Biological Conservation 228 (2018) 215–223

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Biological Conservation

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Predation risk for boreal woodland caribou in human-modified landscapes: T Evidence of spatial responses independent of apparent competition ⁎ Matthew A. Mummaa, , Michael P. Gillinghama, Katherine L. Parkera, Chris J. Johnsona, Megan Wattersb,c a Ecosystem Science and Management, University of Northern , 3333 University Way, Prince George, BC V2N 4Z9, b Environment and Parks, Operations Division - Resource Management, Room 1601, Provincial Building, Box 23, 10320 - 99 Street, Grand Prairie, AB T8V 6J4, Canada c Formally of Ministry of Forests, Lands, Natural Resource Operations and Rural Development, Northeast Operations, Room 400, 10003–110th Avenue, Fort St. John, BC V1J 6M7, Canada

ARTICLE INFO ABSTRACT

Keywords: Management of wildlife often relies upon understanding mechanisms linking anthropogenic disturbance to Apparent competition population declines. The most-cited mechanism by which disturbance threatens boreal caribou (Rangifer tar- Anthropogenic linear features andus caribou) is the exacerbation of apparent competition via increases in early successional forage, and sub- Boreal forest sequent changes in the densities and distributions of other prey species and gray (Canis lupus). An al- Roads ternative mechanism is the direct alteration of via positive responses by wolves to Seismic lines anthropogenic features. We conducted a mechanistic evaluation of hypotheses explaining human-mediated in- creases in boreal caribou mortality across northeast British Columbia. We evaluated support for (i) numeric apparent competition (increased prey densities) by evaluating relationships between disturbances, moose (Alces alces) density, and caribou survival. To evaluate (ii) spatial apparent competition (altered prey distribution) and (iii) wolf spatial responses (altered wolf distribution independent of prey), we modeled the relationships be- tween disturbances and indices of caribou-moose and caribou-wolf co-occurrence and then examined predation risk for caribou as a function of co-occurrence. We did not detect any relationships between anthropogenic disturbances, moose density, and caribou survival. Although caribou-moose co-occurrence increased predation risk, we observed both positive and negative relationships between disturbances and caribou-moose co-occur- rence. In contrast, caribou-wolf co-occurrence increased predation risk and was positively correlated with an- thropogenic linear features. Contrary to other boreal caribou populations, our analyses demonstrate stronger support for the direct effects of anthropogenic linear features on caribou-wolf spatial overlap, leading togreater risk for caribou. Our research highlights the need for region-specific management actions to conserve and re- cover widely distributed species.

1. Introduction populations are declining (Hebblewhite, 2017), largely resulting from the impact of anthropogenic disturbance on interactions between car- Decreased biodiversity (Ribeiro et al., 2015) and declines in species' ibou, predators, and other prey species (Ehlers et al., 2016). Woodland abundance (Inger et al., 2015) are linked to increasing levels of an- caribou utilize a spacing-out strategy by distributing themselves as in- thropogenic disturbance. These correlations present strong evidence of dividuals or in small groups across relatively flat, resource-poor terrain the impact of an ever-increasing human footprint. Effective manage- (Bergerud and Page, 1987). Historically, woodland caribou ranges ment actions to preserve and restore wildlife populations, however, contained low densities of predators and alternative prey species, but often rely on the identification of specific mechanisms (McDonald- large-scale industrial development has increased the abundance and Madden et al., 2010) by which disturbances disrupt ecological pro- distribution of predators and prey (via the creation of early successional cesses (Martínez-Ramos et al., 2016). vegetation), thereby increasing risk for caribou (Latham et al., 2011a). The majority of woodland caribou (Rangifer tarandus caribou) The boreal forest of western Canada contains one of the largest

