Trade-offs between sight lines and escape habitat determine spatial strategies of risk management by a keystone herbivore

Animals living in risky environments can manage the risk by at least four inter-related mechanisms (Brown and Kotler 2004): time allocation (honing activity periods to times of low risk), space use (choosing habitats and foraging patches where risk is low, e.g., Creel et al. 2005), apprehension (reducing risk by being aware or vigilant), and foraging tenacity (maintaining harvest rates in the presence of danger). To these we can add social benefits of grouping behaviours and cooperation. The allocation of each mechanism will depend on such characteristics as the temporal pattern of risk (Lima and Bednekoff 1999; Higginson et al. 2012), the forager’s state (McArthur et al. 2014; Monclús et al. 2015; Bannister and Morris 2016), the density and spatial distribution of competing individuals (China et al. 2008; Dupuch et al. 2014), trade-offs between resource quality and risk (Lima and Dill 1990; McArthur et al. 2014), the functional and numerical responses of predators (Dupuch et al. 2014), and the scale of environmental variation (e.g., Druce et al. 2006; Heithaus and Dill 2006; Hodson et al. 2010). The joint characteristics of predators and prey and their interaction with spatial variation in habitat thus dictate the prey species’ landscape of fear—their spatially explicit map of predation risk (Brown et al. 1999; Altendorf et al. 2001; Laundré et al. 2001; van der Merwe and Brown 2008; Laundré et al. 2010). Although the literature on fearful foraging is extensive, we do not generally know the conditions under which foragers favour one strategy over another or how those strategies might vary with spatial scale.

Advancing our understanding of risk management requires an evaluation of each mechanism, and its potential interactions with others, in a natural and spatially variable environment. We thus designed experiments on snowshoe hares (Lepus americanus Erxleben, 1777) to explore how spatial variation influences their risk management strategies and to determine how habitat can modulate behavioural mechanisms that reduce predation risk.

We set the stage by describing our study system and its appropriateness for assessing risk management. Next, we link risk with concepts of fine and coarse-grained foraging. We use those concepts to generate a priori expectations enabling risk management by hares. We then describe three experiments that we used to test each expected outcome. We analyze each experiment separately and synthesize the results to yield a complete picture of hares’ perception of, and behavioural responses to, spatial variation in predation risk. We conclude with a short discussion of the insights that snowshoe hare foraging provides to our understanding of risk management.

Snowshoe hares are an appropriate model system for studies of risk management for at least four inter-dependent reasons. Hares seek refuge when not foraging, they forage singly, they are deeply embedded as a keystone species in climate-induced predator–prey cycles with Canada lynx (Lynx canadensis Kerr, 1792) (Krebs et al. 2001a, 2001b; Krebs 2011; Yan et al. 2013), and they occupy a stressful but time-dependent landscape of fear (Boonstra et al. 1998; Sheriff et al. 2009; Krebs et al. 2014). Hares in fragmented or patchy landscapes are especially vulnerable to predation (Wolff 1980; Wirsing et al. 2002), and virtually all hares meet death at the teeth and talons of their predators (Krebs et al. 2014). Hares reduce risk in winter by time allocation. They forage from dusk through dawn and tend to avoid open areas during moonlit nights (Gilbert and Boutin 1991). Little is known, however, about the ways in which hares might integrate other mechanisms into a spatially dependent risk-management strategy.

With these points in mind, we chose two sites located within alder (Alnus viridis (Chaix) DC.) dominated shrublands on a 40 ha area regenerating from agriculture and forest harvest in northwestern Ontario, Canada (48°19′N, 89°47′W). Alder habitat is preferred by snowshoe hares in winter because it shelters animals from the elements and provides refuge from predators (Pietz and Tester 1983).

Site 1 represented fine grain where there was a sharp ecotone between dense 3 m tall alder and an abandoned, open, 2.6–4.8 m wide logging trail. Site 2 represented coarse grain where large patches (>30 m wide) of open grassland–old field with sparsely distributed 3 m tall red pine (Pinus resinosa Aiton) saplings were embedded along a similarly sharp ecotone within the alder matrix (Morris 2005). Snowshoe hares consumed the few shrubs and saplings within less dense areas of alder, the more numerous shrubs along the ecotone toward more open habitat, and lower branches of pine in otherwise open areas. Hares did not browse the mature alder. Hares tend to avoid open habitat when possible and forage there with less intensity than in adjacent forest habitat (Morris 2005; Hodson et al. 2010) presumably because they perceive a greater risk of predation (Keith et al. 1984; Smith et al. 1988; Hik 1995; Rohner and Krebs 1996).

