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Intensity of space use reveals conditional sex‐specific effects of prey and conspecific density on home range size

Intensity of space use reveals conditional sex‐specific effects of prey and conspecific density... Capreolus capreolus, carnivore, kernel home Home range (HR) size variation is often linked to resource abundance, with range estimator, ranging behavior, sex differences expected to relate to sex-specific fitness consequences. However, spatiotemporal variation, utilization distribution. studies generally fail to disentangle the effects of the two main drivers of HR size variation, food and conspecific density, and rarely consider how their rela- Correspondence tive influence change over spatiotemporal scales. We used location data from Malin Aronsson, Department of Ecology, 77 Eurasian lynx (Lynx lynx) from a 16-year Scandinavian study to examine Swedish University of Agricultural Sciences, HR sizes variation relative to prey and conspecific density at different spa- Grimso€ Wildlife Research Station, SE-730 91 tiotemporal scales. By varying the isopleth parameter (intensity of use) defining Riddarhyttan, Sweden. the HR, we show that sex-specific effects were conditional on the spatial scale Tel: +46 581 697312; E-mail: malin.aronsson@slu.se considered. Males had larger HRs than females in all seasons. Females’ total HR size declined as prey and conspecific density increased, whereas males’ total HR Funding Information was only affected by conspecific density. However, as the intensity of use within Funding is from the Swedish Environmental the HR increased (from 90% to 50% isopleth), the relationship between prey Protection Agency, Norwegian Environment density and area showed opposing patterns for females and males; for females, Directorate, the Swedish Research Council the prey density effect was reduced, while for males, prey became increasingly Formas, the Research Council of Norway, the important. Thus, prey influenced the size of key regions within male HRs, Norwegian Institute for Nature Research, the Swedish Association for Hunting and Wildlife despite total HR size being independent of prey density. Males reduced their Management, WWF-Sweden and “Marie- HR size during the mating season, likely to remain close to individual females Claire Cronstedts” foundations, the County in estrous. Females reduced their HR size postreproduction probably because of Governor’s Office for Hedmark, Oslo and movement constrains imposed by dependent young. Our findings highlight the Akershus, Østfold, Oppland, Buskerud, importance of simultaneously considering resources and intraspecific interac- Vestfold, and Telemark Counties, the tions as HR size determinants. We show that sex-specific demands influence Carnivore Management Boards in regions 2, the importance of prey and conspecific density on space use at different spa- 3, and 4 and 8, the municipalities of Trysil, Fla, Gol, Hjartdal, Nes, Nore og Uvdal, Rollag, tiotemporal scales. Thus, unless a gradient of space use intensity is examined, Sauherad, Tinn, and Al. factors not related to total HR size might be disregarded despite their impor- tance in determining size of key regions within the HR. Received: 25 January 2016; Accepted: 8 February 2016 Ecology and Evolution 2016; 6(9): 2957– doi: 10.1002/ece3.2032 of its central role in influencing population dynamics and Introduction distribution, home range (HR) size has been extensively Access to critical resources is an essential determinant of studied. Differences in body size, diet, social organization, individual fitness, with spacing behavior being a key and mating system explain general HR size variation factor regulating this access (Morales et al. 2010). Because between species (McNab 1963; Clutton-Brock and Harvey ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. 2957 This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Determinants of Lynx Home Range Size M. Aronsson et al. 1978; Kelt and Van Vuren 2001; Carbone et al. 2011), resources, and HR use should show temporal variation while resource distribution, abundance, and predictability associated with seasonal breeding (Gittleman and Thomp- together with density of competing conspecifics are son 1988). important drivers of HR size variation within species Multiscale approaches have recently been used to (Maher and Lott 2000; McLoughlin and Ferguson 2000; study spatiotemporal effects of food abundance and abi- Jetz et al. 2004; Mitchell and Powell 2004; Lopez-Bao otic factors on HR determination (Borger et al. 2006a; et al. 2014). Lopez-Bao  et al. 2010; van Beest et al. 2011; Campioni Because resource distribution and conspecific interac- et al. 2013; Morellet et al. 2013; Campos et al. 2014; tions are not uniform, the relative importance of Godsall et al. 2014). However, few studies of free-ran- resources and conspecifics in relation to HR variation ging animals have been able to simultaneously assess the should change both in space and time (Borger € et al. effect of food and conspecific density on individual 2006a; van Beest et al. 2011; Campos et al. 2014). As HRs spacing behavior, as these two factors are often strongly are often defined in terms of some minimum intensity of correlated in natural systems (Benson et al. 2006). Fur- space use by the focal animal (Kie et al. 2010), critical thermore, sex-specific space use patterns are expected to insights can be gained by examining how the effect of emerge when the fitness of one sex is largely determined range size determinants changes as intensity of space use by resources for offspring provisioning, while the other changes within the HR (Fig. 1). For example, factors that is largely regulated by mating opportunities (Emlen and are important for determining total HR may become less Oring 1977; Clutton-Brock and Harvey 1978). Conse- important in determining the size of more intensively quently, within-species studies that simultaneously exam- used areas within the HR and vice versa (i.e., compared ine the sex-specific effects of conspecific density and to the second- and third-order habitat selection; Johnson resource distribution on multiple spatiotemporal scales 1980). Similarly, relationships between conspecifics, are largely lacking. (A) (B) Prey density Conspesific density Isopleth (%) 90 80 70 60 50 Female Male Female Male Increasing intensity of area use Figure 1. Home range (HR) estimation obtained as a probability density function of intensity of area use (A). We estimated lynx HR size at 5 use intensities represented by the 90% (total HR), 80%, 70%, 60%, and 50% isopleths where intensity of use increases with decreasing isopleth level (i.e., darker areas = higher use). We predict that range size determinants will vary within an animal’s HR relative to the intensity of use (B). Female HRs should be just large enough to contain sufficient food resources to survive and nourish offspring, and hence, the negative effect of prey density on range size should be strongest on the total HR size (90% isopleth, light grey) and become less important with decreasing isopleth level. We predict the opposite pattern for males as total HR size is set to maximizing mating opportunities whereas basal energy needs should affect space use at a lower isopleth levels (darker grey). For females, we expect conspecific density to show its greatest effect on total HR size due to territorial behavior. For males, however, conspecific density represent both resources (females) and competitors (males), and thus, we expect the effect of conspecific density on male spacing behavior to vary with conspecific density per se. 2958 ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. Effect on range size Increasingly negative Increasingly positiv M. Aronsson et al. Determinants of Lynx Home Range Size In this study, we assessed sex-specific spatiotemporal of the Scandinavian Peninsula (57°–63°N, 9°–17°E) for influences of prey and conspecific density on variation in resident animals ≥20 months old. The study area encom- HR size for a solitary predator, the Eurasian lynx (Lynx passes a north–south environmental gradient where pri- lynx). We used individual location data from large-scale mary productivity, roe deer abundance (Capreolus and long-term telemetry studies (1996–2012) in Sweden capreolus: the primary prey for lynx in this region; Odden and Norway. Because of population expansion and active et al. 2006, 2013; Gervasi et al. 2014), proportion of agri- management of lynx (i.e., hunting) in this system, we had cultural land, and human density increase to the south, uncorrelated variation in prey density and conspecific whereas the period with snow cover increases to the density across male and female HRs, allowing us to inves- north. For a detailed description of the study areas, see tigate three main questions. First, do lynx show sex-speci- Andren et al. (2006) and Odden et al. (2013). fic relationships in how prey and conspecific density Lynx were captured and immobilized using strict influence total HR size? Females should reduce their HR ethics-approved handling protocols (see Andren et al. size as prey and conspecific density increase (Adams 2006; Arnemo et al. 2011). Animals were fitted with VHF 2001; Mitchell and Powell 2004), whereas males’ HR size transmitters (1996–2008: VHF collars MOD335 and should mainly be affected by conspecific density as males’ MOD400NH), intraperitoneal transmitters (IMP/150/L HR is expected to be set to maximize mating opportuni- and IMP/400/L; Telonics, Mesa, AZ, USA) or GPS collars ties (Sandell 1989). Second, how do prey and conspecific (2003–2014; GPS plus mini, Vectronics Aerospace, Berlin, densities influence sex-specific HR sizes relative to the Germany; Lotek 3300SL; Lotek Wireless, Newmarket, intensity of space use within the HR? For this, we com- Ontario, Canada; Televilt Posrec 300 and Tellus 1C, Fol- pared five spatial scales of increasing intensity of HR use lowit, Lindesberg, Sweden). (Fig. 1A), with an expectation of contrasting patterns Reproductive status for female lynx ≥2 years was between the sexes as females’ and males’ HR size should checked annually using telemetry locations in May–June be regulated by different factors at the total HR scale to find the natal lair. Kitten survival was determined by (Fig. 1B). Finally, we examined sex-specific within-year snow tracking in November–January (i.e., changes in litter temporal effects on HRs. We compared mating and non- size). For detailed description of determination of repro- mating seasons to test whether males increase their HR ductive status and kitten survival, see Gaillard et al. size during the mating season (i.e., roaming; cf. Sandell (2014). 1989). For females, we expected no effect of mating sea- son, but that the effect of prey density on HR size during Home range size estimation and suckling and kitten rearing would be stronger for repro- spatiotemporal scale ducing compared to nonreproducing females. We estimated lynx HR (km ) using the fixed-kernel method (Worton 1989) with the “adehabitatHR” package Materials and Methods (Calenge 2006) in R (R Core Team 2014). The kernel method estimates an utilization distribution (UD); conse- Study system quently, kernel HR estimations are obtained as a function Eurasian lynx in Scandinavia were almost hunted to of an individual’s relative use of space (Marzluff et al. extinction by the early 20th century, but due to legal pro- 2004). From the UD, an animal’s HR is defined as the tection and hunting restrictions, they have substantially smallest area that accounts for a specific proportion (iso- recovered during the last decades and are now widespread pleth) of the animal’s total use of space; thus, an animal’s throughout Sweden and Norway, with a total population intensity of use of the area increases with decreasing iso- estimate ~1800–2300 individuals in 2011 (Chapron et al. pleth values (Fig. 1A). We estimated lynx total HR as the 2014). The lynx is a solitary and polygamous carnivore 90% isopleth using the reference bandwidth multiplied by that displays intrasexual territoriality, although there may 0.8 (Kie et al. 2010, 2013) to explore the influence of prey be some degrees of intrasexual HR overlap (Mattisson and conspecific density on annual (i.e., 1st February in et al. 2011). Lynx mate in March (Mattisson et al. 2013) year t to 31st January in year t + 1) and seasonal basis. and give birth in late May/early June, and females give Furthermore, we calculated the 80%, 70%, 60%, and 50% birth for the first time at the age of 2 (Nilsen et al. 2011). isopleths to examine how the effect of prey density and Juveniles become independent at 8–10 months, and most conspecific density on area used changes with increasing subadults have settled at 18 months of age (Samelius et al. intensity of space use within the HR (Fig. 1). 