Testing dynamic variance-sensitive foraging using individualdifferences in basal metabolic rates of zebra finches

Kimberley J. Mathot, Sophie Godde, Vincent Careau, Donald W. Thomas and Luc-Alain Giraldeau

K. J. Mathot (kjmathot@alumni.sfu.ca), S. Godde and L.-A. Giraldeau, Groupe de Recherche en Ecologie Comportementale et Animale, Deptdes Sciences Biologiques, Univ. du Quebec a Montreal, Case postale 8888, Succursale Centre-Ville, Montreal, Quebec, H3C 3P8, Canada. � V.Careau and D. W. Thomas, Dept de Biologie, Univ. de Sherbrooke, 2500 Boulevard de l’Universite, Sherbrooke, Quebec, J1K 2R1, Canada.

Social foragers can alternate between searching for food (producer tactic), and searching for other individuals that havelocated food in order to join them (scrounger tactic). Both tactics yield equal rewards on average, but the rewardsgenerated by producer are more variable. A dynamic variance-sensitive foraging model predicts that social foragers shouldincrease their use of scrounger with increasing energy requirements and/or decreased food availability early in the foragingperiod. We tested whether natural variation in minimum energy requirements (basal metabolic rate or BMR) is associatedwith differences in the use of producer�scrounger foraging tactics in female zebra finches Taeniopygia guttata. Aspredicted by the dynamic variance-sensitive model, high BMR individuals had significantly greater use of the scroungertactic compared with low BMR individuals. However, we observed no effect of food availability on tactic use, indicatingthat female zebra finches were not variance-sensitive foragers under our experimental conditions. This study is the first toreport that variation in BMR within a species is associated with differences in foraging behaviour. BMR-relateddifferences in scrounger tactic use are consistent with phenotype-dependent tactic use decisions. We suggest that BMR iscorrelated with another phenotypic trait which itself influences tactic use decisions.

Energetic state is an important factor influencing foragingdecisions in animals (Stephens and Krebs 1986). Whenfaced with increased energy demands or an increasedprobability of energetic shortfall, many animals will increasetheir time allocated to foraging (Turpie and Hockey 1993),accept greater predation danger while foraging (Lima andDill 1990) or adopt different foraging tactics (Stephens andKrebs 1986). Changes in foraging tactic use can occurunder increased energy requirements due to changes in theforager’s preference or aversion to variance, and henceuncertainty, in the food reward associated with a givenforaging tactic. Variance-sensitive foragers act in order tominimize the probability of energetic shortfall.

Predictions from static models of variance-sensitiveforaging are captured by the now famous energy-budgetrule: be variance-averse when expected energy budget ispositive, be variance-prone when expected energy budget isnegative (Stephens 1981). However, this rule is based on astatic analysis that does not take into account the remainingtime horizon when the decision must be made. Dynamicstate-dependent models of variance-sensitive foraging areoften better predictive devices because they expect that anindividual’s preference or aversion to variance depends bothon its energetic state and the time available in the foragingperiod to reach its energetic requirement (Houston andMcNamara 1999, Barta and Giraldeau 2000) (Fig. 1).When expecting an energetic shortfall, animals should

prefer more variable outcomes if they have only a shorttime remaining in the foraging period (Caraco andGiraldeau 1991, Barta and Giraldeau 2000). However,animals expecting an energetic shortfall but with much timeremaining in the foraging period, should favour the tacticthat provides more certain rewards, and avoid variance(Barta and Giraldeau 2000). In this study we propose to testpredictions of a dynamic variance-sensitive model.

The influence of energetic state on variance-sensitiveforaging behaviour has largely been studied by comparingindividuals during periods of low and high energeticdemand, by food depriving individuals in order to increasetheir energetic requirements, or by altering food availability(reviewed by Kacelnik and Bateson 1996, Bateson andKacelnik 1998). However, in many species, there aremarked inter-individual differences in energy needs (Speak-man et al. 2006). For example, basal metabolic rate (BMR),which represents the minimum energy requirement of anon-growing, post-absorptive organism that is at rest in itsthermoneutral zone during its normal period of inactivity(McNab 1997), can differ more than 2-fold betweenindividuals of the same species (Speakman et al. 2006).These inter-individual differences are often repeatable overextended periods of time (Bech et al. 1999, Horak et al.2002, Labocha et al. 2004, Rønning et al. 2005) indicatingconsistent differences in minimum energy requirements ofindividuals.