Hares and their heavily used runways were abundant in both sites. Runways crossed over the linear logging trail (yielding fine-grained use along runways) but not the larger open-field patches (coarse grain) where their sporadic tracks were scattered towards individual foraging (e.g., red pine) opportunities. We verified that the hares lived in a fearful landscape by documenting the presence of predator species including lynx, red fox (Vulpes vulpes fulvus (Desmarest, 1820)), coyote (Canis latrans Say, 1823), grey wolf (Canis lupus Linnaeus, 1758), fisher (Martes pennanti (Erxleben, 1777)), pine marten (Martes americana (Turton, 1806)), American mink (Neovison vison (Schreber, 1777)), and several large owl species (via direct observation, wildlife camera photos during our experiments at the same stations used for observing hares, or spoor). Crepuscular great gray owls (Strix nebulosa Forster, 1772) posed a significant risk to hares near dawn and dusk, whereas more nocturnal horned owls (Bubo virginianus (Gmelin, 1788)) and barred owls (Strix varia Barton, 1799) also hunted hares overnight. Wing marks in snow, blood, and body parts confirmed that two hares were killed by avian predators at our study transects immediately after the experiments concluded (one each at the fine-grained and coarse-grained scale, both at the boundary between open and alder habitats).

We can gain insight into the tools available for managing predation risk by contemplating the interdependence between each mechanism and the spatial scale of resource patches (Brown 1999). Scale will depend on the spatial acuity and movement capacity of individuals, as well as constraints imposed by spatial patterns in the foraging landscape.

We can formalize our insights by contemplating the optimal harvest rate expected from prey individuals exposed to risk. We follow Gilliam and Fraser (1987) by considering a forager that can choose to remain in a safe refuge or forage in two habitats that differ in risk. We further assume that the forager maximizes its survival subject to procuring some minimal amount of resource necessary to maintain its energetic state (e.g., snowshoe hares surviving winter). Under these conditions,where QHR is quitting-harvest rate, the instantaneous foraging rate obtainable when the last forager leaves the resource patch; C is the metabolic cost of foraging; μ is the instantaneous likelihood of being killed by a predator while in the patch; P is the probability of surviving the foraging period; ϕ_t is the marginal fitness of engaging in alternative activities (including time spent in the refuge); ϕ_F is the marginal value of survival (the only direct component of fitness for non-reproducing individuals); and ∂F/∂E is the marginal value of fitness in terms of energy (Brown 1992).

Imagine that the foraging species occupies a patchy environment where its movement characteristics cause individuals to encounter habitat and resource patches in the proportions in which they occur (a fine-grained environment, Levins 1962). Individuals can nevertheless alter their space use by allocating more time to safe habitat and foraging patches than they do to risky ones. Their ability to do so will increase as the scale of the environment moves towards coarse grain (defined as the scale where individuals have the option to occupy one habitat only, Levins 1962; e.g., use only the safe habitat and its resource patches). We thus expect, if individuals manage risk by time allocation, that hares will prefer the safe alder habitat over risky open areas and that their preference for alder will be greater at the coarse-grained scale.

Vigilance reduces risk, so if hares manage risk with vigilance, we expect higher vigilance in risky as opposed to safe habitat. If risk is related to cover, then vigilance should be reduced in experiments that supplement safety with cover.

Exposure to risk at the fine-grained scale is directly proportional to the frequency of the two habitats. The potential to preferentially use safe habitat is increased at coarse scales, and thus mean vigilance might be reduced. But if risk increases with the size of risky patches, then hares should be more vigilant in risky habitat at the coarse-grained scale than at the fine-grained scale.

