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- Materials and methods
1. Olfactory predator search processes differ fundamentally to those based on vision, particularly when odour cues are deposited rather than airborne or emanating from a point source. When searching for visually cryptic prey that may have moved some distance from a deposited odour cue, cue context and spatial variability are the most likely sources of information about prey location available to an olfactory predator.
2. We tested whether the house mouse (Mus domesticus), a model olfactory predator, would use cue context and spatial variability when searching for buried food items; specifically, we tested the effect of varying cue patchiness, odour strength, and cue–prey association on mouse foraging success.
3. Within mouse- and predator-proof enclosures, we created grids of 100 sand-filled Petri dishes and buried peanut pieces in a set number of these patches to represent visually cryptic ‘prey’. By adding peanut oil to selected dishes, we varied the spatial distribution of prey odour relative to the distribution of prey patches in each grid, to reflect different levels of cue patchiness (Experiment 1), odour strength (Experiment 2) and cue–prey association (Experiment 3). We measured the overnight foraging success of individual mice (percentage of searched patches containing prey), as well as their foraging activity (percentage of patches searched), and prey survival (percentage of unsearched prey patches).
4. Mouse foraging success was highest where odour cues were patchy rather than uniform (Experiment 1), and where cues were tightly associated with prey location, rather than randomly or uniformly distributed (Experiment 3). However, when cues at prey patches were ten times stronger than a uniformly distributed weak background odour, mice did not improve their foraging success over that experienced when cues were of uniform strength and distribution (Experiment 2).
5. These results suggest that spatial variability and cue context are important means by which olfactory predators can use deposited odour cues to locate visually cryptic prey. They also indicate that chemical crypsis can disrupt these search processes as effectively as background matching in visually based predator–prey systems.
- Top of page
- Materials and methods
The outcomes of predator–prey interactions have a major influence on both the ecology of predators and the dynamics of their prey (Tinbergen, Impekoven & Franck 1967; Lima 2002). To better understand how predators find their prey, many recent studies have modelled optimum predator movement strategies, including variations of random and Lévy walks, nearest-neighbour and trajectory-directed searching (e.g. Higgins & Strauss 2004; Viswanathan et al. 1999; Bartumeus 2009; Reynolds 2010). However, there is abundant evidence for strong selection on enhanced sensory capabilities in the game of detection and evasion between predator and prey, meaning that cues of prey activity are likely to be of fundamental importance in the search strategies of predators (Conover 2007).
Understanding the differences between direct and indirect cues of prey activity is essential to understanding their role in predator search. Much of the work modelling predator movements considers scenarios where detection and localization of prey occur simultaneously (Ruxton 2009), i.e. where predators rely upon direct visual detection of prey (e.g. Higgins & Strauss 2004; Viswanathan et al. 1999; Bartumeus 2009; Reynolds 2010; Tinbergen, Impekoven & Franck 1967). These models represent movement patterns that maximize rates of prey encounter. However, active prey often also emit abundant indirect cues, for which predator movement strategies that maximize information gain may be more profitable (e.g. Vergassola, Villermaux & Shraiman 2007). For example, UV sensing raptors forage in patches with high concentrations of UV visible urine marks secreted by their vole prey (Koivula & Korpimaki 2001); the searching raptors aim to increase information gain which inevitably precedes prey encounter.
Olfactory detection of prey is a particularly widespread, indirect mode of searching for prey used by a diverse range of predators. Animals inescapably emit body odours that provide clues to their presence and location, and many predatory animals are physiologically well equipped to exploit these cues (Conover 2007). Many potential prey species also intentionally use chemical communication for social or sexual intraspecific signalling, and predators can eavesdrop on these cues as illegitimate receivers (Zuk & Kolluru 1998). Often, terrestrial mammals deposit odour cues onto surfaces in their environment (either intentionally when signalling or unintentionally when resting), and then move elsewhere (e.g. see Hughes & Banks 2010). These deposited olfactory cues may persist long after the donor animal’s departure, thus encountering an odour cue is only the first step in the search process of olfactory predators. They must then use information within the spatial context of that deposited odour cue to locate their prey, a very specific type of search process, which to our knowledge has not been studied within the literature covering animals tracking either aquatic (e.g. Atema 1996; Ide et al. 2006; Webster & Weissburg 2009), or airborne (e.g. Carde & Willis 2008; Reynolds et al. 2009; Riffell, Abrell & Hildebrand 2008) odour plumes, or in visually based models of predator search. As all cues are spatially variable, information about prey location is likely embedded within different features of this variation (Plotnick 2007; Vergassola, Villermaux & Shraiman 2007). Indeed, a lack of variation in potential cues provides no information to searching predators; this is the basis of camouflage or background matching (Stevens & Merilaita 2009), which has been extensively studied in visual systems (e.g. Kettlewell 1955; Ruxton, Sherratt & Speed 2004; Merilaita & Lind 2005). More recently, olfactory background matching has been recognized in invertebrate systems; for example, Mechanitis polymnia larvae are defended against predatory ants by the close match between the chemical make-up of their cuticular lipids and those of their host plant (Henrique, Portugal & Trigo 2005). Similarly, Biston robustum caterpillars are visually cryptic on their host plant, but their cuticular chemicals are also very similar to those of the plant; this chemical crypsis prevents ant attack even after antennal contact has been made (Akino, Nakamura & Wakamura 2004). Additionally, chemical camouflage of female moth pheromone plumes by broadcast artificial pheromones effectively disrupts moth mating systems (Carde & Minks 1995), suggesting that, as in visual systems, olfactory cues must be sufficiently spatially variable to be distinguished from their background by a searcher.