⁎ Corresponding author. E-mail addresses: [email protected] (M.A. Mumma), [email protected] (M.P. Gillingham), [email protected] (K.L. Parker), [email protected] (C.J. Johnson), [email protected] (M. Watters). https://doi.org/10.1016/j.biocon.2018.09.015 Received 16 May 2018; Received in revised form 27 August 2018; Accepted 8 September 2018 0006-3207/ © 2018 Elsevier Ltd. All rights reserved. M.A. Mumma et al. Biological Conservation 228 (2018) 215–223 reserves of fossil fuels in the world (United States Energy Information of statistical analyses, we provide managers with an assessment of po- Administration, 2015). Increased demand, along with new technolo- tential mechanisms leading to caribou population declines in northeast gies, make the extraction of fossil fuels in the boreal a priority for the BC and demonstrate the utility of a mechanistic approach to facilitate global fossil fuel industry (Giacchetta et al., 2015). Oil and natural gas informed decision-making. extraction has led to extensive changes to the boreal landscape (Allred et al., 2015), with potentially devastating consequences for the boreal 2. Methods population of woodland caribou (Hebblewhite, 2017). The exacerbation of apparent competition is theorized as the pri- 2.1. Boreal caribou mary mechanism by which anthropogenic disturbances limit the dis- tribution and abundance of boreal caribou (Festa-Bianchet et al., 2011). Boreal caribou across Canada are listed as Threatened (Environment Apparent competition is the indirect, negative effect one species can Canada, 2012). In 2012, all five populations (Calendar, Chinchaga, Fort have on another (or both species can have on each other) as mediated Nelson, Maxhamish, and Snake-Sahtaneh) in BC (Fig. 1) were assessed through a shared predator (Holt, 1977). Anthropogenic landscape fea- as Not Self Sustaining, with a minimum human footprint of 58% across tures resulting from fossil fuel extraction (i.e., well pads, roads, pipe- those ranges (Environment Canada, 2012). Boreal caribou occur at low lines, and seismic lines), along with forestry activities (i.e., cutblocks densities, thus abundance estimates were expensive and lack certainty, and roads), have increased early successional (seral) habitat in the but a declining trend is apparent. Across northeast BC, populations western boreal, thus providing ample forage for prey species, such as declined from ~1 512 individuals in 2004 to ~1 279 in 2010. In 2016, moose (Alces alces americanus) and white-tailed (Odocoileus virgi- there was a minimum estimate of 728 individuals. Wolf predation was nianus), and thereby increasing total prey biomass (Latham et al., the primary cause of caribou mortality (Culling and Cichowski, 2017). 2011b). Subsequent increases in gray wolf (Canis lupus) densities are thought to increase wolf encounters with boreal caribou and decrease 2.2. Study site, capture, and seasons caribou survival. Although the impact of increasing wolf and prey densities on boreal caribou (hereafter numeric apparent competition) is Our study site (~69 000 km2) consisted of undulating terrain (ele- established (Latham et al., 2011b), disturbance-related changes in prey vations ranging from ~214 to 1 084 m) with vast peatland complexes, and predator behaviors and distributions might also influence caribou deciduous and mixed-wood uplands, and riparian areas (Delong et al., survival (Whittington et al., 2011; Peters et al., 2013). 1991). The northern continental climate was characterized by cold Anthropogenic disturbance might increase caribou-wolf encounters winters and short summers (Environment Canada, 2016). Caribou and and decrease caribou survival by indirectly or directly altering the moose were the most prominent large species, but tend to distribution of wolves. The distribution of apparent competitors, such occupy different habitats. Generally, caribou select for peatlands and as moose, and their overlap with boreal caribou might be altered avoid uplands, while moose select uplands and avoid peatlands through the creation of early seral habitat via anthropogenic dis- (Mumma and Gillingham, 2017). Both species utilize riparian areas turbances. Spatial overlap between caribou and wolves would be in- during certain seasons. Moose density across the study area was rela- creased indirectly as wolves pursue other prey species now frequenting tively low, ranging from 0.018 to 0.246 moose/km2 (Thiessen, 2010; caribou habitats. Hereafter, we refer to this