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Summer roadside use by White-tailed Deer and Mule Deer in the Rocky Mountains, Alberta.

ABSTRACT--Deer-vehicle collisions are on the rise in North America, requiring a better understanding of road use patterns by deer. We examined summer use of roadside areas by White-tailed Deer (Odocoileus virginianus) and Mule Deer (Odocoileus hemionus) in the central Rocky Mountains, Alberta. Deer surveys were conducted along the main highway at dawn and dusk for 6 summers. We observed more White-tailed Deer than Mule Deer along the highway during the study. White-tailed Deer were also involved in collisions with vehicles more often than Mule Deer, and may pose a higher risk for collisions because they tend to flee when approached. Time of day did not affect Mule Deer sightings during the study period, but White-tailed Deer were observed more frequently in the morning than evening. Both species were observed more frequently in May than other months. While little association was observed between deer species, large-scale spatial segregation along the highway did not occur. Our data suggest that drivers were likely to encounter deer in single-species pairs, and based on deer roadside use, we suggest that the potential for deer-vehicle collisions was highest in May, close to dawn, and along the northern sections of the highway. Deer-vehicle collision data indicated that the predominant locations of collisions reflected the spatial patterns of roadside usage by deer, but temporal patterns of collisions are also affected by visibility and traffic patterns. Collision-mitigation strategies incorporating deer behavior and driver-education are discussed.

Key words: Alberta, deer-vehicle collisions, group size, highway, Kananaskis Valley, Mule Deer, Odocoileus hemionus, Odocoileus virginianus, road use, White-tailed Deer


White-tailed Deer (Odocoileus virginianus) and Mule Deer (Odocoileus hemionus) are closely related species that are found across many regions of North America. While the primary distribution of White-tailed Deer is in eastern North America and Mule Deer in the west, these 2 species often occur sympatrically (Whittaker and Lindzey 2004). Their feeding habits are similar (Anthony and Smith 1977; Krausman 1978), but they primarily use different habitats. Mule Deer are often found in rugged and open terrain, while White-tailed Deer select less rugged, forested habitat (Wiggers and Beasom 1986; Avey and others 2003; Whittaker and Lindzey 2004). However, both species can use a variety of habitats, resulting in sympatry (Anthony and Smith 1977; Wiggers and Beasom 1986; Brunjes and others 2009a, 2009b).

Spatial and temporal resource partitioning are necessary for similar species to coexist in sympatric areas (Caughley and Sinclair 1994). Kramer (1973) suggested that these strategies, as well as avoidance behaviors, may allow the coexistence of White-tailed Deer and Mule Deer in southeastern Alberta. In central Colorado, Whittaker and Lindzey (2004) also showed that avoidance and seasonal differences in habitat use by the 2 species permit coexistence without direct competition. Similarly, competition was not observed between White-tailed Deer and Mule Deer in northern Montana, even though their use of forage classes was very similar, because each preferred and mainly consumed distinct plant species (Martinka 1968). Differences in anti-predator behaviors between species also facilitate habitat segregation at different scales (Lingle 2002). While the habitat use and sympatry of White-tailed Deer and Mule Deer are well-known for forested and prairie habitats, information on their particular use of roadside areas is scarce.

Incidents of collisions between deer and vehicles are increasing in North America, attributed to increases in traffic volume and the populations of both humans and deer (Putman 1997; Gunson and others 2004; Hussein and others 2007). Total economic losses due to large mammal-vehicle collisions are estimated at $111 million/y in Canada (Transport Canada 2003). Deer have been shown to prefer clearings with adjacent forest cover over completely forested areas, potentially explaining, in part, their attraction to roadside areas (Farrell and Tappe 2007; Stewart and others 2007). These areas are often groomed, containing easily digestible forbs and grasses, and collisions between deer and vehicles occur most frequently when the verges are narrow (Vangilder and others 1982; Found and Boyce 2011). Attraction to salt likely also contributes to the attraction of deer to roadsides (Laurian and others 2008).

Given the significance of roadside habitat to deer, and their increasing interactions with humans, we believe that the use of roadsides by White-tailed Deer and Mule Deer requires further investigation. To accomplish this, we examined the summer use of roadside areas in the Kananaskis Valley, Alberta, Canada, by White-tailed Deer and Mule Deer over a 6-y period. We used surveys along the main highway to assess spatial and temporal patterns of sightings, association, and social organization of the 2 deer species, and consider the implications for deer-vehicle interactions.


