BLBK374-04

BLBK374-Brown

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Char Count=

Chapter 4

Learning about Danger: Chemical Alarm Cues and Threat-Sensitive Assessment of Predation Risk by Fishes Grant E. Brown, Maud C.O. Ferrari and Douglas P. Chivers

4.1

Introduction

Most species are at risk of predation during some, if not all, phases of their lives. As a result, there exists strong selection pressure for early detection and avoidance of potential predation threats. However, predator avoidance has the potential to be very costly, as it reduces time and energy available for other activities such as foraging, mating and territorial defence (Godin & Smith 1988; Sih 1992) or forces prey to utilise suboptimal habitats (Gotceitas & Brown 1993), leading to a reduction in energy intake and reproductive output (Lima & Dill 1990). Presumably, prey that can adjust the intensity of their predator avoidance response according to the level of perceived risk should be at a selective advantage (Helfman 1989; Lima & Dill 1990). This supposition is known as threat-sensitive predator avoidance (Helfman 1989; Chivers et al. 2001) Threat-sensitive assessment of predation risk is complicated by the fact that predation itself is highly variable in space and time (Sih et al. 2000; Griffin 2004; Lima & Steury 2005; Ferrari et al. 2009a). Likewise, the form of predation and the degree of risk may change dramatically as prey individuals grow (size-dependent predation risk; Br¨onmark & Miner 1992), shift habitat preferences with ontogeny (Werner & Gilliam 1984) or move within heterogeneous habitats (Golub et al. 2005). Prey may also move between prey guilds (Olson et al. 1995; Olson 1996; Brown et al. 2001) and are subject to seasonal changes in biotic and/or abiotic conditions (Gilliam & Fraser 2001). This high degree of variability can result in unpredictable and variable predation risk. Prey that can reliably assess local predation risk based on recent experience (i.e. learning) should be better able to deal with variability in predation pressure. Our recent reviews (Brown & Chivers 2005, 2006) have highlighted the mechanisms of chemically mediated learning in prey fishes. Our goal here is to review some of the new directions in the field of chemically mediated predator recognition. Specifically, we examine the role-learning plays in the threat-sensitive mediation of predation risk.

Fish Cognition and Behavior, Second Edition. Edited by Culum Brown, Kevin Laland and Jens Krause.  C 2011 Blackwell Publishing Ltd. Published 2011 by Blackwell Publishing Ltd.

BLBK374-04

BLBK374-Brown

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

60

Fish Cognition and Behavior

4.2

Chemosensory cues as sources of information

Char Count=

An underlying assumption of any approach to threat-sensitive behavioural decision models is that prey can reliably assess local predation threats in real time. Within aquatic ecosystems, this risk assessment is often mediated via chemosensory cues (Kats & Dill 1998; Wisenden & Chivers 2006). Public information regarding local predation risk is available from a suite of cues, including damage-released chemical alarm cues, disturbance cues and predator odours (Chivers & Smith 1998). Damage-released cues are found in a wide variety of taxonomically diverse prey fishes and are produced and/or stored in the epidermis. When released, following mechanical damage to the skin, these cues can elicit dramatic short-term increases in species typical antipredator behaviours (Chivers & Smith 1998; Wisenden & Chivers 2006). Recent studies suggest that there is often a strong relationship between the relative concentration of alarm cues prey detect and the intensity of the antipredator responses displayed by the prey (Jachner & Rydz 2002; Dupuch et al. 2004; Brown et al. 2006a, 2009). Moreover, prey may attend to alarm cues at very low concentrations by increasing vigilance towards secondary risk assessment cues (Brown et al. 2004) or may show subtle adjustments in their foraging tactics (Foam et al. 2005a). A second class of chemosensory cues are the so called ‘disturbance cues’. These are metabolic by-products released by stressed or disturbed prey prior to an attack by a predator (Wisenden et al. 1995; Jord˜ao & Volpato 2000; Vavrek et al. 2008). They are released in the absence of skin damage to the prey. While behavioural response to disturbance is typically of a lower intensity than to the more often studied damage-released cues, there still exists a strong threat-sensitive response to varying concentrations of disturbance cues (Vavrek & Brown 2009). Finally, the chemosensory cues originating from predators themselves can provide information regarding the intensity of local threats (Kusch et al. 2004; Ferrari et al. 2006a). In some cases, the degree of sophistication of chemosensory risk assessment is remarkable. Fathead minnows (Pimephales promelas, Cyprinidae), for example, are known to distinguish predator size, predator proximity and predator density – all based on predator odours (Kusch et al. 2004; Ferrari et al. 2006b).

4.2.1

Learning, innate responses and neophobia

Researchers studying predator recognition have spent considerable time attempting to identify the relative importance of experience versus genetic factors in the acquisition of responses to predators. We have some good examples of prey fishes that do not appear to respond to predators unless they have experience, cases where prey seem to respond to predators without experience and examples where experience modifies what appears to be ‘innate’ responses. Chivers & Smith (1994a,1994b) demonstrated the importance of experience in responses of fathead minnows to pike (Esox lucius, Esocidae) cues. They found that fathead minnow eggs collected from pike sympatric populations and reared under laboratory conditions exhibited no apparent recognition of either the chemical or visual

BLBK374-04

BLBK374-Brown

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Learning about Danger: Chemical Alarm Cues and Threat Sensitivity

Char Count=

61

cues of a predatory pike, while wild caught individuals (from the same population) of the same size/age did (Chivers & Smith 1994b). Subsequent stocking experiments demonstrated that naive populations of minnows would quickly acquire recognition of introduced predators (Chivers & Smith 1995). Perhaps the most striking example of this rapid recognition was demonstrated by Brown et al. (1997). They introduced 39 juvenile pike into a 4-ha lake containing approximately 78,000 minnows and found recognition of the pike odour by minnows within 4 days. Several other species, including brook stickleback (Culaea inconstans, Gasterosteidae; Chivers et al. 1995), brook trout (Salvelinus namaycush, Salmonidae; Mirza & Chivers 2000, 2001), brown trout (Salmo trutta, Salmonidae; Alvarez & Nicieza 2003), common bully (Gobiomorphus cotidianus, Eleotridae; Kristensen & Closs 2004) and zebra danio (Danio rerio, Cyprinidae; Bass & Gerlai 2008), fail to exhibit responses to predators without prior experience. Conversely, Scheurer et al. (2007) provided strong support that fishes can respond to predators even though they have no prior experience with them. They tested F2 hatcheryreared offspring of steelhead trout originally collected from a stream population that contained Dolly Varden (S. malma, Salmonidae, a common predator of juvenile steelhead) and a lake population that was devoid of Dolly Varden. The lake population was originally stocked with steelhead collected from the stream population at least 15 generations previously. Despite at least 15 generations of isolation, the lake population showed responses to the odour of Dolly Varden predators, as did the stream population, when tested under common laboratory conditions. These results might indicate genetically fixed, i.e. innate, predator recognition. There are several other examples of what may appear to be ‘innate’ predator recognition in a variety of prey fishes. Juvenile Chinook salmon (Berejikian et al. 2003) and arctic charr (S. alpinus, Salmonidae; Vilhunen & Hirvonen 2003) exhibit increased antipredator responses when exposed to novel predator odours. Likewise, Hawkins et al. (2004) have shown that juvenile Atlantic salmon (S. salar, Salmonidae) significantly increased opercular flap rates upon detection of novel cues, suggesting increased vigilance or olfactory sampling as opposed to true recognition (Gibson & Mathis 2006). Predator naive Nile tilapia (Oreochromis niloticus, Cichlidae) show a similar increase in opercular movements during exposure to visual predator cues (Barreto et al. 2003). Can such apparent innate recognition occur in the absence of genetic fixation? The answer is likely yes. Prey may exhibit strong avoidance responses to any novel cue, a phenomenon known as neophobia (Sneddon et al. 2003). Responding with a fright response to any novel cue is much different than having genetically fixed responses to specific predator cues. In either case, being able to respond to predators upon a first encounter should eliminate the cost of learning (Blumstein 2006; Ferrari et al. 2007). As prey grow or develop sufficient behavioural plasticity, learning should replace neophobic responses, allowing prey to ‘fine-tune’ their recognition and avoidance of predators. This is likely very important in populations characterised by variable predation pressure, where true innate recognition would prove limiting. We will return to the importance of learning versus innate responses later when we discuss the predator recognition continuum hypothesis in Section 4.5.

BLBK374-04

BLBK374-Brown

62

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Char Count=

Fish Cognition and Behavior

4.2.2 Learned predator recognition through conditioning with alarm cues It is well established that many fishes can learn to recognise unknown predators through conditioning with alarm cues. In this well-studied mechanism, the pairing of a damagereleased alarm cue with either the visual or chemical cues of a novel predator results in learned recognition of that predator (Chivers & Smith 1998; Brown & Chivers 2005, 2006). For example, Magurran (1989) showed that European minnows (Phoxinus phoxinus, Cyprinidae) acquire the recognition of the chemical cues of predatory pike after a single exposure to pike odour paired with conspecific alarm cues. Chivers & Smith (1994a,1994b) likewise reported that fathead minnows could learn the sight or the odour of a pike in the same way. Similar conditioning results have been shown for brook stickleback (Chivers et al. 1995), brown trout (Alvarez & Nicieza 2003), common bully (Kristensen & Closs 2004) and zebra danios (Bass & Gerlai 2008). Learned recognition through conditioning with alarm cues enhances survival during staged encounters with live predators (Mirza & Chivers 2000, 2001; Darwish et al. 2005). There is growing evidence that chemically mediated learning allows prey to fine-tune their predator recognition. For example, Berejikian et al. (2003) found that the strength of an ‘innate’ response to novel predators could be enhanced through conditioning with alarm cues. Recent studies have also shown a significant ontogenetic effect on both innate predator avoidance and chemosensory learning. Juvenile Atlantic salmon exhibited significant innate responses to predator odours when tested 10–15 weeks post-hatching; however, younger (<3 weeks post-hatching) or older (28–36 weeks post-hatching) salmon did not (Hawkins et al. 2008). The same study showed that young salmon did not acquire the recognition of a novel predator odour paired with conspecific alarm cues, while older salmon did show significant learned responses (Hawkins et al. 2008). These data strongly suggest a complementary relationship between ‘innate’ and ‘learned’ responses.

