nena masthead
NENA Home Staff & Editors For Readers For Authors

Effect of Direct and Indirect Cues of Predation Risk on the Foraging Behavior of the White-footed Mouse (Peromyscus leucopus)
Benjamin G. Fanson

Northeastern Naturalist, Volume 17, Issue 1 (2010): 19–28

Full-text pdf (Accessible only to subscribers.To subscribe click here.)

 

Access Journal Content

Open access browsing of table of contents and abstract pages. Full text pdfs available for download for subscribers.



Current Issue: Vol. 30 (3)
NENA 30(3)

Check out NENA's latest Monograph:

Monograph 22
NENA monograph 22

All Regular Issues

Monographs

Special Issues

 

submit

 

subscribe

 

JSTOR logoClarivate logoWeb of science logoBioOne logo EbscoHOST logoProQuest logo

2010 NORTHEASTERN NATURALIST 17(1):19–28 Effect of Direct and Indirect Cues of Predation Risk on the Foraging Behavior of the White-footed Mouse (Peromyscus leucopus) Benjamin G. Fanson* Abstract - Understanding predator-prey dynamics requires an understanding of how prey assess predation risk. This study tested the effect of microhabitat, moon stages, and mammalian predator urines (Vulpes vulpes [Red Fox], Mustela vison [Mink], and Procyon lotor [Raccoon]) on the degree of predation risk perceived by Peromyscus leucopus (White-footed Mouse). Giving-up densities from artificial food patches were used to quantify perceived predation risk. White-footed Mice exhibited a strong preference for cover microhabitat and for the new moon stage. However, the mice did not significantly alter their foraging behavior in response to the predator urines compared to a water control. Additionally, mice foraged less on colder nights. The results suggest that mammalian predator urines may not provide reliable information on actual predation risk for the White-footed Mice and that the mice extensively use indirect cues to assess predation risk. Introduction Perceived predation risk affects an animal’s decision-making process across several axes of behavior (e.g., foraging, mating, and parental care [Caro 2005, Lima and Dill 1990]). During periods of higher perceived predation risk, animals may alter their behavior in many ways, such as avoiding riskier areas or decreasing their activity level (Caro 2005, Kats and Dill 1998). The consequences of these altered behaviors can shape population and community dynamics (Lima 1998). Several theoretical studies have explored the ecological effects of anti-predator behavior on community interactions (Bouskila 2001, Brown 2001, Luttbeg and Schmitz 2000, Luttbeg and Sih 2004). However, a crucial assumption of these models is that prey possess the ability to assess and update their estimates of predation risk. Therefore, a key component in understanding the ecological effects of antipredator behavior is to understand how prey assess predation risk. Most prey probably use indirect cues to estimate predation risk. For example, many animals appear to alter their activity in response to temporal (e.g., night vs. day) and spatial characteristics (e.g., forest vs. grassland, under a shrub vs. in the open) that may be associated with different degrees of predation risk (Brown and Kotler 2004, Caro 2005, Lima 1998). Prey can also use information from direct cues (e.g., odor or sound of a predator) for estimating predation risk (Kats and Dill 1998). Indirect cues probably represent relatively static rules of thumb and provide limited information. *Department of Biological Sciences, Purdue University, 915 West State Street, West Lafayette, IN 47907; bfanson@gmail.com. 20 Northeastern Naturalist Vol. 17, No. 1 Direct cues have the potential to provide a variety of information including predator type, predator state, and likelihood of a predator encounter (Kats and Dill 1998, Laurila et al. 2004, McNamara et al. 2005). Rodents have been shown to use indirect cues to assess predation risk. Studies have shown that microhabitat, habitat, lunar cycle, and time of day can affect a rodent’s perceived predation risk (Brown and Kotler 2004, Caro 2005, Lima and Dill 1990). In general, less is known about responses to direct