The influence of habitat use on harvest vulnerability of cow elk (Cervus canadensis).

Pressure from hunting can alter the behavior and habitat selection of game species. During hunting periods, cervids such as elk (Cervus canadensis) typically select for areas further from roads and closer to tree cover, while altering the timing of their daily activities to avoid hunters. Our objective was to determine the habitat characteristics most influential in predicting harvest risk of elk. We captured 373 female elk between January 2015 and March 2017 in the Uinta-Wasatch-Cache National Forest and surrounding area of central Utah, USA. We determined habitat selection during the hunting season using a resource selection function (RSF) for 255 adult cow elk. Additionally, we used a generalized linear mixed model to evaluate risk of harvest based on habitat use within home ranges (3rd order selection) as well as the location of the home range on the landscape to evaluate vulnerability on a broader scale. Female elk selected for areas that reduced hunter access (rugged terrain, within tree cover, on private land). Age, elevation and distance to roads within a home range were most influential in predicting harvest risk (top model accounted for 36.2% of AIC weight). Elevation and distance to trees were most influential in predicting risk when evaluating the location of the home range (top model accounted for 42.1% of AIC weight). Vulnerability to harvest was associated with proximity to roads. Additionally, survival in our landscape decreased with age of femaleelk.

Introduction

Selection of resources and habitats is a driving force influencing animal population [1]. As such, a thorough understanding of the factors that influence habitat selection is vital for proper management and conservation of a species [2]. Because resources are not uniformly available across the landscape, organisms select the most beneficial habitats [3]. Selection occurs at multiple scales and has been categorized into specific orders of selection [4]. The broadest of these scales, first order selection, describes selection of a geographic range, while second order narrows the selection further to local sites [5]. Third order selection describes usage patterns of local areas and finally, fourth order selection can describe selection at finer scales (e.g., foraging sites). Selection of habitats may be influenced by quality of forage, risk of predation, competition, energy trade-offs, or anthropogenic influences like development, outdoor recreation, and hunting [6-8].

Pressure from hunting (additional disturbance, increased risk of mortality) can influence behavior and habitat selection of game species. During hunting periods, game species often shift habitat use away from areas with optimal resource quality towards areas offering greater security [9]. For example, black bears (Ursus americanus) and wolves (Canis lupus) shifted habitat use towards less accessible areas, further from roads [6]. White-tailed deer (Odocoileus virginianus) altered their habitat use and timing of daily activity to avoid hunters [10]. Hunting led to reduced intraspecific competition, decreased mating opportunities, and increased group size in red deer (Cervus elaphus) and Dall sheep (Ovis dalli), likely due to the removal of dominant individuals [10, 11]. Understanding the effects of harvest and anthropogenic activities on behavior, resource selection, and population dynamics is fundamental to conservation.

Rocky Mountain elk (Cervus canadensis), a big game species in North America respond to hunting pressure suggesting that hunters may influence elk population dynamics beyond the direct effects of harvest-related mortality. During the hunting season, elk select for areas further from roads and often use private land as refuge [12-15]. Daily movement rates increase and elk expend additional energy avoiding hunters [16, 17]. Additionally, flight distances of elk increase during hunting periods, while group sizes decrease, suggesting elk are aware of the increased risk of mortality [17, 18]. Not only can hunting pressure influence distribution of elk, the distribution of elk on the landscape may influence susceptibility to harvest. Vulnerability of elk to harvest is likely influenced by hunter efficiency, habitat selection by elk, and detectability of elk [19]. Detectability of elk can vary with time of day, cover type, and presence of snow. It may also decrease with age as older individuals become familiar with annual hunting pressure [20].

As elk age, they may learn to avoid hunters by reducing use of high-risk areas [20, 21]. Bull elk had more pronounced responses to hunting pressure than cows and mature bulls exhibited greater flight distances than younger bulls, consistent with higher rates of harvest for mature bulls [18]. Older cow elk reduced movement rates during the hunting period and increased use of rugged terrain [20]. Further, the same study showed that cows over the age of 9 or 10 were almost invulnerable to harvest by hunters. As long-lived, gregarious animals, elk may learn to avoid hunters by altering habitat use.

The risk of harvest for game animals is likely influenced by a multitude of factors, including selection of habitat during the hunting season. Our objectives were to determine the habitat characteristics most influential in predicting harvest risk of elk. We expected risk of harvest to be correlated with hunter accessibility and that elk in rugged, less-accessible areas would be at reduced risk. Further, we predicted older elk would show reduced use of high-risk areas. We treated the rifle season and archery season as one long hunting season. While differences may have existed between the two seasons, the general patterns and predictions associated with harvest risk shouldn’t change. Elk that selected habitats closer to roads and in less rugged terrain, for example, were expected to be at increased risk. While we were unable to evaluate all factors that potentially influenced the habitat use of elk during the hunting season, we compared patterns of use during the hunting season and examined differences in use between hours of risk (daytime) and hours when hunting was not allowed (nighttime) to provide an overall understanding of how habitat use changes during hours of harvest risk. Identifying the factors associated with harvest risk of elk can increase knowledge of population dynamics, advance understanding of the responses of game species to hunters, and provide additional insight into age structure of the population, thereby improving management.

Methods

Study area

This study was part of a larger study on the movement patterns and habitat use of elk, conducted in the Wasatch Mountains and surrounding areas of central Utah, USA west of Salt Lake City (Fig 1). The Wasatch Mountains are the southwestern portion of the Rocky Mountains extending approximately 400 kilometers [22], and have steep, rugged slopes from past glaciation events [23]. The Wasatch range is formed from dolomite and limestone [24]. This area receives an approximately 40 centimeters of annual precipitation, which varies with elevation [25]. Base elevation in the region is approximately 1370 meters and Mount Nebo, at 3620 meters, is the highest point along the range, as well as other prominent peaks such as Mount Timpanogos and Mount Olympus [26, 27]. The species composition of plant communities varies with elevation and have been described across distinct elevational zones [28]. Below 1980 meters, the Upper Sonoran Zone, is dominated by sagebrush (Artemisia spp) and Mexican cliffrose (Purshia stansburyana). Elevations between 1981–2440 meters, the Transition Zone, are populated by brush species like Gambel oak (Quercus gambelii) and curl-leaf mountain mahogany (Cercocarpus ledifolis; [29]). Above the Transition Zone is the Canadian Zone, from 2440–2900 meters, which is characterized by aspen (Populus tremuloides) and white fir (Abies concolor), then followed by the Hudsonian Zone, characterized by subalpine fir (Abies lasiocarpa) and Engelmann spruce (Picea engelmannii). Finally, the Arctic-Alpine Life Zone, above 3200 meters, is populated by primrose (Oenothera spp) and alpine moss. Predators of elk in this region are limited; no wolves or grizzly bears (Ursus arctos) occur and predation from mountain lions (Puma concolor) is minimal, typically restricted to calves or older, weakened individuals.

