- Email: [email protected]
Learning and remembering of spatial patterns by hummingbirds
pnim.
Behav.,
1995, 50, 1273-1286
Learning and remembering of spatial patterns by hummingbirds GLENN
D. SUTHERLAND & CLIFTON of Zoology, University of British
Department
(Received 20 January 1994; jinal acceptance 6 March
LEE GASS Columbia
initial acceptance 30 April 1994; 1995; MS. number: A7118R)
Abstract. Hummingbirds’ responsesto the spatial distribution of their food were examined using arrays of visually identical feeders in the laboratory. Rufous hummingbirds, Selasphorus rufus, learned to visit Profitable feeders in square arrays of 64 feeders on a wall in which only half contained food and the only source of information about feeder quality was location. Birds learned quickly and well if profitability was simply patterned. They learned more slowly but eventually reached high performance on complex patterns, especially if feeders were regularly distributed. Memory of pattern accounted for much more of performance on all patterns than either simple movement rules or memory of individual locations. When food distributions were switched to their mirror images after birds had reached asymptotic performance, all birds that had performed well before the switch continued for several trials to visit the feedersthey had visited before the switch, lagging in redistributing effort to match the new pattern. It is suggestedthat in the absence of visible correlates of feeder quality, hummingbirds use coarse-grained memories of the spatial patterning of energetic profitability to guide their foraging. These memories develop with repeated experience of environments, develop more quickly in simply patterned environments and persist despite changes in food distribution. Poorer performance in complex arrays is inconsistent with a fine-grained model in which birds remember point sources of food independently. Persistenceof foraging patterns at the c%st of significantly reduced gross food intake and severely reduced net intake after pattern switches demonstrates that hummingbirds rely greatly on memory of profitability in guiding foraging; however, their quick recovery to previous performance shows that they quickly modify their memory of places on the basis of new information. These results are compared with some recent field studies of hummingbird foraging in which use of memory could not be reliably demonstrated, or was only one of several mechanisms underlying foraging patterns. 0 1995 The Association
Animals’ food varies in quality, quantity and availability at several spatial scales including whole geographical regions, habitats within them and the home ranges of individuals (Gass & Montgomerie 1981; Menzel & Wyers 1981; Gass & Roberts 1992; Holling 1992). Individuals could take advantage of this variation if they could learn and remember its spatial distribution, and Wolf & Hainsworth (1983) suggested that repeated exposure to information about profitability is a potential advantage of territoriality. The distribution and abundance of nectar available to territorial hummingbirds, for example, is influenced Correspondence:G. D. Sutherland,Centre for Applied Conservation Biology, Faculty of Forestry, University of British Columbia, Vancouver, B.C. V6T 124, Canada (email: [email protected]). C. L. Gass is at the Department of Zoology, University of British Columbia, Vancouver, B.C. V6T 124, Canada. 000333472/95/l
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for the Study of Animal
Behaviour
by the dispersion and nectar production rates of flowers, the spatial and temporal history of foraging by the hummingbirds and their avian and insect competitors (Zimmerman 1981; Wolf & Hainsworth 1983; Armstrong et al. 1987) and other factors. Recent laboratory and field studies of strategies underlying patterns of exploitation of patches by hummingbirds (Gass & Sutherland 1985; Valone 1992) and granivores (Valone 1991) show that ability to remember patch information is an important component of foraging successin territorial species. Several food-hoarding species can remember for hours, days or months the locations of many food items that they have hidden (see reviews in Shettleworth 1985; Sherry 1987). Spatial memory has also been studied in non-hoarding species including pigeons, Columba livia (Wilkie & Summers 1983; Spetch & Honig 1988) doves
$3 1995 The Association
1273
for the Study
of Animal
Behaviour
1274
Animal
Behaviour,
(Wilkie et al. 1981), rats, Rattus norvegicus (Olton & Samuelson 1976; Roberts 1979, 1982), gerbils, Meriones unguiculatus (Collett et al. 1986), chimpanzees, Pan troglodytes (Menzel 1973, 1978), marmosets, Saguinus fuscicollis (Menzel & Juno 1982) and humans (Aadland et al. 1985). Spatial relationships between features or resources are basic components of the environments of animals (Balda & Kamil 1989) and the ability to remember spatial locations is likely to be of general importance for foraging (Sherry 1987). Current laboratory paradigms that model key features of field situations are examining what factors influence spatial memory capacity and retention times at the spatial scale of point locations (Krebs et al. 1990; Jacobs & Liman 1991; Balda & Kamil 1992; Jacobs 1992). Several studies have suggested that hummingbirds and other nectarivores use spatial memory in foraging. Euglossine bees repeatedly return to the locations of particular plants along their foraging routes, even after the plants are removed (Janzen 1971). Honey bees, Apis mellifra, may navigate as if they use ‘landmark maps’ (Gould 1986a, 1987), but their representations do not include geometrical map-like relationships among places (Dyer 1991). Sunbirds and honeycreepers may use spatial memory to avoid revisiting inflorescencesthey have depleted (Gill & Wolf 1977; Kamil 1978). Hummingbirds rapidly learn individual locations in small arrays of feeders, with or without cues such as colour (Gass 1978; Cole et al. 1982), but this ability is influenced more by spatial position than by colour cues (Miller et al. 1985; Brown & Gass 1993). In the field, hummingbirds learn, preferentially use and remember at least overnight the most profitable patches of flowers in their territories, even if these are small and distributed among many others in a heterogeneous habitat (Gass 8t Sutherland 1985; Gill 1988). Attempts to identify, without using experimental manipulations, how hununingbirds use spatial memory in the field have produced ambiguous results, however (Wolf & Hainsworth 1991). These studies suggest that hummingbirds can learn spatial distributions at several spatial scales, but raise questions about their reliance on detailed spatial information in fine-grained situations with many patches (Wolf & Hainsworth 1991). To what extent and how quickly do hummingbirds learn spatial patterns? What determines how quickly and how well they learn them? How long
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do they remember patterns, and how quickly do they learn new ones when conditions change? To explore these questions, we designed a series of laboratory studies that provided geometrically different patterns of nectar availability in arrays of 64 visually identical feeders in which the only source of information about feeder quality was location. Hummingbirds had to learn and prefer. entially visit profitable feeders to maintain neutral or positive energy balance over a series of trials. PILOT STUDY: THE LIMITS PATTERN COMPLEXITY
OF
In this pilot we presented a sequence of increas. ingly complex patterns of nectar availability to individuals on consecutive days to discover the limits of their ability to learn them. Arrays were the same size (64 feeders) and contained the same proportion of profitable feeders (half), but had differently patterned nectar availabilities. Although this non-randomized design precludes statistical analysis of responses to degree of complexity, deteriorating performance on successive days would suggest that pattern complexity is involved. We asked two questions. Can humming. birds learn complex patterns? If so, what patterns would be appropriate for our later experiments into the dynamics of learning and relearning patterns? Methods We used four naive, wild-caught adult female rufous hummingbirds, Selasphorus rufus, maintained communally in a large aviary for 6 months before testing (13.5: 10.5 h 1ight:dark photoperiod). The maintenance food was 22% sucrose solution (mass/mass) with added protein (95% soya protein), minerals (Avimin), vitamins (Avitron), fatty acids (Linatone) and wheat germ oil on weekdays, and 35% (mass/mass)sucrose on weekends. Unlimited Drosophila were available at all times in the aviary, but not in experimental chambers. We performed all training and experiments in an experimental chamber (8.1 x 3.5 x 2.5 m) with a perch in the centre and a green painted wooden panel (1.07 x 1.24 m) mounted on one wall with a regular orthogonal array of 64 feeders on 11-cm centres horizontally and vertitally. The feeders were purple plastic syringe
Sutherland
& Gas: Hummingbird
(a)
(b)
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do.00000 00.000.. ao00.000 d,oooooo 00.000.. 00.000..
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El&ure 1. The four patterns of feeder quality: (a) Halves, (b) Quarters, (c) Checkerboard, (d) Random. 0: Good feeder locations (i.e. feeders containing food at the start of trials): 0: bad feeder locations. Not drawn to scale.