Study Area

The Kananaskis Valley is a 4200-[km.sup.2] multiuse area located in the front ranges of the Canadian Rocky Mountains, approximately 70 km west of the city of Calgary, Alberta. The main land use is recreational, and given its close proximity to Calgary, tourist visitation is very high during the summer months. Summer average traffic volume (Highway 40) has been estimated at 2850 vehicles/d between 2005 and 2010 (Alberta Transportation 2012). Between 2005 and 2009, 66.1% of recorded wildlife-vehicle collisions in the Kananaskis Valley involved deer, and 76.0% of all recorded deer-vehicle collisions occurred between May and August (Office of Traffic Safety, Alberta Transportation, unpubl, data).

One main highway (Highway 40) runs through the Kananaskis Valley in a north-south orientation, with roadsides primarily composed of managed (mowed) grassy areas containing numerous forbs (for example, Achillea millefolium, Castilleja miniata, Hedysarum sulphurescens, Taraxacum officinale), sedges (Carex spp.), grasses, and other short browse species (for example, Salix spp. and Shepherdia canadensis). Riparian areas can also be found along a few sections of the highway. Roadsides containing low-height vegetation span several meters perpendicular to the highway, followed by dense stands of Quaking Aspen (Populus tremuloides) and lower subalpine mixed conifer forests (White Spruce, Picea glauca, and Lodgepole Pine, Pinus contorta).

The elevation of our study area ranges from 1390 to 1650 m. During our study period, precipitation averaged 32.2 cm/y and temperature ranged from -10.4 to 34.3[degrees]C (Environment Canada 2012). Deer hunting was not permitted during the season when our observations were made.

Deer Surveys

We conducted deer surveys between early May and the end of August from 2005 to 2010. We observed deer along a 33-kin fixed transect approximately 4 d/wk shortly after sunrise or before sunset. These times were selected because the activity level of White-tailed Deer has been shown to peak at dawn and dusk (Montgomery 1963; Rouleau and others 2002). Surveys were conducted by driving south on Highway 40 between the University of Calgary Biogeosciences Institute (UTM: Zone 11, 637506E, 5654844N, WGS84) and Fortress Mountain (UTM: Zone 11, 629670E, 5627457N, WGS84); the duration of each trip was approximately 30 min. If deer were observed on or directly beside the road, we recorded the species, number of individuals, and location of observation (distance travelled from the University of Calgary Biogeosciences Institute). Roadside sightability was consistent throughout the transect.

Data Analysis

Analyses were performed using IBM SPSS Statistics 19.0 (SPSS 2010) and SAS 9.2 (SAS Institute 2010). Differences among groups were considered statistically significant at P [less than or equal to] 0.05. Data are presented as means [+ or -] SE.

Generalized linear mixed models were used to test for differences in the numbers of White-tailed Deer and Mule Deer observed per survey among months and times of day (morning versus evening). Data from all years were combined, and year, and week of survey nested within year were included as random factors. Log link functions and negative binomial error distributions were applied in the analyses, and sequential Bonferroni adjustments were used for pairwise post-hoc comparisons where appropriate. Similar models were used to test for differences between the numbers of White-tailed Deer and Mule Deer observed per survey, and among the numbers of White-tailed Deer, Mule Deer, and mixed-species groups observed per survey. Group types were defined as either a solitary animal, or as 2 or more deer [less than or equal to] 100 m apart and >100 m from another deer. Differences in group sizes were examined using generalized linear mixed models with the weekly average number of deer observed per survey (White-tailed Deer, Mule Deer, or both, respectively) included as a covariate; year, and week of survey nested within year included as random factors; and with log link functions and Poisson error distributions. Sequential Bonferroni adjustments were used for pairwise post-hoc comparisons.

The degree of association between deer species was examined using similarity coefficients, which were based on the observed grouping patterns of White-tailed Deer and Mule Deer. Numerous similarity coefficients have been used in the literature, each with its own merits and biases (see Legendre and Legendre 1998). Consequently, we used 2 independent coefficients to describe monthly and annual patterns of cohesion between the species. The coefficient of species association, described by Whittaker and Fairbanks (1958) and modified by Southwood (1966), ranges from complete association (+1) to repulsion (-1). Jaccard's coefficient of community (Jaccard 1901) assesses the degree of association between 2 species and ranges from 0 to 1, ascending in positive association. We also used multiple regressions to examine the relationship between monthly similarity coefficients and the corresponding numbers of White-tailed Deer and Mule Deer observed per survey.