4.3

Variable predation risk and flexible learning

It is now abundantly clear that prey fishes can show dramatic adjustments in the intensity of their antipredator response according to the level of perceived risk and that they are capable of learning to recognise novel predator cues. A growing body of research has built upon these two findings, examining the role of chemically mediated learning in the development of threat-sensitive response patterns. Ferrari et al. (2005) asked if the strength of the learned response to a novel predator odour is related to the intensity of the initial conditioning experience. They exposed predator-naive fathead minnows to low, intermediate or high relative concentrations of conspecific alarm cues, paired with the odour of a novel predator (brook charr, S. fontinalis, Salmonidae). During the initial conditioning phase, minnows exhibited stronger antipredator responses to the high concentration cues than the low concentration cues. When retested 24 hours later, Ferrari et al. (2005) found that the learned response to charr odour matched the intensity of response during the initial conditioning phase. Likewise, they found a similar correlation between the intensity of response to charr odour between experienced tutors

BLBK374-04

BLBK374-Brown

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Learning about Danger: Chemical Alarm Cues and Threat Sensitivity

Char Count=

63

and naive observers in a social learning study (Ferrari et al. 2005). Thus, acquired predator recognition through a single conditioning with alarm cues or a single observational learning opportunity appears to allow for the acquisition of threat-sensitive response patterns. Zhao et al. (2006) extended these findings, demonstrating that goldfish (Carassius auratus, Cyprinidae) were able to make similar threat-sensitive associations based on predator diet cues. They fed northern pike diets of either goldfish (with a recognisable alarm cue) or swordtails (Xiphophorus helleri, Poceiliidae; lacking an alarm cue recognised by minnows) and then exposed goldfish to varying concentrations of the predator odour. Goldfish exhibited increased antipredator responses proportional to the concentration of predator odour presented. When tested to a standard predator odour (pike-fed swordtails) during recognition trials, goldfish exhibited predator avoidance responses matching the intensity the fish exhibited during the initial conditioning trials. Moreover, when exposed to a live predator during staged encounters, goldfish initially conditioned to the highest concentration of predator odour (i.e. strongest learned recognition) were more likely to survive than those exposed to lower concentrations (i.e. weaker learned recognition) or the non-conditioned controls (i.e. no recognition of pike). Together, these data suggest that there is indeed a functional link between learning and the acquisition of context appropriate threat-sensitive response patterns. However, under ecologically realistic conditions, we should expect prey to be exposed to multiple learning opportunities. This raises the issue of ‘conflicting’ information, where prey may experience relatively high- and low-risk situations within short time frames. How might this influence threat-sensitive learning? Ferrari & Chivers (2006a) tested whether recent experience shapes threat-sensitive learning. Prey fishes may continually update their learned recognition of potential predators, with the intensity of antipredator behaviour mimicking the most recent learning experience. Ferrari & Chivers (2006a) tested this by exposing fathead minnows to either a high or a low concentration of conspecific alarm cue plus the odour of brook charr. The paired cues were given daily, for 6 consecutive days, one of four combinations: 6 low, 5 low 1 high, 1 low 5 high or 6 high concentrations of conspecific alarm cue plus the odour of brook charr. The intensity of antipredator behaviour when exposed to charr odour alone appeared to match the most recent ‘conditioning’ experience. This suggests that prey do not simply ‘average’ the intensity of learning opportunities, but do indeed adjust their level of antipredator response to the most recent experience. The concentration of predator odour detected during conditioning events also provides valuable information about the threat of the predator. Ferrari et al. (2006c) conditioned fathead minnows with conspecific alarm cue paired with either high or low concentrations of northern pike odour. Regardless of the concentration, there was no difference in response intensity when minnows were tested for recognition to the same concentration of predator odour used during the conditioning event (i.e. low–low = high–high). Perhaps this is not surprising, as the initial intensity of the antipredator response is governed by the concentration of alarm cue detected (which was the same for this study). However, when conditioned with a low concentration predator odour and then tested against a high concentration cue, minnows increased the intensity of the predator avoidance response. Conversely, when conditioned to a high concentration and then tested against a low concentration, minnows reduced the intensity of their response. Taken together with previous studies, these data

BLBK374-04

BLBK374-Brown

64

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Char Count=

Fish Cognition and Behavior

highlight the sophistication of the chemically mediated learning system, allowing prey to associate context-dependent risk with specific learned cues.

4.3.1

Assessing risk in time

Predation risk is known to vary from moment to moment and over daily, seasonal, yearly and generational scales (Sih et al. 2000; Magurran 2005). Until recently there was a surprising lack of information on how prey fishes dealt with such variation in risk. This stands in sharp contrast to numerous studies showing that prey animals, including fishes, can learn to associate specific foraging location with times of day or specific seasons (Foote & Brown 1998; Reebs 1999). Reebs (1999) demonstrated that inangas (Galaxias maculatus, Galaxiidae) were able to learn to associate a specific location with the temporal availability of food. However, inangas were unable to make the same association with a predictable predation risk (Reebs 1999). Yl¨onen et al. (2006) found partial support for temporally dependent learning in juvenile yellow perch (Perca fluviatilis, Percidae) and ruffe (Gymnocephalus cernuus, Percidae). Both perch and ruffe were able to acquire the recognition of the chemical cues of pike and burbot (Lota lota, Lotidae). However, while neither prey species showed clear evidence of diel patterns in avoidance, juvenile perch did respond with a stronger response to burbot at night. Yl¨onen et al. (2006) suggest that this may be due to the primarily nocturnal foraging habits of burbot. However, recent studies with larval amphibians demonstrate a clear ability to associate acquired predator recognition cues with time of day. Ferrari et al. (2008a) exposed larval wood frogs (Rana sylvatica) to predatory tiger salamanders (Ambystoma tigrinum) in the presence of wood frog alarm cues in the evening and tiger salamanders alone in the morning (vs. salamander only morning and evening controls) over a 9-day period. Wood frog tadpoles conditioned to recognise the salamander cue exhibited a significant recognition of the predator cue when tested in the morning, but showed a significantly stronger response when tested in the evening. These results suggest that wood frogs not only are able to learn to recognise the chemical cue of a common predator but can learn to associate the level of risk with time of day. The ability to learn threat-sensitive recognition based on predictable temporal patterns presumably would provide considerable benefits to prey fishes. Clearly, this hypothesis requires additional examination. Recent studies have examined the way in which prey fishes adjust the intensity of their antipredator responses within the context of the risk allocation model proposed by Lima & Bednekoff (1999). This model predicts that as predation risk fluctuates over time, the intensity of prey vigilance and foraging should depend on both the level of risk and the proportion of time that predators are present. If predators are usually absent, prey can meet their energy demands during safe periods, and thus respond strongly during the rare times when predators are present. In contrast, if predators are omnipresent, prey might need to forage actively even though predators are present. Studies with rainbow trout (Mirza et al. 2006), convict cichlids (Foam et al. 2005b; Brown et al. 2006b; Ferrari et al. 2010a), guppies (Poecilia reticulata, Poeciliidae; Brown et al. 2009b) and several flatfishes (Boersma et al. 2008) provide at least partial support for the risk allocation model.

BLBK374-04

BLBK374-Brown

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Learning about Danger: Chemical Alarm Cues and Threat Sensitivity

4.3.2

Char Count=

65

Sensory complementation and threat-sensitive learning

Under natural conditions, we might expect that prey would be exposed to multiple sources of information simultaneously. How these multiple information sources interact to allow for threat-sensitive behavioural decisions has only recently been examined. The sensory complementation hypothesis suggests that prey capable of accessing multiple risk assessment cues should be better able to gain reliable information regarding local threats (Smith & Belk 2001; Brown & Magnavacca 2003; Blanchet et al. 2007) and that multiple cues should interact in an additive or synergistic fashion (Lima & Steury 2005). There is a growing body of evidence that supports this hypothesis. For example, Blanchet et al. (2007) found that under laboratory conditions, stream dwelling young-of-the-year (YOY) Atlantic salmon responded in an additive fashion when presented with predator odour (adult rainbow trout-fed YOY Atlantic salmon) combined with a visual predator model in comparison to when the fishes were exposed to either visual or chemical cues alone. They found a similar response patterns when quantifying different response variables. Smith & Belk (2001) found similar chemical plus visual interactions in their study of the threat-sensitive predator inspection behaviour of western mosquitofish (Gambusia affinis, Poeciliidae). Recent studies have shown that sensory complementary effects may differ depending on age and/or experience. Kim et al. (2009) have shown an interaction between the additive value of combined chemical and visual cues with age class in wild Atlantic salmon. YOY and parr salmon were exposed to conspecific alarm cues (or a stream water control) followed by the presentation of a visual threat. Both YOY and parr exhibited significant increases in their latency to resume foraging following exposure to the chemical cue (relative to the control), but only YOY salmon exhibited a significant increase in latency to resume foraging following the subsequent exposure to the visual cue. Parr initially exposed to the control or conspecific alarm cue showed similar latencies to resume foraging after exposure to the visual cue. However, parr exhibited an additive response to chemical plus visual cues when looking at the flight initiation distance. Parr initially exposed to the chemical alarm cue exhibited a significantly greater reactive distance to the visual cue. YOY salmon showed no difference in the reactive distance. Thus, additive effects may be present, but differ depending on experience or age (Kim et al. 2009). Chris Elvidge (unpublished data) suggests that sensory complementation of information might depend on learning or experience. Elvidge presented wild juvenile Atlantic salmon with realistic model predators (visual cues) in a series of streams varying in ambient pH. Previous studies have shown that weakly acidic conditions inhibit the detection and response to conspecific alarm cues by juvenile salmon (Leduc et al. 2006). Presumably, salmon in neutral streams have had previous opportunity to assess risk based on the combined visual plus chemical cues, whereas salmon in the acidic streams would not have prior experience with chemical information. Elvidge’s results suggest that under weakly acidic conditions, juvenile salmon treat a standardised visual threat as a higher risk than under neutral conditions. The sensory complement model would argue that if prey have had previous experience with combined cues (as in the neutral streams), detection of a potential threat via a single sensory modality would be perceived as a lower risk than the same cue accompanied by additional sensory inputs. Likewise, Jachner (2001) demonstrated an interesting interaction between experience and the response of juvenile roach

