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Do predator and prey foraging activity patterns match? A study of coyotes (Canis latrans), and lagomorphs (Lepus californicus and Sylvilagus audobonii)
Journal of Arid Environments 75 (2011) 112e118
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Do predator and prey foraging activity patterns match? A study of coyotes (Canis latrans), and lagomorphs (Lepus californicus and Sylvilagus audobonii) I. Arias-Del Razo a, *, L. Hernández b,1, J.W. Laundré b, 2, O. Myers c a
Instituto de Ecología, A.C. Posgrado, Km. 2.5 carretera antigua a Coatepec 351, Congregación El Haya, 91070 Xalapa, Veracruz, Mexico Instituto de Ecología, A.C. Centro Regional Durango, Boulevard del Guadiana 123, Los Remedios 34100, Victoria de Durango, Durango, Mexico c University of New Mexico, MSC 10 5550, 1, Albuquerque, NM 87131, USA b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 1 September 2009 Received in revised form 2 August 2010 Accepted 20 September 2010 Available online 13 October 2010
Many aspects of an animal’s ecology are associated with activity patterns. One important and controversial one is in the predator/prey relationship. We examined temporal patterns of coyotes (Canis latrans) and lagomorphs (Lepus californicus, Sylvilagus audobonii), their main prey in the Chihuahuan Desert. We test the hypothesis that a predator and prey will have non-random distribution of activity relative to each other; this non-random activity could be a substantial overlap or the lack of synchrony depending on the competing theories. We used GPS collars to track coyotes; we identified areas of activity and determined daily patterns. We installed lagomorph feeding stations and game cameras in coyote activity areas to assess lagomorph patterns. All three species were mainly crepuscular. Black-tail jackrabbits and Audubon’s cottontail rabbits had different hourly patterns of activity (P < 0.001). Activity peaks for jackrabbits occurred between 0400e0700 h, and 1800e2000 h. Cottontail rabbit activity peaks occurred between 0500e0700 h, and 1800e2000 h. The coyote evening activity peak was synchronous with lagomorph activity, but the morning peak occurred from 0700 to 1000. We found partial lack of synchrony in the activity patterns of the predator and its prey. Ó 2010 Elsevier Ltd. All rights reserved.
Keywords: Chihuahuan desert Cottontail rabbits Jackrabbit Predator/prey
1. Introduction Many aspects of an animal’s ecology are associated with daily activity, the time of day when that animal is awake and active (Hall and Ross, 2007). When active, an animal’s behavior is an outcome of many conflicting demands. Two major ones are: the activity required to maximize nutritional and reproductive objectives, and the need to minimize costs and risk of predation (Alkon and Saltz, 1988). Times of activity for prey are normally associated with increased mortality risk (Lima and Dill, 1990). The activity of prey relative to predation risk has been studied in a number of different taxa (Blaustein and Fugle, 1981; Fox et al., 1992; Kronfeld-Schor and Dayan, 2003; Lima, 1998; Zaret and Suffern, 1976). Such studies * Corresponding author. Instituto de Ecología, A.C., Departamento de Posgrado. Km 2.5 Carretera Antigua a Coatepec 351, Congregación El Haya, 91070 Xalapa, Veracruz. México. Tel.: þ52 228 842 18 00x2004. E-mail addresses: [email protected] (I. Arias-Del Razo), lhernan1@oswego. edu (L. Hernández), [email protected] (J.W. Laundré), [email protected] (O. Myers). 1 Present address: Rice Creek Field Station, Department of Biological Sciences, 225 Piez Hall, SUNY Oswego, Oswego, NY 13126, USA. 2 Present address: Department of Biological Sciences, 128 Piez Hall, SUNY Oswego, Oswego, NY 13126, USA. 0140-1963/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.jaridenv.2010.09.008
highlight the importance of temporal patterns in vulnerability to predators for prey behavior. For example, nocturnal behavior and moonlight avoidance might be behavioral activity adaptations of herbivorous small mammals to reduce predation risk (Alkon and Saltz, 1988; Clarke, 1983; Kotler et al., 1994; Kramer and Birney, 2001). Another anti-predator strategy for prey would be to avoid an overlap between their hours and the areas of activity and the ones of their predator. On the other hand, studies have shown the importance of activity patterns to the hunting success of predators (Ables, 1969; Asa and Wallace, 1990; Boal and Giovanni, 2007; Geffen and Macdonald, 1993). Temporal feeding activity patterns in predators could be either an innate activity rhythm or a response to an activity pattern of the prey (Giller and Sangpradub, 1993). Studies focused on how prey behaviorally trade-off predation and starvation risk have been instrumental in our understanding of behavioral ecology, social organization, foraging ecology, and evolutionary relationships (Geist, 1974; Jarman, 1974). There is also growing evidence that indirect effects of these trade-offs by the prey can affect other species and have consequences on the dynamics of the entire community (Peacor and Werner, 2000; Ripple and Bestcha, 2003). However, our understanding of the full consequences of this trade-off is limited because we know little about the behavior of predators. This is especially true
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regarding activity patterns of prey and predator. One recent exception is that of Roth and Lima (2007) who examined daily activity patterns of avian prey and their predators under natural conditions. However, more studies like this are needed to better understand the importance of activity patterns in ecology. Activity patterns of coyotes (Canis latrans) have been reported in a variety of different habitats, but without considering activity patterns of their prey (Atwood et al., 2004; Fedriani et al., 2000; Gantz and Knowlton, 2005). Most reported that coyotes are active both day and night, with peaks of activity during crepuscular hours (Andelt, 1985; Gompper, 2002). Lagomorphs, the main prey of coyotes in different habitats, including desert habitats (Andelt et al., 1987; Clark, 1972; Cypher and Spencer, 1998; Delibes et al., 1986; Delibes and Hiraldo, 1987; Fedriani et al., 2000; Hernández and Delibes, 1994; Hernández et al., 1994, 2002; MacCracken, 1982; Marti et al., 1993), are also reported to be nocturnal with evening feeding periods that vary greatly with weather, season, and phase of the moon (Best, 1996). In general, jackrabbits (Lepus spp.) became active within 30 min of sunset, and retreated to daytime forms under shrubs between dawn and sunrise, regardless of season (Costa et al., 1976). Lord (1961) reported that activity of cottontail rabbits (Sylvilagus spp.) began at 1700 h and ceased at about 0700 h. Mech et al. (1966) suggested a relation between onset of activity and sunset, and cessation of activity and sunrise for eastern cottontails (Sylvilagus floridanus) and snowshoe hares (Lepus americanus). They suggest that cessation of activity may be stimulated by a certain light intensity rather than actual sunrise, but they did not consider predation risk and other environmental conditions. In this paper we examined the daily activity patterns of coyotes in the Chihuahuan Desert and, black-tailed jackrabbits (Lepus californicus) and Audubon’s cottontail rabbits (Sylvilagus audobonii), which have been shown to be coyotes main prey (Delibes et al., 1986; Hernández and Delibes, 1994; Hernández et al., 1994, 2002). Although there are temporal and spatial shift responses from predators and their prey, we will only concentrate on the temporal ones. We first used GPS technology to establish activity areas used by coyotes; we then conducted lagomorph feeding trials to estimate hourly activity levels of lagomorphs within the areas previously documented with coyote activity. We used this arrangement to ensure the presence of both, predator and prey in the same areas. We used these data to test the hypothesis that a predator and prey will have non-random distribution of activity relative to each other; this non-random activity could be a substantial overlap or the lack of synchrony depending on the competing theories. 2. Materials and methods 2.1. Study area We conducted our research in the Mapimí Biosphere Reserve (MBR). The Reserve is a protected area located in northern Mexico, between the states of Durango, Chihuahua and Coahuila (26 400 N, 103 400 W). Elevation ranges from 1000e1800 m. Average annual rainfall is 264 mm with 71% of the annual total occurring from June to September. The mean annual temperature is 21 C; in the coldest month (January) the mean is 12 C. Summers are warm, with mean temperatures varying from 24 C in September to 28 C in June (SEMARNAP, 2000). Vegetation is a xerophytic scrub as described by Rzedowski (1978) and consists primarily of creosote (Larrea tridentata), honey mesquite (Prosopis glandulosa), tobosa grass (Pleuraphis mutica), and cacti (Opuntia rastrera) (Montaña, 1988).