2011). During the study period, the number of locations We used location data from 1998 to 2010 (Sweden) acquired per individual varied extensively as radiotracking and 1996 to 2012 (Norway) from the south-central part technology developed. Due to the value of long-term, ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. 2959 Determinants of Lynx Home Range Size M. Aronsson et al. individual-based ecological studies (Pelton and van we calculated the conspecific density index as the area- Manen 1996; Clutton-Brock and Sheldon 2010), we weighted annual number of lynx family groups across the included animals monitored with both GPS and VHF biogeographical regions (Sweden) or carnivore manage- technology. To reduce biases from different sampling fre- ment areas (Norway) overlapping each HR (Sweden 0–4; quencies between animals and years (Borger et al. 2006b), Norway 0.23–0.5 family groups per 1000 km ). Because we randomly sampled 1 location/day/individual. Mean lynx monitoring focuses on family groups, there can be (SE) annual locations per individual were 83  7.4. We annual lynx HRs with zero lynx density (i.e., males and/ only included animals with ≥25 locations and monitored or females without kittens; 4 home ranges of 157). ≥7 months (annual) or ≥half the season (seasonal), result- During the study period, the national population man- ing in a total of 157 annual HRs for 77 individual lynx. agement goals were 300 and 65 family groups for Sweden For each individual with >100 annual locations, we ran- and Norway, respectively, resulting in higher lynx hunting domly subsampled from 10 to 100 locations, resampled quotas and lower lynx density in Norway compared to 200 times, to calculate the mean proportion of reference Sweden (Ministry of the Environment 2003; Andren et al. area (all annual locations/individual) included in HR size 2006; Linnell et al. 2010; SEPA 2013). The high hunting estimates in relation to number of locations used. Mean quotas in Norway in combination with the ongoing proportion of reference area (SD) and mean coefficient southward expansion of the Swedish lynx population of variation (SD) for 25 locations were 0.85  0.04 and (Samelius et al. 2011) resulted in uncorrelated prey and 0.12  0.03, compared to 0.97  0.02 and 0.05  0.02 conspecific densities (compared to the null model: for 83 locations. Although the number of locations per DAIC = 8.6, w = 0 for Norway and DAIC = 4.0, c i c individual differed depending on collar technology w = 0.12 for Sweden), allowing us to simultaneously (VHF = 64  3, range: 25–175; GPS = 230  12, range: study their effects on lynx HR size. 120–333), there was no effect of collar type on annual HR size (models including collar type compared to null mod- Statistical analyses els: DAIC = 3.4, w = 0.15). c i We calculated mating (February 1 to April 15; males: We used general linear mixed models with a Gaussian n = 18; females: n = 22) and nonmating season HRs error distribution using the “lme4” package (Bates et al. (April 16 to January 31; males: n = 28, females: n = 55). 2014) in R with log-transformed HR size as the response Although lynx mate in March, the annual and mating variable. Individual identity and year were fitted as ran- season HR calculations began in February to buffer dom effects in all models to account for repeated mea- potential premating behavioral changes just before mating surements. Log-transformed prey and conspecific density (i.e., searching for or guarding mates). For females, we indices were included as covariates together with their also calculated suckling (May 20 to September 30 repre- pairwise interactions with sex. Because of contrasting senting birth to end of lactation, n = 71) and rearing sea- management regimes in Sweden and Norway (i.e., lynx sonal HRs (May 20 to January 31 representing birth to population goals and hunting quotas), we also included independence: n = 44). country and the interaction between country and sex. Although prey and conspecific density varied between countries, there was no support for the interaction Prey and conspecific density indices between country and prey or conspecific densities on We used reported yearly number of hunted roe deer (i.e., annual HR size (Fig. 2; Table S1) so these interactions hunting bag) at the hunting district level in Sweden were not further considered. Furthermore, there was no (Swedish Association for Hunting and Wildlife Manage- support for additional latitudinal patterns in HR size not ment, available at: www.jagareforbundet.se) and munici- explained by prey or conspecific density (best model pality level in Norway (Statistics Norway, available at: including latitude DAIC = 22.2; variable relative impor- www.ssb.no) as a proxy for prey density (Appendix S1). tance weight for latitude = 0, cf. Table 1). For conspecific density, we used lynx monitoring results To test for seasonal HR size differences, we compared where density of lynx family groups (i.e., female with kit- mating and nonmating seasons (males and females) and tens) is estimated at a regional scale based on snow track- suckling and rearing seasons (females). For females, we ing in January and February each year (Linnell et al. initially included reproductive status as a three-level 2007). We calculated a HR-specific annual prey density explanatory factor (i.e., reproducing with surviving kit- index as the area-weighted average annual roe deer bag tens; reproducing but lost all kittens; nonreproducing). size across the hunting districts (Sweden) or municipali- However, there was no HR size differences between the ties (Norway) overlapping each annual HR (Sweden 13– two classes of reproducing females (models including kit- 123; Norway 0.5–81 shot roe deer per 10 km ). Similarly, ten survival compared to null models: DAIC = 1.75, 2960 ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. M. Aronsson et al. Determinants of Lynx Home Range Size Norway Sweden Candidate models were compared using the sample-size corrected Akaike information criterion (AIC ) and AIC weights (w ) from the “MuMIn” package (Barton 2013) in ● i R. Models with DAIC <2 were used to generate model- averaged parameter estimates (Burnham and Anderson 2002). We used a bootstrap method implemented in R using the “ez” package (Lawrence 2013) to calculate 95% confidence intervals for mixed models. We used AIC weights on the full candidate model set to generate rela- tive variable importance weights (RVI) for each explana- tory variable. Model residuals did not violate assumptions for normality, homogeneity of variance, and structure rel- ative to predictors. Means are presented with standard errors unless otherwise stated. Results Males Females Males Females There were clear sex-specific differences in annual HR size (90% isopleth males = 1045  66 km , range: 303– Figure 2. Country-specific mean (SE) prey density index (roe deer; 2290, n = 57; females = 483  35 km , range: 109–1853, squares), conspecific density index (triangles), and male and female n = 100), with range size dramatically decreasing with lynx home range size (circles). Estimates are based on raw data. increased intensity of space use for both sexes (80%, 70%, 60%, and 50% isopleth area (km ): 748  48, w = 0.29 for suckling season and DAIC = 4.55, i c 566  37, 432  29, and 325  22 for males and w = 0.09 for rearing season); therefore, we included 343  25, 255  19, 192  15, and 142  11 for female reproductive status as a two-level factor (repro- females). Total annual HR size for both males and ducing and nonreproducing). females was negatively related to conspecific density Table 1. Highest ranked candidate models relating annual lynx home range (HR) size (n = 157) to conspecific density (lynx; L), prey density (roe deer; R), country (C), latitude (Lat), sex (S; difference of females from males), and interactions (*). The 90% kernel isopleth represents the total HR and decreasing isopleth values represents an increasing intensity of HR use (Fig. 1). For each model, we show sample-size corrected AIC (AIC ), difference in AIC relative to the highest ranked model (DAIC ), and AIC weights (w ). For simplicity, only models with w > 0.01, univariate mod- c c i i els, and intercept-only models are shown. 90% isopleth, total HR 80% isopleth 70% isopleth 60% isopleth 50% isopleth Spatial scale Model AIC DAIC w AIC DAIC w AIC DAIC w AIC DAIC w AIC DAIC w c c i c c i c c i c c i c c i L + R + S + R*S 216.8 0.0 0.37 225.2 0.0 0.3 235.6 0.0 0.24 247.1 0.5 0.19 257.9 0.9 0.15 L + R + S 219.1 2.3 0.11 226.2 1.0 0.18 235.7 0.1 0.22 246.6 0.0 0.24 257.0 0.0 0.24 R + S + R*S 219.8 3.0 0.08 228.8 3.6 0.05 239.4 3.8 0.03 251.0 4.4 0.03 261.8 4.8 0.02 L + R + S + L*S + R*S 220.4 3.6 0.06 228.8 3.6 0.05 239.1 3.5 0.04 250.6 4.0 0.03 261.4 4.4 0.03 C + L + R + S + R*S 220.7 3.9 0.05 229.2 4.0 0.04 239.5 3.9 0.03 250.9 4.3 0.03 261.7 4.7 0.02 C + L + R + S + C*S 221.2 4.4 0.04 229.7 5.0 0.03 239.8 4.2 0.03 251.0 4.4 0.03 261.6 4.6 0.03 C + S + C*S 221.3 4.5 0.04 229.5 4.3 0.04 239.1 3.5 0.04 249.9 3.3 0.05 259.9 2.9 0.06 C + L + S + C*S 221.5 4.7 0.03 229.7 4.5 0.03 239.3 3.7 0.04 250.3 3.7 0.04 260.5 3.5 0.04 C + R + S + R*S 221.7 4.9 0.03 230.0 4.8 0.03 240.2 4.6 0.02 251.5 4.9 0.02 261.9 4.9 0.02 L + S 221.9 5.1 0.03 229.1 3.9 0.04 238.2 2.6 0.06 249.0 2.4 0.07 259.3 2.3 0.08 L + R + S + L*S 222.0 5.2 0.03 229.2 4.0 0.04 238.6 3.0 0.05 249.5 2.9 0.06 259.8 2.8 0.06 C + L + R + S 222.7 5.9 0.02 229.9 4.7 0.03 239.4 3.8 0.03 250.3 3.7 0.04 260.7 3.7 0.04 S 234.9 18.1 0.00 242.7 17.5 0.00 252.1 16.5 0.00 262.8 16.2 0.00 273.1 16.1 0.00 L 260.7 43.9 0.00 267.6 42.4 0.00 276.7 41.1 0.00 287.5 40.9 0.00 298.0 41.0 0.00 C 265.5 48.7 0.00 272.2 47.0 0.00 281.2 45.6 0.00 291.8 45.2 0.00 301.9 44.9 0.00 Intercept only 269.7 52.9 0.00 277.0 51.8 0.00 286.3 50.7 0.00 297.0 50.4 0.00 307.4 50.4 0.00 R 271.3 54.5 0.00 278.4 53.2 0.00 287.7 52.1 0.00 298.5 51.9 0.00 309.0 52.0 0.00 Lat 294.2 77.5 0.00 301.4 76.19 0.00 310.9 75.29 0.00 321.8 75.2 0.00 332.3 75.33 0.00 The models used for model average parameter estimates for each isopleth are indicated in boldface. ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. 2961 Home range size (km ) 0200 400 600 800 1000 1200 020 40 60 80 Prey density index Conspecific density index Determinants of Lynx Home Range Size M. Aronsson et al. (Fig. 3; Table 1). However, prey density affected female, Seasonal effects but not male total HR size, with HR decreasing with increasing prey density (Fig. 3). Although female total Contrary to our expectations, males’ HR size was smaller HRs (90% isopleth) were larger in Norway compared to during the mating compared to nonmating season 2 2 (789  68 vs. 1029  93 km ), while females’ HR size Sweden (Norway = 734  67 km , range; 225–1853, was larger during the mating season (647  112 vs. n = 39; Sweden = 322  108, range: 109–733, n = 61), this difference was explained by conspecific and prey den- 486  53 km ; Table 3). Reproducing females had smal- sity, and not by country (RVI: prey = 0.86, conspeci- ler HRs compared to nonreproducing females during fic = 0.81, country = 0.31; cf. Table 2). both suckling and rearing periods (Table S3). Prey density was not related to HR size during suckling, but it was negatively related to the rearing season HR size. Con- Sex-specific intensity of space use effects specific density was negatively related to female seasonal As predicted, both prey and conspecific density showed HR size, regardless of reproductive status (Table S3). spatial scale-dependent effects on HR size, with the largest difference in sex-specific effect of prey density on HR size Discussion at the 90% isopleth (Fig. 4; Table 1). For females, the negative effect of prey on range size decreased with By simultaneously examining prey and conspecific density increasing intensity of space use, while males showed the in a spatiotemporal context, we show that new insights opposite pattern with the negative effect of prey density can be found in the study of sex differences in spacing on range size becoming evident for high intensity of space behavior. The importance of being able to account for use (Fig. 4). For males, the proportion of the total HR both prey and conspecific density when studying HR size encompassed by the highest intensity of space use (50% should not be underestimated, as this allowed us to and 60% isopleths) decreased with increasing prey den- demonstrate that observed differences in total HR size sity, but this effect was not found for other isopleth area between Sweden and Norway (Fig. 2) were completely ratios (Fig. S1; Table S2). The negative relationship explained by different prey and conspecific densities. Fur- between conspecific density and HR size was evident for thermore, we show that the effect of prey density on total both sexes, but this effect did not decrease with increasing HR size is restricted to females, in contrast to a previous study that did not account for the confounding effects of intensity of space use (Fig. 4; Table 1). (A) (B) Males Females Figure 3. Sex-specific relationships between annual lynx home range size (km ; 90% fixed- kernel isopleth) and (A) prey density (i.e., roe deer), and (B) conspecific density. Model- averaged predictions derived from the highest ranked models from Table 1 are shown (solid lines = males, dashed lines = females) with associated 95% CIs (see Table 2 for parameter estimates), where all other explanatory variables were held at their mean values. Home range size predictions were back- –1 012345 0.0 0.4 0.8 1.2 1.6 transformed to their normal scale for the Log(prey density) Log(conspecific density) figure. 