BLBK374-04

BLBK374-Brown

66

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Char Count=

Fish Cognition and Behavior

(Rutilus rutilus, Cyprinidae) to conspecific alarm cues. Hatchery-reared roach exhibited threat-sensitive responses to conspecific alarm cues. Moreover, when repeatedly exposed to alarm cues, roach increased time on a foraging patch, suggesting a reduced antipredator response. However, wild caught, presumably experienced, roach exhibited only a weak response to alarm cues. Jachner (2001) argued that upon detection of the alarm cues experienced roach would increase vigilance towards either the smell or sight of a predator. In the absence of these secondary cues, roach did not show a strong antipredator response. Together, these studies provide indirect evidence of the role of sensory complementation in predator recognition learning. To date, we know of only a single study examining the direct effects of additive sensory inputs on chemosensory learning in fishes. Ferrari et al. (2008c) tested juvenile rainbow trout for additive responses to two different chemosensory cues. Trout exposed conspecific disturbance and chemical alarm cues combined responded in an additive fashion, supporting the sensory complement hypothesis. They then tested for additive learning effects by conditioning trout to recognise a novel predator odour paired with disturbance cue, alarm cue or the combined disturbance plus alarm cue. While they report no learning in trout initially exposed to the disturbance cue plus predator odour treatment, they did find stronger learning among trout initially conditioned with disturbance plus alarm cues. Thus, their results suggest that complementary interactions among multiple sensory modalities result in enhanced learning opportunities.

4.4

Generalisation of risk

Though learning has the obvious benefit of allowing prey to respond to temporal and spatial variations in risk, it is not without costs. In order to learn to recognise a novel predator, prey must have an initial encounter with the predator, representing at least a momentary increase in risk. Presumably, if prey can generalise what they actually learn, this would reduce the ‘direct learning’ costs associated with learning specific predators. For both visual and chemical predator cues, there should exist considerable variability among individual conspecific predators. Yet prey conditioned to recognise an individual predator are able to generalise other predators of the same species. But, can prey actually generalise learned information across different predator species that are similar in appearance or smell to the ones the prey already recognises?

4.4.1

Generalising of predator cues

A series of elegant studies with mammals (Griffin et al. 2001; Stankowich & Coss 2007), amphibians (Ferrari et al. 2009b) and fishes (Ferrari et al. 2007, 2010b; Brown et al. 2011a) have shown that prey conditioned to a reference predator can exhibit learned responses to chemical and visual cues of predators with which the prey have no experience. Moreover, predators that are more distantly related to the reference predator are not recognised. For example, Ferrari et al. (2007) conditioned predator-naive fathead minnows to recognise lake trout (S. namaycush, Salmonidae) and then tested for the recognition of lake trout, brook charr, rainbow trout (Oncorhynchus mykiss, Salmonidae), pike or white sucker (Catostomus

BLBK374-04

BLBK374-Brown

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Learning about Danger: Chemical Alarm Cues and Threat Sensitivity

Char Count=

67

commersoni, Catostomidae). Minnows exhibited a learned response to the three salmonid odours, and no significant response towards the pike or sucker odours. More interesting is that the intensity of the learned response was strongest for the reference predator and weakest (though still significant) towards the confamilial predator (rainbow trout), with the response to the congeneric predator (brook charr) being intermediate. By generalising learned predator recognition, prey should be able to gain the benefits of learning specific predator cues, without having to directly assess multiple predators independently (Griffin et al. 2001; Darwish et al. 2005; Ferrari et al. 2007). What specifically is being generalised? The results of Ferrari et al. (2007) suggest that generalisation is based on chemical similarities among phylogenetically related predators, but was independent of the predator’s diet. Presumably, related predator species would produce chemosensory cues more similar to each other than would more distantly related predators. We might also expect predators sharing similar diets, regardless of phylogenetic relatedness, to produce cues that are readily generalised by prey. Dietary cues are known to allow for the recognition of novel predators (Mathis & Smith 1993a, 1993b; Chivers & Mirza 2001). It is likely that a combination of chemical similarities among related predators plus common diets (especially among sympatric predators) would provide sufficient information to allow for generalisation of learned predator recognition. Ferrari et al. (2010c) show that generalisation can also be based on visual cues. Fathead minnows conditioned to recognise the visual cues of brown trout exhibited a similar response to the visual cues of rainbow trout, but not yellow perch. They argue that this is due to learning of similar body shape or some other visual feature. Intuitively, this makes sense. Magurran (1989) found that European minnows (P. phoxinus, Cyprinidae) were less likely to learn to recognise the visual cues of the non-predatory tilapia, compared to those of the predatory pike. Chivers & Smith (1994b) showed similar effects with fathead minnows. These results suggest that some specific visual cues may be more easily generalised in the context of predator recognition (Smith 1997). Studies looking at chemosensory cues typically restrict predators to a common diet in order to minimise possible dietary effects. An intriguing study would be to vary diet and predator taxa to directly assess this. If, as argued by Ferrari et al. (2007), prey benefit from generalised predator recognition via a reduction in the costs associated with learning specific predators, then we would expect higher risk cues to be more readily generalised than lower risk cues. Indeed, Ferrari et al. (2008c) found that fathead minnows conditioned with a high concentration of alarm cue (high perceived risk) exhibited generalised learning of trout cues, while minnows conditioned with low concentrations of alarm cue (low perceived risk) did not. These results suggest that prey may generalise the recognition only to highly threatening species but not to those of lower perceived risks.

4.4.2

Generalisation of non-predator cues

Pre-exposure to a predator cue, in the absence of any conditioning stimulus (latent inhibition), can result in the inability of prey to acquire recognition of a novel predator (Acquistapace et al. 2003; Ferrari & Chivers 2006b, 2009). For example, Ferrari & Chivers (2006b) exposed fathead minnows to brook charr odour or distilled water once per day for 5 consecutive days and then conditioned them to recognise brook charr as a predator.

BLBK374-Brown

68

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Char Count=

Fish Cognition and Behavior

80 A. Generalised learning of predator odours

B. Generalised learning of non-predator odours

60 Change in time moving (seconds)

BLBK374-04

Pre-exposed to pumpkinseed odour Pre-exposed to distilled water

40 20 0 –20 –40 –60 –80

PS

LE

RB

YP

DW

PS

LE

RB

YP

Fig. 4.1 Mean (SE) change in time spent moving for juvenile rainbow trout. Panel A: Juvenile rainbow trout were initially conditioned with trout alarm cue paired with the odour of a novel predator (pumpkinseed) and subsequently tested for the learned avoidance of pumpkinseed (PS), longear sunfish (LE), rock bass (RB), yellow perch (YP) or a distilled water (DW) control. Trout were able to generalise the learned recognition of pumpkinseed to the congeneric longear sunfish and the confamilial rock bass, but not to yellow perch (no different from the distilled water control). Panel B: Juvenile rainbow trout were pre-exposed to distilled water twice per day for 3 days and conditioned with alarm cue paired with the odour of one of four predators. When tested for recognition, trout were equally able to acquire the recognition of the predator odours (open circles). However, when pre-exposed to pumkinseed odour twice per day for 3 days (solid circles) and then conditioned to recognise the predator odours, trout were inhibited from learning pumpkinseed odour. In addition, trout appeared to generalise this inhibition and were unable to learn to recognise the odour of the congeneric longear sunfish. There was no inhibition of learning of rock bass or yellow perch odours. Modified from Brown et al. (2011a).

Minnows pre-exposed to distilled water were able to learn to recognise charr as a predator, but those pre-exposed to charr odour were not. Brown et al. (2011a) used this latent inhibition mechanism to test the hypothesis that juvenile rainbow trout can generalise the recognition of both predator and non-predator cues. In their first experiment, juvenile trout were conditioned to recognise pumpkinseed odour as a reference predator and then tested for the recognition of pumpkinseed, longear sunfish, rock bass or yellow perch odours. Trout conditioned to recognise pumpkinseed exhibited strong learned antipredator responses to the pumpkinseed and the odour of the congeneric longear sunfish. They observed a weaker (but still significant) response to the confamiliar rock bass and no response to the more distantly related yellow perch (Fig. 4.1A). In the second experiment, trout that had been pre-exposed to pumpkinseed odour did not learn to recognise pumpkinseed as a predation threat. Moreover, pre-exposure to pumpkinseed odour also inhibited learning of the odour of longear sunfish cues (Fig. 4.1B).