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2.2. Coyote 2.2.1. Coyote capture and data collection We trapped coyotes during the winters of 2004 through 2006. We used #3 Oneida Victor soft catch padded jaw traps, positioned on the side of dirt roads. We baited the traps either with sardines, bobcat or coyote urine, or commercial perfume. We monitored traps early in the morning and in the evening. We attached GPS LotekÒ collars only on animals greater than one year old. The collars were programmed to remain on the animal for 9 weeks at which time they automatically released and we then retrieved them. During the nine weeks, collars were programmed to estimate coyote locations every 30 min from 2000 to 0800 h and every 2 h during the daylight hours. We collared ten adult coyotes with GPS collars, five female and five male, ranging in ages from approximately 1.5e5 years old. We obtained location data for two periods: October 2004eApril 2005 and November 2005eApril 2006. Locations in daylight hours were collected on even hours for six coyotes and on odd hours for four coyotes, and therefore activity estimates were available for all hours of the day.
2.2.2. Analysis of coyote data Coyote location data were analyzed to determine (a) relative activity over space to identify areas where lagomorph feeding trials should be conducted, and (b) to determine activity during each hour of the day. We determined activity areas of coyotes based on the grid method (Laundré and Keller, 1981), and determined the level of activity based on the number of Standard Deviations, below and above the mean of relocations/grid. Low use grids were at least 2.9 SD below the mean activity and high use grids were 1.4 SD above the mean of relocations/ grid. For each coyote we identified six activity areas for potential use in lagomorph feeding trials. Calculated distances between successive GPS locations were used as an estimate of coyote movement. Measurements made over different observation time scales (0.5 or 2 h) were normalized to distance moved per hour (km/h) to assess activity patterns (Ables, 1969; Andelt and Gibson, 1979). Before analyses coyote activity measures were log-transformed and then replicate measures within a coyote, hour, and day were averaged to normalize the data and to stabilize residual variances. We used mixed model regression that included random effects for coyotes and dates within coyotes in addition to the residual error variance. The addition of random effects in the analysis accounts for non-independence of repeated observations while allowing unbalanced samples. Measurements made at two time scales may have different variances even after they are normalized to a per unit time basis. We tested whether a heterogeneous variance model was necessary by formulating the residual variance as a log-linear function of the two measurement scales. We also conducted a sensitivity analysis by preparing a thinned dataset that included only 2-h location intervals to see if the different location interval had important effects on results. Fixed effects in the model included sex, hour of day, and month. We did not include interactions in our main analyses to test whether within day activity varied with sex or month, because replication of coyotes within sexes and of months was limiting, however we did test for interactions in supplemental analyses. Analysis models were fitted by maximum likelihood (SAS v9.2Ò, proc mixed), and predicted population-averaged geometric mean activity estimates for each hour (km/h and 95% confidence interval) were obtained by exponentiation of the least squares adjusted means and confidence interval bounds.
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2.3. Lagomorph 2.3.1. Lagomorph data collection To estimate activity of lagomorphs, we conducted 30 feeding trials in areas within low, moderate and high levels of coyote activity described above. Activity areas for five coyotes that wore their collars for nine weeks and had at least forty-two 24 h complete blocks (range: 42e55) were used to conduct lagomorphs feeding trials. Two feeding trays were established in each of the low, moderate, and high activity strata for each coyote home range, which provided a total of 30 feeding stations, six for each animal (Fig. 1). It is commonly accepted that when active, feeding activity occupies most of an animal’s time (Wolton, 1983), taking up to 70% of an animal’s active period (Wauters, 2000). Thus, we used this feeding time as a general index of activity level. Lagomorph activity was assessed during three periods: NovembereDecember 2005, FebruaryeMay 2006 and FebruaryeMarch 2007. At each tray we placed digital game cameras (Leaf River DC-1BUÒ) that were active for 24 h for at least six days with a maximum of 25 days. We filled the 30 40 cm trays with 500 g of loose alfalfa and placed them 4.5 m away from the camera, the feeders were positioned at least 2 m from surrounding bushes. We set up the camera on a 2 4 cm wooden stake at a height of 30 cm from the ground. The motion sensor was set to capture first and second movements, with a 3 min delay between photographs. All animals were counted in each photograph, unless they were hard to see in the picture or if it was difficult to define the species because they were too far from the camera. We could not identify individual lagomorphs, so we could not assign photographs to particular individuals. Therefore we used the number of photographs taken per hour as our primary measure to assess temporal activity patterns of lagomorphs.
