OR I G I NA L R E S EAR CH The use of anthropogenic areas helps explain male brown bear movement rates and distance travelled during the mating season D. Falcinelli1,2 , M. del Mar Delgado2, I. Kojola3, S. Heikkinen3, C. Lamamy4 & V. Penteriani5 1Department of Environmental Biology (DBA), Sapienza University of Rome, Roma, Italy 2Biodiversity Research Institute (IMIB, CSIC–University of Oviedo–Principality of Asturias), Mieres, Spain 3Natural Resources Institute Finland (LUKE), Rovaniemi, Finland 4Forest is life, TERRA Research Unit, Gembloux Agro-Bio Tech, University of Liege, Gembloux, Belgium 5Department of Evolutionary Ecology, National Museum of Natural Sciences (MNCN), Spanish National Research Council (CSIC), Madrid, Spain Keywords brown bear; Ursus arctos; mating; movement patterns; movement ecology; step-selection analysis; multi-use landscape; human-modified landscape. Correspondence Daniele Falcinelli, Sapienza University of Rome, 5 Piazzale Aldo Moro, 00185 Roma, Italy. Email: daniele.falcinelli@gmail.com Vincenzo Penteriani, National Museum of Natural Sciences (MNCN), 2 c/Jose Gutierrez Abascal, 28006 Madrid, Spain. Email: v.penteriani@csic.es Editor: Femke Broekhuis Associate Editor: Craig Jackson and Stephanie Periquet Received 22 February 2023; revised 5 June 2024; accepted 25 June 2024 doi:10.1111/jzo.13199 Abstract During the reproductive period, mating strategies are a significant driver of adapta- tions in animal behaviour. For instance, for polygamous species, greater movement rates during the mating season may be advantageous due to the increased probabil- ity of encountering several potential mates. The brown bear Ursus arctos is a soli- tary carnivore that lives at low densities, with a polygamous mating system and an extended mating season of nearly 3 months. Here, we hypothesized that male brown bears may show changes in movement patterns and space-use behaviour during their mating season. Using long-term (2002–2013) telemetry data from the Finnish Karelia male population (n = 24 individuals; n = 10 688 GPS locations), we first analysed daily movement metrics, that is, speed, net and total distance with respect to the period (mating vs. post-mating) and several environmental predictors. Then, we conducted a step-selection analysis for each of these periods. Throughout the year, male bears selected forested/shrub habitats and increased movement rates near main roads. During the mating season, reproductive needs seem to trigger roaming behaviour in adult males to maximize encounter rates with potential recep- tive females. However, all movement metrics increased within areas of high human activity, suggesting a bear response to a higher risk perception while using those areas. During the post-mating period, overlapping with the bear hyperphagia and the hunting season, males selected anthropogenic areas farther from main roads and trails, suggesting a trade-off between foraging opportunities and risk avoidance. Introduction Most organisms undergo seasonal changes in behaviour (Cooke et al., 2014; Simpson & Balsam, 2016). For instance, during the reproductive period, the diverse needs associated with mat- ing can drive significant changes in animal behaviours (Goode- nough et al., 2009). In particular, male mammals exhibit many mating-related behaviours during this period, such as agonistic vocalizations, mate-guarding (associated with a reduction in foraging efficiency), increased territoriality, and roaming behav- iour (e.g., Clutton-Brock, 1989; Clutton-Brock & Albon, 1979; Girard-Buttoz et al., 2014; Marino, 2012). Mammals show a great variability in mating systems (Clutton-Brock, 1989), such as monogamy, that is, males and females bonded to a single partner (Ribble, 1991), polygyny, that is, males mate with multiple females (Clutton-Brock & Albon, 1979), and polygamy/promiscuity, that is, males and females mate with multiple partners (Boonstra et al., 1993). Despite this variation, most mammals are polygynous (Clutton- Brock, 1989), and large ranges and greater movements during the mating season may be advantageous because of the increased probability of encountering several different or asyn- chronously receptive mates (Clutton-Brock, 1989; Shuster & Wade, 2003). Whereas the reproductive success of females is usually limited by the number of offspring they can produce and rear, that of males, in the absence of parental care, is instead proportional to the number of females with which they mate and successfully fertilize (Clutton-Brock & Harvey, 1978; Journal of Zoology  (2024) – ª 2024 The Author(s). Journal of Zoology published by John Wiley & Sons Ltd on behalf of Zoological Society of London. 1 This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. Journal of Zoology. Print ISSN 0952-8369 Shuster & Wade, 2003). Consequently, roaming widely in search of receptive mates (i.e., roaming-to-mate) is a behaviour exhibited primarily by males in order to improve their fitness (Clutton-Brock, 1989). Several mammalian taxa with a polygy- nous/promiscuous mating system, and where females range more or less widely and unpredictably (sensu Clutton- Brock, 1989), show an increase in their roaming behaviour, including marsupials, rodents, ungulates, and carnivores (e.g., Edelman & Koprowski, 2006; Fisher & Lara, 1999; Foley et al., 2015; Graw et al., 2019). Outside the reproductive sea- son, animals prevalently shift their focus from mating to pro- curing food, with spacing and the size of male ranges being no longer determined by the availability and spatial distribution of receptive mates but by, for example, the spatial abundance of food (Erlinge & Sandell, 1986). Animal movement and space use can be influenced by vari- ous external factors, including food and shelter availability, landscape structure, habitat characteristics, and anthropogenic