Use of sections of the highway by White-tailed Deer and Mule Deer was examined to determine whether both species were present along the extent of the highway, or if differential clustering and large-scale spatial segregation were present. For this analysis, the highway was partitioned into discrete, equally available sections (resources), and each species' occupation of each section was evaluated using generalized linear mixed models to estimate coefficients of resource selection (resource selection functions, RSFs) (Manly and others 2002; Gillies and others 2006; McLoughlin and others 2010). The models estimated RSFs for each species in each year by evaluating the observed presence-absence of at least 1 individual in each section for each survey. Week of survey was included as a random factor, and logit link functions and binomial error distributions were applied in the analyses. Species-specific RSFs for 2 spatial scales, 3-km sections and-8 km sections, were modelled each year. Partitioning the highway into 3-km sections represented the smallest spatial scale, allowing the maximum number of parameters for models to achieve convergence; 8-km sections were selected because they partitioned the highway approximately into quarters.


We conducted 399 deer surveys over the course of the study period; 16.63 [+ or -] 0.65 surveys were conducted each month (range = 10 to 21), while 33.00 [+ or -] 1.55 (range = 29 to 37) morning surveys and 33.50 [+ or -] 1.18 (range = 30 to 37) evening surveys were conducted per year.

Number of Deer Observed

More White-tailed Deer were observed per survey than Mule Deer during the study ([F.sub.1,790] = 62.32, P < 0.001; Fig. 1), with no interaction detected between deer species and month ([F.sub.3,790] = 0.61, P = 0.61). We also detected no interaction between time of day and month when examining temporal variation in the numbers of White-tailed Deer ([F.sub.3,391] = 2.20, P = 0.09) and Mule Deer ([F.sub.3,391] = 1.11, P = 0.35) observed per survey. More White-tailed Deer were observed per survey in the morning than in the evening ([F.sub.1,391] = 54.28, P < 0.001), but there were no differences in the number of Mule Deer observed between morning and evening surveys ([F.sub.1,391] = 1.88, P = 0.17; Fig. 2). The numbers of both White-tailed Deer ([F.sub.3,391] = 39.82, P < 0.001) and Mule Deer ([F.sub.3,391] = 16.09, P < 0.001) observed per survey differed among months, with the highest number of deer from both species observed in May (all P < 0.001; Fig. 3). More White-tailed Deer were also observed per survey in June than July (P = 0.002) and August (P = 0.005), but no difference was observed between the latter 2 months (P = 0.64; Fig. 3). The number of Mule Deer observed per survey did not differ among June, July, and August (all P [greater than or equal to] 0.09; Fig. 3).

Group Dynamics

We detected differences in the numbers of each type of group observed per survey ([F.sub.2,1194] = 85.03, P < 0.001). White-tailed Deer groups were most common (both P < 0.001) and an intermediate number of Mule Deer groups were observed (P < 0.001), while mixed-species groups were rare (both P < 0.001; Fig. 4). Group sizes also differed among the group types ([F.sub.2,957] = 14.92, P < 0.001), with mixed-species groups being largest (both P [less than or equal to] 0.001), but no difference observed between White-Tailed Deer and Mule Deer groups (P = 0.22; Fig. 5).

Spatial Dynamics

Similarity Coefficients.--Most months of each year, and most years in total, had very high negative coefficients of species association (Table 1), suggesting a fairly strong repulsion between White-tailed Deer and Mule Deer. The multiple regression model examining the relationship between monthly coefficients of species association and the corresponding numbers of White-tailed Deer and Mule Deer observed per survey was significant ([R.sup.2] = 0.41, [F.sub.2,21] = 7.35, P = 0.004), with the majority of variation in monthly coefficients explained by the numbers of Mule Deer observed (B = 0.07 [+ or -] 0.02, t = 3.74, P = 0.001, Square semi-part correlation = 0.39). This indicates that greater interaction between species occurred when more Mule Deer were present. White-tailed Deer observations did not contribute significantly to variation in species association (t = -1.38, P = 0.18).

