Chapter 21 Changes in Elk Resource Selection and Distribution with the Reestablishment of Wolf Predation Risk

CHAPTER 21

Changes in Elk Resource Selection and Distribution with the Reestablishment of Wolf Predation Risk P. J. White,* Robert A. Garrott,† Steve Cherry,{ Fred G. R. Watson,} Claire N. Gower,† Matthew S. Becker,† and Eric Meredith{ *National Park Service, Yellowstone National Park † Fish and Wildlife Management Program, Department of Ecology, Montana State University { Department of Mathematical Sciences, Montana State University } Division of Science and Environmental Policy, California State University Monterey Bay

Contents I. II. III. IV. V. VI.

Introduction Methods Results Discussion Summary References

452 454 456 465 473 473

Theme How animals use resources at local and landscape scales can differ depending on whether starvation is the primary limiting factor or significant predation risk also exists. With predation, individuals face the added and often conflicting demands of obtaining adequate nutrition while reducing predation risk. However, disentangling differences between the respective resource selection strategies in a given system is rarely possible. We evaluated changes in resource selection and prey distribution for a non-migratory elk population formerly limited by winter starvation and now subjected to wolf predation in the Madison headwaters area of Yellowstone National Park. Analyses of elk resource selection prior to wolf establishment (1991–1992 through 1997–1998) demonstrated a dynamic spatial and temporal response to changes in snow pack at the local and landscape level, with elk selecting areas with low snow mass, but forced to occupy areas with higher local snow mass as conditions on the winter range became more severe (Chapter 8 by Messer et al., this volume). We hypothesized that variables affecting elk resource selection prior to wolves would retain their primacy in post-wolf models (1998–1999 through 2005–2006), but that the magnitude of each would change depending on its contribution to predation risk. Broad-scale changes in prey distribution could also occur if the collective attributes of a landscape serve to alternately provide areas with decreased or increased predation risk. Thus, we also evaluated the potential for landscape-scale shifts in the distribution of the elk population among the three drainages of the The Ecology of Large Mammals in Central Yellowstone R. Garrott, P. J. White and F. Watson ISSN 1936-7961, DOI: 10.1016/S1936-7961(08)00221-2

Copyright # 2009, Elsevier Inc. All rights reserved.

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Madison headwaters area if elk selected distinct prey refuges and avoided areas where they were particularly vulnerable to wolf predation. Alternatively, elk distribution shifts among the three drainages could also result from differential predation risk with lower densities of animals in high risk areas due to the removal by wolves of substantial numbers of prey.

I. INTRODUCTION Predation risk may have an important influence on resource selection by prey because animals often must choose between minimizing the risk of predation and obtaining enough forage to meet nutritional demands and maximize reproductive success (Gilliam and Fraser 1987, Sweitzer 1996, Rachlow and Bowyer 1998, Kie 1999, Grand 2002, Ben-David et al. 2004, Gustine et al. 2006). The costs of resource selection choices in the form of increased predation will likely vary both spatially and temporally in heterogeneous and diverse landscapes where animals make choices based on biological (e.g., age, reproductive status, nutritional condition), environmental (e.g., vegetation, snow, topography), and social variables (e.g., density, group size; Krebs 1980, Lima and Dill 1990). Animals in these environments should attempt to minimize detrimental effects of the main limiting factors (e.g., food, predation, snow), but may make trade-offs among these if the risks associated with several potential limiting factors are competing and vary with scale (Rettie and Messier 2000, Yasue´ et al. 2003, Dussault et al. 2005). Ungulates in mountainous, temperate, and high latitude environments often use multiple strategies to accrue food supplies during winter (e.g., Johnson et al. 2001). These strategies may be a product of the heterogeneous environment or a landscape with dynamic predation risk that can vary at fine and broad temporal and spatial scales (Creel and Winnie 2005, Gude et al. 2006). For example, animals may select for areas higher in vegetation quality or with topography and snow characteristics that increase access to forage (Schmidt 1993, Gustine et al. 2006). Alternatively, they may minimize predation risk by increasing separation from predators or selecting topography that serves as a form of escape terrain (Bergerud and Page 1987, Barten et al. 2001). This plasticity in use of resources can also make animals less predictable in space and time (Gustine et al. 2006). Thus, individual and group responses to spatiotemporal variations in food availability and predation risk may affect the distribution of animals, nutrient acquisition, and demography (Sih 1980, 1982; Werner and Hall 1988, Schmitz 1997; Downes 2001; Creel et al. 2005, 2007; Dussault et al. 2005; Gustine et al. 2006). Elk in the Madison headwaters area of Yellowstone National Park provided an excellent opportunity to evaluate the effects of predation risk on resource selection decisions because they have relatively low reproductive potential, use a heterogeneous landscape to meet stringent seasonal demands, are nonmigratory and not subject to human hunting, are demographically sensitive to predation, and in the absence of wolves were strongly limited by winter starvation mortality (Garrott et al. 2005; Chapters 11 and 23 by Garrott et al., this volume). We evaluated how elk resource selection changed when wolves were restored and elk were confronted with trade-offs between predation risk and starvation. We compared habitat, snow pack, and topographical attributes at locations used by elk and locations selected at random from an area considered available to the population across several different categories of landscape-scale snow conditions. Given the constraints of foraging in a severe winter environment, we assumed that the fundamental drivers of elk resource selection prior to wolf recolonization identified by Messer et al. (Chapter 8 by Messer et al., this volume) would remain unchanged. Therefore, we predicted the models most supported by the data collected during colonization and after wolves became established in the study system would be similar to the top approximating models for the pre-wolf data. However, we expected the strength of the covariate coefficients would change substantially because the most-effective resource selection strategies for minimizing starvation risk would likely not be optimal when confronted with

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predation risk (Mech et al. 2001, Creel et al. 2005, Hebblewhite et al. 2005, Gude et al. 2006, Kauffman et al. 2007). Snow pack has been reported to substantially increase the vulnerability of ungulates to wolf predation by impeding their escape attempts and reducing their body condition due to prolonged nutritional deprivation and periods of high energetic costs (Peterson 1977; Nelson and Mech 1986; Huggard 1993; Post et al. 1999; Mech and Peterson 2003; Chapter 9 by White et al., Chapter 11 by Garrott et al., and Chapters 16 and 17 by Becker et al., this volume). Thus, we predicted the decrease in the odds of elk occurrence with increasing snow pack (Chapter 8 by Messer et al., this volume) would become more pronounced after wolves became established in the system. Likewise, we predicted the positive effect of snow heterogeneity on odds of elk occurrence (Chapter 8 by Messer et al., this volume) would strengthen after wolves became established in the system because heterogeneity provides more opportunities for elk to locate areas of low snow pack where they would be less vulnerable to successful attacks. Based on the findings of Messer et al. (Chapter 8 by Messer et al., this volume), we anticipated elk would select geothermal and meadow environments and lower elevations, and that this selection would be heightened during and after wolf colonization (Figure 21.1). Though wolves in the Madison headwaters area selected for geothermal areas, meadows, and areas near various types of habitat edges (Bergman et al. 2006), these areas still have higher food quantity and quality (Chapter 9 by White et al., this volume). They also have lower snow pack and, in turn, lower energy requirements for foraging and traveling elk. Furthermore, some geothermal habitats support wet meadow areas with high vegetative productivity or plants that photosynthesize year-round (Despain 1990). In addition to potential changes in resource selection as a consequence of the reestablishment of predation risk for elk in this system, broad distributional shifts were also possible (Lima 1998). Landscapes are complex combinations of many different attributes (Turner and Gardner 1991), some of which may provide areas that serve as effective ‘‘refuges’’ where prey are less detectable or less vulnerable if attacked by predators (Andrewartha and Birch 1984, Berryman and Hawkins 2006). Other combinations of landscape attributes may work in concert to define areas where prey are particularly vulnerable to predation (Lima 1992, Hebblewhite et al. 2005, Hopcraft et al. 2005). The simple linear combinations of landscape covariates employed in resource selection models may not

