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Individual behavioural specialisation and adaptation learning.






Another for of learning is singled out here, basing on the idea that animals often do not learn to do something really new in order to gain advantage from their environment; instead, they learn to select quickly and to manipulate readily with innate behavioural patterns, and this can be considered a separate form of learning, which can be called adaptation learning. This form of learning is closely connected with behavioural specialisation in populations: some specimens are predisposed to accomplish a certain part of a whole, species-specific, repertoire and consequently they learn more readily within this specific domain.

An impressive example of behavioural specialisation came from the study on how insects of different sizes and level of intelligence catch jumping springtails, small inoffensive creatures that nevertheless are equipped with a jumping fork appendage (furcula) attached at the end of the abdomen. The furcula is a jumping apparatus enabling the animal to catapult itself (hence the common name springtail), thereby changing sharply the direction of movement and to escape attacks of predators. Reznikova and Panteleeva (2001, 2005) revealed springtail hunters in beetles of the family Staphylinidae as well as in several species of ants. Although beetles are taxonomically far from ants, there are three similar groups both in the beetles and ants: (1) good hunters that catch a jumping victim from the first spurt; (2) poor hunters that perform several wrong spurts until they catch a springtail; and (3) no-hunters that even do not display any interest to the victims. Behavioural stereotypes were similar in ants and beetles, with one great difference: ants were able to bring their hunting technique up to standard of the next level whereas beetles were not. It turned out later that hunting behaviour in ants incorporated several variants of development, one of them is based on maturation rather than learning, while others include elements of social learning and different levels of flexibility. We will return to this sophisticated development of behaviour in Chapter 23. As far as beetles are concerned, there are three distinct types of behaviours relative to jumping victims in populations, and this is one of examples of individual behavioural specialisation.

Bolnick et al. (2003) present a huge collection of examples of individual behavioural and ecological specialisation for 93 species distributed across a broad range of taxonomic groups. In many species some specimens in populations are more risk averse than others, possibly reflecting different optimisation rules (in terms of Optimal Foraging Theory, see Charnov, 1976). Besides, individuals vary in their prey-specific efficiency because of search image formation. Individuals also vary in social status, mating strategy, microhabitat preferences and so on. In some species individuals constitute groups on the basis of relatively stable features. Bluegill sunfish serves as a good example of differentiation of individuals relatively to their foraging strategy (see review in: Bolnick et al., 2003). When a population of bluegills was experimentally introduced to a pond, individuals quickly divided into benthic and limnetic specialists. The remanding generalists constituted 10-30% of the population and appeared to have a lower intake rate of food.

There is an example of more complex individual specialisation in the oystercatcher Haematopus ostralegus. In this species individual birds specialise both on prey species and on particular prey-capture techniques such as probing mud for worms or hammering bivalves. Individuals that use bivalves tend to specialise on different hammering or stabbing techniques that reflect intraspecific variation in prey shell morphology. Individuals are limited to learning a small repertoire of handling behaviours, while additional trade-offs are introduced by functional variation in bill morphology. Subdominant and juvenile birds are often restricted to sub- optimal diets rather than those they would choose in the absence of interference competition (Goss-Custard et al., 1984; Sutherland et al., 1996).

In all cases described above behavioural specialisation within populations is based on intricate composition of innate predisposition of individuals to choose a way of prey handling, to averse risk or not, to dominate over conspecifics or to avoid conflicts, and so on. Some specimens can possess complex behavioural patterns that allow them to learn readily within a specific domain. This ability can be called cognitive individual specialisation.

The idea of adaptation learning is based on the experimental study on inter-relations between ants and carabid beetles (Reznikova and Dorosheva, 2004, 2005). To examine the ability of four carabids species to avoid collisions with Formica aquilonia red wood ants, the researchers used two experimental techniques. In laboratory, they tested carabids’ ability to avoid a clash in a Y-shaped labyrinth containing an active ant tied up with a thread in one section (Fig VII-6 -a, b, c, d, e). Four carabid species tested in the labyrinth displayed a clear tendency to learn, that is, to modify their behaviour in order to avoid collisions with ants. In all four species individuals comprised three groups that differed by their ability to learn to averse clashes: 45-76% made less then 35% of errors in the labyrinth (“good learners”), and 17-39% made more than 65% of errors (“bad learners). The remanding intermediate group was relatively small in all species (from 10 to 20%). This can be considered individual specialisation relative to the ability to avoid dangerous by means of learning. “Good learners” successfully avoided conflict with ants each applying one out of a set of stereotyped behavioural tactics: (1) attempts to round the ant; (2) to turn away after touching the ant with antennae; (3) to turn away without a contact; (4) to avoid a dangerous section at all; (5) to stop near the ant with legs and antennae hidden (see Fig.VII-7). Members of different species appeared to use specific preferences for definite sets of tactics. For example, for Pterostichus oblongopunctatus tactics 1 and 2 are preferable, whereas P. magus prefers tactics 2 and 5. Complementary field experiments (Reznikova and Dorosheva, 2004) enabled the researchers to suggest that effective combination of tactics allows carabids to penetrate ant foraging territory and to particularly avoid interference competition.