cues. Detection of mammalian predators is likely to occur mostly via olfaction (Herman and Valone 2000, Jedrzejewski et al. 1993, Ward et al. 1997). Nolte et al. (1994) suggested that prey may use odors associated with sulfurous metabolites from meat digestion as indicators of a predator presence. However, previous studies have shown mixed responses of prey to urine and feces of mammalian predators (Hayes et al. 2006, Herman and Valone 2000, Kats and Dill 1998, Orrock et al. 2004). In this study, I examined the effects of indirect (microhabitat and moon stage) and direct (predator urines) cues of predation risk on the foraging behavior of Peromyscus leucopus (Rafinesque) (White-footed Mouse). By measuring patch use in artificial foraging patches, I first tested for differences between microhabitats (under a shrub or in the open) across two lunar cycles. Then, during a waning moon stage, I measured the patch use of mice in both microhabitats when exposed to the urine of Vulpes vulpes L. (Red Fox), Mustela vison Schreber (Mink), and Procyon lotor L. (Raccoon), and to a water control. Methods Study site and study species The study was conducted during the winter of 2004–2005 at Purdue University’s Ross Biological Reserve near West Lafayette, IN. This hardwood forest borders the Wabash River and contains a mix of old growth and secondary growth patches. The forests are dominated by Quercus spp. (oaks), Carya spp. (hickories), Acer spp. (maples), and Fagus spp. (beeches). The undergrowth of the secondary forest is mostly Lonicera maackii (Rupr.) Herder (Amur Honeysuckle). White-footed Mice are abundant in the mixed forests of the eastern United States and were common at the study site. These omnivorous rodents are prey to various mammalian predators. Mink are a major predator of White-footed Mice (Korschgen 1958, Mumford and Whitaker 1982), but are rare at the Ross Reserve. Red Fox are common at this site (B.G. Fenson, pers. observ.) and can prey heavily on White-footed Mice (Mumford and Whitaker 1982). Raccoon are also present at this site, but are not primary predators of White-footed Mice (although occasional predation events have been documented; Mumford and Whitaker 1982). Experiments The use of foraging patches has become a common tool for measuring perceived risk in animals (Brown and Kotler 2004). Patch-use theory 2010 B.G. Fanson 21 predicts that a forager should leave a patch when the harvest rate diminishes to the point that it equals the foraging costs (including predation, energetic, and missed-opportunity costs) (Brown 1988). At this point, the amount of food left in the patch (called giving-up density; GUD) provides a surrogate for the quitting harvest rate. Thus, by manipulating only the predation costs, it is possible to obtain a quantitative measure of perceived predation risk by comparing GUDs between patches (Brown 1988). For the foraging patches, I used one-gallon plastic milk containers with the lids on (14 x 14 x 23 cm). I cut a hole in the bottom and fitted a PVC pipe (6 cm in diameter by 15 cm in length) into the hole to act as an entrance for the mice. I then thoroughly mixed 10 g of small popcorn seeds into 1.5 L of dry sand and added it to the foraging patch. The container was then laid on its side with the PVC pipe angled to provide a ramp into the container. The milk containers allowed ambient light in, but protected the sand from moisture. Mice were accustomed to foraging in these kind of patches, which had been used in previous studies in this area. To manipulate indirect cues, I tested for differences in perceived risk under cover and in open microhabitats during two lunar cycles (early Dec through late Jan). I collected three days of data for both the waxing and waning stages (moon disc ≈70% illuminated; 2 sequential days for first lunar cycle, one for the second cycle), two days of data during the full moon stage (moon disc >95% illuminated; one day for each lunar cycle), and three days during the new moon stage (moon disc <5%; sequential days between the two full moons). For the experimental setup, I haphazardly placed six stations in secondary