Anita. Behav., 1971, 19, 695-706 THE HUNTING BEHAVIOUR OF INDIVIDUAL GREAT TITS IN RELATION TO SPATIAL VARIATIONS IN THEIR FOOD DENSITY BY JAMES N. M. SMITH & RICHARD DAWKINS Department of Zoology, South Parks Road, Oxford Abstract. Individual great tits responded to variations in food density by spending a large proportion of their total searching time in the regions of highest food density. Lower densities, however, were not treated differentially, and the birds were slow to react to spatial changes in food density. The results are related to those of L. Tinbergen and T. Royama. The experimental birds' behaviour provides support for Royama's hypothesis that great tits can relate their hunting effort to the profitability of different feeding areas. Tinbergen's search image hypothesis at present lacks behavioural support in titmice and further work is required if searching images are to be thought to play a role in the hunting behaviour of the great tit. The way in which predators respond to vari- ations in the distribution and density of their food is important in helping to understand two problems: 'How is the behaviour of a predator adapted to ensure efficient feeding?' and 'What effect does such behaviour have on populations of the predator's prey species ?' The relationship between the insects of a Scots Pine (Pinus sylvestris) plantation and their avian predators was studied in detail over eight consecutive breeding seasons by Tinbergen (1960) in Hulshorst (Gelderland) in the Nether- lands. Tinbergen and his collaborators paid particular attention to the density of the larvae of pinewood insects (mainly Lepidoptera) and their representation in the diet of their titmouse predators (more correctly, that proportion of the diet fed to the nestlings). The main predator studied was the great tit (Parus major), but other passerines were also involved in the pre- dation. Tinbergen found that, for a number of the main prey species, those at the lowest prey densities tended not to be taken by the tits. At intermediate densities, the proportion of each species in the tits' diet rose sharply, but this increase tended to level off at very high prey densities. Tinbergen compared the observed predation with sets of 'expectation curves' relating the percentage of a particular prey species in the tits' diet to its density in the habitat. These were built up on the basis of the density of alternative prey, on the relative acceptability of the individual prey species, and on an assump- tion that the predators were searching at random. None of these curves gave satisfactory fits to the data, except for green sawfly larvae (Diprion spp.). At low and high densities the percentage of most prey species in the diet fell below ex- pectation, but rose above expectation at moder- ate prey densities. Tinbergen concluded from this that the birds were not taking prey at ran- dom. He also noted that, when a new prey species first became available in the food com- plex, there was a lag before its appearance in the tits' diet. Tinbergen offered three hypotheses to account for the last finding: (a) That the average size of prey, and hence their relative acceptability was small when they first appeared. This interpretation was not con- sistent with the data. (b) That the birds were not hunting in the area where the new prey species appeared. There was evidence that this factor was contri- buting to the result in one of the prey species studied, adults of the bordered white moth (Bupalus pinarius) which were taken on the ground (Mook, Mook & Heikens 1960). Tinbergen rejected this as a general explanation, however, on the grounds that all other prey species occurred in the canopy of the pine wood, where the tits might have been expected to encounter them as soon as they appeared in the food complex. Note that this last point would not follow if searching in the canopy had been non- random. (c) That the lag was a consequence of a learn- ing process in the birds. Tinbergen further considered that specific characters of the prey were involved in this learning and that the birds performed 'a highly selective sieving operation on the visual stimuli reaching the retina'. He labelled this the formation of a 'specific search- ing image' and generalized it to account for the under-representation of the species at low densities in the tits' diet. He attributed the dis- crepancy from expectation at high densities to 695
Transcript
Anita. Behav., 1971, 19, 695-706
THE HUNTING BEHAVIOUR OF INDIVIDUAL GREAT TITS IN RELATION
TO SPATIAL VARIATIONS IN THEIR FOOD DENSITY
BY JAMES N. M. SMITH & RICHARD DAWKINS Department of Zoology, South Parks Road, Oxford
Abstract. Individual great tits responded to variations in food density by spending a large proportion of their total searching time in the regions of highest food density. Lower densities, however, were not treated differentially, and the birds were slow to react to spatial changes in food density. The results are related to those of L. Tinbergen and T. Royama. The experimental birds' behaviour provides support for Royama's hypothesis that great tits can relate their hunting effort to the profitability of different feeding areas. Tinbergen's search image hypothesis at present lacks behavioural support in titmice and further work is required if searching images are to be thought to play a role in the hunting behaviour of the great tit.
The way in which predators respond to vari- ations in the distribution and density of their food is important in helping to understand two problems: 'How is the behaviour of a predator adapted to ensure efficient feeding?' and 'What effect does such behaviour have on populations of the predator's prey species ?'