2.3.2. Analysis of lagomorph data The effect of time of day and coyote activity level on counts of lagomorphs photos per hour was analyzed using generalized mixed model regression to account for repeated measurements. The analyses employed a log link between the mean response and linear predictor variables, such as species, coyote activity level and hour, and assumed a Poisson response probability distribution. The analyses also included an additional random effect variance terms for coyote home ranges and for sample dates within location to account for correlation of repeated measurements. Primary fixed effects in the model were species, coyote activity level, hour of day, species hour interaction, and sampling location. An overdispersion parameter was used to inflate variances to account for remaining sources of variation not accounted for by the analysis. Analysis models were conducted using SAS v9.2 (SAS v9.2Ò, proc glimmix). Predicted population-averaged geometric mean activity estimates for each hour (photos/h and 95% confidence interval) were obtained by taking the exponent of the least squares adjusted means and confidence interval bounds. 3. Results 3.1. Coyote activity patterns The results of our coyote activity analysis based on logtransformed km/h estimates for movement distances showed that activity was not uniform over the day (p < 0.001) and that there were two main peaks of activity; one in the morning between 0700 and 1000 h and another in the evening between 1800 and 2000 h (Fig. 2). A heterogeneous variance model was used to estimate movement rates and confidence intervals, because the residual variance for the 2 h intervals was 1.38 times the variance for the 0.5 intervals (p < 0.001
Fig. 1. An example, GPS locations of one coyote and six feeding tray locations at MBR.
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Fig. 2. Coyote activity at MBR as determined by mixed model regression analysis of GPS locations collected during October 2004eApril 2005 and November 2005eApril 2006; Error bars are 95% confidence intervals.
95% CI ¼ 1.30e1.48). Sex (p ¼ 0.97) and month (p ¼ 0.08) were not associated with coyote activity levels. When we subjected these analyses to the thinned dataset containing only 2 h location intervals we found no compelling evidence that different location intervals had important effects on the coyote activity pattern analysis. Crepuscular peaks and nighttime km/h are slightly lower and confidence intervals were wider, but the overall pattern was unchanged. We conducted a supplemental analysis to assess whether female and male coyote had the same temporal activity patterns. The effect of sex hour was highly significant (p < 0.001), which means that on the log scale of analysis the mean response over hours for females and males were not parallel. The net effect seen was that females in this sample increased their evening activity an hour earlier than males (1700 vs. 1800), but the results were more uncertain because of the larger number of parameters needed to describe unique temporal patterns for each sex. Given the minimal replication of coyotes within sex we doubt that the small differences in patterns have ecological relevance. 3.2. Lagomorph activity patterns We conducted analyses to evaluate whether cottontail rabbits and jackrabbits had different temporal patterns of activity and whether activity was affected by predetermined coyote activity levels. Although we obtained 1045 photographs of black-tail jackrabbits, and 894 of cottontail rabbits, lagomorph photos were rare during the daylight hours with no photos containing cottontail rabbits taken during the hours of 1000e1600 over the study and only two photos with jackrabbits taken during these hours. Therefore lagomorph activity during these hours was at or below the practical limit of detection for these methods. The sparseness of
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the photo record during these hours caused numerical problems for analyses, and therefore the hours 1000e1600 could not be included in some analyses. Because of the numerical problems caused by zeros, Fig. 3A, shows the crude photo/h with 95% Poisson confidence intervals based on a summation over all locations and dates. The point estimates for activity are unbiased but the confidence intervals are too narrow, because they do not account for repeated measurements. The confidence intervals were retained in the figure to provide a rough estimate of the relative uncertainty. Additional results from subset analyses that excluded hours 1000e1600 are shown in Fig. 3B. Due to the sparseness of lagomorph photos in some hours even after excluding hours 1000e1600, we were unable to obtain numerical convergence of statistical algorithms when we attempted to test whether lagomorph activity was determined by a species coyote activity hour interaction. Analyses proceeded by dropping the threeeway interaction and testing for a significant species hour effect (p ¼ 0.02) on activity and a species coyote activity effect (p < 0.001) after adjusting for month of sample (p ¼ 0.42). The average hourly pattern of lagomorph activity is shown in Fig. 3B. The overall detection rates were similar for cottontail rabbits 0.09 photos/h (95% CI ¼ 0.04e0.21) and for jackrabbits 0.16 photos/h (95% CI ¼ 0.07e0.38), however the significant species hour interaction (p < 0.001) indicates there were some differences in the temporal patterns despite the considerable variation in estimated activity. These results show a somewhat more pronounced crepuscular pattern for jackrabbits than cottontails. Activity peaks for jackrabbits occurred between 0400e0700 h, and 1800e2000 h. Cottontail rabbit activity peaks occurred between 0500e0700 h, and 1800e2000 h. No lagomorph activity could be detected at feeding trays during 1000e1600. We next conducted separate analyses for rabbits and jackrabbits to ascertain whether hourly lagomorph activity varied with coyote activity level. Lagomorph activity differences among different coyote activity levels were approximately proportional with the hour coyote interaction test failing with p > 0.9 for both species (Fig. 4). If the interaction was significant we would have observed more crossing or divergence of the activity rate lines over time. The hypothesis of proportionality is appropriate because the Poisson analysis employs a log link between the mean and the response variable. 3.3. Predator/prey activity patterns Activity assessments for lagomorphs and coyotes were made using different instruments, which produced different activity measures (photos/h and km/h), and therefore graphical methods were used to evaluate species differences in temporal activity patterns described above (Fig. 5). Because there were no differences in activity patterns of cottontail rabbits and jackrabbits among the
Fig. 3. Crude (A) and predicted (B) lagomorphs activity (photos/camera-hour). Error bars for crude rate are 95% Poisson confidence intervals, and error bars for the adjusted rates are from a mixed model regression analysis that adjusted for month and coyote activity levels. Note different scale for y-axes.
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Fig. 4. Lagomorph crude activity rates (photos/camera-hour) at low, moderate, and high coyote activity level areas for cottontail rabbits (A) and black-tailed jackrabbits (B). Error bars are 95% Poisson confidence intervals but do not account for repeated measurements.