forests and another six in primary forests (>50 m between nearest stations). At each station, I placed one foraging patch in a cover location (under a pile of honeysuckle branches and leaves) and another patch ≈1 m away in a more open location. During the experiment, I mixed seeds into the sand <1 h before sunset and allowed the mice to forage all night. In the morning, I capped the PVC pipe to prevent any foraging during the day. The next evening I collected the remaining seeds and re-charged the patch. The collected seeds were cleaned and weighed (±0.1 g) to measure GUDs. Finally, minimum nightly temperatures were recorded. For the direct cue experiment, I used commercially obtained urines of three different mammals: Red Fox, Mink, and Raccoon. I selected fox urine because foxes are a current predator for this population and Mink urine since Mink are a historically common predator. The Raccoon is abundant throughout the Ross Reserve and is not a major predator; therefore, the Raccoon urine represented a urine control. Finally, I used water as the sham control. Since mice may perceive the risk of the direct predator cues differently depending on the microhabitat, I also tested for a microhabitat by scent interaction. The results from the previous experiment revealed avoidance of patches during the waxing and full moon stages, so I chose to conduct this experiment during the waning and new moon stages of the lunar stage in order to get high response rates. 22 Northeastern Naturalist Vol. 17, No. 1 The experimental setup was similar to the indirect cue experiment. I used the same foraging patch design and the same stations as the first experiment. I used a replicated Latin square design with night (x4) and station (x4) as blocking factors and scents as the treatment factor. A set of four stations was used in each replicate, thus giving three replicates (12 stations). During a waning moon stage, I applied a different scent each night to the whole station (both cover and open microhabitats). At each foraging patch, a metal wire with a hook was placed into the ground near the entrance (<10 cm). On the hook, I placed a strip of absorbent cloth that had been sprayed (≈0.5 mL) with the specified scent treatment (the urine had been warmed to ≈38 ºC to mimic mammalian body temperature). The treatments were applied <1 h before sunset. The following day I collected the remaining seeds, removed the cloth strip, and wiped down the wire with isopropyl alcohol (for all treatments). I then reran the above experiment during the following new moon stage, resulting in each station receiving two applications of each scent. Trapping To confirm the identify of the foragers and the number of individuals at a station, I live-trapped at the end of each experiment for two nights (total of four nights). At each station, I baited three Sherman live-traps with millet and corn seeds, giving a total of 144 trap nights. All stations had at least one White-footed Mouse individual, with three of the 12 stations having more than one mouse (up to three). No individual was caught at multiple stations, and no other species were caught. Statistical analysis I performed two separate mixed-model analyses using PROC MIXED (SAS 9.1; Cary, NC). For the lunar data, I created a mixed linear model with microhabitat and moon stage as the fixed factors. For the scent data, I created a mixed model with microhabitat and scent type as the fixed factors. Additionally, since the ambient temperature can affect the energetic costs of foraging (Brown 1988, Kotler et al. 1993), I added in nightly minimum temperatures as a covariate to both models. To test for the potential problem of carryover effects with the scent data, I initially included an additional factor that included the previous treatment type (see Littell et al. 2006). After running the model, this effect was found to be nonsignificant (P = 0.54) and was removed. All stations most likely had the same individual(s) foraging in both patches at a station. Additionally, patches foraged temporally closer should be more correlated than patches further apart in time. To deal with these covariations, I included station and night as random factors and then modelled the residual correlation matrix using the spatial power law (“sp[pow]” in MIXED). This method is similar to a first-order autoregressive correlation, but is applicable for unequally spaced data (Littell et al. 2006). I then applied a Kenward-Roger correction to the denominator degrees of freedom (Littell et al. 2006). 