4.5

Predator recognition continuum hypothesis

Ferrari et al. (2007) argued that learning to recognise novel predators is merely one point along a continuum of predator recognition. At one extreme, prey would be genetically fixed to exhibit true innate recognition of predators, independent of any experience. At the

BLBK374-04

BLBK374-Brown

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Learning about Danger: Chemical Alarm Cues and Threat Sensitivity

Char Count=

69

other extreme, recognition would be learned, but any acquired information could be fully generalised to appropriate stimuli. Ferrari et al. (2007, 2008c) argue that such a continuum would arise primarily through variability in the spatial and/or temporal predictability of predation threats. This model consists of two related issues: (1) selection to learn and (2) selection to generalise.

4.5.1 Ecological selection for innate versus learned recognition of predators Given the demonstrated range of responses from innate to learned in how prey fishes recognise potential predators (see Subsection 4.2.1), we can make some predictions regarding the ecological conditions favouring either extreme form of recognition (Brown & Chivers 2005; Ferrari et al. 2007). Though poorly understood, the key factor is likely variability in predation pressure, in both overall intensity and predator type. Under conditions of intense predation pressure or conditions of a small and stable predator guild, selection should favour an experience independent response to novel predators (Breden et al. 1987; Vilhunen & Hirvonen 2003; Riechert 2005). Under such conditions, exposure to novel situations, including a novel predator, may elicit a strong predator avoidance response simply because the costs of not doing so would be disproportionately high (Hirvonen et al. 2000). Such ‘experience independent’ responses could be in the form of true innate responses (i.e. genetically fixed) or neophobia. Neophobic responses (see Subsection 4.2.1) would be particularly beneficial for species lacking sufficient behavioural plasticity in early life history phases to allow for threat-sensitive responses (Killen & Brown 2006). Moreover, neophobic responses would not require genetic fixation to a specific predator type, and thus might represent a ‘midpoint’ between innate and learned responses. Conversely, populations exposed to variable predation risk may be selected to learn context-appropriate responses due to the relatively high costs associated with ‘false responses’ to non-risky stimuli. Such variability in predation risk may arise from a number of ecological variables including spatial and temporal variabilities in predator encounters (Sih et al. 2000; Lima & Steury 2005), ontogenetic shifts in microhabitat use (Olson et al. 1995; Olson 1996) or size-dependent risk (Br¨onmark & Miner 1992; Nilsson & Br¨onmark, 2000). While clearly an oversimplification, this theoretical starting point could potentially lead to testable predictions.

4.5.2

Ecological selection for generalised learning

Ferrari et al. (2007) argued that selection towards generalised learning may be linked to the ratio of predators to non-predators. Under conditions where heterospecifics are predominately potential predation threats (high predator to non-predator ratio), prey may benefit from generalising the visual and/or chemical cues of learned predators to all heterospecifics with similar traits. This would allow prey to reduce the costs associated with direct interactions (learning) while still responding to variable predation risks. However, under conditions where fewer heterospecifics represent actual predation threats (low predator to non-predator ratio), generalising to all heterospecifics might represent a reduction in time and energy available for other fitness-related activities. As such, depending on the predator and prey

BLBK374-04

BLBK374-Brown

70

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Char Count=

Fish Cognition and Behavior

guild structure, the use of generalised or non-generalised predator recognition may allow prey to optimise threat-sensitive trade-offs (Ferrari et al. 2007, 2008c).

4.6

Retention: the forgotten component of learning

Despite the large volume of literature focusing on the acquisition of predator recognition in fishes and other taxa, surprisingly little is known regarding the retention of acquired information. Following a single pairing of an alarm cue and a novel predator odour, hatcheryreared rainbow trout retain a learned response for up to 21 days (Brown & Smith 1998) though the response begins to decline rapidly after 10 days (Mirza & Chivers 2000). Fathead minnows conditioned to recognise visual cues of either northern pike or goldfish as potential predators showed similar intensities of learned predator recognition when tested 2 days post-conditioning. However, when re-tested for visual recognition nearly 2 months post-conditioning, those initially conditioned to pike show a stronger response than did those initially conditioned to goldfish (Chivers & Smith, 1994a), suggesting differential retention. Presumably, prey should only respond to learned predator cues as long as they represent an actual threat (Gonzalo et al. 2009). So far, we have argued that learning to recognise novel predators allows prey to balance the conflicting pressures associated with successful predator avoidance and a suite of other behavioural activities. To date, the majority of studies have focused on the presence of learning abilities and on the mechanisms and selection that shape learning abilities. A poorly understood aspect of the learning equation is ‘how long should prey retain’ acquired information. Several models have addressed the issue of retention of learned responses within the context of foraging decisions (McNamara & Houston 1987; Mangel 1990; Hirvonen et al. 1999). These models generally predict that there should exist a ‘memory retrieval’ window that allows for a flexible response pattern. Under relatively constant environmental conditions, information regarding foraging decisions should be retained longer (i.e. remain within the memory window), while under highly variable environmental conditions, older learned foraging information would be of lower value, hence fall outside this window (i.e. be ‘forgotten’). Such models predict that learned information should only be retained as long as it is relevant (Pravosudov & Clayton 2002; Brydges et al. 2008) and that acquired information that is no longer relevant is forgotten (i.e. no longer capable of eliciting an adaptive behavioural response; Mackney & Hughes 1995). Using this framework, Ferrari et al. (2010b) have proposed an analogous model dealing with learned predator recognition. They argue that the question of how long prey should retain information is equally important in the context of adaptive value as the ability to acquire recognition of novel predators. The retention of information or ‘memory window’ should only exist as long as the information is relevant. Responding to outdated or suboptimal information is costly, as it takes away from time and energy available for other activities such as foraging. Ferrari et al. (2010b) proposed that a suite of extrinsic and intrinsic factors should interact to shape the ‘memory window’ of prey fishes. Extrinsic factors such as high turnover rate of predator communities and high frequency of diet shifts of predators should have the effect of reducing the length of the plastic or flexible ‘memory window’ as individual prey would likely only be at risk of particular

BLBK374-Brown

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Char Count=

Learning about Danger: Chemical Alarm Cues and Threat Sensitivity

71

predators for a limited time frame. Conversely, increased predator encounter rates, predictability of predators and/or probability of predator attacks are extrinsic factors, which would be predicted to extend the memory window. Likewise, intrinsic factors such as increased growth rates, impending life history shifts or morphological antipredator defences should result in a shortened memory window. Slower growth rates, simple life histories or a lack of morphological defences should increase the value of learned information, and hence extend the length of the memory window. Brown et al. (2011b) directly tested this model by manipulating the growth rate of juvenile rainbow trout and testing for the retention of the learned recognition of pumpkinseed odour. Trout were fed either high or low food rations for a period of 7 days (sufficient to induce different growth rates) and then conditioned to recognise the odour of pumpkinseed as a threat. Trout tested for the recognition of pumpkinseed odour 24 hours post-conditioning exhibited similar learned responses, regardless of growth rate (Fig. 4.2A). However, when tested for a learned response 8 days post-conditioning, only those on the low food ration exhibited an antipredator response. Trout fed on the high food ration were no different from distilled water controls (Fig. 4.2A). As a companion study, Brown et al. (in press b) conditioned trout of two size classes (similar to the final size of high vs. low food ration groups from the first study) that had been fed proportionally similar food rations and tested for the retention of pumpkinseed odour 24 hours and 8 days post-conditioning. They reported no difference in the retention of learned information (Fig. 4.2B). These data

20 A. High vs. low-growth rates Change in time moving (seconds)

BLBK374-04

B. Large vs. small initial mass

0

–20

–40

–60

–80

High Low growth rate growth rate

High Low growth rate growth rate

24 hours post-conditioning 8 days post-conditioning

Large initial size

Small initial size

24 hours post-conditioning

Small Large initial size initial size

8 days post-conditioning

Fig. 4.2 Mean (SE) change in time moving for juvenile rainbow trout initially conditioned with trout alarm cue paired with a novel predator (pumpkinseed) odour and subsequently exposed to pumkinseed odour alone. Panel A: Trout on a high versus low growth (5% vs. 1% mean body weight day per day) diet exhibited similar reductions in time spent moving when tested for recognition of pumpkinseed odour 24 hours post-conditioning. However, when tested for recognition 8 days post-conditioning, only trout in the low-growth treatment exhibited recognition of pumpkinseed odour; trout on the high-growth diet were no different from controls (not shown). Panel B: In order to determine if these trends were due to growth rate or absolute size, trout of two size ranges (fed 1% mean body weight day per day) were conditioned and tested as above. Small (∼0.6 g) and large (∼1.8 g) trout exhibited similar responses when tested for recognition on both testing days, suggesting that retention of learned recognition is not influenced by absolute size. Modified from Brown et al. (2011b).

BLBK374-04

BLBK374-Brown

72

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Char Count=

Fish Cognition and Behavior

suggest that growth rate does indeed influence the length of the memory window. A likely proximate mechanism in this case might be that increased growth rates result in increased energy demands, resulting in a shift in threat-sensitive trade-offs in favour of risk-prone behavioural tactics in the case of high growth rate trout. This raises the intriguing possibility of information renewal (Brown & Chivers 2005). Given that predation risk is variable, we might expect that prey should indeed ‘forget’ acquired information that is no longer relevant. But under high-risk conditions (high rates of encounter), we would expect this information to be continually reinforced. The question remains if repeated exposure over time results in enhanced learning opportunities in which the learned response is greater (stronger) than that resulting from a single conditioning event or if the retention is extended, or both. Vilhunen (2006) conditioned hatchery-reared Arctic charr juveniles to the odour of pikeperch (Sander lucioperca, Percidae) which had been fed a diet of Arctic charr once or four times (with 4 days between each conditioning). Vilhunen (2006) reports stronger antipredator responses (relative to unconditioned controls) by charr exposed four times to the predator. In addition, when exposed to a live predator during staged encounters, those that received multiple exposures had a higher probability of survival than did those conditioned a single time. While not a direct test of the hypothesis that repeated exposure enhances intensity and retention of learning, it does suggest that multiple conditionings increase the strength (and possibly retention) of learned information.