FIGURE 21.1 Elk grazing along the Madison River in Yellowstone National Park during late winter. The occurrence of elk was not decoupled from wolves because elk continued to select for areas with high snow heterogeneity even though there was a high risk of predation. This strategy was apparently viable in certain portions of the landscape due to the presence of escape terrain such as rivers adjacent to preferred foraging areas (Photo by Shana Dunkley).

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adequately capture the collective attributes of a landscape that define areas where prey are particularly vulnerable and areas prey may be protected from predation. If such areas existed in our study system, then a combination of differential mortality associated with these areas and possible movements of elk out of areas of high perceived predation risk and into areas of lower risk could effectively change the distribution of the population. While we had no strong a priori hypotheses with respect to potential refuge areas within our study system, we recognized that snow pack was deeper in upper reaches of the Gibbon and Firehole drainages compared to the Madison drainage (Chapter 6 by Watson et al., this volume), and that small geothermal areas surrounded by deep snow pack could represent environmental traps where elk would be particularly vulnerable to predation. Such areas were scattered throughout the Gibbon and Firehole drainages and were routinely occupied by small groups of elk prior to wolf reestablishment due to their relatively high food availability and quality (Chapter 9 by White et al., this volume). Similarly, we suspected that structural differences in topography and hydrology, and their differing spatial arrangement among the three drainages (Chapter 8 by Messer et al., this volume), offered differing amounts of effective escape habitat for elk when attacked by wolves. Thus, we hypothesized that differences in overall landscape heterogeneity among the three drainages of the study system could result in broad distributional shifts in the population as a consequence of the reestablishment of wolves.

II. METHODS We used telemetry homing procedures and a stratified random sampling regime to repeatedly visually locate adult female elk fitted with radio collars during daylight hours between November 15 and April 30 of eight consecutive winters (1998–1999 through 2005–2006). For each independent elk location, we selected 20 random locations from within the boundary of the available winter range (Chapter 8 by Messer et al., this volume) and assigned the same date as their corresponding elk location to ensure equal temporal distribution in the response. We used a digital elevation model to estimate elevation (ELEV) and the solar radiation index (SRI; Iqbal 1983, Keating et al. 2007) for each actual and random location. We also designated habitat type (HAB) for each location as meadow, burned forest, unburned forest, or geothermal using vegetation cover and geothermal data layers developed with Landsat 7 Enhanced Thematic Mapper satellite imagery (Chapter 2 by Newman et al., this volume). In addition, we used the Langur snow pack model (Chapter 6 by Watson et al., this volume) to estimate the spatial and temporal heterogeneity of the snow pack each day during winter. We calculated mean snow water equivalent (i.e., SWEA; water content of snow) at the local scale as the average of all 28.5
28.5-m pixels within a 100-m radius of each elk location. We also calculated snow heterogeneity (SNHA; spatial variability of snow) at the local scale as the standard deviation of estimated SWE of all pixels within a 100-m radius of each elk location. We calculated mean snow water equivalent and snow heterogeneity at the landscape scale (SWEL, SNHL) each day using all pixels within the defined winter range we considered available to the elk. In addition, we also calculated an annual index of snow pack severity (SWEacc) by summing the mean daily SWE for the study area (SWEL) from October 1 to April 30 (Garrott et al. 2003), which provided a single metric integrating snow pack depth, density, and duration. Data were partitioned into a colonization period (1998–1999 through 2001–2002) when wolves were initially occupying various river drainages and elk were adjusting to their presence, and an established wolf period (2002–2003 through 2005–2006) when one or more packs consistently used each drainage. We used log odds ratios (Agresti 1990) to determine the likelihood of an elk occurring at a particular location for the wolf colonizing and established periods, depending on local and landscape-scale snow pack conditions. We sorted all actual and random locations into one of three categories depending on the landscape SWEL estimate for that date (low 0–0.1 m, medium > 0.1–0.2 m, high > 0.2–0.3 m).

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Next, we sorted locations into local SWEA levels, categorized by 0.05-m increments. We then calculated the log odds and 95% confidence intervals of an elk location occurring in a particular local SWEA level within each landscape SWEL category, as described in Messer et al. (Chapter 8 by Messer et al., this volume). We also used this approach to calculate log odds ratios of local SNHA, categorized into 0.02-m increments, within the same landscape SWEL categories. Modeling animal distributions based on resource selection or similar types of habitat modeling exercises is a common research activity (Manly et al. 2002). The basic purpose of such models is to predict animal distributions. Thus, it is useful to obtain some idea of the generalizability of a model beyond the data that was used in its development (Beutel et al. 1999, Vaughan and Ormerod 2005). While resampling of the training data set can be used to evaluate a model’s predictive ability (Boyce et al. 2002), applying the model to independent data sets provides a more rigorous assessment of a model’s generalizability (Vaughan and Ormerod 2005). Messer et al. (Chapter 8 by Messer et al., this volume) incorporated landscape attributes into matched case–control logistic regression analyses (also known as conditional logistic regression) to gain insights into elk resource selection patterns prior to wolf reestablishment in the study system. Actual and random locations were matched by date to ensure that snow pack covariates associated with both the used and random locations were drawn from the same daily snow pack predictions from the Langur model. Three a priori model suites were evaluated, representing (1) static landscape attributes (ELEV, HAB, SRI; seven models total), (2) temporally dynamic snow pack attributes (SWEA, SNHA, SWEL; seven models total), and (3) combinations of both static landscape and temporally dynamic snow pack attributes (13 models total). We considered the evaluation of these a priori model suites using seven years of elk telemetry data collected before wolf colonization to be a training data set from which there was a single model in each of the three a priori model suites that received all the support from the data, as well as an overall top model that included three static landscape covariates and two temporally dynamic snow pack covariates (Chapter 8 by Messer et al., this volume). We used PROC PHREG to fit these same model suites and estimate parameter coefficients (SAS 2000) for two additional, independent data sets including (1) the period when wolves were colonizing the study system, and (2) the period when wolf packs were established in all drainages of the study system. We compared these results with those reported by Messer et al. (Chapter 8 by Messer et al., this volume) for the pre-wolf period to evaluate the hypothesis that elk resource selection patterns changed after the establishment of predation risk in the system. We ranked models and compared their relative abilities to explain variation in the data using Akaike’s Information Criteria (AIC), with Akaike model weights (wi) used to address model selection uncertainty (Burnham and Anderson 2002). We also compared the 95% confidence intervals of each variable to evaluate if the coefficients were statistically different among time periods. An annual estimate of the elk population and the distribution of the population among the three drainages of the study area were obtained each spring from 1997 through 2007 by conducting a series of replicate mark–resight surveys using the radio-collared animals as the marked sample (Chapter 23 by Garrott et al., this volume). Surveys were initiated when elk began aggregating in the meadows adjacent to the rivers to feed on the first green forages of the spring (Figure 21.2) and were conducted by traveling roads that paralleled the rivers and meadows through each drainage. During 1997–2004, 10– 11 replicate surveys were conducted each spring. However, 16–33 replicates were needed each spring during 2005–2007 to maintain adequate precision as elk abundance decreased and became more patchily distributed (Chapter 23 by Garrott et al., this volume). Surveys were generally conducted on consecutive days, but low visibility due to spring snowstorms occasionally resulted in 1–3-day breaks between surveys. We used the joint hypergeometric likelihood estimator in Program NOREMARK (White 1996) to calculate a population estimate and confidence limits from these replicate road-based surveys. We estimated the proportion of the elk population in each drainage by summing the total number of animals detected on the replicate surveys in each drainage and dividing by the total number of animals detected throughout the study area during the surveys. The number of elk in each drainage was then