Fig 1

Study of harvest vulnerability of elk was conducted in the Wasatch and surrounding management units of central Utah, U.S.A.

Colored polygons denote the separate management units in the area.

Elk hunting in Western US

Because hunting is the primary tool used to manage populations, the goal in most regions of the western Unites States is to provide opportunity for hunters while managing populations. To attain these management goals, there are often different game management units with different goals ranging from primarily opportunity (increased opportunity to harvest any animal) to primarily “quality (i.e., increased likelihood of harvesting a mature male)”. Different seasons (e.g., archery only, muzzleloader only, and any weapon) for different portions of the population (females only, males only, or either sex) and the various seasons generally run from August through January. In our study area, archery-only seasons typically start in mid-August and run through mid-late September. Any weapon hunts (most hunters electing to hunt with a rifle) start in October and end in January. Of course, differences among weapons types and seasons affect the likelihood of successfully harvesting an animal [30]. Hunter’s using archery tackle are typically less successful than those using firearms. Likewise, it is hypothesized that hunters pursuing females are typically more successful than hunters pursuing males unless it is a unit managed for high “quality” as these populations generally have a relatively high proportion of males.

Methods of take primarily consist of ambush, still-hunting, or spot and stalk methods. For the ambush method, hunters generally sit in a location of vantage (hill, tree stand, etc.) in areas known to have elk or along travel paths and wait for an individual to travel into the open within their effective hunting range. The still-hunting method consists of the hunter moving quietly and very slowly, with regular stops, through elk habitat in an attempt to spot an animal before the animal is aware of the hunter’s presence. The spot and stalk method is when a hunter searches from a vantage with a spotting scope or other optics in an attempt to locate game, often at a great distance (up to several km away). Once the game is located, the hunter plans an approach (i.e., stalk) to get within effective hunting range without detection. There are a few other less common methods (e.g., small-scale game drives by groups of hunters, driving roads while looking for elk, etc.).

Elk capture

We captured elk via helicopter net-gunning from January 2015 through March 2017 [31]. Individuals were restrained using hobble straps and fit with a blindfold, no sedation or euthanasia was involved. All capture and handling of wildlife was approved by the Brigham Young University Institutional Animal Care and Use Committee (permit #150112).We collected body measurements, blood, and fecal samples for each elk, as well as an estimate of body condition [32] and age based on dental wear. Approximately 10–16 mLs of blood were collected from each individual from either the neck or the leg and subsequently used for mineral analysis. Aging by tooth wear is not always accurate, however, post-hoc analyses of teeth from deceased elk via cementum analysis found that over 80% of individuals were accurately aged to within one year. We measured loin muscle thickness and rump fat using ultrasonography. Body mass and ingesta free body fat were calculated for each individual [33]. Captured individuals were then fitted with VHF radio and GPS collars before being released. In order to balance frequency of data collection and longevity of the collars, we programmed collars to collect a GPS location every 13 hours. Mortality warnings were triggered by a lack of animal movement after 8 hours. When we received a mortality warning, we attempted to locate the deceased animal and determine cause of death within 48 hours.

Analysis

Evaluating habitat use during hunting season

We calculated separate home ranges for each elk and each hunting season. We restricted our analysis to locations collected during the hunting season to limit any additional effects from seasonal changes. We created 95% minimum convex polygons (MCPs) using locations during the hunting season [34-36]. Opening day varied a little bit each year, but always occurred in mid-August; conclusion of the fall hunting season did not vary and ended on January 31st each year. A separate MCP was created for each hunting season, such that if an elk lived through all three years examined, three separate MCPs were created. We excluded animals with less than 50 locations during the hunting season to avoid biased estimates of home ranges [37, 38]. Although prior studies have raised questions on the legitimacy of MCPs to estimate home ranges, we used this method as a boundary to evaluate selection of each individual, as opposed to estimating size of the home range. Additionally, habitat occupied by elk did not include any uninhabitable areas that could have resulted in inaccurate MCPs. As a result, we considered these boundaries adequate to evaluate selection within the area used by each individual. We analyzed selection preferences during the hunting season using a resource selection function (RSF) to provide an understanding of habitat selection and distribution of individuals [39]. Based on known locations of use from collared individuals, relative probabilities of use can be estimated with an RSF [40, 41]. Within each MCP, we compared an equal number of used locations to random locations, after confirming that this number was sufficient to capture availability by looking at whether or not 95 percent confidence intervals from random locations spanned the mean from all pixels within a home range. We acquired habitat variables at 30-m resolution from the Utah Automated Geographic Reference Center (AGRC). Habitat variables included a 30-meter digital elevation model (DEM), land ownership, a layer of roads in the area, and dominant vegetation. As forest roads are frequently used during hunting season, we combined motorized roads and forest roads into a single layer to compute distance to roads. Ruggedness, slope, and aspect layers were created from the DEM using ArcGIS. Distance to trees, roads, and private land were computed in ArcGIS based on the rasters acquired from Utah AGRC. We included distance to private land as a variable as private land is often used as a means of refuge from hunting pressure by game species [12, 15]. While some landowners do allow hunting, this land is not available to the general public and, as such, typically experiences reduced or no hunting pressure. Other factors may be confounding the habitat selection of elk, such as seasonal changes, presence of predators, or varying pressure from hunters throughout the season or between weapon types. However, all samples (whether from harvested elk or elk that survived the hunting season) were treated identically and analyzed in the same manner limiting potential bias.

To examine habitat use during the hunting season, we evaluated 27 candidate models of habitat selection using an AICc model selection process for logistic regression models in program R [42, 43]. Variables were screened for collinearity in program R. We categorized each location as occurring during hunting hours, when elk are susceptible to risk, or outside of hunting hours, when risk of harvest is absent. Legal hunting hours started 30 minutes prior to sunrise and ended 30 minutes after sunset. We used these same time intervals to classify locations as occurring day or night. To examine differences in selection between day (i.e., when elk are susceptible to harvest) and night, we used interaction terms between habitat variables and a binary variable to denote the time as either day (1) or night (0). We formulated animal ID as a random intercept to account for repeated measures and dependence of the locations [44]. We validated our top model using k-fold cross validation with k = 5 and computed a Spearman’s rank correlation.