4.7

Conservation, management and learning

Here, we have reviewed the latest developments in the field of chemically mediated predator recognition learning, highlighting the incredible degree of sophistication in this learning process. Moreover, we have highlighted the dynamic interplay between acquired predator recognition and threat-sensitive behavioural decision-making in prey fishes. In this final section, we will briefly touch on some conservation and management implications of this work.

4.7.1

Conditioning predator recognition skills

A commonly stated goal of predator training is that it may allow us to ‘teach’ threatened or commercially important species raised in hatcheries to recognise potential predation threats prior to stocking (Brown & Day 2002; Brown & Laland 2003; Bischof & Zedrosser 2009). Hatchery-reared fishes stocked into natural waterways often suffer intense predation pressure (Shively et al. 1996; Henderson & Letcher 2003), particularly within the first days to weeks post-stocking. However, to date, such an approach has met with limited success (Wisenden et al. 2004; Hawkins et al. 2007). For example, Hawkins et al. (2007) conditioned hatchery-reared juvenile Atlantic salmon to recognise pike and released conditioned and unconditioned salmon into a loch in which pike was the major predator of juvenile salmon. They report no difference in survival between the conditioned and unconditioned prey. These results differ from those of Berejikian et al. (1999) that found enhanced survival of Chinook salmon smolts following predator recognition training. One reason for the failure to find increased survival of trained prey may be the issue of retention. Hatchery

BLBK374-04

BLBK374-Brown

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Learning about Danger: Chemical Alarm Cues and Threat Sensitivity

Char Count=

73

fishes are typically fed high-growth diets, possibly leading to reduced retention rates of acquired information (see Section 4.6). Another possibility might be the effects of hatchery selection itself. A growing body of literature shows that hatchery-breeding programmes may actually be selecting for high growth and risk-taking behavioural tactics (Malavasi et al. 2008; Houde et al. 2010). Selection acting on threat-sensitive tactics may reduce the likelihood of retention of responses to learned information. Studies comparing hatchery reared to wild stock conspecifics are needed to address this question.

4.7.2

Anthropogenic constraints

A growing volume of literature demonstrates significant impairment of alarm cue detection and function by prey exposed to sublethal concentrations of anthropogenic pollutants (Schotz et al. 2000; Scott et al. 2003; McPherson et al. 2004; Leduc et al. 2006; Kusch et al. 2008; Tierney et al. 2008). Presumably, an inability to detect alarm cues would result in impaired learning opportunities. Recent studies by Leduc et al. (2004a, 2006, 2010) demonstrate that juvenile salmonids are unable to detect conspecific alarm cues under weakly acidic conditions in laboratory and field trials. Moreover, the ability to learn (Leduc et al. 2004b, 2007a, 2007b) and retain (Smith et al. 2008) predator recognition is likewise impaired under weakly acidic conditions. Moreover, what remains unknown is whether such a sublethal effect on risk assessment and learning has real fitness consequences for prey fishes. Presumably, an inability to assess chemosensory predator cues might lead to increased risk of predation. Such an increase in predation risk may have direct effects (i.e. reduced survival) or indirect effects (reduced foraging opportunity, exclusion to suboptimal habitats or reduced recruitment). Clearly, additional laboratory and (perhaps most importantly) field studies are required to assess the potential impacts of anthropogenic stressors on prey fish populations.

4.7.3

Field-based studies

To date, only a handful of studies have examined learning under fully natural conditions. This represents a critical gap in our understanding of the functional importance of predator recognition learning. Clearly, laboratory studies are important, but they often lack ecological realism and are typically conducted under ‘ideal’ conditions (i.e. well-fed prey, absence of background predation risks). In order to assess the full ecological relevance of chemically mediated learning, additional studies are required to test the degree to which prey fishes rely on learned information under fully natural conditions. For example, one factor that deserves attention is the potential impact of abiotic conditions on chemically mediated learning in wild populations. While Leduc et al. (2007a, 2007b) have shown that juvenile Atlantic salmon can acquire the recognition of novel odours in natural streams, C.J. Macnaughton & G.E. Brown (unpublished data), working with the same population, failed to replicate these findings. One logical difference between these studies is that while Leduc conducted his trials during periods of low water depth and current speeds, Macnaughton & Brown (unpublished data) conducted their studies during 2 years of abnormally high rainfall (leading to increased stream depth and current speeds). This suggests that naturally occurring abiotic cycles may seasonally limit learning opportunities.

BLBK374-04

BLBK374-Brown

May 27, 2011

74

Fish Cognition and Behavior

4.8

Conclusions

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Char Count=

Carefully controlled laboratory studies have shown an exceptionally high degree of sophistication in the learning abilities of prey fishes. Prey fishes can be conditioned to recognise predators based on a single learning event. The prey learns to recognise not only the predator as a threat, but also the level of threat posed by the predator, making it possible for the prey to match the intensity of their antipredator response to the risk posed by the predator. Prey fishes continually update information regarding the risk level of predators and learn the temporal foraging patterns of their predators. Prey fishes can generalise recognition of one predator to other similar species and hence avoid some of the costs associated with learning. We are just beginning to understand how long prey should retain information about predators and how learning operates under natural conditions. In order to assess the full ecological relevance of chemically mediated learning, additional studies are required under fully natural conditions. Ideally, this ecologically relevant information should allow for the planning and implementation of realistic management and conservation programmes.

Acknowledgements We thank Chris Elvidge, Christopher Jackson and James Grant for their helpful comments. Financial support for our research on predator learning was provided by Concordia University, the University of Saskatchewan and NSERC of Canada.

References Alvarez, D. & Nicieza, A.G. (2003) Predator avoidance behaviour in wild and hatchery-reared brown trout: the role of experience and domestication. Journal of Fish Biology, 63, 1565–1577. Acquistapace, P., Hazlett, B.A. & Gherardi, F. (2003) Unsuccessful predation and learning of predator cues by crayfish. Journal of Crustacean Biology, 23, 364–370. Barreto, R.E., Luchiari, A.C. & Marcondes, A.L. (2003) Ventilatory frequency indicates visual recognition of an allopatric predator in Nile tilapia. Behavioural Processes, 60, 235–239. Bass, S.L.S. & Gerlai, R. (2008) Zebrafish (Danio rerio) responds differentially to stimulus fish: the effects of sympatric and allopatric predators and harmless fish. Behavioural Brain Research, 186, 107–117. Berejikian, B.A., Tezak, E.P. & LaRae, A.L. (2003) Innate and enhanced predator recognition in hatchery-reared Chinook salmon. Environmental Biology of Fishes, 67, 241–251. Berejikian, B.A., Smith, R.J.F., Tezak, E.P. et al. (1999) Chemical alarm signals and complex hatchery rearing habitats affect antipredator behaviour and survival of Chinook salmon (Oncorhynchus tshawytscha) juveniles. Canadian Journal of Fisheries and Aquatic Sciences, 56, 830–838. Bischof, R. & Zedrosser, A. (2009) The educated prey: consequences for exploitation and control. Behavioral Ecology, 20, 1228–1235. Blanchet, S., Bernatchez, L. & Dodson, J.J. (2007) Behavioural and growth responses of a territorial fish (Atlantic salmon, Salmo salar, L.) to multiple predatory cues. Ethology, 113, 1061–1072. Blumstein, D. (2006) The multipredator hypothesis and the evolutionary persistence of antipredator behavior. Ethology, 112, 209–217. Boersma, K.S., Ryer, C.H., Hurst, T.P. et al. (2008) Influences of divergent behavioural strategies upon risk allocation in juvenile flatfishes. Behavioral Ecology and Sociobiology, 62, 1959–1968.