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FIGURE 21.2 An aggregation of elk feeding along the Madison River in Yellowstone National Park. Mark–resight surveys to obtain annual population estimates and determine the proportion of the population in each drainage of the study area were conducted each spring when elk were concentrated in the low elevation meadow complexes (Photo by Shana Dunkley).

estimated by multiplying the population estimate by the estimated proportion of the population in each drainage. We integrated the results of the resource selection analyses and the mark–resight surveys into graphic presentations of changes in relative elk abundance and distribution over the 16 years (1992– 2007) we conducted intensive studies of this population. Maps approximating the distribution of elk in the study area for the last winter of the pre-wolf (1997–1998), colonizing (2001–2002), and established (2006–2007) periods were generated by using the most-supported resource selection model for each period to distribute the estimated number of elk that were present in each drainage during the spring mark–resight surveys for each of these years. We fixed snow pack attributes to represent the mean peak landscape SWEL experienced during the 16 winters of our studies.

III. RESULTS We collected 3423 locations of 88 adult, female elk (25–30 instrumented animals per year) during eight winters, including 1541 locations during wolf colonization (1998–1999 through 2001–2002) and 1882 locations after wolves became established in the system (2002–2003 through 2005–2006). We compared these data to 4869 locations of 45 adult female elk during seven winter seasons before wolves colonized the system (1991–1992 through 1997–1998; Chapter 8 by Messer et al., this volume). The annual variation in snow pack severity differed among the three study periods. Winters during the pre-wolf period had an average SWEacc of 3009 and ranged between 1744 and 5690 cm days. Winters during the wolf colonizing period had an average SWEacc of 2265 and ranged between 1042 and 3749 cm days. Winters during the established wolf period had an average SWEacc of 2071 and ranged between 1707 and 2508 cm days. Climate data were available to parameterize the Langur snow

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pack model (Chapter 6 by Watson et al., this volume) and calculate SWEacc for the most recent 24 winters (1983–1984 through 2006–2007), with an average SWEacc for this time series of 2337 cm days and a range between 1042 and 5690 cm days. Thus, average snow pack severity was higher than the historic average during the pre-wolf period, similar to the historic average during the wolf colonizing period, and lower than the historic average during the established wolf period. The frequency distribution of observed elk locations compared to the samples of random points drawn from the available winter range before, during, and after wolf colonization suggests elk disproportionately selected areas with lower local snow pack and tended to avoid areas of higher local snow pack. This pattern of selection was consistent for all three study periods despite the differences in winter severity among the periods, as evidenced by the decreasing range of the distributions from the pre-wolf period to the post-wolf period (Figure 21.3). Likewise, log odds ratios demonstrated that elk were less likely to occur in an area as local SWEA increased with this trend consistent for all three categories of landscape SWEL (Table 21.1, Figure 21.4). However, the log odds ratios for any given local SWEA increased with increasing landscape SWEL, indicating that as snow pack on the winter range became more severe elk were more likely to occupy areas of more severe local SWEA than they were under less severe snow pack conditions. While the log odds ratio curves were similar among the three study periods at low and moderate landscape SWEL, there was a clear tendency for elk to more strongly avoid severe snow pack conditions as wolves colonized and became established in the study system (Figure 21.4). Local snow pack heterogeneity also influenced elk occupancy across all three categories of landscape SWEL, with the likelihood of elk occurrence quickly increasing and then decreasing slightly as local SNHA levels exceeded 0.06–0.08 m (Table 21.1, Figure 21.5). This selection for increased local heterogeneity increased with increasing landscape SWEL, but the patterns were similar for all three study periods. The same landscape and snow pack models selected for the training data set (i.e., pre-wolf; Chapter 8 by Messer et al., this volume) during conditional logistic regression analyses received all of the support from the independent data sets collected during and after wolf colonization. Model comparisons both within and among the static landscape, dynamic snow, and combined landscape-snow model suites resulted in the same top-ranking models with the most-supported model in each suite receiving a model weight of 1.0 (Table 21.2). Coefficient estimates indicated elk selection for areas with lower local snow pack became stronger after wolves became established in the study system, and this selection intensified as landscape SWEL increased (Table 21.3). Selection of snow heterogeneity was similar among time periods. Elk showed stronger selection for lower elevations after wolves became established in the area, with some evidence of selection for lower exposure to solar radiation (Table 21.3). All habitat coefficients were negative, indicating that elk selection remained strongest for the reference geothermal type during all three study periods. While the coefficient estimates for each of the habitat categories either consistently increased or decreased from the pre-wolf to the postwolf period, coefficient confidence intervals overlapped among time periods, providing little evidence of fundamental shifts in elk selection of habitat types after changes in selection for snow characteristics were accounted for with other covariates (Table 21.3). In other words, the coefficient estimates derived from each independent data set during and after wolf colonization were similar to the pre-wolf training data set. These results suggest that the resource selection models initially developed in Chapter 8 by Messer et al. (this volume) had substantial ability to predict elk occupancy in our study system when applied to other time periods. This assessment is limited to our study system because no independent data sets from other areas were evaluated (Vaughan and Ormerod 2005). Results of the annual spring replicate mark–resight surveys documented major shifts in the distribution of elk among the three drainages. When surveys were initiated in 1997, just prior to initial recolonization of the study area by wolves, the elk population was approximately equally distributed among the three drainages. Over the next decade, the proportion of the population detected in the Gibbon drainage decreased precipitously, the proportion in the Firehole drainage decreased modestly, and the proportion in the Madison drainage increased substantially (Figure 21.6). The number of elk