Evaluating harvest vulnerability based on 3rd order habitat use

We evaluated harvest vulnerability of elk based on habitat use at two scales: habitat use within home ranges [19] and at a broader scale based on the overall location of the home range on the landscape using the centroid of each home range [36]. We modeled risk of harvest by hunters using logistic regression with 1 corresponding to survival and 0 representing harvest [19]. We included variables for distance to roads, aspect, elevation, slope, terrain ruggedness, distance to tree cover, and distance to private land [14, 19]. Variables were screened for collinearity in program R. We evaluated vulnerability to harvest based on 3rd order selection by averaging data from all locations within the home range and considered each hunting season from every elk as an individual observation [45], resulting in a data set with each row containing the average value of each variable for one elk during one season. We excluded locations that occurred outside of hunting hours, as there was no risk of harvest mortality during these hours. We used linear mixed-effects regression models to examine habitat characteristics as fixed effects and again incorporated animal ID as a random intercept to account for dependence between repeated observations for a single individual. We evaluated 20 candidate models of harvest vulnerability using an AICc selection process in program R [42, 43]. Some of these models included age to determine if older elk were less susceptible to harvest than younger elk.

Evaluating harvest risk based on location of home range

Additionally, we evaluated harvest risk based on the location of the home range on the broader landscape using the centroid of each home range [36]. We chose to use the center of the home range to examine how risk of harvest may change based on the overall position of the home range on the broader landscape. As such, the centroid can be used to evaluate this broader geographic location. We obtained measurements of the aforementioned habitat characteristics for the centroid of each home range. We evaluated the same set of 20 candidate models to compare influential habitat characteristics between the two scales. Using the top model, we developed a map of risk of hunter harvest across the study area [46].

Results

Between January of 2015 and March of 2017, we captured and collared 373 female elk. We restricted the analysis to locations during the hunting season and removed any elk with less than 50 locations, at which point 255 animals remained. We created separate home ranges for each hunting season during which an animal had locations, totaling 358 home ranges. In total, 80 animals were harvested by hunters throughout the 3-year period, 58 of which were included in this analysis based on the criteria described above.

Out of 27 candidate models of habitat use, the top model accounted for 83.6% of the weight compared to 16.4% for the second most supported model (Table 1; Spearman’s rank ρ = 1, p = 0.0167). Habitat use of elk during the hunting season was influenced by aspect, elevation, ruggedness, slope, and distance to private land, trees, roads, day vs night, and an interaction between time of day and ruggedness, distance to private land, and distance to trees. According to the interaction terms in the model, elk selected for rugged terrain, closer to private land and tree cover during the day compared to nighttime (Table 2). Overall, elk selected for areas that were high in elevation and far from roads and tree cover. Steep slopes and rugged terrain were associated with decreased probability of use.

Table 1

AICc model selection results for 27 candidate models of habitat use.

	d.f.	AICc	ΔAICc	Weight
Aspect + Elevation + Day*Ruggedness + Slope + DistTrees + DistRoads + Day + DistPriv + Day*DistPriv + Day*DistTrees	13	191845.2	0.00	0.836
Aspect + Elevation + Ruggedness + Slope + DistTrees + DistRoads + Day + DistPriv + Day*DistPriv + Day*DistTrees	12	191848.5	3.26	0.164
Aspect + Elevation + Ruggedness + Slope + DistTrees + DistRoads + Day + DistPriv + Day*DistPriv	11	192073.3	228.10	0.000
Aspect + Elevation + Ruggedness + Slope + DistTrees + DistRoads + DistPriv+ Day + Day*DistTrees	11	192214.2	368.97	0.000
Null	1	193528.7	1683.48	0.000

Top model included aspect, elevation, ruggedness, slope, distance to trees, distance to roads, and distance to trees, accounting for 83.6% of the total weight. The variable Day represents a binary variable identifying a location as occurring within hours of hunting risk (Day, 1) or outside of hunting hours (0). We included Animal ID as a random effect in every model. The top five models based on AICc are included in the table.

Table 2

Output from top model (based on AICc) of habitat selection of elk during the hunting season.

	Estimate	Std. Error	p–Value
Intercept	-0.0045	0.0073	0.533
Aspect	0.0634	0.0054	< 0.001
Elevation	0.0394	0.0066	< 0.001
Day	0.0133	0.0109	0.221
Ruggedness	-0.0448	0.0077	< 0.001
Slope	-0.1368	0.0062	< 0.001
DistTrees	0.0992	0.0084	< 0.001
DistRoads	0.0881	0.0059	< 0.001
DistPriv	0.0078	0.0080	0.331
Day*Ruggedness	0.0251	0.0109	0.022
Day*DistPriv	-0.2163	0.0113	< 0.001
Day*DistTrees	-0.1663	0.0111	< 0.001

The variable Day represents a binary variable identifying a location as occurring within hours of hunting risk (Day, 1) or outside of hunting hours (0).

We determined habitat factors that had the greatest support for predicting risk of harvest and found differing results between the two scales examined. Within each animal’s home range, harvest vulnerability was most influenced by distance to roads, elevation, and age of the animal (top model accounted for 36.2% of the weight, Table 3). According to our top model, harvest risk increased with proximity to roads (p = 0.056, Table 4, Fig 2). Additionally, probability of survival during hunting season was lower at higher elevations (Fig 3) and for older animals (Fig 4). Interactions terms between age and distance to roads, distance to trees, distance to private land, and elevation were not supported in the models.

Table 3

AICc model selection results for 20 candidate models of survival based on habitat use.

	d.f.	AICc	ΔAICc	Weight
Age + DistRoads + Elevation	5	283.7	0.00	0.369
DistRoads + Elevation + Age + DistPriv	6	285.0	1.37	0.186
Age + Elevation + DistRoads + Ruggedness	6	285.7	2.07	0.131
Age + Elevation	4	286.1	2.45	0.108
Age + Elevation + Age*Elevation	5	287.4	3.73	0.057
Null	1	295.1	11.48	0.001

We included Animal ID as a random effect in every model. Models with greater than five percent of the cumulative weight are listed below. Top model included age, distance to roads, and elevation, accounting for 36.2% of the total weight. The top five models based on AICc are included in the table.

Table 4

Output from top model (based on AICc) of survival of elk based on habitat use.

	Estimate	Std. Error	p–Value
Intercept	1.932	0.171	< 0.001
Age	-0.113	0.151	0.453
DistRoads	0.414	0.222	0.0625
Elevation	-0.311	0.176	0.0764

Fig 2

Predictive model of harvest vulnerability of elk in central Utah, U.S.A., as a function of increasing distance to roads, according to the top model from AICc selection.

