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Effects of food supply, hunger, danger and competition on choice of foraging location by the fifteen-spined stickleback, Spinachia spinachia L.
Anita. Behav., 1991,42, 131-139
Effects of food supply, hunger, danger and competition on choice of foraging location by the fifteen-spined stickleback, Spinachia spinachia L. M. I. C R O Y & R. N. H U G H E S * School o f Biological Sciences, University College o f North Wales, Bangor, Gwynedd, LL57 2UW, U.K.
(Received 27 June 1990; initial acceptance 15 August 1990; final acceptance 21 December 1990; MS. number." 3601)
Abstract. A group of fifteen-spined sticklebacks were given the choice of two food sources. The fish
sampled both sources, but with decreasing frequency as each trial progressed. Sampling was more frequent when the fish were hungry than when partially satiated. The fish spent more time at the more profitable source, discrimination being marked when profitability was determined by delivery rate, but less pronounced when determined by prey size. Given food sources of equal mean delivery rate, hungry fish concentrated on the variable source and partially satiated fish on the constant source. The fish became more reluctant to feed and to visit a source where there had recently been a simulated threat of predation, but reluctance was less when the dangerous source was also more profitable, especially when the fish were hungry. The fish distributed themselves in proportion to the profitability of the food source (ideal free distribution). Competitive ability varied among the fish according to their size. The two largest, competitively superior fish sampled the food sources more frequently than their inferior competitors. They quickly intercepted food and could efficiently track any short-term changes in delivery rate. Inferior competitors sampled frequently at first, but then settled for one food source, concentrating on prey missed by their competitive superiors and reducing travel costs. Fifteen-spined sticklebacks, therefore, behave in accordance with the 'energy maximization premise', subject to the constraints that risks of starvation and predation are minimized and that adjustments must be made towards competitors. Sampling is a conspicuous feature of the foraging behaviour and is appropriate to the temporally and spatially heterogeneous, natural food supply of these fish. During the prolonged popularity of optimal foraging theory, experiments abundantly vindicated the idea that foragers tend to maximize their net rate of energy gain (Hughes 1980; Pyke 1984; Stephens & Krebs 1986). Inevitably, subsequent theoretical refinement has relaxed simplifying assumptions, particularly in three areas. These are (1) information acquisition by sampling (Oaten 1977; Green 1980; Johnston & Turvey 1980; Iwasa et al. 1981; McNamara 1982), (2) energy status of the forager and the perception of risk, either as a precarious food supply (Caraco et al. 1980; Stephens 1982) or as danger from predators (Gilliam 1990; McNamara 1990) and (3) competition among foragers (Sutherland & Parker 1985). Although often considered in isolation (but see Milinski 1990), all the above factors are likely to influence the behaviour of any forager that has a labile energy budget, exploits variable food supplies, ranges widely in its habitat and is not entirely soli*To whom all correspondence should be addressed. 0003 3472/91/070131+09 $03.00/0
tary. For this reason, we decided to examine their effects on the foraging behaviour of the fifteenspined stickleback. This animal shows energy maximizing behaviour when selecting its diet, is sensitive to short-term changes in hunger and rapidly learns the characteristics of prey and of their locality (Croy & Hughes 1991a, b). If sampling is important, foragers should visit food sources alternately, before deciding to exploit the most profitable source exclusively. In the case of great tits, Parus major, the frequency of sampling is correlated with the similarity in profitability of the food sources (Krebs et al. 1978). If energy status is important, starving foragers should exploit variable food sources offering the chance of a large reward, sufficient to restore a positive energy balance, whereas those already in a positive energy balance should concentrate on more predictable supplies of food. This is characteristic of small birds and mammals with precarious energy budgets (Barnard 1990), but could also be true of active poikilotherms with a limited energy storage capacity. All
9 1991 The Association for the Study of Animal Behaviour 131
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vulnerable foragers should be sensitive to the risk of predation, but sensitivity may be reduced if there is an urgent requirement for food. Thus when hungry, three-spined sticklebacks, Gasterosteus aculeatus, will approach closer to perceived danger in order to obtain larger rewards (Milinski & Heller 1978). Competition among foragers may interact with productivity of the food sources, through the differential distribution of individuals. If foragers are of similar competitive ability, their numbers should become distributed directly in proportion to the profitability of alternative food sources, according to the ideal free distribution (Fretwell & Lucas 1970). Superficial agreement with this prediction has been found among three-spined sticklebacks (Milinski 1979, 1984), mallard, Anasplatyrhynchos (Harper 1982) and cichlids, Aequidens curviceps (Godin & Keenleyside 1984). Details of behaviour, however, revealed a more complex situation in these cases, involving unequal competitive abilities and correlated differences in foraging behaviour. There is, therefore, a need for more information on mechanisms that result in superficial conformity with the ideal free distribution (Sutherland & Parker 1985; McNamara & Houston 1990). METHODS
General Methods We maintained sticklebacks of 125-150mm total length, on the flesh of mussels, Mytilus edulis, for 2 months prior to the experiments. For use as live prey, we cultured Artemia sp. on a daily ration of Rhodomonas balthica. We set up an experimental aquarium, measuring 1500 x 700 x 700 mm, containing seawater at 11 + 1~ and illuminated overhead by 60-W fluorescent tubes on a 12:12 h light: dark photoperiod. We screened three sides of the aquarium with black polythene sheeting and left the fourth clear for observation. Two foraging areas were delimited by a central, Perspex partition, flanked on either side by a band of weed made from strands of polythene. The weed was sufficiently dense to occlude vision from one foraging area to the other and provided a refuge for uneaten prey. A 150-mm gap between the central partition and rear wall allowed the fish to move freely between foraging areas. Each foraging area was furnished with an aerator, recirculation filter and gravel substratum. To deliver prey at known rates into each foraging area, we made twin-carousels, controlled by a
microcomputer (Croy 1989). We positioned the carousels in front of the aquarium, so that they delivered food into each foraging area at a point marked by a clump of weed. We video-recorded the behaviour of the fish and transcribed the data using a microcomputerized event recorder. Before each set of experiments, unless otherwise stated, we ensured that the fish were already familiar with the prey and the apparatus. On 8 consecutive days, we placed fish individually in the experimental aquarium, allowed them to settle for 30-45 min and, using both carousels, fed them with one Artemia every 20 s over a 20-min period, commencing at a standard time of day for each fish. By the end of a daily feeding period, the fish showed signs of satiation.