Oikos 118: 545�552, 2009

doi: 10.1111/j.1600-0706.2008.17357.x,

# 2009 The Authors. Journal compilation # 2009 Oikos

Subject Editor: Jan van Gils. Accepted 7 November 2008

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Here we ask whether individual differences in BMRwithin a species are associated with differences in the use ofhigh- or low-variance foraging tactics in a group foragingcontext. We use a group foraging context because whenindividuals forage in groups they can alternate between twoforaging tactics; actively searching for food (producertactic), or searching for other group mates that have locatedfood in order to join them (scrounger tactic) (Barnard andSibly 1981, Giraldeau and Caraco 2000). Both tactics aremaintained in groups via negative frequency-dependencebecause producer does better relative to scrounger whenproducer is rare, and vice versa (Vickery et al. 1991,Mottley and Giraldeau 2000). The stable frequency oftactic use exists at the point where no individual canincrease its fitness via a unilateral shift in tactic use (Mottleyand Giraldeau 2000). Although the mean payoff to eachtactic is the same within groups at equilibrium, the variance,and hence uncertainty of payoff, is greater for producer thanfor scrounger (Lendvai et al. 2004, Wu and Giraldeau2004).

We tested whether inter-individual differences in BMRwere associated with differences in the use of high-variance(producer) and low-variance (scrounger) foraging tactics.Because BMR reflects the minimum energy requirement ofan individual, we assume that individuals with high BMRswould have higher overall energy requirements thanindividuals with low BMRs (Daan et al. 1990, Ricklefs1996). Therefore, because foraging trials were carried outearly in the day, leaving foragers with much time to meettheir energy requirements, we predicted that high BMRindividuals would have a higher use of scrounger, thelow-variance tactic, compared with low BMR individuals.We used captive-bred zebra finches Taeniopygia guttata

because in zebra finches, BMR is both repeatable (Rønninget al. 2005) and heritable (Rønning et al. 2007), andindividual differences in BMR have been shown to bepositively correlated with differences in daily energyexpenditure (Vezina et al. 2006). Zebra finches are a widelyused model system in behavioural studies (Zann 1996),including group foraging in a producer�scrounger game(Giraldeau et al. 1990, Beauchamp 2006).

BMR-related differences in foraging tactic use werepredicted based on a dynamic variance-sensitive producer�scrounger model (Barta and Giraldeau 2000). However,phenotype-dependent tactic use could also generate BMR-related differences in the use of scrounger, if BMR iscorrelated with a phenotypic trait that influences tactic use.In order to test whether BMR-related differences in tacticuse were due to variance-sensitive foraging, foraging trialswere conducted under both high and low food abundance.Phenotype-dependent tactic use decisions may or may notbe affected by food treatment. In contrast, variance-sensitiveforagers should show higher use of the scrounger tactic withdecreasing food abundance, if lower food abundanceincreases the probability of energetic shortfall (Barta andGiraldeau 2000). Therefore, if food abundance does notinfluence the use of the scrounger tactic, we can concludethat variance-sensitive foraging decisions do not underlieany BMR-related differences in social foraging tactic use.

Methods

Study subjects

Zebra finches were maintained on a 12:12 h light:dark cycle(lights on from 06:00 to 18:00 h) at temperatures between22 and 248C in same-sex groups with ad libitum access towater at all times. Outside of experimental periods, thebirds were housed together in cages (113�61�90 cmhigh) with ad libitum access to vitamin-supplementedcommercial millet seed mixture.

BMR measurements

Between March and April 2007, we obtained measures ofthe BMR of 28 female zebra finches. We used females onlyto avoid confounding sex and BMR, as female zebra fincheshave higher BMRs than males (Rønning et al. 2005). Birdswere taken from their holding aviaries and placed indivi-dually in the metabolic chambers at 18:00 h in the evening(the start of their resting phase). Measurements of O2

consumption were obtained over the 12 h resting phase,and the birds were removed from the chambers at 06:00 h.We recorded the mass (to 0.01 g) and crop contents(number of seeds visible in the crop, Zann and Straw1984) of birds both immediately before being placed in themetabolic chambers and immediately after being removedfrom the metabolic chambers.

BMR was measured as O2-consumption rates using atwo-channel open flow respirometry system. H20 and CO2

were removed from influent air using Drierite and sodalime, and the air was then pumped through two metabolicchambers made from 900 ml metal cylinders with airtightlids. The chambers were maintained at 35958C, which is

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Figure 1. Schematic representations of predictions from (a) static,and (b) dynamic variance-sensitive foraging models with respect toan individual’s expectation of energetic shortfall and the time ofday. Figure (b) is adapted from Barta and Giraldeau 2000. Notethat predictions for variance-prone or variance-averse behaviour donot imply absolute preferences in producer�scrounger foraging.

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within the thermoneutral zone of the zebra finch (Calder1964). A constant air-flow rate into the chambers of315 ml �min�1 was maintained using mass-flow controllers.The O2 concentration in effluent air streams (dried withDrierite) was measured using two O2 analyzers. Twoadditional streams of dry and CO2-free air were used tocalibrate analysers at 20.95% O2 (baseline). An automaticvalve switched between streams, so that 10 min of baselineO2 concentration were recorded for every 60 min measuredin the chambers. We allowed one minute delay betweenswitches in order to allow the system to wash outcompletely. Analog outputs from the O2 analyzers andthermocouple inside chambers were fed to a computer via a16-bit A/D converter card. Oxygen concentrations wererecorded at 6 s intervals.