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Proportions of locations

0.25 Pre-wolf 0.20 0.15

Actual Random

0.10 0.05

0.75

0.70

0.65

0.60

0.55

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0.45

0.40

0.35

0.30

0.25

0.20

0.15

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0.05

0.00

0.00

SWE (m)

Proportions of locations

0.25 Wolf colonization

0.20 0.15

Actual Random

0.10 0.05

0.65

0.70

0.75

0.65

0.70

0.75

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0.45

0.40

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0.20

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0.00

0.00

SWE (m)

Proportions of locations

0.25 Wolves established 0.20 0.15

Actual Random

0.10 0.05

0.60

0.55

0.50

0.45

0.40

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00

0.00

SWE (m)

FIGURE 21.3 Histograms comparing the local-scale snow water equivalent (SWEA) available within the study area (random) to the mean SWEA in the 100-m radius around observed elk locations (actual) before (n ¼ 4869), during (n ¼ 1541), and after (n ¼ 1882) wolf colonization in the Madison headwaters area of Yellowstone National Park during 1991–1992 through 2005–2006.

estimated in both the Gibbon and Firehole drainages also decreased, with estimates suggesting an ephemeral increase in elk abundance in the Madison drainage that was negligible by the end of the study (Figure 21.6). The high values for both the estimated proportion and number of elk in the Madison drainage in 2001 were anomalies in the data due to the appearance of a large group of elk in

TABLE 21.1 Log odds ratios (LOR) and standard errors (SE) determining the likelihood of elk occurrence under changing local- and landscape-scale snow water equivalents (SWE; m) and snow heterogeneity (SNH) in the Madison headwaters area of Yellowstone National Park before, during, and after wolf colonization in the Madison headwaters area of Yellowstone National Park during 1991–1992 through 2005–2006 Landscape SWE categories SWE low (0.00–0.10 m) Local snow levels SWE 0.00–0.05 0.05–0.10 0.10–0.15 0.15–0.20 0.20–0.25 0.25–0.30 0.30–0.35 0.35–0.40 0.40–0.45 SNH 0.00–0.02 0.02–0.04 0.04–0.06 0.06–0.08 0.08–0.10 0.10–0.12 0.12–0.14 0.14–0.16

Pre-wolf

Colonizing

SWE moderate (0.10–0.20 m) Post-wolf

Pre-wolf

Colonizing

SWE high (0.20–0.30 m)

Post-wolf

Pre-wolf

Colonizing

Post-wolf

LOR

SE

LOR

SE

LOR

SE

LOR

SE

LOR

SE

LOR

SE

LOR

SE

LOR

SE

LOR

SE

0.62 0.02 1.35

0.09 0.09 0.19

1.15 0.37 1.90 2.24

0.09 0.09 0.25 0.71

1.79 0.27 1.59

0.12 0.12 0.34

1.63 1.21 0.08 1.20 1.96 2.87

0.05 0.05 0.05 0.07 0.14 0.41

1.44 0.96 0.07 0.89 1.71 2.48

0.12 0.10 0.09 0.12 0.28 0.71

1.52 1.13 0.20 1.15 2.31 2.85

0.07 0.06 0.07 0.09 0.22 0.50

1.85 1.46 1.08 0.46 0.60 1.25 1.83 2.84 3.53

0.08 0.08 0.07 0.07 0.08 0.10 0.18 0.45 1.00

2.06 1.89 1.27 0.41 1.00 1.43 3.29

0.20 0.21 0.19 0.16 0.20 0.28 1.00

1.71 1.83 1.11 0.83 1.62 3.52

0.23 0.22 0.20 0.18 0.35 1.00

0.58 0.60 0.36

0.11 0.12 0.30

0.56 0.55 0.37 0.09

0.88 0.46 0.27 0.73

0.17 0.23 0.64

0.15 0.16 0.72

1.92

1.16

1.08 0.26 0.94 1.01 0.70 0.31

0.05 0.05 0.05 0.08 0.16 0.46

0.92 0.56 0.77 0.76 0.33

0.09 0.09 0.12 0.19 0.46

0.75 0.17 0.71 0.65 0.26 0.06

0.06 0.06 0.07 0.11 0.24 0.59

1.17 0.23 0.67 0.96 1.04 0.82 0.13 0.23

0.07 0.06 0.07 0.08 0.10 0.15 0.33 0.73

1.52 0.01 1.02 1.04 1.23 0.53

0.19 0.15 0.17 0.20 0.23 0.53

1.01 0.88 0.82 1.03 1.35

0.23 0.20 0.18 0.21 0.26

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3 Low landscape SWE

Log odds ratio

2 1

Established

0

Colonizing

−1

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−2 −3 −4 0.00–0.05

0.10–0.15

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3

0.40–0.45

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Log odds ratio

2 1

Established

0

Colonizing Pre-wolf

−1 −2 −3 −4 0.00–0.05

0.10–0.15

3

0.20–0.25 0.30–0.35 Snow water equivalent (m)

0.40–0.45

High landscape SWE

Log odds ratio

2 Established

1

Colonizing

0

Pre-wolf

−1 −2 −3 −4 0.00–0.05

0.10–0.15

0.20–0.25 0.30–0.35 Snow water equivalent (m)

0.40–0.45

FIGURE 21.4 Log odds of elk occurrence in local snow water equivalent conditions given low (0–0.1), medium (0.1– 0.2), and high (0.2–0.3) landscape snow water equivalent (SWE) conditions before, during, and after wolf colonization in the Madison headwaters area of Yellowstone National Park during 1991–1992 through 2005–2006.

the meadows adjacent to the Madison River that remained in the area for several weeks. We believed these animals were early spring migrants that wintered outside of the study area because there were no collared animals associated with this group and it contained a much higher proportion of calves than had been recorded anywhere in the study area that year. To illustrate the influence of wolf colonization on the distribution of elk in the Madison headwaters, we used our most-supported resource selection models to generate maps depicting the odds of elk occurrence in the Firehole, Gibbon, and Madison drainages before, during, and after wolf colonization. Elk were widely distributed through all three drainages prior to wolves, as evidenced by the relatively

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Log odds ratio

3 2

Low landscape SWE

1

Established

0

Colonizing Pre-wolf

−1 −2 0.00–0.02

0.04–0.06 0.08–0.1 Snow heterogeneity (m) Established

3

Colonizing 2 Log odds ratio

0.12–0.14

Medium landscape SWE

Pre-wolf

1 0 −1 −2 0.00–0.02

0.04–0.06 0.08–0.1 Snow heterogeneity (m) Established

3

Colonizing 2 Log odds ratio

0.12–0.14

High landscape SWE

Pre-wolf

1 0 −1 −2 0.00–0.02

0.04–0.06 0.08–0.1 Snow heterogeneity (m)

0.12–0.14

FIGURE 21.5 Log odds of elk occurrence in local snow heterogeneity conditions given low (0–0.1), medium (0.1– 0.2), and high (0.2–0.3) landscape snow water equivalent (SWE) conditions before, during, and after wolf colonization in the Madison headwaters area of Yellowstone National Park during 1991–1992 through 2005–2006.

