Behavioral Ecologydoi:10.1093/beheco/arq032

Advance Access publication 15 March 2010

Determinants of false alarms in staging flocks ofsemipalmated sandpipers

Guy BeauchampFaculty of Veterinary Medicine, University of Montreal, PO Box 5000, St-Hyacinthe, Quebec, CanadaJ2S 7C6

False alarms occur when animals flee abruptly upon detection of a threat that subsequently proved harmless. False alarms arecommon in many species of birds and mammals and account for a surprisingly high proportion of all alarms. False alarms areexpected to be more frequent in larger groups, where the odds of misclassifying threats are higher, and under environmentalconditions where detection of threats is compromised, such as low light levels. In addition, false alarms should be less frequentwhen the energetic cost of fleeing increases. I examined these hypotheses in roosting flocks of staging semipalmated sandpipers(Calidris pusilla) over 2 years. False alarms increased with group size but the effect of group size was confounded by the fact thatmore attacks by falcons (Falco spp.) were directed at larger roosts. False alarms were more frequent at low light levels and laterduring staging. As individuals double their body mass during staging, the energetic cost of fleeing must greatly increase thuscontributing to decreased responsiveness. A simple reduction in responsiveness caused by repeated exposures to harmless signalswould also produce a temporal decrease in responsiveness but this hypothesis cannot account for the effect of group size andlight level. Study of the determinants of false alarms provides an opportunity to examine adjustments in behavior in relation tochanges in perceived predation risk. Key words: false alarm, group size, predation risk, roosting, semipalmated sandpiper,stopover ecology. [Behav Ecol 21:584–587 (2010)]

Animals often interrupt their activities and flee to coverupon detecting potential threats. Such threats, however,

often prove harmless and much time is thus spent fleeing atthe expense of fitness-enhancing activities such as feeding.False alarms are a common feature in many species of birdsand mammals and account for a surprisingly large proportionof alarms in some species (Hoogland 1981; Cresswell et al.2000; Blumstein et al. 2004; Kahlert 2006). It is thought thata high level of responsiveness to potential threats is a low-coststrategy that reduces the likelihood of not respondingappropriately when a real attack does occur, the ‘‘better-safe-than-sorry’’ principle.For a single individual, the appropriate level of responsive-

ness should depend on the costs and benefits of responding ornot responding to potential threats whether they prove real orharmless. The costs of responding include the energetic costsimposed by fleeing and the foregone returns from any cur-tailed activity. Not responding upon detection of a potentialthreat allows foragers to avoid these costs but at the risk of hav-ing to deal with a real predator. Not responding is also moredangerous if threat detection is hampered. This can occurwhen detection conditions are not ideal, for instance at lowlight levels (Lima 1988), or in the presence of visual obstruc-tion (Guillemain et al. 2001), or if harmless and real threatsshare many features, making discrimination more difficult.In a group, individuals can rely on their own detection as

described above but can also react to the responses of compan-ions (Pulliam 1973). When relying on detection by compan-ions, it is not always obvious to decide whether departures arecaused by a real alarm or are due to nonthreatening factors,such as satiation for instance (Lima 1995). However, given

that multiple, simultaneous departures are more likely to rep-resent independent responses to a real threat, individuals ingroups that have not detected the threat by themselves couldrely on these multiple departures to take appropriate action(Lima 1994; Proctor et al. 2001; Beauchamp and Ruxton2007b). Although the risk of not detecting a potential threatis certainly lower in a group because many more eyes arescanning the surroundings, false alarms can still occur ina group given that the first few detectors are still relying ontheir own potentially biased assessment of threats and non-detectors rely on this potentially biased information. In fact,given that there are more potential detectors in a group, onewould predict that false alarms should actually increase withgroup size because the odds of misclassifying a threat, at thelevel of the group, increase with the number of independentassessments of a potential threat (Treisman 1975). Notresponding in a group is also costly because individuals thatare left behind following the departure of companions may bemore at risk of attack by predators (Quinn and Cresswell 2005;Beauchamp and Ruxton 2007a; Sirot and Touzalin 2009).Surprisingly, few studies have examined the determinants of

false alarms in animal groups. In a study of foraging redshanks(Tringa totanus), individuals were more likely to take flight inalarm on cloudy days and later in the overwintering season(Hilton et al. 1999). Clouds decrease light levels thus increas-ing the odds of misclassifying threats. Proneness to alarm laterin the season was interpreted as a low-risk strategy in birds thatare less likely to face starvation. In the same species, the ratioof false alarms to real attacks decreased with the number ofreal attacks and on rainy days as both are expected to increaseperceived predation risk. The effect of group size was notinvestigated in this system.One difficulty with an analysis of false alarms in foraging ani-

mals is that the foregone returns from interrupting foragingare not negligible. Therefore, factors affecting the value of for-aging are likely to influence the choice to respond or not topotential threats making it more difficult to compare false

Address correspondence to G. Beauchamp. E-mail: guy.beauchamp@umontreal.ca.