2962 ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. Home range size (km ) 0 200 400 600 800 1000 1200 1400 1600 0 200 400 600 800 1000 1200 1400 1600 M. Aronsson et al. Determinants of Lynx Home Range Size Table 2. Relative variable importance (RVI) and model-averaged parameter estimates with standard error (SE) for each variable retained in the best models for each HR isopleth in Table 1 (S = sex, R = prey density, L = conspecific density). 90% isopleth, total HR 80% isopleth 70% isopleth 60% isopleth 50% isopleth Parameter RVI Estimate SE RVI Estimate SE RVI Estimate SE RVI Estimate SE RVI Estimate SE Intercept 7.04 0.21 6.91 0.28 6.68 0.27 6.45 0.27 6.20 0.26 S 1.00 0.21 0.24 1.00 0.51 0.36 1.00 0.61 0.35 1.00 0.67 0.34 1.00 0.73 0.32 R 0.86 0.00 0.06 0.83 0.06 0.07 0.78 0.07 0.07 0.74 0.08 0.07 0.69 0.09 0.07 L 0.81 0.29 0.10 0.84 0.33 0.11 0.85 0.34 0.11 0.84 0.36 0.11 0.82 0.37 0.12 R*S 0.62 0.20 0.07 0.5 0.12 0.04 0.39 0.09 0.04 0.32 0.08 0.03 0.26 0.06 0.03 (A) (B) 10 1 2 3 4 5 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Figure 4. Sex-specific relationships between annual home range (HR) size (km ) and (A) prey density (i.e., roe deer), and (B) conspecific density for a range of isopleths (90, 80, 70, 60, and 50%) that represent increasing intensity of use of the HR (Fig. 1). The lines show model-averaged predictions for the different isopleth levels from Table 1, with all other explanatory variables kept at their mean values. HR size predictions were back- –1 0 1 2 3 4 5 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 transformed to their normal scale for the Log(prey density) Log(conspecific density) figure. For model parameters, see Table 2. conspecific density and found a negative relationship sity of space use increased within the HR (Fig. 4). This between roe deer density and total HR size for both male indicates that although food availability is a key driver of and female lynx (Herfindal et al. 2005). By assessing sex- total HR size for females, factors other than food define specific range size determinants as intensity of space use female space use in the more intensively used areas (e.g., increased within the HR, we could show that it is only at availability of den sites, or habitats that provide protec- higher isopleth levels (50–60%) that male space use is tion for females and their offspring from human intru- influenced by prey density. sion and intraguild predation; Kelt and Van Vuren 2001; Females’ total HR size decreased as prey density Basille et al. 2013; Rauset et al. 2013). Because areas that increased, supporting the expectation that females adapt provide protection and den sites are commonly in steep, their space use relative to the resources needed to survive rugged terrain or dense forest (Rauset et al. 2013), they and successfully reproduce (Sandell 1989). However, the may represent local habitats with little variation in prey influence of prey density on area use decreased as inten- density. Thus, although intensively used areas are often ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. 2963 Home range size (km ) Females Males 0 200 400 600 800 1000 1200 0 200 400 600 800 1000 1200 0 200 400 600 800 1000 1200 0 200 400 600 800 1000 1200 Determinants of Lynx Home Range Size M. Aronsson et al. Table 3. Full candidate models testing the influence of sex (S; differ- Contrary to our predictions, the effect of conspecific ence of females from males) and season (M; difference of mating sea- density did not change with intensity of space use for son from nonmating season) on lynx seasonal home range (HR) size. either sex (Fig. 4; Table 2) suggesting that intrasexual Seasonal HRs are estimated as the 90% fixed-kernel isopleth. Terms interactions may occur in the area between the 50% iso- are as in Table 1. pleth and the HR borders. For females, the negative Model AIC DAIC w c c i effect of conspecific density on HR size likely results from intrasexual competition (Maher and Lott 2000; S + M + S*M 1784 0.0 1.00 Benson et al. 2006). For males, however, the relationship S + M 1798 14 0.00 between HR size and conspecific density is probably dri- S 1807 23 0.00 M 1824 40 0.00 ven by two factors: that is, reduced maximum HR size Intercept only 1833 49 0.00 as conspecific density increases due to the cost of increased competition and increasing HR size at low Model parameter estimate (SE) for highest ranked model: Seasonal conspecific density to increase their encounters with home range size = 810  101  558  12 *S  217  100 *M + females. Total HR size of male lynx did not adapt to 282  133 * S*M. encompass a similar number of female HRs as conspeci- assumed to contain high and predictable prey densities fic density changed (Fig. 2), contrary to bobcats (Lynx (e.g., Maher and Lott 2000; Powell 2000), our results rufus) that exhibit an isometric relationship between show that this is not necessarily the case because it was male and female HRs (Ferguson et al. 2009). Instead, the size of the outer area of the females’ HR that the ratio between male and females’ HR size was posi- responded strongest to changes in prey density (Fig. 4; tively related to prey density in our study. Consequently, Table 2). This suggests that it is the less intensively used male lynx in areas with high prey density encounter areas (i.e., those relating to the total HR size) that are more females compared to males in low prey density critical for food provisioning. The fact that lynx select areas where males and females HRs are more similar in different habitats to rest during the day or between kills size. This suggests that male lynx have an upper bound compared to hunting (Bouyer et al. 2015) could explain for their HR size, likely due to the energetic costs of this decoupling of intensively used areas from prey maintaining large territories and increased risk of mor- density. tality associated with using unfamiliar areas that out- For males, that prey density did not affect total HR size weighs any additional fitness benefits of encountering supports the expectation that male large-scale space use is more females (Kelt and Van Vuren 2001). primarily driven by access to mates, not food (Sandell We found that males’ HR during the mating season 1989). However, a negative relationship between prey was smaller than during nonmating season, indicating density and male range size became visible with increasing that male lynx do not generally adopt a roaming mating intensity of space use due to energetic requirements tactic. We suggest that this behavioral pattern is because (Fig. 4). This is also supported by the proportion of the female Eurasian lynx [as well as Canadian lynx total HR included in the 50% isopleth area being nega- (L. canadensis) and Iberian lynx (L. pardinus)], contrary tively correlated with prey density for males but not to other felids, are strictly seasonal breeders due to a females (Fig. S1; Table S2). Furthermore, when males’ mono-estrous cycle (Jewgenow et al. 2014; Painer et al. area use was similar to females’ total HR size (i.e., males’ 2014). Hence, males move over smaller areas and interact 60% isopleth = 432  29 vs. females’ total HR more when they stay close to receptive females during a size = 483  35 km ), the interaction between prey den- short mating season, whereas they keep larger exclusive sity and sex was not included in the best model HRs during the rest of the year to reduce the presence of (Table 1). competing males before the mating season. This is also Our results show scale-dependent, sex-specific effects of supported by (1) observations of lethal male-male interac- different resources on spacing behavior, corresponding to tions during the mating season (Mattisson et al. 2013), the scale-dependent habitat selection suggested by Rettie (2) that male lynx only show moderate seasonal changes and Messier (2000) to reflect the hierarchy of fitness-lim- in hormonal levels related to reproductive capacity iting factors. At a finer spatial scale (within HR), the (Muller € et al. 2014), and (3) that male total annual HR importance of different space use determinants will be size is negatively affected by conspecific density but not conditional on the coarser scale (total HR) to maximize by prey density. an individual fitness (i.e., for females’ total HR = food Because the most energy-consuming activities for females are lactation and feeding young (Gittleman and requirements, 50% isopleth = shelter/protection; for males’ total HR = access to females, 50–60% isopleth = Thompson 1988), there is an expectation that prey den- food requirements). sity effects on HR size should be strongest during these 2964 ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. M. Aronsson et al. Determinants of Lynx Home Range Size critical periods of high energetic requirements (Sandell Conflict of Interest 1989). However, females with kittens had consistently smaller seasonal HRs than nonreproducing females, and None declared. the effect of prey density on HR size was similar for reproducing and nonreproducing females at both seasonal Data Accessibility and annual time scales. Thus, reductions in HR size for reproducing females during suckling is likely due to Relevant data for this study will be archived in the Dryad young, dependent kittens limiting the mother’s mobility Digital Repository conditional on acceptance. (Dahle and Swenson 2003) as well as female lynx avoiding human disturbance during this period (White et al. References 2015). That nonreproducing females did not reduce their Adams, E. S. 2001. Approaches to the study of territory size HR size during summer despite an increase in prey avail- and shape. Annu. Rev. Ecol. Syst. 32:277–303. ability (i.e., small prey and domestic sheep; Odden et al. Andren, H., J. D. C. Linnell, O. Liberg, R. Andersen, A. 2006, 2013; Gervasi et al. 2014) suggests that nonrepro- Danell, J. Karlsson, et al. 2006. Survival rates and causes of ducing female HR size is regulated by prey availability mortality in Eurasian lynx in multi-use landscapes. Biol. during the winter. Conserv. 131:23–32. Our results highlight the importance of simultaneously Arnemo, J. M., A. Evans, and A. Fahlman. 2012. Biomedical considering resources and intraspecific interactions as protocols for free-ranging brown bears, grey wolves, determinants of animal spacing patterns. By examining wolverines and lynx. Available at: http://www1.nina.no/ variation in intensity of space use, instead of only focus- RovviltPub/pdf/Biomedical%20Protocols%20Carnivores% ing on total HR and/or an arbitrarily chosen core area 20March%202012.pdf (usually 50- or 30% isopleth for kernel HR estimations; Barton,  K. 2013. MuMIn: multi-model inference, R package Vander Wal and Rodgers 2012), we show that large version 1.9.13. http://CRAN.R-project.org/package=MuMIn knowledge gains are still to be made in the study of spac- Basille, M., B. Van Moorter, I. Herfindal, J. Martin, J. D. C. ing behavior. We recommend a spatiotemporal approach Linnell, J. Odden, et al. 2013. Selecting habitat to survive: be used in future HR studies, as it highlights how the use the impact of road density on survival in a large carnivore. of different resources varies in importance within an ani- PLoS One 8:e65493. mal’s HR. Consequently, factors that may not be related Bates, D., M. Maechler, B. Bolker, and S. Walker. 2014. lme4: to total HR size still may be important determinants in linear mixed-effects models using Eigen and S4, R package animal spatial ecology. In turn, this will lead to better version 1.1-6. http://CRAN.R-project.org/package=lme4 models of ecological systems to both inform theory and van Beest, F. M., I. M. Rivrud, L. E. Loe, J. M. Milner, and A. management. Mysterud. 