Fig. 5. Comparison of activity levels for coyotes (km/h), cottontail rabbits and jackrabbits (photos/camera-hour) at MBR.
three activity levels of coyotes, we combined the data per species for this analysis. Coyotes and lagomorphs were all least active during daylight hours and had crepuscular activity peaks. The evening peak for all three species was around 1900 h, but morning peaks for lagomorphs were between about 0400e0700 compared to 0700e1000 for coyotes. 4. Discussion and conclusions Relative to our proposed hypotheses, our data partially supported the one suggesting lack of synchrony in the activity patterns of coyotes and lagomorphs evening peaks were synchronous but morning peaks were less so (Fig. 5). As in most studies, we found that coyotes were mainly crepuscular with substantial activity extending into the day. We also observed that the morning coyote activity peak was later than for lagomorphs. Neither species of lagomorphs had detectable levels of activity during the daylight hours. The game theory model suggests that predator activity should match the pattern of its prey closely, and that prey will largely drive the temporal dynamics of the game: when prey is most active, the predator should be too (Kotler et al., 2002). These predictions are supported by some studies of predatory birds (Rijnsdorp et al., 1981) that state that small mammals are only available to raptors when they are active. However, mammalian predators and their prey have not been the subjects of similar studies (Zielinski, 2000). The general activity pattern of lagomorphs in semi-arid environments seems to be a balance between antipredatory and thermoregulatory strategies (Villafuerte et al., 1993). The almost consistent lack of lagomorphs activity during the day is possibly
related to their avoidance of high daytime temperatures (Bradley, 1967; Ilan and Yom-Tov, 1990; Rogowitz, 1997). The fact that some activity is noted on cloudy days, and thus, lower temperatures, seems to support this hypothesis (Villafuerte et al., 1993). In contrast, it has been argued that high predation risk during the day is considered the reason that most small mammals are nocturnal or crepuscular (Park, 1940; Daan and Aschoff, 1982). Darkness provides some cover from predators, or if predation pressure at night is less than during the day, nocturnal activity may be favored by selection (Zielinski, 2000). Though arguments can be presented for both hypotheses, regardless of the actual driving force, lagomorphs are not very active during the daytime. Because of this lack of daytime lagomorph activity, our study concentrated on the timing of activity from dusk to dawn. During this time, temperatures become less of a factor, and the timing of lagomorph foraging activity suggests that they might be taking some advantage to actively feed early in the morning and during the night, when predation risk is lower, avoiding coyotes, its principal predator (Hoffmeister, 1986). The question then becomes why coyotes would not seem to overlap completely their hours of activity with the ones of their main prey? Zielinski (2000) states predators that hunt primarily using sight and sound should forage during the active phase of their prey, when they are most vulnerable and producing cues that betray their location. However, Bider (1962) suggested that activity peaks of carnivores are related to senses used in hunting. Coyote eyes appear to be a compromise designed for crepuscular activity (Bekoff, 1978). Both the coyote’s scotopic sensitivity (Horn and Lehner, 1975) and activity patterns in the laboratory (Kavanau and Ramos, 1975) suggest a crepuscular activity proclivity. So it is possible that coyotes lack enhanced nighttime vision, compared to other predator species, e.g. bobcats (Lynx rufus). Wells and Lehner (1978) reported the relative priority of senses in locating rabbits for coyotes in the laboratory to be (in order of decreasing importance) vision, audition, and olfaction. Since coyotes are adapted to hunt mainly by pursuit (Bekoff, 1978) and as they rely on visual cues (Horn and Lehner, 1975), seeking lagomorphs in the dark may not be very effective. The “Risk Allocation Hypothesis” proposed by Lima and Bednekoff (1999) argues that temporal variation in risk can actually drive much of the anti-predator behavior observed in nature. They state that when there is a temporal variation in risk, if the periods of high risk are brief, then a foraging animal might choose to stop feeding completely and ride out the “pulse” of high risk in a state of heightened anti-predator behavior; the lost feeding time may then be shifted to low-risk periods. This is what seems to be happening in our study and can explain the partial lack of synchrony between coyotes and lagomorphs.
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In summary, our data partially supports the hypothesis of lack of synchronization between a predator and its prey, showing that in a temporal scale the prey uses part of the day to actively feed when predator activity is low. Thus instead of predator and prey activity patterns overlapping completely, as we would assume, they should be engaged in a temporal behavioral response race (Sih, 1992). Like the spatial behavioral response race proposed by Sih (1992), prey should be seeking those times of the 24 h where predator lethality is low. Predators on the other hand, hunt during peak lethality for a reduced prey base that is more accessible. The outcome of this race then determines how much activity patterns overlap.
Acknowledgements This research was funded by CONACYT-2002-C01-41930/A-1, coordinated by Lucina Hernández, supported under Grant CONACYT no. 179242. We would like to thank Instituto the Ecología, A.C., for founding and facilities given during this research; the people of the Biosphere Reserve of Mapimí for allowing us to conduct the experiments within their rangelands; the two anonymous reviewers for their comments and suggestions, that improve this article; Timothy C. Roth II, provided helpful comments; Matthew Opas for revising the language; Earth Watch Institute volunteers, Juan Pablo Esparza, Manuela Terrazas, Jesus Martinez, and Jesus Manuel Zuñiga, helped with data collection; Karina Grajales for being in charge of the SEMARNAT/CONANP permits that allows us to work; Herrera, Terrazas Díaz, Arias and Del Razo families special thanks for all the help and support. Experimental procedure was consistent with the SEMARNAT/CONANP animal ethic protocols.
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(Ed.), Estudio integrado de los recursos vegetación, suelo y agua en la Reserva de la Biosfera de Mapimí. I. Ambiente Natural y humano. Instituto de Ecología, A.C. Publicación 23, México, p. 290. Park, O., 1940. Nocturnalisme the development of a problem. Ecological Monographs 10, 485e536. Peacor, S.D., Werner, E.E., 2000. Predator effects on an assemblage of consumers through induced changes in consumer foraging behavior. Ecology 81, 1998e2010.
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Rijnsdorp, A., Daan, S., Dijkstra, C., 1981. Hunting in the kestrel, Falco tinnunculus, and the adaptive significance of daily habits. Oecologia 50, 391e406. Ripple, W.J., Bestcha, R., 2003. Wolf reintroduction, predation risk, and cottonwood recovery in Yellowstone National Park. Forest Ecology and Management 184, 299e313. Rogowitz, G.L., 1997. Locomotor and foraging activity of the white-tailed jackrabbit (Lepus townsendii). Journal of Mammalogy 78, 1172e1181. Roth II, T.C., Lima, S.L., 2007. The predatory behavior of wintering Accipiter hawks: temporal patterns in activity of predators and prey. Oecologia 152, 169e178. Rzedowski, J., 1978. Vegetación de México. Limusa, México, D.F. SEMARNAP, 2000. Programa de Manejo: Reserva de la Biosfera Mapimí. SEMARNAP. Comisión Nacional de Áreas Protegidas, México. Sih, A., 1992. Prey uncertainty and the balancing of antipredator and feeding needs. The American Naturalist 139, 1052e1069.
