Reactive response to predation risk affects foraging time of hares, yet not their phosphorus intake

Antipredator responses could affect nutrient intake, which could lead to nutritional de�cits. However, little is known about the antipredator response of small herbivores because most are nocturnal or crepuscular and therefore very di�cult to study in the �eld. Therefore we experimentally assessed the effect of a reactive response to predation risk on the nutrient (i.e., phosphorous) intake of the European hare (Lepus europaeus) by using three different playback sounds. Additionally, we studied the time spent being costly vigilant, the time spent foraging, and the vegetation height in which the hares were present by using accelerometers and GPS. Our results showed that elevated predation risk from our playback experiment did not affect the 1) phosphorus intake, 2) time spent being costly vigilant, and 3) time spent in tall vegetation. However, elevated predation risk did increase the time spent foraging. Possibly hares spent more time foraging with an increased predation risk because hares cannot seek refuge from predators. Additionally, the effect on phosphorus intake could be weak because phosphorous intake does not bene�t a �ight escape, while the reactive response acts late in the predation sequence limiting the effect on hare ecology. Prey anti-predator responses seem strongly related to the escape tactics of prey species that can differ between different habitats and the time of the day. More detailed �eld studies are necessary to get a better insight into species’ anti-predator-food tactics.


INTRODUCTION
For predators to successfully feed on prey, they need to complete different sequential stages in the predation process, namely: search, detect (or encounter), chase, capture, handle and consume prey (Bateman et al. 2014).At each stage of the predation process, prey in their turn can use antipredator responses to reduce predation risk (Uetz and Hieber 1994; Creel and Creel 2002;Creel 2018).In particular, prey invests most antipredator effort in avoiding detection or becoming chased (Fuiman and Magurran 1994; but see Bateman et al. 2014), as the chance to avoid being killed presumably decreases further in the predation sequence (Endler 1991).
To reduce the probability of becoming detected by a predator, prey may avoid habitats with predators (Lima and Dill 1990), hide in dens (Olsson et al. 2008), spend more time in habitats that provide cover (e.g., tall vegetation) (Grubb, 2005;Hopewell et (Stevens and Ruxton 2019).For example, elk moved to more dense vegetation to decrease their predation risk, after wolves arrived in Yellowstone National Park (Gude and Garrott 2003;Creel and Winnie 2005;Gude et al. 2005).Similarly, European hare spend more time in tall vegetation when red foxes were more active (Weterings et al. 2018).
To reduce the probability of becoming chased, prey may spend more time vigilant to improve detection of approaching predators (Creel et al. 2017).Besides, prey can escape before the chase (Cooper and Frederick 2007) or select habitats that allow escaping at a later time (Heithaus et al. 2009), or show a predator that it has been seen (Holley 1993) to avoid becoming chased.For example, zebras increased their time spent vigilant when lions were present (Periquet et al. 2012).Furthermore, when predation risk increased, guinea pigs increased their time spent vigilant when the distance to cover increased (Cassini 1991).Similarly, during high predation risk, gerbils forage close to bush microhabitat, to allow escape into cover (Kotler et al. 1991).
Presumably, predation risk imposes constraints on prey by increasing the need to make alternative choices (Hawlena and Perez-Mellado 2009).The use of antipredator behavior depends on the context (Périquet et al. 2017) and comes with a cost, such as physiological costs (Zanette et al. 2014), movement costs (Weterings et al. 2016), foraging costs (Creel et al. 2017), nutritional costs (Christianson and Creel 2010) or energetic costs (MacLeod et al. 2014).Insight into the costs of antipredator behavior on nutrient intake is important, because prolonged nutritional de cits could eventually lead to a reduced birth-and survival rate (Creel and Christianson 2008;Cresswell 2010).