activities (del Mar Delgado et al., 2010; Martin et al., 2013; Nathan et al., 2008). Landscape and habitat features can partic- ularly impact animal movement behaviour during different times of the year, including the reproductive season. For instance, during this period, male red pandas Ailurus fulgens were found to travel longer daily distances while avoiding roads and small-habitat patches with low forest cover (Bista et al., 2021). Additionally, male polecats Mustela putorius demonstrated a preference for riparian habitats and ponds, which facilitated their increased movements while searching for mates (Rondinini et al., 2006). In such context, understand- ing how landscape characteristics can alter animal movement patterns during biologically sensitive periods like mating may have important implications from both management and con- servation perspectives, especially within human-modified land- scapes (e.g., Martin et al., 2013; Moriarty et al., 2016). Actually, the distribution range of many mammalian species is characterized by high human densities, widespread human activities, and infrastructures, such as urban development and dense networks of transport infrastructures (Morales-Gonzalez et al., 2020; Penteriani et al., 2020), which cause increased mortality and multiple human-driven disturbances in move- ments and rhythms of activity (Bischof et al., 2009; Ordiz et al., 2017). The brown bear Ursus arctos is a solitary carnivore that lives at relatively low densities and has an extended mating season lasting for ~3 months from May to July (Swenson et al., 2021, 2023). Moreover, brown bears are polygamous, that is, individuals of both sexes mate a variable number of times with a variable number of partners during a given mat- ing season (Steyaert et al., 2012; Swenson et al., 2021, 2023). Thus, male bear movement behaviour and space-use have the potential to be strictly related to mating needs. To date, how- ever, few studies have directly related movement patterns to male mating behaviour (Dahle & Swenson, 2003a, 2003b; Edwards & Derocher, 2015). Thus, our main aim here is to integrate movement data with remotely sensed environmental data to explore the potential consequences of brown bear mat- ing needs on their movements. Using long-term telemetry data from the Finnish Karelia brown bear population, we hypothesize that male brown bears may show changes in both movement and space-use patterns during their mating season due to attempts to maximize suc- cessful reproduction, that is, finding mates. Thus, we have first derived multiple daily movement metrics (i.e., speed, net and total distance displaced) and analysed them via linear mixed- effects models (LMMs) with respect to the period (mating vs. post-mating) and several predictors describing daily bear habi- tat use. Second, in order to better investigate how landscape structure affects seasonal bear movement, we have performed a step-selection analysis based on (mixed) conditional logistic regression (Fortin et al., 2005; Thurfjell et al., 2014) for mat- ing and post-mating seasons. Firstly, we predict that males would show greater daily dis- placements and faster movements to cover more ground during the mating season compared with the post-mating period to increase the chance of encountering a receptive mate (prediction 1). Further, we expect that males would show more risky behav- iours during mating than in the post-mating season. Indeed, brown bears usually tend to avoid areas with higher human activ- ity, infrastructure, and consequent disturbance (e.g., de Gabriel Hernando et al., 2020; Martin et al., 2010; Nellemann et al., 2007; Preatoni et al., 2005; Rode et al., 2006), a proxy of risky areas (Morales-Gonzalez et al., 2020). However, the roaming-to-mate need for males might be stronger than avoid- ance of sources of human disturbance. Thus, we predict the mat- ing season to have higher movement parameters than the post-mating season, and this is further enhanced by human-derived risk via human presence, activity, and infrastruc- ture (prediction 2). Finally, we predict that male bears would use more disturbed habitats, that is, with higher human activity and disturbance, during mating than post-mating (prediction 3). Materials and methods Study area Our study area encompassed a large part of central-eastern and southern Finland, covering about 220 000 km2 (Fig. 1). The elevation ranges from 100 to 576 m a.s.l., although around 80% of the surface area consists of low-lying land below 200 m in altitude. Forests cover ~75% of the study area: located in the boreal vegetation zone, they are composed mainly of coniferous Scots pine Pinus sylvestris and Norway spruce Picea abies, mixed with broad-leaved species, such as birches Betula spp., alders Alnus spp., and European aspen Populus tremula (Ahti et al., 1968). The landscape is also characterized by the extensive presence of lakes and wetlands, that is, swamps, marshes, and peat bogs. Human population density averages ~17 inhabitants/km2, which is nearly three times lower in eastern Finland compared with southern Finland (https://www.tilastokeskus.fi/tup/suoluk/suoluk_vaesto_en.html). High-traffic roads are scarce throughout the study area, but a developed network of low-traffic roads allows humans easy access to bear habitats (Penteriani et al., 2021). The brown bear population in Finland has increased and expanded during 2 Journal of Zoology  (2024) – ª 2024 The Author(s). Journal of Zoology published by John Wiley & Sons Ltd on behalf of Zoological Society of London. Movements of male brown bears during mating D. Falcinelli et al. 14697998, 0, D ow nloaded from https://zslpublications.onlinelibrary.w iley.com /doi/10.1111/jzo.13199 by Duodecim Medical Publications Ltd, W iley Online Library on [01/08/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on