Sampling Behaviour We subjected nine individual fish to daily feeding trials each 20 min long as described above, but with two additional regimes of food delivery. First, the carousels delivered one Artemia per 20 s in one foraging area and two per 20 s in the other. Delivery rates were assigned randomly between the two areas on three consecutive daily trials. To nullify any bias that may have been developed by the experimental fish, delivery rates were equalized at one Artemia per 20 s for three more daily trials. Second, we repeated the procedure using equal delivery rates, but with Artemia of optimal mass (Croy & Hughes 1990) in one area and half the optimal mass in the other, assigned randomly between areas on three successive daily trials. We recorded the proportion of time a fish spent foraging in each area, together with the frequency of switching between areas during 1-min intervals throughout each trial. Risk-sensitive Foraging We wished to test the idea that hungry fish should be risk prone, choosing the variable food supply, and partially satiated fish risk averse, preferring the constant supply. First, we gave nine replicate fish the opportunity to assess and learn the characteristics of the two food sources, one delivering one Artemia every 20 s, the other with the same mean delivery rate, but dispensing no or two Artemia in random order at 20-s intervals. Eight daily trials, each of 10 min and commencing at a standard time of day for each fish, were judged sufficient for the fish to learn the differences between foraging areas (Croy & Hughes 1990). We then deprived the fish of
Croy & Hughes: Patch choice by sticklebacks Table I. Statistical characteristics of the variable food source used to investigaterisk-sensitiveforaging Variation of reward
Mean reward
Variance of reward
Variance/ Mean
2or0 3orl 4or0
1 2 2
2 2 8
2 1 4
Reward = number of prey items per delivery. food for 24 h and repeated the feeding protocol on 3 consecutive days, noting the initial choice of foraging area, the time spent in each area and the frequency of switching between areas during 1-min intervals throughout the trials. Finally, we repeated the entire procedure I h after having satiated the fish with mysid flesh. To investigate the effect of variance in food supply (Caraco 1981), we ran two further sets of experiments, using the same general protocol, but delivering two Artemia every 20 s in the constantdelivery area and one or three in random sequence, then none or four in the variable-delivery area (Table I). Danger of Predation We wished to investigate the influence of perceived danger and its interaction with hunger and delivery rate on the choice of foraging area. We subjected 18 fish to the preliminary feeding protocol (General Methods). We then kept a control group of six of the 18 fish unfed for 24h and subjected them to a 20-min trial in which one optimally sized Artemia per 20 s was dispensed in each foraging area. We ran a second trial 6 h later, when the fish would have become hungry again (Croy & Hughes 1991b). We repeated the entire procedure on each of 3 consecutive days, recording the numbers offish feeding in each area throughout the trials. Using the same feeding regime with a second group of six fish, we simulated danger at mid-trial by dropping a realistic model kingfisher into one of the foraging areas (Pitcher et al. 1988). Remote control ensured that the fish could not anticipate the arrival of the model, which was removed immediately after plunging. We separated replicate trials by 3-day intervals, to avoid the fish habituating to the model (Magurran & Girling 1986). We repeated the experiment with the model predator, using a third group of six fish I h after
133
they had been satiated with mysid flesh. Finally, we repeated the entire set of experiments with the same fish but with a delivery rate of two Artemia per 20 s in the 'dangerous' area and one Artemia per 20 s in the 'safe' area.
Competition First, we established the differences in competitive ability among six fish, the maximum number identifiable without tagging. Using the preliminary feeding protocol (General Methods), we allowed the six fish to become familiar with the apparatus and food source. Between trials, we satiated the fish with mysid flesh, in order to standardize their hunger levels. The fish were then collectively subjected to six, daily, 20-min trials in the same foraging area; we finally repeated the entire procedure in the other foraging area. We recorded the number of successful attacks on prey made by each fish throughout the trials. Having established their competitive hierarchy, we observed the foraging behaviour of the six competitors presented with a choice of foraging location. Before the experiments we allowed the fish to become accustomed to the two food sources and to reach comparable hunger levels during 8 days of standard feeding protocol, as described above. We then subjected the competitors to three, daily, 20-min trials in which one optimally sized Artemia per 20 s was delivered to each foraging area. We recorded the number of successful attacks and number of switches between areas made by each fish. To investigate the criteria used by the fish to decide where to forage, we repeated the experiment three times using the same fish, with the following modifications. First, the Artemia were dispensed at the same mean rate as before, but at irregular intervals. Second, the Artemia were dispensed at twice the normal rate in one area, assigned randomly. Equal rates were then restored for 3 days to nullify any preference of foraging area resulting from the experiment. Third, Artemia of half the optimal size were dispensed at the normal rate in one area and optimally sized prey in the other, assigned randomly. RESULTS
Sampling The mean proportions of time spent foraging in alternative areas with equal delivery rates and prey
Animal Behaviour, 42, 1
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Figure 1. Response to profitability: proportion of total time that individual fish spent feeding at alternative food sources, A and B. Data are medians with quartiles. (a) Delivery rates equal; (b) delivery rate etA twice that of B; (c) delivery rates equal, but prey size in A twice that in B. size were not significantly different (Fig. 1, M a n n Whitney U-test, Z = 1, N = 5 4 , P > 0 . 1 ) . The fish switched between foraging areas at an average rate of once every 20 s in the first half of a trial and once every 56 s in the second (Wilcoxon matched-pairs signed-ranks test, Z = 2 . 4 5 , N = 2 7 , P<0-05). A similar temporal decline in sampling rate also occurred in other trials, below (Wilcoxon matchedpairs signed-ranks test, Z = 2.60, N = 27, P < 0"01 in both trials). When presented with food sources of unequal profitability, the fish spent significantly more time in the more profitable area (Fig. 1, U-test, Z = 6 . 2 1 , N = 5 4 , P<0.001). Switching frequency was not significantly different between trials with equal and unequal food sources (;(2= 2.46, df= 1, P > 0-1). Although the fish spent significantly more time foraging in the area with optimally sized prey (Fig. 1, U-test, Z = 2.14, N = 54, P < 0-05), their discrimination between areas was less pronounced than in the previous experiment with unequal delivery rates and similar prey size. The fish switched between foraging areas offering differently sized prey more frequently than in trials with equal delivery rate and prey size (Z 2 = 6.26, df= 1, P < 0.05). N o significant difference in switching frequency was found between individuals (Z2= 15-38, dr=8, P > 0 ' 0 5 ) . This contrasts with the marked differences in switching frequency observed within groups of fish in the Competition experiments (see below).
Risk-sensitive Foraging Hungry fish first attacked prey significantly more often at the variable food source (Fig. 2, hierarchi-
Type of food source
Figure 2. Risk-sensitive foraging: numbers of fish attacking their first prey item in either the constant (D) or the variable (111) food source. Description of reward: (a) constant = 1, variable = 2 or 0; (b) constant = 2, variable = 3 or 1; (c) constant=2, variable=4 or 0. First pair of columns: hungry fish, second pair: partially satiated fish. cat log-linear analysis, G = 41-54, df= 2, P < 0"001), but their response was not significantly influenced by the variance to mean ratio (G=0.34, df=2, P > 0 . 5 ) . In contrast, partially satiated fish first attacked prey significantly more often at the constant food source (Fig. 2, G=20.03, df=l, P<0.001). Differences in the variance to mean ratio had no significant effect on the tendency to favour the constant food source (Table I; G = 2"90, df=2, P > 0.2). Hungry fish spent significantly more time feeding at the variable than at the constant food source (Friedman A N O V A , ;(2= 10.89, df= 1, P<0-001). They switched between foraging areas more frequently than partially satiated fish (;(2 = 7.12, df= 1, P<0.01). There was no significant variation among the fish in the proportion of time spent feeding during trials (;(2=5.18, df=8, P > 0 . 1 ) or in the frequency of switching between food sources (;(2 =9.07, df= 8, P>0.1).
Danger of Predation When delivery rates were equal (Fig. 3a), fish in the control group distributed themselves evenly between the two foraging areas (data pooled for both hunger levels, ;(2=3.16, df=l, P>0"05). Once the model predator had been presented, the number of fish feeding in the dangerous area was depressed throughout the remaining 10rnin of the trial (ANOVA, F = 1 2 4 . 1 , df=2, P<0.001). Avoidance of the dangerous area was less pronounced among hungry fish (ANOVA, F = 4 9 . 6 ,
Croy & Hughes." Patch choiceby sticklebacks
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Figure 4. Competitive hierarchy: number of attacks per
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Figure 3. Risk of predation: numbers of fish foraging at alternative food sources, A and B. Data are means with 95% confidence limits. [23: partially satiated fish; I1: hungry fish. (a) Delivery rates equal; (b) delivery rate of B twice that of A.
df=2, P<0.001). Approximately equal distributions of fish between foraging areas were resumed in all trials occurring 6 h after the threat. When delivery rates were unequal (Fig. 3b), fish in the control group distributed themselves in proportion to the food supply (Z2=44.0, df=l, P<0-001). Fewer fish fed in the dangerous area after the threat (ANOVA, F=246.5, df=2, P<0.001), but this response was less pronounced than in the previous experiment, when delivery rates were equal in the dangerous and safe areas. Hungry fish were more reluctant to avoid the dangerous area than partially satiated fish (ANOVA, F = 13.38, df=2, P<0.001). Six hours after the threat, in all trials, the fish resumed a distribution in proportion to the food supply (Fig. 3a, b).
