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Signalling theory
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Within evolutionary biology, signalling theory refers to a body of theoretical work examining communication between individuals. The central question is when animals with conflicting interests should be expected to communicate "honestly". Mathematical models in which organisms signal their condition to other individuals as part of an evolutionarily stable strategy are the principal form of research in this field.
iology, signals are traits, including structures and behaviors, that have evolved specifically because they change the behavior of receivers in ways that benefit the signaler .
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Within evolutionary biology, signalling theory refers to a body of theoretical work examining communication between individuals. The central question is when animals with conflicting interests should be expected to communicate "honestly". Mathematical models in which organisms signal their condition to other individuals as part of an evolutionarily stable strategy are the principal form of research in this field.
Honest signals
In biology, signals are traits, including structures and behaviors, that have evolved specifically because they change the behavior of receivers in ways that benefit the signaler . Traits or actions that benefit the receiver exclusively are called cues. When an alert bird deliberately gives a warning call to a stalking predator and the predator gives up the hunt, the sound is a signal. When a foraging bird inadvertently makes a rustling sound in the leaves that attracts predators and increases the risk of predation, the sound is a cue.
Signaling systems are shaped by the extent to which signalers and receivers have mutual interests. An alert bird warning off a stalking predator is communicating something useful to the predator: that it has been detected by the prey; it might as well quit wasting its time stalking this alerted prey, which it is unlikely to catch. When the predator gives up, the signaler can get back to other important business. Once the stalking predator is detected, the signaling prey and receiving predator have a mutual interest terminating the hunt .
Within species, mutual interests generally increase with kinship . Kinship is central to models of signaling between relatives, for instance when broods of nestling birds beg and compete for food from their parents . The distinction between signals and cues is not clear, and probably not useful for immune, endocrine and neural signaling between the cells within an individual, at least to the extent that all of these cells are clonal descendents of a fertilized egg and there are no conflicts of interest between them.
The concept of honesty in animal communication is controversial because it is difficult to determine intent and use that as a criterion to discriminate deception from honesty, as we do in human interactions . Because of this, biologists who use the phrase ”honest signals” use it in a statistical sense. Biological signals, like warning calls or resplendent tail feathers, are considered honest if they are correlated with, or reliably predict, something useful to the receiver. In this usage, honesty is a useful correlation between the signal trait (which economists call ”public information” because it is readily apparent) and the unobservable thing of value to the receiver (which economists refer to as “private information” and biologists often refer to as “quality”). Honest biological signals do not need to be perfectly informative, reducing uncertainty to zero; they only need to be honest “on average” to be potentially useful . Ultimately the value of the signaled information depends on the extent to which it allows the receiver to increase its fitness.
Dishonest signals
Because there are both mutual and conflicting interests in most animal signaling systems, the fundamental problem in evolutionary signaling games is dishonesty or cheating. Why don’t foraging birds just give warning calls all the time, at random (false alarms), just in case a predator is nearby? If peacocks with bigger tails are preferred by peahens, why don’t all peacocks display big tails? Too much cheating would disrupt the correlation at the foundation of the system, causing it to collapse. Receivers should ignore the signals if they are not useful to them and signalers shouldn’t invest in costly signals if they won’t alter the behavior of receivers in ways that benefit the signaler. What prevents cheating from destabilizing signaling systems? It might be apparent that the costs of displaying signals must be an important part of the answer. However, understanding how costs can stabilize an “honest” correlation between the public signal trait and the private signaled quality has turned out to be a long, interesting process.
An example of dishonest signalling comes from Fiddler crabs such as Uca lactea mjoebergi, which have been shown to bluff in regards to their fighting ability. Upon regrowing a lost claw, a crab will occasionally regrow a weaker claw that nevertheless intimidates crabs with smaller but stronger claws. The proportion of dishonest signals is low enough that it is not worthwhile for crabs to test the honesty of such signals, as combat can be dangerous and expensive.
History
The question of whether individuals of the same species might not be attempting to deceive each other was raised by Richard Dawkins and John Krebs in 1978. This thinking was prompted by the application of a gene-centered view of evolution to the use of threat displays. Dawkins & Krebs criticised previous ethologists, such as Nikolaas Tinbergen and Desmond Morris among others, for supporting the view that such displays were used "for the good of the species". Dawkins and Krebs (and Krebs and Dawkins, 1982) argued that such communication ought to be viewed as an evolutionary arms race in which signallers evolve to become better at manipulating receivers, while receivers evolve to become more resistant to manipulation.