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spatial patterns (Fig. 1). Patterns remained constant within days but increased in complexity each day, as follows: day 1, Halves; day 2, Quarters; day 3, Checkerboard; day 4, Random (a different randomly generated pattern than that used for training). At the beginning of each trial, the 32 good feederscontained 2 ~1of 25% sucrosesolution, and the 32 bad feeders contained 2 )11of water. This volume is typical of hummingbird flowers (Gass & Roberts 1992). Because hummingbirds usually empty flowers in the field (Gass & Montgomerie 1981; Carpenter 1987) and only one of 40 feeders visited in a preliminary test contained any measurable residual sucrosesolution, we assumed that all revisits during trials were unprofitable. We kept birds in the experimental chamber without food for 15-20 min before trial I each day. We observed trials from outside the chamber through a one-way mirror, recorded visits on a tape-recorder and then transcribed them into a computer. Data analysis
needle cups plugged with epoxy, mounted on removable corks. Between trials, we removed visited feeders from the panel (without entering the chamber), refilled them with a Hamilton repeating dispenser, and replaced them. Experimental
procedures
In the field, rufous hummingbirds typically alternate between brief (< 1 min) foraging bouts in which they visit a sequence of flowers, and S-lomin periods of perching (Gass Kc Sutherland 1985). Our experiments modelled this behaviour pattern. The array was exposed for 1 min every 10min by raising a window blind covering it. Birds could stop feeding and return to the perch at any time before we lowered the blind. On each of the 3 days before testing, each bird had 20 trials of training, as follows. On training day 1, all 64 feeders contained 2 ~1of 25% sucrose solution at the beginning of each trial. On training days 2 and 3, only 32 feeders contained food, distributed in a different randomly generated pattern each day. Between training sessionsthe birds lived in the aviary under normal maintenance conditions. Beginning at 0830 hours on each of 4 consecutive days, each bird had 40 trials in one of four
We were interested in studying hummingbirds’ responses to individual locations, so we termed any visit to a good feeder location as correct, whether it was a profitable first visit on a trial, or an unprofitable revisit later during the same trial. We expressedthis as an overall % correct measure of performance for each trial. This measure has four components: total first visits made to good feeders and to bad feeders during trials, and revisits to both types of feeder. Improvements in performance could result from increasing either measure of visits to good feeders or by decreasing either measure of visits to bad feeders. We eliminated trials with less than eight visits from further analysis to avoid analytical biases introduced by short sequences (15 of 640 trials). We used the non-parametric Walsh test (Siegel 1956) for our matched-pairs tests because the assumptions of parametric tests could not reliably be met. For a sample size of four (as in the pilot), probabilities cannot be determined below P=O.O62. Where pooled means for sample sizes greater than two are given, standard deviations are also reported. Results and Discussion Performance on all patterns started near 50% correct (chance), then improved (Fig. 2). On
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Trial Figure 2. Overall performanceon each pattern in the
pilot study: Halves (top) and Checkerboard(bottom); Quarters (top) and Random (bottom). Points are averagesfor four birds over four trials; vertical bars represent95% confidenceintervals. The broken horizontal line indicates chance performance. The figure summarizes38 399 visitsto feedersin 625 trials. Halves, performance for all four birds averaged 87.8% ( f 9.01) by trial 10. All four birds exceeded 90% at least once within 10 trials, three achieved 100% at least once in the first 20 trials, and none achieved lessthan 80% in any of the last 10 trials. On Quarters, all birds performed above 70% by trial 10, and average performance reached 76.6% ( f 9-50) in the last five trials. Only two birds achieved 100% on any trial on Quarters, but no individual achieved less than 65% after trial 20. On Checkerboard and Random, improvement in performance was small (Fig. 2; Checkerboard: mean f SD performance for trials l-5=52.4 f 4.02%; trials 36-40 = 6 1.2 f 4.02%; Random: mean performance for trials l-5=54*2 f 5.87%; trials 36-40=61.7 f 5.48%; one-tailed Walsh test: N=4, P=O.O62 for both comparisons). Despite the difference in complexity between the Checkerboard and Random patterns, performance on them was nearly identical and showed no sign of reaching an asymptote as on Halves or Quarters (Fig. 2). Qn either Checkerboard or Random, no bird exceeded 74% on any trial, and none achieved less than 50% after trial 26. On the Halves and Quarters patterns, our birds improved their performance principally by increasing first visits to good feeders during trials (Table I). All birds also improved performance by decreasing their first visits to bad feeders (Table I). However, trends in the proportions of good and bad feeders that were revisited were less clear for these patterns. On Halves, some birds increased their revisits to good feeders, but no trend was
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apparent on Quarters (Table I). All birds decreased their revisits to bad feeders on the Halves pattern, but only some did on Quarters (Table I). Trends in all four components of performance were more equivocal on both Checkerboard and Random than on Halves and Quarters. On average, the number of first visits to good feeders was higher at the end of the pilot for both Checker. board and Random (Table I). Even in this cornponent, not all birds were consistent in their response. For the other components, there was little difference between early and late trials, and no consistent trends emerged on either Checker. board or Random (Table I). Overall, these results suggest that humming. birds can learn all the patterns we presented, but the fact that at least 25% of all visits to good feeders were revisits on every pattern makes another interpretation possible. If our birds had revisited good feeders immediately after successful visits, this result would provide no evidence of spatial memory, and our composite measure of performance would overestimate learning. But our birds generally did not revisit good feeders immediately. During the last five trials on each pattern, they visited at least three other feeders (both good and bad) on average before revisiting good feeders (Halves: 4.85 f 5.4; Quarters: 4.98 f 5.2; Checkerboard: 3.03 f 3.2; Random: 3.74 f 4.7) and only 612% of all revisits to good feeders occurred within two intervening visits (Halves: 11.7%, Quarters: 11.8%; Checkerboard: 6%; Random: 10.1%). We conclude that our composite measure of performance adequately describes the development of spatial memories. In summary, good performance on Halves and Quarters shows that hummingbirds can learn patterned arrays that offer no visible correlates to feeder quality. Poorer performance on Checkerboard and especially Random implies that hum mingbirds may require spatial structure of some kind to help them organize their learning. HOWever, measurable improvements on the two complex patterns suggest that to learn even them is not beyond the capability of hummingbirds. Thus hummingbirds can discover and use the detailed spatial structure of their environments. Our design cannot clearly resolve how spatial structure influencesspatial learning, however. Performance may have deteriorated on later complex patterns either because earlier experience with simpler ones
Sutherhnd
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Table I. Changes in the four componentsof performancebetweenthe first five trialsand the last five trials in the pilot Component
Trials 1-5
Trials 3&40
19.2 f 9.1 9.4 l 6.5
28.4 f 3.2 5.2 f 3.8
0.062 0.062
23.0 f 23.1 3.9 f 6.1
32.1 f 12.0 0.8 f I.4
>0.062 0.062
21.2 * 6.6
13.5f 5.7
29.0 f 2.9 7.4 f 4.5
0.062 0.062
27.0 f 9.7 7.4 f 6.0
25.3 f 12.0 2.2 f 2.0
BO.062 >0.062
22.3 f 7.3 21.1 f 7.1
26,9 f 4.5 20.6 f 6.1
>0.062 BO.062
17.9 f 7.2
14.8f 6.5
21.7 f 6.3 9.8 f 4.7
>0+62 >0@62
22.4 f 9.0 20.7 f 8.5
27.5 f 3.7 18.8 f 5.0
BOG62 >0.062
IS.1 f 8.5 11.0+6.7
16.8 f 5.4 8.4 f 4.6
BO.062 >o+I62
P
Halves Number of first visits To good feeders To bad feeders Percentage revisits To good feeders To bad feeders Quarters Number of first visits To good feeders To bad feeders Percentage revisits To good feeders To bad feeders cbeskerboud Number of first visits To good feeders To bad feeders Percentage revisits To good feeders To bad feeders
RIUldOIll Number of fust visits To good feeders To bad feeders Percentage revisits To good feeders To bad feeders
Shown are means ( f SD) of the four birds for each component. P-values were calculated using the Walsh test and are one-tailed.
interfered with later learning, or because learning complex patterns is more diEcult. EXPERIMENT 1: DEVELOPMENT OF PATTERNED EXPECTATIONS ABOUT FEEDER QUALITY The pilot study demonstrated that hummingbirds can learn large, patterned arrays that offer no visible cues to nectar availability, but it did not distinguish between two plausible explanations of the results. Our birds may have learned spatial relationships among feeders, which would he consistent with the notion of cognitive maps as discussedby Menzel & Wyers (1981), Gould (1986b), Gass (1985) and others. In principle, however, simpler, local, rules of thumb could account for the results with no spatial memory, no cognition,
and no knowledge of spatial relationships (Krebs et al. 1983; Wilkie & Summers 1983; Stephens & Krebs 1986; Wolf Jc Hainsworth 1990, Dyer et al. 1993). For example, learning a pair of simple, spatially undifferentiated rules to guide arearestricted search (i.e. turn more after finding food and jump after not finding food), could have kept our birds in patches of good feeders, gotten them out of patches of bad feeders and accounted for most of the pilot results (seealso Oster & Heinrich 1976; Stephens & Krebs 1986). In an experimental field study of rufous hummingbird patch choice (Gass 8c Sutherland 1985), we found no evidence of such rules of thumb and concluded that spatial memory of patches was required to explain our results. To distinguish between these possibilities, we repeated the pilot experiment using the Quarters pattern, but switched the pattern to its mirror
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image midway through the day, after birds had reached high performance. If improvement results from learning spatially undifferentiated rules of movement, the rules should apply as well after the switch as before and birds should continue at high performance. But if improvement results from learning the positions of good feeders, whether independently or as patterns, performance should deteriorate sharply after the switch to well below chance levels, and stay low until birds stop using or modify the old pattern and learn the new one. Experimental switches of the structure of foraging habitats are powerful diagnostic tools for revealing mechanisms of learning. For example, Vander Wall (1982) and Balda & Turek (1984) evaluated nutcrackers’ responses to sudden dislocations or removals of landmark cues to infer how they recovered hidden caches. Methods We used six naive, adult, wild-caught rufous hummingbirds (four females and two males). Maintenance and training methods were similar to the pilot. The experimental chamber was also the same, except that feeders were plastic tubing (1.67 mm inner diameter x 20 mm long) with enlarged, upturned, open reservoirs at the end. Feeders were mounted I1 cm apart horizontally and vertically behind 2.4mm holes in a metal panel on the wall of the chamber. Feeder positions were marked with round 19-mm fluorescent orange Avery labels with central 64mm holes for the feeder tubes. Birds could not see the contents of feeders, and in a preliminary test in which we replaced good feeders with either empty or waterfilled feeders, birds probed both, so here bad feeders were empty instead of containing water as in the pilot. A microcomputer recorded signals from photodarlington photocells triggered by the birds’ bills on arrival and departure from feeders. On the day after training, each bird had 30 40-s trials on the same Quarters pattern we used in the pilot study (Fig. 1). After trial 30, we replaced all feeders with clean ones and switched the pattern to its mirror image for the remaining 30 trials; good feeders were suddenly bad, and vice versa. Results and Discussion Before the switch, results were similar to those of the pilot for the Quarters pattern (Fig. 3; compare with Fig. 2). All birds began near chance
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Trial Figure 3. Overall performance in experiment 1. * pattern was switched to its mirror-image after trial 34 (indicated by the solid vertical line). The broken hori. zontal line indicates chance performance. Each point i; an average for six birds for each trial. The figun summarizes I3 341 visits to feeders in 360 trials.