Received 10 September 2009; revised 17 December 2009; accepted12 February 2010.

� The Author 2010. Published by Oxford University Press on behalf ofthe International Society for Behavioral Ecology. All rights reserved.For permissions, please e-mail: journals.permissions@oxfordjournals.org

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alarms across conditions. A further difficulty is that false alarmsin a foraging context may be used deceptively by individuals tousurp resources from others or to increase access to food(Møller 1988; Kahlert 2006; Wheeler 2009). Here, I proposean analysis of false alarms in resting animals where the onlycost of responding to a potential threat is the energetic cost offleeing. Deceptive use of alarm signals is unlikely in animalsthat are not competing for any resources but simply resting. Iexamine false alarms in staging semipalmated sandpiper(Calidris pusilla) flocks roosting on the shore at high tide. Inparticular, I examined the hypothesis that false alarms shouldbe more frequent in larger groups and under environmentalconditions that increase perceived predation risk, such as lowlight levels. Sandpipers double their body mass during fallstaging (Hicklin 1987). This large increase in body mass willundoubtedly increase the energetic cost of flying and I pre-dicted that false alarms should occur less often with length ofstay in the staging area.

MATERIALS AND METHODS

Data collection

The study was conducted from 28 July to 13 August in 2008 and2009 at Daniel’s flats, New Brunswick, Canada (lat 45.73� N,long 64.65� W). Daniel’s flats are located at the northernend of Chignecto Bay in the upper Bay of Fundy. Tides, aver-aging 11.5 m in height, expose mudflats twice daily in the area.Using a 203 60 scope, I monitored birds at a diurnal high-tideroost located on a pebbly beach approximately 100-m away.From my vantage point, I could easily count the number ofroosting birds and detect avian predators because I had an un-obstructed field of view around the roost.At the beginning of each focal observation, I counted the

number of birds either directly, when the roost was small, orusing local landmarks to determine the approximate size ofthe roost and then multiplying the area by 100 birds per m2

(Mawhinney et al. 1993). I also noted time of day, air temper-ature (�C), wind velocity (km/h), and light intensity (Lux)obtained from handheld devices. I also noted the occurrenceof rain. Roosting birds frequently left the roost in alarm andreturned some time later at the same location. For eachalarm, I recorded the time when birds departed and returnedto the roost and assessed the cause of each alarm. Alarms werecharacterized as real when an attack by an avian predator(mostly Falco peregrinus and Falco columbarius but occasionallyCircus cyaneus) took place. When I could not detect the pres-ence of a predator following an alarm, I classified the alarm asfalse. I could not determine the exact cause of false alarms inroosting flocks.A focal observation ended when roost size changed due to

the arrival or departure of companions or when the birdsstarted feeding. A new focal observation started on the sameday if the newly formed flock subsequently reconvened to roostat the same site. Changes in roost size in subsequent focal obser-vations on any given day were substantial with up to 10-foldchanges in size. There were from 1 to 4 focal observations eachday but most days provided only one focal observation.

Statistical analysis

For each focal observation, I calculated the cumulative timespent in the roost (excluding flight duration). I used a negativebinomial regressionmodel to examine the determinants of thehighly rightly skewed number of false alarms during each focalobservation. The cumulative time spent in the roost during a fo-cal observation was used as an offset to control for differentduration of stay by the birds at the roost. By including focal

observation duration in the model and forcing the parameterestimate to be equal to one, which is what the offset does, it istherefore possible to compare the number of false alarms evenwhen focal observations differ in duration. The independentvariables included year (2008 vs. 2009), stopover phenology(early vs. late), log10 of roost size, the occurrence of rain, windvelocity, air temperature, light intensity, and number of realalarms. The final model was obtained through sequential re-moval of nonsignificant variables. Using information aboutroost size at this and other sites in the Bay, I classified focalobservations as occurring early in staging (up to the 7th ofAugust, after peak arrival) or late. The proportion of birdsthat have doubled their mass since arrival is low early in stag-ing and higher later (Hicklin 1987).The prevalence of attacks by avian predators was examined

in relation to the previous independent variables in a logisticregression model. I used the prevalence of attacks, that iswhether or not a roost was attacked at all during the focal ob-servation on a given day, rather than the actual number ofattacks since repeated attacks on a given day at the same roostmay not be independent events. I used cumulative time spentin the roost as an offset.I compared the number of false alarms at the same roost in

the first and in the last 10 min of roosting for all focal obser-vations that lasted more than 20 min. I divided the number offalse alarms by the cumulative time spent roosting ineach period to calculate false alarm rate. I compared earlyand late false alarm rates for matched data using a paired t-test.