Increased vigilance can come at a cost to nutrient intake (i.e., costly vigilance) when an animal stops processing food (i.e., chewing, lubricating & swallowing), while scanning the environment (Hik 1994;Abramsky et al. 2002;Fortin et al. 2004;Creel 2018).For example, dark-eyed juncos foraged more on whole seeds when predation risk increased, to allow visual scanning of the surrounding, even though whole seeds were less pro table than seeds without a shell (Lima 1988).In contrast to prey in short vegetation, animals in tall vegetation stop processing food to improve auditory detection of approaching predators (Benhaiem et al. 2008), as visual detection of approaching predators in tall vegetation is di cult (Hopewell et al. 2005; Riginos and Grace 2008).As a consequence, spending time in tall vegetation can come at a cost to nutrient intake when the food in tall vegetation is nutrient-poor (i.e., in nitrogen and phosphorus) (Shipley 2007; but see Hodges and Sinclair 2003) or contains a high percentage of bers that increases the handling time of food (Barboza et al. 2009).Nevertheless, prey can often compensate for the costs of antipredator behavior (Luttbeg et al. 2003).To compensate for the low-quality food or the increase in handling time, herbivores in tall vegetation could spend more time foraging (i.e., searching & cropping) to ingest su cient nutrients (Heuermann et al. 2011).Additionally, as a result of stress, prey can adjust the composition of their diet, thereby changing the types of nutrients or energy ingested (Hawlena and Schmitz 2010b).However, animals may only show compensatory behavior in a speci c context.For example, European hares in tall vegetation only spend more time foraging when the vegetation contains low edible biomass (Weterings et al. 2018).
Prey that better match their defense towards predators more often focus on escape tactics (i.e.reactive response), while species that poorly match their defense towards the predator more often focus on avoidance tactics (i.e.proactive response) (Dellinger et al. 2019).Prey that is effective in avoiding predator detection is often less effective in escaping predators (Creel et al. 2014).Creel (2018) suggested that predation risk that is unpredictable and of short duration (i.e., an encounter) does not affect the nutrient intake of prey.However, this has not been tested yet for cryptic herbivores (Creel 2018), because nutrient intake for nocturnal or crepuscular herbivores is very di cult to observe or measure in the eld, especially when in cover (Ashby 1972).
Therefore, we experimentally tested the short-term effect of a predator-prey encounter on the nutrient intake of a small herbivore.To understand this effect, we additionally studied the time spent costly vigilant, the vegetation height in which the animals were present, and the time spent foraging.
As a case study, we focused on the European hare (Lepus europaeus) as a cryptic herbivore, which is a widespread species in North-western Europe (NDFF 2020).The European hare is a solitary non-central place forager that is common in open grassland areas (Barnes and Tapper 1986) but can use tall vegetation as cover or resting places (Neumann et al. 2011).Predation risk strongly affects hare behavior and spatial use (Weterings et al. 2016;2019).European hares spend approximately half of their active time being vigilant (Lush et al. 2015) and use of crypsis or a ight response to escape predators (Focardi and Rizzotto 1999).
We hypothesize that after a predator-prey encounter in short vegetation, hares 1) spend more time in tall vegetation that provides more cover (Neumann et al. 2011;Weterings et al. 2018) (Table 1).As a consequence, in contrast to short vegetation, hares 2) spend more time costly vigilant in tall vegetation (Monclús and Rödel 2008;Trefry and Hik 2009) to improve auditory detection of approaching predators (Benhaiem et al. 2008).Following, in contrast to short vegetation, hares 3) will spend more time foraging in tall vegetation (Shipley 2007) to compensate for any losses in nutrient intake (Heuermann et al. 2011).
Therefore, overall, we hypothesize that a predator-prey encounter does not affect the nutrient intake of the European hare.Moreover, for species that rely more on sound than sight and smell, such as hares (Łopucki et al. 2017), playbacks are generally more meaningful in assessing prey response to encounters (Jarvis 2004).Furthermore, playbacks may often be more alarming than visual cues (Cohen et al. 2009).Hares that participated in the playback experiment were selected based on their spatial distribution to maximize the distance between individual hares treated.It was assumed that hares within 300 meters of each other were assigned the same treatment.We used playbacks of conspeci c alarm calls of hares instead of playbacks of predators, because prey often responds more strongly to conspeci c alarm calls than to playbacks of predators (Schmidt et 1992).Playbacks were played for forty seconds at 20:00 hours (CET), because hare activity and foraging behavior peaks during that time (Hansen 1996), thereby increasing the chance of triggering anti-predator responses during foraging.Audio boxes were placed 50 meters south from the core location of GPS activity at 20:00 hours on previous days (mean distance between boxes = 1117 ± 1882 m), with the largest speaker directed towards the north to standardize distribution of playbacks in different directions.