The rate of O2 consumption (VO2) was calculated usingEq. 3a from Koteja (1996) without absorbing CO2 fromeffluent air prior to gas analysis as this minimizes error inthe conversion of O2 consumption to energy expenditurewhen the respiratory quotient is unknown. Birds with seedsremaining in their crops in the morning were excluded (n�3) from BMR estimates as they would not have attainedpost-absorptive status during the measurement period. Weused ExpeData to select and calculate the lowest 10 minaverage VO2, and this was used to represent the BMR. Bodymass at the time of BMR measurement was used tocalculate mass-specific BMR based on the assumption oflinear body mass loss between the two successive massmeasurements. In order to convert O2 consumption toenergy consumption, we used a respiratory quotient 0.8(Koteja 1996).

Foraging trials

Of the 25 birds from which we obtained useable BMRmeasurements, one was not used during foraging trialsbecause she began wing moult prior to experiments and hadvisibly reduced flying ability. We formed four flocks of sixbirds from the remaining 24 birds. Birds were categorizedaccording to their BMRs: the four individuals with thehighest BMRs were classified as ‘high’, the four individualswith the lowest BMRs were classified as ‘low’, and all otherbirds were classified as ‘intermediate’. We randomlyassigned birds to the four flocks with the constraint thateach group contain one high and one low BMR bird. Priorto the start of experiments, one bird died, reducing thegroup size of one flock to five. High and low BMR birdswere given colour leg flags to allow for individualidentification. In two flocks, high BMR individuals werebanded with red colour flags, and low BMR individualswere banded with yellow colour flags. The colour schemewas reversed for the other two flocks.

Foraging trials took place in May and June 2007 inindoor aviaries (1.5�3.8�2.3 m high). Each aviary con-tained two large perches and a foraging grid placed on tablesapproximately 90 cm above the aviary floor, which alloweda seated observer to videotape the birds through a one-waymirror using a 8 mm color camcorder mounted on a tripod.The foraging grid was covered by a sheet of black plastic atall times except during the foraging trials. The perches wereplaced at the far end of the aviary so that birds could not see

directly into the wells from the perches, but had to fly downto the foraging grid to search for food.

Birds were given two days to become familiar with theaviaries. Food was removed at 18:00 h on the evening of thesecond day, and each evening thereafter (evenings 2 through10). Trials commenced at 08:30 h the following mornings(day 3 through day 14), 2.5 h after lights on. Thus, thebirds were deprived of food for 14.5 h (12 h dark phase,plus 2.5 h the following morning) durations that werenecessary given that zebra finches store seeds in theirextensible crops for overnight use.

Foraging trials were conducted for 12 days (day 3 throughday 14) seven times per day at 1 h intervals. Each group wastested under two different food conditions: ‘high’ and ‘low’.During the high food condition, 10 white millet seeds wereplaced in each of 20 randomly selected wells. During the lowfood condition, 10 white millet seeds were placed in 10randomly selected wells for each trial. Following each trial,any remaining seeds or seed husks were removed from thegrid before placing seeds in the new randomly selected wells.The grid was covered with a sheet of black plastic until thestart of the next foraging trial, and birds typically rested onthe perches during the inter-trial interval. The quantity ofseeds available in the high and low food treatment wereselected based on pre-trials which showed that the high foodtreatment resulted in an approximately neutral energy budget(average mass loss: 0.1190.06 g, n�6), and the low foodtreatment resulted in a negative energy budget (average massloss: 0.5590.06 g, n�6).

In order to keep patch encounter rate similar betweenthe two food conditions, the size of the foraging gridsdiffered between food treatments. Although this would alterthe density of birds on the foraging grids, neither variance-sensitive nor rate maximizing producer�scrounger modelspredict any effect of group density on the frequency ofproducer-scrounger foraging alternatives (Caraco andGiraldeau 1991, Vickery et al. 1991). Furthermore, unlikemany other animals, zebra finches are very tolerant ofconspecifics in close proximity to themselves, and do notshow increased aggression with increased proximity ofconspecifics (Caryl 1975).

During the high food treatment, the foraging gridconsisted of two side-by-side plywood boards with acombined dimension of 2.0�1.2 m, in which there was atotal of 198 wells. In the low food condition, the foraginggrid was made up of a single plywood board withdimensions of 1.0�1.2 m and a total of 99 wells. Forboth sets of foraging grids, wells were 1.3 cm in diameter,0.8 cm deep, and spaced at 10 cm intervals. The order inwhich groups received the food treatments was randomized,with two groups receiving the high food treatment first, andtwo groups receiving the low food treatment first.

