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Anti-predator behaviours are commonly observed amongst prey populations. These behaviours can be costly, however, because they generally take away time from other potentially fitness-enhancing behaviours (Brown & Kotler 2004). For example, prey may have to avoid the richest resource patches when trading-off energy gains for safety (Lima & Dill 1990; Lima 1998). Bison (Bison bison L.) have been observed to decrease their selection of optimal food items in response to predation risk, resulting in lower rates of energy gains (Fortin & Fortin 2009). Prey also uses vigilance to avoid being surprised by a predator, a behaviour that tends to decrease foraging rate (Lendrem 1983; Brown 1999). In general, the level of anti-predator behaviour should increase with the risk of mortality, the prey's energy state, and its fitness, and decrease as its marginal value of energy rises (Brown 1999; Brown & Kotler 2004).
The co-evolution of predators and prey may result in prey developing chronic anti-predator responses (Schmitz, Krivan & Ovadia 2004). Because of the high costs of anti-predator behaviours, a specific chronic response may not always maximize fitness, and it may be beneficial for the prey to adjust its level of anti-predator behaviour based on its current perception of the threat level. A prey should exhibit its strongest anti-predator behaviour in brief and infrequent high-risk situations, whereas allocation of anti-predator effort to high-risk situations should decrease as they become more frequent or lengthy (Lima & Bednekoff 1999; Creel et al. 2008). Chronic and ephemeral behavioural responses should ultimately be dictated by factors such as the mobility of predators, their hunting mode (Schmitz, Krivan & Ovadia 2004) and the prey escape tactics (Wirsing, Cameron & Heithaus 2010). An optimal prey response may not simply use either chronic or ephemeral anti-predator behaviours, but may use a combination of both. Such a combination of anti-predator responses can then be used to characterize a prey's ‘landscape of fear’, in which ‘hills’ and ‘valleys’ are defined by the predation risk and related in particular to spatial patterns in habitat features (Laundré, Hernández & Ripple 2010). Given the possibility of chronic and ephemeral behavioural responses to risk, the landscape of fear could vary broadly, from static to highly dynamic according to the spatial and temporal scales of the prey's perception of risk. A comprehensive assessment of the impact of predators should therefore involve the quantification of a prey's perceptual range (or the range within which signs of predators can trigger a response), together with the time that the perceived changes in threat last (Lima & Dill 1990; Lima & Zollner 1996).
Several studies have examined the impact of the presence of predators at fine temporal and spatial scales. For example, elk tend to leave food-rich grasslands and moved into the protective cover of wooded areas when wolves were present in the same drainage on the same day (Creel et al. 2005). They also increase their movement rate when wolves are within 5 km from its location during the previous 4 h (Proffitt et al. 2009), a response that may vary with the presence of calves, group size and season (Liley & Creel 2008). Elk become more vigilant when wolves are present within 3 km from their location (Liley & Creel 2008). Likewise, zebra (Equus quagga B.) display intense vigilance when lions (Panthera leo L.) are within 2 km (Périquet et al. 2012), and individuals become less abundant on grasslands during the night if lions have also been present during the past 24 h (Fischhoff et al. 2007). In general, the presence of lions within a 2-km fixed radius during the previous 24 h influences habitat preferences of both grazers and browsers (Valeix et al. 2009). Most of these fine-scale studies (i) approximate perception of predator presence by a binary presence/absence of predator (ii) in a fixed radius and (iii) over a fixed temporal window around the prey locations. This coarse level of information on prey's assessment of predator presence might not suffice to evaluate the role of anti-predator behaviours on the spatial dynamics of prey and, more generally, on food web properties.
Here, we evaluated the behavioural response of forest-dwelling woodland caribou (Rangifer tarandus caribou L.) and moose (Alces alces L.) to the passage of grey wolves, in the Côte-Nord region of Québec during winter and summer. Forest-dwelling caribou is considered threatened across the Canadian boreal forest (COSEWIC 2006), and the conservation of this ecotype has a strong impact on forest management. Food resources are not considered as a limiting factor for these caribou, and, instead, their population dynamics would be driven by top-down forces (Courtois et al. 2007). Given the importance of risk effects on top-down systems, a better understanding of the perception of predator presence by caribou, and their reaction to it, can provide valuable information of high conservation value. The response of moose to predation risk can also have consequences on caribou conservation, because a high hunting success of wolves on moose can lead to an increase in the wolf population, which in turn can be detrimental to the caribou populations (Wittmer et al. 2007).