performance, improved quickly from the start, and were still improving by trial 30 (Fig. 3). Although each bird had performed at 75% or more correct visits for at least 10 trials before the switch, each dropped to well below 50% for at least two trials after the switch such that average performance on trial 31 was 3 1.8 f 12.8% (one. tailed Walsh test, trials 29-30 versus 31-32: N=6, P=O.O16). The first visit of each trial for each bird on trials just before and just after the switch illustrate this dramatic shift in performance. Whereas 88.5 f 32.6% of the first visits of trials by all birds had been correct on trials 2630, 100% were incorrect on the next five trials for all birds. In fact, performance on the first six visits of trials was significantly higher on trials 26-30 than on the five trials after the switch (trials 2630: 86.1 f 18.5%; trials 31-35: 31.8 f 27.9%; onetailed Walsh test: N=6, P=O.O16). Thus, these birds continued to begin trials by visiting locations that had provided food but did no longer, and they failed to visit feeders that now contained food. These results are incompatible with the rule-of-thumb hypothesis, because the local rules that it postulates about how the profitability of visits influences subsequent movements cannot apply to first visits. We cannot reject the spatial memory hypothesis. Performance recovered quickly after the switch. Our birds averaged 75% by trial 40 and had regained pre-switch performance by trial 60 (Fig. 3). All components of overall performance for the
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& Gas:
Hummingbird
last five trials differed insignificantly from the last five trials before the switch (first visits to good feeders in trials 2630= 17.7 f 7.9; trials 55-60=22.2 f 6.7; first visits to bad feeders in trials 2630=7.6 f 4.9; trials 5560= 10.0 f 3.7; percentage revisits to good feeders in trials 26-30~41.5 f 9~2%; trials 55-60~40.3 f 9.5%; percentage revisits to bad feeders in trials 2630= 13.6 f 10.2%; trials 55-60= 19.7 f 9.5%; one-tailed Walsh tests: N=6, P>O.O94for all four components). Persistence of previously profitable spatially differentiated patterns of foraging in the face of inverted spatial patterns of opportunity demonstrates that improved performance in these experiments does not entirely result from learning spatially undifferentiated rules for moving between good and bad feeders. Although rules of this kind may be involved, particularly in the early stages of learning, they can explain neither the distributions of visits that we observed, nor their disruption. On the contrary, within 30 trials at most, these hummingbirds behaved as if they knew profitable locations and persisted in using this knowledge despite contradictory experience of feeder quality and poor energetic performance.
EXPERIMENT COMPLEX
2: LEARNING PATTERNS
OF
One interpretation of the poor performance on the Checkerboard and Random patterns in the pilot experiment is that hummingbirds have limited ability to learn many locations independently, and may require coarse-grained environmental structure to facilitate spatial learning. However, it may be unreasonable to expect them to learn complex patterns quickly in a situation that providesno useful information except location. If so, an alternative explanation for the pilot results is that hummingbirds simply require more time or more experience to learn complex patterns than we provided. In other words, the pilot did not distinguish qualitative limitations of capacity from quantitative differences in rates of learning relatively fine-grained structure in situations that provide no useful information except location. In experiment 2 we asked whether hummingbirds can learn Checkerboard and Random patterns well and how long they take to learn them. The experiment was open-ended in this respect,
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and we analysed each day’s results to determine what to do the next day. As in experiment 1, we planned a mirror-image switch in pattern midway through the final day (for each pattern, the final day was whenever birds had reached consistent performance that appeared asymptotic). Methods
We used five naive, adult, wild-caught rufous hummingbirds (three females and two males), maintained in individual’ cages on 13.5:10.5 L:D photoperiod for 2 months before the experiment. They ate Nektar-Plus commercial hummingbird food (Nekton U.S.A.) ad libitum on weekdays and 35% sucrose solution on weekends. Unlimited Drosophila were available at all times except during experiments. The experimental chamber, feeder array, method of data collection and experimental protocol were identical to those used in experiment 1. Training was also the same, except that the three daily training sessions lasted 6 h instead of 4. Birds lived in the experimental chamber from the beginning of training to the end of each experiment. Between training sessions and between days of the experiment the array was covered, and 35% sucrose solution was available ad libitum from a hanging feeder. Beginning on the first day after its training, we tested each bird on Checkerboard, then returned it to its home cage for 2-4 weeks. Then, after another 3 days of training (as described above), we tested each bird on Random. We assume that the long period between treatments and the second training session render the two treatments independent of each other, although our major conclusions do not depend on this assumption. Each individual had 125-165 trials on each pattern, 2 or more consecutive days of 40 trials each, then a final day of 45 trials with a mirror-image switch in pattern after trial 25. At the switch, we replaced all feeders with clean ones before adding sucrose solution. The Checkerboard experiment lasted 3 days for four birds. Bird 4 improved more slowly than the others, so we waited to switch the pattern until after trial 25 on day 4. The Random experiment lasted 4 days for all birds. Bird 3 visited the array on less than half of its trials, so we excluded its data from analyses.As in the previous experiment we excluded from analysis trials on which any
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switch; first visits to bad feeders increased from 5.2 f 2.8 in the first five trials to 6.3 f 4.6 in the last five trials before the switch). On Checkerboard, there was a significant tenResults and Discu&on dency for our birds to decrease their revisits to All five birds improved significantly before the good or bad feeders within trials before the switch switch on Checkerboard (mean performance: first (mean percentage revisits to good feeders in trials five trials=52.7 f 3.1%; last five trials before the l-5=38.5 f 22.8%; trials lOl-105=21*0 f 14.5%; switch=80.9 f 4.7%; one-tailed Walsh test: N= 5, mean percentage revisits to bad feeders in trials PO.O62). On Random, however, performance feeders= 7.8 f 9.5%). Note that these results differ varied widely between birds: two birds exceeded in two ways from those in the pilot experiment. 90% correct more than once and averaged 85% in Here, those birds whose performance improved the five trials before the switch (Fig. 4b), whereas before the switch generally did not visit as many the other two never exceeded 62% and averaged of the good feeders as in the pilot, and they only 52% during that same period. In general, showed a much stronger tendency to avoid over the longer duration of this experiment rela- visiting bad feeders on both Checkerboard and tive to the pilot, those birds that did improve Random. reached higher levels of performance than on the As in experiment 1, every bird that had signifisame patterns in the pilot (compare Fig. 4 with cantly improved on either pattern before the Fig. 2). switch showed an immediate drop in performance This improvement in performance before the after the switch (Fig. 4a, b). The decrease was switch on Checkerboard was primarily because more dramatic and more consistent on Checkerbirds significantly decreased their number of first board, where all birds had achieved high performvisits to bad feeders from an average of 12.9 f 3.7 ance before the switch (mean % correct: last five in the first five trials down to an average of trials before switch=80.96 f 4.7%; first five trials 4.0 f 2.2 in the last five trials before the switch after switch= 34.3 f 23.5%; one-tailed Walsh test: (one-tailed Walsh test: N=5, SO.031). Birds also N=5, P
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Figure 4. Performance on (a) Checkerboard and (b) Random for all trials of experiment 2. Each individual’s performance is indicated by a different symbol. For Checkerboard, the thick solid line indicates the mean performance of four individuals on each trial. Not shown for Checkerboard is the performance of the bird that required 4 days to complete the experiment. For Random, the thick solid line indicates the mean performance of the two individuals that improved before the switch and whose performance was disrupted by the switch; the thin solid he indicates mean performance of the other two individuals. Horizontal broken lines indicate chance performance and vertical broken lines
t:
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PcO.03 1). Similarly, the first six visits of each trial averaged 87.6 f 16.3% to good feeders in the last five trials before the switch, significantly higher than the 33.4 f 23.2% average in the five trials after the switch (one-tailed Walsh test: N=S, PcO.031). On Random, the two birds whose performance dropped significantly after the switch made 55.6% of their first visits to good feeders in the five trials before the switch but only 44.4% in the five trials after the switch. These two birds also made more of their first six visits to good feeders (83.7%) in the five trials before than in the five trials after the switch (44.0%). No comparable trends were observed for the two birds unaffected by the switch. In fact, they tended to make more of their first visits to good feeders after than before the switch (20.0% in the five trials before versus 60.0% in the five trials after), and only slightly more of their first six visits were to good feeders in the five trials after the switch (56.6%) than before (552%). These results support the conclusion from experiment 1 that development of spatially structured expectations is a component of learning and they extend that conclusion to complex patterns. The results suggest that poorer performance on complex patterns results more from quantitative constraints on rate of spatial learning than from qualitative limitations of capacity. It is possible that the two birds that did not learn the Random patterns and were not thrown off by the switch may have approached or exceeded their qualitative limits. The fact that they performed as well as the others for most of day 1 (Fig. 4b) hints that they may have been able to learn the pattern. But the fact that they then dropped to chance and remained there for the next 3 days may indicate that they found learning the pattern too costly, and followed some alternative strategy. We can offer no solid evidence to distinguish between these possibilities. We initially argued that hummingbirds should learn the Checkerboard pattern faster and better than Random because its patches are equal in size and regularly spaced: it is less complex geometrically. The results showed that birds did learn Checkerboard more quickly; four of five birds reached criterion in 2.5 days on Checkerboard, but only two of four birds reached criterion at all on Random, and those required 3.5 days. It is less clear, however, that they learned the Checkerboard pattern any better than Random. The lack
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of statistical power in this experiment precludes specifying how constraints on learning of finescale patterns might operate. GENERAL
DISCUSSION
Questions about learning and use of patterns of variation at various spatial and temporal scales are becoming increasingly important in foraging ecology and behaviour (Kamil 1978; Gass 1985; Holling 1992; Benhamou 1994), although identifying the scale on which they do this is a difficult problem (Stephens& Krebs 1986; Gass& Roberts 1992; Healy & Hurly 1995). Three of our results support the conclusion from other studies that spatial memory is an important component of hummingbird foraging behaviour at the scale of patches of flowers (Gass & Sutherland 1985) and may be important at the within-patch scale(Miller et al. 1985; Gill 1988; Valone 1992; cf. Wolf & Hainsworth 1991). First, hummingbirds learned profitable locations within numerically large patterned arrays of visually identical feeders. Second, birds who had learned arrays continued to visit previously profitable locations that no longer contained food, so the profitability of visiting them was negative. This illustration of behavioural inertia is similar to Ewald’s (1980) observation that Anna’s hummingbirds continued to visit and territorially defend feeders in the field after their sugar water had been replaced with water. Third, although the spatial complexity of arrays constrained the rate at which birds learned them, the fact that some individuals performed well even on Random suggests that hummingbirds’ ultimate capacity to learn spatial patterns is probably beyond anything they faced in these experiments. The mirror-image switches in experiments 1 and 2 allowed analysis of foraging in the absence of current reinforcement, permitting a distinction between possible kinds of learning. Persistenceof previously profitable spatial patterns of foraging under these conditions is strong evidence that the hummingbirds did not learn just simple, spatially unstructured rules of movement such as have been proposed in ‘area restricted search’ hypotheses (Oster & Heinrich 1976; Stephens & Krebs 1986); instead, they learned either patterns of profitability or patterns of foraging movements. A reasonable interpretation is that foragers develop spatially structured expectations about the quality
Sutherland & Gas: Hummingbird spatial memory ,,f their environments and guide their movements 4th these. An experimental field study of rufous hummingbirds also produced several kinds of evidence for this conclusion (Gass & Sutherland 1985). This capability is not surprising, given the degreeof patterning of natural environments and the wealth of evidence that learned expectations are common and important in the daily lives of ntany kinds of animals (Krebs et al. 1983; Gass 1985).