The first three days of foraging trials were used to trainthe birds on the seed distribution, and were not videotaped.The following three days of foraging trials were videotapedas the observer (KJM or SG) called out the location ofindividuals into the audio channel of the videotape recorderto facilitate the identification of the focal individual duringthe playbacks from which data were recorded. Videos wereanalyzed by a single observer (KJM). Following the finalforaging trial for a given food abundance treatment,foraging grids were set up for the next food distribution

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(a grid was either removed or added to the aviary). Again,the first three days under the new food treatment served astraining on the seed distribution, followed by three days offilming.

Body mass was measured before (07:30 h) and after(14:30 h) foraging trials each day by placing the bird in apaper bag and weighing it on a digital balance to 0.01 g.These mass recordings allowed us to assess mass changeduring the foraging trials.

Video analysis

Data were recorded from video playbacks of trials playing at1/2 speed. Videos were observed in random sequence byKJM. Because colour bands were reversed for half of thegroups (high BMR individuals were banded yellow and lowBMR individuals banded red in two groups, and vice versafor the other two groups), the BMR status of the individualcould not be inferred based on the colour of its leg bandswhen coding videos. Behavioural observations were madefor both the high and low BMR bird in each group for eachforaging trial. In ground feeding birds, individuals hop withthe head oriented downwards when producing, and withthe head oriented upwards while scrounging (Coolen et al.2001). Therefore, we recorded the following behaviours:hop with head up (imaginary line from the eyes through thenares is at or above horizontal), hop with head down(imaginary line is below the horizontal), produce patch(first to feed at patch), scrounge patch (feeding from a patchwhere ]1 other bird is feeding), and off the grid. For thehigh food condition, half of the total available patches werediscovered within approximately 60 s, whereas this occurredin the first 30 s for the low food condition. We thereforerestricted behavioural observations to the first 60 s and thefirst 30 s of video playbacks for the ‘high’ and ‘low’ foodabundance treatments respectively.

Producer�scrounger models predict relative use of thealternative foraging tactics (producer and scrounger) ratherthan absolute use of these tactics (Caraco 1981, Vickeryet al. 1991, Barta and Giraldeau 2000). Therefore, for eachtrial we calculated proportion of hops with the head up(hops with head up/[hops with head up�hops with headdown]) as an index of scrounger use. Because there wererelatively few patch finding and patch joining events perindividual within trials, we calculated the proportion ofpatches scrounged (no. patches scrounged/[no. patchesproduced�no. patches scrounged]) over all trials in a day.

Statistical analyses

All statistical analyses were carried out using R v.2.6.1 (RDevelopment Core Team 2007 /<http://www.R-project.org/>). BMR values (in Jh�1g�1) for the three categories ofbirds (‘high’, ‘intermediate’ and ‘low’) were compared usingan ANOVA with ‘BMR’ as a fixed factor. Tukey HSD tests(‘stats’ library) were used to make comparisons between pairsof BMR levels.

The effective sample sizes in our experiments were small,with BMR and food abundance treatments being carriedout in only four flocks. Furthermore, the large number ofrepeated observations made within flocks for a given set of

conditions meant that there was significant pseudo-replica-tion in our data set. Therefore, we used linear mixed-effectsmodels (LMEs) to analyze both mass and behavioural data.LMEs provide estimates of the influence of fixed effects onthe mean as well as the influence of random effects on thevariance, thereby accounting for the non-independence oferrors resulting from the repeated measures within flocks(Pinheiro and Bates 2000).

LMEs were constructed using the ‘lme’ function of the‘nlme’ package in R. We calculated the change in mass duringthe foraging trials by subtracting the mass values recorded at14:30 h from mass values recorded at 07:30 h. We testedwhether mass change varied as a function of ‘BMR’ or ‘foodabundance’ by including ‘BMR’ (high or low), ‘foodabundance’ (high or low), and their interactions as fixedeffects in the model, and flock, id within flock, and daywithin id within flock as random effects (�1j flock/id/day).

For analyses of behavioural data (proportion of hopswith head up, and proportion of patches joined), BMR(high or low), food abundance (high or low), and theirinteraction were included as fixed effects in the models.Flock, id nested within flock, and trial nested within idnested within flock, were included as a random effects(random��1jflock/id/trial) in the model for proportionof hops with head up. Flock, id nested within flock, and daynested within id nested within flock, were included as arandom effects (random��1jflock/id/day) in the modelfor proportion of patches joined.

Prior to analyses, proportion data were arcsine squareroot transformed to meet assumptions of normality andlinearity (Zar 1999). We checked residuals for violations ofmodel assumptions by visual inspection of residuals versusfitted values plots. Significance was set at pB0.05 and non-significant interactions were removed from the models.Values presented are means9SE.