mechanism as spatial ap- McNay et al., 2013). In addition to wolves, common large predators parent competition, representing the change in caribou-wolf dynamics included black bears (Ursus americanus) and grizzly bears (Ursus arctos). as a result of changes in the distribution of other prey species (Holt and Wolf densities were only available for a small portion of the study site, Kotler, 1987). Alternatively, anthropogenic disturbance might directly thus preventing their use in analyses and ranged from 7 to 15.6 wolves/ lead to increases in caribou-wolf spatial overlap as a result of positive 1 000 km2 (Serrouya et al., 2016). Densities of bears were unknown. spatial responses by wolves to roads and seismic lines (DeCesare, 2012) Resource roads (0.79 km/km2) and seismic lines (1.84 km/km2) were (cleared, < 2–10 m-wide paths created during fossil fuel exploration). widespread as a result of natural gas development, which also results in Previous research demonstrated that wolves move faster when traveling well pads and pipelines (Fig. 1). Logging contributed additional roads on anthropogenic linear features (Dickie et al., 2017b) and are more and cutblocks (~2% of study site cut within last 40 y) primarily in the likely to use caribou habitats when linear features are present (DeMars western portion of the study site. Most roads were seasonal or tem- and Boutin, 2018). Caribou are also more likely to encounter wolves porarily used during resource extraction activities, but without active near linear features (Mumma et al., 2017). restoration, recovery of unused roads and seismic lines is slow in the Our objectives were to examine the mechanisms by which anthro- nutrient-poor boreal landscape (Lee and Boutin, 2006) and might result pogenic disturbance influences apparent competition and predation by in a different successional trajectory (Finnegan et al., 2018). Fire is a wolves on boreal caribou in northeast British Columbia (BC), Canada, in keystone process in boreal ecosystems (Weber and Flannigan, 1997), order to guide future management efforts. We evaluated support for but the proportion of burns (< 3% of study site within last 40 y) in three hypotheses that related anthropogenic disturbance to the spatial northeast BC was small. co-occurrence of caribou, moose, and wolves and mortality for caribou. Female caribou were captured from all five ranges in northeast BC Following the (i) numeric apparent competition (increased prey den- each winter from December 2012 to March 2016 and affixed with sity) hypothesis, the proportion of cutblocks and burns are positively several models of radio and GPS collars using aerial net-gunning (BC correlated with moose density, and moose density is negatively corre- Wildlife Permits FJ12-76949, FJ12-80090, and FJ12-83091). Wolves lated with caribou survival. Linear features are unimportant in regards were captured and affixed with GPS-telemetry collars over the same to the numeric apparent competition hypothesis because of their small time period (BC Wildlife Permit FJ14-156487). Male and female moose contribution of early seral habitat (< 1% of study site; Pattison et al., were fitted with GPS-telemetry collars in March 2015 and December 2016). The (ii) spatial apparent competition (altered prey distribution) 2016 (BC Wildlife Permit FJ14-152798). All collared individuals were hypothesis predicts that cutblocks, burns, roads, and seismic lines are monitored regularly, and when collared caribou and moose exhibited positively associated with moose-caribou overlap and that moose-car- little or no movement, site investigations were conducted and cause of ibou overlap is associated with higher risk of mortality for caribou (i.e., death determined (i.e., predation, starvation, disease, harvest, etc.) predation risk). Lastly, our (iii) wolf spatial response hypothesis pre- when possible. Locations were investigated for evidence of a chase or dicts that cutblocks, burns, roads, and seismic lines are positively re- struggle and predator sign (scat, hair, predator beds, etc.). The state of lated to caribou-wolf overlap (independent of moose) and that caribou- the carcass was also considered, and when available, tissues were col- wolf overlap is related to higher predation risk for caribou. By explicitly lected to assess caribou health (Culling and Culling, 2017). testing these hypotheses using data from multiple sources and a variety Animal behaviors vary seasonally with changes in food availability