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importantly, birds began trials just after the pattern switches with direct flights to previously good feeders. Similarly, each morning in a field experiment, hummingbirds preferentially visited patches of flowers that had been good the previous day regardless of their current profitability (Gass & Sutherland 1985). The fact that they anticipated incorrectly after the switch is difficult to interpret in any other way than that they used spatial memory to guide their choices. Other studies of hummingbirds have produced similar evidence of both fine (e.g. Miller et al. 1985; Brown & Gass Implications for Hummingbird Spatial Memory 1993) and coarse-grdined memory (Armstrong Ideas about how animals perceive, remember et al. 1987). and respond to their environments are becoming Our results show clearly that regardless of the clear enough to allow studies of foraging to effec- extent to which hummingbirds use proximal cues tively distinguish alternatives. Gould (1984) con- to guide foraging in nature, they can use spatial trasted parameter-based hypotheses about spatial memory alone. There is considerable evidence for memory, under which animals abstract a limited use of correlates of profitability by nectarivorous set of attributes or pattern elements from scenes foragers (Heinrich 1979; Dyer 1991; Brown & and later reconstruct the scenes from them, and Gass 1993). Our experimental environment was picture-based hypotheses, under which they poor in visible information but rich in spatial remember whole scenes in a unitary way. This structure, and most birds performed well on all of distinction is similar to that between cue-based the patterns we presented. This demonstrates that and cognitive mapping hypotheses (Olton 198). spatial memory and other cognitive processesare Work to date on honey bees predominantly sup- central components of hummingbirds’ foraging ports parameter-based spatial memory (Dyer competence. Although our results with humming1991; Dyer et al. 1993; but see Gould 1986b. birds are consistent with criteria for map-like 1987). but field experiments with hummingbirds representations developed by Menzel & Wyers as yet allow no conclusions about the underlying (1981) and Gould (1984, 1986a), they cannot form of memory (Gass & Sutherland 1985; Wolf distinguish whether other mechanisms such as & Hainsworth 1991). A critical piece of evidence low-level environmental cues or rules of thumb for cognitive mapping is whether animals ‘take arc also used in foraging. Our laboratory environshortcuts’, moving directly between familiar but ment was much less rich in many kinds of ,widely separated points along routes they may information than even the simplest of field ennever have taken before (Gould 1986a). To do vironments, and it is likely that use of information this, they must respond to ‘momentarily absent about the distribution, availability and relative stimuli or currently non-sensed features of the profitability of food of various kinds and on environment’ (Menzel & Wyers 1981). and this is various spatial and temporal scales, may confer a general feature of cognition. Our experiments ability to forage effectively in a wide variety of provide two kinds of evidence that hummingbirds situations (Dukas & Real 1991; Valone 1992). Our construct cognitive maps of their environments observation that not all birds learned the complex spatial pattern corroborates Valone’s (1992) conand use them to guide their foraging. First, although the hummingbirds could not clusion that some birds use memory while others perceive the quality of feeders except by probing may rely on other mechanisms in foraging in them and could not perceive distribution of prof- patchy environments. itability except by inducing it from their experIn two recent studies of hummingbirds foraging ience of feeders, they clearly responded to the in large, moderately patchy territories of Ipomopdistribution of energy in their environments. Sec- sis aggregata, Wolf & Hainsworth (1990, 1991) ond, as performance improved on all patterns, assessedtwo hypotheses about how non-random individuals increasingly began trials with direct foraging could occur: (1) hummingbirds rememflights from their perches to good feeders. More ber information from previous foraging bouts, or
1284
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Behaviour,
(2) they respond to patterns of rewards on current bouts. They analysed patterns of movement among inflorescences within clumps and among clumps of inflorescences, and they found little evidence for the use of memory information at either scale. They cautioned, however, that their results reveal more about the difficulty of assessing use of memory in complex, unmanipulated natural environments than about whether memory is important in hummingbird foraging (Wolf & Hainsworth 1991). While our laboratory study does not fit clearly within either of the scales examined by Wolf & Hainsworth, ij does underline the advantages to hummingbirds of using memory when their foraging situations either require it (as in these laboratory experiments), or facilitate it as in field studies of natural or artificial patches of varying qualities (Gass & Sutherland 1985; Valone 1992). This study does not address directly the issue of spatial scale of spatial memory that we raised in the Introduction. Although the pilot experiment suggested that the resolution of hummingbird spatial memory is limited, it is unclear what spatial scale of natural memory problem the wall panels simulated. Nor do our experiments address whether spatial pattern learning is specific to any scaleor is general and independent of scale.While we refer to the groups of good and bad feeders in the Halves, Quarters, and Checkerboard treatments of the pilot experiment as ‘patches’, and imagine them to represent patches of natural flowers to the birds, the experiments do not indicate whether they actually did so, and they differ from natural patches in several ways. For example, natural patches of the same speciesare separated from each other and differ to some extent in their internal arrangement (Gass & Sutherland 1985), but our patches abutted and were identical visually. In spite of these cautionary notes, however, the results encourage consideration of the abstract, geometric structure of habitats as important components of the foraging problems animals face in nature.
ACKNOWLEDGMENTS Peter Cahoon contributed intellectually to many aspects of the project, and Kaaren Lewis and Karen Price helped collect data. Peter Cahoon, Don Ludwig, Don Wilkie and Dave Zittin
50.
5
assisted with analysis. Russ Balda, Gayle Brown, Lynn Carpenter, Paul Ewald, Al Kamil, Rick Miller, Jamie Smith, Staffan Tamm, Don Wilkie, Rob Willson and an anonymous referee made many helpful suggestions on early versions of the manuscript. Financial support was provided by the National Sciencesand Engineering Research Council (NSERC) operating grant 58-9876 to C.L.G. and NSERC and University of British Columbia postgraduate scholarships to G.D.S.
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McGaugh Guilford. Siegel, S. 1956. Nonparameaic Statistics for the Behavioral Sciences. New York: McGraw-Hill. Spctch, M. L. & Honig, W. K. 1988. Characteristics of -pigeons’ spatial working memory in an open-field task. Anim. Learn. Behav.. 16, 123-131. Stephens, D. W. & Krebs, J: R..1986. Foraging Theory. Princeton, New Jersey: Princeton University Press. Valone, T. 1. 1991. Bayesian and prescient assessment: foraging with pre-harvest information. Anim. Behav., 41,569-577. Valone, T. J. 1992. Information for patch assessment: a field investigation with black-chinned hummingbirds. Behav. Ecol., 3, 21 l-222.