uniform odds of occurrence (Chapter 8 by Messer et al., this volume; Figure 21.7). During wolf colonization, modest dispersal (Chapter 18 by Gower et al., this volume) and substantial elk mortality due to wolves (Chapter 23 by Garrott et al., this volume) resulted in the Gibbon drainage having low odds of elk occurrence, with reduced odds in the Firehole drainage as well (Figure 21.8). Odds of elk occurrence were substantially lower in the Firehole drainage by the end of the study after wolf packs became established in the system (Figure 21.9). The vast majority of elk occurred in the Madison

TABLE 21.2 Selection results of models examining the effects of static landscape and dynamic snow covariates on variation in winter elk distribution before, during, and after wolf colonization in the Madison headwaters area of Yellowstone National Park during 1991–1992 through 2005–2006 Pre-wolf

Model Structure Snow models SWEAþSNHAþ(SWEA
SWEL)þ (SNHA
SWEL) SWEAþSNHAþ(SWEA
SNHA) SWEAþ(SWEA
SWEL) SWEAþSNHA SWEA SNHAþ(SNHA
SWEL) SNHA Landscape models HBTþELVþSRI HBTþELV ELV SRIþELV HBTþSRI HBT SRI Landscape and snow models SWEAþSNHAþHBTþELVþSRI SWEAþHBTþELVþSRI SWEAþSNHAþHBTþ (SWEA
SNHA)þ(SWEL
HBT) SWEAþSNHAþHBTþ (SWEA
SNHA)þ(SNHA
HBT)

Wolf colonization

Post-wolf

K

Within suite DAIC

Among suite DAIC

Within suite DAIC

Among suite DAIC

Within suite DAIC

Among suite DAIC

Among suite wi

4

0

939

0

525

0

925

0

3 2 2 1 2 1

449 451 549 924 3985 4094

1388 1390 1488 1863 4924 5033

72 142 140 268 1218 1216

597 667 665 793 1743 1741

91 87 113 191 1661 1670

1016 1012 1038 1116 2586 2595

0 0 0 0 0 0

5 4 1 2 2 1 1

0 2 952 953 3652 3657 4855

1443 1445 2395 2396 5095 5100 6298

0 7 294 288 1334 1338 1648

467 474 761 755 1801 1805 2115

0 55 358 298 1634 2038 2242

419 474 777 717 2053 2457 2661

0 0 0 0 0 0 0

7 6 9

0 593 1284

0 593 1284

0 194 546

0 194 546

0 139 917

0 139 917

1.0 0 0

9

1294

1294

572

572

965

965

0

SWEAþSNHAþHBTþ (SWEA
SNHA)þ(SWEA
HBT) SWEAþSNHAþHBTþ (SWEA
SNHA) SWEAþSNHAþHBTþ (SWEL
HBT) SWEAþSNHAþHBTþ (SNHA
HBT) SWEAþSNHAþHBTþ (SWEA
HBT) SWEAþSNHAþHBT SWEAþHBTþ(SWEL
HBT) SWEAþHBTþ(SWEA
HBT) SWEAþHBT

9

1360

1360

595

595

976

976

0

6

1360

1360

589

589

978

978

0

8

1388

1388

606

606

940

940

0

8

1388

1388

631

631

986

986

0

8

1460

1460

662

662

999

999

0

5 7 7 4

1468 1741 1752 1813

1468 1741 1752 1813

660 726 768 776

660 726 768 776

1005 1004 1058 1070

1005 1004 1058 1070

0 0 0 0

SWEA, local-scale snow water equivalent; SWEL, landscape-scale snow water equivalent; SNHA, local-scale snow heterogeneity; SNHL, landscape-scale snow heterogeneity; SRI, solar radiation index; ELV, elevation; HBT, habitat; K, number of model parameters; △AIC, the change in AIC value relative to the best model; AIC model weight.

TABLE 21.3 Coefficient values and confidence intervals for the best-supported models examining the effects of static landscape and dynamic snow covariates examining variation in winter elk distribution before, during, and after wolf colonization in the Madison headwaters area of Yellowstone National Park during 1991–1992 through 2005–2006 Pre-wolf Covariate

b est.

95% Low CI

Wolf colonization 95% High CI

Snow model SWEAþSNHAþ(SWEA
SWEL)þ(SNHA
SWEL) SWEA 20.9 22.0 19.9 SNHA 21.3 18.4 24.2 SWEA
SWEL 34.5 31.4 37.7 SNHA
SWEL 36.4 45.2 27.5 Landscape model HBTþSRIþELV HBT Burned forest 1.70 1.81 1.60 Unburned forest 1.35 1.44 1.26 Meadow 1.27 1.38 1.16 SRI 0.320 0.623 0.017 ELV 0.009 0.010 0.009 Combined snow-landscape model SWEAþSNHAþHBTþELVþSRI SWEA 6.5 7.0 6.0 SNHA 14.1 12.9 15.2 HBT Burned forest 0.58 0.70 0.46 Unburned forest 0.38 0.49 0.28 Meadow 0.46 0.58 0.33 ELV 0.007 0.008 0.007 SRI 7.070 7.450 6.690

Post-wolf

b est.

95% Low CI

95% High CI

b est.

95% Low CI

95% High CI

26.4 18.4 60.0 21.7

28.7 12.0 50.1 48.9

24.0 24.8 70.0 5.6

39.6 20.4 134.2 43.4

43.7 8.9 109.9 112.5

35.5 32.0 158.4 25.7

1.67 1.17 1.29 0.716 0.009

1.86 1.32 1.48 1.184 0.010

1.49 1.01 1.09 0.248 0.009

1.75 1.34 1.53 1.750 0.012

1.94 1.30 1.74 2.186 0.013

1.55 0.97 1.31 1.314 0.011

7.7 17.4

8.8 15.0

6.6 19.8

11.4 18.8

12.8 15.7

10.0 21.8

0.66 0.33 0.60 0.008 7.590

0.88 0.51 0.82 0.008 8.204

0.45 0.15 0.38 0.007 6.976

0.74 0.28 0.77 0.010 9.850

0.96 0.47 1.00 0.011 10.531

0.52 0.09 0.54 0.009 9.169

SWEA, local-scale snow water equivalent; SWEL, landscape-scale snow water equivalent; SNHA, local-scale snow heterogeneity; SNHL, landscape-scale snow heterogeneity; SRI, solar radiation index; ELV, elevation; HBT, habitat; K, number of model parameters; △AIC, the change in AIC value relative to the best model; AIC model weight.

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Changes in Elk Resource Selection and Distribution

Proportion animals detected

0.9

Madison

0.8

Gibbon

0.7

Firehole

0.6 0.5 0.4 0.3 0.2 0.1

19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07

0.0

400 350

Number of elk

300

Madison Gibbon Firehole

250 200 150 100 50

07 20

06 20

05 20

04 20

03

02

20

20

19 98 19 99 20 00 20 01

19

97

0

FIGURE 21.6 Estimated changes in the proportion of the elk population and the total number of elk occupying the Madison, Gibbon, and Firehole River drainages from 1997 through 2007. Estimates were based on replicate (n ¼ 10–33) mark–resight surveys conducted during the early stages of snow melt-out in late March or April when elk were concentrated in meadows adjacent to the rivers and the road system (Chapter 23 by Garrott et al., this volume).