COSTLY VIGILANCE AND FORAGING TIME
To investigate time spent costly vigilant and time spent foraging, we recorded accelerometer (ACC) data of collared hares in three axes, every two minutes for 24 hours a day with a frequency of 10.54 Hz per axis.To interpret the accelerometer data, a hand-held video camera was used to record behavior of collared hares in the eld.We recorded behavior of eight hares; six hares from this study site and two hares from a similar coastal dune habitat on Schiermonnikoog island.The six hares in our two study sites were observed when hares were expected to be the most visible and active (7:00-10:00 and 13:00-16:00).We recorded a total of 9225 seconds of behavior (mean 1153 sec, SD ± 1509).

VEGETATION HEIGHT
To investigate the vegetation height, we measured the vegetation height at ve orthogonal locations in six random 2 x 2 m quadrants in each of the 20 vegetation types (n = 120).Next, we recorded GPS locations of individual hares every 12 minutes for 24 hours a day, and used ArcGIS (version 10.7) to link the GPS location of the hares with the average height of the vegetation type at that location.

NUTRIENT INTAKE
To test the effect of predation risk on nutrient intake, the available food quantity (i.e., edible biomass) and nutrient concentrations of each vegetation type were measured.We collected samples of edible biomass for seven of the most important plant species in the diet of hares (i.e.(Resheff et al. 2014).We used the time sitting alert as a proxy for the time spent costly vigilance, and cropping time as a proxy for foraging time.We chose cropping time instead of chewing time to determine the foraging time, because cropping time was classi ed with higher precision and recall than chewing time.Even though there is a trade-off between cropping time and chewing time (Spalinger and Hobbs 1992), nutrient intake increases when chewing time as well as cropping time increases (Gross et al. 1993).

VEGETATION HEIGHT
To calculate the fraction of time hares spent in a certain vegetation height in an hour, the GPS location of the hares was linked to a high-resolution GIS map (1:5000) of the different vegetation types (Everts et al. 2008;Everts et al. 2009).However, whenever hares were present in multiple vegetation types within an hour, we calculated the weighted vegetation height.

NUTRIENT INTAKE
We calculated the relative nutrient intake of hares by multiplying the time spent cropping by the nutrient concentration in the edible biomass (Fig. 1).
The average edible biomass (g/m 2 ) was calculated for each vegetation type by summing the amount of edible biomass (g) of all plant species in one square meter of a vegetation type up to 50 cm in height.
The average content of each nutrient (N, P, Ca) + NDF in every vegetation type was calculated by averaging the percentage of nutrients in the edible biomass present in the vegetation type, weighted by their volume per square meter up to 50 cm in height (see Weterings et al. 2018).We chose phosphorus as a proxy for nutrient intake because phosphorus is one of the most important nutrients for hares (Miller 1968).Besides, even though all nutrient concentrations were strongly correlated with each other (Spearson's rho > 0.91, p < 0.001), the phosphorus concentration correlated the least with the mean vegetation height of a vegetation type (r = 0.45, p = 0.03, n = 22).