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Vander Wall, S. B. 1982. An experimental analysis of cache recovery in Clark’s nutcracker. Anim. Behav., 30,8494. Wilkie, D. M., Spetch, M. L. & Chew, L. 1981. The ring dove’s short-term memory capacity for spatial information. Anim. Behav., 29, 639-641. Wilkie, D. M. & Summers, R. J. 1983. Pigeons’ spatial memory: factors a&.cting delayed matching of key location. J. exp. Analysis Behav., 37,4>56. Wolf, L. L. & Hainsworth, F. R. 1983. Economics of foraging strategies in sunbirds and hummingbirds. In: Behavioural Energetics: the Cost of Survival in Verte-
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brutes (Ed. by E. P. Aspey Br S. I. Lustic), pp. 22~ 264. Columbus, Ohio: Ohio State University Press. Wolf, L. L. & Hainsworth, F. R. 1990. Non-random foraging by hummingbirds: patterns of movement between Ipomopsis aggregata (Purschl V. Grant infloresc&es. Funct. GoI. i 4, 149151. Wolf, L. L. & Hainsworth, F. R. 1991. Hummingbird foraging patterns: visits to clumps of Ipomopsis aggre. gata inflorescences. Anim. Behav., 41,803-812. Zimmerman, M. 1981. Patchiness in the dispersion of nectar resources: probable causes. Oecologia (Berl.), 49, 154157. -Is
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1995, 50, 1273-1286
Learning and remembering of spatial patterns by hummingbirds GLENN
D. SUTHERLAND & CLIFTON of Zoology, University of British
Department
(Received 20 January 1994; jinal acceptance 6 March
LEE GASS Columbia
initial acceptance 30 April 1994; 1995; MS. number: A7118R)
Abstract. Hummingbirds’ responsesto the spatial distribution of their food were examined using arrays of visually identical feeders in the laboratory. Rufous hummingbirds, Selasphorus rufus, learned to visit Profitable feeders in square arrays of 64 feeders on a wall in which only half contained food and the only source of information about feeder quality was location. Birds learned quickly and well if profitability was simply patterned. They learned more slowly but eventually reached high performance on complex patterns, especially if feeders were regularly distributed. Memory of pattern accounted for much more of performance on all patterns than either simple movement rules or memory of individual locations. When food distributions were switched to their mirror images after birds had reached asymptotic performance, all birds that had performed well before the switch continued for several trials to visit the feedersthey had visited before the switch, lagging in redistributing effort to match the new pattern. It is suggestedthat in the absence of visible correlates of feeder quality, hummingbirds use coarse-grained memories of the spatial patterning of energetic profitability to guide their foraging. These memories develop with repeated experience of environments, develop more quickly in simply patterned environments and persist despite changes in food distribution. Poorer performance in complex arrays is inconsistent with a fine-grained model in which birds remember point sources of food independently. Persistenceof foraging patterns at the c%st of significantly reduced gross food intake and severely reduced net intake after pattern switches demonstrates that hummingbirds rely greatly on memory of profitability in guiding foraging; however, their quick recovery to previous performance shows that they quickly modify their memory of places on the basis of new information. These results are compared with some recent field studies of hummingbird foraging in which use of memory could not be reliably demonstrated, or was only one of several mechanisms underlying foraging patterns. 0 1995 The Association
Animals’ food varies in quality, quantity and availability at several spatial scales including whole geographical regions, habitats within them and the home ranges of individuals (Gass & Montgomerie 1981; Menzel & Wyers 1981; Gass & Roberts 1992; Holling 1992). Individuals could take advantage of this variation if they could learn and remember its spatial distribution, and Wolf & Hainsworth (1983) suggested that repeated exposure to information about profitability is a potential advantage of territoriality. The distribution and abundance of nectar available to territorial hummingbirds, for example, is influenced Correspondence:G. D. Sutherland,Centre for Applied Conservation Biology, Faculty of Forestry, University of British Columbia, Vancouver, B.C. V6T 124, Canada (email: [email protected]). C. L. Gass is at the Department of Zoology, University of British Columbia, Vancouver, B.C. V6T 124, Canada. 000333472/95/l
11273+
14 $12.00/O
for the Study of Animal
Behaviour
by the dispersion and nectar production rates of flowers, the spatial and temporal history of foraging by the hummingbirds and their avian and insect competitors (Zimmerman 1981; Wolf & Hainsworth 1983; Armstrong et al. 1987) and other factors. Recent laboratory and field studies of strategies underlying patterns of exploitation of patches by hummingbirds (Gass & Sutherland 1985; Valone 1992) and granivores (Valone 1991) show that ability to remember patch information is an important component of foraging successin territorial species. Several food-hoarding species can remember for hours, days or months the locations of many food items that they have hidden (see reviews in Shettleworth 1985; Sherry 1987). Spatial memory has also been studied in non-hoarding species including pigeons, Columba livia (Wilkie & Summers 1983; Spetch & Honig 1988) doves
$3 1995 The Association
1273
for the Study
of Animal
Behaviour
1274
Animal
Behaviour,
(Wilkie et al. 1981), rats, Rattus norvegicus (Olton & Samuelson 1976; Roberts 1979, 1982), gerbils, Meriones unguiculatus (Collett et al. 1986), chimpanzees, Pan troglodytes (Menzel 1973, 1978), marmosets, Saguinus fuscicollis (Menzel & Juno 1982) and humans (Aadland et al. 1985). Spatial relationships between features or resources are basic components of the environments of animals (Balda & Kamil 1989) and the ability to remember spatial locations is likely to be of general importance for foraging (Sherry 1987). Current laboratory paradigms that model key features of field situations are examining what factors influence spatial memory capacity and retention times at the spatial scale of point locations (Krebs et al. 1990; Jacobs & Liman 1991; Balda & Kamil 1992; Jacobs 1992). Several studies have suggested that hummingbirds and other nectarivores use spatial memory in foraging. Euglossine bees repeatedly return to the locations of particular plants along their foraging routes, even after the plants are removed (Janzen 1971). Honey bees, Apis mellifra, may navigate as if they use ‘landmark maps’ (Gould 1986a, 1987), but their representations do not include geometrical map-like relationships among places (Dyer 1991). Sunbirds and honeycreepers may use spatial memory to avoid revisiting inflorescencesthey have depleted (Gill & Wolf 1977; Kamil 1978). Hummingbirds rapidly learn individual locations in small arrays of feeders, with or without cues such as colour (Gass 1978; Cole et al. 1982), but this ability is influenced more by spatial position than by colour cues (Miller et al. 1985; Brown & Gass 1993). In the field, hummingbirds learn, preferentially use and remember at least overnight the most profitable patches of flowers in their territories, even if these are small and distributed among many others in a heterogeneous habitat (Gass 8t Sutherland 1985; Gill 1988). Attempts to identify, without using experimental manipulations, how hununingbirds use spatial memory in the field have produced ambiguous results, however (Wolf & Hainsworth 1991). These studies suggest that hummingbirds can learn spatial distributions at several spatial scales, but raise questions about their reliance on detailed spatial information in fine-grained situations with many patches (Wolf & Hainsworth 1991). To what extent and how quickly do hummingbirds learn spatial patterns? What determines how quickly and how well they learn them? How long
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do they remember patterns, and how quickly do they learn new ones when conditions change? To explore these questions, we designed a series of laboratory studies that provided geometrically different patterns of nectar availability in arrays of 64 visually identical feeders in which the only source of information about feeder quality was location. Hummingbirds had to learn and prefer. entially visit profitable feeders to maintain neutral or positive energy balance over a series of trials. PILOT STUDY: THE LIMITS PATTERN COMPLEXITY
OF
In this pilot we presented a sequence of increas. ingly complex patterns of nectar availability to individuals on consecutive days to discover the limits of their ability to learn them. Arrays were the same size (64 feeders) and contained the same proportion of profitable feeders (half), but had differently patterned nectar availabilities. Although this non-randomized design precludes statistical analysis of responses to degree of complexity, deteriorating performance on successive days would suggest that pattern complexity is involved. We asked two questions. Can humming. birds learn complex patterns? If so, what patterns would be appropriate for our later experiments into the dynamics of learning and relearning patterns? Methods We used four naive, wild-caught adult female rufous hummingbirds, Selasphorus rufus, maintained communally in a large aviary for 6 months before testing (13.5: 10.5 h 1ight:dark photoperiod). The maintenance food was 22% sucrose solution (mass/mass) with added protein (95% soya protein), minerals (Avimin), vitamins (Avitron), fatty acids (Linatone) and wheat germ oil on weekdays, and 35% (mass/mass)sucrose on weekends. Unlimited Drosophila were available at all times in the aviary, but not in experimental chambers. We performed all training and experiments in an experimental chamber (8.1 x 3.5 x 2.5 m) with a perch in the centre and a green painted wooden panel (1.07 x 1.24 m) mounted on one wall with a regular orthogonal array of 64 feeders on 11-cm centres horizontally and vertitally. The feeders were purple plastic syringe
Sutherland
& Gas: Hummingbird
(a)
(b)
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0000.0.. 0000.0.. 0000.0.. 0000.0.. 0.000000 0.000000 0.000000 0.000000
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El&ure 1. The four patterns of feeder quality: (a) Halves, (b) Quarters, (c) Checkerboard, (d) Random. 0: Good feeder locations (i.e. feeders containing food at the start of trials): 0: bad feeder locations. Not drawn to scale.