Villafuerte, R., Kufner, M.B., Delibes, M., Moreno, S., 1993. Environmental factor influencing the seasonal daily activity of the European rabbit (Oryctolagus cuniculus) in a Mediterranean area. Mammalia 57, 341e347. Wells, M.C., Lehner, P.N., 1978. The relative importance of the distance senses in coyote predatory behaviour. Animal Behaviour 26, 251e258. Wauters, L.A., 2000. Squirrels e medium-sized granivores in woodland habitats. In: Halle, S., Stenseth, N.C. (Eds.), Activity Patterns in Small Mammals: An Ecological Approach. Springer-Verlag Berlin Heidelberg, Germany, pp. 95e118. Wolton, R.J., 1983. The activity of free-ranging wood mice Apodemus sylvaticus. Journal of Animal Ecology 52, 781e794. Zaret, T.M., Suffern, J.S., 1976. Vertical migration in zooplankton as a predator avoidance mechanism. Limnology and Oceanography 21, 804e813. Zielinski, W.J., 2000. Weasels and martense carnivores in northern latitudes. In: Halle, S., Stenseth, N.C. (Eds.), Activity Patterns in Small Mammals: An Ecological Approach. Springer-Verlag Berlin Heidelberg, Germany, pp. 95e118.
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Journal of Arid Environments journal homepage: www.elsevier.com/locate/jaridenv
Do predator and prey foraging activity patterns match? A study of coyotes (Canis latrans), and lagomorphs (Lepus californicus and Sylvilagus audobonii) I. Arias-Del Razo a, *, L. Hernández b,1, J.W. Laundré b, 2, O. Myers c a
Instituto de Ecología, A.C. Posgrado, Km. 2.5 carretera antigua a Coatepec 351, Congregación El Haya, 91070 Xalapa, Veracruz, Mexico Instituto de Ecología, A.C. Centro Regional Durango, Boulevard del Guadiana 123, Los Remedios 34100, Victoria de Durango, Durango, Mexico c University of New Mexico, MSC 10 5550, 1, Albuquerque, NM 87131, USA b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 1 September 2009 Received in revised form 2 August 2010 Accepted 20 September 2010 Available online 13 October 2010
Many aspects of an animal’s ecology are associated with activity patterns. One important and controversial one is in the predator/prey relationship. We examined temporal patterns of coyotes (Canis latrans) and lagomorphs (Lepus californicus, Sylvilagus audobonii), their main prey in the Chihuahuan Desert. We test the hypothesis that a predator and prey will have non-random distribution of activity relative to each other; this non-random activity could be a substantial overlap or the lack of synchrony depending on the competing theories. We used GPS collars to track coyotes; we identified areas of activity and determined daily patterns. We installed lagomorph feeding stations and game cameras in coyote activity areas to assess lagomorph patterns. All three species were mainly crepuscular. Black-tail jackrabbits and Audubon’s cottontail rabbits had different hourly patterns of activity (P < 0.001). Activity peaks for jackrabbits occurred between 0400e0700 h, and 1800e2000 h. Cottontail rabbit activity peaks occurred between 0500e0700 h, and 1800e2000 h. The coyote evening activity peak was synchronous with lagomorph activity, but the morning peak occurred from 0700 to 1000. We found partial lack of synchrony in the activity patterns of the predator and its prey. Ó 2010 Elsevier Ltd. All rights reserved.
Keywords: Chihuahuan desert Cottontail rabbits Jackrabbit Predator/prey
1. Introduction Many aspects of an animal’s ecology are associated with daily activity, the time of day when that animal is awake and active (Hall and Ross, 2007). When active, an animal’s behavior is an outcome of many conflicting demands. Two major ones are: the activity required to maximize nutritional and reproductive objectives, and the need to minimize costs and risk of predation (Alkon and Saltz, 1988). Times of activity for prey are normally associated with increased mortality risk (Lima and Dill, 1990). The activity of prey relative to predation risk has been studied in a number of different taxa (Blaustein and Fugle, 1981; Fox et al., 1992; Kronfeld-Schor and Dayan, 2003; Lima, 1998; Zaret and Suffern, 1976). Such studies * Corresponding author. Instituto de Ecología, A.C., Departamento de Posgrado. Km 2.5 Carretera Antigua a Coatepec 351, Congregación El Haya, 91070 Xalapa, Veracruz. México. Tel.: þ52 228 842 18 00x2004. E-mail addresses: [email protected] (I. Arias-Del Razo), lhernan1@oswego. edu (L. Hernández), [email protected] (J.W. Laundré), [email protected] (O. Myers). 1 Present address: Rice Creek Field Station, Department of Biological Sciences, 225 Piez Hall, SUNY Oswego, Oswego, NY 13126, USA. 2 Present address: Department of Biological Sciences, 128 Piez Hall, SUNY Oswego, Oswego, NY 13126, USA. 0140-1963/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.jaridenv.2010.09.008
highlight the importance of temporal patterns in vulnerability to predators for prey behavior. For example, nocturnal behavior and moonlight avoidance might be behavioral activity adaptations of herbivorous small mammals to reduce predation risk (Alkon and Saltz, 1988; Clarke, 1983; Kotler et al., 1994; Kramer and Birney, 2001). Another anti-predator strategy for prey would be to avoid an overlap between their hours and the areas of activity and the ones of their predator. On the other hand, studies have shown the importance of activity patterns to the hunting success of predators (Ables, 1969; Asa and Wallace, 1990; Boal and Giovanni, 2007; Geffen and Macdonald, 1993). Temporal feeding activity patterns in predators could be either an innate activity rhythm or a response to an activity pattern of the prey (Giller and Sangpradub, 1993). Studies focused on how prey behaviorally trade-off predation and starvation risk have been instrumental in our understanding of behavioral ecology, social organization, foraging ecology, and evolutionary relationships (Geist, 1974; Jarman, 1974). There is also growing evidence that indirect effects of these trade-offs by the prey can affect other species and have consequences on the dynamics of the entire community (Peacor and Werner, 2000; Ripple and Bestcha, 2003). However, our understanding of the full consequences of this trade-off is limited because we know little about the behavior of predators. This is especially true