The relationship between the insects of a Scots Pine (Pinus sylvestris) plantation and their avian predators was studied in detail over eight consecutive breeding seasons by Tinbergen (1960) in Hulshorst (Gelderland) in the Nether- lands. Tinbergen and his collaborators paid particular attention to the density of the larvae of pinewood insects (mainly Lepidoptera) and their representation in the diet of their titmouse predators (more correctly, that proportion of the diet fed to the nestlings). The main predator studied was the great tit (Parus major), but other passerines were also involved in the pre- dation. Tinbergen found that, for a number of the main prey species, those at the lowest prey densities tended not to be taken by the tits. At intermediate densities, the proportion of each species in the tits' diet rose sharply, but this increase tended to level off at very high prey densities. Tinbergen compared the observed predation with sets of 'expectation curves' relating the percentage of a particular prey species in the tits' diet to its density in the habitat. These were built up on the basis of the density of alternative prey, on the relative acceptability of the individual prey species, and on an assump- tion that the predators were searching at random. None of these curves gave satisfactory fits to the data, except for green sawfly larvae (Diprion spp.). At low and high densities the percentage of most prey species in the diet fell below ex-
pectation, but rose above expectation at moder- ate prey densities. Tinbergen concluded from this that the birds were not taking prey at ran- dom. He also noted that, when a new prey species first became available in the food com- plex, there was a lag before its appearance in the tits' diet. Tinbergen offered three hypotheses to account for the last finding:
(a) That the average size of prey, and hence their relative acceptability was small when they first appeared. This interpretation was not con- sistent with the data.
(b) That the birds were not hunting in the area where the new prey species appeared. There was evidence that this factor was contri- buting to the result in one of the prey species studied, adults of the bordered white moth (Bupalus pinarius) which were taken on the ground (Mook, Mook & Heikens 1960). Tinbergen rejected this as a general explanation, however, on the grounds that all other prey species occurred in the canopy of the pine wood, where the tits might have been expected to encounter them as soon as they appeared in the food complex. Note that this last point would not follow if searching in the canopy had been non- random.
(c) That the lag was a consequence of a learn- ing process in the birds. Tinbergen further considered that specific characters of the prey were involved in this learning and that the birds performed 'a highly selective sieving operation on the visual stimuli reaching the retina'. He labelled this the formation of a 'specific search- ing image' and generalized it to account for the under-representation of the species at low densities in the tits' diet. He attributed the dis- crepancy from expectation at high densities to
695
696 A N I M A L B E H A V I O U R , 19. 4
the tits selecting for food variety to avoid a monotonous diet.
At the time, there was little evidence for the third hypothesis, but it has since been demon- strated that wild birds may show striking prefer- ence in feeding on rare cryptic food items (Allen 1967). The importance of the specific properties of prey has also been shown by Croze (1970), and M. Dawkins (1971) has proved that the ability of domestic chickens to see cryptically coloured food grains changes with experience. There is, however, no direct evidence in titmice.
Tinbergen's conclusions have been criticized strongly by Royama (1970). Royama correctly points out that Tinbergen's hypothesis has since come to be treated as an established fact, and that the evidence scarcely warrants such a conclusion. Royama made extensive studies of the food fed to nestlings by great tits in both broad-leaved and larch woodlands. He also found that there were no proportional or linear relations between the density of prey species and their occurrence in the nestlings' diet, but he disagreed with Tinbergen's conclusions on both factual and theoretical grounds and constructed an alternative model to account for his own and Tinbergen's data. The fundamental assumption of this model is that the predator tries to maximize its hunting efficiency by sampling the food in different parts of the habitat ('niches') and spending most time where its success rate is high. Prey occurring at low densities are under-represented in the predator's diet, not because the predator does not learn to find them because they are rare, but because the predator rejects them as being 'unprofitable', i.e. providing a low return in biomass or energy per unit hunting time. This is consistent with Royama's finding that some large lepidopterous larvae, though relatively rare, are extensively taken by great tits, and that very few encounters with a prey species seem to be necessary to lead to a sequence of them being brought to the nest. Though it is not clear that use of searching im- ages need be contrary to efficiency in hunting, Royama's suggested mechanism of sampling 'niches' and distributing hunting effort, accord- ing to their 'profitability' makes clearer adaptive sense.
Royama's model generates predictions which accord with both his own and Tinbergen's data, and it makes a prediction about th~ behaviour of the tits (sampling a number of niches and distributing search effort non-randomly between them) which is readily testable. Some support
for this suggestion is provided by the work of Gibb (1958, 1962), who found that blue tit (Parus eaeruleus) and coal tit (Parus ater) predation on a single species of moth larvae living in pine cones could be assessed by the traces of attacks left by the fits. Although the predation was low at low densities, it was clear from the traces of attack that this was not because the tits had failed to find the prey at low density. Whether this would be true for different prey species in different areas is another question.