The game theoretical model of the war of attrition was applied to the problem, and appeared to suggest that threat displays ought not to convey any reliable information about intentions (Caryl, 1979). This led to a re-examination of the empirical evidence, and much debate .
The sports handicapping metaphor
In 1975, Amotz Zahavi proposed a verbal model for how signal costs could constrain cheating and stabilize an “honest” correlation between observed signals and unobservable qualities, based on an analogy to sports handicapping systems . He called this idea the handicap principle. The purpose of a sports handicapping system is to reduce disparities in performance, making the contest more competitive. In horse racing, intrinsically faster horses are given heavier weights to carry under their saddles. In amateur golf , better golfers have fewer strokes subtracted from their raw scores. This creates correlations between the handicap and unhandicapped performance, and if the handicaps work as they are supposed to, between the handicap and handicapped performance. If you knew nothing about two race horses or two amateur golfers except their handicaps, you could infer which horse or golfer has had the better performance in the recent past, and which competitor is most likely to win: the horse with the bigger weight handicap and the golfer with the smaller stroke handicap. By analogy, if peacock tails act as a handicapping system, and a peahen knew nothing about two peacocks but the sizes of their tails, she could “infer” that the peacock with the bigger tail has greater unobservable intrinsic quality, in the sense that it is better able to pay the costs of displaying the tail (here, “infer” is shorthand for the idea that females that prefer bigger tails are at a selective advantage). Display costs can include extrinsic social costs, in the form of testing and punishment by rivals, as well as intrinsic production costs .
The essential idea here is intuitive and probably qualifies as folk wisdom. It was articulated quite nicely by Kurt Vonnegut, in his 1961 short story Harrison Bergeron . In Vonnegut’s futuristic dystopia, the Handicapper General uses a variety of handicapping mechanisms to reduce inequalities in performance. A spectator at a ballet comments: “it was easy to see that she was the strongest and most graceful of all dancers, for her handicap bags were as big as those worn by two hundred pound men.” Zahavi interpreted this analogy to mean that higher quality peacocks with bigger tails are signaling their ability to "waste" more of something important by trading it off for a bigger tail. This resonates with Veblen’s idea that conspicuous consumption and extravagant status symbols can signal wealth .
One area where there is currently a lot of research on this idea involves the duel roles of carotenoid pigments in immune system function and in yellow-red bird feathers . Carotenoids have to be ingested because animals cannot synthesize them de novo. It is hypothesized that birds with redder feathers are demonstrating their ability to “waste” more carotenoids by allocating them to feathers rather than to immune function. The red feathers are hypothesized to be an immunocompetence handicap .
Zahavi’s conclusions rest on his verbal interpretation of a metaphor, and initially, the handicap principle was not well received by evolutionary biologists . However, in 1984, Nur and Hasson used life history theory to show how differences in signaling costs, in the form of survival-reproduction tradeoffs, could stabilize a signaling system roughly as Zahavi imagined. Later in the decade, several papers using genetic models also began to suggest that the idea just might work, at least some times . The logjam was broken in 1990 by Alan Grafen, who developed a very complicated marginal fitness maximization model of evolutionary signaling games and came to the conclusion that, given certain assumptions, a handicap-like signaling system could be evolutionarily stable, if higher quality signalers paid lower marginal survival costs for their signals. This, and the seminal paper by W. D. Hamilton and Zuk suggesting that sexually selected signals are signals of health, in a never-ending co-evolutionary race between hosts and their parasites, led to an explosion of research on the relationship between sexually selected signals, parasites and mate preferences.