Competition The number of successful attacks per trial was correlated with length of the fish (Spearman rank correlation, rs=0.68, df=71, P<0.001). Mean
attack rate ranged from 1 per trial for the smallest fish, 125 mm in length, to 20 per trial for the largest, 150 mm in length. The fish, therefore, could be ranked in competitive ability according to their size (Fig. 4). The frequency of switching between foraging areas varied considerably among the fish (;(2= 28.87, df=5, P<0-001). The two largest fish switched the most and there was a significant correlation among the fish between switching frequency and attack frequency (r s = 0.54, df= 71, P < 0"001). As in the Sampling experiments (see above) switching frequency declined within trials and was always significantly less in the second half of a trial than in the first (Wilcoxon matched-pairs test, Z = 2.91, N = 54, P < 0.001). There was no significant difference in switching frequency between trials with equal arid unequal delivery rates (Fig. 5a, b, Z2=0-21, dr= l, P > 0"6), but when delivery rates were equal, fish switched significantly more often in trials with unequal sizes of prey than in those with optimally sized prey only (Fig. 5a, c, Z2 = 6.4, dr= l, P < 0"01). There was no significant difference in the distribution offish between alternative areas, either with constant or irregular food supplies (Friedman ANOVA, Z2=2.44, d r = l , P>0.05) and so the data were pooled for the following analyses. There was no significant departure from an even distribution of fish between food sources with equal delivery rates (Z2=3.27, d r = l , P>0"05). With unequal delivery rates, the fish distributed themselves proportionately (Z2 = 60'0, df= l, P < 0.001). When delivery rates were equal, but prey size differed, the fish distributed themselves evenly (;(2= 0.03, dr= l, P > 0.9). We concluded, therefore, that the fish were responding to reward frequency rather than rate of energy gain per se.
Animal Behaviour, 42, 1
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Figure 5. Sampling behaviour: frequency of switching between alternative food sources, plotted as a function of time during the trial. Data are medians with quartiles. (a) Food sources with equal delivery rates; (b) one food source with twice the delivery rate of the other; (c) food sources with equal delivery rates, but with prey items of twice the mass in one than the other9 DISCUSSION Sampling is an important component of the foraging behaviour of fifteen-spined sticklebacks. In our experiments, the fish frequently switched between food sources at the beginning of a trial, the rate declining to a low level within 20 min. Hunger would have declined in parallel, but since similar trends were shown by initially hungry and partially satiated fish, the reduction in switching frequency probably corresponded to an increasing awareness of the relative quality of the food sources, resulting in a decision by the fish to concentrate on the source with the higher delivery rate. This resembles the sampling behaviour first described for great tits
(Krebs et al. 1978). Our sticklebacks also discriminated between food sources on the basis of prey size, but evidently this required more prolonged sampling than discrimination between delivery rates. Delayed discrimination based on the size of food items has also been recorded for mallard (Harper 1982). In that study, food sources had equal delivery rates, but pieces of bread were twice as large at one source. The birds initially distributed themselves evenly, as if responding to reward frequency, but later redistributed in the ratio 2:1, suggesting a response to the size of the food and hence to the rate of energy intake. Fifteen-spined sticklebacks are sensitive to probabilistic variation of food supply and modify their foraging behaviour in accordance with their energy status. Partially satiated fish, with a positive energy budget, initially preferred variable food supplies, whereas those deprived of food for 24 h and therefore with a smaller positive energy balance (Walkey & Meakins 1970), preferred variable supplies. Hungry fish, however, switched less frequently between food sources as each trial progressed and this may have resulted from decreasing hunger levels, tending to make the fish shift from a risk-prone to a risk-averse state (Barnard 1990). The variance of mean ratio in reward rate seemed to have little influence on the sticklebacks, in contrast to dark-eyed juncos, Junco hyemalis, which show hunger-dependent sensitivity to this parameter (Caraco 1981). This marked response of fifteen-spined sticklebacks to supply variance is surprising, in view of the small risk of fatal starvation. Poikilothermic metabolism and substantial bodily energy reserves should enable adults to survive many days without food. Risk-sensitive foraging is to be expected where animals quickly exhaust their energy reserves and where there is a cyclical energy debit caused by circadian restrictions in foraging opportunity. Without such periodic starvation, foragers are expected always to be risk averse (e.g. McNamara 1990; McNamara & Houston 1990). Foraging activity in fifteen-spined sticklebacks may have a tidal rhythmicity, especially among those fish confined to shallow pools at low tide. Availability of prey may also fluctuate tidally. Yet it seems unlikely that critically long periods of food deprivation will occur regularly. How precarious must the daily energy budget be in order to justify risksensitivity? Starvation, if not potentially fatal within the cycle, must at least jeopardize the forager's
Croy & Hughes." Patch choice by sticklebacks chances of recuperation. If irredeemable energy loss is not a significant possibility, then some other explanation must be sought for the apparently risksensitive foraging behaviour of fifteen-spined sticklebacks. More information is needed. Many animals are known to adjust their foraging behaviour in response to the threat of predation. Examples include three-spined sticklebacks (Ibrahim & Huntingford 1989), sparrows, Passer domesticus (Grub & Greenwald 1982), squirrels, Sciurus carolinensis (Lima et al. 1985) and minnows, Phoxinus phoxinus (Pitcher et al. 1988). In general, animals are more reluctant to forage in places where they perceive a risk of being attacked; but when danger and food supply coincide, foragers may partially overcome their reluctance in proportion to hunger or potential reward. ' Risk- balancing' (Frazer & Huntingford 1986), in which the forager approaches closer to a source of danger to achieve greater reward, may be an optimal response when foraging is normally associated with the risk of predation (Pitcher 1980). This has been demonstrated experimentally for juvenile Coho salmon Onchorhynchus kisutch (Dill 1983), three-spined sticklebacks (Milinski 1985) and minnows (Pitcher et al. 1988). Fifteen-spined sticklebacks are probably constantly at risk to predation by larger fish and birds, especially by terns, gulls and cormorants, all of which are regularly seen hunting in the tide pools where we obtained our fish. Although our experiments did not quantify how much risk sticklebacks would tolerate for a given reward rate (cf. Abrams & Dill 1989), they clearly showed that the likelihood of persisting after threat increased with reward rate. Foragers are also liable to become more reckless when hungry. After food deprivation, three-spirted sticklebacks prefer to forage where there isa high density of prey, but when partially satiated they choose less productive areas, where time can be more effectively partitioned between foraging and vigilance (Milinski & Heller 1978). Our fifteenspined sticklebacks were more likely to remain foraging after a threat when they were hungry. Reluctance to forage in the vicinity of danger, therefore, is partially overcome by increasing hunger or reward potential, emphasizing the importance of energy state as a regulator of foraging behaviour (McNamara & Houston 1986; Houston et al. 1988; Sih & Moore 1990). Competition is yet another factor influencing the behaviour of foragers. If competition is of the