We assessed nonlethal effects of wolves on caribou and moose by means of using step selection functions (SSF, Fortin et al. 2005) integrating information on both animal movements and habitat selection, along with an index of predator presence. This indexes a discounting function of both time since and distance from passage. The discounting function was assessed using optimization techniques applied to the SSFs, which identify the temporal scales and spatial extents over which caribou and moose respond to the recent passage of wolves in summer and winter. Our results highlight the dynamic aspect of the predator–prey game, which characterized by a combination of chronic and ephemeral anti-predator responses.
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- Materials and methods
- Supporting Information
We applied optimization techniques to movement analysis to demonstrate that both caribou and moose respond to the passage of wolves by displaying ephemeral responses, the nature of which differs importantly depending on species and season. Our analysis, however, does not identify the exact distance and time during which prey is capable of detecting the passage of a wolf. Given the discrete nature of our field data (locations recorded at 4 h intervals), the cues triggering the response of caribou and moose might have been detected at much closer distances and finer temporal scales than reported by our analysis, especially in summer when they travel at a faster speed (Basille et al. 2013). What our analysis does reveal is that, once large herbivores acquire a signal of predator presence, their movement and habitat selection can be altered over rather large distances and long time-scales.
Both caribou and moose showed seasonal differences in their response to the passage of wolves. Prior passage of wolves had an impact on both species at longer temporal scales, but finer spatial scales, in winter than in summer. First, caribou and moose could roam over larger areas during the 4-h relocation interval in summer than in winter because of their faster travel speed in the absence of snow (Basille et al. 2013). Therefore, they should be able to detect the presence of wolves at farther distances in summer than winter during the relocation interval, especially given that wolves also tend to range over larger areas in summer than in winter. Second, the vulnerability of prey increases with snow depth (Wikenros et al. 2009), and caribou and moose might get fitness benefits by having more acute responses to predation risk in winter than in summer.
Seasonal differences in the influence of wolf were stronger on movement decisions of caribou than moose (Table 2). This difference is somewhat surprising given that wolves generally focus their hunt on moose than caribou (Hayes et al. 2000; Joly & Patterson 2003). The difference might reflect a higher risk of mortality for caribou than moose following an encounter with wolves (Mech & Boitani 2010). Alternatively, radio-collared moose might have crossed fewer wolf paths compared with collared caribou because moose travelled less than caribou during both seasons.
We detected four types of behaviours following the passage of a predator, within the distance and time resulting from the optimization algorithm: lack of response in habitat selection, increased selection of safe land cover types, decreased selection of risky land cover types, and increased selection of food-rich areas.
Both species displayed a lack of response for a number of land cover types. For example, caribou avoided closed-canopy mature conifer in winter and in summer, as observed by Courbin et al. (2009), regardless of the whereabouts of wolves. Moose selected mixed and deciduous forests, regardless of the season and of the changes in wolf spatial dynamics. Mixed and deciduous forests are food-rich areas for moose all year long (Sæther & Andersen 1990). Although these stands are also selected by wolves (Courbin et al. 2009), they are organized in small patches in the study area, a patchiness that might reduce the risk of co-occurrence of the two species, even if both species are making selective use of these stands. This is consistent with other studies suggesting that a complex habitat structure reduces the predation rate (Warfe & Barmuta 2004) and favours the stability of predator-prey systems (Hauzy et al. 2010).