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spatial patterns (Fig. 1). Patterns remained constant within days but increased in complexity each day, as follows: day 1, Halves; day 2, Quarters; day 3, Checkerboard; day 4, Random (a different randomly generated pattern than that used for training). At the beginning of each trial, the 32 good feederscontained 2 ~1of 25% sucrosesolution, and the 32 bad feeders contained 2 )11of water. This volume is typical of hummingbird flowers (Gass & Roberts 1992). Because hummingbirds usually empty flowers in the field (Gass & Montgomerie 1981; Carpenter 1987) and only one of 40 feeders visited in a preliminary test contained any measurable residual sucrosesolution, we assumed that all revisits during trials were unprofitable. We kept birds in the experimental chamber without food for 15-20 min before trial I each day. We observed trials from outside the chamber through a one-way mirror, recorded visits on a tape-recorder and then transcribed them into a computer. Data analysis
needle cups plugged with epoxy, mounted on removable corks. Between trials, we removed visited feeders from the panel (without entering the chamber), refilled them with a Hamilton repeating dispenser, and replaced them. Experimental
procedures
In the field, rufous hummingbirds typically alternate between brief (< 1 min) foraging bouts in which they visit a sequence of flowers, and S-lomin periods of perching (Gass Kc Sutherland 1985). Our experiments modelled this behaviour pattern. The array was exposed for 1 min every 10min by raising a window blind covering it. Birds could stop feeding and return to the perch at any time before we lowered the blind. On each of the 3 days before testing, each bird had 20 trials of training, as follows. On training day 1, all 64 feeders contained 2 ~1of 25% sucrose solution at the beginning of each trial. On training days 2 and 3, only 32 feeders contained food, distributed in a different randomly generated pattern each day. Between training sessionsthe birds lived in the aviary under normal maintenance conditions. Beginning at 0830 hours on each of 4 consecutive days, each bird had 40 trials in one of four
We were interested in studying hummingbirds’ responses to individual locations, so we termed any visit to a good feeder location as correct, whether it was a profitable first visit on a trial, or an unprofitable revisit later during the same trial. We expressedthis as an overall % correct measure of performance for each trial. This measure has four components: total first visits made to good feeders and to bad feeders during trials, and revisits to both types of feeder. Improvements in performance could result from increasing either measure of visits to good feeders or by decreasing either measure of visits to bad feeders. We eliminated trials with less than eight visits from further analysis to avoid analytical biases introduced by short sequences (15 of 640 trials). We used the non-parametric Walsh test (Siegel 1956) for our matched-pairs tests because the assumptions of parametric tests could not reliably be met. For a sample size of four (as in the pilot), probabilities cannot be determined below P=O.O62. Where pooled means for sample sizes greater than two are given, standard deviations are also reported. Results and Discussion Performance on all patterns started near 50% correct (chance), then improved (Fig. 2). On
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Trial Figure 2. Overall performanceon each pattern in the
pilot study: Halves (top) and Checkerboard(bottom); Quarters (top) and Random (bottom). Points are averagesfor four birds over four trials; vertical bars represent95% confidenceintervals. The broken horizontal line indicates chance performance. The figure summarizes38 399 visitsto feedersin 625 trials. Halves, performance for all four birds averaged 87.8% ( f 9.01) by trial 10. All four birds exceeded 90% at least once within 10 trials, three achieved 100% at least once in the first 20 trials, and none achieved lessthan 80% in any of the last 10 trials. On Quarters, all birds performed above 70% by trial 10, and average performance reached 76.6% ( f 9-50) in the last five trials. Only two birds achieved 100% on any trial on Quarters, but no individual achieved less than 65% after trial 20. On Checkerboard and Random, improvement in performance was small (Fig. 2; Checkerboard: mean f SD performance for trials l-5=52.4 f 4.02%; trials 36-40 = 6 1.2 f 4.02%; Random: mean performance for trials l-5=54*2 f 5.87%; trials 36-40=61.7 f 5.48%; one-tailed Walsh test: N=4, P=O.O62 for both comparisons). Despite the difference in complexity between the Checkerboard and Random patterns, performance on them was nearly identical and showed no sign of reaching an asymptote as on Halves or Quarters (Fig. 2). Qn either Checkerboard or Random, no bird exceeded 74% on any trial, and none achieved less than 50% after trial 26. On the Halves and Quarters patterns, our birds improved their performance principally by increasing first visits to good feeders during trials (Table I). All birds also improved performance by decreasing their first visits to bad feeders (Table I). However, trends in the proportions of good and bad feeders that were revisited were less clear for these patterns. On Halves, some birds increased their revisits to good feeders, but no trend was
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apparent on Quarters (Table I). All birds decreased their revisits to bad feeders on the Halves pattern, but only some did on Quarters (Table I). Trends in all four components of performance were more equivocal on both Checkerboard and Random than on Halves and Quarters. On average, the number of first visits to good feeders was higher at the end of the pilot for both Checker. board and Random (Table I). Even in this cornponent, not all birds were consistent in their response. For the other components, there was little difference between early and late trials, and no consistent trends emerged on either Checker. board or Random (Table I). Overall, these results suggest that humming. birds can learn all the patterns we presented, but the fact that at least 25% of all visits to good feeders were revisits on every pattern makes another interpretation possible. If our birds had revisited good feeders immediately after successful visits, this result would provide no evidence of spatial memory, and our composite measure of performance would overestimate learning. But our birds generally did not revisit good feeders immediately. During the last five trials on each pattern, they visited at least three other feeders (both good and bad) on average before revisiting good feeders (Halves: 4.85 f 5.4; Quarters: 4.98 f 5.2; Checkerboard: 3.03 f 3.2; Random: 3.74 f 4.7) and only 612% of all revisits to good feeders occurred within two intervening visits (Halves: 11.7%, Quarters: 11.8%; Checkerboard: 6%; Random: 10.1%). We conclude that our composite measure of performance adequately describes the development of spatial memories. In summary, good performance on Halves and Quarters shows that hummingbirds can learn patterned arrays that offer no visible correlates to feeder quality. Poorer performance on Checkerboard and especially Random implies that hum mingbirds may require spatial structure of some kind to help them organize their learning. HOWever, measurable improvements on the two complex patterns suggest that to learn even them is not beyond the capability of hummingbirds. Thus hummingbirds can discover and use the detailed spatial structure of their environments. Our design cannot clearly resolve how spatial structure influencesspatial learning, however. Performance may have deteriorated on later complex patterns either because earlier experience with simpler ones
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Table I. Changes in the four componentsof performancebetweenthe first five trialsand the last five trials in the pilot Component
Trials 1-5
Trials 3&40
19.2 f 9.1 9.4 l 6.5
28.4 f 3.2 5.2 f 3.8
0.062 0.062
23.0 f 23.1 3.9 f 6.1
32.1 f 12.0 0.8 f I.4
>0.062 0.062
21.2 * 6.6
13.5f 5.7
29.0 f 2.9 7.4 f 4.5
0.062 0.062
27.0 f 9.7 7.4 f 6.0
25.3 f 12.0 2.2 f 2.0
BO.062 >0.062
22.3 f 7.3 21.1 f 7.1
26,9 f 4.5 20.6 f 6.1
>0.062 BO.062
17.9 f 7.2
14.8f 6.5
21.7 f 6.3 9.8 f 4.7
>0+62 >0@62
22.4 f 9.0 20.7 f 8.5
27.5 f 3.7 18.8 f 5.0
BOG62 >0.062
IS.1 f 8.5 11.0+6.7
16.8 f 5.4 8.4 f 4.6
BO.062 >o+I62
P
Halves Number of first visits To good feeders To bad feeders Percentage revisits To good feeders To bad feeders Quarters Number of first visits To good feeders To bad feeders Percentage revisits To good feeders To bad feeders cbeskerboud Number of first visits To good feeders To bad feeders Percentage revisits To good feeders To bad feeders
RIUldOIll Number of fust visits To good feeders To bad feeders Percentage revisits To good feeders To bad feeders
Shown are means ( f SD) of the four birds for each component. P-values were calculated using the Walsh test and are one-tailed.
interfered with later learning, or because learning complex patterns is more diEcult. EXPERIMENT 1: DEVELOPMENT OF PATTERNED EXPECTATIONS ABOUT FEEDER QUALITY The pilot study demonstrated that hummingbirds can learn large, patterned arrays that offer no visible cues to nectar availability, but it did not distinguish between two plausible explanations of the results. Our birds may have learned spatial relationships among feeders, which would he consistent with the notion of cognitive maps as discussedby Menzel & Wyers (1981), Gould (1986b), Gass (1985) and others. In principle, however, simpler, local, rules of thumb could account for the results with no spatial memory, no cognition,
and no knowledge of spatial relationships (Krebs et al. 1983; Wilkie & Summers 1983; Stephens & Krebs 1986; Wolf Jc Hainsworth 1990, Dyer et al. 1993). For example, learning a pair of simple, spatially undifferentiated rules to guide arearestricted search (i.e. turn more after finding food and jump after not finding food), could have kept our birds in patches of good feeders, gotten them out of patches of bad feeders and accounted for most of the pilot results (seealso Oster & Heinrich 1976; Stephens & Krebs 1986). In an experimental field study of rufous hummingbird patch choice (Gass 8c Sutherland 1985), we found no evidence of such rules of thumb and concluded that spatial memory of patches was required to explain our results. To distinguish between these possibilities, we repeated the pilot experiment using the Quarters pattern, but switched the pattern to its mirror
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image midway through the day, after birds had reached high performance. If improvement results from learning spatially undifferentiated rules of movement, the rules should apply as well after the switch as before and birds should continue at high performance. But if improvement results from learning the positions of good feeders, whether independently or as patterns, performance should deteriorate sharply after the switch to well below chance levels, and stay low until birds stop using or modify the old pattern and learn the new one. Experimental switches of the structure of foraging habitats are powerful diagnostic tools for revealing mechanisms of learning. For example, Vander Wall (1982) and Balda & Turek (1984) evaluated nutcrackers’ responses to sudden dislocations or removals of landmark cues to infer how they recovered hidden caches. Methods We used six naive, adult, wild-caught rufous hummingbirds (four females and two males). Maintenance and training methods were similar to the pilot. The experimental chamber was also the same, except that feeders were plastic tubing (1.67 mm inner diameter x 20 mm long) with enlarged, upturned, open reservoirs at the end. Feeders were mounted I1 cm apart horizontally and vertically behind 2.4mm holes in a metal panel on the wall of the chamber. Feeder positions were marked with round 19-mm fluorescent orange Avery labels with central 64mm holes for the feeder tubes. Birds could not see the contents of feeders, and in a preliminary test in which we replaced good feeders with either empty or waterfilled feeders, birds probed both, so here bad feeders were empty instead of containing water as in the pilot. A microcomputer recorded signals from photodarlington photocells triggered by the birds’ bills on arrival and departure from feeders. On the day after training, each bird had 30 40-s trials on the same Quarters pattern we used in the pilot study (Fig. 1). After trial 30, we replaced all feeders with clean ones and switched the pattern to its mirror image for the remaining 30 trials; good feeders were suddenly bad, and vice versa. Results and Discussion Before the switch, results were similar to those of the pilot for the Quarters pattern (Fig. 3; compare with Fig. 2). All birds began near chance
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Trial Figure 3. Overall performance in experiment 1. * pattern was switched to its mirror-image after trial 34 (indicated by the solid vertical line). The broken hori. zontal line indicates chance performance. Each point i; an average for six birds for each trial. The figun summarizes I3 341 visits to feeders in 360 trials.
