Mechanism as a constraint on function .1 Perceptual constraints

In document [Chris Barnard] Animal Behavior Mechanism org (Page 191-194)

Box 3.5 Behavioural rhythmicity

3.5 Mechanism and constraint

3.5.1 Mechanism as a constraint on function .1 Perceptual constraints

How the animal perceives the world inevitably shapes how it can respond to objects and events around it. We have already seen how perception can constrain response in our examples of perceptual rules of thumb (, Crude approximations, such as the ‘prey’ and ‘enemy’ distinction in toads, or the more sophisticated inventiveness of human visual perception, can provide economical mechanisms for decision-making, but also expose the limitations of the system.

Perceptual rules of thumb predispose the animal to notice and respond to particular cue configurations in the environment. Recent studies suggest that such perceptual or sensory biases may constrain later evolutionary developments and play a key role in the evolution of animal signalling systems, including those involved in mate choice (e.g.

Basolo 1990; Ryan et al. 1990; Chapters 10 and 11). The exploitation of sensory biases (dubbed sensory exploitation by Ryan 1990) in mating leads to individuals, usually females (Chapter 10), preferring mates with certain characteristics simply because they have inherited a sensory/perceptual system that is responsive to some aspect of them, not because the characteristics themselves confer any reproductive advantage. Thus, for example, female platyfish (Xiphophorus maculatus) prefer conspecific males with artificial extensions to their tail fins (Basolo 1990), perhaps because they suggest the males are larger than they really are. The extensions resemble those sported naturally by males of the closely related swordtail (X. helleri; Fig. 3.35) to attract females of their own species, but do not occur naturally in platyfish. However, a molecular phylogeny (2.2) suggests that platyfish and swordtails inherited their preference from a common ancestor, so the preference for a tail extension among female platyfish appears to be a retained, but now functionless, ancestral trait (Basolo 1995). A potential hazard of this ancestral baggage is that females might end up mating with males of the wrong species.

In the Xiphophorus case this is a small risk because platyfish and swordtails seldom co-occur, but there are several other groups of closely related species, for example in birds, where new zones of overlap may well lead to hybridisation through sensory bias.

Pre-existing sensory biases may reflect other features that act as attention-grabbers.

In some water mites and jumping spiders, for example, males entice females by exploiting

Figure 3.35 Male swordtails (Xiphophorus helleri) possess an exaggerated extension to their caudal fin that appears to have been sexually selected through female choice.

However, females of the closely related platyfish (X. maculatus) also prefer males with tail extensions, even though males of their own species do not possess them. See text. After Manning & Dawkins (1998).

their responsiveness to cues suggesting food, rather like the courtship displays of pheasants and peafowl in Figure 1.13. In the wax moth Achroia grisella, male signals seem to be derived from the ultrasonic emissions of predatory bats, to which the female’s ears are particularly attuned ( (Greenfield & Weber 2000). In these species, therefore, courtship signals have been channelled by pre-existing response characteristics of females honed in other contexts. Intuitively, one might expect such biases to be widespread, and Phelps & Ryan (2000) have recently shown how important an influence they might be using a neural network approach (, in this case modelling the evolution of phonotactic cues in female túngara frogs (Physalaemus pustulosus) (

Neural network models have also been used to explore another kind of perceptual bias in animals, commonly revealed as enhanced responsiveness to supernormal stimuli.

In many cases where they have been tested, animals have shown greater responsiveness to stimuli that exaggerate those of the normal target stimuli. Thus, oystercatchers (Haematopus ostralegus) will show a stronger incubation response to an artificial egg several times the normal size. Similarly, male sticklebacks will preferentially court model females with bellies distended well beyond those of normal gravid females. Supernormal stimuli are a reflection of the approximate rules of thumb used to make decisions in a world of normal variation. Such rules are, as we have noted, easily fooled by artificial stimuli. Nevertheless, neural network models of visual preferences suggest that heightened responsiveness to supernormal stimuli may be a basic property of perceptual systems (Arak & Enquist 1993). Motor constraints

Perceptual mechanisms impose some constraints and biases on behaviour. Effector systems impose others. Motor constraints form the basis for some forms of ‘honest’ signalling (Chapter 11), where, for instance, vocal status signals depend on the pitch of the sound, and the latter depends on the size and resonating qualities of the vocal apparatus. Here, only large, competitive individuals can emit deep, penetrating calls (Davies & Halliday 1978). In some cases, however, the vocal apparatus imposes more basic constraints on vocal behaviour. A study of song development in swamp sparrows (Melospiza georgiana) by Jeffrey Podos provides a nice example.

While it is well known that the development of elaborate songs in birds can be limited by constraints on learning and memory, Podos (1996) tested the idea that the physical performance of song may also impose a mechanical constraint. Swamp sparrows have a complex song structure in which syllables (groups of notes) are repeated in a series of trills (Fig. 3.36a). Such songs are likely to be demanding to produce because of the rapid breathing and muscular modulations required, but may nevertheless be under strong sexual selection (2.4.1, Chapter 10) to become more elaborate. If vocal mechanism is a factor constraining further elaboration, then pushing the system beyond its normal performance limits should result in characteristic production errors, such as dropped syllables or breaks in song performance. Podos challenged young birds by exposing them during their song learning phase to songs with trill rates artificially accelerated by between 26% and 92% (Fig. 3.36a). When he examined their later songs, he found precisely the kind of production errors expected if performance was subject to motor constraint (Fig. 3.36b). Errors included trill rate reductions (but never augmentations), note omissions, pauses in trill structure and deceleration within trills, all features consistent with motor constraint rather than limitations of learning or memory. Constraints in the context of learning are discussed further in Chapter 6.

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isement songs of swamp sparrows (Melospiza georgiana) (i, iii, v), and the manipulated versions of each (ii, iv, vi) that were used to train young birds. Note the structuring of the songs into syllables that are repeated as trills, and the compression of the trills in the manipulated versions. See text. (b) Imitations of manipulated training songs (ii, iv, vi in Fig. 3.36a) by five different individuals.

Song 1 has a reduced trill rate compared with its model (ii in Fig. 3.36a), song 2 omits some of the notes in its model (iv in Fig. 3.36a), while songs 3, 4 and 5 have pauses interspersed among their syllables – all changes consistent with a motor con-straint on song learning. See text. After Podos (1996).

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