Anim Cogn (2011) 14:809–816 DOI 10.1007/s10071-011-0414-5
ORIGINAL PAPER
Prey behaviour across antipredator adaptation types: how does growth trajectory influence learning of predators? Maud C. O. Ferrari • Grant E. Brown • Gary R. Bortolotti • Douglas P. Chivers
Received: 17 November 2010 / Revised: 22 April 2011 / Accepted: 28 April 2011 / Published online: 10 May 2011 Ó Springer-Verlag 2011
Abstract Despite the fact that the ability of animals to avoid being consumed by predators is influenced by their behaviour, morphology and life history, very few studies have attempted to integrate prey responses across these adaptation types. Here, our goal was to address the link between life-history traits (size and growth trajectory) of tadpoles and behavioural responses to predators. Specifically, we wanted to determine whether information learned about predators was influenced by prey growth trajectory before and after learning. We manipulated the size/growth trajectory of tadpoles by raising them under different temperatures. Tadpoles raised on a slow-growth trajectory (under cold conditions) and taught to recognize a salamander subsequently showed stronger responses after 2 weeks than tadpoles that were raised on a fast-growth trajectory (under warm conditions). When we account for the effect of size (r2 = 0.22) on the responses of prey to predator cues, we find that the growth trajectory prelearning but not post-learning influences the learned
M. C. O. Ferrari (&) Department of Environmental Science and Policy, University of California, Davis, CA 95616, USA e-mail:
[email protected] G. E. Brown Department of Biology, Concordia University, Montreal, QC H4B 1R6, Canada G. R. Bortolotti D. P. Chivers Department of Biology, University of Saskatchewan, Saskatoon, SK S7N 5E2, Canada Present Address: M. C. O. Ferrari Department of Biomedical Sciences, WCVM, University of Saskatchewan, Saskatoon, SK S7N 5B4, Canada
responses of the tadpoles. The differences in responses to predators may reflect differential memory associated with the predator. To our knowledge, this is the first study that has attempted to link life-history traits (size and growth rate) with learning of predators. In order to gain a comprehensive understanding of antipredator responses of prey animals, we call for additional integrative studies that examine prey antipredator responses across adaptation types. Keywords Learning Predator recognition Growth rate Antipredator behaviour Risk assessment Woodfrog
Introduction Prey species have been shown to respond to predation risk in a multitude of ways, including via altered behavioural, morphological or life-history patterns (Lima 1998a), although the vast majority of studies have focused on shortterm behavioural responses to immediate risk (Lima and Dill 1990). Short-term behavioural studies allow researchers to better understand the types of trade-offs affecting prey decision-making, specifically how factors, such as body size, hunger level, reproductive state or group size, affect the type and intensity of prey responses to risk (Bednekoff and Lima 1998; Lima 1998b; Lima and Dill 1990; Helfman 1989). Longer-term adaptations, such as predator-induced changes in morphology and life-history patterns also alter the probability of an individual being detected, attacked or captured by a predator, and as such should affect how prey respond to an immediate threat (Bronmark and Miner 1992; Harvell 1990). Unfortunately, life-history or morphological adaptations have been often studied independently of short-term behavioural responses
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(Bronmark and Miner 1992; Laurila et al. 2002), and very few studies have attempted to integrate prey antipredator responses across adaptation types. There are a few notable exceptions. These studies use a threat-sensitive predator avoidance framework, whereby prey exhibiting morphological traits that make them less vulnerable to capture will reduce the intensity of their behavioural responses. For instance, both DeWitt et al. (1999) and Hoverman et al. (2005) showed that snails with vulnerable shell morphologies displayed behavioural compensation when faced with a predation threat. Likewise, Chivers et al. (2007) examined the interaction between morphology and antipredator responses in goldfish. Goldfish exposed to predation risk significantly increased their body depth-to-length ratio, which gives them a survival advantage against gape-limited predators. Deep-bodied goldfish displayed a lower intensity of antipredator responses than shallow-bodied ones, consistent with the hypothesis that individuals with morphological defences exhibit less behavioural modification than those lacking such defences. Along these lines, a general framework of behavioural compensation was introduced by Lind and Cresswell (2005), predicting that individuals with higher energy reserves need not put themselves at a risk of predation through seeking highly