Similarly, Jaccard's coefficient of community was very small for all months and all years in total (Table 1), indicating a low degree of association between the 2 species. The multiple regression model examining the relationship between Jaccard's coefficients and the corresponding numbers of White-tailed Deer and Mule Deer observed per survey was also significant ([R.sup.2] = 0.34, [F.sub.2,21] = 5.32, P = 0.01), with the majority of variation in coefficients explained by the numbers of Mule Deer observed (B = 0.02 [+ or -] 0.01, t = 3.18, P = 0.01, Square semi-part correlation = 0.32). White-tailed Deer observations did not contribute significantly to variation in species association (t = -1.15, P = 0.26).

Resource Selection Functions.--When the highway was partitioned into 3-km sections, estimated White-tailed Deer and Mule Deer RSFs were not significant (all P [greater than or equal to] 0.14) in all years, indicating that no selection or avoidance of highway sections by either species could be detected at this relatively small spatial scale. When we partitioned the highway into 8-km sections, we detected that both species selected the northern sections of the highway over the southern sections, and large-scale segregation between the 2 species was rarely observed. RSFs showed that White-tailed Deer were present in highway sections 1 or 2, or both, more frequently than the other 2 sections in all years, using section 2 most heavily (Fig. 6). Section 2 was also highly selected by Mule Deer in each year, but their overall RSF pattern indicated greater use of most of the highway sections, and less spatial clustering, than White-tailed Deer (Fig. 6). Significant (P [less than or equal to] 0.04) inverse RSFs between the 2 species were detected in 2005 and 2010 for sections 4 and 3, respectively (Fig. 6), indicating that Mule Deer were using these specific sections heavily, but White-tailed Deer appeared to be avoiding these areas. However, these 2 y were the only occurrences of this phenomenon, which we would expect to be very common if the 2 species were consistently avoiding each other via large-scale spatial segregation.


We observed greater numbers of White-tailed Deer than Mule Deer in roadside areas during the study period. It is possible that this disparity reflects the relative abundances of these species in the Kananaskis Valley, although it is also possible that White-tailed Deer simply used roadside areas more than Mule Deer, regardless of the abundances of the species. However, the latter is unlikely, given that Mule Deer: (1) would also have been attracted to the easily digestible grasses and forbs present beside the road (Vangilder and others 1982); (2) are more likely than White-tailed Deer to select open habitats (Wiggers and Beasom 1986; Avey and others 2003; Whittaker and Lindzey 2004); and (3) have been reported as being dominant over White-tailed Deer during interspecific interactions (Anthony and Smith 1977). Both species are sensitive to traffic disturbance and avoid roadsides to a similar degree when traffic volume is high (Pelletier 2006). Overall, we believe that our observations of more White-tailed Deer on the roadside likely reflect their relative abundance in the Kananaskis Valley.

White-tailed Deer flee when they are confronted by a predator, whereas Mule Deer remain in place and aggressively defend themselves, their offspring, and group members (Lingle and others 2005). This difference in anti-predator behavior may have important implications for deer-vehicle collisions because White-tailed Deer may be more likely to scatter, either alongside or across a road, if they feel threatened by an approaching vehicle. Deer-vehicle collision data in our study area (Office of Traffic Safety, Alberta Transportation, unpubl. data) did not discriminate between species, but we most often observed White-tailed Deer fleeing across the road when our vehicle was approaching, while Mule Deer rarely did so. We also obtained deer-vehicle collision records from the provincial wildlife management agency that were less comprehensive, but occasionally discriminated between deer species. Between 2006 and 2010, 77.3% of deer-vehicle collisions in our study area that identified the deer species (n = 22) involved White-tailed Deer, as did 81.3% of collisions (n = 91) on the nearby Trans-Canada Highway (Alberta Sustainable Resource Development, unpubl, data). However, this disparity is likely heavily influenced by the apparent higher abundance of White-tailed Deer in our study area, where 71.0 [+ or -] 4.8% of all deer observed per year in our study (n = 319.00 [+ or -] 20.42) were White-tailed Deer. Overall, it is unclear to what degree species-specific differences in behavior contribute to differences in collision rates, and should be the focus of further study.