It is important to note that in the cited experiments animals did not learn something new such as remembering a new path in a labyrinth or pressing a lever in response to a presenting stimulus. Instead, facilitation of manipulations with innate behavioural patterns by animals took place in these experiments. It is worth to note that animals very quickly learn to “juggle” with behavioural patterns which are ready for operation. Perhaps, adaptation learning can be implemented on a wide variety of species.

“Ecological intelligence”. As we have already seen in this book, there are some impressive examples of complex behaviour in animals closely related to ecological traits of species. In those cases when these behaviours include sophisticated learning one can reason about “ecological intelligence”. Let us consider one of the most astonishing example concerning abilities of food hoarding animals to memorise hundreds of sites of food location.

Observing birds that are attracted to a winter feeder, one can see, among others, great tits, blue tits and marsh tits. The great tits and the blue tits congregate at the feeder, eating as fast as they can. They interrupt their meal only to chase away their competitors. A marsh tit nonetheless darts in, grabs a peanut and flies off. It is back almost immediately to grab another. It stores the peanuts nearby, each in a different site, until the feeder is empty. Then it searches out its hidden food. The marsh tit is one of food storing species. Another example is a nutcracker. This pale-grey bird with black wings and a long beak flits through woodlands, collecting seeds during times of plenty and tucking them away for a hungry winter's day. During a year, each bird buries 22, 000 to 33, 000 seeds in up to 2, 500 locations, and researchers estimate that the bird recovers two-thirds of them up to 13 months later. Nutcrackers carry their seeds as far as 25 kilometres to cache them (Balda, 1980). Detailed studies have demonstrated that food-storing birds really do remember large numbers of storage sites over long periods, and their memory could be an example of cognitive specialisation.

Food hoarding (or caching) is a fundamental adaptation of animals to variation in food supplies. The detailed systematically review of food hoarding in birds, mammals, and arthropods is given in Vander Wall’s (1990) book. Sherry (1989) cites one of the earliest descriptions and, what is even more important, the earliest experimental paradigm of studying food storing behaviour. This belongs to Baron von Perney (1660 – 1731) whose observations and methods were unknown until they were rediscovered by Stresemann (1947). Perney provided a remarkably accurate description of the basic methods that are used today for observing food storing in birds in captivity. He allowed a tit to collect and hide seeds in a room, then re-hided them and examined what birds had remembered. Basing on a same method, Brodbeck and Shettleworth (Brodbeck, 1994; Brodbeck and Shettleworth, 1995) compared spatial memory abilities in food storing chickadees and non - food storing juncos. Birds were allowed to return after a few minutes or hours to food which they had encountered briefly once before. The food was a peanut hidden in a brightly decorated block of wood on the wall of a large aviary. Four new feeders in four new locations were used on every trial. When the birds returned directly to the baited feeder on a high proportion of trials, they were tested to see what they remembered by swapping the formerly baited feeder with another one of the feeders on occasional unrewarded tests, thus dissociating location from pattern and colour cues. Chickadees nearly always went first to the former location of the baited feeder, even though it was now occupied by a feeder that looked entirely different. In contrast, juncos chose about 50: 50 between that feeder and the formerly baited feeder in its new location. Clayton and Krebs (1994) obtained similar results comparing food hoarding Clark nutcrackers with two close but non storing species.

Experiments of Balda and Kamil (1992) with Clark's nutcrackers challenged the idea that the birds were following some subtle sensory clue to the seeds themselves instead of relocating particular sites. The birds were able to find their cashes in the sandy aviary floor irrespective of whether or not the researchers put landmarks such as cinder blocks, wall posters, and so on in the room. In a further refinement of the experiments, experimenters built a floor that was 30 feet by 50 feet, with 330 holes drilled in it to hold either cups of sand or plugs. Still, the birds maintained their high success rate in relocating their hiding places. Researchers also tested one of his graduate students at caching. The student hid seeds and 30 days later found only about half as many caches as a bird typically did.

The very specific ability to memorise site locations in food storing species seems to be closely related with some important brain adaptations. Just as in mammals, in birds the hippocampus is important for spatial memory. It is consistent with the idea that food storing involves the evolution of a modular cognitive capacity: in food storing species of birds the hippocampus is larger relative to the body size and telencephalon volume (most of the rest of the brain) than in non-storing species. Krushinskaya (1966) was the first to show that lesions that include the avian hippocampus disrupt food-cache recovery in food storing birds. More recently many detailed findings appeared in this field which include, in particular, that the hippocampal enlargement that occurs as animals store more food during the autumn is accompanied by increased neurogenesis. Included are studies in which males and females of the same species differ, perhaps, only seasonally in space use and concomitantly in hippocampal volume (Sherry and Duff, 1996; Smulders et al., 2000). In principle, a relationship between the relative size of the hippocampal formation and the degree of specialisation for food hoarding was shown in many avian species (Krebs et al., 1989; Sherry et al., 1989). However, recent results revealed a surprising differences between species from continents, with North American species possessing significantly smaller hippocampi than Eurasian ones (Lucas et al., 2004).