DATA ANALYSIS
We explored the data using the protocol of Zuur et al. (2010) to identify potential statistical problems.Because all males were juveniles, we could not investigate the effect of life-stage in our analysis.We used Generalized Additive Mixed Models (GAMMs) to test the effect of the treatment on the fraction of time spent costly vigilant by hares (N = 1390) (i.e., beta distribution), the average vegetation height (N = 1227) in which the hares were present (i.e., Gaussian distribution), the fraction of time spent cropping (N = 1342) (i.e., beta distribution) and on the nutrient intake by hares (N = 1342) (i.e., Gaussian distribution) using the 'GAMM4' R-package (version 0.2-6).GAMMs describe highly nonlinear relationships between response and explanatory variables using smoothing functions (Guisan et al. 2002).In total we investigated 168 hours (7 days times 24 hours) of response by the hares.All four global models included the treatment, the control variables sex, body weight, temperature, wind speed, rainfall, prior treatment, time of day and the interaction treatment*time of day.Because hares shift between short and tall vegetation during a day at dusk and dawn (Schai-Braun et al. 2012), we included time of day and the interaction treatment*time of day in the analysis.The variable 'prior treatment' was added to control for any carryover effects by the treatment the day before.The prior treatment on the rst day of a treatment block was categorized as no treatment.Additionally, we transformed 1) the amount of rainfall into presence-absence data, because the data mainly showed zeros, and 2) nutrient intake (log(x + 1)) because the data were right-skewed.Vegetation height was excluded from the nutrient intake model and the time spend cropping model due to multicollinearity.We found no multicollinearity between the other control variables.All continuous covariates were standardized to compare the effect size within and between models.Hare ID and treatment day block within hare ID were considered random factors.We excluded one hare from the analysis, because we did not identify its sex.A GAMM with cyclic smoother was used to model the effects during the time of day, to avoid discontinuity between subsequent days.Temporal autocorrelation among subsequent hours within a time block was addressed by including an autocorrelation structure, modeling a decreasing degree of autocorrelation with increasing temporal distance between data points.We chose an autoregressive (AR(1)) covariance type for individual time blocks at each site as this resulted in the best t.The Akaike Information Criterion (AIC) was used to select the nal model using the 'base' R-package (version 3.6.1).We validated the nal model by using the 'MuMIn' R-package (version 1.43.17) to plot the residuals against the predicted value and all the covariates.

RESULTS
Compared to a playback of sheep and no playback, hares only spent more time foraging after an alarm call of a conspeci c hare (Table 2).
Tab. 2 Results of the generalized linear mixed models on the effect of type of treatment on the costly vigilance, vegetation height in which the hares were present, foraging time, and nutrient intake of European hare (Lepus europaeus).The results are based on 55 treatment day blocks, twelve days and nine hares in two study sites.The sample size is in hours.

VEGETATION HEIGHT
We found that the playback of conspeci c alarm calls did not affect the average vegetation height in which hares were present (Wald X 2 [2] = 0.201, p = 0.818).However, between 6 AM and 4 PM (Wald X 2 [8] = 37.01, p < 0.001), hares spent signi cantly more time in taller vegetation (Fig. 3), which corresponds to the time when the hares spent more time costly vigilant.

FORAGING TIME
Hares spent more time cropping food after a playback of a conspeci c alarm call compared to a playback of sheep, and no sound (Wald X 2 [2] = 10.42,p = 0.005); Fig. 4).Hares with a lower bodyweight spent more time cropping (Wald X 2 [1] = 7.16, p = 0.007).Furthermore, hares spent more time cropping in absence of rain compared to the presence of rain (Wald X 2 [1] = 6.49, p = 0.011).Finally, time of day was not signi cantly related to the time spent cropping (Wald X 2 [1] = 0.204, p = 0.651).Hares thus spent a similar amount of time per hour cropping throughout the day and the night.

PHOSPHOROUS INTAKE
We found that the playback of conspeci c alarm calls did not affect the phosphorus intake of hares (Wald X 2 [2] = 0.088, p = 0.915).However, the phosphorus intake of hares was signi cantly affected by time of day (Wald X 2 [7] = 4.81, p < 0.001; Fig. 7), with a gradual increase in intake between 4AM and 4PM, after which the phosphorus intake decreased again.Moreover, hares had a signi cantly higher phosphorus intake in the absence of rain compared to the presence of rain (Wald X 2 [1] = 13.64,p < 0.001).