The activity level of White-tailed Deer has been shown to peak at dawn and dusk (Montgomery 1963; Rouleau and others 2002). We observed more White-tailed Deer in roadside areas near dawn than dusk, but time of day did not influence Mule Deer sightings. We also observed more individuals of both deer species in roadside areas in May compared to other summer months. This is likely because parturition occurs in early to mid-June for both species (Whittaker and Lindzey 1999; Lingle and others 2005), after which females spend more time in dense vegetation where their fawns are better able to hide from predators (Lent 1974; Lingle and others 2005). Unfortunately, we were not able to test this hypothesis because we did not record the sex and age class of individuals observed in roadside areas. Deer may have also been more attracted to roadside areas in May due to the increased sodium concentration found in vegetation along highways in the spring and early summer (Laurian and others 2008). Sodium intake by deer and other ungulates can be below optimal levels in the winter, causing preferential feeding on sodium-rich vegetation in roadside areas following winter (Weekes and Kirkpatrick 1976; Belovsky and Jordan 1981; Fraser and others 1982; Laurian and others 2008).

Group dynamics in roadside areas may affect the potential for deer-vehicle collisions, depending on the number, size, and composition of groups present. We observed more groups of White-tailed Deer than Mule Deer per survey, and based on species-specific responses to potential threats, the risk of collisions could be higher if White-tailed Deer groups are more common and larger than Mule Deer groups along the road. In this scenario, drivers would likely have to respond to several deer fleeing during a single encounter, possibly in different directions. However, group size did not differ between White-tailed Deer and Mule Deer in roadside areas in our study, which is similar to their summer grouping patterns observed away from roads (Lingle 2003). On average, both species of deer congregated in pairs, and the movements of 2 or more deer along the roadside are potentially more distracting to drivers than solitary individuals, but the risk of collision may be mitigated by improved detection of deer when multiple individuals are present. According to Blackwell and Seamans (2009), group size also had no effect on the distance from an approaching vehicle that initiated the fleeing response of White-tailed Deer in their study area (Ohio, USA).

We observed very few mixed-species groups in roadside areas, and mixed-species groups were often larger than single-species groups. Kramer (1973) also reported very few mixed-species groups observed in southeastern Alberta (1.2% of 2178 observed groups). Enhanced predator detection is reported as being the main advantage of mixed-species grouping by ungulates (Lingle 2001; Stensland and others 2003). However, when being preyed upon in the winter, White-tailed Deer and Mule Deer in mixed-species groups split up, with each species performing their typical defensive behaviors (Lingle 2001). This is also likely the case in the summer, because the preferred defensive behaviors of each species are consistent across seasons (Lingle 2001; Lingle and others 2005). We would expect to observe a larger number of mixed-species groups if individuals maintained their grouping in order to actively deter an attack, or if mixed-species grouping conferred substantial foraging benefits. Grazing and browsing species would receive no real foraging advantage from mixed-species groups, with competition for food likely being a larger confounding issue (Stensland and others 2003).

A very low degree of association was observed between White-tailed Deer and Mule Deer in roadside areas throughout the study. While competitive exclusion has been reported between sympatric White-tailed Deer and Mule Deer (Anthony and Smith 1977), it is more likely that the 2 species simply avoid each other (Kramer 1973; Krausman 1978; Wiggers and Beasorn 1986; Whittaker and Lindzey 2004), resulting in the small-scale spatial segregation we observed. Whittaker and Lindzey (2004) speculated that lower population sizes of White-tailed Deer and Mule Deer allow for avoidance between species, but that increases in the population size of either species may restrict the ability of individuals to avoid each other, leading to less segregation and increased interactions between species. Spatial segregation and single-species grouping are more prevalent when the number of White-tailed Deer observed per survey is relatively high, but an increased presence of Mule Deer leads to greater interaction. In general, drivers can expect to encounter both deer species along the extent of the highway, but in segregated groups, and are likely to encounter more individuals of each species within the first 2 (northern) highway sections.