2010 B.G. Fanson 23 I visually inspected all residuals for normality and homoscedasticity assumptions, and no transformations were needed for either model. For any significant factors, I performed post-hoc comparisons of the least square means, and to control for Type I error, I applied a Tukey-Kramer adjustment to the P-values. All means are displayed with ± SE, unless otherwise indicated. Results Microhabitat and moon stage Microhabitat and moon stage appeared to have a strong effect on GUDs (F2,85.9 = 6.66, P = 0.012; F2,5.99 = 6.42, P = 0.027, respectively); however, there appears to be no strong interaction between the two variables (F3,115 = 1.77, P = 0.16; Fig. 1). Mice foraged patches in the cover microhabitat to lower GUDs than in the open microhabitat (5.39 ± 0.74 vs. 6.17 ± 0.74 g), and there was no strong evidence that this preference or the magnitude of the difference changed with different moon stages; however, moon stage did affect the overall pattern of foraging. Mice foraged 100% of the patches during the new moon stage, 68% of the patches during the waning stage, 50% during waxing stage, and 29% during the full moon. The new moon stage and waning stage had the lowest mean GUDs and did not differ significantly from Figure 1. Effect of moon stage on the giving-up densities of White-footed Mice. Error bars represent 1 standard error. Different letters indicate a significant difference in means (P < 0.05). 24 Northeastern Naturalist Vol. 17, No. 1 each other (Δ⎯x = 2.05 ± 1.25 g; t6.91 = 1.64, P = 0.428). However, new moon did differ significantly from waxing (Δ⎯x = 4.18 ± 1.24 g; t6.57 = 3.40, P = 0.05) and full moon (Δ⎯x = 6.43 ± 1.70 g; t5.96 = 3.78, P = 0.04) stages. However, after Tukey adjustments, waning stage did not differ significantly from waxing (Δ⎯x = 2.14 ± 1.19 g; t5.67 = 1.79, P = 0.36) or full (Δ⎯x = 4.39 ± 1.67 g; t5.45 = 2.64, P = 0.13) stage. Finally, nightly temperature had a significant negative relationship with GUDs (β = -0.22 ± 0.04 g/ºC; F1,54.9 = 33.15, P < 0.001). Microhabitat and scents Overall, 91% of the 168 patches were foraged over the seven nights. Only two of the 84 stations had no foraging activity. GUD results showed no strong evidence that the predator urine affected their foraging behavior (F3,25.4 = 2.05, P = 0.13). Interestingly, the water treatment had the highest mean GUDs (5.11 ± 0.60 g), followed by Raccoon (4.9 ± 0.60 g), Mink (4.2 ± 0.60 g), and fox (3.82 ± 0.60 g) treatment. However, water and fox GUDs were not significantly different (Δ⎯x = 1.30 ± 0.58 g; t26.3 = 2.25, P = 0.14). The water treatment mean was very similar to the waning stage mean in the first experiment (Δ⎯x = 0.44 ± 0.71 g; t14 = 0.62, P = 0.54). The mice did have lower GUDs in the cover compared to the open microhabitat (3.56 ± 0.52 vs. 5.46 ± 0.52 g, respectively; F1,10.6 = 22.48, P = 0.0007). I found no strong evidence that microhabitat affected the scent preference of the mice (F3,117 = 0.23, P = 0.88). Similar to the previous experiment, temperature also had a negative effect on GUDs (β = -0.42 ± 0.09 g/ºC; F1,4.65 = 22.00, P = 0.007). Discussion The objective of this study was to examine a forager’s use of indirect and direct cues of predation risk. Moon stage and microhabitat had strong effects on the foraging behavior of White-footed Mice. The mice foraged patches more thoroughly during the new moon stages and when foraging under vegetation. No strong support existed that mice foraged the microhabitats differently during different moon stages. In contrast to the strong effects of the indirect cues, the direct due of predator scent had little effect on foraging behavior during the waning and new moon phase. Minimum nightly