performance, improved quickly from the start, and were still improving by trial 30 (Fig. 3). Although each bird had performed at 75% or more correct visits for at least 10 trials before the switch, each dropped to well below 50% for at least two trials after the switch such that average performance on trial 31 was 3 1.8 f 12.8% (one. tailed Walsh test, trials 29-30 versus 31-32: N=6, P=O.O16). The first visit of each trial for each bird on trials just before and just after the switch illustrate this dramatic shift in performance. Whereas 88.5 f 32.6% of the first visits of trials by all birds had been correct on trials 2630, 100% were incorrect on the next five trials for all birds. In fact, performance on the first six visits of trials was significantly higher on trials 26-30 than on the five trials after the switch (trials 2630: 86.1 f 18.5%; trials 31-35: 31.8 f 27.9%; onetailed Walsh test: N=6, P=O.O16). Thus, these birds continued to begin trials by visiting locations that had provided food but did no longer, and they failed to visit feeders that now contained food. These results are incompatible with the rule-of-thumb hypothesis, because the local rules that it postulates about how the profitability of visits influences subsequent movements cannot apply to first visits. We cannot reject the spatial memory hypothesis. Performance recovered quickly after the switch. Our birds averaged 75% by trial 40 and had regained pre-switch performance by trial 60 (Fig. 3). All components of overall performance for the
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& Gas:
Hummingbird
last five trials differed insignificantly from the last five trials before the switch (first visits to good feeders in trials 2630= 17.7 f 7.9; trials 55-60=22.2 f 6.7; first visits to bad feeders in trials 2630=7.6 f 4.9; trials 5560= 10.0 f 3.7; percentage revisits to good feeders in trials 26-30~41.5 f 9~2%; trials 55-60~40.3 f 9.5%; percentage revisits to bad feeders in trials 2630= 13.6 f 10.2%; trials 55-60= 19.7 f 9.5%; one-tailed Walsh tests: N=6, P>O.O94for all four components). Persistence of previously profitable spatially differentiated patterns of foraging in the face of inverted spatial patterns of opportunity demonstrates that improved performance in these experiments does not entirely result from learning spatially undifferentiated rules for moving between good and bad feeders. Although rules of this kind may be involved, particularly in the early stages of learning, they can explain neither the distributions of visits that we observed, nor their disruption. On the contrary, within 30 trials at most, these hummingbirds behaved as if they knew profitable locations and persisted in using this knowledge despite contradictory experience of feeder quality and poor energetic performance.
EXPERIMENT COMPLEX
2: LEARNING PATTERNS
OF
One interpretation of the poor performance on the Checkerboard and Random patterns in the pilot experiment is that hummingbirds have limited ability to learn many locations independently, and may require coarse-grained environmental structure to facilitate spatial learning. However, it may be unreasonable to expect them to learn complex patterns quickly in a situation that providesno useful information except location. If so, an alternative explanation for the pilot results is that hummingbirds simply require more time or more experience to learn complex patterns than we provided. In other words, the pilot did not distinguish qualitative limitations of capacity from quantitative differences in rates of learning relatively fine-grained structure in situations that provide no useful information except location. In experiment 2 we asked whether hummingbirds can learn Checkerboard and Random patterns well and how long they take to learn them. The experiment was open-ended in this respect,
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and we analysed each day’s results to determine what to do the next day. As in experiment 1, we planned a mirror-image switch in pattern midway through the final day (for each pattern, the final day was whenever birds had reached consistent performance that appeared asymptotic). Methods
We used five naive, adult, wild-caught rufous hummingbirds (three females and two males), maintained in individual’ cages on 13.5:10.5 L:D photoperiod for 2 months before the experiment. They ate Nektar-Plus commercial hummingbird food (Nekton U.S.A.) ad libitum on weekdays and 35% sucrose solution on weekends. Unlimited Drosophila were available at all times except during experiments. The experimental chamber, feeder array, method of data collection and experimental protocol were identical to those used in experiment 1. Training was also the same, except that the three daily training sessions lasted 6 h instead of 4. Birds lived in the experimental chamber from the beginning of training to the end of each experiment. Between training sessions and between days of the experiment the array was covered, and 35% sucrose solution was available ad libitum from a hanging feeder. Beginning on the first day after its training, we tested each bird on Checkerboard, then returned it to its home cage for 2-4 weeks. Then, after another 3 days of training (as described above), we tested each bird on Random. We assume that the long period between treatments and the second training session render the two treatments independent of each other, although our major conclusions do not depend on this assumption. Each individual had 125-165 trials on each pattern, 2 or more consecutive days of 40 trials each, then a final day of 45 trials with a mirror-image switch in pattern after trial 25. At the switch, we replaced all feeders with clean ones before adding sucrose solution. The Checkerboard experiment lasted 3 days for four birds. Bird 4 improved more slowly than the others, so we waited to switch the pattern until after trial 25 on day 4. The Random experiment lasted 4 days for all birds. Bird 3 visited the array on less than half of its trials, so we excluded its data from analyses.As in the previous experiment we excluded from analysis trials on which any
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switch; first visits to bad feeders increased from 5.2 f 2.8 in the first five trials to 6.3 f 4.6 in the last five trials before the switch). On Checkerboard, there was a significant tenResults and Discu&on dency for our birds to decrease their revisits to All five birds improved significantly before the good or bad feeders within trials before the switch switch on Checkerboard (mean performance: first (mean percentage revisits to good feeders in trials five trials=52.7 f 3.1%; last five trials before the l-5=38.5 f 22.8%; trials lOl-105=21*0 f 14.5%; switch=80.9 f 4.7%; one-tailed Walsh test: N= 5, mean percentage revisits to bad feeders in trials P
0
I
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60
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.
.
80
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120
.:
.-
.
-
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-
Day 4 140
. . I
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160
180
. . I . . . 1
demarcate
days.
Figure 4. Performance on (a) Checkerboard and (b) Random for all trials of experiment 2. Each individual’s performance is indicated by a different symbol. For Checkerboard, the thick solid line indicates the mean performance of four individuals on each trial. Not shown for Checkerboard is the performance of the bird that required 4 days to complete the experiment. For Random, the thick solid line indicates the mean performance of the two individuals that improved before the switch and whose performance was disrupted by the switch; the thin solid he indicates mean performance of the other two individuals. Horizontal broken lines indicate chance performance and vertical broken lines
t:
20
40
60
80
100
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PcO.03 1). Similarly, the first six visits of each trial averaged 87.6 f 16.3% to good feeders in the last five trials before the switch, significantly higher than the 33.4 f 23.2% average in the five trials after the switch (one-tailed Walsh test: N=S, PcO.031). On Random, the two birds whose performance dropped significantly after the switch made 55.6% of their first visits to good feeders in the five trials before the switch but only 44.4% in the five trials after the switch. These two birds also made more of their first six visits to good feeders (83.7%) in the five trials before than in the five trials after the switch (44.0%). No comparable trends were observed for the two birds unaffected by the switch. In fact, they tended to make more of their first visits to good feeders after than before the switch (20.0% in the five trials before versus 60.0% in the five trials after), and only slightly more of their first six visits were to good feeders in the five trials after the switch (56.6%) than before (552%). These results support the conclusion from experiment 1 that development of spatially structured expectations is a component of learning and they extend that conclusion to complex patterns. The results suggest that poorer performance on complex patterns results more from quantitative constraints on rate of spatial learning than from qualitative limitations of capacity. It is possible that the two birds that did not learn the Random patterns and were not thrown off by the switch may have approached or exceeded their qualitative limits. The fact that they performed as well as the others for most of day 1 (Fig. 4b) hints that they may have been able to learn the pattern. But the fact that they then dropped to chance and remained there for the next 3 days may indicate that they found learning the pattern too costly, and followed some alternative strategy. We can offer no solid evidence to distinguish between these possibilities. We initially argued that hummingbirds should learn the Checkerboard pattern faster and better than Random because its patches are equal in size and regularly spaced: it is less complex geometrically. The results showed that birds did learn Checkerboard more quickly; four of five birds reached criterion in 2.5 days on Checkerboard, but only two of four birds reached criterion at all on Random, and those required 3.5 days. It is less clear, however, that they learned the Checkerboard pattern any better than Random. The lack
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of statistical power in this experiment precludes specifying how constraints on learning of finescale patterns might operate. GENERAL
DISCUSSION
Questions about learning and use of patterns of variation at various spatial and temporal scales are becoming increasingly important in foraging ecology and behaviour (Kamil 1978; Gass 1985; Holling 1992; Benhamou 1994), although identifying the scale on which they do this is a difficult problem (Stephens& Krebs 1986; Gass& Roberts 1992; Healy & Hurly 1995). Three of our results support the conclusion from other studies that spatial memory is an important component of hummingbird foraging behaviour at the scale of patches of flowers (Gass & Sutherland 1985) and may be important at the within-patch scale(Miller et al. 1985; Gill 1988; Valone 1992; cf. Wolf & Hainsworth 1991). First, hummingbirds learned profitable locations within numerically large patterned arrays of visually identical feeders. Second, birds who had learned arrays continued to visit previously profitable locations that no longer contained food, so the profitability of visiting them was negative. This illustration of behavioural inertia is similar to Ewald’s (1980) observation that Anna’s hummingbirds continued to visit and territorially defend feeders in the field after their sugar water had been replaced with water. Third, although the spatial complexity of arrays constrained the rate at which birds learned them, the fact that some individuals performed well even on Random suggests that hummingbirds’ ultimate capacity to learn spatial patterns is probably beyond anything they faced in these experiments. The mirror-image switches in experiments 1 and 2 allowed analysis of foraging in the absence of current reinforcement, permitting a distinction between possible kinds of learning. Persistenceof previously profitable spatial patterns of foraging under these conditions is strong evidence that the hummingbirds did not learn just simple, spatially unstructured rules of movement such as have been proposed in ‘area restricted search’ hypotheses (Oster & Heinrich 1976; Stephens & Krebs 1986); instead, they learned either patterns of profitability or patterns of foraging movements. A reasonable interpretation is that foragers develop spatially structured expectations about the quality
Sutherland & Gas: Hummingbird spatial memory ,,f their environments and guide their movements 4th these. An experimental field study of rufous hummingbirds also produced several kinds of evidence for this conclusion (Gass & Sutherland 1985). This capability is not surprising, given the degreeof patterning of natural environments and the wealth of evidence that learned expectations are common and important in the daily lives of ntany kinds of animals (Krebs et al. 1983; Gass 1985).