DISCUSSION
We investigated the effect of a predator-prey encounter on the nutrient intake of a small cryptic herbivore, the European hare.As a response to conspeci c alarm calls, 1) hares did not increase their time spent costly vigilant in tall vegetation, 2) hares did not spend more time in tall vegetation, but 3) increased their time spent foraging in short and tall vegetation.Still, the phosphorus intake of hares was not affected.
Therefore, the antipredator response of the European hare to our playback treatment did not come with a nutritional cost in phosphorus.Hares could possibly adjust their diet to compensate for losses in nutrient intake (  1984).Alternatively, food quality could interact with safety to affect dietary responses to predation.For example, L. catesbeianus tadpoles adjust their body nutrient stoichiometry in response to predation risk (Guariento et al. 2015).Besides, Eurasian siskins that did not reduce their food intake rate with increased predation risk, showed more effective behavior to detect or escape from a predator, compared to individuals that did reduce their food intake (Pascual and Senar 2014).In response to an encounter, prey possibly compensate for the loss in carbohydrates, which are spent during a ight response (Hawlena and Schmitz 2010a).In contrast, prey probably do not need to compensate for a loss in phosphorus or calcium, as these nutrients are not spent during an escape, but are required for stronger bones (Rhinehart and Hawlena 2020).The latter could explain the lack of a nutritional cost in phosphorus as observed in our study.Nevertheless, because the reactive response acts late in the predation sequence and occurs less frequent (see also Barnier et al. 2014;Christianson and Creel 2010), the effect on prey ecology at a population level would be limited (Creel 2018).
The time spend costly vigilant did not increase as a result of the 'risky' playback of conspeci c alarm calls of hares.It is unlikely that this behavioral response was shown because of the type of playback used, as hares did respond to our cue by increasing their time spend foraging.Besides, playbacks of conspeci c alarm calls are used successfully to trigger antipredator behavior in many other studies (e.g., Blumstein et  spend more time being vigilant in response to a temporary increase in predation risk, because they have more fat reserves and, therefore, can limit risky foraging activity that could attract predators (Brown 1999).Prey species with a lower bodyweight, however, need to spend time foraging, even in risky habitats, as they need the nutrients to survive (Bachman 1993).
Overall, we found that playback of conspeci c alarm calls of hares did not affect the antipredator responses of hares including their phosphorus intake.Animals consume food resources as a complex mixture of nutrients in varying levels of availability to maximize their response to predation (Zaguri et al. 2022), while minimizing the effects of toxics (Kirmani et al. 2010).In contrast to the consumption of phosphorus, an encounter's nutritional costs are more likely to affect the consumption of carbohydrates by prey, as carbohydrates are spent during the ight response.However, short-term effects of a predatorprey encounter on the nutrient intake of a small herbivore probably do not affect the population dynamics of prey (see Zanette et al. 2014).Furthermore, prey anti-predator responses (i.e., vigilance or a habitat shift) seem strongly related to the escape tactics of prey species that can differ between different habitats and can differ during the time of the day.After all, more detailed eld studies on the effects of predation risk on the nutrient intake of prey species are necessary to get a better insight into species' antipredator-food tactics.The four-step process of food intake with the formula that shows the proxies used for foraging time and nutrient intake.
Declarations FUNDING This study was funded by the Netherlands Organization for Scienti c Research (NWO) (023.001.222 to MW), Van Hall Larenstein University of Applied Sciences, and Wageningen University.