Results

BMR

Summary statistics for three representations of BMR(ml O2 h�1, ml O2 h�1 g�1 and J h�1 g�1) are providedin Table 1 in order to facilitate comparisons between themeasures obtained in our study with those obtained in otherstudies. Energy consumption (J h�1 g�1) differed signifi-cantly according to BMR category (F2,20�5.09,p�0.016). High BMR birds differed significantly fromboth intermediate and low BMR birds (Tukey HSD,q�2.53, pB0.05), by 17 and 23%, respectively. BMR ofintermediate and low BMR birds did not differ significantlyfrom one another (Tukey HSD, q�2.53, p�0.05).

Daily variation in body mass

In the LME for change in body mass, the BMR�Foodinteraction was significant (Table 2). High BMR birds lostmass throughout the foraging trials during the low foodabundance treatment, but gained mass during the high foodabundance treatment. Low BMR birds lost mass throughoutforaging trials during the low food abundance treatment,

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and maintained stable mass during the high food abundancetreatment (Fig. 2).

Foraging behaviour

The effect of BMR on the proportion of hops made withthe head up did not differ according to food treatment(BMR�Food: p �0.50). However, the proportion ofhops made with the head up was significantly affected by‘BMR’ (F1,3�12.03, p�0.040, Table 2, Fig. 3). HighBMR birds had a higher use of the scrounger tacticcompared with low BMR birds. There was no effect of‘Food’ on the proportion of hops made with the headoriented upwards (F1,167�2.70, p�0.10, Table 2).

The effect of BMR on the proportion of patches joineddid not vary according to food treatment (BMR�Food: p�0.50). Although individuals with higher BMRs tended tojoin a greater proportion of patches than low BMRindividuals, this effect just failed to reach conventionallevels of statistical significance (F1,3�7.92, p�0.067,Table 2, Fig. 4). Again, food abundance treatment didnot affect the proportion of patches joined (F1,39�1.35,p�0.25, Table 2).

Discussion

Dynamic variance-sensitive producer�scrounger foragingmodel predicts that increasing an individual’s expectationof energetic shortfall should result in an increased use of thevariance-averse tactic, scrounger, early in the foragingperiod (Barta and Giraldeau 2000). We tested for an effectof BMR on scrounging behaviour. We assumed that higherBMR equates with greater expectation of energy shortfall,all else being equal, because higher BMR is associated with

higher daily energy requirements (Vezina et al. 2006).Individuals with high BMRs did have a greater use of thescrounger tactic compared with individuals with low BMRs.These results match qualitative predictions from Barta andGiraldeau’s (2000) dynamic variance-sensitive social fora-ging model. However, birds did not adjust their use ofproducer and scrounger tactics when foraging at twodifferent levels of food abundance, as would also havebeen expected in a dynamic variance-sensitive foraginggame (Barta and Giraldeau 2000) and so variance-sensitiveforaging cannot account for the birds’ behaviour.

We observed a significant effect of BMR on scroungerinvestment but we did not detect a significant effect ofBMR on the proportion of patches joined. Nonetheless, thedirection of the trends observed in the proportion ofpatches joined with respect to BMR level are the same asfor proportion of hops with the head up. High BMR birdstended to join a greater proportion of patches than lowBMR birds, with the exception of one low BMR individualwhich did not conform to this pattern in the low foodtreatment. Removal of this individual from the analysisresulted in a significant effect of BMR on the proportion ofpatches joined in both high (F1,2�34.63, p�0.03) andlow (F1,2�26.12, p�0.04) food treatments. The findingthat high BMR individuals had greater use of the scroungerforaging tactic (proportion of hops with head up) is similarto those reported for house sparrows Passer domesticus,which increased their use of scrounger when their energeticrequirement was experimentally manipulated using fans toincrease their overnight energy loss (Lendvai et al. 2004,2006).

The patterns of mass change across food treatmentsindicate that the probability of energetic shortfall wasgreater in the low food abundance treatment. However,individuals did not adjust their use of the scrounger tacticaccording to food abundance. Thus, given that the focal

Table 1. Mass-dependent and mass-specific basal metabolic rate (BMR) expressed as oxygen consumption and energy expenditure of femalezebra finches according to their classification into low, intermediate, and high categories. Values presented are means91 SE. Sample sizesare indicated in parentheses.