Top model included age, distance to roads, and elevation.

Fig 3

Predictive model of harvest vulnerability of elk in central Utah, U.S.A., as a function of elevation, according to the top model from AICc selection.

Top model included age, distance to roads, and elevation.

Fig 4

Predictive model of harvest vulnerability of elk in central Utah, U.S.A., as a function of increasing age.

Values are derived from top model according to AICc selection. Top model included age, distance to roads, and elevation.

Based on overall location of the home range on the landscape, vulnerability to harvest was most influenced by elevation and distance to trees (top model accounted for 42.1% of the weight, Table 5). The top model included an interaction between elevation and distance to trees (p = 0.028, Table 6) suggesting that at higher elevations, distance to trees became more influential in predicting harvest risk. At higher elevations, increasing distance to tree cover was positively associated with survival. We used the top model based on home range centroids to create a heatmap of harvest vulnerability across the study area (Fig 5) to illustrate high-risk areas. Our results predicted high vulnerability in the northwest (Currant Creek/Wasatch front) and southwest portions (Nebo Mountains) of the study area, as well as throughout the Uinta Mountains near the center of the study site. Additionally, we predict low vulnerability in the southeastern portion (Uinta basin).

Table 5

AICc model selection results for 20 candidate models of survival based on overall location of the home range on the landscape.

	d.f.	AICc	ΔAICc	Weight
Elevation + DistTrees + Elevation*DistTrees	5	239.0	0.00	0.421
Elevation + Ruggedness	4	242.1	3.15	0.087
Age + Elevation	4	242.3	3.33	0.080
Age*DistRoads + Age + DistRoads	5	242.5	3.52	0.072
Age*Elevation + Age + Elevation	5	242.8	3.87	0.061
Age + DistRoads + Elevation	5	243.7	4.71	0.040
Age + DistTrees + DistPriv	5	243.8	4.79	0.038
Age*DistTrees + Age + DistTrees	5	243.8	4.81	0.038
DistPriv + DistTrees	4	244.3	5.33	0.029
Age*DistPriv + Age + DistPriv	5	244.4	5.38	0.029
Age + Elevation + DistPriv	5	244.4	5.38	0.029
Slope + Aspect + Ruggedness + DistTrees	6	244.6	5.61	0.025
Elevation + DistTrees + Ruggedness + DistRoads	6	244.9	5.95	0.021
Null	1	295.1	56.16	0.000

We included Animal ID as a random effect in every model. Models with greater than two percent of the cumulative weight are listed below. Top model included elevation, distance to trees, and an interaction term, accounting for 42.1% of the total weight. Models carrying at least 2% of the total weight were included in the table.

Table 6

Output from top model (based on AICc) of survival of elk based on based on overall location of the home range on the landscape.

	Estimate	Std. Error	p–Value
Intercept	10.784	1.447	< 0.001
Elevation	0.430	0.811	0.596
DistTrees	0.507	0.804	0.528
Elevation*DistTrees	1.228	0.560	0.028

Fig 5

Heat map of harvest vulnerability of elk based on the location of the home range on the landscape, modeled as a function of elevation, distance to trees, and an interaction between elevation and distance to trees.

Discussion

Overall, elk selected for areas at high elevations, far from roads and further from tree cover. Elk altered habitat selection during hunting hours, selecting for areas that limited hunter access. Specifically, elk selected for rugged terrain, tree cover and private land when risk of mortality was greater. Additionally, we found preference for flatter, less rugged terrain. Our study incorporated similar variables as prior studies in assessing habitat selection by elk such as vegetation and cover, road density, land ownership, topographical complexity, and various measures of hunter effort or access [19, 47, 48]. Based on our top model, elk altered their selection preferences during hunting hours, increasing use of areas with limited hunter access (rugged terrain, close to private land and tree cover), supporting our predictions and suggesting elk altered their habitat use in response to heightened risk [49]. We also found preference for flatter, less rugged areas further from tree cover, contrary to our expectations, however during the winter elk may select flatter grasslands for forage [9], possibly explaining the use of flatter, open areas. During the hunting season, elk selected for rugged areas with lower road density, closer to tree cover, consistent with other populations of elk [19, 45]. Additionally, we found a preference for private land, consistent with prior studies of hunted populations of elk [12, 14, 15]. Our results support previous findings of elk selecting for areas with limited hunter access during periods of heightened risk of harvest [50].

Within an animal’s home range, harvest vulnerability was best predicted by distance to roads, age of the individual, and elevation. Elk had increased survival further from roads. Survival decreased with increasing elevation. This was likely due to public land generally occurring at higher elevations than private land within our study area; as hunting primarily occurred on public land, this may explain the decreased survival at higher elevations. Vulnerability of elk to harvest is often correlated with road density or proximity to roads [19, 45, 47, 51]. Our results support the idea that harvest risk increases with proximity to roads [50]. Additionally, survival decreased with age [52], and none of our models with age and habitat variable interactions were among the top supported models. This finding differs from previous work where elk have been shown to learn to avoid hunters with age. Older females reduced movement rates in the presence of hunting pressure and, as a result, had higher survival [53]. Older cow elk also increased use of rugged terrain closer to roads [20]. The specific reasons we did not detect learning in our study and why older elk were more likely to be harvested are unclear. In our study, we experienced relatively high harvest rates (23 percent; 58/255) that may have overcome evidence of learning. Alternatively, learning may have occurred, but because we only monitored elk for 3 seasons and many of our animals were not caught until the 2nd or 3rd year it simply wasn’t detected. Thurfjell et al. [20], for example, monitored elk for up to 5 years. Further evaluation of learning by elk in response to hunting is warranted.

Based on the centroid of the home range, risk of harvest was best predicted by distance to trees, elevation, and an interaction between the two. Probability of survival was higher with increasing distance to trees at high elevations, somewhat contradictory to our expectations. However, overlap between elk and hunters was highest in forested areas and lower in uncovered areas [51], possibly explaining why we found lower harvest risk away from forest cover. Additionally, elk decreased use of forested areas during the hunting season [20, 47], consistent with our results that survival increased as distance to trees increased.