2011. What determines variation in home range sizes across spatio-temporal scales in a large browsing herbivore? J. Anim. Ecol. 80:771–785. Acknowledgments Benson, J. F., M. J. Chamberlain, and B. D. Leopold. 2006. The study is conducted within the Scandinavian Lynx Regulation of space use in a solitary felid: population Project, Scandlynx (http://scandlynx.nina.no/) and would density or prey availability? Anim. Behav. 71:685–693. not have been possible without the help from a large Borger, € L., N. Franconi, F. Ferretti, F. Meschi, G. De Michele, number of fieldworkers and students. Funding is from the A. Gantz, et al. 2006a. An integrated approach to identify Swedish Environmental Protection Agency, Norwegian spatiotemporal and individual-level determinants of animal Environment Directorate, the Swedish Research Council home range size. Am. Nat. 168:471–485. Formas, the Research Council of Norway the Norwegian Borger, € L., N. Franconi, G. De Michele, A. Gantz, F. Meschi, Institute for Nature Research, the Swedish Association for A. Manica, et al. 2006b. Effects of sampling regime on the Hunting and Wildlife Management, WWF-Sweden and mean and variance of home range size estimates. J. Anim. “Marie-Claire Cronstedts” foundations, the County Ecol. 75:1393–1405. Governor’s Office for Hedmark, Oslo and Akershus, Øst- Bouyer, Y., G. San Martin, P. Poncin, R. C. Beudels-Jamar, J. fold, Oppland, Buskerud, Vestfold, and Telemark Coun- Odden, and J. D. C. Linnell. 2015. Eurasian lynx habitat ties, the Carnivore Management Boards in regions 2, 3, selection in human-modified landscape in Norway: effects of and 4 and 8, the municipalities of Trysil, Fl a, Gol, Hjart- different human habitat modifications and behavioral states. Biol. Conserv. 191:291–299. dal, Nes, Nore og Uvdal, Rollag, Sauherad, Tinn, and Al. We thank A. Danell for compiling all roe deer hunting Burnham, K. P., and D. R. Anderson. 2002. Model selection data needed for this study and A. Ordiz and E. Nilsen for and multimodel inference, 2nd edn. Springer-Verlag, valuable comments on the article. New York. ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. 2965 Determinants of Lynx Home Range Size M. Aronsson et al. Calenge, C. 2006. The package adehabitat for the R software: a Jewgenow, K., J. Painer, O. Amelkina, M. Dehnhard, and F. tool for the analysis of space and habitat use by animals. Goeritz. 2014. Lynx reproduction – long-lasting life cycle of Ecol. Model. 197:516–519. corpora lutea in a feline species. Reprod. Biol. 14:83–88. Campioni, L., M. del Mar Delgado, R. Lourenco, G. Johnson, D. H. 1980. The comparison of usage and availability Bastianelli, N. Fernandez, and V. Penteriani. 2013. measurements for evaluating resource preference. Ecology Individual and spatio-temporal variation in the home range 61:65–71. behavior of a long-lived, territorial species. Oecologia Kelt, D. A., and D. H. Van Vuren. 2001. The ecology and 172:371–385. macroecology of mammalian home range area. Am. Nat. Campos, F. A., M. L. Bergstrom, A. Childers, J. D. Hogan, K. 157:637–645. M. Jack, A. D. Melin, et al. 2014. Drivers of home range Kie, J. G., J. Matthiopoulos, J. Fieberg, R. A. Powell, F. characteristics across spatiotemporal scales in a Neotropical Cagnacci, M. S. Mitchell, et al. 2010. The home-range primate, Cebus capucinus. Anim. Behav. 91:93–109. concept: are traditional estimators still relevant with modern Carbone, C., N. Pettorelli, and P. A. Stephens. 2011. The bigger telemetry technology? Philos. Trans. R. Soc. Lond. B Biol. they come, the harder they fall; body size and prey abundance Sci. 365:2221–2231. influence predator-prey ratios. Biol. Lett. 7:312–315. Kie, J. G. 2013. A rule-based ad hoc method for selecting a Chapron, G., P. Kaczensky, J. D. C. Linnell, M. von Arx, D. bandwidth in kernel home-range analyses. Anim. Biotelem. Huber, H. Andren, et al. 2014. Recovery of large carnivores 2013:13. in Europe’s modern human-dominated landscapes. Science Lawrence, M. A. 2013. ez: Easy analysis and visualization of 346:1517–1519. factorial experiments, R package version 4.2-2. http:// Clutton-Brock, T., and P. H. Harvey. 1978. Mammals, CRAN.R-project.org/package=ez resources and reproductive strategies. Nature 273:191–195. Linnell, J. D. C., P. Fiske, I. Herfindal, J. Odden, H. Brøseth, Clutton-Brock, T., and B. C. Sheldon. 2010. Individuals and and R. Andersen. 2007. An evaluation of structured snow- populations: the role of long-term, individual-based studies track surveys to monitor Eurasian lynx populations. Wildlife of animals in ecology and evolutionary biology. Trends Ecol. Biol. 13:456–466. Evol. 25:562–573. Linnell, J. D. C., H. Brøseth, J. Odden, and E. Nilsen. 2010. Dahle, B., and J. E. Swenson. 2003. Home ranges in adult Sustainable harvesting a large carnivore? Development of Scandinavian brown bears (Ursus arctos): effect of mass, sex, Eurasian lynx populations in Norway during 160 years of reproductive category, population density and habitat type. shifting policy. Environ. Manage. 45:1142–1154. J. Zool. Lond. 260:329–335. Lopez-Bao,  J. V., F. Palomares, A. Rodrıguez, and M. Emlen, S. T., and L. W. Oring. 1977. Ecology, sexual Delibes. 2010. Effects of food supplementation on home- selection, and the evolution of mating systems. Science range size, reproductive success, productivity and 197:215–223. recruitment in a small population of Iberian lynx. Anim. Ferguson, A. W., N. A. Currit, and F. W. Weckerly. 2009. Conserv. 13:35–42. Isometric scaling in home-range size of male and female Lopez-Bao, J. V., A. Rodrıguez, M. Delibes, J. M. Fedriani, bobcats (Lynx rufus). Can. J. Zool. 87:1052–1060. J. Calzada, P. Ferreras, et al. 2014. Revisiting food-based Gaillard, J.-M., E. B. Nilsen, J. Odden, H. Andren, and J. D. C. models of territoriality in solitary predators. J. Anim. Ecol. Linnell. 2014. One size fits all: Eurasian lynx females share a 83:934–942. common optimal litter size. J. Anim. Ecol. 83:107–115. Maher, C. R., and D. F. Lott. 2000. A review of ecological Gervasi, V., E. B. Nilsen, J. Odden, Y. Bouyer, and J. D. C. determinants of territoriality within vertebrate species. Am. Linnell. 2014. The spatial-temporal distribution of wild and Midl. Nat. 143:1–29. domestic ungulates modulates lynx kill rates in a multi-use Marzluff, M., J. J. Millspaugh, P. Hurvitz, and M. S. landscape. J. Zool. 292:175–183. Handcock. 2004. Relating resources to a probabilistic Gittleman, J. L., and S. D. Thompson. 1988. Energy allocation measure of space use: forest fragments and Steller’s Jays. in mammalian reproduction. Am. Zool. 28:863–875. Ecology 85:1411–1427. Godsall, B., T. Coulson, and A. F. Malo. 2014. From Mattisson, J., J. Persson, H. Andren, and P. Segerstrom. € 2011. physiology to space use: energy reserves and Temporal and spatial interactions between an obligate androgenization explain home-range size variation in a predator, the Eurasian lynx, and a facultative scavenger, the woodland rodent. J. Anim. Ecol. 83:126–135. wolverine. Can. J. Zool. 89:79–89. Herfindal, I., J. D. C. Linnell, J. Odden, E. B. Nilsen, and R. Mattisson, J., P. Segerstrom, € J. Persson, M. Aronsson, G. R. Andersen. 2005. Prey density, environmental productivity Rauset, G. Samelius, et al. 2013. Lethal male-male and home-range size in the Eurasian lynx (Lynx lynx). interactions in Eurasian lynx. Mamm. Biol. 78:304–308. J. Zool. 265:63–71. McLoughlin, P. D., and S. H. Ferguson. 2000. A hierarchical Jetz, W., C. Carbone, J. Fulford, and J. H. Brown. 2004. The pattern of limiting factors helps explain variation in home scaling of animal space use. Science 306:266–268. range size. Ecoscience 7:123–130. 2966 ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. M. Aronsson et al. Determinants of Lynx Home Range Size McNab, B. K. 1963. Bioenergetics and the determination of differences in habitat selection between sympatric large home range size. Am. Nat. 97:133–140. carnivores. Oecologia 172:701–711. Ministry of the Environment. 2003. Rovvilt i norsk natur Rettie, W. J., and F. Messier. 2000. Hierarchical habitat [Carnivores in Norwegian nature]. Stortingsmelding 15 selection by woodland caribou: its relationship to limiting (2003–2004) [In Norwegian]. factors. Ecography 23:466–478. Mitchell, M. S., and R. A. Powell. 2004. A mechanistic home Samelius, G., H. Andren, O. Liberg, J. D. C. Linnell, J. Odden, range model for optimal use of spatially distributed re- P. Ahlqvist, et al. 2011. Spatial and temporal variation in sources. Ecol. Model. 177:209–232. natal dispersal by Eurasian lynx in Scandinavia. J. Zool. Morales, J. M., P. R. Moorcroft, J. Matthiopoulos, J. L. Frair, 286:120–130. J. G. Kie, R. A. Powell, et al. 2010. Building the bridge Sandell, M. 1989. The mating tactics and spacing patterns of between animal movement and population dynamics. solitary carnivores. Pp. 64–82 in J. L. Gittelman, ed. Philos. Trans. R. Soc. Lond. B Biol. Sci. 365:2289–2301. Carnivore behavior, ecology, and evolution. Cornell Univ. Morellet, N., C. Bonenfant, L. Borger, F. Ossi, F. Cagnacci, M. Press, New York. Heurich, et al. 2013. Seasonality, weather and climate affect SEPA; Swedish Environmental Protection Agency. 2013. home range size in roe deer across a wide latitudinal Nationell forvaltningsplan € for € lodjur 2013-2017. [National gradient within Europe. J. Anim. Ecol. 82:1326–1339. management plan for lynx 2013-2017]. ISBN 978-91-620- Muller, € K., S. Koster, J. Painer, A. Soderberg, € D. Gavier- 8648-0. [In Swedish]. Arkitektkopia, Bromma, Sweden. Widen, E. Brunner, et al. 2014. Testosterone production and Vander Wal, E., and A. R. Rodgers. 2012. An individual-based spermatogenesis in free-ranging Eurasian lynx (Lynx lynx) quantitative approach for delineating core areas of animal throughout the year. Eur. J. Wildl. Res. 60:569–577. space use. Ecol. Model. 224:48–53. Nilsen, E. B., J. D. C. Linnell, J. Odden, G. Samelius, and H. White, S., R. A. Briers, Y. Bouyer, J. Odden, and J. D. C. Andren. 2011. Patterns of variation in reproductive Linnell. 2015. Eurasian lynx natal den site and parameters in Eurasian lynx (Lynx lynx). Acta Theriol. maternal home range selection in multiple-use landscapes. 57:217–223. J. Zool. 297:87–98. Odden, J., J. D. C. Linnell, and R. Andersen. 2006. Diet of Worton, B. J. 1989. Kernel methods for estimating the Eurasian lynx in the boreal forest of southeastern Norway: utilization distribution in home range studies. Ecology the relative importance of livestock and hares at low roe 70:164–168. deer density. Eur. J. Wildl. Res. 52:237–244. Odden, J., E. B. Nilsen, and J. D. C. Linnell. 2013. Density of Supporting Information wild prey modulates lynx kill rates on free-ranging domestic sheep. PLoS One 8:e79261. Additional Supporting Information may be found in the Painer, J., K. Jewgenow, M. Dehnhard, J. M. Arnemo, J. D. C. online version of this article: Linnell, J. Odden, et al. 2014. Physiologically persistent Appendix S1. The use of yearly roe deer hunting bags as corpora lutea in Eurasian Lynx-Longitudinal ultrasound and proxy for roe deer density. endocrine examinations intra-vitam. PLoS One 9:e90469. Figure S1. Proportion of 90% isopleth area included in Pelton, M., and F. van Manen. 1996. Benefits and pitfalls of the 50% isopleth for male in relation to prey density long-term research: a case study of black bears in Great index. Smoky Mountains National Park. Wildl. Soc. Bull. Table S1. Model selection relating lynx annual home 24:443–450. range size to (a) the interaction between country and prey Powell, R. A. 2000. Home ranges, territories, and home range density index and (b) the interaction between country estimators. Pp. 65–110 in L. Boitani and T. Fuller, eds. and conspecific density index. Techniques in animal ecology: uses and misuses. Columbia Table S2. Model selection relating sex-specific annual Univ. Press, New York. home range isopleth area-ratios to prey density index and R Development Core Team. 2010. R: a language and country. environment for statistical computing. R Foundation for Table S3. Model selection relating lynx female seasonal Statistical Computing, Vienna, Austria. http://www.R- home range size to reproductive status, prey density, con- project.org. (accessed August 1, 2011). Rauset, G. R., J. Mattisson, H. Andren, G. Chapron, and J. specific density and country. Persson. 2013. When species’ ranges meet: assessing ª 2016 The Authors. 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Intensity of space use reveals conditional sex‐specific effects of prey and conspecific density on home range size

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References (75)

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Wiley
Copyright
© 2016 Published by John Wiley & Sons Ltd.
