies on ‘metacognition’, where animals exhibit an understanding of their own conceptual representations (beliefs about beliefs). If uncertain about their own knowledge, they will choose a ‘don't know’ response, for lesser reward, rather than guessing [ 41 ]. Most research in this experimental paradigm been done on rhesus macaques but related work documents metacognition in dolphins, rats and pigeons (cf. [ 42 ]). Such experiments involve a response to some discrimination task, yielding a food reward, but an additional response is allowed for uncertain cases, often glossed as ‘I don't know’. The animal can choose the ‘don't know’ option when uncertain, receiving a smaller food reward than they would receive for a correct answer, but no punishment. Typically, in situations of high uncertainty (e.g. stimuli ambiguous from a human perspective), animals in these experiments choose the ‘uncertain’ button.

Although some critics have suggested that animals in such experiments simply form a new perceptual category (e.g. ‘unfamiliar’) and pushing the button for this, this possibility can be ruled out in most of the primate experiments (for the refutation of this and other ‘killjoy’ hypotheses, cf. [ 43 ]). Recent experiments are most compelling. Monkeys are first trained on one set of experimental stimuli, for example, based on colour discrimination, to learn the ‘don't know’ option. If this response was really tied to perceptual cues (e.g. colour) about the training stimuli, there should be no carry-over of this third option to novel stimulus sets. Instead, monkeys immediately transfer their appropriate use of the third option to novel situations (e.g. area discrimination) or even from past (retrospective) judgements to future (prospective) judgements [ 44 ]. This strongly suggests that the animals truly doubt their knowledge (represent their own uncertainty) and can transfer a response based on this meta-knowledge to novel situations. These and other data have convinced even previous sceptics that animals possess representations about representations, and therefore ‘concepts’ in this more demanding Davidsonian sense [ 45 ]. Of course, human metacognition is more sophisticated, involving thoughts about thoughts about thoughts… But that fact provides no empirical grounds to deny basic second-order metacognition to other animals. Given these modern data, denials that animals possess basic non-verbal concepts seem misinformed and anti-scientific (e.g. [ 30 ]).

I hasten to add that my claim here is not that animal concepts are of the same complexity or flexibility as those of humans. That would be absurdly anthropomorphic and would ignore the fact that language, as a multi-component system [ 16 ], also includes recursive compositional machinery that allows us to flexibly combine basic concepts into complex, hierarchically structured thoughts. This compositionality is a key component of linguistically structured thought, independent of externalization. Indeed, Chomsky terms it the ‘Basic Property’ of language and argues that it was selected in the human lineage precisely for its value in structuring internal thought, rather than externalizing these thoughts via speech [ 4 , 46 ]. There is at present little evidence of complex compositionality in animal communication or cognition (beyond things like transitivity, discussed below) [ 47 ]. But crucially, if we want to understand the evolution of this component, the appropriate starting point is animal conceptual abilities, and cannot be limited to the signals animal produce.

I now turn to the empirical data supporting my main contention that animals possess more concepts than their communication systems allow them to express. For reasons of space and concision, this is a very selective review—the data are so abundant that a full treatment requires an entire book (for this I recommend [ 2 , 29 ]). I will thus focus on a few examples from clever species, like primates and dolphins, plus honeybees, because these are well documented in easily accessible publications.

4. Animal signals ≠ animal concepts

To empirically demonstrate that a species can conceptualize more than they can express requires both an understanding of their communication system and independent data concerning their cognition. A nice example to start with is the honeybee Apis mellifera , in which communication and cognition are well-studied. The honeybee communication system allows a forager who has discovered flowers, upon returning to the hive, to inform other foragers of their location [ 48 , 49 ]. In the darkness of the hive, the bee performs a stereotyped (and apparently innate) ‘waggle dance’ whose direction, relative to gravity, signals the azimuth direction of the flowers (relative to the sun). The duration of the waggle portion correlates with the distance to the flowers, and by combining these cues, the dance provides a remarkably accurate indication of the location of these flowers. This system is also remarkable in ‘referring’ to an entity not currently present or visible to the communicators (thus sharing the property of ‘displacement’ with human language; [ 50 ]). Finally, the system is flexible, because a honeybee can ‘refer’ to the location of other objects than flowers when necessary, for instance, water or a new nest-site (I put ‘refer’ in quotes to avoid philosophical debate—I simply mean that a honeybee's dance reliably allows naive honeybees to locate the object in question).