Low BMR (4) Intermediate BMR (15) High BMR (4) Overall (23)

ml O2 h�1 36.7991.46 39.9790.75 49.1591.46 41.0191.02ml O2 h�1 g�1 2.6990.19 2.8990.10 3.4990.19 2.9690.09J h�1 g�1 54.2193.83 58.1891.98 70.2193.83 59.5891.87

Table 2. Linear mixed-effects model for (A) daily patterns of mass change, (B) proportion of hops with the head up, and (C) proportion ofpatches joined in female zebra finches. The models includes the following random effects: flock, id nested within flock, and day (or trial)nested within id nested within flock

Source of variation num DF den DF F-value p-value

A. Daily patterns of mass changeBMR 1 3 25.78 0.015Food 1 22 194.75 B0.0001BMR�Food 1 22 17.41 0.0004

B. Arcsine square root (proportion of hops with head up)BMR 1 3 �3.47 0.04Food 1 167 �1.64 0.10

C. Arcsine square root (proportion of patches joined)BMR 1 3 �2.81 0.067Food 1 39 �1.16 0.25

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individuals were insensitive to the large differences in theprobability of energetic shortfall between the two foodabundance treatments, variance-sensitivity is not likely tounderlie the observed BMR-related differences in tactic use.However, the correlation between foraging behaviour andBMR observed in this study is robust, and provides the firstdemonstration that variation in BMR within a species isassociated with differences in foraging behaviour.

The mechanism underlying the correlation betweenforaging behaviour and BMR remains to be examined.However, we suggest that the use of producer and scroungerforaging tactics is phenotype-dependent, and the relation-ship between BMR and tactic use may arise because BMR is

correlated with another phenotypic character that influencestactic use decisions. Higher BMR may correlate with higherdominance rank (Buchanan et al. 2001), and dominancerank has been suggested as a possible factor mediatingproducer�scrounger foraging decisions (Barta and Giraldeau1998, Giraldeau and Beauchamp 1999). However, in zebrafinches, BMR is repeatable over periods of years (Rønninget al. 2005), while dominance rank is unstable over periods ofdays (Evans 1970, Caryl 1975). Furthermore, two previousstudies have failed to find any effect of dominance rank onproducer�scrounger tactic use in this species (Giraldeau et al.1990, Beauchamp 2006). We therefore suggest that it isunlikely that BMR-related differences in producer�scrounger foraging tactic use observed in this study reflectdominance-mediated foraging decisions.

An alternative possibility is that differences in BMRreflect differences in body composition (Daan et al. 1990,Scott et al. 1992), which in turn affect individuals’ ability touse producer and scrounger alternatives. Hopping rates aregreater when employing the scrounger tactic compared withthe producer tactic (Wu and Giraldeau 2004). Rapidmovement while scrounging may be beneficial, becausethe sooner a scrounger arrives at the patch, the more foodthere will be remaining for it to share in eating. Individualsthat are able to power more rapid movement should receivegreater payoffs when playing the scrounger tactic comparedwith individuals that are not able to do so. Rapid movementwould presumably require more muscle, and muscle is ahighly metabolically active tissue (Scott et al. 1992). Thus,relatively greater amounts of muscle for a given body masscould at once increase an individual’s mass specific BMRand their ability to play scrounger. Differences in musclemass have also been suggested to underlie inter-specificdifferences in BMR and foraging behaviour in two orders ofbirds. Among both Caprimulgiformes (McNab andBonaccorso 1995) and Falconiformes (Wasser 1986),species using foraging modes that require greater musclepower also have higher BMRs. For example, birds of prey

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Figure 3. Investment in the scrounger tactic (proportion of hopsmade with the head oriented upwards) according to basalmetabolic rate (BMR) and food abundance in female zebrafinches. Each symbol denotes a different flock. Lines connect highand low BMR individuals from the same flock under the samefood conditions. Note that the data presented are untransformed,while proportion data were arcsine square root transformed forstatistical analyses. Values presented are means91 SE.

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Figure 4. Proportion of patches joined according to basalmetabolic rate (BMR) and food abundance in female zebrafinches. Each symbol denotes a different flock. Lines connecthigh and low BMR individuals from the same flock under thesame food conditions. Note that the data presented are untrans-formed, while proportion data were arcsine square root trans-formed for statistical analyses. Values presented are means91 SE.

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Figure 2. Change in mass (g) during foraging trials (from 07:30 hto 14:15 h) as a function of food abundance treatment and basalmetabolic rate (BMR) in female zebra finches. Dashed lineindicates no mass change. Solid lines connect high and lowBMR individuals from the same flock under the same foodconditions. Each symbol denotes a different flock. Valuespresented are means91 SE.

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that use powered flight to catch prey have higher BMRsthan those which hunt primarily by soaring (Wasser 1986).

Phenotype-dependent tactic use decisions would accountfor the surprising patterns of mass change across foragingtrials. Both high and low BMR birds showed similar levelsof mass loss during the low food abundance treatment.However, high BMR birds gained mass in the high foodabundance treatment while low BMR birds maintainedstable mass. This indicates that high BMR individualsreceived greater payoffs than low BMR birds in the highfood abundance treatment. If the payoff to producer andscrounger foraging alternatives were strictly frequency-dependent, all individuals should receive equal payoffs atequilibrium (Vickery et al. 1991). However, if the payoffsto producer and scrounger are both frequency- andphenotype-dependent, then payoffs should be equal withinphenotypes, but not necessarily between phenotypes (Repkaand Gross 1995).