Canyon of the Madison River drainage, with few elk in the Gibbon drainage and a small, decreasing number of elk in the Firehole drainage.

IV. DISCUSSION We did not detect profound changes when contrasting habitat selection by elk before, during, and after wolf colonization, though modest and consistent changes in coefficients across the three study periods suggested subtle shifts in selection may have been occurring. Elk continued to select geothermal areas

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FIGURE 21.7 The relative distribution of elk in the Madison headwaters area of Yellowstone National Park, Montana and Wyoming, USA, before wolves began recolonizing the area in 1998–1999.

with higher food quantity and quality (Chapter 9 by White et al., this volume) even though wolves also selected for these areas (Bergman et al. 2006). Similarly, both Mao et al. (2005) and Kauffman et al. (2007) concluded that data from elk occupying the northern portion of Yellowstone did not yield empirical support for elk substantially altering their habitat selection and movement patterns after wolf restoration. This consistent, strong preference by elk for apparently dangerous habitats appears somewhat paradoxical, but likely reflects the continued need for elk to access as high a quality of forage as available during the severe winter months when they experience lower metabolizable energy intake (Garrott et al. 1996; Chapter 9 by White et al., this volume) and diminishing fat reserves (Cook et al. 2004). Elk in the Madison headwaters area apparently obtained necessary food resources since there was no indication of any considerable change in foraging time (Chapter 20 by Gower et al., this

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467

FIGURE 21.8 The relative distribution of elk in the Madison headwaters area of Yellowstone National Park, Montana and Wyoming, USA, during wolf colonization between 1998–1999 through 2001–2002.

volume) and we did not detect any substantial decreases in over-winter nutrition after wolves became established in the system (Chapter 22 by White et al., this volume). The ability of elk to mediate predation risk through small-scale movements, changes in grouping behavior and activity patterns (Chapters 18–20 by Gower et al., this volume), or the use of landscape features that provide effective escape from predators may explain why they continued similar patterns of habitat selection despite the increased predation risk in geothermal and meadow areas due to high use by wolves (Lima 1992, Hebblewhite et al. 2005, Bergman et al. 2006; Chapters 18–20 by Gower et al., this volume). Lima (1992) demonstrated that habitat choice can be influenced by the probability of escape as well as the probability of attack itself. Thus, even though elk in the Madison headwaters area were predictable in space and time for wolves to locate, they also occupied areas with landscape

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FIGURE 21.9 The relative distribution of elk in the Madison headwaters of Yellowstone National Park, Montana and Wyoming, USA, after wolf packs became established in the area (2002–2003 through 2005–2006).

attributes that reduced vulnerability and served as refuges with lower predation risk. Elk have a relatively high probability of escape when attacked by wolves in open environments because wolves are inefficient predators, being successful in about 20% of their attempts (Mech et al. 2001). Also, the large body size and dangerous defensive capabilities of elk can maim or kill wolves when elk have room to maneuver. In addition, elk occurred in larger groups after wolf colonization (Chapter 19 by Gower et al., this volume), which likely enhanced their probability of escape through the dilution effect (Hamilton 1971, Bertram 1978, Treherne and Foster 1982, Dehn 1990) and group detection of predators (Pulliam 1973, Pulliam and Caraco 1984, Elgar 1989). Thus, Mech et al. (2001) found that only 1% of elk in groups of up to 150 were killed when attacked by wolves. Similarly, there was a negative correlation (R2 ¼ 0.66) between mean annual group size of Madison headwaters elk and wolf

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469

kill rates on elk (Chapter 17 by Becker et al., this volume). Therefore, the collective response of slightly larger group sizes, and more dynamic grouping behavior (Chapter 19 by Gower et al., this volume), may function as an effective strategy when other defensive tactics of elk, such as fleeing, likely do not work as well in deep snow or thick forests, where thick vegetation and downed timber may pose a hindrance to efficient escape. Nearly all studies of wolf predation in North America report snow pack as an important factor affecting vulnerability of ungulate prey (Mech and Peterson 2003), including ours (Chapter 9 by Gower et al., Chapter 11 by Garrott et al., and Chapter 16 by Becker et al., this volume). Thus, we predicted elk would modify their use of the landscape with respect to snow pack attributes after wolves became established in the system. During our pre-wolf studies, when winter starvation was the predominant source of mortality for elk (Chapter 11 by Garrott et al., this volume), we found that elk selected local areas with lower and more heterogeneous snow pack. We predicted the selection for both of these snow pack attributes would become stronger with the reestablishment of predation risk from wolves. Data collected during and after wolf colonization supported these predictions. We documented an approximate doubling of the SWEA coefficient from the pre-wolf to the post-wolf period, with a modest increase in selection for more heterogeneous local snow conditions (SNHA). Similar studies of elk resource selection conducted in the greater Yellowstone ecosystem since the reestablishment of wolves have found no evidence that elk responded to wolf predation risk by altering their selection of snow pack characteristics (Mao et al. 2005, Winnie et al. 2006). However, these studies incorporated coarsescale snow pack covariates in their analyses that were not likely to capture variations in snow pack attributes at meaningful spatial and temporal scales for addressing interactions between elk and wolves. The dramatic shift in the distribution of elk during and after wolf colonization (Figures 21.7–21.9) was not due to a redistribution of elk from the Gibbon and Firehole drainages to the Madison drainage. Intensive tracking of radio-collared elk during the 16-year study demonstrated that individual adult, female elk maintained fidelity to home ranges within a drainage (Chapter 18 by Gower et al., this volume), a behavioral trait commonly documented for elk and many other ungulates (Ortega and Franklin 1995, Bowyer et al. 1996, Nicholson et al. 1997, Berger 2004). Small numbers of instrumented females were recorded moving temporarily between drainages, but these movements were not common and we documented no animals abandoning a traditional winter home range in the Gibbon or Firehole drainage to establish residency in the Madison drainage (Chapter 18 by Gower et al., this volume). Instead, we attribute the virtual disappearance of elk from the Gibbon drainage and the substantial decrease in numbers of elk occupying the Firehole drainage to a modest level of dispersal by elk from their traditional winter home ranges after wolf recolonization (Chapter 18 by Gower et al., this volume) and, most importantly, to wolf predation removing animals. Of the 312 adult elk killed by wolves during our studies, 62% were found in the Firehole drainage and 19% were found in each of the Gibbon and Madison drainages. However, these numbers are confounded by annual changes in the number of elk that occupied each of the drainages. Using annual autumn estimates of the adult population in each of the drainages (Chapter 16 by Becker et al., this volume) and the total number of wolf-killed adult elk discovered in each drainage, we estimate the average annual percentages of resident adult elk killed by wolves during winters from 1998–1999 through 2006–2007 were 47% (95% CI ¼ 16–77%) in the Gibbon drainage, 17% (95% CI ¼ 11–22%) in the Firehole drainage, and 4% (95% CI ¼ 2–5%) in the Madison drainage. Concurrent demographic studies of this population indicated the amount of predation experienced by elk in the Gibbon and Firehole drainages resulted in substantial decreases in elk numbers in these drainages (Chapters 11 and 23 by Garrott et al., this volume). These data suggest that the three drainages represented a gradient of predation risk for elk where attributes of the Gibbon drainage resulted in an area of particularly high vulnerability, the Firehole drainage represented an area of moderately high vulnerability, and the Madison drainage potentially serving as a prey refuge where wolves had difficultly successfully attacking elk. Predation risk is a function of where predators hunt and the landscape attributes, individual behaviors, and physiological