rewarding foraging opportunities and hence would show lower intensity of antipredator responses. Here, we were interested in using the same threat-sensitive predator avoidance framework to assess the interaction between prey life history (specifically prey size and growth history) and behavioural responses. In particular, we were interested in knowing whether changes in prey size and growth history affected not only the intensity of behavioural responses to predator cues, but also the cognitive functions associated with predator recognition and risk assessment. In other words, could we find a link between size/growth history and predator-related encoding of information, such as predator information acquired through learning? Learning of predators has been a topic widely studied in aquatic systems (Chivers and Smith 1998; Ferrari et al. 2010b for reviews; Brown and Chivers 2005). From flatworms to larval amphibians, one effective way for aquatic species to acquire recognition of novel predators is the simultaneous pairing of predator cues (odour, sight or sound) with injured conspecific cues (Ferrari et al. 2010b for a review). This mode of learning allows for sophisticated, fine-tuned information about predators, such as recognition of the predator identity (Chivers and Smith 1993), the risk level associated with the predator (Ferrari et al. 2005), and the time at which the predator is most dangerous (Ferrari and Chivers 2009b). Each piece of information learned about the predator is weighted through time to provide prey with an up-to-date but often conservative estimate of the risk posed by the predator (Ferrari
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and Chivers 2006, 2009b; Bouskila and Blumstein 1992). It is often difficult to understand factors that may affect learned predator recognition, in part because of the difficulties associated with distinguishing the effects of learning (what type of information was encoded) from the context-dependent responses (state-dependent variables that affect decision-making in the short term). For example, hungry individuals may not behaviourally respond to novel predator cues paired with alarm cues, but they still acquire recognition of predator cues through this pairing, as evident by the fact that they subsequently respond to predator cues when they are satiated (Brown and Smith 1996). Hence, the differences in response to predators may not be due to a failure in recognition, but rather a hunger-induced shift towards maximizing foraging at the cost of predator avoidance. The goal of this experiment was to investigate whether and how changes in life history (size and growth history) would influence the ability of prey to respond to predators that they recently learned as dangerous. We used temperature to mediate differences in growth rate in woodfrog tadpoles, Rana sylvatica, and obtain tadpoles on a fast- or slow-growth trajectory. The tadpoles were then conditioned to recognize a novel predator, a tiger salamander Ambystoma tigrinum, via pairing with injured conspecific cues. Woodfrog tadpoles have been shown to successfully learn the identity and the risk associated with novel predator through this mode of learning (Ferrari et al. 2008, 2009; Ferrari and Chivers 2009b). After conditioning, we maintained or switched the growth trajectory of the tadpoles, so that we could assess the effects of growth trajectory before and after learning on the responses of tadpoles. The tadpoles were then tested for their responses to injured conspecific cues (general risk cue—positive control), water (negative control) or salamander odour. We predicted that growth rate should not affect the responses of tadpoles to injured conspecific cues, since these cues provide information on a non-specific threat and should elicit antipredator responses independently of experience or size. We also predicted that individuals on a faster growth trajectory would learn to recognize the salamander as a lower-risk threat as compared to individuals on a slow-growth trajectory. This prediction stems from the assumption that faster growing individuals will outgrow their predators sooner than slowgrowing individuals, hence making them overall less susceptible to predation risk in the future. An obvious caveat resulting from our growth rate manipulation is that tadpoles from different treatments would differ in size, and any differences in response to the predator could be due to a simple cost-benefits trade-off, whereby bigger individuals respond less to a predator because of decreased vulnerability (Helfman 1989). To test the effects of pre- and post-learning growth trajectory on the learned response independently of size, we statistically removed the size effect and determined the effect of
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pre- and post-learning growth trajectory on the variation in behavioural responses to the predator when the ‘overall size’ effect was accounted for.