W iley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License recent decades, and it has now recovered some degree of con- nectivity with the Scandinavian population (Kopatz et al., 2021). Bear captures and movement data collection From 2002 to 2013, we captured 71 brown bears throughout our study area and Russian Karelia, that is, 115 total captures, with some individuals captured several times (2002: n = 9; 2003: n = 6; 2004: n = 13; 2005: n = 7; 2006: n = 6; 2007: n = 7; 2008: n = 7; 2009: n = 9; 2010: n = 17; 2011: n = 16; 2012: n = 15; 2013: n = 3), but for the purpose of this study, we used only the GPS locations of adult males within Finland (n = 10 688 locations, denning period excluded; n = 24 indi- viduals; mean number of locations per individual  SD = 427  347). However, we decided not to remove bear resting or bed sites (i.e., inactive locations) or short-distance consecutive steps from the analysis for two main reasons: (a) resting or inactivity is part of the bear life and movement strategy of individuals, thus they should not be removed if the aim is to analyse movement patterns in their totality. For example, speed without resting would not really represent the velocity of bear displacements but only a less interesting parameter as bear speed when moving; and (b) Figure 1 The study area is located in central and eastern Finland. The hatched surfaces indicate areas where the GPS locations (2002–2013) of male brown bears (n = 24) are distributed. Red surfaces identify anthropogenic areas, as defined by the CORINE Land Cover 2012 (see Table S1). Basemap credits: © 2009 Esri – World Shaded Relief. Journal of Zoology  (2024) – ª 2024 The Author(s). Journal of Zoology published by John Wiley & Sons Ltd on behalf of Zoological Society of London. 3 D. Falcinelli et al. Movements of male brown bears during mating 14697998, 0, D ow nloaded from https://zslpublications.onlinelibrary.w iley.com /doi/10.1111/jzo.13199 by Duodecim Medical Publications Ltd, W iley Online Library on [01/08/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on W iley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License because inactive locations are present in both phases (mating vs. post-mating), resting or inactivity would not be contaminat- ing movement analyses. The details of capture and anaesthetization have been pro- vided in previous studies (i.e., Lamamy et al., 2022; Penteriani et al., 2021). Bears were sexed and weighed, and we extracted the first premolar for age estimation by counting annual cementum layers. Bears were considered adults at the age of 5; males usually reach sexual maturity at 4–5 years, and youn- ger males may still be in a dispersal phase (Støen, 2006). We equipped each individual with a collar carrying a 1.5-kg Global Positioning System (GPS) transmitter (Televilt, Lindes- berg, Sweden; Vectronic Aerospace GmbH, Berlin, Germany). The weight of the collars was <0.5–1.0% of adult males (mean  SD = 212  61 kg). Collars had a pre-programmed drop-off mechanism with an average battery life of 1 year. Whenever the mechanism did not work on schedule due to technical flaws, we recaptured the bear to remove the collar. Regardless, we removed all collars before the end of the pro- ject in 2014. The capture, handling, anaesthetizing, and collar- ing of bears met the guidelines issued by the Animal Care and Use Committee at the University of Oulu and permits were provided by the provincial government of Oulu and the Regional State Administrative Agency (OYEKT-6-99, OLH- 01951/Ym-23, ESAVI/3229/04.10.07/2013). The GPS fix rate varied roughly from 1 to 4 h (6–24 loca- tions/day; see also Lamamy et al., 2022; Penteriani et al., 2021, 2022). Signals from the satellite transmitters were recorded by the ARGOS satellite system (https://www.cls.fr/en/ cls-group/). We recorded the positional dilution of precision (PDOP) value for all 3-D fixes and the horizontal dilution of precision for 2-D fixes. We excluded all 2-D fixes according to the procedure of D’Eon et al. (2002). While this data-screening method reduces the dataset, it allows for a high detection percentage of large location errors (Bjørneraas et al., 2010). Digital environmental data To investigate the characteristics of the landscape where male bears moved, we selected a set of topographic, landcover, and human disturbance variables. All environmental variables were derived from free-downloadable spatial datasets (see Table S1 for all details), converted to raster layers with a spatial resolu- tion of 100 m, and reprojected into a common Coordinate Ref- erence System (i.e., EPSG: 3067 – ETRS89/TM35FIN(E,N) – Finland). We used a Digital Terrain Model (DTM) to derive a Terrain Ruggedness Index (TRI) using the R package spatialEco (Evans & Murphy, 2023). Terrain Ruggedness Index was cal- culated by taking the square root of the sum of squared differ- ences in elevation of each DTM grid cell to its eight neighbours (Riley et al., 1999). To characterize land use, we subsumed the classification of the CORINE Land Cover 2012 into six categories considered to be relevant for brown bear ecology in our study area: (1) anthropogenic areas, that is, all surfaces altered by humans, including urban areas, man-made infrastructures, and agricultural areas; (2) mixed-deciduous for- est; (3) coniferous forest; (4) natural open areas, that is, grass- lands, moors, and all wetland areas; (5) shrubland; and (6) water bodies. Afterward, we transformed each landcover cate- gory of interest (i.e., all except water bodies; Barry et al., 2020; Van de Walle et al., 2019) into a binary raster layer, indicating the presence (1) or absence (0) of that cate- gory. For all binary layers, we thus calculated the proportion of category occupancy within a circular moving window with a 1300-m radius around every raster grid cell (i.e., proportional coverages). The radius value was chosen based on the average 4-h step length pooled over all individuals (i.e., 1273 meters, see below). As for human disturbance variables, we first reclassified the linear infrastructure network into (1) main roads (i.e., paved roads and from two to four lanes; average density within the study area: 0.25 km/km2); (2) secondary roads (i.e., paved and unpaved roads with one lane; average density: 1.09 km/km2); and (3) human trails (average density: 0.06 km/ km2). We then rasterized the shapefile layers and, through proximity analysis, derived the four distance variables (Table S1), that is, distance (in meters) from main roads (DMR), secondary roads (DSR), human trails (DHT), and human settlements (DHS). The processing and calculation of all rasters were carried out with the software R version 4.0 (R Core Team, 2023), QGIS version 3.3 (QGIS Development Team, 2023), and GRASS GIS version 8.2 (GRASS Develop- ment Team, 2022). Linear mixed models for movement metrics Data preparation: Daily movement parameters To analyse seasonal variation in movement patterns, we first prepared a consistent dataset by resampling GPS locations at a 4-h fix rate, and we then calculated daily bear trajectories through the R package adehabitatLT (Calenge, 2006). To deal with missing data and since we did not have high-resolution environmental data for the neighbouring Russian Karelia (see above and Barry et al., 2020), we only kept complete daily tra- jectories (i.e., with six locations) within the Finnish territory. Further, we excluded daily trajectories where the daily net dis- tance was zero to deal with days of complete inactivity. For each retained daily trajectory, we next estimated three movement parameters: (1) daily net distance, the distance trav- elled between the initial position and the final position on a daily scale; (2) daily total distance, the cumulative sum of the distance between successive relocations on the same daily tra- jectory; and (3) daily average speed, the daily mean of the step distance (i.e., the displacement between two consecutive relo- cations) divided by the time interval between consecutive loca- tions. We calculated both net and total daily distance because these might be very different (Austin et al., 2004; Rittenhouse & Semlitsch, 2006). On a daily scale, an individual could actu- ally move even considerably while remaining roughly in the same area, thus ending its daily trajectory close to its initial position. In this case, net displacement will be very short, but the total distance travelled might be very large. 4 Journal of Zoology  (2024) – ª 2024 The Author(s). Journal of Zoology published by John Wiley & Sons Ltd on behalf of Zoological Society of London. Movements of male brown bears during mating D. Falcinelli et al. 14697998, 0, D ow nloaded from https://zslpublications.onlinelibrary.w iley.com /doi/10.1111/jzo.13199 by Duodecim Medical Publications Ltd, W iley Online Library on [01/08/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on W iley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Lastly, for each retained trajectory, we derived the selected environmental variables on a daily scale. We thus extracted the entire set of environmental information at each spatial location and calculated the daily average value for all (quantitative) variables. Statistical analysis In a first exploratory step, all environmental variables were screened for collinearity using a Pearson’s correlation coeffi- cient threshold of r > |0.6| (Hosmer & Lemeshow, 2000). The only pair of correlated variables was the distance from human settlements with that from main roads (r = 0.66); we conse- quently excluded the distance to settlements variable from the analyses (see below). For each of the three movement parameters estimated at a daily scale (i.e., daily net distance, daily total distance, and daily average speed), we built a global linear mixed-effects model (LMM) using the R package nlme (Pinheiro et al., 2023). Visual analysis of residuals was first performed for each global model to check for model assumptions and the presence of outliers. After the log-transformation of our response variables, model residuals were normally distributed, and we thus fitted the models using a Gaussian distribution. The global model included one of the aforementioned move- ment parameters as a response variable and the following explanatory variables: (1) season, i.e., mating vs. post-mating season. The mating period was defined from 1 May to 31 July, while the post-mating period was from 1 August to 31 Octo- ber, when most of the bears enter the den to hibernate. Wild berries, the most important food source during the bear post-mating hyperphagic period in that area, are available onwards late July (Penteriani et al., 2021), making our classifi- cation based on a relevant biological break; (2) the previously cited nine predictors of daily habitat use, that is, DHS excluded. All environmental predictors included were standard- ized (i.e., Z-score normalization) to facilitate the correct inter- pretation and comparison of parameter estimates (Grueber et al., 2011); and (3) interaction terms between the season and each of the environmental predictors, in order to detect possi- ble differences in characteristics of the landscape where male bears moved between the two periods. Since the number of daily sessions (i.e., a session corresponds to one GPS-tracking day) varied within individuals (mean = 50, range = 3–164) and years (mean = 105, range = 16–303), we included the individual and the year as crossed random effects. Furthermore, in each model, we included the autoregressive correlation structure AR(1) to account for the temporal autocorrelation of daily movement parameters. We used the R package MuMIn (Barton, 2023) to derive