ISSN
2045-7758
eISSN
20457758
DOI
10.1002/ece3.2032
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27217946
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Abstract

Capreolus capreolus, carnivore, kernel home Home range (HR) size variation is often linked to resource abundance, with range estimator, ranging behavior, sex differences expected to relate to sex-specific fitness consequences. However, spatiotemporal variation, utilization distribution. studies generally fail to disentangle the effects of the two main drivers of HR size variation, food and conspecific density, and rarely consider how their rela- Correspondence tive influence change over spatiotemporal scales. We used location data from Malin Aronsson, Department of Ecology, 77 Eurasian lynx (Lynx lynx) from a 16-year Scandinavian study to examine Swedish University of Agricultural Sciences, HR sizes variation relative to prey and conspecific density at different spa- Grimso€ Wildlife Research Station, SE-730 91 tiotemporal scales. By varying the isopleth parameter (intensity of use) defining Riddarhyttan, Sweden. the HR, we show that sex-specific effects were conditional on the spatial scale Tel: +46 581 697312; E-mail: malin.aronsson@slu.se considered. Males had larger HRs than females in all seasons. Females’ total HR size declined as prey and conspecific density increased, whereas males’ total HR Funding Information was only affected by conspecific density. However, as the intensity of use within Funding is from the Swedish Environmental the HR increased (from 90% to 50% isopleth), the relationship between prey Protection Agency, Norwegian Environment density and area showed opposing patterns for females and males; for females, Directorate, the Swedish Research Council the prey density effect was reduced, while for males, prey became increasingly Formas, the Research Council of Norway, the important. Thus, prey influenced the size of key regions within male HRs, Norwegian Institute for Nature Research, the Swedish Association for Hunting and Wildlife despite total HR size being independent of prey density. Males reduced their Management, WWF-Sweden and “Marie- HR size during the mating season, likely to remain close to individual females Claire Cronstedts” foundations, the County in estrous. Females reduced their HR size postreproduction probably because of Governor’s Office for Hedmark, Oslo and movement constrains imposed by dependent young. Our findings highlight the Akershus, Østfold, Oppland, Buskerud, importance of simultaneously considering resources and intraspecific interac- Vestfold, and Telemark Counties, the tions as HR size determinants. We show that sex-specific demands influence Carnivore Management Boards in regions 2, the importance of prey and conspecific density on space use at different spa- 3, and 4 and 8, the municipalities of Trysil, Fla, Gol, Hjartdal, Nes, Nore og Uvdal, Rollag, tiotemporal scales. Thus, unless a gradient of space use intensity is examined, Sauherad, Tinn, and Al. factors not related to total HR size might be disregarded despite their impor- tance in determining size of key regions within the HR. Received: 25 January 2016; Accepted: 8 February 2016 Ecology and Evolution 2016; 6(9): 2957– doi: 10.1002/ece3.2032 of its central role in influencing population dynamics and Introduction distribution, home range (HR) size has been extensively Access to critical resources is an essential determinant of studied. Differences in body size, diet, social organization, individual fitness, with spacing behavior being a key and mating system explain general HR size variation factor regulating this access (Morales et al. 2010). Because between species (McNab 1963; Clutton-Brock and Harvey ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. 2957 This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Determinants of Lynx Home Range Size M. Aronsson et al. 1978; Kelt and Van Vuren 2001; Carbone et al. 2011), resources, and HR use should show temporal variation while resource distribution, abundance, and predictability associated with seasonal breeding (Gittleman and Thomp- together with density of competing conspecifics are son 1988). important drivers of HR size variation within species Multiscale approaches have recently been used to (Maher and Lott 2000; McLoughlin and Ferguson 2000; study spatiotemporal effects of food abundance and abi- Jetz et al. 2004; Mitchell and Powell 2004; Lopez-Bao otic factors on HR determination (Borger et al. 2006a; et al. 2014). Lopez-Bao  et al. 2010; van Beest et al. 2011; Campioni Because resource distribution and conspecific interac- et al. 2013; Morellet et al. 2013; Campos et al. 2014; tions are not uniform, the relative importance of Godsall et al. 2014). However, few studies of free-ran- resources and conspecifics in relation to HR variation ging animals have been able to simultaneously assess the should change both in space and time (Borger € et al. effect of food and conspecific density on individual 2006a; van Beest et al. 2011; Campos et al. 2014). As HRs spacing behavior, as these two factors are often strongly are often defined in terms of some minimum intensity of correlated in natural systems (Benson et al. 2006). Fur- space use by the focal animal (Kie et al. 2010), critical thermore, sex-specific space use patterns are expected to insights can be gained by examining how the effect of emerge when the fitness of one sex is largely determined range size determinants changes as intensity of space use by resources for offspring provisioning, while the other changes within the HR (Fig. 1). For example, factors that is largely regulated by mating opportunities (Emlen and are important for determining total HR may become less Oring 1977; Clutton-Brock and Harvey 1978). Conse- important in determining the size of more intensively quently, within-species studies that simultaneously exam- used areas within the HR and vice versa (i.e., compared ine the sex-specific effects of conspecific density and to the second- and third-order habitat selection; Johnson resource distribution on multiple spatiotemporal scales 1980). Similarly, relationships between conspecifics, are largely lacking. (A) (B) Prey density Conspesific density Isopleth (%) 90 80 70 60 50 Female Male Female Male Increasing intensity of area use Figure 1. Home range (HR) estimation obtained as a probability density function of intensity of area use (A). We estimated lynx HR size at 5 use intensities represented by the 90% (total HR), 80%, 70%, 60%, and 50% isopleths where intensity of use increases with decreasing isopleth level (i.e., darker areas = higher use). We predict that range size determinants will vary within an animal’s HR relative to the intensity of use (B). Female HRs should be just large enough to contain sufficient food resources to survive and nourish offspring, and hence, the negative effect of prey density on range size should be strongest on the total HR size (90% isopleth, light grey) and become less important with decreasing isopleth level. We predict the opposite pattern for males as total HR size is set to maximizing mating opportunities whereas basal energy needs should affect space use at a lower isopleth levels (darker grey). For females, we expect conspecific density to show its greatest effect on total HR size due to territorial behavior. For males, however, conspecific density represent both resources (females) and competitors (males), and thus, we expect the effect of conspecific density on male spacing behavior to vary with conspecific density per se. 2958 ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. Effect on range size Increasingly negative Increasingly positiv M. Aronsson et al. Determinants of Lynx Home Range Size In this study, we assessed sex-specific spatiotemporal of the Scandinavian Peninsula (57°–63°N, 9°–17°E) for influences of prey and conspecific density on variation in resident animals ≥20 months old. The study area encom- HR size for a solitary predator, the Eurasian lynx (Lynx passes a north–south environmental gradient where pri- lynx). We used individual location data from large-scale mary productivity, roe deer abundance (Capreolus and long-term telemetry studies (1996–2012) in Sweden capreolus: the primary prey for lynx in this region; Odden and Norway. Because of population expansion and active et al. 2006, 2013; Gervasi et al. 2014), proportion of agri- management of lynx (i.e., hunting) in this system, we had cultural land, and human density increase to the south, uncorrelated variation in prey density and conspecific whereas the period with snow cover increases to the density across male and female HRs, allowing us to inves- north. For a detailed description of the study areas, see tigate three main questions. First, do lynx show sex-speci- Andren et al. (2006) and Odden et al. (2013). fic relationships in how prey and conspecific density Lynx were captured and immobilized using strict influence total HR size? Females should reduce their HR ethics-approved handling protocols (see Andren et al. size as prey and conspecific density increase (Adams 2006; Arnemo et al. 2011). Animals were fitted with VHF 2001; Mitchell and Powell 2004), whereas males’ HR size transmitters (1996–2008: VHF collars MOD335 and should mainly be affected by conspecific density as males’ MOD400NH), intraperitoneal transmitters (IMP/150/L HR is expected to be set to maximize mating opportuni- and IMP/400/L; Telonics, Mesa, AZ, USA) or GPS collars ties (Sandell 1989). Second, how do prey and conspecific (2003–2014; GPS plus mini, Vectronics Aerospace, Berlin, densities influence sex-specific HR sizes relative to the Germany; Lotek 3300SL; Lotek Wireless, Newmarket, intensity of space use within the HR? For this, we com- Ontario, Canada; Televilt Posrec 300 and Tellus 1C, Fol- pared five spatial scales of increasing intensity of HR use lowit, Lindesberg, Sweden). (Fig. 1A), with an expectation of contrasting patterns Reproductive status for female lynx ≥2 years was between the sexes as females’ and males’ HR size should checked annually using telemetry locations in May–June be regulated by different factors at the total HR scale to find the natal lair. Kitten survival was determined by (Fig. 1B). Finally, we examined sex-specific within-year snow tracking in November–January (i.e., changes in litter temporal effects on HRs. We compared mating and non- size). For detailed description of determination of repro- mating seasons to test whether males increase their HR ductive status and kitten survival, see Gaillard et al. size during the mating season (i.e., roaming; cf. Sandell (2014). 1989). For females, we expected no effect of mating sea- son, but that the effect of prey density on HR size during Home range size estimation and suckling and kitten rearing would be stronger for repro- spatiotemporal scale ducing compared to nonreproducing females. We estimated lynx HR (km ) using the fixed-kernel method (Worton 1989) with the “adehabitatHR” package Materials and Methods (Calenge 2006) in R (R Core Team 2014). The kernel method estimates an utilization distribution (UD); conse- Study system quently, kernel HR estimations are obtained as a function Eurasian lynx in Scandinavia were almost hunted to of an individual’s relative use of space (Marzluff et al. extinction by the early 20th century, but due to legal pro- 2004). From the UD, an animal’s HR is defined as the tection and hunting restrictions, they have substantially smallest area that accounts for a specific proportion (iso- recovered during the last decades and are now widespread pleth) of the animal’s total use of space; thus, an animal’s throughout Sweden and Norway, with a total population intensity of use of the area increases with decreasing iso- estimate ~1800–2300 individuals in 2011 (Chapron et al. pleth values (Fig. 1A). We estimated lynx total HR as the 2014). The lynx is a solitary and polygamous carnivore 90% isopleth using the reference bandwidth multiplied by that displays intrasexual territoriality, although there may 0.8 (Kie et al. 2010, 2013) to explore the influence of prey be some degrees of intrasexual HR overlap (Mattisson and conspecific density on annual (i.e., 1st February in et al. 2011). Lynx mate in March (Mattisson et al. 2013) year t to 31st January in year t + 1) and seasonal basis. and give birth in late May/early June, and females give Furthermore, we calculated the 80%, 70%, 60%, and 50% birth for the first time at the age of 2 (Nilsen et al. 2011). isopleths to examine how the effect of prey density and Juveniles become independent at 8–10 months, and most conspecific density on area used changes with increasing subadults have settled at 18 months of age (Samelius et al. intensity of space use within the HR (Fig. 1). 