137
'scramble' rather than the 'contest' or 'despotic' type, then the ideal free distribution model (Fretwell & Lucas 1970) successfully predicts the observed trend for local densities of foragers to match food supplies (Milinski 1979, 1984; Godin & Keenleyside 1984; Pitcher et al. 1988). Behavioural mechanisms responsible for this matching are, however, poorly understood (Sutherland & Parker 1985). One possibility is that foragers constantly update their evaluation of food sources by comparing current feeding rates with memorized success (Kacelnik & Krebs 1985). An example of this type of mechanism is the relative pay-off sum (Harley 1981). A decision to exploit a food source depends on the individual's own measurement of reward rate and so when averaged among individuals, this process will generate the ideal free distribution independently of whether food supplies are regular or irregular. Such appears to be the case with three-spined sticklebacks (Milinski 1984). In the original models of ideal free distributions and relative pay-offsums, competitive abilities were assumed to be equal, but in reality they will vary among foragers. Modification of the relative pay-off sum to accommodate competitive inequalities (Regelmann 1984) generates the prediction that better competitors should distribute themselves according to the profitability of food sources, pre-empting poorer competitors, who should switch more frequently between food sources, taking opportunities as they arise. Threespined sticklebacks (Milinski 1984) and cichlids (Godin & Keenleyside 1984) seem to behave in this way. Fifteen-spined sticklebacks, also, distribute themselves in accordance with the ideal free distribution model, independently of whether food supplies are regular or irregular. Contrary to Milinski's (1984) results or those of Godin & Keenleyside (1984), however, the individuals switching most frequently among our fish were the better competitors, not the poorer. It seems likely, therefore, that the relative pay-off sum does not apply to this case. A more plausible mechanism achieving the ideal free distribution would be the adoption of different foraging strategies as a result of competitive interference among individuals (Sutherland & Parker 1985; Krebs & Davies 1987). There was no difference in switching frequency among isolated fish, but when placed in competition, the largest, superior individuals switched more frequently than the inferior ones. Swimming generally is less costly in time and energy for larger
138
Animal Behaviour, 42, 1
fish (Webb 1984), but they require more food than smaller individuals to become satiated. These larger fish could reach food faster than others already nearer the source of food. By switching frequently between food sources, the superior fish would be able to track any changes in profitability and apportion their searching effort accordingly: a useful trait if local depletion is likely to be rapid (Croy 1989). Poorer competitors appeared to adopt a different strategy. After an initial period of relatively intense sampling, they switched infrequently between food sources, perhaps 'making the best of a bad job' by concentrating on prey missed by their competitive superiors and by reducing travel costs. In conclusion, we have shown that, when choosing between sources of food, fifteen-spined sticklebacks behave qualitatively in accordance with the energy maximization, premise, subject to the constraints that risk of starvation and predation are minimized. Competition exerts an additional constraint, but the different strategies employed by competitively superior and inferior fish probably maximize energy gain in either case, a possibility that should be amenable to further experimental investigation. A notable behavioural feature of fifteen-spined sticklebacks is the relatively high frequency of sampling. This suggests that the sticklebacks normally forage among heterogeneously distributed prey. Stomach contents reveal a predominance of gammarid amphipods and mysid prawns (Kislalioglu & Gibson 1976). Gammarids are benthic, relatively clumsy, bulky prey, whereas mysids are pelagic and agile. Sticklebacks feed in a frequency-dependent manner on such prey (Croy 1989), a process involving learned handling skills, associated changes in preference and the modifying effect of hunger level (Croy & Hughes 1990, 1991a, b). Gammarids tend to crawl on the substratum, particularly among weed. They maintain relatively constant densities over a time scale of several foraging bouts and so represent a dependable, moderately profitable food supply. Mysids swim in open spaces in the vicinity of weed, often gregariously. Moving with the tide, their ephemeral swarms present a variable food supply that may yield high rewards. The natural habitat and prey of the fifteen-spined stickleback therefore display characteristics that would be expected to promote the frequent sampling and flexible foraging behaviour observed in the laboratory.
ACKNOWLEDGMENTS M.I.C. was supported by a SERC studentship.
REFERENCES Abrams, M. V. & Dill, L. M. 1989.A determination of the energeticequivalence of the risk of predation. Ecology, 70, 999-1007. Barnard, C. J. 1990. Food requirement and risk-sensitive foraging in shortfall minimizers. In: Behavioural Mechanisms of Food Selection, NA TO ASI Series, G20 (Ed. by R. N. Hughes), pp. 187-213. Berlin: Springer Verlag. Caraco, T. 1981. Energy budgets, risk and foraging preferences in dark-eyed juncos, Junco hyemalis. Behav. Ecol. Sociobiol., 8, 213-217. Caraco, T., Martindale, S. & Whitham, T. S. 1980. An empirical demonstration of risk-sensitive foraging preferences. Anim. Behav., 28, 820-830. Croy, M. I. 1989. Characteristics of learning associated with feeding in marine predators. Ph.D. thesis, University of Wales. Croy, M. I. & Hughes, R. N. 1990. The combined effects of learning and hunger in the feeding behaviour of the fifteen-spinedstickleback (Spinachia spinachia L.). In: Behavioural Mechanisms of Food Selection, NA TO ASI Series, G20 (Ed. by R. N. Hughes), pp. 215534. Berlin: Springer Verlag. Croy, M. I. & Hughes, R. N. 1991a. The role of learning and memory in the feeding behaviour of the fifteenspined stickleback, Spinachia spinachia L. Anita. Behav., 41, 149-159. Croy, M. I. & Hughes, R. N. 1991b. The influence of hunger on feeding behaviour and on the acquisition of learned foraging skills in the fifteen-spinedstickleback, Spinachia spinachia L. AnOn. Behav., 41, 161-170. Dill, L. M. 1983. Adaptive flexibility in the foraging behaviour of fishes. Can. J. Fish. Aquatic. Sci., 40, 398-408. Frazer, D. F. & Huntingford, F. A. 1986. Feeding and avoiding predation hazard: the behavioural response of the prey. Ethology, 73, 56-68. Fretwell, S. D. & Lucas, H. L. 1970. On territorial behaviour and other factors influencinghabitat distribution in birds. I. Theoretical development. Acta biotheor., 19, 16-36. Gilliam, J. F. 1990. Hunting by the hunted: optimal prey selection by foragers under predation hazard. In: Behavioural Mechanisms of Food Selection, NA TO ASI Series, G20 (Ed. by R. N. Hughes), pp. 797-819. Berlin: Springer Verlag. Godin, J.-G. J. & Keenleyside,M. A. H. 1984.Foraging on patchily distributed prey by a cichlid fish (Teleosteidae, Cichlidae): a test of the ideal free distribution theory. Anon. Behav., 32, 120-131. Green, R. F. 1980. Bayesian birds: a simple example of Oaten's stochastic model of optimal foraging. Theor. Pop. Biol., 18, 244-256. Grubb, T. C. & Greenwald, L. 1982. Sparrows and brushpile: foraging responses to different combinations of