Methods Water, predators and test species Four weeks prior to starting the experiment, a 1,900-L tub was filled with well water and seeded with zooplankton, phytoplankton and aquatic plants using a fine mesh dip net. This was done to ensure that our holding and test water did not contain any cues from salamanders. Tiger salamanders occur in the region of our field site in central Alberta, Canada, but our research from the past 4 years indicates that no salamanders inhabit our study pond and that woodfrog tadpoles do not show any innate recognition of salamander cues (Ferrari et al. 2009; Ferrari and Chivers 2009a). This water is hereafter referred to as well water. Three tiger salamanders (snout-vent length: mean ± SD = 9.1 ± 0.4 cm) were caught from a pond on the University of Saskatchewan campus in April 2009 using Gee’s Improved minnow traps. The three salamanders were kept in a plastic tub containing 30 L of well water and fed earthworms every 2 days. Woodfrog egg clutches were collected in early May 2009 from a pond in central Alberta. Six clutches laid the same night were transferred into a plastic pool filled with pond water and left floating on the pond to equalize the temperatures of the water in the pool and pond. After hatching, the tadpoles were provided with rabbit chow to supplement the algae already present in the pool. The tadpoles were raised for 2 weeks before being used. Stimulus preparation Salamander odour was obtained from soaking one salamander in 2 L of well water for 24 h, and the salamanderconditioned water was then frozen in 200-mL aliquots. Odours were made from all three salamanders, and the odours from the three animals were randomly used throughout the experiment. The stimulus was thawed and brought to ambient temperature prior to being used. The injured conspecific cue solution used in the conditioning trials was prepared a few minutes prior to being used, by sacrificing and crushing 96 tadpoles with a mortar and pestle in 240 mL of well water. Experimental design The experiment consisted of raising tadpoles on a fast- and slow-growth trajectory by manipulating their holding
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temperature. After 6 days, tadpoles were conditioned to recognize the odour of a tiger salamander as a predator. After conditioning, half the tadpoles from each treatment were maintained on their respective growth trajectory, while the other half was switched to the other trajectory. After 2 weeks, tadpoles from each treatment group were tested for their response to water (negative control), injured conspecific cues (positive control) and salamander odour. Tadpoles were raised in tubs. Although we tested tadpoles individually, we used tubs, not tadpoles, as our replicate unit, as tadpoles raised from the same tubs were not truly independent from one another. Experimental setup Temperature manipulation We chose to use temperature, and not food, to manipulate growth rate, to avoid a hunger level confound in our results. There was excess food (rabbit chow) on the bottom of the tubs throughout our experiment, so we are confident the tadpoles did not differ in their hunger level. On 20 May 2009, 24 tubs (40 9 30 9 30 cm) containing *12 L of well water and rabbit chow were set outdoors. One ice pack (15 9 20 cm) at ambient temperature was placed in each tub. On 21 May, we collected 720 tadpoles from our holding pool and measured the length of a sub-sample of 20 (total length: mean ± SD = 10.7 ± 0.1 mm). We then arbitrarily placed 30 tadpoles in each of the 24 tubs. Twelve randomly chosen tubs were assigned to the ‘warm’ treatment while the other half were assigned to the ‘cold’ treatment. On that day, the ice packs from the cold treatment group were replaced by a set of frozen ice packs, while the ice packs from the warm treatment were removed and placed back in the tubs. Twice a day, around 1,200 and 1,600 h, the ice packs from the cold treatment group were replaced with frozen ones. The ice packs from the warm treatment group were also removed and put back in the tubs to control for disturbance. This procedure effectively cooled the water from 1,200 until *1,800 h. Temperature checks were performed 3 times per day, at 1,400, 1,600 (prior to changing the ice pack) and 1,800 h, to keep track of the actual temperature difference induced by the ice packs. This ‘cooling’ procedure was identical throughout the experiment, both before and after conditioning and testing (temperatures mean ± SD: cold treatment: 11 ± 3°C, warm treatment: 20 ± 4°C). We did not attempt to induce a temperature difference at other times, because the early spring overnight temperatures at our latitude were already low (range 2–10°C). Hence, the two environmental conditions did not differ in their low temperatures, but only in their high temperatures.