The possibility of an experimental approach into the distribution of hunting effort in relation to food density was suggested by the work of Hassell (1971), who found that individual para- sites (Nemeritis eaneseens, Hymenoptera) search- ing over a range of host densities in a laboratory population, spent a disproportionately large percentage of their time at the highest host densities. Other evidence which suggests that a laboratory approach to this problem might be fruitful comes from studies on 'probability learning' in birds, which suggest that titmice could behave in a similar way to Hassell's parasites. In such studies (e.g. Mackintosh 1969) a pigeon or a chicken in a problem box is pre- sented with two stimuli, one of which provides it with a reward on a random, say 75 per cent, of all responses (key-pecking, etc.), while the other stimulus is rewarded on only 25 per cent of responses. The subject learns to make more than 75 per cent of its responses to the 75 per cent rewarded stimulus. (The most efficient strategy, if the situation is stable, is to direct all the responses to the 75 per cent rewarded stimulus.) This is effectively the problem en- countered by a predator whose food occurs at differing densities in different spatial locations in its habitat, except that the predator is faced with more than two choices and that the situ- ation is inherently less stable, and hence less 'predictable'.
An experiment was therefore designed, on the probability learning principle, but using a number of different food densities, as did Hassell, to test whether a small group of great tits would indeed learn to distribute their hunting effort in relation to food density. It is likely that great tits in the wild may have secondary cues to the density of their prey species, e.g. leaf damage, or webs spun by some species of prey such as Aeantholyda nemoralis, one of the most im- portant prey species of Tinbergen's great tits. However, this factor was eliminated by making
SMITH & DAWKINS: H U N T I N G BEHAVIOUR OF GREAT TITS 697
the tits perform an operant response (removing the cap from a small, cylindrical pot) before they were able to see the prey or any manifesta- tion of them. The motor patterns and context of the behaviour are close to those shown by wild great tits searching for beech mast and ground-dwelling invertebrates among leaf litter.
Methods The Birds
Two male ('white' and 'blue-white') and three female ('red-white', 'mauve' and 'blue') great tits were used. The birds were named after the comb- ination of colour rings they carried. They had been hand-raised from the nestling stage (about 12 days post-hatching) and were 9 to 10 months old when tested. They had previously been used in an investigation of the relationship between flocking behaviour and feeding and were accus- tomed to working for food rewards by searching in a number of types of food container. Their staple diet was a mash composed of commercial chick crumbs, hemp seed, grit, bran, dried meat, puppy meal, boiled egg and vitamin additives. The mash was removed from the test area during experiments. The birds were also given 'meal- worms' (larvae of the flour beetle, Tenebrio mollitor) which served as prey in the experiment; these were the birds' preferred food.
The Aviary The indoor aviary used was divided into two
portions each of which had access to an out- side compartment. The layout is illustrated in Fig. 1. Part of the indoor area was used as a
A
I I
Slack cage
i
1 /
OI
Out side B
I Trapdoor
Search area: 12f1" (3-7m)
Fig. 1. Plan view of the experimental area. Full lines around the perimeter indicate solid walIs. Lines marked with crosses are wire mesh partitions. 01 and 02 are positions of observers.
stock cage where all the birds, except the one being tested, were held. The dimensions of the experimental area were 4.6 • 3.7 • 2.0 m (minimum height). Each of the four feeding areas (stippled in Fig. 1) consisted of a hardboard base to which were glued 256 pots in a 16 • 16 square array. The pots were made from cylin- drical sections of plastic pipe 38 mm in diameter and 30 mm high. Each pot wa~ covered by a cap of aluminium alloy foil 0-024 mm thick, as shown in Figs 1 and 2.
OTHERS
Fig. 2. Methods used by great tits to remove caps f rom the food pots.
Recording Methods The main record of the behaviour of each
bird was recorded by an observer at position 01 (Fig. 1) using an automatic keyboard recorder which represents behavioural events as notes on a small electronic organ. The sequence of coded events is tape recorded and subsequently decoded by a small digital computer which recognizes the frequency of each note and prints out a record of the event and time at which it occurred. The system is described in detail by R. Dawkins (1971). Four behaviours were recorded: lands in one of four areas; leaves area; searches (i.e. removes foil cap); and finds a meal- worm. The vast majority of the time spent on each board was spent in actually moving across the board removing food caps rhythmically. As an illustration of this, bird 'blue-white' removed
698 A N I M A L B E H A V I O U R , 19, 4
a total of 100 caps in a single bout of searching on a board with density 1, the mean interval between cap removals being 1.18 s, with a standard error of 0.05 s. In addition to the timed measures, the bird left a visual record of its searching activity by the trail of removed caps and this was recorded at the end of each experi- ment.
Training and Testing Procedure Single birds were trained to remove caps to
obtain a mealworm by first presenting food at a density of one mealworm to four pots with some of the caps removed so that the tit could see the mealworms from a perch. The five birds used learned to remove caps to obtained meal- worms within 30 min of the first presentation; a sixth bird that used an inefficient technique to remove the caps (pecking through the cap it was perched on), was not tested in the experi- ment. The techniques used by the birds to re- move the caps are illustrated in Fig. 2.