216 M.A. Mumma et al. Biological Conservation 228 (2018) 215–223

Fig. 1. Boreal caribou ranges and moose density survey areas in northeast British Columbia, Canada (A) and inset maps displaying the locations of all roads (B) and seismic lines (C) within the study site. Gray polygons represent areas with high density seismic (C).

(e.g., growing versus non-growing seasons, Gillingham and Parker, Therneau, 2018) to evaluate the relationship between caribou survival 2008) or vulnerability (e.g., poor body condition or presence of young, and moose density (α = 0.05). Cox proportional hazards models relate Mumma et al., 2017). Considering seasonal behaviors and environ- the time until mortality (hazard) to individual covariates. Although mental conditions for each species, and recognizing potential changes there are no assumptions regarding the shape of the baseline hazard in vulnerability to predation for caribou and moose, we defined four function, explicit within Cox models is the assumption that covariates seasons (i.e., calving, late summer, early winter, and late winter). act upon (increase or decrease) the baseline hazard function in a pro- Further details are located in Appendix A. portional manner. We used a recurrent time of origin (June 1) approach (Fieberg and DelGiudice, 2009) and accounted for individuals con- 2.3. Numeric apparent competition tributing multiple years by estimating robust ‘sandwich’ standard errors (Therneau and Grambsch, 2000). To account for spatial and temporal To assess support for the (i) numeric apparent competition hy- heterogeneity, we included range and year as random intercepts. We pothesis, we first used a linear model (Gaussian family, identity link)to evaluated the assumption of proportionality using metrics based on 2 regress previously estimated moose densities against the prevalence of Schoenfeld residuals (Fox, 2002) and estimated a pseudo R (Cox and several anthropogenic features. Distance sampling (Buckland et al., Snell, 1989) corrected for censored data (O’Quigley et al., 2005). All 2005) was used to estimate moose densities for 13 survey areas (Fig. 1) analyses were conducted in program R (R Core Team, 2015). in northeast BC (Thiessen, 2010; McNay et al., 2013). Distance sam- pling estimates animal densities via a detection function that is ap- 2.4. Spatial apparent competition and wolf spatial responses proximated using the distances between transects and animal sightings. Across each survey area, transects were flown via helicopter (3 or 6km We applied the same framework to evaluate the spatial apparent apart) at a height of ~100 m above the ground and a speed between competition (ii) and wolf spatial response (iii) hypotheses. We used 75–120 km/hr. We anticipated that moose densities would be largely resource selection functions (RSF) to model the spatial responses of driven by vegetation, and therefore included the proportions of a ve- caribou, moose, and wolves to anthropogenic features. We then used getation class selected (deciduous swamp) and a vegetation class the resource selection functions of each species to predict indices of avoided (treed bog) by moose in this system (Mumma and Gillingham, caribou-moose co-occurrence and caribou-wolf co-occurrence (see de- 2017). We estimated the proportions of cutblocks and burns (< 40 y scription of eq. (1) below). Next, we examined correlations between old) and the densities (km/km2) of roads and seismic lines for each anthropogenic landscape features and co-occurrence, and co-occur- survey area. We built models including the proportions of deciduous rence and the risk of mortality for caribou (i.e., predation risk). swamp and treed bog and our disturbance covariates and selected the Resource selection functions were modeled using mixed-effects lo- most parsimonious model using Akaike’s information criteria (Akaike, gistic regression (Johnson et al., 2006), including random intercepts for