BLBK374-04

BLBK374-Brown

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Learning about Danger: Chemical Alarm Cues and Threat Sensitivity

Char Count=

75

Breden, F., Scott, M. & Michel, E. (1987) Genetic differentiation for anti-predator behavior in the Trinidadian guppy, Poecilia reticulata. Animal Behaviour, 35, 618–620. Br¨onmark, C. & Miner, J.G. (1992) Predator-induced phenotypic change in body morphology in crucian carp. Science, 258, 1348–1350. Brown, C. & Day, R. (2002) The future of stock enhancements: bridging the gap between hatchery practice and conservation biology. Fish and Fisheries, 3, 79–94. Brown, C. & Laland, K.N. (2003) Social learning in fishes: a review. Fish and Fisheries, 4, 280– 288. Brown, G.E. & Chivers, D.P. (2005) Learning as an adaptive response to predation. In: P. Barbosa & I. Castellanos (eds) Ecology of Predator–Prey Interactions, pp. 34–54. Oxford University Press, Oxford. Brown, G.E. & Chivers, D.P. (2006) Learning about danger: chemical alarm cues and the assessment of predation risk by fishes. In: C. Brown, K. Laland & J. Krause (eds) Fish Cognition and Behavior, pp 49–69. Blackwell Publishing Ltd., Oxford. Brown, G.E. & Magnavacca, G. (2003) Predator inspection behaviour in a characin fish: an interaction between chemical and visual information? Ethology, 109, 739–750. Brown, G.E. & Smith, R.J.F. (1998) Acquired predator recognition in juvenile rainbow trout (Oncorhynchus mykiss): conditioning hatchery-reared fish to recognize chemical cues of a predator. Canadian Journal of Fisheries and Aquatic Sciences, 55, 611–617. Brown, G.E., Poirier, J.-F. & Adrian, J.C., Jr. (2004) Assessment of local predation risk: the role of subthreshold concentrations of chemical alarm cues. Behavioral Ecology, 15, 810–815. Brown, G.E., Chivers, D.P. & Smith, R.J.F. (1997) Differential learning rates of chemical versus visual cues of a northern pike by fathead minnows in a natural habitat. Environmental Biology of Fishes, 49, 89–96. Brown, G.E., LeBlanc, V.J. & Porter, L.E. (2001) Ontogenetic changes in the response of largemouth bass (Micropterus salmoides, Centrarchidae, Perciformes) to heterospecific alarm pheromones. Ethology, 107, 401–414. Brown, G.E., Bongiorno, T., DiCapua, D.M. et al. (2006a) Effects of group size on the threat-sensitive response to varying concentrations of chemical alarm cues by juvenile convict cichlids. Canadian Journal of Zoology, 84, 1–8. Brown, G.E., Rive, A.C., Ferrari, M.C.O. et al. (2006b) The dynamic nature of antipredator behavior: prey fish integrate threat-sensitive antipredator responses within background levels of predation risk. Behavioral Ecology and Sociobiology, 61, 9–16. Brown, G.E., Ferrari, M.C.O., Malka, P.H. et al. (2011a) Generalization of predators and nonpredators by juvenile rainbow trout: learning what is and what is not a threat. Animal Behaviour. doi: 10.1016/j.anbehav.2011.03.013. Brown, G.E., Ferrari, M.C.O., Malka, P.H., et al. (2011b) Growth rate and retention of learned predator cues by juvenile rainbow trout: faster-growing fish forget sooner. Behavioral Ecology and Sociobiology. doi: 10-1007/s00265-011-1140-3. Brown, G.E., Macnaughton, C.J., Elvidge, C.K. et al. (2009) Provenance and threat-sensitive predator avoidance patterns in wild-caught Trinidadian guppies. Behavioral Ecology and Sociobiology, 63, 699–706. Brydges, N.M., Heathcote, R.J.P. & Braithwaite, V.A. (2008) Habitat stability and predation pressure influence learning and memory in populations of three-spined sticklebacks. Animal Behaviour, 75, 935–942. Chivers, D.P. & Mirza, R.S. (2001) Predator diet cues and the assessment of predation risk by aquatic vertebrates: a review and prospectus. In: A. Marchlewska-Koj, J.J. Lepri & D. M¨uller-Schwarze (eds) Chemical Signals in Vertebrates, Vol. 9, pp. 227–284. Kluwer Academic, New York. Chivers, D.P. & Smith, R.J.F. (1994a) Fathead minnows, Pimephales promelas, acquire predator recognition when alarm substance is associated with the sight of unfamiliar fish. Animal Behaviour, 48, 597–605. Chivers, D.P. & Smith, R.J.F. (1994b) The role of experience and chemical alarm signaling in predator recognition by fathead minnows, Pimephales promelas. Journal of Fish Biology, 44, 273–285.

BLBK374-04

BLBK374-Brown

76

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Char Count=

Fish Cognition and Behavior

Chivers, D.P. & Smith, R.J.F. (1995) Free-living fathead minnows rapidly learn to recognize pike as predators. Journal of Fish Biology, 46, 949–954. Chivers, D.P. & Smith, R.J.F. (1998) Chemical alarm signalling in aquatic predator–prey systems: a review and prospectus. Ecoscience, 5, 338–352. Chivers, D.P., Brown, G.E. & Smith, R.J.F. (1995) Acquired recognition of chemical stimuli from pike, Esox lucius, by brook sticklebacks, Culaea inconstans (Osteichthyes, Gasterosteidae). Ethology, 99, 224–234. Chivers, D.P., Mirza, R.S., Bryer, P.J. et al. (2001) Threat-sensitive predator avoidance by slimy sculpins: understanding the role of visual versus chemical information. Canadian Journal of Zoology, 79, 867–873. Darwish, T.L., Mirza, R.S., Leduc, A.O.H.C. et al. (2005) Acquired recognition of novel predator odour cocktails by juvenile glowlight tetras. Animal Behaviour, 70, 83–89. Dupuch, A., Magnan, P. & Dill, L.M. (2004) Sensitivity of northern redbelly dace, Phoxinus eos, to chemical alarm cues. Canadian Journal of Zoology, 82, 407–415. Ferrari, M.C.O. & Chivers, D.P. (2006a) The role of learning in the development of threat-sensitive predator avoidance: how do fathead minnows incorporate conflicting information? Animal Behaviour, 71, 19–26. Ferrari, M.C.O. & Chivers, D.P. (2006b) The role of latent inhibition in acquired predator recognition by fathead minnows. Canadian Journal of Zoology, 84, 505–509. Ferrari, M.C.O. & Chivers, D.P. (2009) Latent inhibition of predator recognition by embryonic amphibians. Biology Letters, 5, 160–162. Ferrari, M.C.O., Lysak, K. & Chivers, D.P. (2010c) Turbidity as an ecological constraint on learned predator recognition and generalization in a prey fish. Animal Behaviour, 79, 515–519. Ferrari, M.C.O., Messier, F. & Chivers, D.P. (2006b) The nose knows: minnows determine predator proximity and density through detection of predator odours. Animal Behaviour, 72, 927–932. Ferrari, M.C.O., Messier, F. & Chivers, D.P. (2008a) Larval amphibians learn to match antipredator response intensity to temporal patterns of risk. Behavioral Ecology, 19, 980–983. Ferrari, M.C.O., Messier, F. & Chivers, D.P. (2008c) Can prey exhibit threat-sensitive generalization of predator recognition? Extending the predator recognition continuum hypothesis. Proceedings of the Royal Society of London, Series B, 275, 1811–1816. Ferrari, M.C.O., Sih, A. & Chivers, D.P. (2009a) The paradox of risk allocation: a review and prospectus. Animal Behaviour, 78, 579–585. Ferrari, M.C.O., Brown, G.E., Bortolotti, G.R. et al. (2010b) Linking predator risk and uncertainty to adaptive forgetting: a theoretical framework and empirical test using tadpoles. Proceedings of the Royal Society of London, Series B, 277, 2205–2210. Ferrari, M.C.O., Brown, G.E., Messier, F. et al. (2009b) Threat-sensitive generalization of predator recognition by amphibians. Behavioral Ecology and Sociobiology, 63, 1369–1375. Ferrari, M.C.O., Gonzalo, A., Messier, F. et al. (2007) Generalization of learned predator recognition: an experimental test and framework for future studies. Proceedings of the Royal Society of London, Series B, 274, 1853–1859. Ferrari, M.C.O., Trowell, J.J., Brown, G.E. et al. (2005) The role of learning in the development of threat-sensitive predator avoidance by fathead minnows. Animal Behaviour, 70, 777–784. Ferrari, M.C.O., Capitania-Kowk, T. & Chivers, D.P. (2006c) The role of learning in the acquisition of threat-sensitive responses to predator odours. Behavioral Ecology and Sociobiology, 60, 522– 527. Ferrari, M.C.O., Elvidge, C.K., Jackson, C.D. et al. (2010a) The responses of prey fish to temporal variation in risk: sensory habituation or risk assessment? Behavioral Ecology, 21, 532– 536. Ferrari, M.C.O., Vavrek, M.A., Elvidge, C.K. et al. (2008b) Sensory complementation and the acquisition of predator recognition by salmonid fishes. Behavioral Ecology and Sociobiology, 63, 113–121. Foam, P.E., Harvey, M.C., Mirza, R.S. et al. (2005a) Heads up: juvenile convict cichlids rely on chemosensory information to make threat-sensitive foraging decisions. Animal Behaviour, 70, 601–607.

BLBK374-04

BLBK374-Brown

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Learning about Danger: Chemical Alarm Cues and Threat Sensitivity