Once the birds had learned to remove the caps, the ratio of rewarded to unrewarded pots was reduced to 1 : 1 5 and three to six more trials were carried out to determine the birds' preferences for different feeding areas. In these, four half-areas with 128 pots were used. In all cases the working rate of the birds increased during this training period.
The birds were then tested, using the four complete areas (as shown in Fig. 1) for the first time. When a test was due to occur, the test bird was driven gently into outside compartment B and the trapdoor (Fig. 1) was closed. The bird was then deprived of food for approximately one hour while the experiment was laid out. The stock birds were kept in outside area A during the actual test period to prevent any possibility of observational learning. On all occasions, the t rapdoor was opened at the start of the test period and the test bird entered im- mediately. Each trial was timed to last for 5 min from the time that the test bird first landed in any feeding area. At the end of the 5-rain period, the bird was driven gently back into the outside compartment.
The birds were provided with different densit- ies of mealworms in each area so that the highest density area contained 16, the next highest 8, then 4 and finally one mealworm per 256 pots. The location of each density was kept constant between trials. The highest density was sited in the location that the bird had visited least during training and the lowest density in the most
visited location. The actual location of the meal- worms within the 256 pots in a feeding area was determined by random number tables with the restriction that no pot contained more than one mealworm. Each bird was given a series of 5-min trials until the criterion that more than half of its searching time was spent on one board on seven out of eight successive trials was reached. This took between twelve and fifteen trials for four of the birds, but required twenty- two for the fifth, 'red-white'. Trials were re- peated at approximately hourly intervals during daylight. Up to seven trials were run per day, six being the commonest number. When the consistency criterion was reached, the positions of densities 1 and 16 were reversed so that the birds were now rewarded at a low rate in the location where they had previously been re- warded at a high rate and vice versa. Intermed- iate density boards were not changed. This new condition was then held stable for a further ten to thirteen trials.
All statistical tests were taken f rom Seigel (1956).
Results The overall results are presented in two different ways in Figs 3 and 4. In Fig. 3 examples are given of cumulative records of the searching time (ordinate, see figure legend for definition) plotted against the number of trials for two in- dividual birds. In Fig. 4 the overall response of all the birds to the highest density (16) is shown.
Performance of Birds Up to the Reversal Point Figure 3 shows that the individual birds
learned to discriminate the highest density areas from the lower densities, but that the speed of this learning differed within individuals. 'Mauve ' spent the greater part of its time searching in the area of highest density almost from the start while 'red-white' learned much more slowly. These two birds were extremes, the other three birds being more like 'mauve ' than 'red-white'. I f the distribution of searching times in the less dense areas is considered, there was no clear tendency for the birds to visit these in proportion to the density of food present. This was also true for the three individuals not shown in the cumul- ative plots. There were in fact striking differ- ences in the way that individual birds treated the lower density areas.
Bearing this heterogeneity in mind, the pooled data for the responses of all five birds to food density is shown in Fig. 5. The black bars of
SMITH & DAWKINS: HUNTING BEHAVIOUR OF GREAT TITS 699
No of 5 rain trials Fig. 3. The cumulative distribution of searching time over the four densities for two individual great tits, (a) 'red-white' and (b) 'mauve'. Searching time is the total time spent on a feeding area, not including the time taken to handle prey. After the reversal point, the locations of densities 1 and 16 are reversed while those of 4 and 8 remain unchanged.
1001 /, . . . . Reversal White .,. klV I
�9 \ / ~,,# . ~ 100
o. .it.,-.-,.,',,', 100 A " ..,./'R : X # Blue- ~ 50
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o i ! ! iP l ,.,.,: A ol; ;, #! ?uv
1001 �9 t .......... \ Blue iX / "--R �9
10 20 30 TRIALS
Fig. 4. Response of all five birds to the highest prey density. The ordinate is the time spent by each bird at the highest density expressed as a percentage of the total searching time on that trial. The switch in location of the richest prey area is indicated by the symbol 'R' and the break in each record.
DISTRIBUTION OF [ ] SEARCH EFFORT [100
(on last 8 trials before reversat) I
1 ~ 5o ~.