from each global model all possible submodels (i.e., with all possible combinations of variables) with relative values of Akaike’s information criterion corrected for small sample size (AICC), AICC difference (DAICC), and Akaike weight (wi). Akaike weight of a given model represents the relative likeli- hood of that model being the best model among the full sub- model set (Burnham & Anderson, 2002). Models with a DAICC < 4 were considered equally parsimonious since the level of empirical support of such models is still substantial (Burnham et al., 2011; Burnham & Anderson, 2002). Parame- ter coefficients and the relative importance value (RIV) of each explanatory variable were obtained using the ‘natural’ model averaging approach on this top model set (Burnham & Ander- son, 2002; Grueber et al., 2011). Indeed, averaging the full submodel set, or a large proportion of it, is not recommended because (a) parameter estimates from models with very poor weights are spurious and (b) those sets may include redundant models, such as nested models (Grueber et al., 2011). The RIV of each explanatory variable was estimated by summing the Akaike weights for each model in which a given variable appears (Burnham & Anderson, 2002). Step-selection analysis for mating and post-mating seasons Step-selection functions overview Step-Selection Functions (SSFs) are among the most popular and powerful methods to estimate the use of space and resources by animals moving through a landscape (Fortin et al., 2005; McLoughlin et al., 2010). Basically, SSFs com- pare environmental attributes of used steps (i.e., linear seg- ments linking two consecutive animal locations) with those of alternative random steps taken from the same starting point, most generally using conditional logistic regression (Thurfjell et al., 2014). In this way, random steps characterize what is available to the animal during its movement, and they are ran- domly generated from empirical or parametric distributions of step lengths and turning angles; including movement and allowing the data to define the availability sample, SSFs can better investigate the choices made by animals in selecting the resources compared with other approaches (for more details, see Avgar et al., 2016; Thurfjell et al., 2014). Data preparation: Available steps generation In order to investigate habitat selection during mating and post-mating season movements, we first calculated the straight-line distance (i.e., step length) between successive locations for all daily trajectories within Finland using the R package adehabitatLT (Calenge, 2006). Then, each observed step was matched with 10 random steps that we assumed to be available at each relocation, sharing the same starting point as the observed step but differing in length and/or direction. Since we probably underestimated longer bear displacements because animals most likely do not travel in a straight line during the time gap between successive relocations, we decided to gener- ate available steps as in Forester et al. (2009). Specifically, the lengths of random steps were drawn through a parametric sampling method, using a negative exponential distribution with a rate parameter k1 = 2546 m (i.e., twice the observed mean 4-h step length), and thus an integrated step-selection analysis approach (Avgar et al., 2016). Turning angles for the random steps were instead sampled from a uni- form distribution between 0 and 2p. We then extracted the value of environmental variables at the endpoints of each Journal of Zoology  (2024) – ª 2024 The Author(s). Journal of Zoology published by John Wiley & Sons Ltd on behalf of Zoological Society of London. 5 D. Falcinelli et al. Movements of male brown bears during mating 14697998, 0, D ow nloaded from https://zslpublications.onlinelibrary.w iley.com /doi/10.1111/jzo.13199 by Duodecim Medical Publications Ltd, W iley Online Library on [01/08/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on W iley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License observed and available step, as we were interested in inferring habitat selection (Avgar et al., 2016; Thurfjell et al., 2014). Finally, all random steps whose endpoints fell outside the Finnish territory were discarded from the availability set (see above). Statistical analysis We built one iSSF model for the mating period and one for the post-mating one (defined above) using mixed conditional logistic regression (Duchesne et al., 2010; Fortin et al., 2009) with the R package mclogit (Elff, 2022). The model structure was as follows: (1) used (coded as 1) and available (coded as 0) steps as binary response variable; (2) each used step with its associated random steps as the stratum (i.e., for matching the used and available steps); (3) terrain rugged- ness, landcover variables, distance from main roads, second- ary roads, and human trails as environmental predictors; (4) step length as a predictor variable, to reduce bias in esti- mates of model coefficients (Avgar et al., 2016; Forester Figure 2 Monthly box plots for each daily movement metric (net distance, total distance and speed) highlighted differently depending on the season (green = mating; orange = post-mating). Values for April are also presented (in black), in order to show the increase in metrics at the onset of mating season (see text for details). 