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Conditioning phase Conditioning took place on day 6 (26 May). No temperature treatments were applied this day to ensure all the tadpoles were at the same temperature (for at least 12 h prior to and 12 h following the learning event), and that temperature per se would not affect the temperaturerelated learning abilities of the tadpoles. In the morning, the length of five arbitrarily chosen tadpoles from each of the 24 tubs was measured, and tadpoles were returned to their holding tubs. The tadpoles were then left undisturbed for 1 h. We then injected 10 mL of injured conspecific cues paired with 20 mL of salamander odour in each of the 24 tubs. One hour after conditioning, we performed a 100% water change on all the tubs and added rabbit chow. In each of the warm and cold treatment groups, we randomly chose six tubs that would be maintained in their previous treatment group while the other six would be exposed to the other treatment group. The temperature treatments started again on 27 May. After the conditioning event, 6 of the 12 tubs from the cold treatment and 6 of the 12 tubs from the warm treatment were exposed to the cold treatment, while the other 12 received the warm treatment, giving us four experimental groups: cold–cold, cold–warm, warm–cold and warm–warm. The temperature manipulation methodology was identical to that before the conditioning event. The tadpoles were treated this way for an additional 2 weeks. We performed water changes in all the tubs every 3 days and added fresh food daily in all tubs. To keep track of tadpole growth rates throughout the experiment, we measured the length of five arbitrarily chosen tadpoles from each of the 24 tubs on the morning of 5 June. Testing and behavioural assay Testing took place from 9 June to 11 June. Each day, two tubs from each of the four treatment groups were used for behavioural observations. That day, tadpoles from the eight tubs were maintained and tested at ambient temperature. Thus, the same number of tadpoles from each of the four treatment groups was tested each day. One hour before testing, individual tadpoles were placed in 0.5-L cups filled with well water. Tadpoles were exposed to 5 mL of well water, salamander odour or cues from one injured conspecific. To control for size differences in tadpoles used to prepare injured conspecific cues, cues were made from four tadpoles, one tadpole from each treatment group (cold–cold, warm–cold, cold–warm and warm–warm), and suspended into 20 mL of water. This solution was used for four behavioural trials, one from each treatment group. We used a well-
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established behavioural protocol to quantify the antipredator responses of tadpoles (Ferrari and Chivers 2008, 2009a; Ferrari et al. 2008). The typical antipredator response of larval amphibians, including woodfrog tadpoles, is to decrease activity upon detection of predation cues. Thus, a line was drawn on the bottom of the testing cups, and the number of lines crossed was recorded during the 4-min pre and 4-min post-stimulus periods. The cues were gently introduced in the cup using a syringe to minimize disturbance. We considered a line was crossed when the entire body of the tadpole was on the other side of the line. The order of testing was randomized between the treatments, and the observer was blind to the cues for which tadpoles were tested. We tested 11–15 tadpoles from each tub, 3–5 tadpoles being tested for responses to each of the three cues, for a total of 329 trials. The day after the end of the testing phase, the length of five randomly chosen tadpoles from each tub was measured. Despite the size difference among groups, we did not see a difference in developmental stage; all tadpoles were at Gosner stage 25 (Gosner 1960). Statistical analysis Tadpole size This analysis was done to establish size differences between temperature groups. The lengths of the five tadpoles measured from each tub were averaged, and the mean length per tub was used as our raw data. Hence, tub, not tadpole, was our replication unit. We assessed the effect of pre-conditioning treatments (cold vs. warm treatment), post-conditioning treatments (cold vs. warm treatment) and time on the size of the tadpoles at time 1 (prior to conditioning, 26 May), time 2 (7 days prior to testing, 5 June) and time 3 (2–3 days following the beginning of testing, 12 June) using a 2-way repeatedmeasure ANOVA. Behavioural responses This analysis was done to compare the intensity of response of the tadpoles from different temperature treatments. We calculated the change in proportion of line crosses from the prestimulus baseline. As for the size analysis, we averaged the behavioural values obtained from tadpoles from the same tub exposed to the same cue, hence tub, not the individual tadpole, was considered our sampling unit. For each cue, the effects of pre-conditioning and postconditioning treatments were assessed. Data were normally distributed, and the variances were homogeneous among treatments. The effect of pre-conditioning treatment indicated whether the learned response to predators was affected by initial size/growth rate (learning by small/slow-growing vs. large/fast-growing tadpoles).
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The effect of post-conditioning treatment indicated the effect of size/growth rate ‘post-conditioning’ (since the information was acquired) on the responses of prey to predators. The effect of the interaction indicated whether the effects of initial size/growth rate at learning and growth rate post-learning were additive or interactive. Size can explain the variation in response to predator odour above and beyond the learned information using a cost/benefit framework. Bigger individuals display lower intensity response to the predator cues, because they perceive the predator as less risky than smaller individuals (Helfman 1989). To account for this, we performed a 2-way ANOVA on the studentized residuals of the regression between size and behavioural response. Although the measurements of size (x-axis) were not measured without error (regression assumption), we considered the error negligible in comparison to the error in behaviour measurement (Zar 1999). The analysis was performed using the size of tadpoles at time 3 (2-3 days after start of testing), but also on the size of the tadpoles assessed at the day of testing (sizeassessed = sizetime2 ? (sizetime3 - sizetime2) 9 2/3), to provide a conservative analysis. The ‘2/3’ reflects that testing took place at *2/3 of the time elapsed between the two measurement dates (Fig. 1), with the assumption than growth rate was linear during that time.