2011). During the study period, the number of locations We used location data from 1998 to 2010 (Sweden) acquired per individual varied extensively as radiotracking and 1996 to 2012 (Norway) from the south-central part technology developed. Due to the value of long-term, ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. 2959 Determinants of Lynx Home Range Size M. Aronsson et al. individual-based ecological studies (Pelton and van we calculated the conspecific density index as the area- Manen 1996; Clutton-Brock and Sheldon 2010), we weighted annual number of lynx family groups across the included animals monitored with both GPS and VHF biogeographical regions (Sweden) or carnivore manage- technology. To reduce biases from different sampling fre- ment areas (Norway) overlapping each HR (Sweden 0–4; quencies between animals and years (Borger et al. 2006b), Norway 0.23–0.5 family groups per 1000 km ). Because we randomly sampled 1 location/day/individual. Mean lynx monitoring focuses on family groups, there can be (SE) annual locations per individual were 83  7.4. We annual lynx HRs with zero lynx density (i.e., males and/ only included animals with ≥25 locations and monitored or females without kittens; 4 home ranges of 157). ≥7 months (annual) or ≥half the season (seasonal), result- During the study period, the national population man- ing in a total of 157 annual HRs for 77 individual lynx. agement goals were 300 and 65 family groups for Sweden For each individual with >100 annual locations, we ran- and Norway, respectively, resulting in higher lynx hunting domly subsampled from 10 to 100 locations, resampled quotas and lower lynx density in Norway compared to 200 times, to calculate the mean proportion of reference Sweden (Ministry of the Environment 2003; Andren et al. area (all annual locations/individual) included in HR size 2006; Linnell et al. 2010; SEPA 2013). The high hunting estimates in relation to number of locations used. Mean quotas in Norway in combination with the ongoing proportion of reference area (SD) and mean coefficient southward expansion of the Swedish lynx population of variation (SD) for 25 locations were 0.85  0.04 and (Samelius et al. 2011) resulted in uncorrelated prey and 0.12  0.03, compared to 0.97  0.02 and 0.05  0.02 conspecific densities (compared to the null model: for 83 locations. Although the number of locations per DAIC = 8.6, w = 0 for Norway and DAIC = 4.0, c i c individual differed depending on collar technology w = 0.12 for Sweden), allowing us to simultaneously (VHF = 64  3, range: 25–175; GPS = 230  12, range: study their effects on lynx HR size. 120–333), there was no effect of collar type on annual HR size (models including collar type compared to null mod- Statistical analyses els: DAIC = 3.4, w = 0.15). c i We calculated mating (February 1 to April 15; males: We used general linear mixed models with a Gaussian n = 18; females: n = 22) and nonmating season HRs error distribution using the “lme4” package (Bates et al. (April 16 to January 31; males: n = 28, females: n = 55). 2014) in R with log-transformed HR size as the response Although lynx mate in March, the annual and mating variable. Individual identity and year were fitted as ran- season HR calculations began in February to buffer dom effects in all models to account for repeated mea- potential premating behavioral changes just before mating surements. Log-transformed prey and conspecific density (i.e., searching for or guarding mates). For females, we indices were included as covariates together with their also calculated suckling (May 20 to September 30 repre- pairwise interactions with sex. Because of contrasting senting birth to end of lactation, n = 71) and rearing sea- management regimes in Sweden and Norway (i.e., lynx sonal HRs (May 20 to January 31 representing birth to population goals and hunting quotas), we also included independence: n = 44). country and the interaction between country and sex. Although prey and conspecific density varied between countries, there was no support for the interaction Prey and conspecific density indices between country and prey or conspecific densities on We used reported yearly number of hunted roe deer (i.e., annual HR size (Fig. 2; Table S1) so these interactions hunting bag) at the hunting district level in Sweden were not further considered. Furthermore, there was no (Swedish Association for Hunting and Wildlife Manage- support for additional latitudinal patterns in HR size not ment, available at: www.jagareforbundet.se) and munici- explained by prey or conspecific density (best model pality level in Norway (Statistics Norway, available at: including latitude DAIC = 22.2; variable relative impor- www.ssb.no) as a proxy for prey density (Appendix S1). tance weight for latitude = 0, cf. Table 1). For conspecific density, we used lynx monitoring results To test for seasonal HR size differences, we compared where density of lynx family groups (i.e., female with kit- mating and nonmating seasons (males and females) and tens) is estimated at a regional scale based on snow track- suckling and rearing seasons (females). For females, we ing in January and February each year (Linnell et al. initially included reproductive status as a three-level 2007). We calculated a HR-specific annual prey density explanatory factor (i.e., reproducing with surviving kit- index as the area-weighted average annual roe deer bag tens; reproducing but lost all kittens; nonreproducing). size across the hunting districts (Sweden) or municipali- However, there was no HR size differences between the ties (Norway) overlapping each annual HR (Sweden 13– two classes of reproducing females (models including kit- 123; Norway 0.5–81 shot roe deer per 10 km ). Similarly, ten survival compared to null models: DAIC = 1.75, 2960 ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. M. Aronsson et al. Determinants of Lynx Home Range Size Norway Sweden Candidate models were compared using the sample-size corrected Akaike information criterion (AIC ) and AIC weights (w ) from the “MuMIn” package (Barton 2013) in ● i R. Models with DAIC <2 were used to generate model- averaged parameter estimates (Burnham and Anderson 2002). We used a bootstrap method implemented in R using the “ez” package (Lawrence 2013) to calculate 95% confidence intervals for mixed models. We used AIC weights on the full candidate model set to generate rela- tive variable importance weights (RVI) for each explana- tory variable. Model residuals did not violate assumptions for normality, homogeneity of variance, and structure rel- ative to predictors. Means are presented with standard errors unless otherwise stated. Results Males Females Males Females There were clear sex-specific differences in annual HR size (90% isopleth males = 1045  66 km , range: 303– Figure 2. Country-specific mean (SE) prey density index (roe deer; 2290, n = 57; females = 483  35 km , range: 109–1853, squares), conspecific density index (triangles), and male and female n = 100), with range size dramatically decreasing with lynx home range size (circles). Estimates are based on raw data. increased intensity of space use for both sexes (80%, 70%, 60%, and 50% isopleth area (km ): 748  48, w = 0.29 for suckling season and DAIC = 4.55, i c 566  37, 432  29, and 325  22 for males and w = 0.09 for rearing season); therefore, we included 343  25, 255  19, 192  15, and 142  11 for female reproductive status as a two-level factor (repro- females). Total annual HR size for both males and ducing and nonreproducing). females was negatively related to conspecific density Table 1. Highest ranked candidate models relating annual lynx home range (HR) size (n = 157) to conspecific density (lynx; L), prey density (roe deer; R), country (C), latitude (Lat), sex (S; difference of females from males), and interactions (*). The 90% kernel isopleth represents the total HR and decreasing isopleth values represents an increasing intensity of HR use (Fig. 1). For each model, we show sample-size corrected AIC (AIC ), difference in AIC relative to the highest ranked model (DAIC ), and AIC weights (w ). For simplicity, only models with w > 0.01, univariate mod- c c i i els, and intercept-only models are shown. 90% isopleth, total HR 80% isopleth 70% isopleth 60% isopleth 50% isopleth Spatial scale Model AIC DAIC w AIC DAIC w AIC DAIC w AIC DAIC w AIC DAIC w c c i c c i c c i c c i c c i L + R + S + R*S 216.8 0.0 0.37 225.2 0.0 0.3 235.6 0.0 0.24 247.1 0.5 0.19 257.9 0.9 0.15 L + R + S 219.1 2.3 0.11 226.2 1.0 0.18 235.7 0.1 0.22 246.6 0.0 0.24 257.0 0.0 0.24 R + S + R*S 219.8 3.0 0.08 228.8 3.6 0.05 239.4 3.8 0.03 251.0 4.4 0.03 261.8 4.8 0.02 L + R + S + L*S + R*S 220.4 3.6 0.06 228.8 3.6 0.05 239.1 3.5 0.04 250.6 4.0 0.03 261.4 4.4 0.03 C + L + R + S + R*S 220.7 3.9 0.05 229.2 4.0 0.04 239.5 3.9 0.03 250.9 4.3 0.03 261.7 4.7 0.02 C + L + R + S + C*S 221.2 4.4 0.04 229.7 5.0 0.03 239.8 4.2 0.03 251.0 4.4 0.03 261.6 4.6 0.03 C + S + C*S 221.3 4.5 0.04 229.5 4.3 0.04 239.1 3.5 0.04 249.9 3.3 0.05 259.9 2.9 0.06 C + L + S + C*S 221.5 4.7 0.03 229.7 4.5 0.03 239.3 3.7 0.04 250.3 3.7 0.04 260.5 3.5 0.04 C + R + S + R*S 221.7 4.9 0.03 230.0 4.8 0.03 240.2 4.6 0.02 251.5 4.9 0.02 261.9 4.9 0.02 L + S 221.9 5.1 0.03 229.1 3.9 0.04 238.2 2.6 0.06 249.0 2.4 0.07 259.3 2.3 0.08 L + R + S + L*S 222.0 5.2 0.03 229.2 4.0 0.04 238.6 3.0 0.05 249.5 2.9 0.06 259.8 2.8 0.06 C + L + R + S 222.7 5.9 0.02 229.9 4.7 0.03 239.4 3.8 0.03 250.3 3.7 0.04 260.7 3.7 0.04 S 234.9 18.1 0.00 242.7 17.5 0.00 252.1 16.5 0.00 262.8 16.2 0.00 273.1 16.1 0.00 L 260.7 43.9 0.00 267.6 42.4 0.00 276.7 41.1 0.00 287.5 40.9 0.00 298.0 41.0 0.00 C 265.5 48.7 0.00 272.2 47.0 0.00 281.2 45.6 0.00 291.8 45.2 0.00 301.9 44.9 0.00 Intercept only 269.7 52.9 0.00 277.0 51.8 0.00 286.3 50.7 0.00 297.0 50.4 0.00 307.4 50.4 0.00 R 271.3 54.5 0.00 278.4 53.2 0.00 287.7 52.1 0.00 298.5 51.9 0.00 309.0 52.0 0.00 Lat 294.2 77.5 0.00 301.4 76.19 0.00 310.9 75.29 0.00 321.8 75.2 0.00 332.3 75.33 0.00 The models used for model average parameter estimates for each isopleth are indicated in boldface. ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. 2961 Home range size (km ) 0200 400 600 800 1000 1200 020 40 60 80 Prey density index Conspecific density index Determinants of Lynx Home Range Size M. Aronsson et al. (Fig. 3; Table 1). However, prey density affected female, Seasonal effects but not male total HR size, with HR decreasing with increasing prey density (Fig. 3). Although female total Contrary to our expectations, males’ HR size was smaller HRs (90% isopleth) were larger in Norway compared to during the mating compared to nonmating season 2 2 (789  68 vs. 1029  93 km ), while females’ HR size Sweden (Norway = 734  67 km , range; 225–1853, was larger during the mating season (647  112 vs. n = 39; Sweden = 322  108, range: 109–733, n = 61), this difference was explained by conspecific and prey den- 486  53 km ; Table 3). Reproducing females had smal- sity, and not by country (RVI: prey = 0.86, conspeci- ler HRs compared to nonreproducing females during fic = 0.81, country = 0.31; cf. Table 2). both suckling and rearing periods (Table S3). Prey density was not related to HR size during suckling, but it was negatively related to the rearing season HR size. Con- Sex-specific intensity of space use effects specific density was negatively related to female seasonal As predicted, both prey and conspecific density showed HR size, regardless of reproductive status (Table S3). spatial scale-dependent effects on HR size, with the largest difference in sex-specific effect of prey density on HR size Discussion at the 90% isopleth (Fig. 4; Table 1). For females, the negative effect of prey on range size decreased with By simultaneously examining prey and conspecific density increasing intensity of space use, while males showed the in a spatiotemporal context, we show that new insights opposite pattern with the negative effect of prey density can be found in the study of sex differences in spacing on range size becoming evident for high intensity of space behavior. The importance of being able to account for use (Fig. 4). For males, the proportion of the total HR both prey and conspecific density when studying HR size encompassed by the highest intensity of space use (50% should not be underestimated, as this allowed us to and 60% isopleths) decreased with increasing prey den- demonstrate that observed differences in total HR size sity, but this effect was not found for other isopleth area between Sweden and Norway (Fig. 2) were completely ratios (Fig. S1; Table S2). The negative relationship explained by different prey and conspecific densities. Fur- between conspecific density and HR size was evident for thermore, we show that the effect of prey density on total both sexes, but this effect did not decrease with increasing HR size is restricted to females, in contrast to a previous study that did not account for the confounding effects of intensity of space use (Fig. 4; Table 1). (A) (B) Males Females Figure 3. Sex-specific relationships between annual lynx home range size (km ; 90% fixed- kernel isopleth) and (A) prey density (i.e., roe deer), and (B) conspecific density. Model- averaged predictions derived from the highest ranked models from Table 1 are shown (solid lines = males, dashed lines = females) with associated 95% CIs (see Table 2 for parameter estimates), where all other explanatory variables were held at their mean values. Home range size predictions were back- –1 012345 0.0 0.4 0.8 1.2 1.6 transformed to their normal scale for the Log(prey density) Log(conspecific density) figure. 