temperature positively affected the foraging behavior of the mice. A similar relationship between temperature and GUDs has also been found with gerbils (Kotler et al. 1993). One likely explanation is that higher energetic costs of thermoregulation lead to higher foraging costs. Nightly temperatures ranged from -14 ºC to 10 ºC, resulting in metabolic rates from ≈12 to ≈6 cm3O2(g*h)-1, respectively (Wickler 1980). Patch-use theory predicts that as energetic costs increase, an optimal forager should quit a patch at a higher harvest rate, assuming a constant marginal rate of substitution (that is, no change in the value of energy for the animal) (Brown 1988). Another possibility for this trend is the potential confounding effect of cloud cover. I avoided collecting data on completely cloudy nights, but some nights had a notable amount of cloud cover (up to 80%). Nightly 2010 B.G. Fanson 25 temperature may be positively correlated with cloud cover; therefore, mice would have experienced reduced energetic costs on warmer nights as well as reduced predation risk associated with less moon illumination. However, using meteorological records, I isolated warm clear nights and the residuals for those days were close to the regression line between GUDs and temperature, suggesting that this explanation is not likely. Microhabitat has been frequently shown to affect the foraging behavior of rodents (Brown 1988, Kotler et al. 1993, Orrock et al. 2004). The common explanation is that there is differential predation risk between the microhabitats (Brown 1988, Kotler et al. 1993, Morris 1997). The preference for cover microhabitat is very common when the main predators of a rodent are avian and mammalian. In contrast, snakes often hunt in cover microhabitats and can cause rodents to prefer open microhabitat (Bouskila 1995). At this study site, both foxes and owls are very common, and no snakes were present during this wintertime study. Thus, differences in predation risk most likely explain these preferences. Similarly, for nocturnal rodents, lunar illumination can be associated with higher predation risk, increasing the detection abilities of highly visual predators, such as owls and mammals (Clarke 1983, Kotler et al. 1991). In this study, White-footed Mice had lower GUDs during the new moon than during the waxing and full moon stages, probably due to lower predation risk during new moon stage. Several studies using differing techniques have found similar behavioral responses between full vs. new moon stages for White-footed Mice (Bowers and Dooley 1993, Clark and Kaufman 1991, Jekanoski and Kaufman 1995). However, two studies found no effect of illumination levels on behavior. Barry and Francq (1982) found evidence that White-footed Mice did not avoid higher illumination areas. Schmidt (2006) found White-footed Mice ate similar number of seeds during new and full moon stages; however, the mice did forage fewer seeds during the full moon than the new moon if an owl call was played during the night. For the direct cues, predator urine did not have a significant effect on foraging behavior. A potential concern of any experiment is that the results are an artifact of the design. This experiment implemented a Latin square design that could potentially have carryover effects (that is, previous treatment has subsequent effects on next treatment). However, two pieces of evidence suggest little or no carryover effects. First, the water control mean GUD (5.1 g) in the scent experiment was very similar to the mean GUD during the waning moon stage (4.7 g) in the previous experiment, suggesting that adding a scent did not result in all patches being foraged less. Second, I statistically tested for the effect of the previous treatment on the next night’s GUDs and the result was not significant. Thus, I believe that carryover effects are probably not a major concern in this study. Another potential concern is the power of the design. I conducted a retrospective power analysis using observed variances and actual sample sizes (Thomas 1997). For pairwise comparisons with a Tukey-adjusted α, an 26 Northeastern