Tadpole size The ANOVA results are presented in Table 1. The size of the tadpoles was influenced both by the temperature before and after conditioning. Tukey pairwise post hoc comparisons indicated that the tadpoles from the four treatment groups were in four distinct size classes just before and just after behavioural observations (all P \ 0.003, Fig. 1). For the pre-conditioning period and post-conditioning period respectively, the growth rates, calculated from the change in size in mm/day, were (mean ± SE): cold–cold: 0.27 (±0.05) then 0.23 (±0.02) mm/day; cold–warm: 0.25 (±0.03) then 0.63 (±0.03) mm/day; warm–cold: 0.64 (±0.03) then 0.26 (±0.02) mm/day; warm–warm: 0.59 (±0.04) then 0.75 (±0.03) mm/day. Behavioural responses Pre- and post-conditioning treatments did not influence the behavioural response of tadpoles to water (pre: F1,20 = 1.2, P [ 0.2, post: F1,20 = 0.5, P [ 0.4, interaction: F1,20 = 0.0, P [ 0.9) or to injured conspecific cues (pre: F1,20 = 2.8, P [ 0.1, post: F1,20 = 0.4, P [ 0.5, interaction: F1,20 = 1.5, P [ 0.3). However, the behavioural response of tadpoles to salamander odour was affected by
28 warm/warm cold/warm 26
Testing
warm/cold cold/cold
24
Mean (+/-SE) tadpole length (mm)
Fig. 1 Mean (±SE) tadpole length measured throughout the experimental period. Tadpoles were raised in cold or warm conditions until May 26 and half were subsequently switched to the other treatment. The grey zone indicates the 3-day testing period during which behavioural observations were carried out
Results
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Table 1 ANOVA table showing the effect of time, temperature before conditioning (Tpre) and temperature after conditioning (Tpost) on the size of tadpoles Source
df
F
P value
Within subjects Time
2, 40
1,105
<0.001
Time * Tpre Time * Tpost
2, 40 2, 40
7 254
0.003 <0.001
Time * Tpre * Tpost
2, 40
3
0.069
1, 20
154
<0.001
Tpost
1, 20
359
<0.001
Tpre * Tpost
1, 20
3
0.078
Between subjects Tpre
Bold type indicates significant P-values at a 0.05 alpha level
Mean (+/- SE) proportion change in line crosses
both pre-conditioning (F1,20 = 5.1, P \ 0.035), and postconditioning treatments (F1,20 = 19.9, P \ 0.001), but there was no interaction between the main effects (F1,20 = 0.6, P [ 0.4, Fig. 2). The regression between size and behavioural response was significant, both using size at time 3 (F1,22 = 6.3, P = 0.02, r2 = 0.22) and the size at testing (F1,22 = 8.1, P = 0.009, r2 = 0.27, Fig. 3), indicating that bigger tadpoles responded less to the predator odour. In both cases, the 2-way ANOVA on the studentized residuals of the behavioural responses revealed a significant effect of preconditioning temperature (time 3: F1,20 = 9.2, P = 0.007; time at testing: F1,20 = 7.9, P = 0.011), but no effect of post-conditioning temperature (time 3: F1,20 = 0.3, P = 0.59; time at testing: F1,20 = 0.61, P = 0.44) and no 0.4 0.2 0 -0.2 -0.4 -0.6 -0.8 -1 Cold/Cold
Warm/Cold
Cold/Warm
Warm/Warm
Fig. 2 Mean (±SE) proportion change in line crosses from the prestimulus baseline for tadpoles exposed to water (black bars), salamander odour (grey bars) and crushed conspecific cues (white bars). Tadpoles were maintained in either a warm or a cold environment before or after their conditioning to recognize the salamander odour as a threat (before learning temperature–after learning temperature)
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Proportion change in line crosses from prestimulus
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0.6 0.4 0.2 0 13
16
19
22
25
-0.2 -0.4 -0.6
CC
-0.8
CW -1
WC Mean tadpole size (mm)
WW
Fig. 3 Biplot between the tadpole size (mean size/tub plotted) and intensity of antipredator response (mean intensity of antipredator response) in each of the four treatment groups
interaction (time 3: F1,20 = 0.2, P = 0.63; time at testing: F1,20 = 0.2, P = 0.66). This indicates that, once the effect of size is removed, we find an effect of pre-conditioning temperature on the responses. Tadpoles that were following a slow-growth trajectory at the time of learning displayed stronger responses to the predator odour (Fig. 3).