2962 ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. Home range size (km ) 0 200 400 600 800 1000 1200 1400 1600 0 200 400 600 800 1000 1200 1400 1600 M. Aronsson et al. Determinants of Lynx Home Range Size Table 2. Relative variable importance (RVI) and model-averaged parameter estimates with standard error (SE) for each variable retained in the best models for each HR isopleth in Table 1 (S = sex, R = prey density, L = conspecific density). 90% isopleth, total HR 80% isopleth 70% isopleth 60% isopleth 50% isopleth Parameter RVI Estimate SE RVI Estimate SE RVI Estimate SE RVI Estimate SE RVI Estimate SE Intercept 7.04 0.21 6.91 0.28 6.68 0.27 6.45 0.27 6.20 0.26 S 1.00 0.21 0.24 1.00 0.51 0.36 1.00 0.61 0.35 1.00 0.67 0.34 1.00 0.73 0.32 R 0.86 0.00 0.06 0.83 0.06 0.07 0.78 0.07 0.07 0.74 0.08 0.07 0.69 0.09 0.07 L 0.81 0.29 0.10 0.84 0.33 0.11 0.85 0.34 0.11 0.84 0.36 0.11 0.82 0.37 0.12 R*S 0.62 0.20 0.07 0.5 0.12 0.04 0.39 0.09 0.04 0.32 0.08 0.03 0.26 0.06 0.03 (A) (B) 10 1 2 3 4 5 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Figure 4. Sex-specific relationships between annual home range (HR) size (km ) and (A) prey density (i.e., roe deer), and (B) conspecific density for a range of isopleths (90, 80, 70, 60, and 50%) that represent increasing intensity of use of the HR (Fig. 1). The lines show model-averaged predictions for the different isopleth levels from Table 1, with all other explanatory variables kept at their mean values. HR size predictions were back- –1 0 1 2 3 4 5 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 transformed to their normal scale for the Log(prey density) Log(conspecific density) figure. For model parameters, see Table 2. conspecific density and found a negative relationship sity of space use increased within the HR (Fig. 4). This between roe deer density and total HR size for both male indicates that although food availability is a key driver of and female lynx (Herfindal et al. 2005). By assessing sex- total HR size for females, factors other than food define specific range size determinants as intensity of space use female space use in the more intensively used areas (e.g., increased within the HR, we could show that it is only at availability of den sites, or habitats that provide protec- higher isopleth levels (50–60%) that male space use is tion for females and their offspring from human intru- influenced by prey density. sion and intraguild predation; Kelt and Van Vuren 2001; Females’ total HR size decreased as prey density Basille et al. 2013; Rauset et al. 2013). Because areas that increased, supporting the expectation that females adapt provide protection and den sites are commonly in steep, their space use relative to the resources needed to survive rugged terrain or dense forest (Rauset et al. 2013), they and successfully reproduce (Sandell 1989). However, the may represent local habitats with little variation in prey influence of prey density on area use decreased as inten- density. Thus, although intensively used areas are often ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. 2963 Home range size (km ) Females Males 0 200 400 600 800 1000 1200 0 200 400 600 800 1000 1200 0 200 400 600 800 1000 1200 0 200 400 600 800 1000 1200 Determinants of Lynx Home Range Size M. Aronsson et al. Table 3. Full candidate models testing the influence of sex (S; differ- Contrary to our predictions, the effect of conspecific ence of females from males) and season (M; difference of mating sea- density did not change with intensity of space use for son from nonmating season) on lynx seasonal home range (HR) size. either sex (Fig. 4; Table 2) suggesting that intrasexual Seasonal HRs are estimated as the 90% fixed-kernel isopleth. Terms interactions may occur in the area between the 50% iso- are as in Table 1. pleth and the HR borders. For females, the negative Model AIC DAIC w c c i effect of conspecific density on HR size likely results from intrasexual competition (Maher and Lott 2000; S + M + S*M 1784 0.0 1.00 Benson et al. 2006). For males, however, the relationship S + M 1798 14 0.00 between HR size and conspecific density is probably dri- S 1807 23 0.00 M 1824 40 0.00 ven by two factors: that is, reduced maximum HR size Intercept only 1833 49 0.00 as conspecific density increases due to the cost of increased competition and increasing HR size at low Model parameter estimate (SE) for highest ranked model: Seasonal conspecific density to increase their encounters with home range size = 810  101  558  12 *S  217  100 *M + females. Total HR size of male lynx did not adapt to 282  133 * S*M. encompass a similar number of female HRs as conspeci- assumed to contain high and predictable prey densities fic density changed (Fig. 2), contrary to bobcats (Lynx (e.g., Maher and Lott 2000; Powell 2000), our results rufus) that exhibit an isometric relationship between show that this is not necessarily the case because it was male and female HRs (Ferguson et al. 2009). Instead, the size of the outer area of the females’ HR that the ratio between male and females’ HR size was posi- responded strongest to changes in prey density (Fig. 4; tively related to prey density in our study. Consequently, Table 2). This suggests that it is the less intensively used male lynx in areas with high prey density encounter areas (i.e., those relating to the total HR size) that are more females compared to males in low prey density critical for food provisioning. The fact that lynx select areas where males and females HRs are more similar in different habitats to rest during the day or between kills size. This suggests that male lynx have an upper bound compared to hunting (Bouyer et al. 2015) could explain for their HR size, likely due to the energetic costs of this decoupling of intensively used areas from prey maintaining large territories and increased risk of mor- density. tality associated with using unfamiliar areas that out- For males, that prey density did not affect total HR size weighs any additional fitness benefits of encountering supports the expectation that male large-scale space use is more females (Kelt and Van Vuren 2001). primarily driven by access to mates, not food (Sandell We found that males’ HR during the mating season 1989). However, a negative relationship between prey was smaller than during nonmating season, indicating density and male range size became visible with increasing that male lynx do not generally adopt a roaming mating intensity of space use due to energetic requirements tactic. We suggest that this behavioral pattern is because (Fig. 4). This is also supported by the proportion of the female Eurasian lynx [as well as Canadian lynx total HR included in the 50% isopleth area being nega- (L. canadensis) and Iberian lynx (L. pardinus)], contrary tively correlated with prey density for males but not to other felids, are strictly seasonal breeders due to a females (Fig. S1; Table S2). Furthermore, when males’ mono-estrous cycle (Jewgenow et al. 2014; Painer et al. area use was similar to females’ total HR size (i.e., males’ 2014). Hence, males move over smaller areas and interact 60% isopleth = 432  29 vs. females’ total HR more when they stay close to receptive females during a size = 483  35 km ), the interaction between prey den- short mating season, whereas they keep larger exclusive sity and sex was not included in the best model HRs during the rest of the year to reduce the presence of (Table 1). competing males before the mating season. This is also Our results show scale-dependent, sex-specific effects of supported by (1) observations of lethal male-male interac- different resources on spacing behavior, corresponding to tions during the mating season (Mattisson et al. 2013), the scale-dependent habitat selection suggested by Rettie (2) that male lynx only show moderate seasonal changes and Messier (2000) to reflect the hierarchy of fitness-lim- in hormonal levels related to reproductive capacity iting factors. At a finer spatial scale (within HR), the (Muller € et al. 2014), and (3) that male total annual HR importance of different space use determinants will be size is negatively affected by conspecific density but not conditional on the coarser scale (total HR) to maximize by prey density. an individual fitness (i.e., for females’ total HR = food Because the most energy-consuming activities for females are lactation and feeding young (Gittleman and requirements, 50% isopleth = shelter/protection; for males’ total HR = access to females, 50–60% isopleth = Thompson 1988), there is an expectation that prey den- food requirements). sity effects on HR size should be strongest during these 2964 ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. M. Aronsson et al. Determinants of Lynx Home Range Size critical periods of high energetic requirements (Sandell Conflict of Interest 1989). However, females with kittens had consistently smaller seasonal HRs than nonreproducing females, and None declared. the effect of prey density on HR size was similar for reproducing and nonreproducing females at both seasonal Data Accessibility and annual time scales. Thus, reductions in HR size for reproducing females during suckling is likely due to Relevant data for this study will be archived in the Dryad young, dependent kittens limiting the mother’s mobility Digital Repository conditional on acceptance. (Dahle and Swenson 2003) as well as female lynx avoiding human disturbance during this period (White et al. References 2015). That nonreproducing females did not reduce their Adams, E. S. 2001. Approaches to the study of territory size HR size during summer despite an increase in prey avail- and shape. Annu. Rev. Ecol. Syst. 32:277–303. ability (i.e., small prey and domestic sheep; Odden et al. Andren, H., J. D. C. Linnell, O. Liberg, R. Andersen, A. 2006, 2013; Gervasi et al. 2014) suggests that nonrepro- Danell, J. Karlsson, et al. 2006. Survival rates and causes of ducing female HR size is regulated by prey availability mortality in Eurasian lynx in multi-use landscapes. Biol. during the winter. Conserv. 131:23–32. Our results highlight the importance of simultaneously Arnemo, J. M., A. Evans, and A. Fahlman. 2012. Biomedical considering resources and intraspecific interactions as protocols for free-ranging brown bears, grey wolves, determinants of animal spacing patterns. By examining wolverines and lynx. Available at: http://www1.nina.no/ variation in intensity of space use, instead of only focus- RovviltPub/pdf/Biomedical%20Protocols%20Carnivores% ing on total HR and/or an arbitrarily chosen core area 20March%202012.pdf (usually 50- or 30% isopleth for kernel HR estimations; Barton,  K. 2013. MuMIn: multi-model inference, R package Vander Wal and Rodgers 2012), we show that large version 1.9.13. http://CRAN.R-project.org/package=MuMIn knowledge gains are still to be made in the study of spac- Basille, M., B. Van Moorter, I. Herfindal, J. Martin, J. D. C. ing behavior. We recommend a spatiotemporal approach Linnell, J. Odden, et al. 2013. Selecting habitat to survive: be used in future HR studies, as it highlights how the use the impact of road density on survival in a large carnivore. of different resources varies in importance within an ani- PLoS One 8:e65493. mal’s HR. Consequently, factors that may not be related Bates, D., M. Maechler, B. Bolker, and S. Walker. 