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regarding activity patterns of prey and predator. One recent exception is that of Roth and Lima (2007) who examined daily activity patterns of avian prey and their predators under natural conditions. However, more studies like this are needed to better understand the importance of activity patterns in ecology. Activity patterns of coyotes (Canis latrans) have been reported in a variety of different habitats, but without considering activity patterns of their prey (Atwood et al., 2004; Fedriani et al., 2000; Gantz and Knowlton, 2005). Most reported that coyotes are active both day and night, with peaks of activity during crepuscular hours (Andelt, 1985; Gompper, 2002). Lagomorphs, the main prey of coyotes in different habitats, including desert habitats (Andelt et al., 1987; Clark, 1972; Cypher and Spencer, 1998; Delibes et al., 1986; Delibes and Hiraldo, 1987; Fedriani et al., 2000; Hernández and Delibes, 1994; Hernández et al., 1994, 2002; MacCracken, 1982; Marti et al., 1993), are also reported to be nocturnal with evening feeding periods that vary greatly with weather, season, and phase of the moon (Best, 1996). In general, jackrabbits (Lepus spp.) became active within 30 min of sunset, and retreated to daytime forms under shrubs between dawn and sunrise, regardless of season (Costa et al., 1976). Lord (1961) reported that activity of cottontail rabbits (Sylvilagus spp.) began at 1700 h and ceased at about 0700 h. Mech et al. (1966) suggested a relation between onset of activity and sunset, and cessation of activity and sunrise for eastern cottontails (Sylvilagus floridanus) and snowshoe hares (Lepus americanus). They suggest that cessation of activity may be stimulated by a certain light intensity rather than actual sunrise, but they did not consider predation risk and other environmental conditions. In this paper we examined the daily activity patterns of coyotes in the Chihuahuan Desert and, black-tailed jackrabbits (Lepus californicus) and Audubon’s cottontail rabbits (Sylvilagus audobonii), which have been shown to be coyotes main prey (Delibes et al., 1986; Hernández and Delibes, 1994; Hernández et al., 1994, 2002). Although there are temporal and spatial shift responses from predators and their prey, we will only concentrate on the temporal ones. We first used GPS technology to establish activity areas used by coyotes; we then conducted lagomorph feeding trials to estimate hourly activity levels of lagomorphs within the areas previously documented with coyote activity. We used this arrangement to ensure the presence of both, predator and prey in the same areas. We used these data to test the hypothesis that a predator and prey will have non-random distribution of activity relative to each other; this non-random activity could be a substantial overlap or the lack of synchrony depending on the competing theories. 2. Materials and methods 2.1. Study area We conducted our research in the Mapimí Biosphere Reserve (MBR). The Reserve is a protected area located in northern Mexico, between the states of Durango, Chihuahua and Coahuila (26 400 N, 103 400 W). Elevation ranges from 1000e1800 m. Average annual rainfall is 264 mm with 71% of the annual total occurring from June to September. The mean annual temperature is 21 C; in the coldest month (January) the mean is 12 C. Summers are warm, with mean temperatures varying from 24 C in September to 28 C in June (SEMARNAP, 2000). Vegetation is a xerophytic scrub as described by Rzedowski (1978) and consists primarily of creosote (Larrea tridentata), honey mesquite (Prosopis glandulosa), tobosa grass (Pleuraphis mutica), and cacti (Opuntia rastrera) (Montaña, 1988).
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2.2. Coyote 2.2.1. Coyote capture and data collection We trapped coyotes during the winters of 2004 through 2006. We used #3 Oneida Victor soft catch padded jaw traps, positioned on the side of dirt roads. We baited the traps either with sardines, bobcat or coyote urine, or commercial perfume. We monitored traps early in the morning and in the evening. We attached GPS LotekÒ collars only on animals greater than one year old. The collars were programmed to remain on the animal for 9 weeks at which time they automatically released and we then retrieved them. During the nine weeks, collars were programmed to estimate coyote locations every 30 min from 2000 to 0800 h and every 2 h during the daylight hours. We collared ten adult coyotes with GPS collars, five female and five male, ranging in ages from approximately 1.5e5 years old. We obtained location data for two periods: October 2004eApril 2005 and November 2005eApril 2006. Locations in daylight hours were collected on even hours for six coyotes and on odd hours for four coyotes, and therefore activity estimates were available for all hours of the day.
2.2.2. Analysis of coyote data Coyote location data were analyzed to determine (a) relative activity over space to identify areas where lagomorph feeding trials should be conducted, and (b) to determine activity during each hour of the day. We determined activity areas of coyotes based on the grid method (Laundré and Keller, 1981), and determined the level of activity based on the number of Standard Deviations, below and above the mean of relocations/grid. Low use grids were at least 2.9 SD below the mean activity and high use grids were 1.4 SD above the mean of relocations/ grid. For each coyote we identified six activity areas for potential use in lagomorph feeding trials. Calculated distances between successive GPS locations were used as an estimate of coyote movement. Measurements made over different observation time scales (0.5 or 2 h) were normalized to distance moved per hour (km/h) to assess activity patterns (Ables, 1969; Andelt and Gibson, 1979). Before analyses coyote activity measures were log-transformed and then replicate measures within a coyote, hour, and day were averaged to normalize the data and to stabilize residual variances. We used mixed model regression that included random effects for coyotes and dates within coyotes in addition to the residual error variance. The addition of random effects in the analysis accounts for non-independence of repeated observations while allowing unbalanced samples. Measurements made at two time scales may have different variances even after they are normalized to a per unit time basis. We tested whether a heterogeneous variance model was necessary by formulating the residual variance as a log-linear function of the two measurement scales. We also conducted a sensitivity analysis by preparing a thinned dataset that included only 2-h location intervals to see if the different location interval had important effects on results. Fixed effects in the model included sex, hour of day, and month. We did not include interactions in our main analyses to test whether within day activity varied with sex or month, because replication of coyotes within sexes and of months was limiting, however we did test for interactions in supplemental analyses. Analysis models were fitted by maximum likelihood (SAS v9.2Ò, proc mixed), and predicted population-averaged geometric mean activity estimates for each hour (km/h and 95% confidence interval) were obtained by exponentiation of the least squares adjusted means and confidence interval bounds.