Croy & Hughes: Patch choice by sticklebacks predation risk and energy cost. Anim. Behav., 30, 637-640. Harley, C. B. 1981. Learning and the evolutionarily stable strategy. J. theor. Biol., 89, 611-633. Harper, D. G. C. 1982. Competitive foraging in mallards: 'ideal free' ducks. Anita. Behav., 30, 575-584. Houston, A. I, Clark, C. W., McNamara, J. M. & Mangel, M. 1988. Dynamic models in behavioural and evolutionary ecology. Nature, Lond., 332, 29-34. Hughes, R. N. 1980. Optimal foraging in the marine context. Oceanog. mar. Biol. A. Rev., 18, 423-481. Ibrahim, A. A. & Huntingford, F. A. 1989. Laboratory and field studies of the effect of predation risk on foraging in three-spined sticklebacks (Gasterosteus aculeatus). Behaviour, 109, 46-57. Iwasa, Y., Higashi, M. & Yamamura, N. 1981. Prey distribution as a factor determining the choice of optimal foraging strategy. Am. Nat., 117, 710-723. Johnston, T. D. & Turvey, M. T. 1980. An ecological metatheory for theories of learning. In: The Psychology of Learning and Motivation: Advances in Research and Theory, Vol. 14 (Ed. by G. H. Bower), pp. 147-205. New York: Academic Press. Kacelnik, A. & Krebs, J. R. 1985. Learning to exploit patchily distributed foods. In: Behavioural Ecology: Ecological Consequences of Adaptive Behaviour (Ed. by R. M. Sibly & R, H. Smith), pp. 189-205. Oxford: Blackwell Scientific Publications. Kislalioglu, M. & Gibson, R. N. 1976. Some factors governing prey selection by the fifteen-spined stickleback, Spinachia spinachia. J. exp. mar. Biol. Ecol., 25, 159-169. Krebs, J. R. & Davies, N. B. 1987. An Introduction to Behavioural Ecology. 2nd edn. Oxford: Blackwell Scientific Publications. Krebs, J.R., Kacelnik, A. & Taylor, P. 1978. Test of optimal sampling by foraging great tits. Nature, Lond., 275, 27-31. Lima, S., Valone, T. J. & Caraco, T. 1985. Foraging efficiency: predation risk trade-off in the grey squirrel. Anita. Behav., 33, 155-165. McNamara, J. M. 1982. Optimal patch use in a stochastic environment. Theor. Popul. Biol., 21,269-288. McNamara, J. M. 1990. The starvation-predation tradeoff and some behavioural and ecological consequences. In: Behavioural Mechanisms of Food Selection, NA TO ASI Series, G20 (Ed. by R. N. Hughes), pp. 39 59. Berlin: Springer Verlag. McNamara, J. M. & Houston, A. I. 1986. The common currency for behavioural decisions. Am. Nat., 127, 358-378. McNamara, J. M. & Houston, A. I. 1990. Starvation and predation in a patchy environment. In: Living in Patchy
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Environments (Ed. by B. Shorrocks & I. Swingland), pp. 23-43. Oxford: Oxford University Press. Magurran, A. E. & Girling, S. L. 1986. Predator model recognition and response habituation in shoaling minnows. Anim. Behav., 34, 510--518. Milinski, M. 1979. An evolutionary stable feeding strategy in sticklebacks. Z. Tierpsychol., 51, 36-40. Milinski, M. 1984. Competitive resource sharing: an experimental test of a learning rule for ESSs. Anim. Behav., 321,233-242. Milinski, M. 1985. Risk of predation taken by parasitised sticklebacks under competition for food. Behaviour, 93, 203-216. Milinski, M. 1990. Information overload and food selection. In: Behavioural Mechanisms of Food Selection, NATO ASI Series, G20 (Ed. by R. N. Hughes), pp. 721-737. Berlin: Springer Verlag. Milinski, M. & Heller, R. 1978. Influence of a predator on the optimal foraging behaviour of sticklebacks, Gasterosteus aculeatus. Nature, Lond., 275, 64~644. Oaten, A. 1977. Optimal foraging in patches: case for stochasticity. Theor. Pop. Biol., 12, 263-285. Pitcher, T. W. 1980. Some ecological consequences offish school volumes. Freshw. Biol., 10, 539-544. Pitcher, T. J., Lang, S. H. & Turner, J. T. 1988. A riskbalancing trade-off between foraging rewards and predation risk in shoaling fish. Behav. Ecol. Sociobiol., 22, 225 228. Pyke, G. H. 1984. Optimal foraging theory: a critical review. A. Rev. Ecol. Syst., 15, 523-575. Regelmann, K. 1984. Competitive resource sharing: a simulation model. Anim. Behav., 32, 226-232. Sih, A. & Moore, R. D. 1990. Interacting effects of predator and prey behaviour in determining diets. In: Behavioural Mechanisms of Food Selection, NA TO ASI Series, G20 (Ed. by R. N. Hughes), pp. 771-796. Berlin: Springer Verlag. Stephens, D. W. 1982. Stochasticity in foraging theory: risk and information. D.Phil. thesis, University of Oxford. Stephens, D. W. & Krebs, J. R. 1986. Foraging Theory. Princeton, New Jersey: Princeton University Press. Sutherland, W. J. & Parker, G. A. 1985. Distribution of unequal competitors. In: Behavioural Ecology. Ecological Consequences of Adaptive Behaviour (Ed. by R. M. Sibly & R. H. Smith), pp. 255-273. Oxford: Blackwell Scientific Publications. Walkey, M. & Meakins, R. H. 1970. An attempt to balance the energy budget of a host-parasite system. J. Fish. Biol., 2, 361-372. Webb, P. W. 1984. Body form, locomotion and foraging in aquatic vertebrates. Am. Zool., 24, 107-120.
Effects of food supply, hunger, danger and competition on choice of foraging location by the fifteen-spined stickleback, Spinachia spinachia L. M. I. C R O Y & R. N. H U G H E S * School o f Biological Sciences, University College o f North Wales, Bangor, Gwynedd, LL57 2UW, U.K.
(Received 27 June 1990; initial acceptance 15 August 1990; final acceptance 21 December 1990; MS. number." 3601)
Abstract. A group of fifteen-spined sticklebacks were given the choice of two food sources. The fish
sampled both sources, but with decreasing frequency as each trial progressed. Sampling was more frequent when the fish were hungry than when partially satiated. The fish spent more time at the more profitable source, discrimination being marked when profitability was determined by delivery rate, but less pronounced when determined by prey size. Given food sources of equal mean delivery rate, hungry fish concentrated on the variable source and partially satiated fish on the constant source. The fish became more reluctant to feed and to visit a source where there had recently been a simulated threat of predation, but reluctance was less when the dangerous source was also more profitable, especially when the fish were hungry. The fish distributed themselves in proportion to the profitability of the food source (ideal free distribution). Competitive ability varied among the fish according to their size. The two largest, competitively superior fish sampled the food sources more frequently than their inferior competitors. They quickly intercepted food and could efficiently track any short-term changes in delivery rate. Inferior competitors sampled frequently at first, but then settled for one food source, concentrating on prey missed by their competitive superiors and reducing travel costs. Fifteen-spined sticklebacks, therefore, behave in accordance with the 'energy maximization premise', subject to the constraints that risks of starvation and predation are minimized and that adjustments must be made towards competitors. Sampling is a conspicuous feature of the foraging behaviour and is appropriate to the temporally and spatially heterogeneous, natural food supply of these fish. During the prolonged popularity of optimal foraging theory, experiments abundantly vindicated the idea that foragers tend to maximize their net rate of energy gain (Hughes 1980; Pyke 1984; Stephens & Krebs 1986). Inevitably, subsequent theoretical refinement has relaxed simplifying assumptions, particularly in three areas. These are (1) information acquisition by sampling (Oaten 1977; Green 1980; Johnston & Turvey 1980; Iwasa et al. 1981; McNamara 1982), (2) energy status of the forager and the perception of risk, either as a precarious food supply (Caraco et al. 1980; Stephens 1982) or as danger from predators (Gilliam 1990; McNamara 1990) and (3) competition among foragers (Sutherland & Parker 1985). Although often considered in isolation (but see Milinski 1990), all the above factors are likely to influence the behaviour of any forager that has a labile energy budget, exploits variable food supplies, ranges widely in its habitat and is not entirely soli*To whom all correspondence should be addressed. 0003 3472/91/070131+09 $03.00/0