~ . . 0 ~ 1 4 8 16
PREY DENSITY Fig. 5. Pooled data from all birds on the distribution of hunting effort in relation to food density over the last eight trials before the locations of densities 1 and 16 were reversed. Black bars indicate the observed dis- tribution of searching; unfilled bars indicate the pro- portional distribution of food over the four areas.
the histogram represent the percentage of time the birds spent actually searching (not including the time required to eat mealworms) at each density of food, over the last eight trials before the reversal point. The total t ime spent searching by each bird at each density is given in Table I. The rank sum (Fr iedman Analysis of Variance) for the density 16 has the max imum possible score and all the other rank sums do not differ f rom each other. A simple interpretat ion of this result is that the birds did learn the locat ion of the highest food density, bu t tha t they failed
700 A N I M A L B E H A V I O U R , 19, 4
Table I. Total Times (seconds) Spent Searching at Each Density Over the Last Eight Trials before Reversal
Bird Density 16 Density 8 Density 4 Density 1
'White' 1256 64 197 201
'Blue-white' 932 16 238 290
'Red-wbite' 1224 284 126 0
'Mauve' 1509 58 0 124
'Blue' 1453 37 0 0
Rank sums 20.0 10"0 8"5 11.5
The rank sums differ significantly (P<0-05) on the Friedman two-way analysis of variance.
I t is clear that, al though all birds did visit the new location, only one ( 'blue-white') reversed its previous behaviour by the time the experi- ment was terminated and spent the majori ty o f the available time searching in the new density o f 16. This was not simply a consequence o f the birds failing to find food by chance when they did visit the new high density. This is clearly shown by 'mauve ' in Fig. 6, where data f rom Fig. 5 are plotted along with a measure o f the actual number o f mealworms found on visits to density 16. This bird actually found mealworms in the first three pots it searched, on first visiting the new location o f density 16. Even this dramatically high reward rate did no t overrule the bird's previous lack o f success in that location, and it
to discriminate between the lower densities. A possible contr ibutory factor to the latter failure could be that, for each bird, the pre- ferred area during training was subsequently assigned the lowest density during actual testing, but this does not account for the failure to distinguish densities 4 and 8.
Performance After the Reversal of the Locations of Densities 1 and 16
All the five birds continued to search intens- ively in the location o f the former high density area for at least four trials after the reversal (Table II and examples in Fig. 3). By the tenth trial after reversal, however, the birds spent, on average, only 19 per cent of their searching time in the old high density area. The responses to the new location o f density 16 are shown in Fig. 4.
Fig. 6. The upper part of the figure is taken from Fig. 4. The lower part shows the number of mealworms eaten on each trial. One dot represents the capture of one mealworm.
Table II. Persistence of Response to High Density Location Despite Change in Density to 1 Mealworm Per Board
Percentage of total search time in area of density 16 before No. of trials reversal and density 1 after reversal
SMITH & DAWKINS: HUNTING BEHAVIOUR. OF GREAT TITS 701
only returned to it on four of twelve subsequent trials.
An effect of previous experience is also seen by comparing the responses to the new location of density 16 on the first five visits made to it (i.e. ignoring whether they came on the same trial or not), with their responses on the first five visits to density 16 at the beginning of testing. Figure 7 shows the distributions of intervals between successive visits to this density. (If the
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I-I ,1-1 ,
(b) Treatment a f te r locat ions reversed
r - q 10 15 20
INTERVAL
Fig. 7. The upper histogram (a) shows the frequency distribur of intervals between successive visits to the density 16, when it was first encountered by all birds at the beginning of testing. The lower histogram (b) shows the same measures when the new location of density 16 was first encountered after the locations of densities 1 and 16 had been interchanged. Only the first five intervals for each bird are plotted in each histogram.
first visit is followed by an immediate return, the interval is zero; if fifteen visits are made to other densities, then the interval is fifteen.) The upper histogram shows that the birds re- turned after less than three visits in twenty-three of the twenty-five cases when they first en- countered density 16. After the location re- versal, however, only eleven of the twenty-two intervals are less than three and the whole dis- tribution is shifted to the right. The two dis- tributions differ significantly (P<0.01, Kolmo- gorov-Smirnov two-sample test, one-tailed) and t h e effect is consistent between birds. The lower histogram also shows that birds were still likely to return immediately to the density 16, if they
did visit it after reversal. This suggests that the birds may have reacted to the recent reward rate, but that the effect decayed rapidly with time if it conflicted with longer term experience.
This last conclusion is reinforced if the measure of the interval between successive visits to density 16 is correlated with the rank order of the visit to that density (first, second, etc.). There is a marginally significant decrease in interval size ( r = - - 0 . 3 4 3 , P<0.05 , Spearman Rank Correlation) as the number of visits to density 16 increases during the first five visits when the test series begins, i.e. the birds became increasingly ready to visit the board, but there is no such decrease (r=-}-0.036, P >0 .5 ) in the same measure during the first five visits after reversal.