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2.3. Lagomorph 2.3.1. Lagomorph data collection To estimate activity of lagomorphs, we conducted 30 feeding trials in areas within low, moderate and high levels of coyote activity described above. Activity areas for five coyotes that wore their collars for nine weeks and had at least forty-two 24 h complete blocks (range: 42e55) were used to conduct lagomorphs feeding trials. Two feeding trays were established in each of the low, moderate, and high activity strata for each coyote home range, which provided a total of 30 feeding stations, six for each animal (Fig. 1). It is commonly accepted that when active, feeding activity occupies most of an animal’s time (Wolton, 1983), taking up to 70% of an animal’s active period (Wauters, 2000). Thus, we used this feeding time as a general index of activity level. Lagomorph activity was assessed during three periods: NovembereDecember 2005, FebruaryeMay 2006 and FebruaryeMarch 2007. At each tray we placed digital game cameras (Leaf River DC-1BUÒ) that were active for 24 h for at least six days with a maximum of 25 days. We filled the 30 40 cm trays with 500 g of loose alfalfa and placed them 4.5 m away from the camera, the feeders were positioned at least 2 m from surrounding bushes. We set up the camera on a 2 4 cm wooden stake at a height of 30 cm from the ground. The motion sensor was set to capture first and second movements, with a 3 min delay between photographs. All animals were counted in each photograph, unless they were hard to see in the picture or if it was difficult to define the species because they were too far from the camera. We could not identify individual lagomorphs, so we could not assign photographs to particular individuals. Therefore we used the number of photographs taken per hour as our primary measure to assess temporal activity patterns of lagomorphs.
2.3.2. Analysis of lagomorph data The effect of time of day and coyote activity level on counts of lagomorphs photos per hour was analyzed using generalized mixed model regression to account for repeated measurements. The analyses employed a log link between the mean response and linear predictor variables, such as species, coyote activity level and hour, and assumed a Poisson response probability distribution. The analyses also included an additional random effect variance terms for coyote home ranges and for sample dates within location to account for correlation of repeated measurements. Primary fixed effects in the model were species, coyote activity level, hour of day, species hour interaction, and sampling location. An overdispersion parameter was used to inflate variances to account for remaining sources of variation not accounted for by the analysis. Analysis models were conducted using SAS v9.2 (SAS v9.2Ò, proc glimmix). Predicted population-averaged geometric mean activity estimates for each hour (photos/h and 95% confidence interval) were obtained by taking the exponent of the least squares adjusted means and confidence interval bounds. 3. Results 3.1. Coyote activity patterns The results of our coyote activity analysis based on logtransformed km/h estimates for movement distances showed that activity was not uniform over the day (p < 0.001) and that there were two main peaks of activity; one in the morning between 0700 and 1000 h and another in the evening between 1800 and 2000 h (Fig. 2). A heterogeneous variance model was used to estimate movement rates and confidence intervals, because the residual variance for the 2 h intervals was 1.38 times the variance for the 0.5 intervals (p < 0.001
Fig. 1. An example, GPS locations of one coyote and six feeding tray locations at MBR.
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Fig. 2. Coyote activity at MBR as determined by mixed model regression analysis of GPS locations collected during October 2004eApril 2005 and November 2005eApril 2006; Error bars are 95% confidence intervals.
95% CI ¼ 1.30e1.48). Sex (p ¼ 0.97) and month (p ¼ 0.08) were not associated with coyote activity levels. When we subjected these analyses to the thinned dataset containing only 2 h location intervals we found no compelling evidence that different location intervals had important effects on the coyote activity pattern analysis. Crepuscular peaks and nighttime km/h are slightly lower and confidence intervals were wider, but the overall pattern was unchanged. We conducted a supplemental analysis to assess whether female and male coyote had the same temporal activity patterns. The effect of sex hour was highly significant (p < 0.001), which means that on the log scale of analysis the mean response over hours for females and males were not parallel. The net effect seen was that females in this sample increased their evening activity an hour earlier than males (1700 vs. 1800), but the results were more uncertain because of the larger number of parameters needed to describe unique temporal patterns for each sex. Given the minimal replication of coyotes within sex we doubt that the small differences in patterns have ecological relevance. 3.2. Lagomorph activity patterns We conducted analyses to evaluate whether cottontail rabbits and jackrabbits had different temporal patterns of activity and whether activity was affected by predetermined coyote activity levels. Although we obtained 1045 photographs of black-tail jackrabbits, and 894 of cottontail rabbits, lagomorph photos were rare during the daylight hours with no photos containing cottontail rabbits taken during the hours of 1000e1600 over the study and only two photos with jackrabbits taken during these hours. Therefore lagomorph activity during these hours was at or below the practical limit of detection for these methods. The sparseness of
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the photo record during these hours caused numerical problems for analyses, and therefore the hours 1000e1600 could not be included in some analyses. Because of the numerical problems caused by zeros, Fig. 3A, shows the crude photo/h with 95% Poisson confidence intervals based on a summation over all locations and dates. The point estimates for activity are unbiased but the confidence intervals are too narrow, because they do not account for repeated measurements. The confidence intervals were retained in the figure to provide a rough estimate of the relative uncertainty. Additional results from subset analyses that excluded hours 1000e1600 are shown in Fig. 3B. Due to the sparseness of lagomorph photos in some hours even after excluding hours 1000e1600, we were unable to obtain numerical convergence of statistical algorithms when we attempted to test whether lagomorph activity was determined by a species coyote activity hour interaction. Analyses proceeded by dropping the threeeway interaction and testing for a significant species hour effect (p ¼ 0.02) on activity and a species coyote activity effect (p < 0.001) after adjusting for month of sample (p ¼ 0.42). The average hourly pattern of lagomorph activity is shown in Fig. 3B. The overall detection rates were similar for cottontail rabbits 0.09 photos/h (95% CI ¼ 0.04e0.21) and for jackrabbits 0.16 photos/h (95% CI ¼ 0.07e0.38), however the significant species hour interaction (p < 0.001) indicates there were some differences in the temporal patterns despite the considerable variation in estimated activity. These results show a somewhat more pronounced crepuscular pattern for jackrabbits than cottontails. Activity peaks for jackrabbits occurred between 0400e0700 h, and 1800e2000 h. Cottontail rabbit activity peaks occurred between 0500e0700 h, and 1800e2000 h. No lagomorph activity could be detected at feeding trays during 1000e1600. We next conducted separate analyses for rabbits and jackrabbits to ascertain whether hourly lagomorph activity varied with coyote activity level. Lagomorph activity differences among different coyote activity levels were approximately proportional with the hour coyote interaction test failing with p > 0.9 for both species (Fig. 4). If the interaction was significant we would have observed more crossing or divergence of the activity rate lines over time. The hypothesis of proportionality is appropriate because the Poisson analysis employs a log link between the mean and the response variable. 3.3. Predator/prey activity patterns Activity assessments for lagomorphs and coyotes were made using different instruments, which produced different activity measures (photos/h and km/h), and therefore graphical methods were used to evaluate species differences in temporal activity patterns described above (Fig. 5). Because there were no differences in activity patterns of cottontail rabbits and jackrabbits among the
Fig. 3. Crude (A) and predicted (B) lagomorphs activity (photos/camera-hour). Error bars for crude rate are 95% Poisson confidence intervals, and error bars for the adjusted rates are from a mixed model regression analysis that adjusted for month and coyote activity levels. Note different scale for y-axes.