Despite this impressive communication system, detailed studies of honeybee cognition reveal even more impressive cognitive abilities (reviewed in [ 51 ]). For example honeybees have excellent colour vision and can remember the colour of rewarding versus unrewarding nectar sources over days [ 52 , 53 ]. Nonetheless, their dance ‘language’ has no way to communicate colour information. Even more impressive, a honeybee can judge whether two stimuli are the same or different in colour or pattern [ 54 ] and generalize this behaviour to novel modalities (trained on colour, she immediately transfers the same/different decision to patterns or vice versa). Again, however, the honeybee dance language lacks signals for ‘same’ or ‘different’. Thus, even an insect whose brain occupies 1 mm 3 and contains less than a million neurons has cognitive abilities that significantly outstrip its ability to communicate them.

Turning now to a large-brained species, the bottlenose dolphin Tursiops truncatus is another species for which we have solid data about both cognition and communication. Dolphins have sophisticated cognitive abilities rivalling those of non-human primates [ 31 ]. They rapidly learn a ‘delayed match-to-sample’ task and generalize across hundreds of novel sounds [ 55 ]. Dolphins can remember lists of items (spatial locations, visual objects or sounds), correctly indicating whether a probe stimulus was or was not in the list, and show a classic recency effect, like humans [ 31 ]. Dolphins show cross-modal integration, matching visually and acoustically perceived (via echolocation) object shapes, and show mirror self-recognition, inspecting themselves in a mirror when marked in an otherwise invisible location (and not doing so when sham-marked). Dolphins readily learn to interpret human signals, whether gestural (e.g. pointing) or auditory [ 56 ] and can understand novel combinations of signals (‘sentences’ made up of multiple gestures or sounds) on the first try, based on a simple order-based grammar (e.g. responding correctly to ‘take the hoop to the ball’ versus ‘take the ball to the hoop’). Dolphins can understand the abstract command ‘create’ indicating ‘do something novel’ by performing some new action or ‘repeat’ to perform the act again (thus requiring the dolphin to keep track of what it itself had done). All of these data indicate that dolphins have a flexible, productive capacity to learn, can self-monitor and can retain and manipulate novel concepts across multiple modalities.

However, turning to bottlenose dolphins' well-studied communication system, we get a very different picture. Early studies indicated a quite complex vocal communication system, and the ability of dolphins to learn human words suggested that they might have a ‘language’ of their own [ 57 ]. These suggestions led to careful experiments attempting to understand dolphin communication via observation and playback experiments that, on the contrary, suggested an ordinary mammalian repertoire of vocal signals [ 58 ], with the exception that dolphins are vocal learners and readily learn to mimic both conspecific and human-generated sounds [ 31 , 59 , 60 ]. Vocal learning is put to use in a ‘signature whistle’ system: dolphins emit an individual-specific whistle pattern (for example, when captured) that can be imitated by other dolphins, leading to exchanges and reuniting of separated animals [ 61 ]. Young dolphins initially acquire their whistles, by imitation [ 62 , 63 ]. Although this is an interesting system, with a capacity to signal individuals (reminiscent of ‘names’), it appears to be the most productive aspect of their vocal system.

The evidence against greater expressive ability comes from experiments where two dolphins are allowed to communicate vocally while solving a joint task [ 64 – 66 ]. Individual dolphins readily learn to push on a right or left paddle depending on a visual signal. With more training, two dolphins who can see each other can learn a social version: a signal perceived by one dolphin must be responded to by the other dolphin first, and only afterwards by the second, to provide a food reward to both. The crucial experimental condition involves blocking visual contact between the two individuals. If dolphins possessed a flexible language-like communication system, it should be a simple matter to signal ‘push the left one’ and succeed. Although initial experiments suggested this [ 64 ], more careful follow-up studies showed that these initial successes did not reflect anything language-like. When the roles were reversed (so that the former responder had to become the signaller), the pair totally failed. Furthermore, when the contingency between signal and response was changed, the dolphins had to be retrained from scratch and were not able to simply switch vocal signals to indicate the other action. The researchers concluded that the initial success was a result of trial-and-error learning where incidental sounds made by one animal, or vocal sounds produced whether or not the other animal was present, were used to solve the task [ 58 , 65 ]. Bastian, who led this research project concisely concluded ‘No evidence was found to support the supposition that the social signalling of dolphins is capable of the transfer of arbitrary environmental information’ (p. iii, [ 65 ]). Summarizing, dolphins have very sophisticated cognitive and learning abilities, revealing complex internal concepts, but their capacity to communicate those concepts via their species-typical signals is quite limited.

5. Concepts and communication in primates

My final examples come from two non-human primate species—vervet monkeys and chimpanzees—but similar examples could be provided for many other well-studied primates.