RESULTS

Roosts formed at the same location each day shortly after hightide. Undisturbed birds started to leave the roost about 2-hlater to start feeding. Overall, attacks on roosting birds, primar-ily by falcons, occurred every other day and up to 4 attacksoccurred on any given day. Median focal observation durationwas around 15 min in 2008 and 30 min in 2009 (Table 1).Roost sizes varied from 25 to 15 000. Approximately one falsealarm took place for every minute spent roosting (range 0–4),and there were generally 5 false alarms for every real alarm(Table 1). All birds left the roost during an alarm. After a falsealarm, birds returned to the roost about 30-s later. Birdsoften abandoned the roost for the day after an attack. De-scriptive statistics for the independent variables are presentedin Table 1 for each year.

Table 1

Median (range) of the various independent variables measured inthe 2 study years at Daniel’s flats, New Brunswick, Canada

Variable 2008 2009

Number of focalobservations

20 19

Number of falconattacks per minuteroosting

0 (0–0.37) 0.01 (0–1.52)

Ratio false to realalarma

4.5:1 6.75:1

Log group size 3.24 (1.53–4.18) 2.48 (1.40–4)Wind velocity (km/h) 4.9 (0–18) 11.3 (2.9–18.5)Temperature (�C) 18.9 (16.5–22) 21.3 (12.7–22.8)Light level (Lux) 10 000 (4000–18 000) 20 000 (4400–20 000)Focal observationduration (s)

978 (205–2140) 1710 (375–6600)

a Calculated only when an attack took place (n ¼ 7 in 2008 and n ¼ 10in 2009).

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In the final negative binomial regression model, controllingfor focal observation duration, the number of false alarms wasstatistically significantly lower in 2009 than in 2008, increasedwith group size, decreased with light intensity, and decreasedlater during staging (Table 2). The effect of group size differedbetween the 2 years of study and was absent in 2008 (Table 2).No other interactions were detected (P. 0.34) indicating thatthe effect of light intensity was similar in the 2 years of studyand that the effect of group size and light intensity was similarearly and late in staging. The number of false alarms was notrelated to temperature (b [standard error {SE}]¼20.11 [0.09],P ¼ 0.19), wind velocity (b [SE] ¼ 0.02 [0.03], P ¼ 0.55), theoccurrence of rain (b [SE] ¼ 20.28 [0.39], P ¼ 0.48), and thenumber of attacks (b [SE] ¼ 0.28 [0.17], P ¼ 0.11).

The odds of attacks increased by a factor of 3.1 for each unitincrease in log group size (b [SE]¼ 1.15 [0.53], P¼ 0.03). Thiseffect was independent of year and staging phenology.None of the other independent variables reached statisticalsignificance.The number of false alarms per min spent roosting did not

differ statistically between the first 10 min of the beach(median [range]: 0.59 [0–2.5]) and the last 10 min (0.43[0–2.9]; t ¼ 20.47, P ¼ 0.64, n ¼ 18).

DISCUSSION

Despite a relatively low frequency of attacks by avian preda-tors, staging semipalmated sandpipers interrupted roostingand flew in alarm frequently. Most of these alarms turnedout to be false in the sense that no real danger was actuallypresent. False alarms were more frequent in larger roosts,at low light intensity, and earlier in staging. I discuss theseresults in turn.The positive effect of group size on false alarm rate appears

at first to confirm the hypothesis that in a large group whereindividuals share information about potential threat detection,the sudden departures of a few detectors is sufficient to triggerthe departure of all remaining birds. Given that at the levelof the group, the odds of misclassifying a signal increase withgroup size, false alarms were thus expected to be more fre-quent in larger groups. However, the effect of group size onlyoccurred in one of the 2 study years even though the range ofgroup sizes was similar between years. The nonsignificant effectof group size occurred in the year with the highest frequency offalse alarms suggesting that the effect of group size may havebeen trumped that year by a lower threshold for responding topotential threats. In other avian studies, false alarm rate