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stressors that render prey more or less susceptible to detection, attack, and predation (Holling 1965, Mech and Peterson 2003, Hebblewhite et al. 2005). The changes in strength of resource selection and distribution of the elk population in the study area following colonization by wolves did not result in a disassociation of wolves and elk. Wolves were closely associated with elk wherever they were found in the study system and were constantly coursing through the study system, including areas where prey were at low densities (Bergman et al. 2006). Therefore, we contend that the differences in predation risk among the three drainages of our study system were not due to differences in detection or encounter probabilities, but rather differences in the vulnerability of elk once attacked. When elk are attacked by wolves their primary response is to flee (McNulty et al. 2007). Hence, any landscape attributes that differentially reduce the ease of movement and maneuverability by elk to a greater extent than the pursuing wolves would increase their vulnerability. The ubiquitous presence of snow pack on the landscape through winter, and the substantial impediment to movement it can pose, is certainly a key attribute of the landscape that can influence the relatively vulnerability of elk to wolf predation (Mech and Peterson 2003; Chapters 16 and 17 by Becker et al., this volume). Thus, maps of snow pack (Chapter 6 by Watson et al., this volume) capture two important aspects of the landscape with respect to predation risk for elk, snow pack severity as indexed by SWE and the spatial variability of the snow pack. The Gibbon drainage experienced the most severe and uniform snow pack conditions, with a single large geothermal basin (Norris) and numerous small geothermal features scattered through the drainage. The Firehole drainage also experienced deep snow pack, but contained many geothermal basins that created large contiguous areas of reduced snow pack. In contrast, the Madison drainage is at a lower elevation and experienced lower average snow pack. This drainage does not contain any significant geothermal features, but includes a steep south to southwest-facing slope along most of its length where snow pack is significantly reduced. Elk strongly selected for low snow pack areas (Table 21.3) and in the Gibbon drainage this meant primarily small foraging areas surrounded by deep snow and complex forest structure (e.g., dead fall and thick regeneration after the fires of 1988) which made these animals vulnerable to successful attack by wolves. The deep snow pack of the Firehole drainage was somewhat moderated by the relatively large areas of reduced snow pack due to the spatial extent of the geothermal features, thereby providing elk more opportunities to flee for longer distances before confronting deep snow or other obstacles (Bergman et al. 2006). The lower overall snow pack of the Madison, combined with the steep southern-oriented slope running most of the length of the drainage provided an environment less constrained by snow. There are a number of other attributes of the Madison drainage that may have contributed to reduced vulnerability of the elk to wolf predation, the most prominent being the presence of a deep, wide, and ice-free river that provided escape opportunities in certain areas. We frequently observed elk in the Madison headwaters running into rivers when pursued by wolves, which is a common defensive technique of ungulate prey when attacked by wolves (Peterson 1955, Crisler 1956, Carbyn 1974, Nelson and Mech 1981). Large prey with long legs such as elk can stand in water while wolves may need to swim, thereby substantially reducing their maneuverability and conferring a distinct advantage to the prey (Figure 21.10; Mech and Peterson 2003). Thus, elk along the Madison River can likely tolerate a high risk of attack in their preferred habitats because they have a high probability of escape when attacked (Lima 1992). While both the Gibbon and Firehole Rivers are also ice-free and available all winter to elk, these tributaries are shallower and narrower than the main Madison River. The Gibbon River is shallow along its entire course and the Firehole River has only a few reaches where the river channel is deep. Consequently, while elk still used rivers as escape habitat in these drainages, the characteristics of escape terrain (e.g., depth of river), the complexity of the approach terrain, and its distance from preferred elk habitat, likely dictated whether or not it afforded effective escape from wolves, as evidenced by the fact that the majority of wolf kills on elk in the latter years of the study occurred in or next to waterways (Bergman et al. 2006). We cannot discount that the apparent lower predation risk in the Madison drainage may also reflect elk using areas where wolf densities and use were substantially reduced due to high human activity.

Chapter 21

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471

FIGURE 21.10 Elk utilizing escape terrain while under attack from wolves. Elk frequently fled into the ice-free rivers, though the success of this strategy was likely dependent on the river characteristics. The narrow and shallow Gibbon river, (top), afforded few deep areas and little protection for elk (Photo by John Felis), while the deep and wide Madison River, (bottom), provided effective escape terrain adjacent to preferred foraging areas throughout its length (Photo by Shana Dunkley). Large predators such as wolves and grizzly bears may avoid areas of high human activity, thereby reducing predation risk for prey inhabiting such areas. This phenomenon has been reported for a portion of the Bow Valley in Banff National Park, Canada (Gibeau et al. 2002, Hebblewhite et al. 2005), the headquarters of Yellowstone National Park in Mammoth (Barber-Meyer et al. 2008), and urban/ suburban areas in the western United States. In addition to intensively developed areas, roads and trails may have similar effects on predator behavior (Thurber et al. 1994, Whittington et al. 2005). While a road bisects each of the three drainages in our study system, visitor traffic during winter is concentrated on the Madison and Firehole road segments that link the town of West Yellowstone, Montana with the