Spatial variability, or ‘patchiness’ of an odour cue may simply represent a clumped spatial distribution of the odour cue, or it may result from differences in cue strength. Patchiness and variable strength of odour cues may be attributed to repeated visitation or low mobility of individuals (e.g. at a nest site; Banks, Norrdahl & Korpimaki 2000), from multiple animals (e.g. through intraspecific signal receiving; Hughes, Kelley & Banks 2009), or prolonged exposure to the environment (as aged cues vary in strength and chemical composition; e.g. Buesching, Waterhouse & Macdonald 2002). For a foraging predator, therefore, patchy, strong prey odour cues potentially equate to a higher probability of prey encounter. A tight spatial association between cues and prey is also predicted to be necessary for predators to associate cues with prey location (Pearce 1997), as cue–prey association is a measure of the cue: reward ratio, or how reliably cues indicate prey presence.
We tested whether these three factors – (i) patchiness and (ii) strength of odour cues, and (iii) cue–prey association – provide information to foraging predators using olfaction to locate prey. Optimal foraging theory (Charnov 1976; MacArthur & Pianka 1966) suggests that a predator should be able to improve its foraging success by using such information to update its search strategy (Dall et al. 2005). Whilst optimal foraging theory has been criticized for being too simplistic (Pierce & Ollason 1987), it is reasonable to assume that predators behave so as to maximize energy intake for minimum cost. Such costs may be measured in time, energy expenditure, or other ‘effort’ (Emlen 1966). This ‘decision-making’ process for a foraging predator can be summarized as the reward for effort ratio, or the overall ‘foraging success’ of the predator. For generalist predators, search strategies and prey preferences are predicted to change when preferred prey become scarce (Dukas & Kamil 2001) and foraging success falls.
In three experiments, we attempted to manipulate the foraging success of a model olfactory predator (Mus domesticus) by varying the application of prey odour cues to the environment. Peanuts, a highly valuable ‘prey’ item for mice, were hidden in sand to exclude visual detection. Peanut oil provided prey odour cues, and we varied the spatial distribution of odours to test our prediction that the mice would use this variation to locate the peanuts and improve their foraging success. Rodents were chosen as a model predator as they are known to use a highly developed olfactory system to locate food (Slotnick 2001), including both mobile and immobile prey, and inanimate vegetable matter. As most models of predator search are based on immobile prey, and we assume that mice use olfaction in a similar way to search for all food items, we felt the choice of peanuts as a model prey item was justified by the need to preclude the visual, auditory and vibrotactile cues that live prey such as invertebrates would emit (similarly, to limit foraging kiwis to olfactory search modes, Cunningham, Castro & Potter 2009, killed and buried their mealworm prey).
To test the importance of (i) patchiness in an odour cue, we varied the application of prey odours to simulate varying degrees of conspicuousness to an olfactory predator. We applied single-strength odour only to prey locations (making prey conspicuous), distributed prey odour uniformly on all patches (making prey match their background) or applied no additional odour (control). Thus, if mice use the patchiness of the odour cue to locate prey, then where odour cues are patchy they should be able to increase their foraging success above that expected if searching at random. Where cues match their background, they become effectively camouflaged to a foraging predator, and our hypothesis predicts that mice should only find peanut prey at random, as no information about prey location would be available to them.
To test the importance of (ii) odour strength, we created patchiness in odour concentration by altering the prey cue–background odour strength ratio. If mice direct their search towards locations with stronger odour as a means of locating prey, they should achieve higher foraging success in treatments where prey odours are stronger than background odours. When background odour strength approaches that of the prey odour, the cue becomes uniform and foraging success is predicted to be that of a random search, as in (i). To test whether mice would switch foraging strategies when searching for preferred prey became too costly, in this experiment we also provided pearl barley grains as easily available, but lower value alternate prey.
In our third experiment, we assessed the importance of (iii) cue–prey association for mouse foraging success. We used kernel analysis to determine the spatial scale at which mice were foraging in the second experiment, and then used this information to manipulate the level of spatial association between odour cues and ‘prey’ in the third experiment. Our hypothesis, that spatial association between cue and prey is important for predators to associate information in odour cues with probable prey location, predicts that where the cue–prey association is low mice should experience decreased foraging success, as lower reward rates will weaken cue-following behaviours. Conversely, where the association is strong, mice should be more successful.