6 Journal of Zoology  (2024) – ª 2024 The Author(s). Journal of Zoology published by John Wiley & Sons Ltd on behalf of Zoological Society of London. Movements of male brown bears during mating D. Falcinelli et al. 14697998, 0, D ow nloaded from https://zslpublications.onlinelibrary.w iley.com /doi/10.1111/jzo.13199 by Duodecim Medical Publications Ltd, W iley Online Library on [01/08/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on W iley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License et al., 2009). Again, all predictors were standardized (see above); and (5) individual and year as random slopes (i.e., a mixed-effects model), to account for variation among individ- uals and years (Fieberg et al., 2021; Muff et al., 2020). Since we believed that our model was biologically informed anyway (i.e., we did not add any potentially unnecessary terms), and as more complex formulations of the model (e.g., including interactions) gave some convergence issues (e.g., Fieberg et al., 2021; Muff et al., 2020), we decided to use the results from that model to make inferences. We processed and analysed all data in R version 4.0 (R Core Team, 2023). Results According to the results of LMMs, male brown bears moved over longer daily net distances during the mating season com- pared with the post-mating season, even if they did not show greater daily total distances or higher daily average speed (Fig. 2; see Table 1 for summary statistics and Table 2 for parameter estimates of LMMs). However, during the mating season, all three daily movement parameters increased in areas characterized by human presence, activity, and infrastructure, while only the net distance increased within shrublands (Table 2). In addition, independently of the period, male bears covered greater daily distances at a higher speed in proximity to main roads, but their speed did not increase when close to secondary roads (see also Table S2 for the global model results). Based on parameter estimates from iSSF models (Table 3), during the mating period, male bears selected coniferous and mixed-deciduous forests, as well as shrubbery habitats (Fig. 3). During the post-mating season, male bears continued to select forests and shrubs, but also anthropogenic areas and open areas, while avoiding close proximity to main roads and human trails (Fig. 3; Table 3). Discussion As expected (prediction 1), we found evidence that male brown bears from Finnish Karelia covered greater per-day net distances in the mating than in the post-mating season, but we did not detect a significant season effect for the daily total dis- tance and average speed. Additionally, the observed patterns for daily movement metrics supported our prediction 2, reveal- ing faster/greater displacements of bears within anthropogenic areas during the mating season than post-mating. Since human presence and activity are supposed to be higher in those areas (Morales-Gonzalez et al., 2020), this finding may suggest that adult males in the mating season prioritized the search for mates over avoiding human disturbance. Lastly, the results of the step-selection analysis supported our prediction 3 only par- tially: while male bears avoided disturbed habitats closer to roads and trails only during the post-mating season, they also showed a selection for anthropogenic areas during that period. By examining the monthly trend of daily movement parame- ters (Fig. 2), there appeared to be a yearly variation in their value, that is, a sharp increase in May that continued through- out June, a decrease in July/August and then a gradual increase toward October. Similarly to our results, a wide range of fine-time-scale movement metrics of adult males (e.g., hourly movement distance, daily activity rate, and speed) also increased during the mating period in other brown bear popula- tions, presumably due to the promiscuous mating of this spe- cies (de Gabriel Hernando et al., 2020; Graham & Stenhouse, 2014; Ordiz et al., 2017). The second peak in fall may be related to hyperphagia needs when brown bears con- sume large amounts of high-calorie food to store fat reserves essential for later hibernation (Swenson et al., 2021, 2023). In our study area, located in a boreal landscape at northernmost European latitudes (Esseen et al., 1997), adult males in the hyperphagic period may have still travelled fast and long daily Table 1 Summary statistics of movement parameters and environmental variables, both derived at a daily scale Mean  SD Median Range Mating Post-mating Mating Post-mating Mating Post-mating Movement parameters Net distance (m) 4519  5203 3895  4505 2793 2410 2–29 587 3–28 603 Total distance (m) 8330  7826 7577  6079 5970 5751 41–45 382 52–34 520 Speed (m/h) 351  329 317  254 252 241 2–1890 2–1438 Environmental variables Terrain ruggedness index 2.49  1.37 2.56  1.49 2.22 2.14 0.45–15.49 0.33–9.84 Anthropogenic areas (0–1) 0.02  0.03 0.04  0.05 0.01 0.03 0.00–0.21 0.00–0.33 Mixed-deciduous forest (0–1) 0.12  0.07 0.16  0.08 0.12 0.15 0.01–0.32 0.01–0.43 Coniferous forest (0–1) 0.63  0.10 0.60  0.12 0.63 0.62 0.23–0.84 0.19–0.86 Natural open areas (0–1) 0.06  0.06 0.04  0.05 0.05 0.02 0.00–0.29 0.00–0.28 Shrubland (0–1) 0.13  0.05 0.13  0.04 0.13 0.13 0.04–0.31 0.03–0.32 Distance to settlements (m) 23 295  13 874 18 866  11 492 17 012 14 864 2734–44 557 940–44 501 Distance to main roads (m) 6950  4897 5595  4425 5441 3818 251–22 261 540–19 662 Distance to secondary roads (m) 695  436 662  349 565 568 89–2797 139–2825 Distance to trails (m) 37 152  19 555 31 987  18 355 31 147 27 920 4607–94 069 2786–93 417 Values (mean  SD, median and range) are presented separately for mating (May to July) and post-mating (August to October) seasons. Journal of Zoology  (2024) – ª 2024 The Author(s). Journal of Zoology published by John Wiley & Sons Ltd on behalf of Zoological Society of London. 