was not related to group size (Lindstrom 1989; Cresswellet al. 2000).A difficulty in the interpretation of the results is that larger

roosts also attracted more attacks. A similar finding was ob-served for foraging sandpipers (Beauchamp 2008; Spragueet al. 2008) and has also been documented in many otherspecies (e.g., Lindstrom 1989; Cresswell 1994; Guillemainet al. 2007). Models dealing with false alarms assume thatattack risk is independent of group size (Lima 1994; Proctoret al. 2001; Beauchamp and Ruxton 2007b). The results thussuggest that this assumption is not always met. If larger groupsare more at risk of attack, then more false alarms should beexpected in those groups even when sharing informationabout predation threats, which is also expected to increasefalse alarms in large groups (Giraldeau et al. 2002), doesnot take place. Therefore, future work is needed to tease apartthe effect of overall predation risk from the effect of groupsize on false alarms especially given that group size does notseem to have a consistent effect on false alarms in the speciesexamined thus far.Low light levels are thought to increase the odds of misclas-

sifying threats and therefore false alarms should be more fre-quent under these conditions. In staging semipalmatedsandpipers, false alarms did indeed increase at low light levels.Given that low light levels often occur early and late in the day,false alarms are thus probably most frequent at these times ofday. These results are compatible with the observation that for-aging sandpipers were more likely to leave a foraging patchabruptly early and late in the day, controlling for food density(Beauchamp and Ruxton 2008). Increased skittishness isprobably not a response to increased attack rate at low lightlevels given that there was no relationship between time ofday and frequency of attack by falcons on roosting birdsand more generally on foraging birds in the same area(Beauchamp 2008).As staging progresses, sandpipers double their body mass

over the 10–14 days individuals spend in the Bay during fallstaging. I found that false alarms were less common later dur-ing staging. The increased energetic cost of fleeing in fatterbirds should increase the response threshold to potentialthreats and thus lead to fewer false alarms. The prevalenceof attacks at the roost did not vary with staging phenology sug-gesting that predation risk did not vary to a large extent overthe course of staging and was not directly responsible fora change in the number of false alarms. Increased skittishnesshas been documented in 2 species after exposure to predatorattacks (Hilton et al. 1999; Martın et al. 2009) but in stagingsandpipers the number of false alarms was not related to theactual number of attacks.An alternative hypothesis can account for decreased respon-

siveness as staging progresses. Birds may learn to become lessresponsive to potential threats with increased exposure toharmless signals (Bouskila and Blumstein 1992; Edelaar andWright 2006). However, the learning hypothesis does notmake any prediction related to group size and to light inten-sity, 2 factors which have been found to influence the numberof false alarms in this species, and thus cannot explain all thepresent results. I found no effect of learning within days in thesense that false alarms did not vary with time spent roosting,but it may be the case that learning occurs between ratherthan within days. The fact that roosting birds are mainly adultsat this time of year (Hicklin 1987) also means that many of thesandpipers present at the roosts have been exposed to thepotential threats in the Bay at least once before thus makingthe learning hypothesis less relevant. A more direct test of thehypothesis would be to examine changes in false alarm rate inwintering birds as the season progresses. Given that overwin-tering birds need not accumulate fat until closer to migration

Table 2

Final negative binomial regression model of the number of falsealarms in staging flocks of semipalmated sandpipers controlling forfocal observation duration

Variable b (SE) P valueRelative change in thenumber of false alarms

Year 23.59 (1.59) 0.02 97% lower in 2009 than 2008Phenology 22.09 (0.44) ,0.0001 88% lower later than earlierGroup size 0.80 (0.24) 0.0007 123% higher per unit increase

in log10 of roost size

Group size in2008

0.08 (0.31) 0.79 9% higher per unit increasein log10 of roost size

Group size in2009

1.52 (0.41) 0.0002 357% higher per unit increasein log10 of roost size

Light level 22.08 (0.93) 0.03 88% lower per unit increasein Lux

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time, a reduction in false alarm rate between days would onlybe compatible with the learning hypothesis.In conclusion, staging semipalmated sandpipers adjust their

level of responsiveness to potential threats in a dynamic fashiondepending on the costs and benefits of responding or notresponding to environmental signals. Study of the determi-nants of false alarms thus provides an opportunity to examineadjustments in behavior in relation to changes in perceivedpredation risk.

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