What is important to note is that in many tests of different design food storing species excelled close but non storing species at spatial tasks but they were no better than others in operant tests or colour memory. This enables researchers to conclude that food storing animals such as many species of parids (tits and chickadees), corvids (jays and nutcrackers), and rodents (kangaroo rats, squirrels and others) possess relatively narrow cognitive specialisation basing on their extra ordinate spatial memory. This may be called “ species-specific endowments ”.

It is a topic of controversy to what extent displays of sophisticated behaviour of “species-specific geniuses” (or “cognitive specialists”) can be explained in terms of cognition rather than accomplishing fragments of wired species-specific repertoire.

Let us consider the very complex behaviour of food hoarding Western scrub jays which seem to anticipate problems yet to come. Emery and Clayton (2001) looked at how the jays reacted to the possibility that some neighbour would steal a food cache. Some of the jays in the laboratory had criminal histories of snagging food that another bird had buried. The researchers let the criminal jays as well as ones with clean records to hide treats. When the birds stashed their seeds in private, they didn't take opportunities to move their treasure to a new hiding place. However, if the researchers let another bird get near enough to watch the caching, the criminal jays took the next opportunity to recover the treat and hide it in a different place. The birds with no experience of thievery didn't re-cache. The authors are careful not to say that animals mentally travel in time the same way people do. Still, they argue for continuing to push questions about animals' mental abilities.

Analysing different aspects of the findings described above we can conclude that food hoarding behaviour develops on the basis of specific behavioural domain sitting on a particular brain structure. Within these frames animals demonstrate sophisticated mental abilities and high flexibility of memory. Seemingly, a compromise just has been found between innateness and flexibility.

However, the picture is not simple. The next example shows that the range of flexibility may be relatively narrow. The matter concerns the so called “pilfering avoidance hypothesis” which was debated in behavioural ecology since 70-th (Mac Donald, 1976). Studies on rodents and birds have shown that members of the same species can use several constant scenarios of hoarding and several scenarios of pilferage. They shift their strategies, for instance, from larder to scatter hoarding, in dependence of many factors among which risk of pilfering plays a key role. Animals detect the risk of pilfering by encountering potential competitors by scent and visual cues or directly after pitiful encounter of emptied caches (Hansson, 1986; Clarke and Kramer, 1994; Jenkins and Breck, 1998). There is evidence from many species that animals may alter cache behaviour in the presence of competitor and that personal “criminal past” facilitates alteration of strategies. For example, in experiments of Preston and Jacobs (2001) kangaroo rats were forced by researchers to play roles, in turns, of “stealers” and “victims”. Similarly with Clayton et al’s scrub jays, rodents were likely to change their strategies more readily after experience as victims. Analysis of a huge body of literature has led Vander Wall and Jenkins (2003) to a model that is based on imagination of lives of many rodents and birds under circumstances of reciprocal pilfering. Levels of cache pilferage are often high, that is, 2–30% per day, but victims can return a favour to stealers. It is likely that processing of food-hoarding interacts with inter- and intraspecific competition in many species at an evolutionary level, and certain sets of strategies evolved as a basis for shifting from one strategy to another in dependence of a level of the risk.

All these enable us to consider sophisticated “anticipation” in food storing animals within a frame of a paradigm of “adaptation learning” (Reznikova and Dorosheva, 2004) rather than in terms of tactical deception and taking into account rich social context in birds (Emery and Clayton, 2001). In order to avoid risk of pilfering from conspecifics, animals are likely to choose more and more quickly and effectively a relevant strategy from a set of strategies that already exists rather than contrive something completely new as an answer for an intervention.

 

23. DEVELOPMENTAL STUDIES OF ANIMAL INTELLIGENCE: ROLE OF INNATE AND ACQUIRED BEHAVIOUR

 

One of the most intriguing questions in ethology is to what extent complex behavioural patterns in animals, such as flight, nest building, hunting, and tool using, are determined by inherited programs. What one may say definitely is that each species should be investigated experimentally, and perhaps theoretic constructions are of little help. Lorenz (1935) spoke of “instinct-learning intercalation” describing situations when innate and acquired components become integrated into one behavioural sequence. It is interesting to separate these components experimentally and to investigate how early experience influences behavioural scenario in different species. Development studies help researchers to unravel strapwork of innate and learned components in animals.

A good example here is storing behaviour that was just considered above. The way storing behaviour develops and can later be modified, indicates that storing in birds is better described as a hard-wired behaviour that the birds perform relatively independently on current need and anticipation of future consequences (Shettleworth, 2001). Fledglings begin storing avidly, at around 40 days of age, even when they have ample food and efforts are made to deprive them of storable items and suitable substrates (Clayton, 1995). The items chosen and the expertise with which they are inserted into suitable sites change with experience, as does the selection of sites in adults (Hampton and Sherry, 1994). However, birds store food even under circumstances where they seem unlikely to be anticipating retrieving it. In laboratory, some birds persisted indefinitely in storing peanuts in places where they dropped out of reach (Shettleworth, 1994).

In this Chapter we will analyse experimental approaches for studying the development of complex behavioural patterns.

 


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