2014. lme4: to total HR size still may be important determinants in linear mixed-effects models using Eigen and S4, R package animal spatial ecology. In turn, this will lead to better version 1.1-6. http://CRAN.R-project.org/package=lme4 models of ecological systems to both inform theory and van Beest, F. M., I. M. Rivrud, L. E. Loe, J. M. Milner, and A. management. Mysterud. 2011. What determines variation in home range sizes across spatio-temporal scales in a large browsing herbivore? J. Anim. Ecol. 80:771–785. Acknowledgments Benson, J. F., M. J. Chamberlain, and B. D. Leopold. 2006. The study is conducted within the Scandinavian Lynx Regulation of space use in a solitary felid: population Project, Scandlynx (http://scandlynx.nina.no/) and would density or prey availability? Anim. Behav. 71:685–693. not have been possible without the help from a large Borger, € L., N. Franconi, F. Ferretti, F. Meschi, G. De Michele, number of fieldworkers and students. Funding is from the A. Gantz, et al. 2006a. An integrated approach to identify Swedish Environmental Protection Agency, Norwegian spatiotemporal and individual-level determinants of animal Environment Directorate, the Swedish Research Council home range size. Am. Nat. 168:471–485. Formas, the Research Council of Norway the Norwegian Borger, € L., N. Franconi, G. De Michele, A. Gantz, F. Meschi, Institute for Nature Research, the Swedish Association for A. Manica, et al. 2006b. Effects of sampling regime on the Hunting and Wildlife Management, WWF-Sweden and mean and variance of home range size estimates. J. Anim. “Marie-Claire Cronstedts” foundations, the County Ecol. 75:1393–1405. Governor’s Office for Hedmark, Oslo and Akershus, Øst- Bouyer, Y., G. San Martin, P. Poncin, R. C. Beudels-Jamar, J. fold, Oppland, Buskerud, Vestfold, and Telemark Coun- Odden, and J. D. C. Linnell. 2015. Eurasian lynx habitat ties, the Carnivore Management Boards in regions 2, 3, selection in human-modified landscape in Norway: effects of and 4 and 8, the municipalities of Trysil, Fl a, Gol, Hjart- different human habitat modifications and behavioral states. Biol. Conserv. 191:291–299. dal, Nes, Nore og Uvdal, Rollag, Sauherad, Tinn, and Al. We thank A. Danell for compiling all roe deer hunting Burnham, K. P., and D. R. Anderson. 2002. Model selection data needed for this study and A. Ordiz and E. Nilsen for and multimodel inference, 2nd edn. Springer-Verlag, valuable comments on the article. New York. ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. 2965 Determinants of Lynx Home Range Size M. Aronsson et al. Calenge, C. 2006. The package adehabitat for the R software: a Jewgenow, K., J. Painer, O. Amelkina, M. Dehnhard, and F. tool for the analysis of space and habitat use by animals. Goeritz. 2014. Lynx reproduction – long-lasting life cycle of Ecol. Model. 197:516–519. corpora lutea in a feline species. Reprod. Biol. 14:83–88. Campioni, L., M. del Mar Delgado, R. Lourenco, G. Johnson, D. H. 1980. The comparison of usage and availability Bastianelli, N. Fernandez, and V. Penteriani. 2013. measurements for evaluating resource preference. Ecology Individual and spatio-temporal variation in the home range 61:65–71. behavior of a long-lived, territorial species. Oecologia Kelt, D. A., and D. H. Van Vuren. 2001. The ecology and 172:371–385. macroecology of mammalian home range area. Am. Nat. Campos, F. A., M. L. Bergstrom, A. Childers, J. D. Hogan, K. 157:637–645. M. Jack, A. D. Melin, et al. 2014. Drivers of home range Kie, J. G., J. Matthiopoulos, J. Fieberg, R. A. Powell, F. characteristics across spatiotemporal scales in a Neotropical Cagnacci, M. S. Mitchell, et al. 2010. The home-range primate, Cebus capucinus. Anim. Behav. 91:93–109. concept: are traditional estimators still relevant with modern Carbone, C., N. Pettorelli, and P. A. Stephens. 2011. The bigger telemetry technology? Philos. Trans. R. Soc. Lond. B Biol. they come, the harder they fall; body size and prey abundance Sci. 365:2221–2231. influence predator-prey ratios. Biol. Lett. 7:312–315. Kie, J. G. 2013. A rule-based ad hoc method for selecting a Chapron, G., P. Kaczensky, J. D. C. Linnell, M. von Arx, D. bandwidth in kernel home-range analyses. Anim. Biotelem. Huber, H. Andren, et al. 2014. Recovery of large carnivores 2013:13. in Europe’s modern human-dominated landscapes. Science Lawrence, M. A. 2013. ez: Easy analysis and visualization of 346:1517–1519. factorial experiments, R package version 4.2-2. http:// Clutton-Brock, T., and P. H. Harvey. 1978. Mammals, CRAN.R-project.org/package=ez resources and reproductive strategies. Nature 273:191–195. Linnell, J. D. C., P. Fiske, I. Herfindal, J. Odden, H. Brøseth, Clutton-Brock, T., and B. C. Sheldon. 2010. Individuals and and R. Andersen. 2007. An evaluation of structured snow- populations: the role of long-term, individual-based studies track surveys to monitor Eurasian lynx populations. Wildlife of animals in ecology and evolutionary biology. Trends Ecol. Biol. 13:456–466. Evol. 25:562–573. Linnell, J. D. C., H. Brøseth, J. Odden, and E. Nilsen. 2010. Dahle, B., and J. E. Swenson. 2003. Home ranges in adult Sustainable harvesting a large carnivore? Development of Scandinavian brown bears (Ursus arctos): effect of mass, sex, Eurasian lynx populations in Norway during 160 years of reproductive category, population density and habitat type. shifting policy. Environ. Manage. 45:1142–1154. J. Zool. Lond. 260:329–335. Lopez-Bao,  J. V., F. Palomares, A. Rodrıguez, and M. Emlen, S. T., and L. W. Oring. 1977. Ecology, sexual Delibes. 2010. Effects of food supplementation on home- selection, and the evolution of mating systems. Science range size, reproductive success, productivity and 197:215–223. recruitment in a small population of Iberian lynx. Anim. Ferguson, A. W., N. A. Currit, and F. W. Weckerly. 2009. Conserv. 13:35–42. Isometric scaling in home-range size of male and female Lopez-Bao, J. V., A. Rodrıguez, M. Delibes, J. M. Fedriani, bobcats (Lynx rufus). Can. J. Zool. 87:1052–1060. J. Calzada, P. Ferreras, et al. 2014. Revisiting food-based Gaillard, J.-M., E. B. Nilsen, J. Odden, H. Andren, and J. D. C. models of territoriality in solitary predators. J. Anim. Ecol. Linnell. 2014. One size fits all: Eurasian lynx females share a 83:934–942. common optimal litter size. J. Anim. Ecol. 83:107–115. Maher, C. R., and D. F. Lott. 2000. A review of ecological Gervasi, V., E. B. Nilsen, J. Odden, Y. Bouyer, and J. D. C. determinants of territoriality within vertebrate species. Am. Linnell. 2014. The spatial-temporal distribution of wild and Midl. Nat. 143:1–29. domestic ungulates modulates lynx kill rates in a multi-use Marzluff, M., J. J. Millspaugh, P. Hurvitz, and M. S. landscape. J. Zool. 292:175–183. Handcock. 2004. Relating resources to a probabilistic Gittleman, J. L., and S. D. Thompson. 1988. Energy allocation measure of space use: forest fragments and Steller’s Jays. in mammalian reproduction. Am. Zool. 28:863–875. Ecology 85:1411–1427. Godsall, B., T. Coulson, and A. F. Malo. 2014. From Mattisson, J., J. Persson, H. Andren, and P. Segerstrom. € 2011. physiology to space use: energy reserves and Temporal and spatial interactions between an obligate androgenization explain home-range size variation in a predator, the Eurasian lynx, and a facultative scavenger, the woodland rodent. J. Anim. Ecol. 83:126–135. wolverine. Can. J. Zool. 89:79–89. Herfindal, I., J. D. C. Linnell, J. Odden, E. B. Nilsen, and R. Mattisson, J., P. Segerstrom, € J. Persson, M. Aronsson, G. R. Andersen. 2005. Prey density, environmental productivity Rauset, G. Samelius, et al. 2013. Lethal male-male and home-range size in the Eurasian lynx (Lynx lynx). interactions in Eurasian lynx. Mamm. Biol. 78:304–308. J. Zool. 265:63–71. McLoughlin, P. D., and S. H. Ferguson. 2000. A hierarchical Jetz, W., C. Carbone, J. Fulford, and J. H. Brown. 2004. The pattern of limiting factors helps explain variation in home scaling of animal space use. Science 306:266–268. range size. Ecoscience 7:123–130. 2966 ª 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. M. Aronsson et al. Determinants of Lynx Home Range Size McNab, B. K. 1963. Bioenergetics and the determination of differences in habitat selection between sympatric large home range size. Am. Nat. 97:133–140. carnivores. Oecologia 172:701–711. Ministry of the Environment. 2003. Rovvilt i norsk natur Rettie, W. J., and F. Messier. 2000. Hierarchical habitat [Carnivores in Norwegian nature]. Stortingsmelding 15 selection by woodland caribou: its relationship to limiting (2003–2004) [In Norwegian]. factors. Ecography 23:466–478. Mitchell, M. S., and R. A. Powell. 2004. A mechanistic home Samelius, G., H. Andren, O. Liberg, J. D. C. Linnell, J. Odden, range model for optimal use of spatially distributed re- P. Ahlqvist, et al. 2011. Spatial and temporal variation in sources. Ecol. Model. 177:209–232. natal dispersal by Eurasian lynx in Scandinavia. J. Zool. Morales, J. M., P. R. Moorcroft, J. Matthiopoulos, J. L. Frair, 286:120–130. J. G. Kie, R. A. Powell, et al. 2010. Building the bridge Sandell, M. 1989. The mating tactics and spacing patterns of between animal movement and population dynamics. solitary carnivores. Pp. 64–82 in J. L. Gittelman, ed. Philos. Trans. R. Soc. Lond. B Biol. Sci. 365:2289–2301. Carnivore behavior, ecology, and evolution. Cornell Univ. Morellet, N., C. Bonenfant, L. Borger, F. Ossi, F. Cagnacci, M. Press, New York. Heurich, et al. 2013. Seasonality, weather and climate affect SEPA; Swedish Environmental Protection Agency. 2013. home range size in roe deer across a wide latitudinal Nationell forvaltningsplan € for € lodjur 2013-2017. [National gradient within Europe. J. Anim. Ecol. 82:1326–1339. management plan for lynx 2013-2017]. ISBN 978-91-620- Muller, € K., S. Koster, J. Painer, A. Soderberg, € D. Gavier- 8648-0. [In Swedish]. Arkitektkopia, Bromma, Sweden. Widen, E. Brunner, et al. 2014. Testosterone production and Vander Wal, E., and A. R. Rodgers. 2012. An individual-based spermatogenesis in free-ranging Eurasian lynx (Lynx lynx) quantitative approach for delineating core areas of animal throughout the year. Eur. J. Wildl. Res. 60:569–577. space use. Ecol. Model. 224:48–53. Nilsen, E. B., J. D. C. Linnell, J. Odden, G. Samelius, and H. White, S., R. A. Briers, Y. Bouyer, J. Odden, and J. D. C. Andren. 2011. Patterns of variation in reproductive Linnell. 2015. Eurasian lynx natal den site and parameters in Eurasian lynx (Lynx lynx). Acta Theriol. maternal home range selection in multiple-use landscapes. 57:217–223. J. Zool. 297:87–98. Odden, J., J. D. C. Linnell, and R. Andersen. 2006. Diet of Worton, B. J. 1989. Kernel methods for estimating the Eurasian lynx in the boreal forest of southeastern Norway: utilization distribution in home range studies. Ecology the relative importance of livestock and hares at low roe 70:164–168. deer density. Eur. J. Wildl. Res. 52:237–244. Odden, J., E. B. Nilsen, and J. D. C. Linnell. 2013. Density of Supporting Information wild prey modulates lynx kill rates on free-ranging domestic sheep. PLoS One 8:e79261. Additional Supporting Information may be found in the Painer, J., K. Jewgenow, M. Dehnhard, J. M. Arnemo, J. D. C. online version of this article: Linnell, J. Odden, et al. 2014. Physiologically persistent Appendix S1. The use of yearly roe deer hunting bags as corpora lutea in Eurasian Lynx-Longitudinal ultrasound and proxy for roe deer density. endocrine examinations intra-vitam. PLoS One 9:e90469. Figure S1. Proportion of 90% isopleth area included in Pelton, M., and F. van Manen. 1996. Benefits and pitfalls of the 50% isopleth for male in relation to prey density long-term research: a case study of black bears in Great index. Smoky Mountains National Park. Wildl. Soc. Bull. Table S1. Model selection relating lynx annual home 24:443–450. range size to (a) the interaction between country and prey Powell, R. A. 2000. Home ranges, territories, and home range density index and (b) the interaction between country estimators. Pp. 65–110 in L. Boitani and T. Fuller, eds. and conspecific density index. Techniques in animal ecology: uses and misuses. Columbia Table S2. Model selection relating sex-specific annual Univ. Press, New York. home range isopleth area-ratios to prey density index and R Development Core Team. 2010. R: a language and country. environment for statistical computing. R Foundation for Table S3. Model selection relating lynx female seasonal Statistical Computing, Vienna, Austria. http://www.R- home range size to reproductive status, prey density, con- project.org. (accessed August 1, 2011). Rauset, G. R., J. Mattisson, H. Andren, G. Chapron, and J. specific density and country. Persson. 2013. When species’ ranges meet: assessing ª 2016 The Authors. 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