The birds' response to densities 4 and 8 after reversal contrasts with their apparent failure to discriminate these two densities before reversal. I f the overall numbers of visits paid to the two densities after reversal are compared (Table III), over twice as many visits are made to
Table HI. Comparison of the Numbers of Visits Made to Densities 4 and 8 by Individual Birds
'P' value for Before After comparison of
l(reversal reversal before and after ast eight (all tr ials) reversal
trials) (Fisher exact - - probability test)
4 8 4 8
'Mauve' 1 1 14 7 0 89
'Red-white' 3 8 10 29 0.70
'Blue' 0 2 0 25 1.00
'White' 10 6 11 26 0"03
'Blue-white' 9 1 9 3 0.37
Totals 23 18 44 90 0.007
density 8 than to density 4 (P=0.007, Fisher exact probability test). Although at first it might seem that the birds had either learned at last that the two densities differed, or that they had already possessed the basis for making the discrimination bat had no expressed it, the data show (Table III) that the contributions of individuals are hetero- geneous. Only one bird ('white') shows a change in behaviour under the two different conditions, while 'blue' and 'red-white' behave in a more or less consistent way but make more visits overall
702 A N I M A L B E H A V I O U R , 19, 4
and hence inflate the total visits to density 8 because they already showed an excess of visits to density 8 compared with density 4. To sum up, it seems that the low frequencies of visits to densities 4 and 8 in the last eight trials before reversal may have been obscuring the fact that strong individual differences existed between the birds in their treatment of these areas, and that the overall excess of visits to density 8 after reversal is partly an expression of these differ- ences.
The Effect of the Asymmetry of the Test Area It can be seen from Fig. 1 that birds moving
between the four searching areas do not always have to travel the same distance. The area near the centre of the room is nearer all the other areas than they are to each other, and this is reflected in the birds' behaviour. I f the total number of transitions between areas is accum- ulated and classified according to whether the transitions are 'long' or 'short' (the latter class involving the central area and the former not), the birds make 130 short transitions and only sixty long ones. This differs significantly ( P = 0.0003, Fisher exact test) from the expected numbers of long and short transitions calcu- lated on the basis of the total number of visits to each location. That the effect of the asym- metry did not over-rule the response to density is emphasized by the fact that, despite the topographical bias, the central area is not the area to which the largest number of visits were directed. Only rarely did a bird make a long transition without flying up into a tree or other vantage point. It should, however, be pointed out that the measure of the number of visits is perhaps a poor one, as this was also affected by the fact that two of the birds ('red-white' and 'blue') left the searching area to eat captured mealworms in a high percentage of cases (87 per cent and 94 per cent respectively). The other three birds all ate more than 60 per cent of their total captures on the search areas. The differential treatment of densities 4 and 8 discussed above was not apparently a simple consequence of the topography, as the central board had a density of 4 in two cases, but a density of 8 in only one case.
The Effect of the Concentration of the Searching Effort on Density 16
Although the birds' searching did not seri- ously deplete the average density of mealworms per pot (since at most 155 pots were searched
and eleven mealworms captured in any one trial), the intensive searching on density 16 did influ- ence the results. The birds searching strategy was generally forward-biased, so that they cut a swathe of searched pots through the area they were visiting. When the number of searches exceeded about 70, these paths began to cross and the searching bird was forced to cross areas which had already been searched out to reach 'new ground'. Until the recrossing of paths happened, the birds' search speed was much as in other areas, but at such times, the birds also tended to pick up and toss away foil caps which had previously been removed and this did not always seem to be related to the mere removal of an obstruction to further searching. The net effect of this factor caused a lower average searching speed (i.e. number of caps removed per unit time) on density 16 areas which were the only places where enough depletion occurred. This lowered searching speed was not evident on visits to density 16 before serious depletion had occurred. This factor was also responsible for an apparent difference in the treatment accorded to density 16 by the birds. The number of searches the birds made on each area before leaving unrewarded were smaller on density 16 compared with density 4 (P=0.03; Mann- Whitney 'U ' test), but, if the 'giving-up' times were compared, this difference was no longer significant (P=0.27, 'U ' test). This agrees with the finding of Croze (1970, p. 19). The depletion factor could also have been at least partly responsible for an increase in the average time taken to handle each mealworm with increasing number eaten on any one trial (Fig. 8). This last effect may, however, be a real one, as observa- tion indicated that the birds tended to swallow mealworms whole at the beginning of a trial. Later in a trial they often prepared the meal- worm by first removing the head end, then re- moving the gut and finally, swallowing the abdomen. Handling times involving the latter process were not measured, as the bird usually flew off to a perch before decapitating the meal- worm and the behaviour off the feeding area was not recorded.
Discussion The Potential Effects of the Density Response on Prey Populations
It is clear that, if wild great tits were faced with a similar range of densities and behaved like the experimental birds, they would exert a disproportionately high predation on those prey
SMITH & DAWKINS: HUNTING BEHAVIOUR OF GREAT TITS 703
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1st 3 r d 5th 7th 9th
ORDER OF CAPTURE
Fig. 8. The relation of the mean time taken to handle a single mealworm by all birds to the order of capture within a 5-rain trial. 95 per cent confidence limits are given for the means.
occurring at highest density. Since the time spent searching at lower densities was roughly equal, it would be expected that the effect of individual tits hunting at these densities would be pro- portional to food density, but of relatively low intensity. Tinbergen's data showed that the transition of predation f rom below to above the expectations on a random searching assump- tion occurred at low to moderate relative prey densities, but his measures of density were average figures for each territory rather than micro-habitat densities comparable to the ex- perimental situation. Ideally the behaviour of the tits should be investigated under field con- ditions to test whether the laboratory findings apply to wild birds, but this is of course very hard to achieve.