Vervets Chlorocebus pygerythrus (previously Cercopithecus aethiops ) are small common African monkeys, possessing a suite of different alarm calls that are typically emitted in the presence of different predators [ 67 , 68 ]. The vervet monkey alarm call system is frequently cited as a potential precursor to language [ 10 , 69 ]. However, the three different alarm calls produced to leopards, eagles and snakes in no way exhaust the concepts that vervets can represent. In addition to ‘standard’ primate concepts like individuality and dominance [ 70 ], vervets maintain complex spatial representations of their environment [ 71 ] and can mentally track the locations of hidden group members [ 72 ]. They can socially learn how to access food and rapidly absorb new social preferences about what to eat based on colour [ 73 ]. None of this cognitive sophistication is in any way detectable in their vocal communication system.

Turning finally to our nearest living relatives, the chimpanzees and bonobos ( Pan troglodytes and Pan paniscus ), there is abundant evidence that chimpanzees have highly developed cognitive abilities and can represent basic concepts like colour and shape, as well as abstract concepts including sameness, location, and sequence [ 27 , 74 , 75 ]. Chimpanzees also have social representations including individual identity, dominance and relationships (e.g. ‘child of’) and are capable of transitive inference [ 76 ]. With extensive training, very abstract concepts like number are within their cognitive reach [ 77 , 78 ]. They show at least the beginnings of theory of mind, in that they can represent what competitors do or do not see [ 79 ]. Their tool-using abilities are sophisticated and incorporate future planning [ 80 ]. When trained intensively with human communication systems, they can understand multi-word sentences and indicate an impressive variety of objects and events [ 81 , 82 ] and exhibit flexible cross-modal transfer of information without further training [ 83 ]. In general then, chimpanzees exhibit some of the most sophisticated cognitive abilities known among animals—unsurprising given their close biological relationship to humans.

By contrast, chimpanzee vocal communication is comparable to that seen in many other primates or mammals, with a small repertoire of 30-odd innate vocalizations [ 84 ] including food calls that differ for different food quality [ 85 , 86 ], screams and threats, and complex display calls like pant-hoots [ 87 ]. Chimpanzees are not known to have predator-specific alarm calls like vervets. Their gestural communication system is considerably richer, and perhaps more intentionally informative than their vocal communication [ 88 – 90 ]. But both their vocal and gestural communication skills pale in comparison to their rich and sophisticated cognitive abilities. Cognitive studies demonstrate beyond a reasonable doubt that chimpanzees possess many concepts that their species-typical communication systems cannot express (nor indeed do the utterances of ‘language trained’ chimpanzees come close to expressing the complexity of concepts like number, transitivity or tool use [ 82 , 91 ]). Thus, chimpanzees clearly possess and manipulate concepts that they are unable to communicate. Even the most exhaustive analysis of chimpanzee communication would vastly underestimate the complexity of their non-verbal conceptual world.

It is crucial not to conflate these communicative limitations with the false but frequently repeated claim that primates (or animals more generally) have no voluntary control over their vocalizations. A sizeable body of data clearly demonstrates that they do (cf. [ 92 ]). For example, in the wild, many species (including chickens and monkeys) exhibit ‘audience effects,’ producing vocalizations only when appropriate listeners are around [ 70 , 93 , 94 ], and chimpanzee screams and alarm vocalizations are clearly modulated by the presence and composition of the audience [ 95 , 96 ]. Several bird species produce ‘false’ alarm calls when no predator is present, frightening away competitors and then taking remaining food [ 97 , 98 ]. In an operant setting in the laboratory, numerous studies have demonstrated voluntary production (or inhibition) of vocalizations on command [ 97 , 98 ] in chimpanzees, other primates [ 99 , 100 ] and various other mammals (e.g. cats and dogs, [ 101 ]). Thus, despite a common misconception, animal vocalizations are not reflexive actions, performed inevitably upon the appearance of some external stimulus; but this fact does not imply that their vocalizations provide exhaustive access to their conceptual world.

6. Conclusion: discontinuities in signalling do not indicate cognitive discontinuities

I end by clarifying the key implication of this essay: when considering the evolution of human cognition, we will be fundamentally misled if we attribute to animals only those concepts they can communicate. Externalization of concepts is just one component of language, and another is to help structure our private internal thought [ 4 ]. Thus, we cannot accurately limit our estimation of what humans know to what they say . The same is true of animals, only more so. The flexibility of human language means that we can use it to represent virtually anything we can think (perhaps with considerable effort, in the case of visual, musical or highly abstract concepts). The same flexibility and expressivity is simply not present in animal communication systems. This limitation, rather than any fundamental non-existence of animal concepts, was surpassed by humans during language evolution. Thus, our (linguistic) ability to refer, not our basic ability to conceptually represent, must be explained if we hope to understand the neural and ultimately genetic basis of human language.