Based on our observations of summer roadside use by White-tailed Deer and Mule Deer in the Kananaskis Valley, the potential for collisions is highest in May, close to dawn, and within the first 2 (northern) sections of the highway. When examining actual incidences of deer-vehicle collisions in our study area between 2005 and 2009, most collisions occurred in the 1st section of the highway (Fig. 7), as was expected based on increased use of this area by both species. However, temporal patterns of collisions do not directly correspond to the greatest use of roadside areas by deer. The greatest proportion of collisions occurred in July and June, respectively, likely due to increased daily traffic volumes during those time periods, but it is unclear why relatively few deer-vehicle collisions occurred in August, even though daily traffic volumes were close to peak levels (Fig. 7, Fig. 8a). The times of day when the majority of collisions occurred were in the afternoon (12:00 to 17:00) and at night to just before dawn (21:00 to 05:00) (Fig. 7). Hourly vehicle traffic peaked in the Kananaskis Valley in the afternoon (Fig. 8b), increasing the risk of collisions with deer at this time of day. Hourly vehicle traffic was lowest at night (Fig. 8b), but the decreased visibility of deer could account for the increased frequency of collisions during these hours (Mastro and others 2010). While the predominant locations of collisions reflect the spatial patterns of roadside use by deer, temporal patterns of collisions are not as straightforward (see Allen and McCullough 1976).

While there is signage along Highway 40 that warns drivers of the presence of deer, other techniques that incorporate and account for the spatial and temporal patterns of deer use of roadside areas can be used to help plan mitigation strategies to reduce the risk of deer-vehicle collisions in the Kananaskis Valley. Road-lighting (Reed and Woodward 1981) and lower speed limits along the northern sections of the highway would allow drivers to identify roadside deer earlier and reduce their speed in this high-risk zone. Detailed signage alerting motorists to the times of greatest risk of collisions would also be beneficial, as would increased enforcement of speed limits during those times. Use of alternative de-icing salts, such as calcium chloride, lithium chloride, or calcium-magnesium acetate, would likely attract fewer deer to roadsides in the spring and early summer (Brown and others 2000; Laurian and others 2008). Frequent clearing of vegetation in roadside areas throughout the summer would serve a similar purpose, while potentially increasing the visibility of deer (Lavsund and Sandegren 1991); however, clearing may have the opposite effect if overall forage palatability is enhanced, thereby attracting deer to the roadside (Vangilder and others 1982). Use of intercept feeding using, for example, alfalfa hay and deer pellets (Wood and Wolfe 1988) can be very effective in attracting deer away from roadsides, and can be targeted at months and locations of high roadside use and frequent deer-vehicle encounters (Romin and Bissonette 1996). Incorporating deer behavior and roadside use with enforcement and driver-education strategies would likely ensure the greatest success at mitigating deer-vehicle collisions.


We thank the staff at the Biogeosciences Institute of the Canadian Rockies and Foothills (University of Calgary) for their support, as well as the many field assistants from 2005 to 2010 who helped with data collection. We also thank Alberta Transportation and JT Jorgenson at Alberta Sustainable Resource Development for providing us with traffic and wildlife-collision data, and RL Hoffman, TS Jung, and two anonymous reviewers for their comments on a previous version of the manuscript. Funding was provided by the Natural Sciences and Engineering Research Council of Canada and the Ontario Graduate Scholarship Program.


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Submitted 3 February 2012, accepted 6 March 2013. Corresponding Editor: Thomas Jung.



TABLE 1. Monthly and annual similarity coefficients for
White-tailed Deer and Mule Deer observed during animal surveys.
Coefficient of species association (CSA), from Whittaker and
Fairbanks (1958) and modified by Southwood (1966), ranges from
complete association (+1) to repulsion (-1). Jaccard's coefficient
of community (JCC; Jaccard 1901) ranges from 0 to 1, ascending in
positive association.

Year    cient      May    June    July    August   Total

2005    CSA       -0.81   -0.91   -0.80    -1.00   -0.83
        JCC        0.06    0.03    0.07     0.00    0.05
2006    CSA       -1.00   -1.00   -1.00    -1.00   -1.00
        JCC        0.00    0.00    0.00     0.00    0.00
2007    CSA       -0.53   -0.67   -1.00    -0.85   -0.62
        JCC        0.11    0.13    0.00     0.06    0.10
2008    CSA       -0.98   -0.76   -0.68    -1.00   -0.89
        JCC        0.01    0.08    0.04     0.00    0.03
2009    CSA       -0.89   -1.00   -1.00    -1.00   -0.95
        JCC        0.03    0.00    0.00     0.00    0.01
2010    CSA       -1.00   -0.94   -1.00    -1.00   -0.98
        JCC        0.00    0.02    0.00     0.00    0.01
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Author:Lobo, Nikhil; Millar, John S.
Publication:Northwestern Naturalist: A Journal of Vertebrate Biology
Article Type:Report
Geographic Code:1CANA
Date:Sep 22, 2013
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