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popular Old Faithful area in the upper reaches of the Firehole drainage (National Park Service 2007). The Madison drainage is considerably more restricted than the Firehole drainage, suggesting traffic and human activities might have a stronger affect of inhibiting wolf use in the Madison drainage. However, this disturbance was limited to daylight hours and wolves had a strong propensity to travel and hunt during crepuscular and nocturnal periods (Bergman et al. 2006). Also, wolves in Yellowstone National Park tend to be somewhat habituated and demonstrate considerable tolerance of humans (McNay 2002, Smith and Stahler 2003). The post-wolf redistribution of elk may also reflect their use of areas between wolf territories (Mech 1977). Wolf packs initially established in the Firehole drainage during 1997–1998, with packs expanding into the Gibbon drainage in 2000–2001, and the Cougar Pack establishing along the western boundary of the park and our study area in 2001–2002 (Chapter 15 by Smith et al., this volume). Thus, the Madison drainage was generally located along the periphery of the established wolf pack territories for much of the period of our studies. By the winter of 2004–2005, however, five packs representing approximately 45 wolves were using the entire study area with substantial spatial and temporal overlap between wolf packs (Chapter 15 by Smith et al., this volume). Packs frequently hunted in the Madison drainage, but appeared to have limited success (Chapter 17 by Becker et al., this volume), suggesting that landscape attributes were more responsible for reduced vulnerability of elk to wolf predation than hypothesized mechanisms that may have resulted in wolves tending to avoid the Madison drainage with its abundance of prey. We suggest that since the extirpation of wolves from Yellowstone National Park approximately 70 years ago, elk in the Madison headwaters area began exploiting areas that previously were too risky to occupy. In the absence of predation risk, geothermal features provided localized niches with reduced snow where animals could minimize energetic expenditures and exploit patches of accessible forage that, in some areas, remained photosynthetically active with high nutritional quality through winter. Thus, such areas adequately met the resource requirements of elk during a period when over-winter starvation was the only substantial limiting factor (Chapter 11 by Garrott et al., this volume). Consequently, these niches were thoroughly exploited as documented by pre-wolf data from this study, as well as previous studies conducted in this system (Craighead et al. 1973, Jakubas et al. 1994; Chapter 8 by Messer et al., this volume). Over the 8–10 generations that these conditions existed, elk developed strong fidelity to this occupancy pattern and presented what could be considered a naı¨ve and vulnerable prey when wolves recolonized the area (Berger 1999, Berger et al. 2001, Sand et al. 2006). While we have documented numerous adjustments in elk behavior in this and other chapters (Chapters 18–20 by Gower et al., this volume) that we interpret as responses to the reestablishment of predation risk, we propose that the dramatic changes documented in the distribution of this population were driven primarily by wolves successfully exploiting those vulnerable portions of the elk population occupying the Gibbon and Firehole drainages, with the Madison drainage perhaps serving as an important prey refuge. Our studies documented the transitional dynamics of an evolving large mammal predator–prey system. Thus, it is unclear if the relatively high density of elk that has persisted in the Madison drainage for at least the past three decades (Chapter 11 by Garrott et al., this volume) will persist or if the animals occupying this apparent prey refuge will be subjected to more intensive predation pressure now that numbers of elk in the Firehole and Gibbon drainages have been substantially reduced (Chapter 23 by Garrott et al., this volume). The existence of prey refuges and their consequences on predator–prey dynamics have been an important area of study since Gause’s (1934) classic protozoan experiments. It is well-established from both theoretical and experimental studies that the existence of prey refuges or ‘‘enemy-free’’ space can contribute to the stability of predator–prey interactions (Rosenzweig and MacArthur 1963, Hassell 1978, Strong et al. 1984, Price et al. 1986, Abrams and Walters 1996), with Berryman and Hawkins (2006) arguing that the refuge concept should be considered one of the integrating concepts in ecology and evolution. The refuge may then serve as the limiting resource in this system, with elk competing to occupy those portions of the landscape where there is significantly

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473

reduced risk of being successfully attacked by wolves and wolves competing among themselves to exploit the only high prey density area remaining in our study system. Thus, the stability and persistence of this apparent refuge may dictate the carrying capacity for both predator and prey in this system, as well as influencing the potential for a prey switching response by wolves to exploit the much more formidable, alternate bison prey (Garrott et al. 2007; Chapter 16 by Becker et al., this volume).

V. SUMMARY 1.

2.

3.

4.

5.

6.

7.

8.

We compared the distributions and resource selection by elk before, during, and after wolves colonized the Madison headwaters area of Yellowstone National Park to evaluate how distribution and selection changed when elk were confronted with trade-offs between predation risk and starvation. We collected 3423 locations from 88 radio-collared elk over eight winter seasons during and after wolf colonization (1998–1999 to 2005–2006), and compared them to 4869 locations from 45 elk during seven winter seasons before wolves colonized the system (1991–1992 to 1997–1998). The data supported our prediction that resource selection responses by elk in the Madison headwaters would be the same before and after wolf colonization, with the strength of the selection being stronger after wolves became established in the system. After wolf recolonization, elk were less likely to occupy deeper snow areas in lower elevations as average snow pack on the landscape increased. This finding likely reflects individual behavioral choices by elk and the selective pressure of wolves differentially removing elk from areas with deeper snow. We did not detect profound changes in habitat selection by elk during and after wolf colonization. Elk continued to select geothermal areas with higher food quantity and quality even though wolves also selected for these areas. The distribution of elk became more constrained during and after wolf colonization. The proportion of elk in the Gibbon drainage decreased from 37% in 1997–1998 to zero by 2003–2004. The proportion of elk in the Firehole drainage was 30–43% during 1997–1998 through 2005–2006, but then decreased to 16% during 2006–2007. As a result, the proportion of elk in the Madison drainage increased from 23% in 1997–1998 to 84% by 2006–2007. Elk apparently minimized predation risk during winter by selecting portions of the landscape that increased their probability of escape if attacked, while still providing relatively high quality vegetation and snow characteristics that allowed access to forage. The change in elk distribution after wolf colonization based on landscape characteristics may account for many of the differences observed in elk responses to wolves among different systems. Fine-scale habitat and topographic features strongly influence elk and wolf habitat selection, creating areas with variable levels of predation risk.

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Barber-Meyer, S. M., L. D. Mech, and P. J. White. 2008. Survival and cause-specific elk calf mortality following wolf restoration to Yellowstone National Park. Wildlife Monographs, 169. Barten, N. L., R. T. Bowyer, and K. J. Jenkins. 2001. Habitat use by female caribou: Tradeoffs associated with parturition. Journal of Wildlife Management 65:77–92. Ben-David, M., K. Titus, and L. R. Beier. 2004. Consumption of salmon by Alaskan brown bears: A trade-off between nutritional requirements and the risk of infanticide? Oecologia 138:465–474. Berger, J. 1999. Anthropogenic extinction of top carnivores and interspecific animal behaviour: Implications of the rapid decoupling of a web involving wolves, bears, moose and ravens. Proceedings Royal Society of London B Biological Sciences 266:2261–2267. Berger, J. 2004. The last mile: How to sustain long-distance migration in mammals. Conservation Biology 18:320–331. Berger, J., J. E. Swenson, and I.-L. Persson. 2001. Recolonizing carnivores and naı¨ve prey: Conservation lessons from Pleistocene extinctions. Science 291:1036–1039. Bergerud, A. T., and R. E. Page. 1987. Displacement and dispersion of parturient caribou at calving as antipredator tactics. Canadian Journal of Zoology 65:1597–1606. Bergman, E. J., R. A. Garrott, S. Creel, J. J. Borkowski, and R. M. Jaffe. 2006. Assessment of prey vulnerability through analysis of wolf movements and kill sites. Ecological Applications 16:273–284. Berryman, A. A., and B. A. Hawkins. 2006. The refuge as an integrating concept in ecology and evolution. Oikos 115:192–196. Bertram, B. C. R. 1978. Living in groups: Predator and prey. Pages 64–96 in J. R. Krebs and N. B. Davies (Eds.) Behavioural Ecology: An Evolutionary Approach. Blackwell, Oxford, United Kingdom. Beutel, T. S., R. J. S. Beeton, and G. S. Baxter. 1999. Building better wildlife-habitat models. Ecography 22:219–223. Bowyer, R. T., J. G. Kie, and V. Van Ballenberghe. 1996. 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