This is not to deny that externalized language gives humans a huge conceptual advantage over other species. We acquire many concepts via language that we have no direct access by personal experience, vastly enlarging our potential store of knowledge (some readers may never have personally seen an octopus, but most will nonetheless have some concept OCTOPUS). Blind people, thanks to language, have surprisingly rich conceptions of colour terms [ 102 ], and many abstract or scientific terms such as ‘electron’ or ‘truth’ have no sensory manifestations at all. My argument is not that animals have precisely the same concepts as humans (that would be absurd, because even individual humans do not share precisely the ‘same’ concepts, figure 1 ). My argument concerns the neural and cognitive machinery underlying the formation of mental representations, along with many of the cognitive processes that allow concepts to be formed based on sensory experience and combined at a basic level. These capabilities are shared across species and were therefore present before language evolved and provided the precursors of more complex human concepts.

In many circumstances, the study of animal communication can provide crucial insights into what animals know and remains an important part of comparative investigation of language evolution. But accepting the fundamental fact that animals know much more than they can express implies that the evolution of human language built upon a pre-existing conceptual apparatus much richer than that observable in animal communicative capabilities. It is therefore critical that future scholarly explorations of human language evolution take results from animal cognition research as crucial data for understanding the evolutionary path to human language. Even more crucial is a dedicated research programme to explore in detail animals' abilities to combine concepts. To the extent that they can do so in a flexible, hierarchical manner [ 103 , 104 ], I think we can see the germs of the recursive symbolic system that underlies human linguistic concepts.

Acknowledgements

This essay is dedicated to the fundamental contributions to the study of both animal cognition and communication made by Dorothy Cheney (1950–2018). The author thanks Gesche Westphal-Fitch, Barry Smith and two anonymous reviewers for comments on previous drafts, and Nadja Kavcik for her help with the figure.

Data accessibility

Competing interests.

The author declares that he has no competing interests.

Preparation of this paper was supported by Austrian Science Fund (FWF) DK Grant ‘Cognition & Communication’ (grant no. W1262-B29).

International Journal of Comparative Psychology

Animal Communication and Human Language: An overview

• Barón Birchenall, Leonardo

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Comparative research has proven to be a fruitful field of study on the ontogenetic and phylogenetic evolution of language, and on the cognitive capacities unique to humans or shared with other animals. The degree of continuity between components of human language and non-human animal communication systems, as well as the existence of a core factor of language, are polemic subjects at present. In this article, we offer an overview of the research on animal communication, comparing the resulting data with the current knowledge on human language development. We try to summarize what is currently known about “language abilities” in multiple animals, and compare those facts to what is known about human language. The aim of the article is to provide an introduction to this particular topic, presenting the different sides of the arguments when possible. A special reference is made to the question of syntactic recursion as the main component of language, allegedly absent among non-human animals. We conclude that the current state of knowledge supports the existence of a certain degree of continuity between different aspects of animal communication and human language, including the syntactic domain.

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Animals, ethics, and language: the philosophy of meaningful communication in the lives of animals.

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Nithin Varghese, Animals, Ethics, and Language: The Philosophy of Meaningful Communication in the Lives of Animals, The Philosophical Quarterly , 2024;, pqae057, https://doi.org/10.1093/pq/pqae057

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I have always loved animals, from cats and dogs to the amazing creatures I see in documentaries. However, as a kid, there was nothing quite like cartoons to capture my imagination. Tom & Jerry was one of my favorites. Even though they were a cat and a mouse, they acted just like people, walking on two legs, wearing clothes, and getting super frustrated with each other. Tom, the cat, was always bigger and seemed smarter, but Jerry, the little mouse, always outsmarted him in the end. It got me thinking: were Tom and Jerry just regular animals acting like people, or was there more to them? This curiosity led me to read Humphreys’ Animals, Ethics, and Language: The Philosophy of Meaningful Communication in the Lives of Animals , and it completely transformed my perspective on human-animal relations.

Humphreys’ Animals, Ethics, and Language is groundbreaking. It explores the complex relationship between humans and animals, focusing on anthropomorphism and its impact on various philosophical and scientific disciplines. The book is meticulously structured, beginning with an interesting Introduction that sets the stage for the subsequent chapters. Each chapter unfolds with a blend of historical insights and contemporary debates, providing a comprehensive examination of anthropomorphism and its implications.