Discussion Our results indicate that tadpoles from all four groups did not differ in their response to disturbance (water), nor did they differ in their response to unknown risk (injured conspecific cues). This indicates that size and/or recent growth trajectory does not affect the behavioural responses to those two cues. This pattern was expected, since injured conspecific cues represent an unspecific risk cue and given comparable context-dependent trade-offs, all prey should respond to those cues, regardless of their sizes. Our results also suggest that learned predator recognition is influenced by pre-learning growth rate. We found a significant effect of treatment on the behavioural response to the salamander. The regression indicated, as expected, that overall, bigger tadpoles displayed weaker response to the predator than smaller tadpoles. These results follow established patterns of size-dependent responses to predators by prey of various taxa (Bronmark and Miner 1992; Mirza and Chivers 2003; Mathis et al. 2003; Parkos and Wahl 2010; de Barros et al. 2010). However, above and beyond the size effect, we found that tadpoles on a slow-growth trajectory displayed stronger antipredator responses to the predator. This effect is obvious when comparing the warm/cold group to the cold/warm group. Although tadpoles from the warm/cold
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group were significantly smaller than the tadpoles from the cold/warm group, they still responded to the predator with a weaker response. In order to gain a full appreciation of the way prey animals reduce their probability of being captured, we need to undertake experiments that integrate behaviour, morphology and life history. From a few studies, we know that prey that exhibit predator-induced plasticity in morphology subsequently alter their behavioural responses to predators (Chivers et al. 2007; Hoverman et al. 2005; Relyea 2001). To our knowledge, this is the first study that has attempted to experimentally link lifehistory traits (size and growth rate) with learning of predators. If vulnerability to predators is dependent on prey size, then one can expect that slow-growing individuals should be more susceptible to predators than fast-growing individuals. Moreover, slow-growing individuals should be vulnerable for a longer period of time than fast-growing individuals. Both of these factors should affect the encoding of the risk information during learning. Although we continuously referred to the pre-learning effects as being the results of size and/or growth rate at the time of learning, those two effects need not be linked. In our study, tadpoles that were on a fast-growth trajectory initially were also the bigger tadpoles, so we cannot tease these two factors apart. However, one could distinguish the effects of each of those parameters by having small or large tadpoles on a slow or fast-growth trajectory and see how each group responds to a novel predator after a conditioning trial. It is unknown whether size per se alters learned responses. But, given that all size classes responded equally to the alarm cues, and given that the intensity of the learned response is mediated by alarm cues (Ferrari et al. 2005, 2009), it is unlikely that one size class learned the predator as a highrisk while another size class learned the predator as a lowrisk. Our results may reflect differential learning based on the physiological state of the animals. We conditioned all of the tadpoles at the same temperature to try to ensure that the coding of information was not influenced by temperature. Given that all the tadpoles were at the same temperature for at least 12 h prior to conditioning and were also maintained at the same temperature for another 12 h, we are quite confident that temperature would not affect the efficiency of learning per se. We also fed the animals ad libitum to eliminate hunger effects on learning. However, the group of tadpoles in the ‘cold’ treatment would have spent the day in a ‘warmer-than-usual’ environment. Additionally, although the water temperature was equal among groups at the time of conditioning, we cannot exclude differences in hormone levels acting on a much longer time frame.