1998) for small sample sizes (AICc, Burnham and Anderson, 2002; individuals (Bates et al., 2015). Available locations for each collared Bartón, 2015). Additional details regarding vegetation classes and dis- caribou and moose were determined by buffering each used location by turbance layers are located in Appendix A. that individual’s 90th centile of movement distances between con- We then used Cox proportional hazards models (Cox, 1972; secutive locations for the corresponding season and sampling five

217 M.A. Mumma et al. Biological Conservation 228 (2018) 215–223 random locations from within that buffer (Gustine et al., 2006). We To evaluate the relationship between co-occurrence and the risk of built models separately for male and female moose anticipating dif- mortality for caribou, we contrasted locations with a known caribou ferences in selection between sexes (Eldegard et al., 2012). The 80th mortality attributed to wolves (n = 69) with used locations of collared centile of movement distances were used for wolves to limit buffer size caribou (n = 140 667). Because bias can occur when a large disparity because of their propensity for occasional long-distance movements. exists between events (1; caribou mortality locations) and non-events When modeling resource selection, we selected a suite of landscape (0; caribou locations), we modelled this relationship for each season covariates theorized to influence the distribution of collared caribou, using logistic regression with a bias correction for rare events (Imai moose, and wolves. We included vegetation class layers (see Vegetation et al., 2007). In contrast to the previous analyses, we wanted to tease classes and disturbance layers in Appendix A) as categorical covariates apart the influence of caribou use on co-occurrence from the effects of using deviation coding (Johnson et al., 2004), excluding the ‘other’ male moose, female moose, and wolf use. We, therefore, used the re- vegetation class. New (~0–15 y) and old (~16–40 y) cutblock and burn lative probability of use for male moose, female moose, and wolves as classes were also included as categorical covariates. Continuous cov- the independent variables in our models. We interpreted covariate ariates included elevation (m), distance to water (km), topographic significance using P-values (α = 0.05) and reported pseudo R2 values slope (degrees), vegetation class richness, road density (km/km2), and (McFadden, 1974). All analyses were conducted using program R (R seismic line density (km/km2). Vegetation class richness and road and Core Team, 2015). seismic line densities were estimated at 100-, 500-, and 1 000-m radii for each used and available location. We used those landscape covari- ates to construct competing models and selected the most parsimonious 3. Results model for each species by season using AICc. We evaluated multi- collinearity for our best supported models using the variance inflation 3.1. Numeric apparent competition hypotheses factor (VIF < 2) (package rms; Harrell, 2018; Graham, 2003). We verified model fit through k-fold cross-validation (Boyce et al., 2002) Our most parsimonious model for moose density included the pro- using 10 repetitions of 5-fold cross-validation with 10 bins of equal size portions of deciduous swamp, treed bog, and burns (Table A.1). The (Basille, 2015). Additional details located in Appendix A. model explained ~42% of the variation (Table A.2) in moose density Ideally, true encounters between caribou, moose, and wolves would (Fig. 1). We observed a positive relationship for moose density with be identified to understand the relationship between disturbances, deciduous swamps and burns and a negative relationship with treed spatial overlap, and predation risk. Despite a high amount of spatial and bogs (Table A.2). We did not find evidence of a positive relationship temporal overlap between collar locations (Fig. A.1), identifying po- between the proportion of cutblocks and moose density (Table A.1). tential encounters between individuals was limited and prevented We observed 92 collared caribou mortalities (69 wolf, 15 un- analyses across our four seasons (Mumma et al., 2017). Theoretically, determined, and 8 from other causes including starvation, disease and the probability of co-occurrence should be proportional to the joint harvest) during the course of the study. We did not detect a significant probability of use for two species assuming each species behaves in- relationship between caribou survival and moose density (Table A.3). dependently (Minta, 1992). The assumption of independence might be The model, which included random intercepts for range and year, ex- unrealistic for two highly competitive species or for a predator and plained ~35% of the variation in caribou survival (Table A.3). prey, with the exception of a secondary prey species in a two prey, one predator system (Hebblewhite et al., 2005). In this system, differences in space-use and habitat ecology (Mumma and Gillingham, 2017) 3.2. Species responses to disturbances suggest that caribou and moose are not highly competitive, and that caribou are a secondary prey for wolves. We recognize, however, that We used GPS locations from 120 collared caribou, 60 collared wolves can influence caribou space-use (Latombe et al., 2014), but moose (18 males and 42 females), and 29 collared wolves to fit species- assumed that the joint probability of caribou and wolf use would pro- specific RSFs for each season. The saturated model, which included our vide an index of caribou-wolf co-occurrence (i.e., spatial overlap). categorical vegetation classes, distance to water, vegetation class rich- We used our most parsimonious RSF models to estimate the relative ness, slope, elevation, and road and seismic density was best supported probability of use for caribou, male moose, female moose, and wolves for all species across all seasons (Tables A.4–A.7), except for male at each collared caribou location. We estimated our indices of caribou- moose in late summer (Table A.5). male moose, caribou-female moose, and caribou-wolf co-occurrence (C) Caribou consistently avoided new and old cutblocks and selected by multiplying the relative probability of use for caribou (RSFc) by the new and old burns (Tables 1 and A.8). Caribou avoided higher densities relative probabilities of use (RSFother) for male moose, female moose, of roads and seismic lines in all seasons, apart from seismic lines in and wolves, respectively (Eq. (1)). early winter (Tables 1 and A.8). Male moose selected cutblocks (new and old) and burns (new and old) during calving and late summer, and C= RSFc RSF other (1) in winter selected new cutblocks and new burns (new seral), but Although RSFs provided us with an understanding of individual avoided old cutblocks and old burns (old seral; Tables 1 and A.9). Male species responses to disturbances, we also wanted to explore the effect moose demonstrated variable responses to roads and seismic lines. of disturbances on species co-occurrence. We used beta regression to Roads were selected during calving and avoided during early and late examine the relationship between co-occurrence and cutblocks (old and winter, whereas seismic lines were avoided during calving and selected new), burns (old and new), road density, and seismic line density. Beta in both winter seasons (Tables 1 and A.9). Female moose generally regression assumes a response variable restricted to the interval (0, 1), selected for new cutblocks, demonstrated variable responses to old matching the possible distribution of our co-occurrence indices. cutblocks, and avoided new and old burns (all burns; Tables 1 and Additional details on beta regression are located in Appendix A. We A.10). Females generally avoided both roads and seismic lines, apart recognized that factors beyond disturbances would influence co-oc- from seismic in late summer (Tables 1 and A.10). Wolves generally currence, but our goal was to quantify specific relationships between avoided burns and selected cutblocks (Tables 1 and A.11). Wolves also disturbances and co-occurrence and not to model all variables poten- demonstrated consistent selection for areas with higher road and tially influencing co-occurrence. We, therefore, drew inference byin- seismic line densities (Tables 1 and A.11). The most parsimonious terpreting covariate significance using P-values (α = 0.05). We also models for each species and season were all highly predictive (all 2 reported pseudo R values (Ferrari and Criberi-Neto, 2004) for all rs > 0.92, Boyce et al., 2002). models.