Figure 3 Estimated
Figure 3

Table 1
(Paci et al. 2012)2018)tudy was collected byWeterings et al. (2018)in 2014-2015 in a coastal dune landscape (52°33′N, 4°38′E) in the Netherlands.In this dune landscape, we focused on two study sites (275ha and 50 ha) with a population of European hares (±15 hares/km 2 ).The areas consisted of patches of grass, thicket, brushwood, and forest.2.2 RESEARCH DESIGN/ DATA COLLECTIONIn October 2014 nine hares were caught with Speedset static hare nets (height 45 cm, with 13 cm full mesh; JB's Nets, Alexandria, UK), blindfolded(Paci et al. 2012), and kept in darkened boxes temporarily to reduce stress.Five hares were caught from KB and four hares from VW. Hares were equipped with a (Clinchy et al. 20122012)in time spent foraging in tall vegetation will compensate for any losses in nutrient intake in vegetation that provides cover.lightweightGPS-ACCcollar(69g,2.11,SD ± 0.15% of body weight) that included a radio link for wireless communication (Type A, E-obs GmBH, Gruenwald, Germany) to minimize disturbance of the hares.Sex and life stage were determined by Stroh's method (juvenile < 1 year/adult > 1 year).Healthy hares (weight 2981-4400 g) were tagged without sedation(Gerritsmann et al. 2012).All handling of the hares was approved by the Wageningen University Animal Experiment Committee (no.2014034.b)andfollowedtheEUDirective2010/63 on the protection of animals used for scienti c purposes.To investigate the costs of a predator-prey encounter on European hare nutrient intake, we conducted a playback experiment between 16th of December 2014 and 21st of January 2015.Even though different cues can be used to trigger a response to increased predation risk(Prugh et al. 2019), playbacks are often used in eld studies to investigate immediate responses to predator-prey encounters(Clinchy et al. 2012).