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Beyond the effects of size and growth rate at the time of learning, an alternative and equally plausible explanation for our results would be that the tadpoles on different growth trajectories prior to learning may forget predators at a different rate. Here, we define ‘forgetting’ as the extinction of the learned response in the absence of reinforcement. Not much is known about forgetting in the context of predation. A couple of studies have shown that low-risk threats were ‘forgotten’ faster than high-risk threats (Ferrari et al. 2010a; Gonzalo et al. 2009). More interestingly, Brown et al. (2011) demonstrated that growth rate prior to conditioning, but neither growth rate after conditioning nor size, influences the length of time that rainbow trout remember predator cues. Prey that are slow growing may remember the predator for a longer period of time than those that are faster growing, because their slower growth rate puts them under the risk of predation for a longer period of time. The supposition that prey that are fast growing, and hence have the ability to outgrow their predators, should have a shorter memory, is consistent with the model of adaptive forgetting proposed by Ferrari et al. (2010a). Alternatively, size per se could also explain the differential memories. The concept of infantile amnesia (Neissen 2004) describes a phenomenon in which retention of information could be linked to growth. As a young individual grows, the developing brain undergoes important reorganizational changes, leaving some memories harder to retrieve. Our results certainly fit within this framework. Indeed, bigger tadpoles may have undergone greater reorganizational changes than smaller tadpoles, making information related to the predator harder to retrieve (or only partially retrieved). This would explain why bigger tadpoles responded with a lower intensity of response than smaller ones. For us to validate this hypothesis, we would need to test whether the learning was equal for fastgrowing and slow-growing tadpoles immediately after the conditioning treatment. This would clearly tease apart the effects of learning from the effects of memory. Tadpoles provide a great study system to examine learned recognition of predators (Ferrari et al. 2009, 2010a; Ferrari and Chivers 2009b). Nevertheless, it is important to realize that the life history of tadpoles is such that they often employ a growth-maximizing strategy as opposed to a risk-sensitive strategy. This means that temporal constraints on the availability of their aquatic habitat (risk of dessication) might drive such organisms to be more prone to ignore risk and obtain enough resources to metamorphose before the pond dries out. For prey that have a life history that is less temporally constrained, we should expect that there will be even greater opportunities for interplay between behaviour, morphology and life-history defences. Consequently, we encourage similar studies in taxa with fewer life-history constraints.
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816 Acknowledgments We thank Glen and Jean Chivers for letting us invade their home and wetlands. Thanks to Del and Al Caskey for helping monitoring the tadpoles. Thanks to Aditya Manek and Oliver for field assistance. This research was funded through NSERC Discovery Grants to DPC and GRB, and NSERC PDF to MCOF. All work reported therein was in accordance with the Canadian Council on Animal Care and followed the University of Saskatchewan Animal Care Protocol no. 20070014.
References Bednekoff PA, Lima SL (1998) Re-examining safety in numbers: interactions between risk dilution and collective detection depend upon predator targeting behaviour. Proc Roy Soc B Biol Sci 265(1409):2021–2026 Bouskila A, Blumstein DT (1992) Rules of thumb for predation hazard assessment—predictions from a dynamic-model. Am Natural 139(1):161–176 Bronmark C, Miner JG (1992) Predator-induced phenotypical change in body morphology in crucian carp. Science 258(5086): 1348–1350 Brown GE, Chivers DP (2005) Learning as an adaptive response to predation. In: Barbosa P, Castellanos I (eds) Ecology of predator-prey interactions. Oxford University Press, Oxford, pp 34–54 Brown GE, Smith RJF (1996) Foraging trade-offs in fathead minnows (Pimephales promelas, Osteichthyes, Cyprinidae): Acquired predator recognition in the absence of an alarm response. Ethology 102(9):776–785 Brown GE, Ferrari MCO, Malka PH, Oligny M-A, Romano M, Chivers DP (2011) Growth rate and retention of learned predator cues in juvenile rainbow trout: faster growing fish forget sooner. Behavioral Ecology and Sociobiology (in press) Chivers DP, Smith RJF (1993) The role of olfaction in chemosensorybased predator recognition in the fathead minnow, Pimephales promelas. J Chem Ecol 19(4):623–633 Chivers DP, Smith RJF (1998) Chemical alarm signalling in aquatic