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Table 1 Direction ( ± ) of β coefficients for disturbances in the most parsimonious resource selection functions for boreal caribou, gray wolves, and male (M.) andfemale(F.) moose during calving, late summer, early winter, and late winter in northeast British Columbia, Canada. Missing direction indicates covariate was not included in the most parsimonious model.

Covariate Calving Late summer Early winter Late winter

Caribou M. moose F. moose Wolf Caribou M. moose F. moose Wolf Caribou M. moose F. moose Wolf Caribou M. moose F. moose Wolf

New cutblock − + + − − + + + − + + + − + + + Old cutblock − + + + − + − + − − + − − − − + New burn + + − − + + + − + + − − + + − − Old burn + + − − + + − − + − − − + − − + Road density − + − + − − + − − − + − − − + (km/km2) Seismic density − − − + − + + + + − + − + − + (km/km2)

3.3. Spatial apparent competition hypotheses summer (Table 2). There was an insufficient number of mortalities (n = 4) to run models for early winter. Pseudo R2 values were low Higher caribou-male moose co-occurrence appeared to be primarily (< 0.01 to 0.02). driven by increases in the relative probability of use of male moose across all seasons, although smaller increases in relative probability of 3.4. Wolf spatial response hypothesis use by caribou were evident in late summer, early winter, and late winter (Fig. A.2A–D). We observed significant relationships between Higher caribou-wolf co-occurrence values appeared to be primarily disturbance and the relative probability of caribou-male moose co-oc- driven by increases in the relative probability of use of wolves across all currence in all seasons (Fig. 2, Table A.12). A comparison between the seasons (Fig. A.4A–D). The lower y-intercept in comparison to un- y-intercepts (height of the curves) of undisturbed locations versus dis- disturbed locations suggested that old cutblocks and burns (new and turbed locations revealed that old cutblocks and new and old burns old) were negatively associated with caribou-wolf co-occurrence during were positively related to caribou-male moose co-occurrence during calving (Fig. 4A and 4B, Table A.14). In late summer, old cutblocks also calving (Fig. 2A and 2B) and late summer (Fig. 2C and 2D). In contrast, were negatively related to co-occurrence, in contrast to new and old cutblocks (new and old) and old burns were negatively correlated with burns that were positively related (Fig. 4C and 4D). In early and late caribou-male moose co-occurrence in early (Fig. 2E and 2F) and late winter, cutblocks (new and old) and new burns were negatively asso- winter (Fig. 2G and 2H). New burns were positively correlated in early ciated with co-occurrence, whereas old burns demonstrated a positive winter (Fig. 2E and 2F) and negatively correlated in late winter (Fig. 2G association (Fig. 4E–H). The slope of the curves suggested positive re- and 2H). The slope of the curves demonstrated that road and seismic lationships between road density and caribou-wolf co-occurrence across line densities were negatively associated with caribou-male moose co- all seasons (Fig. 4A, 4C, 4E, and 4G). Seismic lines were negatively occurrence during calving (Fig. 2A and 2B), but positively associated related to co-occurrence during calving and late winter (Fig. 4B and with co-occurrence during late summer (Fig. 2C and 2D) and early 4H), but positively related to co-occurrence during late summer and winter (Fig. 2E and 2F). In late winter, roads were positively related early winter (Fig. 4D and 4F). Pseudo R2 values ranged from 0.01 to and seismic lines were negatively related to co-occurrence (Fig. 2G and 0.18 (Table S16). 2H). Despite finding significant relationships between relative caribou- Caribou-wolf co-occurrence had a significant, positive relationship male moose co-occurrence and disturbance, the amount of variance (α = 0.05) with the risk of mortality for caribou during calving, late 2 explained by beta regression models was low (pseudo R = 0.07 to summer, and late winter (Table 2). Pseudo R2 values were low (< 0.01 0.10, Table A.12). to 0.01). Higher caribou-female moose co-occurrence values appeared to be driven by increases in the relative probability of use for both species 4. Discussion across all seasons (Fig. A.3A–D). We also detected significant relation- ships, across all seasons, between disturbance and the relative prob- We utilized multiple data sources and a variety of statistical ana- ability of caribou-female moose co-occurrence (Fig. 3, Table A.13). lyses to conduct a mechanistic evaluation of three potential hypotheses During calving, the lower y-intercept for new cutblocks and new and explaining human-mediated increases in boreal caribou mortality old burns in comparison to undisturbed locations indicated a negative across northeast BC. The creation of early seral habitat via anthro- correlation with co-occurrence, while the higher y-intercept of old pogenic disturbances and fire, and subsequent increases in moose and cutblocks indicated a positive correlation with co-occurrence (Fig. 3A wolf densities, is the prevailing hypothesis for the declines of boreal and 3B). In late summer, new and old cutblocks were negatively related caribou (Hebblewhite, 2017). Our analyses, however, demonstrated to co-occurrence, but burns (new and old) were positively related stronger support for the wolf spatial response hypothesis. We did not (Fig. 3C and 3D). During early (Fig. 3E and 3F) and late winter (Fig. 3G detect a relationship between anthropogenic disturbances, moose den- and 3H), both cutblocks (new and old) and burns (new and old) were sity, and caribou survival (numeric apparent competition) (Table A.1 negatively related to co-occurrence. Roads were negatively correlated and A.3). Although caribou-moose co-occurrence increased the risk of to caribou-female moose co-occurrence in all seasons (Fig. 3). Seismic mortality (i.e., predation risk) for caribou (spatial apparent competi- lines demonstrated a negative relationship with co-occurrence during tion) (Table 2), the analyses suggested that responses by moose to calving and early and late winter (Fig. 3B, 3F, and 3H), but a positive disturbances were just as likely to decrease caribou-moose co-occur- 2 relationship in late summer (Fig. 3D). Pseudo R values ranged between rence as increase it (Table 1, Figs. 2 and 3). In contrast, wolves con- 0.11 to 0.52 (Table A.13). sistently selected for roads and seismic lines (Table 1), and generally, Caribou-male moose co-occurrence was positively correlated roads and seismic lines were positively related to caribou-wolf co-oc- (α = 0.05) with the risk of mortality for caribou during calving and late currence (Fig. 4). Further, caribou-wolf co-occurrence was positively summer (Table 2). Caribou-female moose co-occurrence was positively related to predation risk for caribou (Table 2). This suggests that an- correlated (α = 0.05) with the risk of mortality for caribou during late thropogenic features, such as roads and seismic lines, have increased