7 D. Falcinelli et al. Movements of male brown bears during mating 14697998, 0, D ow nloaded from https://zslpublications.onlinelibrary.w iley.com /doi/10.1111/jzo.13199 by Duodecim Medical Publications Ltd, W iley Online Library on [01/08/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on W iley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License Table 2 Values of degrees of freedom (d.f.), AICC, DAICC and Akaike weight (wi) of the best (DAICC < 4) linear mixed-effects models for each movement parameter considered (see text for details) Response variable Competing models d.f. AICC DAICC wi Net distance Anthropogenic areas + Season + Shrubs + Anthropogenic areas * season + Shrubs * season 10 3863.04 0.00 0.51 Anthropogenic areas + DMR + Season + Shrubs + Anthropogenic areas * season + Shrubs * season 11 3864.52 1.48 0.24 Anthropogenic areas + DHT + Season + Shrubs + Anthropogenic areas * season + Shrubs * season 11 3865.40 2.36 0.16 Anthropogenic areas + DHT + DMR + Season + Shrubs + Anthropogenic areas * season + Shrubs * season 12 3866.51 3.47 0.09 Explanatory variables b SE CI RIV Intercept 7.10 0.19 6.72; 7.48 Anthropogenic areas 0.43 0.08 0.59; 0.26 1.00 Season (mating) 0.35 0.17 0.01; 0.69 1.00 Shrubs 0.36 0.09 0.53; 0.18 1.00 Anthropogenic areas * season (mating) 0.43 0.15 0.14; 0.73 1.00 Shrubs * season (mating) 0.35 0.12 0.11; 0.58 1.00 DMR 0.17 0.09 0.35; 0.01 0.33 DHT 0.17 0.10 0.03; 0.37 0.25 Total distance Anthropogenic areas + DMR + Season + Anthropogenic areas * season 9 2679.09 0.00 0.42 Anthropogenic areas + DMR 7 2680.04 0.94 0.26 Anthropogenic areas + Season + Anthropogenic areas * season 8 2680.14 1.05 0.25 Anthropogenic areas 6 2682.53 3.44 0.07 Explanatory variables b SE CI RIV Intercept 8.42 0.13 8.17; 8.67 Anthropogenic areas 0.21 0.06 0.32; 0.10 1.00 DMR 0.15 0.05 0.25; 0.04 0.68 Season (mating) 0.04 0.11 0.18; 0.25 0.66 Anthropogenic areas * season (mating) 0.29 0.09 0.12; 0.45 0.66 Speed Anthropogenic areas + DMR + Season + Anthropogenic areas * season 9 2680.08 0.00 0.38 Anthropogenic areas + DMR 7 2680.79 0.71 0.27 Anthropogenic areas + Season + Anthropogenic areas * season 8 2681.50 1.42 0.19 Anthropogenic areas 6 2683.68 3.60 0.06 Anthropogenic areas + DHT + DMR 8 2683.97 3.89 0.05 Anthropogenic areas + DHT + DMR + Season + Anthropogenic areas * season 10 2684.07 3.98 0.05 Explanatory variables b SE CI RIV Intercept 5.26 0.12 5.01; 5.50 Anthropogenic areas 0.21 0.06 0.32; 0.10 1.00 DMR 0.15 0.05 0.25; 0.05 0.75 Season (mating) 0.04 0.11 0.17; 0.26 0.62 Anthropogenic areas * season (mating) 0.28 0.09 0.11; 0.45 0.62 DHT 0.09 0.06 0.03; 0.21 0.11 For each explanatory variable, coefficient (b), standard error (SE), 95% confidence interval (CI), and the relative importance value (RIV) obtained by averaging the top 4AICC of models are reported. Significant explanatory variables (P-value <0.05) are shown in bold. Interaction terms between season and a specific environmental variable are indicated with an asterisk. DMR, distance to main roads; DHT, distance to human trails (see text for all details). 8 Journal of Zoology  (2024) – ª 2024 The Author(s). Journal of Zoology published by John Wiley & Sons Ltd on behalf of Zoological Society of London. Movements of male brown bears during mating D. Falcinelli et al. 14697998, 0, D ow nloaded from https://zslpublications.onlinelibrary.w iley.com /doi/10.1111/jzo.13199 by Duodecim Medical Publications Ltd, W iley Online Library on [01/08/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on W iley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License distances in search of food to fatten up before denning (Dahle & Swenson, 2003a; Edwards & Derocher, 2015; Ordiz et al., 2017). Our findings also suggest that at the daily scale, the net distance (i.e., the more directional way of displacement) may be good proxy to describe both the increased home range size observed during the mating season in brown bears (Dahle & Swenson, 2003a, 2003b; Preatoni et al., 2005) and the roaming behaviour that enabling them to Table 3 Values of coefficients (b), standard errors (SE), and 95% confidence intervals (CI) for the mixed conditional logit models comparing used steps to randomly generated steps; separate models were generated for mating and post-mating season Variable Mating season Post-mating season b SE CI b SE CI TRI 0.02 0.04 0.10; 0.06 0.03 0.04 0.11; 0.05 Anthropogenic areas 0.11 0.12 0.35; 0.12 0.27 0.04 0.19; 0.35 Mixed-deciduous forest 0.69 0.17 0.37; 1.01 0.57 0.16 0.26; 0.88 Coniferous forest 0.93 0.16 0.61; 1.26 0.71 0.10 0.52; 0.90 Open areas 0.22 0.11 0.004; 0.45 0.22 0.09 0.05; 0.39 Shrubs 0.30 0.10 0.10; 0.50 0.23 0.08 0.08; 0.38 DMR 0.10 0.07 0.04; 0.25 0.37 0.11 0.15; 0.59 DSR 0.01 0.06 0.10; 0.12 0.04 0.05 0.06; 0.13 DHT 0.29 0.21 0.12; 0.70 0.55 0.27 0.01; 1.09 Step length 1.74 0.27 2.27; 1.22 1.29 0.17 1.63; 0.94 Numbers in bold represent effects with P-value <0.05. DHT, distance to human trails; DMR, distance to main roads; DSR, distance to secondary roads; TRI, Terrain Ruggedness Index (see text for all details). Figure 3 Contrasted selection coefficients (and 95% confidence intervals) as estimated by step-selection functions (see Table 3) for mating and post-mating movements (in green and orange, respectively). Positive coefficients (b > 0) indicate that resources are used in a larger proportion compared with their availability, negative coefficients (b < 0) indicate that resources are used in a lesser proportion compared with their availability, and null coefficients (i.e., 95% confidence interval of b includes 0) mean that resources are used in proportion to their availability. Journal of Zoology  (2024) – ª 2024 The Author(s). Journal of Zoology published by John Wiley & Sons Ltd on behalf of Zoological Society of London. 