tary. For this reason, we decided to examine their effects on the foraging behaviour of the fifteenspined stickleback. This animal shows energy maximizing behaviour when selecting its diet, is sensitive to short-term changes in hunger and rapidly learns the characteristics of prey and of their locality (Croy & Hughes 1991a, b). If sampling is important, foragers should visit food sources alternately, before deciding to exploit the most profitable source exclusively. In the case of great tits, Parus major, the frequency of sampling is correlated with the similarity in profitability of the food sources (Krebs et al. 1978). If energy status is important, starving foragers should exploit variable food sources offering the chance of a large reward, sufficient to restore a positive energy balance, whereas those already in a positive energy balance should concentrate on more predictable supplies of food. This is characteristic of small birds and mammals with precarious energy budgets (Barnard 1990), but could also be true of active poikilotherms with a limited energy storage capacity. All
9 1991 The Association for the Study of Animal Behaviour 131
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vulnerable foragers should be sensitive to the risk of predation, but sensitivity may be reduced if there is an urgent requirement for food. Thus when hungry, three-spined sticklebacks, Gasterosteus aculeatus, will approach closer to perceived danger in order to obtain larger rewards (Milinski & Heller 1978). Competition among foragers may interact with productivity of the food sources, through the differential distribution of individuals. If foragers are of similar competitive ability, their numbers should become distributed directly in proportion to the profitability of alternative food sources, according to the ideal free distribution (Fretwell & Lucas 1970). Superficial agreement with this prediction has been found among three-spined sticklebacks (Milinski 1979, 1984), mallard, Anasplatyrhynchos (Harper 1982) and cichlids, Aequidens curviceps (Godin & Keenleyside 1984). Details of behaviour, however, revealed a more complex situation in these cases, involving unequal competitive abilities and correlated differences in foraging behaviour. There is, therefore, a need for more information on mechanisms that result in superficial conformity with the ideal free distribution (Sutherland & Parker 1985; McNamara & Houston 1990). METHODS
General Methods We maintained sticklebacks of 125-150mm total length, on the flesh of mussels, Mytilus edulis, for 2 months prior to the experiments. For use as live prey, we cultured Artemia sp. on a daily ration of Rhodomonas balthica. We set up an experimental aquarium, measuring 1500 x 700 x 700 mm, containing seawater at 11 + 1~ and illuminated overhead by 60-W fluorescent tubes on a 12:12 h light: dark photoperiod. We screened three sides of the aquarium with black polythene sheeting and left the fourth clear for observation. Two foraging areas were delimited by a central, Perspex partition, flanked on either side by a band of weed made from strands of polythene. The weed was sufficiently dense to occlude vision from one foraging area to the other and provided a refuge for uneaten prey. A 150-mm gap between the central partition and rear wall allowed the fish to move freely between foraging areas. Each foraging area was furnished with an aerator, recirculation filter and gravel substratum. To deliver prey at known rates into each foraging area, we made twin-carousels, controlled by a
microcomputer (Croy 1989). We positioned the carousels in front of the aquarium, so that they delivered food into each foraging area at a point marked by a clump of weed. We video-recorded the behaviour of the fish and transcribed the data using a microcomputerized event recorder. Before each set of experiments, unless otherwise stated, we ensured that the fish were already familiar with the prey and the apparatus. On 8 consecutive days, we placed fish individually in the experimental aquarium, allowed them to settle for 30-45 min and, using both carousels, fed them with one Artemia every 20 s over a 20-min period, commencing at a standard time of day for each fish. By the end of a daily feeding period, the fish showed signs of satiation.
Sampling Behaviour We subjected nine individual fish to daily feeding trials each 20 min long as described above, but with two additional regimes of food delivery. First, the carousels delivered one Artemia per 20 s in one foraging area and two per 20 s in the other. Delivery rates were assigned randomly between the two areas on three consecutive daily trials. To nullify any bias that may have been developed by the experimental fish, delivery rates were equalized at one Artemia per 20 s for three more daily trials. Second, we repeated the procedure using equal delivery rates, but with Artemia of optimal mass (Croy & Hughes 1990) in one area and half the optimal mass in the other, assigned randomly between areas on three successive daily trials. We recorded the proportion of time a fish spent foraging in each area, together with the frequency of switching between areas during 1-min intervals throughout each trial. Risk-sensitive Foraging We wished to test the idea that hungry fish should be risk prone, choosing the variable food supply, and partially satiated fish risk averse, preferring the constant supply. First, we gave nine replicate fish the opportunity to assess and learn the characteristics of the two food sources, one delivering one Artemia every 20 s, the other with the same mean delivery rate, but dispensing no or two Artemia in random order at 20-s intervals. Eight daily trials, each of 10 min and commencing at a standard time of day for each fish, were judged sufficient for the fish to learn the differences between foraging areas (Croy & Hughes 1990). We then deprived the fish of
Croy & Hughes: Patch choice by sticklebacks Table I. Statistical characteristics of the variable food source used to investigaterisk-sensitiveforaging Variation of reward
Mean reward
Variance of reward
Variance/ Mean
2or0 3orl 4or0
1 2 2
2 2 8
2 1 4
Reward = number of prey items per delivery. food for 24 h and repeated the feeding protocol on 3 consecutive days, noting the initial choice of foraging area, the time spent in each area and the frequency of switching between areas during 1-min intervals throughout the trials. Finally, we repeated the entire procedure I h after having satiated the fish with mysid flesh. To investigate the effect of variance in food supply (Caraco 1981), we ran two further sets of experiments, using the same general protocol, but delivering two Artemia every 20 s in the constantdelivery area and one or three in random sequence, then none or four in the variable-delivery area (Table I). Danger of Predation We wished to investigate the influence of perceived danger and its interaction with hunger and delivery rate on the choice of foraging area. We subjected 18 fish to the preliminary feeding protocol (General Methods). We then kept a control group of six of the 18 fish unfed for 24h and subjected them to a 20-min trial in which one optimally sized Artemia per 20 s was dispensed in each foraging area. We ran a second trial 6 h later, when the fish would have become hungry again (Croy & Hughes 1991b). We repeated the entire procedure on each of 3 consecutive days, recording the numbers offish feeding in each area throughout the trials. Using the same feeding regime with a second group of six fish, we simulated danger at mid-trial by dropping a realistic model kingfisher into one of the foraging areas (Pitcher et al. 1988). Remote control ensured that the fish could not anticipate the arrival of the model, which was removed immediately after plunging. We separated replicate trials by 3-day intervals, to avoid the fish habituating to the model (Magurran & Girling 1986). We repeated the experiment with the model predator, using a third group of six fish I h after
133
they had been satiated with mysid flesh. Finally, we repeated the entire set of experiments with the same fish but with a delivery rate of two Artemia per 20 s in the 'dangerous' area and one Artemia per 20 s in the 'safe' area.