Environmental grain will also influence foraging tenacity. To predict the outcome, assume that time spent vigilant reduces risk, is traded off against active foraging time, and that the quitting-harvest rate, for a given level of resource, decreases as the amount of time spent in the foraging patch increases. The expected quitting-harvest rates (eq. (1)) will be equal between equally accessible safe and risky places, but not the density of the resource when the final forager leaves the patch (giving-up density (GUD), Brown 1988). Vigilant foragers will thus leave risky patches at a higher GUD because they have allocated less of their available foraging time to resource harvest.

Each mechanism can, in theory, respond to experiments that enhance the safety of foraging patches through additional cover. If, for example, hares are less vigilant at foraging sites provisioned with supplemental cover, then the GUD should be lower at sites supplied with additional cover. Finally, if risk in open areas increases with distance from safety, then vigilance in the open habitat should increase and GUD should also increase with distance from alder.

Knowing these expectations, we designed experiments to assess foraging and vigilance in identical resource patches located at different scales in relatively safe versus risky habitats. We did so by taking advantage of the repeated travel along snow-packed runways by snowshoe hares in winter. We contrasted foraging between risky open spaces and the safe refuge afforded by thick alder-covered habitats (Pietz and Tester 1983). Several other studies confirm that hare survival is higher in and near to densely vegetated habitats than in habitats with sparse cover (e.g., Hodson et al. 2010; Feierabend and Kielland 2015).

We were able to include the spatial scale of safety by locating sampling stations along runways that either crossed (fine-grained exposure; runways crossing the logging trail) or did not cross (coarse grain; a few tracks but no packed runways in old-field openings) the two habitats. We then alternated safe versus risky foraging opportunities by adding supplemental cover to resource patches in the riskier open habitat. We designed each experiment such that the supplemental cover in risky habitat mimicked the normal safety that hares would experience in the safety of alder. The design did not allow us to test hypotheses on the effects of additional safety in both habitats.

Hares are thus the tool we use to test theory predicting the effects of scale on the strategies that prey use to manage their perceived risks of predation. We emphasize that our tests of scale refer only to strategies hares might employ when faced with fine versus coarse-grained foraging alternatives. Our research was not designed to evaluate how those strategies might change from one landscape or population to another. Our emphasis is on strategies, not the behaviour of individual hares or their population dynamics. Most studies on snowshoe hares, including those that contemplate space use (Wolff 1980; Wirsing et al. 2002), predation risk (Keith et al. 1984; Smith et al. 1988; Hik 1995) and state-dependent foraging (e.g., Murray 2002) are dedicated towards their use as a model for understanding population cycles (Krebs et al. 2001a, 2001b; Preisser 2009; Krebs 2011, and references therein). Although risk management is applicable to cyclical dynamics, hares at any point in a cycle should adopt strategies of risk management that maximize fitness. We assess predictions emerging from that assumption.

In summary, hares might manage risk by the following expectations. We aim to determine which subset of these strategies they actually use, and they are either confirmed or rejected in the Results section.

The most striking feature of our experiments is that the hares rejected six of eight possible mechanisms to manage predation risk. Each rejection can be accounted for if hares trade off the benefits of hiding spots and escape routes afforded by alder against the cost of less effective vigilance associated with dense and tangled branches that diminish sight lines (e.g., Banks et al. 1999; Embar et al. 2011; Iribarren and Kotler 2012a, 2012b). Accordingly, hares were more vigilant in the alder than in the open. In the open, predators should, for a given level of vigilance, be more easily detected. So as long as hares can quickly dart into the safety of alder, less vigilance in the open may not translate into increased risk.

Compensation of foraging risk by the sight line versus escape habitat trade-off will fail if foraging patches exceed the distance required for safe retreat into dense cover. Hares should respond to the reduced safety through higher levels of vigilance and less tenacious foraging. Our experiments, for both vigilance and GUDs (e.g., Fig. 5), verify this prediction and suggest that the threshold distance for complete compensation is as short as 4 m. The result is remarkably consistent with Hodson et al.’s (2010, p. 613) threshold estimate of ≥4 m by hares foraging in canopy gaps.

Even so, you might wonder why GUDs were not different between control patches in the open versus the supplemental cover treatment. More images were observed under supplemental cover, so the cumulative foraging by hares should have been more intense (lower GUDs). This prediction assumes, however, that hares are equally apprehensive in both scenarios. Apprehension, defined as reduced attention to foraging, can reduce food intake and patch assessment (e.g., Hochman and Kotler 2007). Apprehension that distracts attention from foraging (such as through resting, listening, or head-down scanning) can reduce the accuracy of a prey individual’s resource assessment and reduce the value of knowledge gained while foraging (Dall et al. 2001). Each effect will increase the GUD relative to a safer less apprehensive alternative.