table S1 )
Petrovan et al. 2012)s occurred within the same block; however, hare and sheep playbacks were never used both within the same block.The three treatment blocks were chosen to control for changes in daylight and weather conditions.Weather data were collected from the weather station in IJmuiden (approximately 10 km from Castricum) (Koninklijk Nederlands Meteorologisch Instituut 2020).After each treatment block there were at least ve days without playbacks to avoid carry-over effects (e.g.,Petrovan et al. 2012).Ten different combinations of three playback fragments of each forty seconds were placed in random order.To avoid habituation, fragments were never used more than two times (McGregor et al.
The playback experiment consisted of three different treatments 1) playbacks of conspeci c alarm calls of hares, 2) playbacks of sheep (control playback), and 3) no sound.The playback experiment consisted of three blocks of four days.In every treatment block, hares were either exposed to the treatments from audio boxes (Foxpro Fury2, FOXPRO inc.Lewistown) or to no sound at all (Supplementary materials 1, Weterings et al. 2018)ly analyzed for the concentration of nitrogen (N), phosphorus (P), calcium (Ca), and Neutral Detergent Fiber (NDF).For small herbivores, the amount of ber (i.e., total cell walls) in the food can reduce nutrient intake and affect foraging behavior, since animals generally avoid vegetation types with high ber content(Barboza et al. 2009) (but seeWeterings et al. 2018).video recordings of hare behavior were used to label one-second segments of ACC data that only consisted of the same behavior.Hare behavior was classi ed into six postures (i.e., sitting, sitting alert, standing, standing on hind legs, movement, and jumping), and six activities (i.e., chewing, cropping, grooming, scratching, shaking, and stretching) using the software Avidemux (2.6.6).Labeled segments of ACC data (training data) were used to classify unlabeled segments ACC data into behaviors using Decision Tree (accuracy 80.96 + 0.75% (X + SD)) in the AcceleRater software (Homolka 1987l.2008;Weterings et al. 2018pratensis, Holcus lanatus, Poa trivialis, Taraxacum o cinale, Rubus caesisus(Kuijper et al. 2008;Weterings et al. 2018) and a commercial ower bulb species using the hand-pluck method (de Vries and Schippers 1994).Edible biomass (i.e., the green plant parts that have a high nutritional value and are selected by hares(Homolka 1987)) were collected by the hand-pluck method in six randomly placed circular plots (10 m radius) up to 50 cm in height in each vegetation type (n = 120).Plant parts were air-driedThe Engelhart and Muller-Schwarze 1995; Epple et al. 1993; P ster et al. 1990; Sullivan and Crump Gosler et al. 1995;Kullberg et al. 1996;MacLeod et al. 2005Grace 2008) Loughry1995).Our results did show that in contrast to short vegetation, hares in tall vegetation spent more time being costly vigilant, probably to improve auditory detection of approaching predators due to low visibility(Marboutin and Aebischer 1996;Benhaiem et al. 2008;Riginos and Grace 2008).Differences in vigilance seemed therefore more related to differences in visibility due to vegetation cover than a change in predation risk initiated by our playback.As a response to the treatment simulating a predator-prey encounter, we hypothesized that prey would shift habitat and move to taller vegetation containing more cover(Neumann et al. 2011).In contrast, hares did not move to tall vegetation, but moved to tall vegetation during the transition from night to day.Hares shift from tall to short vegetation during dusk and vice versa during dawn (Schai-Braun et al. 2012).Possibly, hares did not shift habitat to avoid predators in open vegetation, because their defense matched predator attack ecology in open and short vegetation during the night (Dellinger et al. 2019).Short vegetation allows hares to detect approaching predators(Hewson 1977)and to escape predators by ight(Weterings et al. 2016).However, hares only use ight as an escape tactic in open habitat during the night, and make use of crypsis in closed habitat during the day.We therefore suggest that hares have an advantage escaping predation in short vegetation during the night, while they have an advantage escaping predation in tall vegetation during the day(Dellinger et al. 2019).In contrast to the control treatment, playback of conspeci c alarm calls increased the time spent foraging by hares throughout the day, no matter the length of the vegetation.Prey species increase their time spent foraging during high levels of predation risk, when this risk is uniformly spread over the landscape (i.e., they have no place to hide) and missed opportunity costs for foraging are therefore low(Eccard et al. 2008;Eccard and Liesenjohann 2014).This could apply to the European hare, which as a non-central cannot outrun their predator (see alsoDellinger et al. 2019).Besides, our prey could behaved more boldly during winter time, because the available food choices are limited during this season(Kervola 2019).Moreover, if the risk of starvation is high, prey will forage in unsafe habitats(Sih 1980;Sih 1982).In contrast to studies that report hares resting in cover during day time (see e.g Tapper and Barnes 1986), our results show that hares foraged in cover during the day.Possibly hares require a speci c nutritional diet that can only be satis ed by foraging in two different types of habitats (i.e., short and tall vegetation) (see e.g.sparrows; Tinbergen 1980), as mobile species often use multiple habitats to ful ll their biological needs(Firle et al. 1998;Doniol-Valcroze et al. 2012).More importantly, we think that earlier scientists did not observe hares foraging during the day time, because hares spent most of their time in cover during day time and are thus very di cult to observe (see e.g Marboutin and Aebischer 1996).Most recent studies did not use accelerometers that can continuously record behavior of small mammals during their circadian rhythm, even in concealed habitats.Nevertheless, our results do show that during increased predation risk, hares with a lower bodyweight spend more time cropping (i.e., foraging).This corroborates the hypothesis of mass-dependent predation risk (MDPR) (seeGosler et al. 1995;Kullberg et al. 1996;MacLeod et al. 2005).Prey species with a higher body weight spend less time foraging and Mazza et al. (2019) not have a refuge or burrow.However, snowshoe hares (Lepus americanus) (also a non-central place forager) did show a decrease in time spent foraging at high predation risk(Liu et al. 2014).Small mammals that can hide, decrease their time spend foraging during high predation risk(Verdolin 2006).Nevertheless,Mazza et al. (2019)showed that prey that could outrun their predator seem to accept predation risk rather than avoid predation risk and adjust their foraging behavior, compared to prey that