Elk altered habitat use during hunting hours, increasing use of areas with limited hunter access (rugged terrain, within tree cover and closer to private land). Additionally, elk selected for areas far from roads and high in elevation. On a broader scale, vulnerability to harvest was influenced by elevation and distance to trees. Age, elevation and distance to roads were the best predictors of harvest risk based on habitat use within the home range. Much is known about resource selection during the hunting season, however, less research has focused on harvest vulnerability and such studies typically examine risk based on use within the home range, while our study compared vulnerability based on habitat use within home ranges and on the overall location of the home range. Further, our study benefitted from a large sample size and repetition across multiple years. However, some limitations should be taken into consideration as well. Similar studies have incorporated some measure of hunter density or hunter effort [51], which was not available in our study areas. Other habitat variables, such as topographical complexity, that were not measured may have also been influential in predicting vulnerability to harvest. Seasonal effects may have influenced the habitat selection of elk, as well. We restricted our sampling period to the hunting season to remove some seasonal variation, however, the hunting season does coincide with a shift from autumn to winter and therefore, changing temperature and weather patterns may influence habitat use of elk. Further, some variation may have existed throughout the duration of the season, between years or between weapon types, however, there is generally a consistent presence of hunters and an increased risk of mortality once the hunting season commences until the close of the season.

Our study supports the idea that elk select for areas with limited hunter access and highlights habitat characteristics that best predict harvest risk of elk in central Utah. These results provide further insight into the responses of game species to hunting pressure and can be used to inform future management policies. By better understanding vulnerability of elk across the landscape, allocation of hunting permits can be adjusted accordingly in areas of high or low vulnerability to better meet population objectives.

Correlation values for variables used in resource selection models of cow elk in central Utah during the hunting season, calculated using ‘cor()’ function in program R.

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20 Dec 2019

PONE-D-19-22105

Habitat Use and Harvest Vulnerability of Elk (Cervus canadensis): Do Elk Learn to Avoid Hunters as They Age?

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5. Review Comments to the Author

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Reviewer #1: General comments

Deer populations are traditionally managed by means of hunting. Deer may respond to hunting by using refuges, avoiding human activity centers, modifying movement, activity and habitat selection. Accordingly, knowledge of the effects of hunting on deer behavior is necessary to enhance the effectiveness of deer management. In the present manuscript you determine the habitat characteristics most influential in predicting harvest risk of elk and if elk learned to avoid hunters with age. Although I do not call the relevance of these data into question, I have several points that need to be clarified or refined but see my general and specific comments.

Methods

PLOS is an international journal and not all readers are familiar with elk hunting in the USA. In this regard, you should include additional information in Methods (see points below):

How are elk hunted in the Wasatch Mountains and surroundings? Are there different types of hunting (e.g. hunting with beaters, hunting from a hide…)? Please specify

Could you please provide further information about how elk hunting is organized and if there is a shooting plan (number of males, females and fawns)? If there is a shooting plan you should add it in Methods.

All this information will be useful for the interpretation of your results and for the discussion.

Could you please provide more information about what is exactly meant by private land and why you think that this variable should be included to model elk habitat use and risk of harvest? I am especially wondering why private land should be less accessible to hunters given that some private landowners could be hunters too or allow hunters to hunt on their ground according to my understanding. Clarify please.

Study design and statistical analyses:

You wrote “We analyzed selection preferences during the hunting season using a resource selection function”. For me it is not clear what you aim for by doing so. The chosen approach does not enable to draw any conclusions regarding the hunting effect as you cannot be sure that elk alter habitat selection during hunting hours because of hunting or because of other confounding factors (see below).

If all elk included in the present study are exposed to hunting pressure, it precludes a comparison of hunted with non-hunted individuals in order to detect hunting effects.

Comparing habitat selection during the hunting season to the period before or after is not ideal as seasonal trends in selection and changes in behavior due to hunting can be confounded.

To disentangle other effects (e.g. human disturbances, predators, competition with domestic animals…) from hunting effects, you need to choose a different approach. You could e.g. follow the method described in Behr et al. (2017) and build two separate habitat selection models using two nested data sets: the full data set which includes all location data over the entire year (all data model) and the reduced data set in which you exclude the hunting period from the data and interpolate elk habitat use during the missing hunting period (no-hunting model). As stated by Behr et al. (2017) this method could fail to disentangle a seasonal from a hunting effect if the seasonal driver of habitat selection would perfectly coincide with the hunting season. Hence you need to check if there is a correspondence between the natural history of elk and the timing of the hunting season. If there is no correspondence, you are on the save side.

I recommend to take gender into account in the analyses as vulnerability to harvest based on habitat use could differ between males and females.

You should provide more information on how elk were aged and on how many age categories were considered in the analysis.

I recommend to screen for collinearity between predictors prior to the analysis. Check please (see also my specific comments).

I recommend to perform some validations e.g. Spearman rank correlation from the k-fold cross-validation.

Formatting of the manuscript:

You should ease the work of the reviewers and include line and page numbers.

Data availability:

In contrary to the PLOS Data policy, you did not make all data underlying the findings in our manuscript fully available.

Specific comments

Major comments

Introduction

Page 4: Other aspects such as vigilance, site familiarity could influence the risk of harvest as well. I suggest adding them here. Risk of harvest does not only depend on hunter accessibility other factors could be important as well. E.g. once a deer is spotted/discovered the probability to be harvested could depend on sex, antler size, body condition. It depends furthermore on the type of hunting and on the hunting plan (see above). Clarify please.

Page 4: Besides hunting other factors could influence elk habitat selection including disturbances, interspecific competition (e.g. competition with domestic animals) and predators. In these regards, how can you be sure that the observed difference in habitat selection between night and day is solely the effect of hunting and not due to other confounding factors? Clarify please.

Could you, please provide more information about the domestic livestock (page 5: Methods/Study area:)? Which species, herding practices (are they grazing in fenced pastures), is livestock staying out at night, etc.? Could they potentially compete with elk? Clarify please and discuss.

Are predators such as cougar and wolves present in your study area (these species are manly nocturnal) and could they have a confounding effect with hunting? Clarify please and discuss.

Even if you could exclude livestock and predators there could be other confounding factors you do not know about and hence it could be worthwhile to use an approach that enable to disentangle hunting from other effects (see my suggestion above).

Methods

Page 6: “…and age based on dental wear”. Knowing that age estimation by means of dental wear are not very accurate, I was wondering, which age categories were considered in the present study? Clarify please.

Page 6: “minimum convex polygon” Why did you chose MCP knowing that these can include large proportion of unsuitable habitat especially in a human dominated landscape? I would have expected Kernel home ranges. Please justify why you used MCP in the present study.

Analysis

This is section is not well presented and needs some reordering. I recommend adding subtitles before each section. According to the information provided in the manuscript, I see three topics/sections:

1) Habitat selection to examine habitat use during the hunting season by taking into account differences in selection between day and night. Here it would be worthwhile to choose an approach that enables to disentangle hunting from other confounding effects (see my suggestion above).

2) Evaluation of vulnerability to harvest within the home range including learned hunter-avoidance by older elk.