Char Count=

77

Foam, P.E., Mirza, R.S., Chivers, D.P. et al. (2005b) Juvenile convict cichlids (Archocentrus nigrofasciatus) allocate foraging in response to temporal variation in predation risk. Behaviour, 142, 129–144. Foote, C.J. & Brown, G.S. (1998) Ecological relationship between freshwater sculpins (genus Cottus) and beach-spawning sockeye salmon (Oncorhynchus nerka) in Iliamna Lake, Alaska. Canadian Journal of Fisheries and Aquatic Sciences, 55, 1524–1533. Gibson, A.K. & Mathis, A. (2006) Opercular beat rate for rainbow darters Etheostoma caeruleum exposed to chemical stimuli from conspecific and heterospecific fishes. Journal of Fish Biology, 69, 224–232. Gilliam, J.F. & Fraser, D.F. (2001) Movement in corridors: enhancement by predation threat, disturbance, and habitat structure. Ecology, 82, 124–135. Godin, J.-G.J. & Smith, S.A. (1988) A fitness cost of foraging in the guppy. Nature, 333, 69–71. Golub, J.L., Vermette, V. & Brown, G.E. (2005) The response of pumpkinseed sunfish to conspecific and heterospecific chemical alarm cues under natural conditions: the effects of stimulus type, habitat and ontogeny. Journal of Fish Biology, 66, 1073–1081. Gonzalo, A., L´opez, P. & Mart´ın, J. (2009) Learning, memory and apparent forgetting of chemical cues from new predators by Iberian green frog tadpoles. Animal Cognition, 12, 745–750. Gotceitas, V. & Brown, J.A. (1993) Substrate selection by juvenile Atlantic cod (Gadus morhua): effects of predation risk. Oecologia, 93, 31–37. Griffin, A.S. (2004). Social learning about predators: a review and prospectus. Learning and Behavior, 32, 131–140. Griffin, A.S., Evans, C.S. & Blumstein, D.T. (2001) Learning specificity in acquired predator recognition. Animal Behaviour, 62, 577–589. Hawkins, L.A., Armstrong, J.D., & Magurran, A.E. (2007) A test of how predator conditioning influence survival of hatchery-reared Atlantic salmon, Salmo salar, in restocking programmes. Fisheries Management and Ecology, 14, 291–293. Hawkins, L.A., Magurran, A.E. & Armstrong, J.D. (2004) Innate predator recognition in newlyhatched Atlantic salmon. Behaviour, 141, 1249–1262. Hawkins, L.A., Magurran, A.E. & Armstrong, J.D. (2008) Ontogenetic learning of predator recognition in hatchery-reared Atlantic salmon, Salmo salar. Animal Behaviour, 75, 1663–1671. Helfman, G.S. (1989) Threat-sensitive predator avoidance in damselfish–trumpetfish interactions. Behavioral Ecology and Sociobiology, 24, 47–58. Henderson, J.N. & Letcher, B.H. (2003) Predation on stocked Atlantic salmon (Salmo salar) fry. Canadian Journal of Fisheries and Aquatic Sciences, 60, 32–42. Hirvonen, H., Ranta, E., Rita, H. et al. (1999) Significance of memory properties in prey choice decisions. Ecological Modelling, 115, 177–189. Hirvonen, H., Ranta, E., Piironen, J. et al. (2000) Behavioural responses of na¨ıve Arctic charr young to chemical cues from salmonid and non-salmonid fish. Oikos, 88, 191–199. Houde, A.L.S., Fraser, D.J. & Hutchings, J.A. (2010) Reduced anti-predator responses in multigenerational hybrids of farmed and wild Atlantic salmon (Salmo salar L.). Conservation Genetics, doi: 10.1007/s10592-009-9892-2. Jachner, A. (2001) Anti-predator behaviour of na¨ıve compared with experience juvenile roach. Journal of Fish Biology, 59, 1313–1322. Jachner, A. & Rydz, M.A. (2002) Behavioural response of roach (Cyprinidae) to different doses of chemical alarm cues (Schreckstoff). Archieves Hydrobiologica, 155, 369–381. Jord˜ao, L.C. & Volpato, G.L. (2000) Chemical transfer of warning information in non-injured fish. Behaviour, 137, 681–690. Kats, L.B. & Dill, L.M. (1998) The scent of death: chemosensory assessment of predation risk by prey animals. Ecoscience, 5, 361–394. Killen, S.S. & Brown, J.A. (2006) Energetic costs of reduced foraging under predation threat in newly hatched ocean pout. Marine Ecology Progress Series, 321, 255–266. Kim, J.-W., Brown, G.E., Dolinsek, I.J. et al. (2009) Combined effects of chemical and visual information in eliciting antipredator behaviour in juvenile Atlantic salmon Salmo salar. Journal of Fish Biology, 74, 1280–1290.

BLBK374-04

BLBK374-Brown

78

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Char Count=

Fish Cognition and Behavior

Kristensen, E.A. & Closs, G.P. (2004) Anti-predator response of naive and experienced common bully to chemical alarm cues. Journal of Fish Biology, 64, 643–652. Kusch, R.C., Mirza, R.S. & Chivers, D.P. (2004) Making sense of predator scents: investigating the sophistication of predator assessment abilities of fathead minnows. Behavioral Ecology and Sociobiology, 55, 551–555. Kusch, R.C., Krone, P.H. & Chivers, D.P. (2008) Chronic exposure to low concentrations of waterborne cadmium during embryonic and larval development of zebrafish results in long-term hindrance of antipredator responses to alarm cues. Environmental Toxicology and Chemistry, 27, 705–710. Leduc, A.O.H.C., Kelly, J.M. & Brown, G.E. (2004a) Detection of conspecific chemical alarm cues by juvenile salmonids under neutral and weakly acidic conditions: laboratory and field tests. Oecologia, 139, 318–324. Leduc, A.O.H.C., Ferrari, M.C.O., Kelly, J.M. et al. (2004b) Learning to recognize novel predators under weakly acidic conditions: the effects of reduced pH on acquired predator recognition by juvenile rainbow trout (Oncorhynchus mykiss). Chemoecology, 14, 107–112. Leduc, A.O.H.C., Roh, E., Harvey, M.C. et al. (2006) Impaired detection of chemical alarm cues by juvenile Atlantic salmon (Salmo salar) in a weakly acidic environment. Canadian Journal of Fisheries and Aquatic Sciences, 63, 2356–2363. Leduc, A.O.H.C., Roh, E., Breau, C. et al. (2007a) Learned recognition of a novel odour by wild juvenile Atlantic salmon, Salmo salar, under fully natural conditions. Animal Behaviour, 73, 471–477. Leduc, A.O.H.C., Roh, E., Breau, C. et al. (2007b) Effects of ambient acidity on chemosensory learning: an example of an environmental constraint on acquired predator recognition in wild juvenile Atlantic salmon (Salmo salar). Ecology of Freshwater Fishes, 16, 385–394. Leduc, A.O.H.C., Roh, E., Macnaughton, C.J. et al. (2010) Ambient pH and the response to chemical alarm cues in juvenile Atlantic salmon: mechanisms of reduced behavioral responses. Transactions of the American Fisheries Society, 139, 117–128. Lima, S.L. & Bednekoff, P.A. (1999) Temporal variation in danger drives anti-predator behavior: the predator risk allocation hypothesis. American Naturalist, 153, 649–659. Lima, S.L. & Dill, L.M. (1990) Behavioral decisions made under the risk of predation: a review and prospectus. Canadian Journal of Zoology, 68, 619–640. Lima, S.L. & Steury, T.D. (2005) Perception of predation risk: the foundation of nonlethal predatorprey interactions. In: P. Barbosa & I. Castellanos (eds) Ecology of Predator–Prey Interactions, pp. 166–188, Oxford University Press, Oxford. Mackney, P.A. & Hughes, R.N. (1995) Forgaging behaviour and memory window in sticklebacks. Behaviour, 132, 1241–1253. Malavasi, S., Georgalas, V., Mainardi, D. et al. (2008) Antipredator responses to overhead fright stimuli in hatchery-reared and wild European sea bass (Dicentrarchus labrax L.) juveniles. Aquaculture Research, 39, 276–282. Mangel, M. (1990) Dynamic information in uncertain and changing worlds. Journal of Theoretical Biology, 146, 317–332. McNamara, J.M. & Houston, A.I. (1987) Memory and the efficient use of information. Journal of Theoretical Biology, 125, 385–395. Magurran, A.E. (1989) Acquired recognition of predator odour in the European minnow (Phoxinus phoxinus). Ethology, 82, 216–233. Magurran, A.E. (2005) Evolutionary Ecology: The Trinidadian Guppy. Oxford Series in Ecology and Evolution. Oxford University Press, Oxford. Mathis, A. & Smith, R.J.F. (1993a) Fathead minnows (Pimephales promelas) learn to recognize pike (Esox lucius) as predators on the basis of chemical stimuli in the pike’s diet. Animal Behaviour, 46, 645–656. Mathis, A. & Smith, R.J.F. (1993b) Chemical labelling of northern pike, Esox lucius, by the alarm pheromone of fathead minnows, Pimephales promelas. Journal of Chemical Ecology, 19, 1967–1979.

BLBK374-04

BLBK374-Brown

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Learning about Danger: Chemical Alarm Cues and Threat Sensitivity