Caribou also increased their selection of safe land cover types in response to prior passage of wolves. They generally avoided open areas in summer, probably because they are areas of low forage density. On the other hand, they increased their selection of this land cover type when wolves had been within 4·7 km during the past 1·5 days. This reaction might be somewhat similar to caribou selecting lakes in winter (Fortin et al. 2008), which is considered an anti-predator response that would allow them to detect predator from far distances. Given that wolves tend to select open areas in summer (Courbin et al. 2009), the adaptive value of this decision by caribou remains unclear. Predation risk is a function of the probability of encounter with a predator, the probability that an attack takes place given an encounter and the probability of dying from that attack (DeCesare 2012). To obtain a net reduction in predation risk from using open areas, the decrease in detection time would have to outweigh the potential increase in encounter probability with the predator.
Moose avoided open conifer stands with lichen in summer following the passage of a wolf. Open conifer stands with lichen are never a key land cover type for moose, presumably because they do not contain as much food as other land cover types (Crête & Courtois 1997) and because they are selected by wolves (Courbin et al. 2009). Accordingly, the avoidance of open conifer stands with lichen became even stronger in areas that wolves had visited recently. This behavioural response is consistent with an anti-predator response to temporary elevated risk. Moving away from predators and selecting land cover types avoided by them have obvious advantages for prey in terms of the predator–prey space race, because it should increase their chances of being spatially separated (Sih 2005).
Finally, caribou increased their selection of open conifer stands with lichen in winter following the passage of wolves and moved towards wolf paths. As we indicated previously, wolves select open conifer stands with lichen during this season (Courbin et al. 2009; Houle et al. 2010). The long-term response of caribou is to reduce their selection of those stands in areas of high wolf density (Labbé 2012). In this context, our analyses appear to indicate that caribou could benefit from information on the recent passage of wolves to assess the importance of the threat and then adjust their use of food-rich areas based on their assessment of the current risk. Predator inspection has been reported for a broad range of taxa (Dugatkin & Godin 1992; FitzGibbon 1994; Brown & Dreier 2002; Nocera, Taylor & Ratcliffe 2008), and although approaching the predator (or areas where a predator had been present) can increase the risk of an attack, it can also provide information that ultimately could yield a net fitness gain. An important piece of information appears to be whether or not predators are still in the area. We found that once wolves had left an area, the probability that they would return was relatively low for ∼5 days, at which point, the probability of wolves returning remained constant over time (Fig. 6c) and therefore relatively high and poorly predictable. The recent passages of wolves thus seem to inform caribou on the distribution of their predator, thereby providing them with an opportunity to lower their anti-predator behaviour by making greater use of the richest lichen patches. As the information becomes outdated, anti-predator behaviour becomes more acute again. A puzzling aspect of our findings is how prey learns in the first place that they can use an area because wolves have left the areas. Perhaps the observed avoidance of a given area needs to be frequently reinforced by cues of predator presence; otherwise, prey returns rapidly to the area. This hypothesis requires further investigation. Overall, we suggest that the decrease in the selection of lichen-rich patches by caribou in winter indicates that the lower level of selection for open conifer stands with lichen reflects a long-term trade-off between food acquisition and predation risk and might be seen as a chronic anti-predator response.
Few studies consider that prey and predators are both in motion in their analyses (Lima 2002; Sih 2005; Hammond, Luttbeg & Sih 2007). Our study accounts for such dynamic distributions, and as such, it offers a rare assessment of how a combination of short- and long-term anti-predator responses to predation risk drives the spatial dynamics of large herbivores. These adaptive responses translate into dynamic patterns of habitat selection and movements, which in turn yield highly heterogeneous landscapes of fear (Figs 3 and 5). The results have implications on food web properties. For example, trophic cascades can result from long-term avoidance of food-rich habitats that are subject to high predation risk (e.g. Schmitz, Krivan & Ovadia 2004; Fortin et al. 2005), a response that was also observed for caribou in winter (Labbé 2012). However, caribou increased their selection of open conifer stands with lichen for a short period of time when wolves had recently left the area, which should reduce the potential for a trophic cascade. Our study outlines the complexity of the temporal scales over which prey respond to the passage of a predator. These scales vary amongst species and between seasons for a given prey. Predictions of food web dynamics should benefit by accounting for such variations in anti-predator behaviours.