Apart from this Introduction, the book comprises six chapters. The second chapter, “Anthropomorphous Animals and Philosophy”, explores the history of anthropomorphism, tracing its roots back to Ancient Greece. It discusses its relevance in contemporary debates on animal sentience and consciousness. Humphreys starts with an examination of the roots of anthropomorphism in Ancient Greek philosophy, citing Xenophanes’ critique of projecting human qualities onto divine beings (pp. 6–7). She also highlights the skepticism surrounding animal cognition in Cartesian philosophy and its continued influence on modern discourse (pp.12–20). This chapter sets the stage for the book's broader discussion on animal ethics, emphasizing the importance of understanding the historical and philosophical underpinnings of anthropomorphism and mechanomorphism in scientific discourse.

Chapter 3, “Moral Standing and Human Exceptionalism”, calls for a reassessment of our attitudes and treatment toward nonhuman beings. It delves into the philosophical complexities surrounding anthropomorphism, challenging the idea that anthropomorphic attributions are always conceptually and ontologically problematic (p. 25). Instead, it suggests that anthropomorphism arises from a broader understanding of animals and their minds (pp. 25–27). This chapter criticizes the mechanomorphic approach in the natural sciences, which strives for objectivity but can introduce biases that distort reality (pp. 31–33). It also discusses zoomorphism—“the view that ascribes (what are thought to be) nonhuman-like or animal-like qualities to human beings” (p. 33)—as a contrasting concept to anthropomorphism and explores intersectionality to demonstrate how all forms of oppression, including speciesism, are interconnected (pp. 33–40). Humphreys refers to “derogatory name-calling of particular groups of people, which dehumanizes them, portraying them as less than human” (p. 33). Examples include calling Jewish people “rats” and referring to women as “chicks” (p. 33).

Drawing on the work of Gordon Burghardt, Chapter 4, “Critical Anthropomorphism”, explores the attribution of human-like characteristics to animals and its philosophical implications. It calls for a discussion on the “tensions between current conceptions of anthropomorphic practice as problematic and what we know and can come to know about animals through evolutionary theory, natural history, bodily behaviour, and close observation” (p. 46). It revisits the writings of Hume and Montaigne, highlighting parallels with Darwin's views and emphasizing their relevance in contemporary debates (pp. 48–53). This chapter also discusses the intersection of anthropomorphism with phenomenology and embodiment, suggesting that these philosophical perspectives can enrich our understanding of animal consciousness (pp. 53–59).

Chapter 5, “Language and ‘Moral Anthropomorphism’”, delves into the complexities of communication with and between animals, focusing on the attribution of human-like characteristics to animals and its philosophical implications. This chapter discusses the communicative and perceptive skills of animals, highlighting the challenges in objectively evaluating their capacities (pp. 66–80). It concludes by challenging conventional views of language, suggesting that animals, particularly domestic ones, may have better language skills than commonly believed (pp. 91–96). The inclusion of illustrations throughout this chapter (p. 67, p. 69, pp. 72–78) enhances the message by visually demonstrating the importance of understanding animal behavior and avoiding misinterpretations caused by anthropomorphism.

Chapter 6, “Going Home: Returning from Posthumanism via a Defence of Identity as Continuity”, addresses key debates in critical animal studies (a field of study that explores the complex interactions and power dynamics between humans, nonhumans, society, and the environment, generally with an emphasis on critique and praxis, not just theory), particularly focusing on the term “identity theorists” (p. 105) and its potential misinterpretation (pp. 127–29). Humphreys uses the term “identity theorists” in the sense of ethicists who supposedly recognize the moral standing of nonhuman beings based on the features they share with human beings, so that all and only creatures that are similar to humans in certain respects are recognized as due direct moral consideration. This chapter explores the move toward a more inclusive normative stance, such as biocentrism, which argues that all living things have moral standing based on their interests. It challenges the notion of “identity” by developing a more nuanced notion of “continuity” between species, showing how this concept works in moral arguments (pp. 127–28). Humphreys utilizes the work of Frans de Waal, who defines anthropo-denial as “[t]he a priori denial of humanlike characteristics in other animals or animallike characteristics in humans” (p.104). She supports the position of Nina Varsava, a position of anthropo-insistence “that, by definition, stresses the similarities between humans and nonhumans and calls for anthropomorphism of the critical kind” (p. 128). This chapter also discusses the distinction between anthropo-insistence and anthropo-denial, highlighting the importance of understanding and avoiding anthropomorphic misattributions (pp. 121–28). It critiques posthumanism—philosophy that challenges the anthropocentric category of the human being often associated with humanism in the history of ideas—arguing that it perpetuates human-centric ways of thinking and fails to provide conceptual tools to move beyond anthropomorphism in animal ethics (pp. 128–31). Overall, the chapter concludes by advocating for a more nuanced and critical approach to human-animal relations, one that acknowledges the complexities of interspecies interactions while advocating for the protection and well-being of animals (pp. 132–35).