Naturalist Vol. 17, No. 1 effect size of 1.0 g and 2.1 g had 20% and 80% power, respectively. To put this into perspective, microhabitat had an effect size of 1.9 g, and between full and new moon, the effect size was 6.6 g. Consequently, I feel that the design had sufficient power to detect modest to large effects of scents. The scent results do match a similar study with Peromyscus polionotus (Wagner) (Oldfield Mouse), in which the mice did not show any response to mammalian predator odors (Orrock et al. 2004). In that study, they used Lynx rufus (Schreber) (Bobcat), Vulpes sp. (fox), Canis latrans Say (Coyote), and Felis pardalis L. (Ocelot) urines for their predators. However, a potential caveat to the results in both studies is that GUDs were measured only during waning and new moon stages. Schmidt (2006) found that the White-footed Mice only altered its foraging behavior in response to owl vocalizations during the full moon and not the new moon. Therefore, there may be non-additive effects between indirect and direct cues. In other words, the effect of direct cues may vary depending on the lunar phase. This study looked only for such non-additive effects between microhabitat and scents, which were not found. Thus, it is possible that response to predator scents may change across moon stages. The results from this study agree with a recent meta-analysis that analyzed the effect of indirect and direct cues of predation risk on GUDs (Verdolin 2006). The meta-analysis revealed that odor (and actual presence of a predator) had no significant effect on GUDs, but habitat structure had a large, consistent effect on GUDs. The inconsistency in the effects of predator presences and odors suggest that probably no simple rule exists for how prey exploit direct cues of a predator. Using a theoretical model, McNamara et al. (2005) showed that a bird should change its foraging behavior depending on the nature of the information provided by an exposure to a predator. For instance, an encounter with the scent of a predator may indicate that it is still around and more likely to be encountered (e.g., Accipiter nisus (L.) [Eurasian Sparrowhawk]; Cresswell 1996), or it may provide no information on the probability of re-encountering the predator if the predator moves through the environment haphazardly (e.g., Accipiter striatus Vieillot [Sharp-shinned Hawk]; Roth and Lima 2007). Thus, studying the foraging and movement behavior of an animal’s predator should help predict the usefulness of direct cues to its prey. Acknowledgments I wish to thank Jeff Lucas, Adam Boyko, and Mark Nolen for comments and suggestions; Loren Lohmann for assistance in collecting the data; Ani for consistent insights on predator behavior; and Kerry Fanson for editorial comments on the manuscript. Literature Cited Barry, R.E., and E.N. Francq. 1982. Illumination preference and visual orientation of wild-reared mice, Peromyscus leucopus. Animal Behaviour 30:339–344. 2010 B.G. Fanson 27 Bouskila, A. 1995. Interactions between predation risk and competition: A field study of Kangaroo Rats and snakes. Ecology 76:165–178 Bouskila, A. 2001. A habitat selection game of interactions between rodents and their predators. Annales Zoologici Fennici 38:55–70. Bowers, M.A., and J.L. Dooley. 1993. Predation hazard adn seed removal by small mammals: Microhabitat- versus patch-scale effects. Oecologia 94:24–254. Brown, J.S. 1988. Patch use as an indicator of habitat preference, predation risk, and competition. Behavioral Ecology and Sociobiology 22:37–47. Brown, J.S. 2001. Ecology of fear: Foraging games between predators and prey with pulsed resources. Annales Zoologici Fennici 38:71–87. Brown, J.S., and B.P. Kotler. 2004. Hazardous duty pay and the foraging cost of predation. Ecology Letters 7:999–1014. Caro, T. 2005. Antipredator Defenses in Birds and Mammals. The University of Chicago Press, Chicago, IL. Clark, B.K., and D.W. Kaufman. 