Some evidence, which suggests that the situation could potentially occur in the wild is provided by the work of Gibb (1958). Gibb demonstrated significant variations in the 'in- tensity' of the larvae of the eucosmid moth Enarmonia conieolana, which inhabits pine cones and is heavily preyed on during winter by coal and blue tits. The 'intensity' of the larvae (the number of larvae per five pine cones) showed a variation of up to sixteen-fold. This was not necessarily a measure of absolute density as the number of cones per tree was, m one year, inversely related to the intensity.
However, it would provide a density estimate in terms of the search effort required by the hunting bird. The relative frequencies of differ- ent larval intensities found by Gibb are shown in Table IV). Gibb 's data show that the higher intensities are relatively less frequent than the lower intensities and this would potentially operate against a predator attempting to con- centrate its hunting effort at the highest in- tensities. Gibb indeed found that the concen- tration of his tit predators on the high intensities was much weaker than that shown by our ex- perimental birds, but it should be remembered that these were predominantly non-territorial birds searching over fairly large areas. Our experiments were envisaged as a simple model of a stable situation where a bird is familiar with a small area, such as its territory. A more appropriate model of a winter situation would be provided by a situation where the location of the high densities was not fixed and the tit had to sample new feeding areas and assess their profitability without the benefit of recent previous experience.
Table IV. Distribution of 'Intensities' (See Text) of Enarmonia conicolana Larvae in Pine Cones
Larval intensity No. of plots (no. of larvae per
5 pine cones) (15 x 15 m)
<2 93
2-3 131
3--4 43
>4 15
Data from Gibb (1958, Fig. 4, p. 387).
A further example of variations in density of an important prey species of the great tit is pro- vided by the work of G. R. Gradwell (personal communication) on the winter moth, Oper- ophtera brumata. Data collected over a 20-year study by Gradwell and Professor G. C. Varley on the numbers of winter moth larvae that fall to pupate f rom each of five dispersed oak (Quercus robur) trees, show that five to tenfold variations in numbers between the least and most infested trees were common.
I t is also likely that, contrary to Tinbergen's assumption that the prey of his great tits was randomly distributed, that the prey of great fits will show aggregated distributions. A survey by Taylor (1961) has shown that a wide variety
704 A N I M A L B E H A V I O U R , 19, 4
of both cryptic and conspicuous animals tend to show such aggregation, admittedly over differing sizes of sample units. An aggregated prey distribution would favour non-random searching by the predator, as one of us has shown (J.N.M.S. unpublished results) in wild blackbirds, Turdus merula, and has been shown for flocks of the same individual great tits by J. R. Krebs and M. H. MacRoberts and J. M. Cullen (in preparation).
The strong persistence of the experimental birds' searching in areas which had previously contained a high density of food, and their tendency not to return, even if they did visit an area where a high density of food had re- cently appeared, are relevant to the finding of Tinbergen that the appearance of a new prey species in the tits' diet lagged behind its increase in density in the food complex. Both types of behaviour could contribute to the occurrence of such a lag, but other explanations, such as changes in the relative profitabilities of different species (Royama 1970), are also possible. It is also likely that finding a new prey type, par- ticularly a larger, more profitable species, might direct the tits' hunting behaviour to a new area. The delay in reacting to a change in the spatial distribution of food is obviously contrary to the short term hunting efficiency of the birds, and may surprise ecologists. Psychologists, on the other hand, will recognize that the experiment provided a partial reinforcement situation, which is well known (e.g. Hilgard & Marquis 1961) to produce operant behaviour that is resistant to extinction. It remains to be seen whether the degree of persistence shown is an artefact of the simplified experimental environ- ment, but it is interesting to note that Allen (1967) found a striking parallel to this spatial conservatism in the responses of wild birds to new varieties of coloured food items.
The Adaptiveness of the Tits' Behaviour The concentrated searching at the highest
prey density is clearly a more efficient strategy than random searching. The tits' behaviour is very similar to the behaviour of single Nemeritis searching over a range of host densities (Hassell 1971). The Nemeritis, however, probably used tactile, visual or olfactory clues about prey density to orient their searching, rather than a learned assessment of the profitability of differ- ent areas. The failure of the birds to show a discrimination of the lower densities does not accord so simply with Royama's hypothesis.