Char Count=

79

McPherson, T.D., Mirza, R.S. & Pyle, G.G. (2004) Responses of wild fishes to alarm chemicals in pristine and metal-contaminated lakes. Canadian Journal of Zoology, 82, 694–700. Mirza, R.S. & Chivers, D.P. (2000) Predator-recognition training enhances survival of brook trout: evidence from laboratory and field-enclosure studies. Canadian Journal of Zoology, 78, 2198–2208. Mirza, R.S. & Chivers, D.P. (2001) Chemical alarm signals enhance survival of brook charr, Salvelinus fontinalis, during encounters with predatory chain pickerel, Esox niger. Ethology, 107, 989–1006. Mirza, R.S., Mathis, A. & Chivers, D.P. (2006) Does temporal variation in predation risk influence the intensity of anti-predator responses? A test of the risk allocation hypothesis. Ethology, 112, 44–51. Nilsson, P.A. & Br¨onmark, C. (2000) Prey vulnerability to a gape-limited predator: behavioural and morphological impacts on northern pike piscivory. Oikos, 88, 539–546. Olson, M.H. (1996) Ontogenetic niche shifts in largemouth bass: variability and consequences for first-year growth. Ecology, 77, 179–190. Olson, M.H., Mittelback, G.G. & Osenberg, C.W. (1995) Competition between predator and prey: resource-based mechanisms and implication for stage-structured dynamics. Ecology, 76, 1758–1771. Pravosudov, V.V. & Clayton, N.S. (2002) A test of the adaptive specialization hypothesis: population differences in caching, memory and the hippocampus in black-capped chickadees (Poecile atricapilla). Behavioral Neuroscience, 116, 515–522. Reebs, S. (1999) Time-place learning based on food but not on predation risk in a fish, the inanga (Galaxias maculates). Ethology, 105, 361–371. Reiechert, S.E. (2005) Patterns of inheritance of traits associated with predator foraging behavior. In: P. Barbosa & I. Castellanos (eds) Ecology of Predator–Prey Interactions, pp. 55–76. Oxford University Press, Oxford. Schotz, N.L., Turelove, N.K., French, B.L. et al. (2000) Diazinon disrupts antipredator and homing behaviors in Chinook salmon (Oncorhynchus tshawytscha). Canadian Journal of Fisheries and Aquatic Sciences, 57, 1911–1918. Scheurer, J.A., Berejikian, B.A., Thrower, F.P. et al. (2007) Innate predator recognition and freight response in related populations of Oncorhynchus mykiss under different predation pressure. Journal of Fish Biology, 70, 1057–1069. Scott, G.R., Sloman, K.A., Rouleau, C. et al. (2003) Cadmium disrupts behavioural and physiological responses to alarm substance in juvenile rainbow trout (Oncorhynchus mykiss). Journal of Experimental Biology, 206, 1779–1790. Shively, R.S., Poe, T.P. & Sauter, S.T. (1996) Feeding response by northern squawfish to a hatchery release of juvenile salmonids in the Clearwater River, Idaho. Transactions of the American Fisheries Society, 125, 230–236. Sih, A. (1992) Prey uncertainty and the balancing of antipredator and foraging needs. American Naturalist, 139, 1052–1069. Sih, A., Ziemba, R. & Harding, K.C. (2000) New insights on how temporal variation in predation risk shapes prey behavior. Trends in Ecology and Evolution, 15, 3–4. Smith, J.J., Leduc, A.O.H.C. & Brown, G.E. (2008) Chemically mediated learning in juvenile rainbow trout. Does predator odour pH influence intensity and retention of acquired predator recognition? Journal of Fish Biology, 72, 1750–1760. Smith, M.E. & Belk, M.C. (2001) Risk assessment in western mosquitofish (Gambusia affinis): do multiple cues have additive effects? Behavioral Ecology and Sociobiology, 51, 101–107. Smith, R.J.F. (1997) Avoiding and deterring predators. In: J.-G.J. Godin (ed) Behavioural Ecology of Teleost Fishes, pp. 163–190. Oxford University Press, Oxford. Sneddon, L.U., Braithwaite, V.A. & Gentle, M.J. (2003) Novel object test: examining nociception and fear in the rainbow trout. The Journal of Pain, 4, 431–440. Stankowich, T. & Coss, R.G. (2007) The re-emergence of felid camouflage with the decay of predator recognition in deer under relaxed selection. Proceedings of the Royal Society of London, Series B, 274, 175–182.

BLBK374-04

BLBK374-Brown

80

May 27, 2011

10:40

Copyeditor’s Name:

Trim: 244mm X 172mm

Char Count=

Fish Cognition and Behavior

Tierney, K.B., Sampson, J.L., Ross, P.S. et al. (2008) Salmon olfaction is impaired by an environmentally realistic pesticide mixture. Environmental Science and Technology, 42, 4996–5001. Vavrek, M.A. & Brown, G.E. (2009) Threat-sensitive responses to disturbance cues in juvenile convict cichlids and rainbow trout. Annales Zoologica Fennici, 46, 171–180. Vavrek, M.A., Elvidge, C.K., DeCaire, R. et al. (2008) Disturbance cues in freshwater prey fishes: do juvenile convict cichlids and rainbow trout respond to ammonium as an ‘early warning’ signal? Chemoecology, 18, 255–261. Vilhunen, S. (2006). Repeated antipredator conditioning: a pathway to habituation or to better avoidance? Journal of Fish Biology, 68, 25–43. Vilhunen, S. & Hirvonen, H. (2003) Innate antipredator response of Arctic charr (Salvelinus alpinus) depend on predator species and their diet. Behavioral Ecology and Sociobiology, 55, 1–10. Werner, E.E. & Gilliam, J.F. (1984) The ontogenetic niche and species interactions in size-structured populations. Annual Reviews in Ecology and Systematics, 15, 393–425. Wisenden, B.D. & Chivers, D.P. (2006) The role of public chemical information in antipredator behaviour. In: F. Ladich, S.P. Collins, P. Moller, & B.G. Kapoor (eds) Fish Chemoreception, pp 259–278. Science Publisher, Enfield, NH. Wisenden, B.D., Chivers, D.P. & Smith, R.J.F. (1995) Early warning in the predation sequence: a disturbance pheromone in Iowa darters (Etheostoma exile). Journal of Chemical Ecology, 21, 1469–1480. Wisenden, B.D., Klitzke, J., Nelson, R. et al. (2004) Predator-recognition training of hatchery-reared walleye (Stizostedion vitreum) and a field test of a training method using yellow perch (Perca favescens). Canadian Journal of Fisheries and Aquatic Sciences, 61, 2144–2150. Yl¨onen, H., Kortet, R., Myntti, J. et al. (2006) Predator odor recognition and antipredator response in fish: does the prey know the predator diel rhythm? Acta Oecologica, 31, 1–7. Zhao, X., Ferrari, M.C.O. & Chivers, D.P. (2006) Threat-sensitive learning of predator odours by a prey fish. Behaviour, 143, 1103–1121.

Learning about Danger: Chemical Alarm Cues and ...

May 27, 2011 - release of juvenile salmonids in the Clearwater River, Idaho. Transactions of the American Fisheries. Society, 125, 230–236. Sih, A. (1992) Prey uncertainty and the balancing of antipredator and foraging needs. American. Naturalist, 139, 1052–1069. Sih, A., Ziemba, R. & Harding, K.C. (2000) New insights ...

235KB Sizes 1 Downloads 148 Views

Recommend Documents

Degradation of chemical alarm cues under natural ... - Springer Link
Oct 25, 2007 - level of accuracy of the cues for risk assessment may depend on the ... antipredator response to the pond water containing alarm cues 5 min ...

Embedding cues about travel time in schematic maps
slow in terms of distance on the map per minute of travel time. In a schematic map ... eight times as long as Den Haag C–Den Haag HS, and slightly longer than ...

Detecting Semantic Uncertainty by Learning Hedge Cues
Model (HMM) with a specific tag set to label the sentence at the word level. .... E the end of a cue phrase, and O the outside of a cue phrase. The topology of our ...

Severe weather detector and alarm
Jul 21, 2005 - 307 as provided in 37 CFR 1.570(e) for ex parte reexamina tions, or the ...... scales. A display 36 indicates radio signal strength by pro gressive ...

danger - Singer
mensaje de error. Cuando se exhiba un mensaje de error, solucione el problema siguiendo las instrucciones a continuación. 1. Si se pisa el pedal, mientras no ...

Gender Clues and Cues
The Internet allows the process of ''doing gender'' (West & Zimmerman, 1987) to be examined in ways previously ... for a successful interaction, as well as into lay theories of the cues to ..... varied, but many participants chose to discuss classes.

Cues, constraints, and competition in sentence processing
sentence processing, significant controversies remain over the nature of the underlying ...... Psychology: Learning, Memory, and Cognition, 16, 555-568. Fisher ...

Cheap Magnetic Door Alarm Sensors Window Sensor Alarm Home ...
Cheap Magnetic Door Alarm Sensors Window Sensor Al ... ion 90Db Sound Free Shipping & Wholesale Price.pdf. Cheap Magnetic Door Alarm Sensors ...

Epidermal 'alarm substance' - CiteSeerX
Aug 7, 2007 - master culture. Cultures were ... correlation between percid club cell number and degree of ..... greater risk of disease than those at a distance. Perhaps the .... Ferrari, M. C. O. & Chivers, D. P. 2006 Learning threat- sensitive ...

Alarm Flowchart.indd
tinue to call the designated numbers on your phone list—this should include your neighbors, so they can call the police too, and be good witnesses. You must instruct your company to do this (and tell your neighbors what to do if they get that call)

Learning about non-predators and safe places: the ... - Springer Link
Jan 4, 2011 - as during their embryonic development, and to use this information later in ... rapid form of conditioning contrasts with the systematic improvement .... within the framework of generalizing predators versus non- predators or the ...

PDF Learning About Learning Disabilities, Fourth ...
... in relation to the education and development of pupils with learning disabilities. ... Fourth Edition For android by , Download and read Learning About Learning ... Edition by , Learning About Learning Disabilities, Fourth Edition For ios by }.

This day has been about learning about yourself and ...
Canada is a country where freedom of expression is a right. .... “People like you have no business here” once to a person of colour or a woman, for the employee to .... opportunity in order to counter the effects of systemic discrimination.

danger a bangkok.pdf
danger a bangkok.pdf. danger a bangkok.pdf. Open. Extract. Open with. Sign In. Main menu. Displaying danger a bangkok.pdf.

This day has been about learning about yourself and ...
Name: . LEGAL CONSIDERATIONS ... If, in any of the five social areas above, a person faces discrimination on any of these grounds, then she or he ... age—18-65 years (employment); 16+ years (accommodation); 18+ years (all other areas).

Listening to Students About Learning
system. But students do not need reports and headlines to understand how ... Too often, community college students taking basic skills classes have been ...... director for an educational consulting firm, and has held various administrative.

Learning About Healthy Living
In order to give consumers the best chance at successful quitting, it is preferable that ...... brand smoked. Smoking ...... Walk while you talk on a cordless phone.

CROSS-DOMAIN LEARNING ABOUT COMPLEX ...
individual and collaborative settings. The learning supports ... novel ideas and tools, and new ways of comprehending old phenomena, which involve patterns.