1991. Effects of plant litter on foraging and nestingbehavior of prairie rodents. Journal of Mammalogy 72:502–512. Clarke, J.A. 1983. Moonlight's influence on predator prey interactions between Short-eared Owls (Asio flammeus) and Deer Mice (Peromyscus maniculatus). Behavioral Ecology and Sociobiology 13:205–209. Cresswell, W. 1996. Surprise as a winter hunting strategy in Sparrowhawks Accipiter nisus, Peregrines Falco peregrinus and Merlins F. columbarius. Ibis 138:684–692. Hayes, R.A., H.F. Nahrung, and J.C. Wilson. 2006. The response of native Australian rodents to predator odours varies seasonally: A by-product of life-history variation? Animal Behaviour 71:1307–1314. Herman, C.S., and T.J. Valone. 2000. The effect of mammalian predator scent on the foraging behavior of Dipodomys merriami. Oikos 91:139–145. Jedrzejewski, W., L. Rychlik, and B. Jedrzejewski. 1993. Responses of Bank Voles to odors of 7 species of predators: Experimental-data and their relevance to natural predator-vole relationships. Oikos 68:251–257. Jekanoski, R.D., and D.W. Kaufman. 1995. Use of simulated herbaceous canopy by foraging rodents. American Midland Naturalist 133:304–311. Kats, L.B., and L.M. Dill. 1998. The scent of death: Chemosensory assessment of predation risk by prey animals. Ecoscience 5:569–569. Korschgen, L.J. 1958. December food habits of Mink in Missouri. Journal of Mammalogy 39:521–527. Kotler, B.P., J.S. Brown, and O. Hasson. 1991. Factors affecting gerbil foraging behavior and rates of owl predation. Ecology 72:2249–2260. Kotler, B.P., J.S. Brown, and W.A. Mitchell. 1993. Environmental factors affecting patch use in 2 species of gerbilline rodents. Journal of Mammalogy 74:614–620. Laurila, A., J. Kujasalo, and E. Ranta. 2004. Different antipredator behaviour in two anuran tadpoles: Effects of predator diet. Behavioral Ecology and Sociobiology 40:329–336. Lima, S.L. 1998. Nonlethal effects in the ecology of predator-prey interactions: What are the ecological effects of anti-predator decision-making? Bioscience 48:25–34. Lima, S.L., and L.M. Dill. 1990. Behavioral decisions made under the risk of predation: A review and prospectus. Canadian Journal of Zoology 68:619–640. 28 Northeastern Naturalist Vol. 17, No. 1 Littell, R.C., G.A. Milliken, W.W. Stroup, R.D. Wofinger, and O. Schabenberger. 2006. SAS for mixed models. SAS Institute, Inc., Cary, N.C. Luttbeg, B., and O.J. Schmitz. 2000. Predator and prey models with flexible individual behavior and imperfect information. American Naturalist 155:669–683. Luttbeg, B., and A. Sih. 2004. Predator and prey habitat selection games: The effects of how prey balance foraging and predation risk. Israel Journal of Zoology 50:233–254. McNamara, J.M., Z. Barta, A.I. Houston, and P. Race. 2005. A theoretical investigation of the effect of predators on foraging behaviour and energy reserves. Proceedings of the Royal Society B-Biological Sciences 272:929–934. Morris, D.W. 1997. Optimally foraging Deer Mice in prairie mosaics: A test of habitat theory and absence of landscape effects. Oikos 80:31–42. Mumford, R.E., and J.O. Whitaker. 1982. Mammals of Indiana. Indiana University Press, Bloomington, IN. Nolte, D.L., J.R. Mason, G. Epple, E. Aronov, and D.L. Campbell. 1994. Why are predator urines aversive to prey. Journal of Chemical Ecology 20:1505–1516. Orrock, J.L., B.J. Danielson, and R.J. Brinkerhoff. 2004. Rodent foraging is affected by indirect, but not by direct, cues of predation risk. Behavioral Ecology 15:433–437. Roth, T.C., and S.L. Lima. 2007. Use of prey hotspots by an avian predator: Purposeful unpredictability? American Naturalist 169:264–273. Schmidt, K.A. 2006. Non-additivity among multiple cues of predation risk: A behaviorally driven trophic cascade between owls and songbirds. Oikos 113:82–90. Thomas, L. 1997. Retrospective power analysis. Conservation Biology 11:276–280. Verdolin, J.L. 2006. Meta-analysis of foraging and predation risk trade-offs in terrestrial systems. Behavioral Ecology and Sociobiology 60:457–464. Ward, J.F., D.W. MacDonald, and C.P. Doncaster. 1997. Responses of foraging Hedgehogs to Badger odour. Animal Behaviour 53:709–720. Wickler, S.J. 1980. Maximal thermogenic capacity and body temperature of White-footed Mice (Peromyscus) in summer and winter. Physiological Zoology 53:338–346.