Competition First, we established the differences in competitive ability among six fish, the maximum number identifiable without tagging. Using the preliminary feeding protocol (General Methods), we allowed the six fish to become familiar with the apparatus and food source. Between trials, we satiated the fish with mysid flesh, in order to standardize their hunger levels. The fish were then collectively subjected to six, daily, 20-min trials in the same foraging area; we finally repeated the entire procedure in the other foraging area. We recorded the number of successful attacks on prey made by each fish throughout the trials. Having established their competitive hierarchy, we observed the foraging behaviour of the six competitors presented with a choice of foraging location. Before the experiments we allowed the fish to become accustomed to the two food sources and to reach comparable hunger levels during 8 days of standard feeding protocol, as described above. We then subjected the competitors to three, daily, 20-min trials in which one optimally sized Artemia per 20 s was delivered to each foraging area. We recorded the number of successful attacks and number of switches between areas made by each fish. To investigate the criteria used by the fish to decide where to forage, we repeated the experiment three times using the same fish, with the following modifications. First, the Artemia were dispensed at the same mean rate as before, but at irregular intervals. Second, the Artemia were dispensed at twice the normal rate in one area, assigned randomly. Equal rates were then restored for 3 days to nullify any preference of foraging area resulting from the experiment. Third, Artemia of half the optimal size were dispensed at the normal rate in one area and optimally sized prey in the other, assigned randomly. RESULTS
Sampling The mean proportions of time spent foraging in alternative areas with equal delivery rates and prey
Animal Behaviour, 42, 1
134 (a) 0'8 ==
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Figure 1. Response to profitability: proportion of total time that individual fish spent feeding at alternative food sources, A and B. Data are medians with quartiles. (a) Delivery rates equal; (b) delivery rate etA twice that of B; (c) delivery rates equal, but prey size in A twice that in B. size were not significantly different (Fig. 1, M a n n Whitney U-test, Z = 1, N = 5 4 , P > 0 . 1 ) . The fish switched between foraging areas at an average rate of once every 20 s in the first half of a trial and once every 56 s in the second (Wilcoxon matched-pairs signed-ranks test, Z = 2 . 4 5 , N = 2 7 , P<0-05). A similar temporal decline in sampling rate also occurred in other trials, below (Wilcoxon matchedpairs signed-ranks test, Z = 2.60, N = 27, P < 0"01 in both trials). When presented with food sources of unequal profitability, the fish spent significantly more time in the more profitable area (Fig. 1, U-test, Z = 6 . 2 1 , N = 5 4 , P<0.001). Switching frequency was not significantly different between trials with equal and unequal food sources (;(2= 2.46, df= 1, P > 0-1). Although the fish spent significantly more time foraging in the area with optimally sized prey (Fig. 1, U-test, Z = 2.14, N = 54, P < 0-05), their discrimination between areas was less pronounced than in the previous experiment with unequal delivery rates and similar prey size. The fish switched between foraging areas offering differently sized prey more frequently than in trials with equal delivery rate and prey size (Z 2 = 6.26, df= 1, P < 0.05). N o significant difference in switching frequency was found between individuals (Z2= 15-38, dr=8, P > 0 ' 0 5 ) . This contrasts with the marked differences in switching frequency observed within groups of fish in the Competition experiments (see below).
Risk-sensitive Foraging Hungry fish first attacked prey significantly more often at the variable food source (Fig. 2, hierarchi-
Type of food source
Figure 2. Risk-sensitive foraging: numbers of fish attacking their first prey item in either the constant (D) or the variable (111) food source. Description of reward: (a) constant = 1, variable = 2 or 0; (b) constant = 2, variable = 3 or 1; (c) constant=2, variable=4 or 0. First pair of columns: hungry fish, second pair: partially satiated fish. cat log-linear analysis, G = 41-54, df= 2, P < 0"001), but their response was not significantly influenced by the variance to mean ratio (G=0.34, df=2, P > 0 . 5 ) . In contrast, partially satiated fish first attacked prey significantly more often at the constant food source (Fig. 2, G=20.03, df=l, P<0.001). Differences in the variance to mean ratio had no significant effect on the tendency to favour the constant food source (Table I; G = 2"90, df=2, P > 0.2). Hungry fish spent significantly more time feeding at the variable than at the constant food source (Friedman A N O V A , ;(2= 10.89, df= 1, P<0-001). They switched between foraging areas more frequently than partially satiated fish (;(2 = 7.12, df= 1, P<0.01). There was no significant variation among the fish in the proportion of time spent feeding during trials (;(2=5.18, df=8, P > 0 . 1 ) or in the frequency of switching between food sources (;(2 =9.07, df= 8, P>0.1).
Danger of Predation When delivery rates were equal (Fig. 3a), fish in the control group distributed themselves evenly between the two foraging areas (data pooled for both hunger levels, ;(2=3.16, df=l, P>0"05). Once the model predator had been presented, the number of fish feeding in the dangerous area was depressed throughout the remaining 10rnin of the trial (ANOVA, F = 1 2 4 . 1 , df=2, P<0.001). Avoidance of the dangerous area was less pronounced among hungry fish (ANOVA, F = 4 9 . 6 ,
Croy & Hughes." Patch choiceby sticklebacks
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Figure 4. Competitive hierarchy: number of attacks per
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Figure 3. Risk of predation: numbers of fish foraging at alternative food sources, A and B. Data are means with 95% confidence limits. [23: partially satiated fish; I1: hungry fish. (a) Delivery rates equal; (b) delivery rate of B twice that of A.
df=2, P<0.001). Approximately equal distributions of fish between foraging areas were resumed in all trials occurring 6 h after the threat. When delivery rates were unequal (Fig. 3b), fish in the control group distributed themselves in proportion to the food supply (Z2=44.0, df=l, P<0-001). Fewer fish fed in the dangerous area after the threat (ANOVA, F=246.5, df=2, P<0.001), but this response was less pronounced than in the previous experiment, when delivery rates were equal in the dangerous and safe areas. Hungry fish were more reluctant to avoid the dangerous area than partially satiated fish (ANOVA, F = 13.38, df=2, P<0.001). Six hours after the threat, in all trials, the fish resumed a distribution in proportion to the food supply (Fig. 3a, b).
Competition The number of successful attacks per trial was correlated with length of the fish (Spearman rank correlation, rs=0.68, df=71, P<0.001). Mean
attack rate ranged from 1 per trial for the smallest fish, 125 mm in length, to 20 per trial for the largest, 150 mm in length. The fish, therefore, could be ranked in competitive ability according to their size (Fig. 4). The frequency of switching between foraging areas varied considerably among the fish (;(2= 28.87, df=5, P<0-001). The two largest fish switched the most and there was a significant correlation among the fish between switching frequency and attack frequency (r s = 0.54, df= 71, P < 0"001). As in the Sampling experiments (see above) switching frequency declined within trials and was always significantly less in the second half of a trial than in the first (Wilcoxon matched-pairs test, Z = 2.91, N = 54, P < 0.001). There was no significant difference in switching frequency between trials with equal arid unequal delivery rates (Fig. 5a, b, Z2=0-21, dr= l, P > 0"6), but when delivery rates were equal, fish switched significantly more often in trials with unequal sizes of prey than in those with optimally sized prey only (Fig. 5a, c, Z2 = 6.4, dr= l, P < 0"01). There was no significant difference in the distribution offish between alternative areas, either with constant or irregular food supplies (Friedman ANOVA, Z2=2.44, d r = l , P>0.05) and so the data were pooled for the following analyses. There was no significant departure from an even distribution of fish between food sources with equal delivery rates (Z2=3.27, d r = l , P>0"05). With unequal delivery rates, the fish distributed themselves proportionately (Z2 = 60'0, df= l, P < 0.001). When delivery rates were equal, but prey size differed, the fish distributed themselves evenly (;(2= 0.03, dr= l, P > 0.9). We concluded, therefore, that the fish were responding to reward frequency rather than rate of energy gain per se.
Animal Behaviour, 42, 1
136 5 84
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.