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Fig. 2. Relative probability of boreal caribou and male moose co-occurrence as Fig. 3. Relative probability of boreal caribou and female moose co-occurrence a function of new and old burns, new and old cutblocks, and road and seismic as a function of new and old burns, new and old cutblocks, and road and seismic line densities across seasons in northeast British Columbia, Canada. The influ- line densities across seasons in northeast British Columbia, Canada. The influ- ence (magnitude and directionality) of new and old burns and new and old ence (magnitude and directionality) of new and old burns and new and old cutblocks can be inferred by comparing the y-intercepts (height of the curves) cutblocks can be inferred by comparing the y-intercepts (height of the curves) of co-occurrence in disturbed (burns and cutblocks) versus undisturbed loca- of co-occurrence in disturbed (burns and cutblocks) versus undisturbed loca- tions. The influence (magnitude and directionality) of roads and seismic lines tions. The influence (magnitude and directionality) of roads and seismic lines can be inferred by the slope of the plotted curves. can be inferred by the slope of the plotted curves. caribou mortality by changing the distribution of wolves and increasing exacerbation of a ‘landscape of fear’ (Laundré et al., 2001), may caribou-wolf spatial overlap. experience decreased forage availability, along with decreased foraging Despite caribou avoidance of anthropogenic linear features efficiency (increased vigilance), thus reducing body condition andin- (Table 1), positive relationships between linear features and caribou- creasing the vulnerability of adults and their offspring (Creel et al., wolf co-occurrence (Fig. 4) suggest that caribou behavioral responses 2009). are insufficient to compensate for the strong selection for linear features The highly variable relationships between disturbances and caribou- by wolves and the corresponding higher risk caused by roads and moose co-occurrence suggest that the potential influence of dis- seismic lines. This is consistent with other studies demonstrating se- turbances on spatial apparent competition might be both positive and lection of anthropogenic linear features by wolves (Dickie et al., 2017b) negative. In general, caribou-male moose co-occurrence was negatively and higher rates of caribou-wolf encounters near linear features correlated with roads and seismic lines during birthing and late winter (Mumma et al., 2017). Risk for caribou also might be compounded by and positively correlated during late summer and early winter (Fig. 4). theorized increases in wolf search efficiency (Dickie et al., 2017b). Caribou-female moose co-occurrence was negatively related to roads Further, the avoidance of linear features by caribou might result in a and seismic lines with the exception of seismic lines in late summer loss of functional habitat (Latham et al., 2011a). Through the (Fig. 3). Although cutblocks and burns tended to be positively related to

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Table 2 Number of mortalities, β coefficients, standard errors (SE), test-statistics (z- value), and P-values (P-val) for seasonal logistic regression models with a bias correction for rare events evaluating wolf predation risk for boreal caribou as a function of the relative probability of selection of male (M.) moose, female (F.) moose, or wolves in northeast British Columbia, Canada. β coefficients for the intercept of each model are not shown.

Season Model Mortalities β SE z-val P-val

Birthing M. moose 14 11.09 4.03 2.76 < 0.01 F. moose 14 0.25 3.29 0.08 0.94 Wolf 14 18.83 9.61 1.96 0.05 Late summer M. moose 14 2.90 1.14 2.53 0.01 F. moose 14 4.59 1.62 2.83 < 0.01 Wolf 14 11.81 3.57 3.31 < 0.001 Late winter M. moose 37 1.44 0.81 1.78 0.08 F. moose 37 1.40 0.77 1.82 0.07 Wolf 37 7.28 1.79 4.07 < 0.0001 co-occurrence during calving and late summer and negatively related to co-occurrence during early and late winter (Fig. 2 and 3), the biological significance of these effects is likely limited, given the small proportion of cut and burned areas across the northeast BC landscape. Collectively, these results do not support a strong link between disturbances, car- ibou-moose spatial overlap, and predation risk for caribou. Although we did not detect a clear relationship between anthro- pogenic disturbance and changes in moose distribution (Figs. 2 and 3) and density (Table A.1), we did find evidence of apparent competition. Predation risk for caribou was increased in areas with a higher prob- ability of being used by male and female moose in some seasons (Table 2). It important to recognize that apparent competition is a naturally occurring process that can influence species persistence (DeCesare et al., 2010) and an important driver of woodland caribou population dynamics (Latham et al., 2011b). The low densities, how- ever, of moose (0.018–0.246 moose/km2) in northeast BC combined with our inability to link moose densities to anthropogenic disturbances suggest that current and historical moose densities might be similar and that the influence of apparent competition may fall within historical norms. Our analysis did not detect a relationship between moose density and anthropogenic disturbances (Table A.1), although we recognize that this analysis was conducted using a small number of observations (n = 13). We did, however, identify a positive relationship between moose density and the proportion of the landscape comprised of burns (Table A.2). Although the proportion of burns (< 3%) is relatively Fig. 4. Relative probability of boreal caribou and gray wolf co-occurrence as a small in northeast BC, burn frequency, size, and severity are all pre- function of new and old burns, new and old cutblocks, and road and seismic line dicted to increase as a result of climate change (Weber and Flannigan, densities across seasons in northeast British Columbia, Canada. The influence 1997). In the future, a higher proportion of burns might lead to higher (magnitude and directionality) of new and old burns and new and old cutblocks moose densities, thus exacerbating apparent competition with caribou, can be inferred by comparing the y-intercepts (height of the curves) of co-oc- as could increases in the number of cutblocks. currence in disturbed (burns and cutblocks) versus undisturbed locations. The Indeed, the disparity between our findings (wolf spatial response influence (magnitude and directionality) of roads and seismic lines canbein- hypothesis) and those observed in other study areas (numeric apparent ferred by the slope of the plotted curves. competition) are likely, in part, attributed to differences in the pro- portion of cutblocks. In northeast BC, ~2% of the landscape has been is considered the primary threat to boreal caribou (Festa-Bianchet et al., logged within the last 40 yrs. This differs considerably in areas within 2011), our analyses demonstrated stronger support for the wolf spatial and adjacent to caribou ranges in Quebec (~48% cut within last 50 y; response hypothesis. We suggest that the altered distribution of wolves St-Laurent and Dussault, 2012) and certain areas in containing via their use of roads and seismic lines increases caribou-wolf spatial higher proportions of cutblocks and higher moose densities (Avgar overlap and predation risk for caribou in northeast BC. et al., 2015). Although further research will be necessary to substantiate our findings and illuminate mechanisms of boreal caribou decline inother 5. Conclusion areas, our results suggest that range-specific management actions might be necessary to facilitate the recovery of boreal caribou populations Despite the release of a Canadian Federal recovery strategy in 2012 that face unique regional challenges. We recommend limiting current (Environment Canada, 2012), many boreal caribou populations con- and future disturbances in northeast BC. Minimizing development tinue to decline (Environment and Climate Change Canada, 2017) and alone, however, will not address an extensive network of linear features economic pressures continue to outweigh conservation concerns that is the legacy of 30 years of oil and natural gas development. (Hebblewhite, 2017). Although human-mediated apparent competition Restoration activities that reduce the vagility and use of existing roads