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importantly, birds began trials just after the pattern switches with direct flights to previously good feeders. Similarly, each morning in a field experiment, hummingbirds preferentially visited patches of flowers that had been good the previous day regardless of their current profitability (Gass & Sutherland 1985). The fact that they anticipated incorrectly after the switch is difficult to interpret in any other way than that they used spatial memory to guide their choices. Other studies of hummingbirds have produced similar evidence of both fine (e.g. Miller et al. 1985; Brown & Gass Implications for Hummingbird Spatial Memory 1993) and coarse-grdined memory (Armstrong Ideas about how animals perceive, remember et al. 1987). and respond to their environments are becoming Our results show clearly that regardless of the clear enough to allow studies of foraging to effec- extent to which hummingbirds use proximal cues tively distinguish alternatives. Gould (1984) con- to guide foraging in nature, they can use spatial trasted parameter-based hypotheses about spatial memory alone. There is considerable evidence for memory, under which animals abstract a limited use of correlates of profitability by nectarivorous set of attributes or pattern elements from scenes foragers (Heinrich 1979; Dyer 1991; Brown & and later reconstruct the scenes from them, and Gass 1993). Our experimental environment was picture-based hypotheses, under which they poor in visible information but rich in spatial remember whole scenes in a unitary way. This structure, and most birds performed well on all of distinction is similar to that between cue-based the patterns we presented. This demonstrates that and cognitive mapping hypotheses (Olton 198). spatial memory and other cognitive processesare Work to date on honey bees predominantly sup- central components of hummingbirds’ foraging ports parameter-based spatial memory (Dyer competence. Although our results with humming1991; Dyer et al. 1993; but see Gould 1986b. birds are consistent with criteria for map-like 1987). but field experiments with hummingbirds representations developed by Menzel & Wyers as yet allow no conclusions about the underlying (1981) and Gould (1984, 1986a), they cannot form of memory (Gass & Sutherland 1985; Wolf distinguish whether other mechanisms such as & Hainsworth 1991). A critical piece of evidence low-level environmental cues or rules of thumb for cognitive mapping is whether animals ‘take arc also used in foraging. Our laboratory environshortcuts’, moving directly between familiar but ment was much less rich in many kinds of ,widely separated points along routes they may information than even the simplest of field ennever have taken before (Gould 1986a). To do vironments, and it is likely that use of information this, they must respond to ‘momentarily absent about the distribution, availability and relative stimuli or currently non-sensed features of the profitability of food of various kinds and on environment’ (Menzel & Wyers 1981). and this is various spatial and temporal scales, may confer a general feature of cognition. Our experiments ability to forage effectively in a wide variety of provide two kinds of evidence that hummingbirds situations (Dukas & Real 1991; Valone 1992). Our construct cognitive maps of their environments observation that not all birds learned the complex spatial pattern corroborates Valone’s (1992) conand use them to guide their foraging. First, although the hummingbirds could not clusion that some birds use memory while others perceive the quality of feeders except by probing may rely on other mechanisms in foraging in them and could not perceive distribution of prof- patchy environments. itability except by inducing it from their experIn two recent studies of hummingbirds foraging ience of feeders, they clearly responded to the in large, moderately patchy territories of Ipomopdistribution of energy in their environments. Sec- sis aggregata, Wolf & Hainsworth (1990, 1991) ond, as performance improved on all patterns, assessedtwo hypotheses about how non-random individuals increasingly began trials with direct foraging could occur: (1) hummingbirds rememflights from their perches to good feeders. More ber information from previous foraging bouts, or
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(2) they respond to patterns of rewards on current bouts. They analysed patterns of movement among inflorescences within clumps and among clumps of inflorescences, and they found little evidence for the use of memory information at either scale. They cautioned, however, that their results reveal more about the difficulty of assessing use of memory in complex, unmanipulated natural environments than about whether memory is important in hummingbird foraging (Wolf & Hainsworth 1991). While our laboratory study does not fit clearly within either of the scales examined by Wolf & Hainsworth, ij does underline the advantages to hummingbirds of using memory when their foraging situations either require it (as in these laboratory experiments), or facilitate it as in field studies of natural or artificial patches of varying qualities (Gass & Sutherland 1985; Valone 1992). This study does not address directly the issue of spatial scale of spatial memory that we raised in the Introduction. Although the pilot experiment suggested that the resolution of hummingbird spatial memory is limited, it is unclear what spatial scale of natural memory problem the wall panels simulated. Nor do our experiments address whether spatial pattern learning is specific to any scaleor is general and independent of scale.While we refer to the groups of good and bad feeders in the Halves, Quarters, and Checkerboard treatments of the pilot experiment as ‘patches’, and imagine them to represent patches of natural flowers to the birds, the experiments do not indicate whether they actually did so, and they differ from natural patches in several ways. For example, natural patches of the same speciesare separated from each other and differ to some extent in their internal arrangement (Gass & Sutherland 1985), but our patches abutted and were identical visually. In spite of these cautionary notes, however, the results encourage consideration of the abstract, geometric structure of habitats as important components of the foraging problems animals face in nature.
ACKNOWLEDGMENTS Peter Cahoon contributed intellectually to many aspects of the project, and Kaaren Lewis and Karen Price helped collect data. Peter Cahoon, Don Ludwig, Don Wilkie and Dave Zittin
50.
5
assisted with analysis. Russ Balda, Gayle Brown, Lynn Carpenter, Paul Ewald, Al Kamil, Rick Miller, Jamie Smith, Staffan Tamm, Don Wilkie, Rob Willson and an anonymous referee made many helpful suggestions on early versions of the manuscript. Financial support was provided by the National Sciencesand Engineering Research Council (NSERC) operating grant 58-9876 to C.L.G. and NSERC and University of British Columbia postgraduate scholarships to G.D.S.
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Balda. R. P. & Kamil, A. C. 1992. Long-term spatial memory in Clark’s nutcracker, Nucifraga cohunbtinu. Anim.
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Balda, R. P. & Turek, R. J. 1984. The cache-recovery system as an example of memory capabilities in Clark’s nutcracker. In: Animal Cognition (Ed. by H. L. Roitblatt, T. G. Bever & H. S. Terrace), pp. 513-532. Hillsdale, New Jersey: Lawrence Erlbaum. Benhamou, S. 1994. Spatial memory and searching efficiency. Anim. Behav., 41, 1423 -1433. Brown, G. S. & Gass, C. L. 1993. Spatial association learning by hummingbirds. Antin. Behav., 46, 487497. Carpenter, F. L. 1987. Food abundance and territoriality: to defend or not to defend? Am. Zooi., 27, 387-399. Cole, S., Hainsworth, F. R., Kamil, A. C., Mercier, T. & Wolf, L. L. 1982. Spatial learning as an adaptation in hummingbirds. Science, 217, 655-657. Collett, T. S., Cartwright, B. A. & Smith, B. A. 1986. Landmark learning and visuo-spatial memories in gerbils. J. camp. Physiol., 158, 835-851. Dukas, R. & Real, L. A. 1991. Learning foraging tasks by bees: a comparison between social and solitary species. Anim. Rehav., 42,269 -276. Dver. F. C. 1991. Bees acouire route-based memories bu; not cognitive maps in’a familiar landscape. Anim. Behuv.,
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Dyer, F. C., Berry, N. A. & Richard, A. S. 1993. Honey bee spatial memory: use of route-based memories after displacement. Anim. Behuv., 45, 1028-1030.
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