It is possible that further experiments might demonstrate that great tits do discriminate the lower densities in this type of situation, but it could also be the case that the result stems from a fundamental property of the birds' choice behaviour.
With this latter possibility in mind, it is interesting that the indiscriminate behaviour shown between the lower densities is predicted by a version of the threshold model of choice behaviour developed by Dawkins (1969a, b). In the model, stimuli to which responses may be directed (e.g. feeding areas) possess threshold values for each stimulus dimension (e.g. differ- ent relative profitabilities or distance from the nearest perch). The animal is then supposed to respond according to the size of a fluctuating hypothetical variable, so that, if the magnitude of this variable rises above the threshold of the strongest stimulus, then all responses are directed to that stimulus. I f the variable rises above the threshold of any weaker stimulus, the animal will respond indiscriminately, because of a switch of attention to a different stimulus dimension (e.g. distance from the nearest perch, etc.). This would produce qualitative effects just like those shown by the tits, but there are too few birds to make any quantitative assessment of the predictive value of the model.
An important factor in these experiments is that there is a pressure on the tits to maximize their hunting efficiency, since each trial is pre- ceded and followed by periods of food depriva- tion. This will, no doubt, often be true for wild great tits, particularly during the feeding of the young. However, at other times there will not be continuous pressure on wild tits to maintain their hunting efficiency at a maximum. These periods will be used for other maintenance activities, but they may also be used in exploratory foraging, which may be very important in allowing in- dividuals to monitor changes in the spatial pattern and species composition of the food complex. Tame great tits explore and manipulate strange objects intensely and wild titmice are also noted for their exploratory behaviour, which has allowed them to acquire such feeding habits as breaking through the foil caps of milk bottles to obtain cream (Fisher & Hinde 1949).
One of the few field studies on the distribution of hunting behaviour in relation to food density has been the work of Goss-Custard (1970) on the redshank, Tringa totanus. He studied flocks of redshank feeding in winter on the burrowing amphipod, Corophium volutator, in an estuarine
SMITH & DAWKINS: HUNTING BEHAVIOUR OF GREAT TITS 705
habitat. He found that redshank also were choosing to feed in more profitable areas and, in one transect, there was a suggestion that the redshank were spending a disproportionately large amount of time feeding at the highest Corophium densities. In a second transect, the situation was complicated by the redshank taking a large alternative prey (the polychaete, Nereis diversicolor) and there was no cor- relation between redshank density and Coro- phium density or biomass. A factor which could have been inhibiting the redshank from con- centrating their hunting strongly in the most profitable areas was mutual interference in feeding efficiency between flock members.
Some comparable experimental work on the response of vertebrate predators to food density is that of Holling (1959, 1965), who found that deermice (Peromyscus leucopus) showed a rela- tively weak tendency to concentrate on the higher densities of sawfly coccoon prey. Hol!ing presented the different prey densities successive- ly, in combination with an ad libitum supply of less palatable food, I t is less easy to see this design as a plausible model o f a natural situ- ation and it would be interesting to repeat Holling's experiments with a range of prey densities simultaneously available to the rodents.
Another factor which might influence the density level at which it would be profitable for great tits to search intensively for a particular prey species, would be an explanation like the search image hypothesis favoured by Tinbergen. The best evidence that birds have to ' learn to see' prey objects, comes from laboratory experi- ments on chickens (M. Dawkins 1971). When similar careful work has been carried out on great tits in either laboratory or field situations, the status of Tinbergen's hypothesis as a con- tributory factor to their responses to food density will become dear. Until then, Royama 's interpretations provide a simpler explanation which accords better with both the field data and these preliminary experiments.
Acknowledgments Dr J. M. Cullen, J. G. Frazier, Dr M. H. Mac- Roberts, Professor N. Tinbergen, Dr J. D. Goss- Custard and Dr M. Dawkins criticized the manuscript and offered many helpful comments. Miss R. L. de Boer provided valuable assistance in carrying out the experiments. We are especi- ally grateful to Dr J. R. Krebs and Dr M. H. MacRoberts for allowing us to use their hand- reared great tits. Dr M. Dawkins, Dr M. P.
Hassell, Dr G. R. Gradwell, Dr J. R. Krebs, Dr M. H. MacRoberts and Dr J. M. Cullen kindly allowed us to quote from their unpub- lished work. We are grateful to Dr S. Neill for the drawing in Fig. 2, to L. C. Shaffer for photo- graphic advice and assistance and to Mrs P. M. Searle for typing the manuscript. Financial support was received from the Science Research Council. The work was done in the Department of Zoology, Oxford, by kind permission of Professor J. W. S. Pringle.
The work forms part of the thesis work of one of us (J.N.M.S.), who is entirely responsible for its conception, design and presentation. R.D. 's role was confined to developing the recording apparatus, and performing some of the experimental observations.
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(Received 10 February 1971 ; revised 30 April 1971 ; MS. number: 1034)