Re-evaluating biological signaling vs. sports handicapping
Efforts to test the handicap principle empirically have not been decisive, partly because of inconsistent interpretations of Zahavi’s metaphor and Grafen’s marginal fitness model, and partly because of conflicting empirical results: in some studies individuals with bigger signals seem to be paying higher costs, in other studies they seem to be paying lower costs . Recent theoretical analyses have uncovered a possible explanation for the inconsistent empirical results. A series of papers by Getty shows that Grafen’s proof of the handicap principle is based on the critical simplifying assumption that signalers trade off costs for benefits in an additive fashion, the way humans invest money to increase income in the same currency. Grafen’s proof is formally similar to a classic monograph on economic market signaling by Nobel laureate Michael Spence . This assumption that costs and benefits trade off in an additive fashion might be valid for some biological signaling systems, but is not valid for the survival cost – reproduction benefit tradeoff that is assumed to mediate the evolution of sexually selected signals. Fitness depends on the production of offspring and this is a multiplicative function of reproductive success given an individual is still alive times the probability of still being alive, given investment in signals.
Survival-reproduction tradeoffs do not correspond to sports handicaps in any simple, useful way. Zahavi’s intuition was correct in the very general sense that “differences in costs” can stabilize the evolution of an “honest” signaling system, but in sexually selected signaling, “differences in costs” are properly decreasing proportional (or log) marginal costs . The mathematics can be interpreted to mean that higher quality signalers are more efficient at converting signal costs into reproductive benefits. This re-analysis undermines the idea that higher quality signalers are demonstrating their ability to waste more because the pattern of absolute signal costs across signalers of different quality remains undetermined. Depending on the specific form of the tradeoffs in any particular system, higher quality signalers might pay absolutely more or less for big signals than lower quality signalers pay for small signals. This might explain why the empirical data on the relationship between signals and costs are so inconsistent.
Costly signaling and Fisherian diploid dynamics
The effort to discover how costs can constrain an “honest” correlation between public signals and private qualities within signalers is built on strategic models of signaling games, with many simplifying assumptions. These models are most often applied to sexually selected signaling in diploid animals, but they rarely incorporate an important feature of diploid sexual reproduction that was pointed out by Ronald Fisher in the early 20th century: if there are “preference genes” correlated with choosiness in females as well as “signal genes” correlated with display traits in males, choosier females should tend to mate with showier males. Over generations, showier sons should also carry genes associated with choosier daughters and choosier daughters should also carry genes associated with showier sons. This correlation could introduce an evolutionary dynamic known as a Fisherian runaway. Russell Lande explored this with quantitative genetic models and his work inspired a very active line of research in the quantitative genetic framework . These analyses revealed that Fisherian diploid dynamics are very sensitive to signaling and search costs. Recent models have begun to bridge the gap between the costly-signaling and Fisherian-runaway traditions by developing modeling frameworks that incorporate both simultaneously . These models recognize that if fitness depends on both survival and reproduction, having sexy sons and choosy daughters (in the stereotypical model) can be adaptive, increasing fitness just as much as having healthy sons and daughters.
Examples
* Sam Brown and W. D. Hamilton and Marco Archetti proposed the idea that Autumn leaf color is due to the trees signalling to aphids and other pest species that migrate to the trees in autumn. Autumn colour is costly to trees but bright trees might reduce their parasite load; aphids on the other hand might prefer trees with dull leaves because these are the ones with less chemical defenses. Indeed aphids appear to preferentially avoid trees with bright leaves and tree species with bright leaves have more specialist aphid pests than do trees lacking bright leaves. While autumn colours might be a real handicap signal, it is not necessary that the signal is costly to produce. It might also be an index, which is maintained because it is impossible to fake (it would be a signal instead if only strong individuals can afford the cost of displaying it). The topic is still debated.
- Stotting for example in Thomson's Gazelles is cited as an example of signaling: the gazelles jump close to a predator instead of escaping, in what could be a signal of strength.
Human honest signals
Because honest signals are found in a wide variety of species it is reasonable to expect that humans have also evolved honest signals. Examples of human honest signals that have been suggested include neonatal cry quality as a signal that promotes neonatal survival(Madkour et al 1997), increases in activity level (e.g., autonomic nervous system arousal) as a signal that promotes changes in group activity level through mood contagion, or verbal and postural mirroring as a signal that promotes feelings of trust and empathy in others (Pentland 2008). Evidence from behavioral economics show that changes in arousal, trust or empathy also change individual assessments of risk and reward. More abstract honest signals have also been suggested, including the General Intelligence factor (g) as a signal of fitness (Luxen and Buunk 2006) and key features of human language (Lachmann et al 2001).
See also
External links
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