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Figure 5. Sampling behaviour: frequency of switching between alternative food sources, plotted as a function of time during the trial. Data are medians with quartiles. (a) Food sources with equal delivery rates; (b) one food source with twice the delivery rate of the other; (c) food sources with equal delivery rates, but with prey items of twice the mass in one than the other9 DISCUSSION Sampling is an important component of the foraging behaviour of fifteen-spined sticklebacks. In our experiments, the fish frequently switched between food sources at the beginning of a trial, the rate declining to a low level within 20 min. Hunger would have declined in parallel, but since similar trends were shown by initially hungry and partially satiated fish, the reduction in switching frequency probably corresponded to an increasing awareness of the relative quality of the food sources, resulting in a decision by the fish to concentrate on the source with the higher delivery rate. This resembles the sampling behaviour first described for great tits
(Krebs et al. 1978). Our sticklebacks also discriminated between food sources on the basis of prey size, but evidently this required more prolonged sampling than discrimination between delivery rates. Delayed discrimination based on the size of food items has also been recorded for mallard (Harper 1982). In that study, food sources had equal delivery rates, but pieces of bread were twice as large at one source. The birds initially distributed themselves evenly, as if responding to reward frequency, but later redistributed in the ratio 2:1, suggesting a response to the size of the food and hence to the rate of energy intake. Fifteen-spined sticklebacks are sensitive to probabilistic variation of food supply and modify their foraging behaviour in accordance with their energy status. Partially satiated fish, with a positive energy budget, initially preferred variable food supplies, whereas those deprived of food for 24 h and therefore with a smaller positive energy balance (Walkey & Meakins 1970), preferred variable supplies. Hungry fish, however, switched less frequently between food sources as each trial progressed and this may have resulted from decreasing hunger levels, tending to make the fish shift from a risk-prone to a risk-averse state (Barnard 1990). The variance of mean ratio in reward rate seemed to have little influence on the sticklebacks, in contrast to dark-eyed juncos, Junco hyemalis, which show hunger-dependent sensitivity to this parameter (Caraco 1981). This marked response of fifteen-spined sticklebacks to supply variance is surprising, in view of the small risk of fatal starvation. Poikilothermic metabolism and substantial bodily energy reserves should enable adults to survive many days without food. Risk-sensitive foraging is to be expected where animals quickly exhaust their energy reserves and where there is a cyclical energy debit caused by circadian restrictions in foraging opportunity. Without such periodic starvation, foragers are expected always to be risk averse (e.g. McNamara 1990; McNamara & Houston 1990). Foraging activity in fifteen-spined sticklebacks may have a tidal rhythmicity, especially among those fish confined to shallow pools at low tide. Availability of prey may also fluctuate tidally. Yet it seems unlikely that critically long periods of food deprivation will occur regularly. How precarious must the daily energy budget be in order to justify risksensitivity? Starvation, if not potentially fatal within the cycle, must at least jeopardize the forager's
Croy & Hughes." Patch choice by sticklebacks chances of recuperation. If irredeemable energy loss is not a significant possibility, then some other explanation must be sought for the apparently risksensitive foraging behaviour of fifteen-spined sticklebacks. More information is needed. Many animals are known to adjust their foraging behaviour in response to the threat of predation. Examples include three-spined sticklebacks (Ibrahim & Huntingford 1989), sparrows, Passer domesticus (Grub & Greenwald 1982), squirrels, Sciurus carolinensis (Lima et al. 1985) and minnows, Phoxinus phoxinus (Pitcher et al. 1988). In general, animals are more reluctant to forage in places where they perceive a risk of being attacked; but when danger and food supply coincide, foragers may partially overcome their reluctance in proportion to hunger or potential reward. ' Risk- balancing' (Frazer & Huntingford 1986), in which the forager approaches closer to a source of danger to achieve greater reward, may be an optimal response when foraging is normally associated with the risk of predation (Pitcher 1980). This has been demonstrated experimentally for juvenile Coho salmon Onchorhynchus kisutch (Dill 1983), three-spined sticklebacks (Milinski 1985) and minnows (Pitcher et al. 1988). Fifteen-spined sticklebacks are probably constantly at risk to predation by larger fish and birds, especially by terns, gulls and cormorants, all of which are regularly seen hunting in the tide pools where we obtained our fish. Although our experiments did not quantify how much risk sticklebacks would tolerate for a given reward rate (cf. Abrams & Dill 1989), they clearly showed that the likelihood of persisting after threat increased with reward rate. Foragers are also liable to become more reckless when hungry. After food deprivation, three-spirted sticklebacks prefer to forage where there isa high density of prey, but when partially satiated they choose less productive areas, where time can be more effectively partitioned between foraging and vigilance (Milinski & Heller 1978). Our fifteenspined sticklebacks were more likely to remain foraging after a threat when they were hungry. Reluctance to forage in the vicinity of danger, therefore, is partially overcome by increasing hunger or reward potential, emphasizing the importance of energy state as a regulator of foraging behaviour (McNamara & Houston 1986; Houston et al. 1988; Sih & Moore 1990). Competition is yet another factor influencing the behaviour of foragers. If competition is of the
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'scramble' rather than the 'contest' or 'despotic' type, then the ideal free distribution model (Fretwell & Lucas 1970) successfully predicts the observed trend for local densities of foragers to match food supplies (Milinski 1979, 1984; Godin & Keenleyside 1984; Pitcher et al. 1988). Behavioural mechanisms responsible for this matching are, however, poorly understood (Sutherland & Parker 1985). One possibility is that foragers constantly update their evaluation of food sources by comparing current feeding rates with memorized success (Kacelnik & Krebs 1985). An example of this type of mechanism is the relative pay-off sum (Harley 1981). A decision to exploit a food source depends on the individual's own measurement of reward rate and so when averaged among individuals, this process will generate the ideal free distribution independently of whether food supplies are regular or irregular. Such appears to be the case with three-spined sticklebacks (Milinski 1984). In the original models of ideal free distributions and relative pay-offsums, competitive abilities were assumed to be equal, but in reality they will vary among foragers. Modification of the relative pay-off sum to accommodate competitive inequalities (Regelmann 1984) generates the prediction that better competitors should distribute themselves according to the profitability of food sources, pre-empting poorer competitors, who should switch more frequently between food sources, taking opportunities as they arise. Threespined sticklebacks (Milinski 1984) and cichlids (Godin & Keenleyside 1984) seem to behave in this way. Fifteen-spined sticklebacks, also, distribute themselves in accordance with the ideal free distribution model, independently of whether food supplies are regular or irregular. Contrary to Milinski's (1984) results or those of Godin & Keenleyside (1984), however, the individuals switching most frequently among our fish were the better competitors, not the poorer. It seems likely, therefore, that the relative pay-off sum does not apply to this case. A more plausible mechanism achieving the ideal free distribution would be the adoption of different foraging strategies as a result of competitive interference among individuals (Sutherland & Parker 1985; Krebs & Davies 1987). There was no difference in switching frequency among isolated fish, but when placed in competition, the largest, superior individuals switched more frequently than the inferior ones. Swimming generally is less costly in time and energy for larger
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fish (Webb 1984), but they require more food than smaller individuals to become satiated. These larger fish could reach food faster than others already nearer the source of food. By switching frequently between food sources, the superior fish would be able to track any changes in profitability and apportion their searching effort accordingly: a useful trait if local depletion is likely to be rapid (Croy 1989). Poorer competitors appeared to adopt a different strategy. After an initial period of relatively intense sampling, they switched infrequently between food sources, perhaps 'making the best of a bad job' by concentrating on prey missed by their competitive superiors and by reducing travel costs. In conclusion, we have shown that, when choosing between sources of food, fifteen-spined sticklebacks behave qualitatively in accordance with the energy maximization, premise, subject to the constraints that risk of starvation and predation are minimized. Competition exerts an additional constraint, but the different strategies employed by competitively superior and inferior fish probably maximize energy gain in either case, a possibility that should be amenable to further experimental investigation. A notable behavioural feature of fifteen-spined sticklebacks is the relatively high frequency of sampling. This suggests that the sticklebacks normally forage among heterogeneously distributed prey. Stomach contents reveal a predominance of gammarid amphipods and mysid prawns (Kislalioglu & Gibson 1976). Gammarids are benthic, relatively clumsy, bulky prey, whereas mysids are pelagic and agile. Sticklebacks feed in a frequency-dependent manner on such prey (Croy 1989), a process involving learned handling skills, associated changes in preference and the modifying effect of hunger level (Croy & Hughes 1990, 1991a, b). Gammarids tend to crawl on the substratum, particularly among weed. They maintain relatively constant densities over a time scale of several foraging bouts and so represent a dependable, moderately profitable food supply. Mysids swim in open spaces in the vicinity of weed, often gregariously. Moving with the tide, their ephemeral swarms present a variable food supply that may yield high rewards. The natural habitat and prey of the fifteen-spined stickleback therefore display characteristics that would be expected to promote the frequent sampling and flexible foraging behaviour observed in the laboratory.
ACKNOWLEDGMENTS M.I.C. was supported by a SERC studentship.
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