Snowshoe hare escape behaviour (measured by the tortuosity of their escape paths) is relatively stereotyped (Hodges et al. 2014) and they rely heavily on crypsis, immobility, and concealment to reduce detection by predators (Zimova et al. 2014). It is thus possible that hares employ a secondary trade-off between crypsis (immobility) and foraging. Supplemental cover may interfere with predators’ ability to see motionless hare body forms masked by white pelage in a snow-covered landscape. Cryptic immobility nevertheless increases apprehension, and thus reduces foraging efficiency for stationary hares under supplemental cover. Hares cannot easily conceal their body shape in the open and crypsis is less effective, so hares forage more rapidly and efficiently. Our experiments suggest that the two effects, immobility that produces apprehensive foraging under cover versus more time-efficient foraging in the open, counter-balance one another (no difference in GUDs). This hypothesis awaits testing with more detailed video data.

Our data, and those by Morris (2005) showing reduced GUDs with distance from cover, are contrary to Hodson et al. (2010) who did not find an effect of distance on browse diameters in forest gaps. Hodson et al. (2010) proposed that the absence of a distance effect may have been associated with flat harvest rates on jack pine boughs or by evidence that hares, at least on some occasions, carry harvested boughs to safer habitat. Although we cannot irrevocably rule out these possibilities, it does not appear that they can account for our data. Flat harvest curves are unlikely because we (and Morris 2005) found distance-dependent differences in GUDs. Consumption of boughs primarily in safe habitat is similarly unlikely because residual pine needles and tracks documented that most boughs were consumed in close proximity to the foraging patch.

Our data suggest that risk management by snowshoe hares is much more sophisticated than the intuition and evidence (Keith et al. 1984; Smith et al. 1988; Hik 1995; Rohner and Krebs 1996) that hares perceive greater risk in open than in covered habitat. Risk depends on scale (and particularly distance from safety) and can be ameliorated by a multiplicity of compensating strategies. Hares compensate for distance-dependent risk in open habitat with increasing vigilance. Vigilance is only partially effective at reducing scale-dependent risk so hares also forage more apprehensively for less reward (higher GUD).

Our results also add insight to Hodges and Sinclair’s (2005) conclusion that snowshoe hares in food-enriched sites biased their browsing toward dense cover. Hodges and Sinclair (2005) compared travel distances, foraging time (fecal density), habitat use, and natural browse among predator exclosure (N = 1), exclosure plus food (N = 1), food supplemented (N = 2), and control (N = 4) sites. They did not acquire simultaneous estimates of anti-risk behaviours such as vigilance. Our study and those of Morris (2005) and Hodson et al. (2010) reveal clear patterns of risk-sensitive behaviours that can assist in averting predation. But it is not common-sense cause and effect whereby safe foraging induces deleterious effects on nutrition, physiology, reproduction, and survival (e.g., Hodges and Sinclair 2005, p. 280). Rather, strategies of risk management emerge through scale-dependent foraging options. When the scale of risk is fine-grained, hares reveal that trade-offs between the effectiveness of vigilance (sight lines) and escape habitat compensate for differences in predation risk. Each foraging patch yields similar profit. But as the scale shifts towards coarse grain, increased vigilance with distance from safety fails to fully compensate predation risk, so prey also reduce their foraging effort. A study concentrating on a subset of strategies, or one scale of heterogeneity, would fail to assess the multiple spatial and habitat-contingent strategies that prey can use to defuse the risk of predation. More importantly, it would run the risk of misinterpreting cause and effect and thus misinform the connections linking behaviour with its population dynamic and community consequences.

We thank D. Start and S. Moreth for their help in quantifying thousands of camera images, comments from colleagues that improved this contribution, and Canada’s Natural Sciences and Engineering Research Council for its ongoing support of DWM’s research program in evolutionary ecology. This project was conducted under Ontario Ministry of Natural Resources Wildlife Scientific Collector’s Authorizations 1056013 and 1061540.