221 M.A. Mumma et al. Biological Conservation 228 (2018) 215–223 and seismic lines (as movement routes for wolves) should also be behaviour of woodland caribou based on a cognitive movement model. J. Anim. Ecol. considered (Dickie et al., 2017a). Directly reducing moose density, as 84, 1059–1070. Bartón, K., 2015. MuMIn: Multi-model Inference, R Package Version 1.15.1. advocated for mountain caribou in British Columbia (Serrouya et al., Basille, M., 2015. hab, R Package Version 1.20.4. 2017), may have a limited benefit for boreal caribou recovery in Bates, D., Maechler, M., Bolker, B., Walker, S., 2015. Fitting linear mixed-effects models northeast BC where moose densities are low. In Alberta, wolf removal using lme4. J. Stat. Softw. 67, 1–48. Bergerud, A.T., Page, R.E., 1987. Displacement and dispersion of parturient caribou at was initiated as a means to slow the decline of the Little Smoky caribou calving as antipredator tactics. Can. J. 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Caribou and wolf telemetry data are currently accessible and moose Culling, D.E., Culling, B.A., 2017. BC boreal caribou implementation plan: year V (2016–2017), field activities and progress report. In: British Columbia Oil andGas data will be accessible through the BC Oil and Gas Research and Research and Innovation Society, . http://www.bcogris.ca/sites/default/files/bcip- Innovation Society (http://www.bcogris.ca/boreal-caribou/projects/ 2016-07-late-winter-2017-recruitment-survey-report-final-diversified-sept17.pdf, active). Accessed date: 1 August 2018. DeCesare, N.J., 2012. Separating spatial search and efficiency rates as components of predation risk. Proc. R. Soc. Lond. B 279, 4626–4633. Conflict of interest declaration DeCesare, N.J., Hebblewhite, M., Robinson, H.S., Musiani, M., 2010. Endangered ap- parently: the role of apparent competition in endangered species conservation. Anim. The work is original research conducted by the authors. All authors Conserv. 13, 353–362. Delong, C., Annas, R.M., Stewart, A.C., 1991. In: Meidinger, D., Pojar, J. (Eds.), Boreal agree with the contents of the research and its submission to Biological White and Black Spruce Zone, Ecosystems of British Columbia. Special Report Series Conservation. No part of this research has been published elsewhere 6 Ministry of Forests, Victoria, British Columbia, pp. 237–250. and is solely being submitted to Biological Conservation. All sources of DeMars, C.A., Boutin, S., 2018. Nowhere to hide: Effects of linear features on predator- prey dynamics in a large system. J. Anim. Ecol. 87, 274–284. funding are declared in the manuscript and none of the authors have Dickie, M., Serrouya, R., DeMars, C., Cranston, J., Boutin, S., 2017a. Evaluating func- received any direct financial benefit as a result of this manuscript. tional recovery of habitat for threatened woodland caribou. Ecosphere 8, e01936. 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