3) Evaluation of vulnerability to harvest based on the overall location of home range on the landscape including learned hunter-avoidance by older elk.

Page 6: “Based on known locations of use…Lele and Keim, 2006). Please provide further details regarding the sampling design used in the present study fort both within home range and overall location of home range on the landscape. For example, how did you asses availability (number of random locations), etc…See for example Hebblewhite et al. (2005).

Page 6 to page 7: “To examine differences in selection between day …and night…” how did you define day and night in your study? Did you consider that days length changes over the course of the study? Clarify please and provide this information in the manuscript.

Page 7: “We modeled risk of harvest by hunters using logistic regression with 1 corresponding to survival and 0 to harvest…”

In case if elks were harvested during different type of hunting in the present study, I think that it would be wise to consider different categories in the analyses. Clarify please.

I suspect that the harvest risk of a deer varies over the course of the day (highest probability just before dusk and after dawn) and study period (more deer are shot at the beginning of the hunting period then towards the end) and depends as well on the characteristics (sex, age, condition) of each individual. You did not consider these aspects in the present manuscript.

In these regards, could you please provide data about the number of deer (males and females) that are present in your study area, the proportion of collard individuals (males and females) and the proportion of individuals, present in the study area, which are shot each year.

Among the harvested individuals could you please provide information about the sex and age.

Could you please provide further information about the distribution of the number of deer shot over the daily cycle and study period in a graph.

If you have access to the locations of the deer that are shot each year you could use these data to validate your heat map of elk harvest vulnerability.

Page 7: “We included variables for distance to roads, aspect, elevation, slope, terrain ruggedness, distance to tree cover and distance to private land.”

Could you please provide further details regarding the source of the variables used in the present study and their resolution, ideally in a table?

Could you please explain how these variables were sampled in the GIS?

Please provide the size of the radius around each location for the habitat use within home range and the size of the radius around the centroid of each home range for the habitat use at a broader scale based on the overall location of the home range on the landscape.

I do not understand why you used the centroid and did not calculate e.g. the average elevation within each MCP? Clarify please.

Which road categories were considered in the analysis (main roads, forest roads, hiking trails…)? Clarify please.

How did you calculate aspect? Did you use it as a categorical value in the analysis? Clarify please.

Page 7: “We evaluated vulnerability to harvest based on use within the home range by averaging data from all locations within the home range and considered each hunting season from every elk as an individual observation (Hayes et al. 2002).” Not too clear, see also my comment regarding the sampling design used in the present study. Clarify please.

Results

Page 8: How many females and males did you collars?

Could you please summarize the number of females and males collared per age category in a table (elk ID, sex, age, date of capture, date of loss, reason for loss, survey period (number of days), number of fixes)?

Do MCP sizes differ between males and females? If yes, you should take this into consideration in the analysis.

Why did you pool the sexes in the analyses?

I suspect that harvest vulnerability based on habitat varies between sexes (males are more vulnerable than females because of their antlers). Hence, I recommend to take gender into account in the analyses. Do you know if females had calves or not? If yes, you could consider this in the analyses as well. Clarify please.

Page 8: “Steep slopes and rugged terrain were correlated with decreased use.“ Why did you not screen for collinearity between predictors prior to the analysis? Clarify please.

Page 9: “We restricted the model set to locations collected during hunting hours (30 minutes prior to sunrise – 30 minutes past sunset) as animals were at no risk of harvest outside this period.” This is not a result and should be moved to the appropriate section in Methods.

Why did you consider a duration of 30 minutes any justification? Clarify please.

Page 9: “The top model included an interaction between elevation and distance to trees (p = 0.028, Table 6) suggesting that at higher elevations, distance to trees became more influential in predicting harvest risk.” Could you please provide further information on how (direction) harvest risk varied with elevation and distance to trees? Please add this information in the manuscript.

Page 9: “As we were unable to model age across the landscape, the top model based on home range characteristics was used to create a heatmap of harvest vulnerability across the study area (Figure 5) to illustrate high-risk areas.” In contrary to the habitat selection within home ranges you did not provide any result here regarding learned hunter-avoidance by older elk at the broader scale, is there a reason? Clarify please.

Discussion

Page 11: “This was likely due to public land generally occurring at higher elevations than private land within our study area; as hunting primarily occurred on public land, this may explain the decreased survival at higher elevations.” In this regard you should have screened for collinearity between predictors prior to the analysis.

Page 11: “Mature bull elk in Michigan had greater flight distances than yearling bulls, in a population where mature bulls were harvested at five times the rate of yearling bulls (Bender et al. 1999).” This is not really connected to the topic of the present manuscript. This is a behavioral difference and has nothing to do with habitat selection and hence should be removed from the discussion.

Page 12: “Additional work may show patterns of hunter avoidance by elk in central Utah…” Not clear what you mean here. Clarify or remove please.

Page 12: “Based on the centroid of the home range, risk of harvest was best predicted by distance to trees, elevation, and an interaction between the two. The interaction term was positive, suggesting that at higher elevations, survival was higher with increasing distance to trees…” This belongs to results and hence should be moved to this section. Adjust please.

Page 13: “These results can provide further insight into the responses of game species to hunting pressure and can be used to inform future management policies.” This statement is too general. Here you should make some clear and concrete recommendations on how your results can be used to inform management policies. According to your findings what adjustments would be needed in the current management policies? Adjust please.

Minor comments

Introduction

Page 2: “Selection of habitats may be influenced by …” you could add inter- and intraspecific competition as well here.

Methods

Page 6: “late August through January 31st” Could you please provide the exact period?

Results

Page 8: “We evaluated habitat selection in the context of harvest vulnerability within home ranges and on a broader scale to evaluate position of home range on the landscape. We evaluated harvest risk at two scales in order to determine vulnerability based on use within an animals home range as well as based on the overall location of the home range on the broader landscape.” Both sentences have the same meaning. Moreover, this section belongs to Methods and hence should be deleted as these aspects were already mentioned in the corresponding section.

Page 8: “Overall, elk selected…” Not clear what you mean by overall and to which results (e.g. Table) you are referring to here? Clarify please.

Page 9: I suggest changing “Additionally, survival was lower at higher elevations (Figure 3) and for older animals (Figure 4).” to “Additionally, harvest risk was higher at higher elevations (Figure 3) and for older animals (Figure 4).” Because you specifically looked at harvest risk and not overall survival which could include other mortality risk as well. This comment is valid for the whole manuscript. Please check throughout the manuscript and adjust where necessary.

Table 1, legend: “AICc model selection results for 27 candidate models of habitat use.” Only five models are provided here. What is meant by “Day”? Clarify and adjust please.