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Fig. 4. Lagomorph crude activity rates (photos/camera-hour) at low, moderate, and high coyote activity level areas for cottontail rabbits (A) and black-tailed jackrabbits (B). Error bars are 95% Poisson confidence intervals but do not account for repeated measurements.
Fig. 5. Comparison of activity levels for coyotes (km/h), cottontail rabbits and jackrabbits (photos/camera-hour) at MBR.
three activity levels of coyotes, we combined the data per species for this analysis. Coyotes and lagomorphs were all least active during daylight hours and had crepuscular activity peaks. The evening peak for all three species was around 1900 h, but morning peaks for lagomorphs were between about 0400e0700 compared to 0700e1000 for coyotes. 4. Discussion and conclusions Relative to our proposed hypotheses, our data partially supported the one suggesting lack of synchrony in the activity patterns of coyotes and lagomorphs evening peaks were synchronous but morning peaks were less so (Fig. 5). As in most studies, we found that coyotes were mainly crepuscular with substantial activity extending into the day. We also observed that the morning coyote activity peak was later than for lagomorphs. Neither species of lagomorphs had detectable levels of activity during the daylight hours. The game theory model suggests that predator activity should match the pattern of its prey closely, and that prey will largely drive the temporal dynamics of the game: when prey is most active, the predator should be too (Kotler et al., 2002). These predictions are supported by some studies of predatory birds (Rijnsdorp et al., 1981) that state that small mammals are only available to raptors when they are active. However, mammalian predators and their prey have not been the subjects of similar studies (Zielinski, 2000). The general activity pattern of lagomorphs in semi-arid environments seems to be a balance between antipredatory and thermoregulatory strategies (Villafuerte et al., 1993). The almost consistent lack of lagomorphs activity during the day is possibly
related to their avoidance of high daytime temperatures (Bradley, 1967; Ilan and Yom-Tov, 1990; Rogowitz, 1997). The fact that some activity is noted on cloudy days, and thus, lower temperatures, seems to support this hypothesis (Villafuerte et al., 1993). In contrast, it has been argued that high predation risk during the day is considered the reason that most small mammals are nocturnal or crepuscular (Park, 1940; Daan and Aschoff, 1982). Darkness provides some cover from predators, or if predation pressure at night is less than during the day, nocturnal activity may be favored by selection (Zielinski, 2000). Though arguments can be presented for both hypotheses, regardless of the actual driving force, lagomorphs are not very active during the daytime. Because of this lack of daytime lagomorph activity, our study concentrated on the timing of activity from dusk to dawn. During this time, temperatures become less of a factor, and the timing of lagomorph foraging activity suggests that they might be taking some advantage to actively feed early in the morning and during the night, when predation risk is lower, avoiding coyotes, its principal predator (Hoffmeister, 1986). The question then becomes why coyotes would not seem to overlap completely their hours of activity with the ones of their main prey? Zielinski (2000) states predators that hunt primarily using sight and sound should forage during the active phase of their prey, when they are most vulnerable and producing cues that betray their location. However, Bider (1962) suggested that activity peaks of carnivores are related to senses used in hunting. Coyote eyes appear to be a compromise designed for crepuscular activity (Bekoff, 1978). Both the coyote’s scotopic sensitivity (Horn and Lehner, 1975) and activity patterns in the laboratory (Kavanau and Ramos, 1975) suggest a crepuscular activity proclivity. So it is possible that coyotes lack enhanced nighttime vision, compared to other predator species, e.g. bobcats (Lynx rufus). Wells and Lehner (1978) reported the relative priority of senses in locating rabbits for coyotes in the laboratory to be (in order of decreasing importance) vision, audition, and olfaction. Since coyotes are adapted to hunt mainly by pursuit (Bekoff, 1978) and as they rely on visual cues (Horn and Lehner, 1975), seeking lagomorphs in the dark may not be very effective. The “Risk Allocation Hypothesis” proposed by Lima and Bednekoff (1999) argues that temporal variation in risk can actually drive much of the anti-predator behavior observed in nature. They state that when there is a temporal variation in risk, if the periods of high risk are brief, then a foraging animal might choose to stop feeding completely and ride out the “pulse” of high risk in a state of heightened anti-predator behavior; the lost feeding time may then be shifted to low-risk periods. This is what seems to be happening in our study and can explain the partial lack of synchrony between coyotes and lagomorphs.
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In summary, our data partially supports the hypothesis of lack of synchronization between a predator and its prey, showing that in a temporal scale the prey uses part of the day to actively feed when predator activity is low. Thus instead of predator and prey activity patterns overlapping completely, as we would assume, they should be engaged in a temporal behavioral response race (Sih, 1992). Like the spatial behavioral response race proposed by Sih (1992), prey should be seeking those times of the 24 h where predator lethality is low. Predators on the other hand, hunt during peak lethality for a reduced prey base that is more accessible. The outcome of this race then determines how much activity patterns overlap.
Acknowledgements This research was funded by CONACYT-2002-C01-41930/A-1, coordinated by Lucina Hernández, supported under Grant CONACYT no. 179242. We would like to thank Instituto the Ecología, A.C., for founding and facilities given during this research; the people of the Biosphere Reserve of Mapimí for allowing us to conduct the experiments within their rangelands; the two anonymous reviewers for their comments and suggestions, that improve this article; Timothy C. Roth II, provided helpful comments; Matthew Opas for revising the language; Earth Watch Institute volunteers, Juan Pablo Esparza, Manuela Terrazas, Jesus Martinez, and Jesus Manuel Zuñiga, helped with data collection; Karina Grajales for being in charge of the SEMARNAT/CONANP permits that allows us to work; Herrera, Terrazas Díaz, Arias and Del Razo families special thanks for all the help and support. Experimental procedure was consistent with the SEMARNAT/CONANP animal ethic protocols.
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