Earlier studies have demonstrated that inter-specificdifferences in BMR correlate with differences in foragingbehaviour (McNab 2002). However, this study is the firstto report that variation in BMR within a species isassociated with differences in foraging behaviour. Althoughthe reason for BMR-related differences in scrounger tacticuse is unresolved, the correlation between BMR andscrounger tactic use does not seem to be driven byvariance-sensitive foraging decisions. The results are con-sistent with the notion that allocation decisions toproducer�scrounger tactics are phenotype-dependent.Other phenotypic constraints on tactic use have beenidentified for producer�scrounger foraging, including levelsof energy reserves (Wu and Giraldeau 2004, Lendvai et al.2006), dominance status (Liker and Barta 2002, Lendvaiet al. 2006), foraging efficiency (Beauchamp 2006), andindividual vulnerability to predation (Mathot and Giral-deau 2008). Our results suggest that an aspect of pheno-type, which covaries with BMR, may also be influencingtactic use decisions in female zebra finches.

Acknowledgements � These experiments conform to guidelines ofthe Canadian Council for Animal Care and were approved by theUniv. Animal Care Committee (0307-571-0208). We thank JoeNocera and Julien Martin for statistical advice. This research wassupported by an NSERC Discovery Grant to L.-A.G. KJM wasfinancially supported by a Natural Sciences and EngineeringResearch Council (Canada) scholarship.

References

Barnard, C. J. and Sibly, R. M. 1981. Producers and scroungers: ageneral model and its application to captive flocks of housesparrows. � Anim. Behav. 29: 543�550.

Barta, Z. and Giraldeau, L.-A. 1998. The effect of dominancehierarchy on the use of alternative foraging tactics: aphenotype-limited producing-scrounging game. � Behav.Ecol. Sociobiol. 42: 217�223.

Barta, Z. and Giraldeau, L.-A. 2000. Daily patterns of optimalproducer and scrounger use under predation hazard: a state-dependent dynamic game analysis. � Am. Nat. 155: 570�582.

Bateson, M. and Kacelnik, A. 1998. Risk-sensitive foraging:decision making in variable environments. � In: Dukas, R.(ed.), Cognitive ecology. Chicago Univ. Press, pp. 297�341.

Beauchamp, G. 2006. Phenotypic correlates of scroungingbehavior in zebra finches: role of foraging efficiency anddominance. � Ethology 112: 873�878.

Bech, C. et al. 1999. Repeatability of basal metabolism in breedingkittiwakes Rissa tridactyla. � Proc. R. Soc. Lond. B 266:2161�2167.

Buchanan, K. L. et al. 2001. Testosterone influences basalmetabolic rate in male house sparrows: a new cost ofdominance signalling? � Proc. R. Soc. Lond. B 268:1337�1344.

Calder, W. A. 1964. Gaseous metabolism and water relations ofthe zebra finch, Taeniopygia castanotis. � Physiol. Zool. 37:400�413.

Caraco, T. 1981. Risk-sensitivity and foraging groups. � Ecology62: 527�531.

Caryl, P. G. 1975. Aggressive behaviour in the zebra finchTaeniopygia guttata I. Fighting provoked by male and femalesocial partners. � Behaviour 52: 226�252.

Coolen, I. et al. 2001. Head position as an indicator of producerand scrounger tactics in a ground-feeding bird. � Anim. Behav.61: 895�903.

Daan, S. et al. 1990. Avian basal metabolic rates: their associationwith body composition and energy expenditure. � Am. J.Physiol. Regulatory Integr. Compar. Physiol. 259: 333�340.

Evans, S. M. 1970. Aggressive and territorial behaviour in captivezebra finches. � Bird Study 17: 28�35.

Giraldeau, L.-A. and Beauchamp, G. 1999. Food exploitation:searching for the optimal joining policy. � Trends Ecol. Evol.14: 102�106.

Giraldeau, L. A. and Caraco, T. 2000. An introduction toproducer-scrounger games. � In: Krebs, J. R. and Clutton-Brock, T. H. (eds), Social foraging theory. Princeton Univ.Press, pp. 151�173.

Giraldeau, L. A. et al. 1990. The payoffs to producing andscrounging: what happens when patches are divisible?� Ethology 85: 132�146.

Horak, P. et al. 2002. Repeatability of condition indices in captivegreenfinches (Carduelis chloris). � Can. J. Zool. 80: 636�643.

Houston, A. I. and McNamara, J. M. 1999. Models of adaptivebehaviour: an approach based on state. � Cambridge Univ.Press.