Table 2, legend: What is meant by Day? Clarify please.

Table 3, legend: “AICc model selection results for 20 candidate models of survival based on habitat use.” Only six models are provided here. Clarify and adjust please.

Table 5, legend: “AICc model selection results for 20 candidate models of survival based on overall location of the home range on the landscape. Only 14 models are provided here. What is meant by “Day”? Clarify and adjust please.

Figure 1: What is the additional information provided by the inset? Instead I suggest showing the location of the study area in the USA. Adjust please.

Reference cited in this review not already cited in the present manuscript

Gehr, B., E. J. Hofer, M. Pewsner, A. Ryser, E. Vimercati, K. Vogt, and L. F. Keller. 2017. Hunting-mediated predator facilitation and superadditive mortality in a European ungulate. Ecology and Evolution 8:109–119.

Reviewer #2: Very interesting paper, well written and the statistical analyses seems up to date. One thing that comes to mind when looking at your study is that other studies seem to account for the sex of the animal. I am not familiar with the exact policies in Utah, but my experience from elk hunting suggests that hunters have different attitudes towards hunting females and males, often looking for trophies in males, and meat in females (and spikes). Trophies come at a relative high age, also proportion of tags may differ compared to what is available for each sex. I am not sure it is possible, but it would be nice to see if it is possible to distinguish differences if the analyses were re run, once with males and once with females. A study from Alberta by Ciuti et al. (2012), together with the paper by Thurjell et. al that you already cite suggests that, at least in Alberta, the high hunting pressure on males leads more to a selection of traits than a learning experience. There is also the issue of how gregarious animals are during hunting season, it is hard to imagine a learning process without members of a group being shot. As males are less gregarious than females, we would expect a different process there (even though effects has been found in bulls in Michigan as you state).

There are also other studies that suggest lower mortality with age (Wright 2006), thus it would be interesting if you made some attempt to dive in to the differences compared to those studies. (By more detailed analysis as suggested, or at least by a discussion on the subject).

As for the hunting season, from late August to Jan 31st is quite a long time, with quite different weather conditions for the elk (And different weapons and tactics used by hunters, as Utah has an archery season and a Muzzel loader season). Yet I see no attempt to account for that, there are several ways to do this. If you want to account for seasonality and still have the effect of hunting (as they will be mixed up), one way of doing this is to add a factor weekend or weekdays, as we could expect hunting pressure is generally higher on Saturdays and Sundays.

As for minor details such as language and grammar, as a non native English speaker, that is not my forte, and I tried to focus on the structure here.

Ciuti S, Muhly TB, Paton DG, McDevitt AD, Musiani M, Boyce MS. Human selection of elk behavioural traits in a landscape of fear. Proc R Soc B-Biol Sci. 2012;279(1746):4407–16.

Wright GJ, Peterson RO, Smith DW, Lemke TO. Selection of northern Yellowstone elk by gray wolves and hunters. J Wildlife Manage. 2006;70(4):1070–8.

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Reviewer #1: Yes: Fridolin Zimmermann

Reviewer #2: No

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Submitted filename: PONE-D-19-22105_LFB.pdf

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13 Mar 2020

Thank you for the revisions provided to our submitted manuscript. We incorporate the recommended changes and have provided an updated draft of the manuscript. The specific edits that were made are detailed in the "Response to Reviewers" document included in the resubmission. Thank you again for your time and consideration.

Submitted filename: Response to Reviewers 05.03.2020.docx

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21 May 2020

PONE-D-19-22105R1

Habitat Use and Harvest Vulnerability of Elk (Cervus canadensis): Do Elk Learn to Avoid Hunters as They Age?

PLOS ONE

Dear Dr. Sergeyev,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

As you can see, both reviewers were pleased to see the revisions and improvements to your manuscript. For submission of a revised manuscript, please provide additional justification for the inclusion or exclusion of classes of animals as described by Reviewer 1. Additionally, note Reviewer 1's comments about confounding factors in your analysis. Reviewer 2 provides some suggestions for improving the flow and structure of the manuscript. In addition, please note their request for additional discussion of why female elk did not show evidence of some learning, as has been previously suggested.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: No

Reviewer #2: Partly

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: General comments

Although the manuscript has been improved. There are still several points that need further attention. Especially the manuscript is technical not sound as there are several problems in your sampling design and statistical analyses that preclude making sound conclusions at the current stage. But see my general and specific comments below.

In this analysis you apparently only included animals lost to hunter harvest (as you have written in your answers to reviewers).Could you please justify (rational behind) why you only used individuals lost to hunter harvest? Beside that this is not clearly stated in the material and method, I think that you should include all elk cows followed by means of GPS telemetry over the course of this survey in the analyses including those that were not shot over all the hunting seasons, as done by McCorquodale et al. (2003). Check their paper to see exactly how they proceed. Exclusion of animals that survived throughout all hunting seasons might bias our analysis toward elk using less secure environments. Clarify please and adjust if necessary.

In this regard you should summarize the number of cows and bulls collared per age category in a table (elk ID, sex, age, date of capture, date of loss, reason for loss (hunting, predation,…), survey period (number of hunting seasons, number of days, number of fixes). Moreover, you should add in the results how many elk died and how many deaths were hunting related (like McCorquodale et al. 2003).

You mentioned that habitat selection by elk is likely greatly confounded by seasonal effects in Utah. The heavy snows will typically push elk to lower elevations during the colder periods, while availability of forage and extreme heat likely influence habitat use during the summer. For this reason, you restricted our analysis to the hunting season to minimize these seasonal differences. Given that the hunting season stretches from the end of August and is concluded on January 31st, it encompasses the transition from autumn to winter that include significant changes e.g. heavy snows will typically push elk to lower elevations during the colder periods, with snow elks can easier be detected by hunters thanks to the tracks they leave in the snow. Hence as the hunting season stretches over quite a long period, with quite different weather conditions for the elk and different weapons and tactics used by hunters resulting in changes in the hunting success you need to account for that as already recommended by the other reviewer in the analysis.

You excluded animals with less than 50 locations during the hunting season to avoid biased estimates of home ranges. Given that your interest in estimating home ranges was principally to define sampling frames for quantifying characteristics of areas used by elk (rather than a means of estimating a home range as stated in your response to reviewer’s comments), I do not see why you should discard data from elk that were killed before a large sample of relocations were obtained. Exclusion of such animals might bias your analysis toward elk using higher-security environments. Clarify and discuss please.

Variables were screened for collinearity in program R (line 207). Which analysis did use to test for multicollinearity between predictors and what was the threshold? Please provide the results of this analysis as a supplementary material.