In the concluding chapter, “The Application of Key Concepts”, Humphreys discusses the application of key concepts related to animal consciousness, language, and the role of the body in understanding animal mentality. This chapter brings together themes from previous chapters such as “scepticism, communication, language, concepts, and the role of the body in relation to animal mentality” (p. 141). One of the main arguments in this chapter is that problems concerning animal consciousness and our understanding of it are fundamentally problems concerning “language and the description of animal mentality” (p. 141). Humphreys suggests that anthropomorphism is unavoidable when describing “the mental life of other than human animals in a way that avoids mechanomorphism” (p. 164). This chapter emphasizes the importance of “phenomenological methodology” and “folk psychology” in understanding non-human animals, calling for a reflection on our relationship with animals and their own lifeworlds (pp. 158–65). This reflection, while sometimes leading to misinformation, is seen as essential for “re-educat[ing] and rehabituat[ing] ourselves into being sensitive to animals’ communications and … to animal suffering” (p. 164). She concludes emphasizing the need for “an adequate ontology of a lifeworld with animals … and the moral implications of that construction” (p. 165) and calls for urgent action to address the suffering of animals.

This book is groundbreaking because it offers a unique approach to animal ethics. It combines philosophy, animal ethics, ethology, and critical animal studies to offer a unique perspective, moving beyond traditional ideas. Humphreys advocates for a return to fundamental ethical values while challenging the popular posthumanist perspective. She introduces the concept, “moral anthropomorphism” (p. 59), to address problematic views on the moral status of animals.

This book tackles complex topics related to human–animal relationships and ethics through rigorous intellectual discussion. Its strengths lie in its well-organized structure, extensive references, and formal academic tone, making it an excellent resource for scholars and anyone with a strong interest in animal ethics. However, this book's complexity and scholarly tone may pose challenges for casual readers. It could be strengthened by exploring the link between intensive farming, environmental problems, and the ethical treatment of animals in these contexts. Despite these limitations, the book offers a fresh perspective on animal studies, dispelling misconceptions, and advocating for a deeper understanding of animal sentience and communication. It is a thought-provoking read that inspires further exploration into the fascinating world of animal communication. Personally, as someone fascinated by the animal world, this book opened my eyes to new possibilities in interspecies interactions.

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Articles on Animal communication

Displaying 1 - 20 of 21 articles.

Are we really about to talk to whales?

Luke Rendell , University of St Andrews

Why don’t female crickets chirp?

Floyd W. Shockley , Smithsonian Institution

Fowl language: AI is learning to analyze chicken communications to help us understand what all the clucking’s about

Suresh Neethirajan , Dalhousie University

Do dog ‘talking buttons’ actually work? Does my dog understand me? Here’s what the science says

Susan Hazel , University of Adelaide and Eduardo J Fernandez , Florida Institute of Technology

Smell is the crucial sense that holds ant society together, helping the insects recognize, communicate and cooperate with one another

Laurence Zwiebel , Vanderbilt University and Stephen Ferguson , Vanderbilt University

Unlocking secrets of the honeybee dance language – bees learn and culturally transmit their communication skills

James C. Nieh , University of California, San Diego

Mini creatures with mighty voices know their audience and focus on a single frequency

Bernard Lohr , University of Maryland, Baltimore County

Allow me to introduce myself: Squirrels use rattle calls to identify themselves

Shannon M. Digweed , MacEwan University

Physics and psychology of cats – an (improbable) conversation

Beth Daley , The Conversation and Thalia Plata , The Conversation

Scientists at work: New recordings of ultrasonic seal calls hint at sonar-like abilities

Lisa Munger , University of Oregon

When dogs bark, are they using words to communicate?

Clive Wynne , Arizona State University

Animals that can do math understand more language than we think

Erik Nelson , Dalhousie University

Are you a cat whisperer? How to read Fluffy’s facial expressions

Lauren Dawson , University of Guelph

Can we really know what animals are thinking?