Kacelnik, A. and Bateson, M. 1996. Risky theories: the effects ofvariance on foraging decisions. � Am. Zool. 36: 402�434.

Koteja, P. 1996. Measuring energy metabolism with open-flowrespirometric systems: which design to choose? � Funct. Ecol.10: 675�677.

Labocha, M. K. et al. 2004. Individual variation and repeatabilityof basal metabolismin the bank vole, Clethrionomys glareolus.� Proc. R. Soc. Lond. B 271: 367�372.

Lendvai, A. Z. et al. 2004. The effect of energy reserves on socialforaging: hungry sparrows scrounge more. � Proc. R. Soc.Lond. B 271: 2467�2472.

Lendvai, A. Z. et al. 2006. The effects of energy reserves anddominance on the use of social-foraging strategies in the housesparrow. � Anim. Behav. 72: 747�752.

Liker, A. and Barta, Z. 2002. The effects of dominance on socialforaging tactic use in house sparrows. � Behaviour 139:1061�1076.

Lima, S. L. and Dill, L. M. 1990. Behavioral decisions made underthe risk of predation: a review and prospectus. � Can. J. Zool.68: 619�640.

Mathot, K. J. and Giraldeau, L.-A. 2008. Increasing vulnerabilityto predation increases preference for the scrounger foragingtactic. � Behav. Ecol. 19: 131�138.

McNab, B. K. 1997. On the utility of uniformity in the definitionof basal metabolic rate. � Physiol. Zool. 70: 718�720.

551

McNab, B. K. 2002. The physiological ecology of vertebrates: aview from energetics. � Cornell Univ. Press.

McNab, B. K. and Bonaccorso, F. J. 1995. The energetics ofAustralasian swifts, frogmouths and nightjars. � Physiol. Zool.68: 245�261.

Mottley, K. and Giraldeau, L.-A. 2000. Experimental evidencethat group foragers can converge on predicted producer�scrounger equilibria. � Anim. Behav. 60: 341�350.

Pinheiro, J. C. and Bates, D. M. 2000. Mixed-effects models in Sand S-PLUS. � Springer.

Repka, J. and Gross, M. R. 1995. The evolutionarily stablestrategy under individual condition and tactic frequency. � J.Theor. Biol. 176: 27�31.

Ricklefs, R. E. 1996. Avian energetics, ecology and evolution. � In:Carey, C. (ed.), Avian energetics and nutritional ecology.Chapman and Hall, pp. 1�30.

Rønning, B. et al. 2005. Long-term repeatability makes basalmetabolic rate a likely heritable trait in the zebra finchTaeniopygia guttata. � J. Exp. Biol. 208: 4663�4669.

Rønning, B. et al. 2007. Basal metabolic rate: heritability andgenetic correlations with morphological traits in the zebrafinch. � J. Evol. Biol. 20: 1815�1822.

Scott, I. et al. 1992. The metabolic output of avian (Sturnusvulgaris, Calidris alpina) adipose tissue, liver and skeletalmuscle: implications for BMR/body mass relationships.� Comp. Biochem. Physiol. 103A: 329�332.

Speakman, J. R. et al. 2006. The functional significance ofindividual variation in basal metabolic rate. � Physiol.Biochem. Zool. 77: 900�915.

Stephens, D. W. 1981. The logic of risk-sensitive foragingpreferences. � Anim. Behav. 29: 628�629.

Stephens, D. W. and Krebs, J. R. 1986. Foraging theory.� Princeton Univ. Press.

Turpie, J. K. and Hockey, P. A. R. 1993. Comparative diurnal andnocturnal foraging behaviour and energy intake of premigra-tory grey plovers Pluvialis squatarola and whimbrels Numeniusphaeopus in South Africa. � Ibis 135: 156�165.

Vezina, F. et al. 2006. Individually variable energy managementstrategies in relation to energetic costs of egg production.� Ecology 87: 2447�2458.

Vickery, W. L. et al. 1991. Producers, scroungers, and groupforaging. � Am. Nat. 137: 847�863.

Wasser, J. S. 1986. The relationship of energetics of faconiformbirds to body mass and climate. � Condor 88: 57�62.

Wu, G.-M. and Giraldeau, L.-A. 2004. Risky decisions: a test ofrisk sensitivity in socially foraging flocks of Lonchura punctu-lata. � Behav. Ecol. 16: 8�14.

Zann, R. A. 1996. The zebra finch: a synthesis of field andlaboratory studies. � Oxford Univ. Press.

Zann, R. and Straw, B. 1984. Feeding ecology and breeding ofzebra finches in farmland in northern Victoria. � Aust.Wildlife Res. 11: 533�552.

Zar, J. H. 1999. Biostatistical analysis. � Prentice Hall.

552