Could you please provide more details on how you proceeded with the validation (lines 214-215)? How many folds did consider? Clarify please.

Furthermore, I could not find any values of the Spearman’s rank correlation in Table 1 (lines 260-261). What is the value of the Spearman’s rank correlation? Clarify please.

Why do you just do a validation for the “habitat use during hunting season” but not for the remaining two analyses “harvest vulnerability based on 3rd order habitat use” and “harvest risk based on location of home range”. Clarify please.

As your study focus solely on elk cows you need to adjust the title and abstract and the main text accordingly. In the discussion you should focus mainly on findings from other studies related to elk cows, especially if differences between bulls and cows are expected.

You indicated that wolves and bears are absent from the area, however, cougars are present and stated that predation of elk by cougars is generally minimal and typically cougars target young or old individuals in poorer condition. Even though predation of elk by cougars is minimal, even low carnivore densities affect prey behaviour (Kuijper et al. 2016). Besides, I question that cougars target old individuals in poorer condition. I would have rather expected to see such a pattern with wolves. Cougars are stalk and ambush predators and hence have a higher probability to catch less alert prey and exert selection pressure rather on the behavior of their prey (less alert prey have a higher chance to be predated) while wolves, because of the way they hunt, exert selection pressure rather on the condition of their prey. If you were not able to take such confounding effects into account in the analyses you should at least discuss this shortcoming in the discussion of the manuscript.

You wrote that you examined whether habitat use changes in regard to these variables when hunters are present versus absent. Yes, but what if in your study area period of times when hunters are present versus absent overlap with other factors such as disturbances and predators. In this case you cannot distinguish hunting from these confounding effects. You should at least discuss this shortcoming in the discussion of the manuscript.

No track changes are visible in the document “Revised Manuscript with Track Changes”. Please make sure that you upload the right files to ease the work of the reviewers.

Specific comments

Lines 121-123: Could you please specify roughly the period in months of the archery only, muzzleloader only, and any weapon hunting seasons?

Lines 173-175: Did you calculate an MCP for each hunting season that an elk lived/was followed by means of GPS telemetry? Clarify please

Lines 190-192: This sentence can be deleted as this information appears earlier.

Lines 198-203: In the last sentence you repeat what you have already written in the first sentence. Shorten please

Lines 223-226: You repeat what you have written in the previous subchapter. Hence this part can be shortened considerably.

Lines 306-312: Here you repeat the results provided at line 300-302. The whole section starting from line 300 to 312 should be substantially simplified and streamlined. Please rewrite it.

Line 322: “Survival decreased with increasing elevation.” Could also be related to snow cover!? Clarify please and discuss if deemed important.

Lines 336-339: This sentence is not really connected to the topic of the present manuscript. This is a behavioral difference and has nothing to do with habitat selection. Moreover, you restricted your analyses to elk cows. Hence this sentence should be removed from the discussion.

Lines 343-345: This sentence can be removed as it says nothing substantial

Lines 372-374: It is not clear what you mean exactly here. Could you please further develop this idea. In other words, how would you proceed to allocate hunting permits?

Reference cited in my review

Kuijper D P J,Sahlen E,Elmhagen B,Chamaille-Jammes S,Sand H,Lone K, et al. Pawswithoutclaws? Ecological effects of largecarnivores in anthropogenic landscapes. Proceedings of the Royal Society B: Biological Sciences 2016; 283: 20161625. https://doi.org/10.1098/rspb.2016.1625 PMID: 27798302

Reviewer #2: Now that it is clear that this is not an overall elk-study, I think the title and onwards should be clearly stated as female Elk instead of just elk. This follows through the manuscript.

Line 167-172 is a justification for methods used, this is more fitting in the introduction, it also suggests that there is literature on game species about awareness of risk etc… this needs to be referenced directly after the statement.

177-180, do not mention concerns and how you feel in the materials and methods section, describe which method you choose and why, that’s it.

234 Was the modelled random effect regarding slope or intercept or both, and why did you select that way? Compare to Thurfjell 2017 where the formulation of the random effect was used to test if there was a learning effect.

255 How often were locations taken? What was the success rate?

In the discussion, I lack some hypothesis as to why female elk did not show learning, as opposed to precious studies, also why do you think they are more vulnerable at older ages? Think a bit about theese results, and try and formulate something that can be useful for further studies.

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Reviewer #1: Yes: Fridolin Zimmermann

Reviewer #2: Yes: Henrik Thurfjell

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16 Sep 2020

We have uploaded a cover letter detailing the specific edits made in response to the comments provided. We are very grateful to the editors and reviewers for their time in reviewing our study and believe that the comments provided have improved the final product greatly.

Submitted filename: Harvest Vulnerability of Elk_Resubmission R2R.docx

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27 Oct 2020

PONE-D-19-22105R2

The Influence of Habitat Use on Harvest Vulnerability of Cow Elk (Cervus canadensis)

PLOS ONE

Dear Dr. Sergeyev,

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: All comments have been addressed

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Reviewer #1: Yes

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Reviewer #1: Yes

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6. Review Comments to the Author

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Reviewer #1: Line numbers correspond to the document where the track changes are still visible

The manuscript has been considerable improved, and I have only a few minor comments

Best wishes

Fridolin Zimmermann

Line 22: change "Elk" to "female Elk"

Line 30: change "Elk" to "female Elk"

Lines 362-363: You did not study Elk activity. Please adjust the sentence accordingly

Lines 378-379: I do not see the rational given that harvest vulnerability is positively correlated with elevation. Alternatively, snow may have increased elk detectability by hunters at higher elevation and thereby increased the likelihood of mortality at higher elevation. Clarify please.

Lines 383-392: Please reformulate this section in a more concise manner.

Finally, I recommend you to acknowledge reviewers. I consider this good habit as one of the most important point of academic ethics.

**********

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Reviewer #1: Yes: Fridolin Zimmermann

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8 Nov 2020

We are grateful to the editor and reviewers for considering our manuscript. The specific edits are further clarified in the response to reviewers document. Thank you again for your time and consideration

Submitted filename: Harvest Vulnerability of Elk_Resubmission Resp2Rev.docx

Click here for additional data file.

11 Nov 2020

The Influence of Habitat Use on Harvest Vulnerability of Cow Elk (Cervus canadensis)

PONE-D-19-22105R3

Dear Dr. Sergeyev,

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13 Nov 2020

PONE-D-19-22105R3

The Influence of Habitat Use on Harvest Vulnerability of Cow Elk (Cervus canadensis)

Dear Dr. Sergeyev:

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