Jacob Beck , York University, Canada

Curious Kids: do cats and dogs understand us when we miaow or bark?

Quixi Sonntag , University of Pretoria

Eating royal poop improves parenting in naked  mole-rats

Gina Mantica , Tufts University

Studying chimpanzee calls for clues about the origins of human language

Michael Wilson , University of Minnesota

Are dogs trying to tell us something with their expressions?

Jan Hoole , Keele University

How to talk to your dog – according to science

Juliane Kaminski , University of Portsmouth

How the parrot got its chat (and its dance moves)

Larry Taylor , Northumbria University, Newcastle

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How do birds communicate? Northeastern network science models are opening up new possibilities for experts

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Iacopo Iacopini has been working closely with behavioral ecologists to help provide “new insights” into vocal communication among birds by mapping out how flock dynamics play out.

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LONDON — Nature-lovers will know the scene well. A flurry of birdsong, a shake of a tree and out pops a flock of birds flying away in unison together.

But how is it that the quick chatter of song among those birds led to that communal flight? A network scientist at Northeastern University in London has been helping experts to shed light on that question by mapping out how birds communicate when in groups.

Iacopo Iacopini , an assistant professor in the Network Science Institute , has been working closely with behavioral ecologists to provide “new insights” into vocal communication made by animals.

The research has been set out in Iacopini’s paper, “Not your private tête-à-tête: leveraging the power of higher-order networks to study animal communication,” published May 20 in the journal Philosophical Transactions of the Royal Society B: Biological Sciences.

Behavioral ecologists have for decades studied how one songbird is heard by another and then use that understanding to deduce how the one-to-one relationship functions — what is known as a dyadic interaction.

But experts knew that looking at it from that angle was overly simplistic when it is clear that a chirping bird will be heard by several birds in the surrounding vicinity.

Iacopini, along with colleagues from across the world, worked on modeling how birds interact with two or more others in theirs or rival flocks at the same time — what are referred to as higher-order networks.

The network scientists applied hypergraphs — a mathematical diagram showing how objects can have multiple connections simultaneously while in a group scenario — to better understand how light-bellied brent geese coordinate a group takeoff through increased squawks among the gaggle.

The scientists also did similar studies of the North American black-capped chickadees, creating a network to simulate the dawn chorus among what is a territorial family of birds in a bid to illustrate what interactions are occurring during that moment.

According to the five authors of the paper, mapping how these social structures play out has the potential to “reveal how vocal communication contributes to complex behavioral contagions within groups.”

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Iacopini said the trend among network scientists recently has been to focus on human interactions.

But he explained that the case studies he and his colleagues looked at for the paper in terms of non-human animal communication gave him a different kind of “playground” in which to map higher-order networks.

“Animals are another super important domain,” Iacopini said. “Network scientists are already doing a lot of stuff on animal behavior but, in my opinion, not as much as for human interactions.

“I think that the non-human animal world represents another incredibly good playground for these approaches, because you can ask a lot of questions, you can track them, you can record their vocalization, you can track their movements.”

Iacopini hopes that this paper and his experience collaborating with real-world wildlife data will encourage more partnerships between ecologists and network scientists.

“I personally would take this as a potential starting point for a lot of more research and projects on this leveraging,” he said.

“It is also a call for attention from my side, to the network science community. I feel it might be the same for the animal behavior and ecology worlds — to bring the two worlds together to do better science, combining all the strengths of the two different teams now that we can have really good data-collection experiments.”

Co-author Elizabeth Derryberry, a behavioral ecologist at the University of Tennessee who studies birdsong, agreed that the interdisciplinary project had wielded results and opened up “exciting” new possibilities.

She explained that the tools produced by the squad of network-mappers, which also included Nina Fefferman from the University of Tennessee and Matthew Silk from the University of Edinburgh in Scotland, allows those working in the field to identify patterns and make predictions about animal behavior.

Iacopini said he and the team of modelers enjoyed having their equations brought to life by ecologists.

“From our perspective, I think it is nice to see that some of the things that we do may actually go out in the field, instead of remaining on papers and publications online, and that is it,” he said.

Science & Technology

Recent Stories

Finding the beat of collective animal motion

Virtual reality experiments have illuminated the rhythmic glue that could keep animals moving in synchrony.