predator-prey systems: A review and prospectus. Ecoscience 5(3):338–352 Chivers DP, Zhao XO, Ferrari MCO (2007) Linking morphological and behavioural defences: prey fish detect the morphology of conspecifics in the odour signature of their predators. Ethology 113(8):733–739. doi:10.1111/j.1439-0310.2006.001385.x de Barros FC, de Carvalho JE, Abe AS, Kohlsdor T (2010) Fight versus flight: the interaction of temperature and body size determines antipredator behaviour in tegu lizards. Anim Behav 79(1):83–88. doi:10.1016/j.anbehav.2009.10.006 DeWitt TJ, Sih A, Hucko JA (1999) Trait compensation and cospecialization in a freshwater snail: size, shape and antipredator behaviour. Anim Behav 58:397–407 Ferrari MCO, Chivers DP (2006) Learning threat-sensitive predator avoidance: how do fathead minnows incorporate conflicting information? Anim Behav 71:19–26. doi:10.1016/j.anbehav. 2005.02.016 Ferrari MCO, Chivers DP (2008) Cultural learning of predator recognition in mixed-species assemblages of frogs: the effect of tutor-to-observer ratio. Anim Behav 75:1921–1925. doi: 10.1016/j.anbehav.2007.10.037 Ferrari MCO, Chivers DP (2009a) Latent inhibition of predator recognition by embryonic amphibians. Biol Lett 5(2):160–162. doi:10.1098/rsbl.2008.0641 Ferrari MCO, Chivers DP (2009b) Temporal variability, threat sensitivity and conflicting information about the nature of risk:
123
Anim Cogn (2011) 14:809–816 understanding the dynamics of tadpole antipredator behaviour. Anim Behav 78(1):11–16. doi:10.1016/j.anbehav.2009.03.016 Ferrari MCO, Trowell JJ, Brown GE, Chivers DP (2005) The role of learning in the development of threat-sensitive predator avoidance by fathead minnows. Anim Behav 70:777–784. doi: 10.1016/j.anbehav.2005.01.009 Ferrari MCO, Messier F, Chivers DP (2008) Larval amphibians learn to match antipredator response intensity to temporal patterns of risk. Behav Ecol 19(5):980–983. doi:10.1093/beheco/arn056 Ferrari MCO, Brown GE, Messier F, Chivers DP (2009) Threatsensitive generalization of predator recognition by larval amphibians. Behav Ecol Sociobiol 63(9):1369–1375. doi:10.1007/ s00265-009-0779-5 Ferrari MCO, Brown GE, Bortolotti GR, Chivers DP (2010a) Linking predator risk and uncertainty to adaptive forgetting: a theoretical framework and empirical test using tadpoles. Proc Roy Soc B Biol Sci 277(1691):2205–2210. doi:10.1098/rspb.2009.2117 Ferrari MCO, Wisenden BD, Chivers DP (2010b) Chemical ecology of predator-prey interactions in aquatic ecosystems: a review and prospectus. Can J Zool 88:698–724 Gonzalo A, Lopez P, Martin J (2009) Learning, memorizing and apparent forgetting of chemical cues from new predators by Iberian green frog tadpoles. Anim Cogn 12(5):745–750. doi: 10.1007/s10071-009-0232-1 Gosner KL (1960) A simplified table for staging anuran embryos and larvae with notes on identification. Herpetologica 16:183–190 Harvell CD (1990) The ecology and evolution of inducible defences. Q Rev Biol 63:323–340 Helfman GS (1989) Threat-sensitive predator avoidance in damselfish-trumpetfish interactions. Behav Ecol Sociobiol 24(1):47–58 Hoverman JT, Auld JR, Relyea RA (2005) Putting prey back together again: integrating predator-induced behaviour, morphology and life history. Oecologia 144:481–491 Laurila A, Pakkasmaa S, Crochet PA, Merila J (2002) Predatorinduced plasticity in early life history and morphology in two anuran amphibians. Oecologia 132(4):524–530. doi:10.1007/ s00442-002-0984-7 Lima SL (1998a) Nonlethal effects in the ecology of predator-prey interactions—what are the ecological effects of anti-predator decision-making? Bioscience 48(1):25–34 Lima SL (1998b) Stress and decision making under the risk of predation: Recent developments from behavioral, reproductive, and ecological perspectives. In: Stress and Behavior, vol 27. Advances in the Study of Behavior, pp 215–290 Lima SL, Dill LM (1990) Behavioral decision made under the risk of predation—a review and prospectus. Can J Zool 68(4):619–640 Lind J, Cresswell W (2005) Determining the fitness consequences of antipredation behaviour. Behav Ecol 16:945–956 Mathis A, Murray KL, Hickman CR (2003) Do experience and body size play a role in responses of larval ringed salamanders, Ambystoma annulatum, to predator kairomones? Laboratory and field assays. Ethology 109(2):159–170 Mirza RS, Chivers DP (2003) Influence of body size on the responses of fathead minnows, Pimephales promelas, to damselfly alarm cues. Ethology 109(8):691–699 Neissen U (2004) Memory development: new questions and old. Dev Rev 24:154–158 Parkos JJ, Wahl DH (2010) Influence of body size and prey type on the willingness of age-0 fish to forage under predation risk. Trans Am Fish Soc 139(4):969–975. doi:10.1577/t09-098.1 Relyea RA (2001) Morphological and behavioral plasticity of larval anurans in response to different predators. Ecology 82(2): 523–540 Zar JH (1999) Biostatistical analysis, 4th edn. Prentice-Hall, New Jersey