Across nature, animals from swarming insects to herding mammals can organize into seemingly choreographed motion. Over the last two decades, scientists have discovered that these coordinated movements arise from each animal following simple rules about where their neighbors are located. Now, scientists studying zebrafish have shown that neighbors might also be moving to the same beat. The team revealed that fish swimming in pairs took turns to move; and, they synchronized the timing of these movements in a two-way process known as reciprocity. Then, in virtual reality experiments, the team could confirm that reciprocity was key to driving collective motion: by implementing this rhythmic rule, they could recreate natural schooling behavior in fish and virtual conspecifics. The study published in Nature Communications was led by scientists from the Cluster of Excellence Collective Behaviour at the University of Konstanz and the Max Planck Institute of Animal Behavior in Germany (MPI-AB).

The results provide further mechanistic detail to our understanding of how animals self-organize into moving collectives. "We show that it takes two fish to tango," says first author Guy Amichay, who conducted the work while a doctoral student at MPI-AB. "Fish are coordinating the timing of their movements with that of their neighbor, and vice versa. This two-way rhythmic coupling is an important, but overlooked, force that binds animals in motion."

The synchrony of the swarm

Animals moving in synchrony are the most conspicuous examples of collective behavior in nature; yet many natural collectives synchronize not in space, but in time -- fireflies synchronize their flashes, neurons synchronize their firing, and humans in concert halls synchronize the rhythm of clapping.

Amichay and the team were interested in the intersection of the two; they were curious to see what rhythmic synchrony might exist in animal movement. "There's more rhythm to animal movement than you might expect," says Amichay, who is now a postdoctoral researcher at Northwestern University, USA. "In the real world most fish don't swim at fixed speeds, they oscillate."

Using pairs of zebrafish as a study system, Amichay analyzed their swimming to describe the precise pattern of motion. He found that fish, although moving together, did not swim at the same time. Rather they alternated such that one moved, then the other moved, "like two legs walking," he says.

The team then looked into how fish managed to alternate. They generated a computational model with a simple rule of thumb: double the delay of your neighbor.

The rule of reciprocity

The next step was to test this model computationally, or in silico . They set one agent to beat with fixed movement bouts, like a metronome. The other agent responded to the first by implementing the 'double the delay' rhythmic rule. But in this one-way interaction, the agents did not move in the alternating pattern seen in real fish. When both agents responded to each other, however, they reproduced the natural alternation pattern. "This was the first indication that reciprocity was crucial," says Amichay.

But reproducing natural behavior in a computer was not where the study ended. The team turned to virtual reality to confirm that the principle they uncovered would also work in real fish. "Virtual reality is a revolutionary tool in animal behavior studies because it allows us to circumvent the curse of causality," says Iain Couzin, a Speaker at the Cluster of Excellence Collective Behaviour at the University of Konstanz and a Director at MPI-AB.

In nature many traits are linked and so it is extremely difficult to pinpoint the cause of an animal's behavior. But using virtual reality, Couzin says it is possible to "precisely perturb the system" to test the effect of a particular trait on an animal's behavior.

A single fish was put into a virtual environment with a fish avatar. In some trials the avatar was set to swim like a metronome, ignoring the behavior of the real fish. In these trials the real fish did not swim in the natural alternating pattern with the avatar. But when the avatar was set to respond to the real fish, in a two-way reciprocal relationship, they recovered its natural alternating behavior.

Turn-taking partners

"It's fascinating to see that reciprocity is driving this turn-taking behavior in swimming fish," says co-author Máté Nagy, who leads the MTA-ELTE Collective Behavior Research Group at the Hungarian Academy of Sciences, "because it's not always the case in biological oscillators." Fireflies, for example, will synchronize even in one-way interactions.

"But for humans, reciprocity comes into play in almost anything we do in pairs, be it dance, or sport, or conversation," says Nagy.

The team also provided evidence that fish that were coupled in the timing of movements had stronger social bonds. "In other words, if you and I are coupled, we are more attuned to each other," says Nagy.

The authors say that this finding can drastically change how we understand who influences whom in animal groups. "We used to think that in a busy group, a fish could be influenced by any other member that it can see," says Couzin. "Now, we see that the most salient bonds could be between partners that choose to rhythmically synchronize."

• Behavioral Science
• Virtual Reality
• Video Games
• Artificial Intelligence
• Computer Modeling
• Virtual reality
• Pigeon intelligence
• Computer animation
• Experimental economics
• Grid computing
• Herding dog
• Uniform distribution (continuous)

Story Source:

Materials provided by Max-Planck-Gesellschaft . Note: Content may be edited for style and length.

Journal Reference :

• Guy Amichay, Liang Li, Máté Nagy, Iain D. Couzin. Revealing the mechanism and function underlying pairwise temporal coupling in collective motion . Nature Communications , 2024; 15 (1) DOI: 10.1038/s41467-024-48458-z

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