9 D. Falcinelli et al. Movements of male brown bears during mating 14697998, 0, D ow nloaded from https://zslpublications.onlinelibrary.w iley.com /doi/10.1111/jzo.13199 by Duodecim Medical Publications Ltd, W iley Online Library on [01/08/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on W iley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License enhance encounter rates with potential receptive mates (e.g., Fisher & Lara, 1999; Kovach & Powell, 2003). Throughout the year, males strongly selected coniferous and mixed-deciduous forests, emphasizing their importance across the entire range of brown bears (Swenson et al., 2021, 2023). Forest habitats provide bears with foraging opportunities, can- opy cover for thermal comfort and protection against adverse weather and even horizontal cover for hiding and resting dur- ing the day (Ciarniello et al., 2014; Cristescu et al., 2013; Ordiz et al., 2011). As residency time within a particular habitat is hypothesized to decrease with longer step lengths (Turchin, 1998), the observed association between a greater proportion of anthropo- genic area usage and increased speed/displacements during the mating season may indicate a response by bears to a height- ened perception of human-derived risk in these areas (de Gabriel Hernando et al., 2020; Donatelli et al., 2022; Roever et al., 2010; Thorsen et al., 2022). This aligns with findings reported for other brown bear populations, where higher movement rates were observed near roads in spring/early summer (Donatelli et al., 2022; Roever et al., 2010), or where adult males used/ selected disturbed areas near roads and trails during the mating period (Roever et al., 2008; Steyaert et al., 2013; Van de Walle et al., 2019). Male brown bears covered faster and longer daily distances near main roads during the mating season. Since it appears that there was no avoidance of these features, adult males may have used areas closer to linear infrastructures for travelling. This behaviour aligns with previous findings that indicate that roads and trails may serve as efficient travel routes for large car- nivores, including brown bears (e.g., de Gabriel Hernando et al., 2020; Dickie et al., 2020; Dickson et al., 2005; Ladle et al., 2019; Roever et al., 2010). The decreased movement of male bears within anthropo- genic areas during the post-mating season fits well with the selection observed for those areas (Turchin, 1998) and was likely influenced by their increased foraging activity during hyperphagia. Since anthropogenic food resources can indeed affect movement patterns in our study area (Penteriani et al., 2021), and our definition of anthropogenic areas also included all agricultural areas (see above), male brown bears may have restricted movements around both natural food-rich patches (e.g., shrublands) and anthropogenic resources to increase foraging success during hyperphagia (De Angelis et al., 2021; Lamamy et al., 2022; McLoughlin et al., 1999). In this regard, seasonal variation in movement and space-use patterns of males seemed to be driven by a shift in limiting resources, from the distribution of receptive females during the mating season to food abundance and its spatial availability in the post-mating season, as reported for other solitary carnivores with a polygamous mating system (e.g., Erlinge & San- dell, 1986; Johnson et al., 2000). Additionally, the movement and habitat selection patterns observed during the post-mating season may have been influ- enced, at least partly, by hunting pressure. In fact, hunting has been shown to affect movement behaviour and habitat use in brown bears and other harvested apex predators (e.g., Stillfried et al., 2015; Strampelli et al., 2022). For instance, during the hunting season, Scandinavian bears altered their foraging patterns, increased movements during night-time hours, and rested during the day in areas with higher concealment far from human settlements (Hertel et al., 2016; Ordiz et al., 2011, 2012). In our study area, the post-mating period largely over- lapped with the hunting season, which lasted for about 2 months starting 20 August (Lamamy et al., 2022). Therefore, following the start of the annual hunting season, males may have exhibited increased vigilance behaviour in anthropogenic areas and avoided those closer to roads and trails (i.e., higher perceived human-derived risk), suggesting a potential trade-off between foraging opportunities and risk avoidance (Cristescu et al., 2013). In conclusion, when comparing male brown bear movements within and outside the mating period, the results obtained lend support to the notion that a close relationship exists between the biological needs of individuals (i.e., mating), their move- ment behaviour, and their use of space/landscape (Cagnacci et al., 2010a, 2010b; Nathan et al., 2008). During the mating season, males will predominantly be in areas where females are present, thereby largely reflecting areas of female habitat use (Berland et al., 2008; Roever et al., 2008; Steyaert et al., 2013). Conversely, male movements during the post-mating season may primarily mirror their habitat use. Considering the occurrence of human-caused bear mortality in disturbed areas (e.g., Kite et al., 2016; Nielsen et al., 2004), the increased use of anthropogenic areas during the mating season is relevant for the conservation of this species. It may require management interventions where necessary to mitigate conflicts between humans and bears (Roever et al., 2010). The potential trade-off between security and food that became apparent during the post-mating season warrants attention to prevent anthropogenic areas from acting as attractive sinks (Morales-Gonzalez et al., 2020; Penteriani et al., 2018). Acknowledgements During this research, DF was supported by a post-degree scholarship of the programme ‘Perfezionamento all’estero’ and a doctorate scholarship by the Sapienza University of Rome. VP was financially supported by I + D + i Project PID2020- 114181GB-I00 funded by MCIN/AEI/10.13039/501100011033 and by the European Union. We wish to thank the Finnish Transport Infrastructure Agency and the Digiroad staff for data and metadata on the road network, and Ester Erica Mantero for the help provided for the graphics of the figures. We are also grateful to Antero Hakala, Leo Korhonen, Reima Ovaskai- nen, Seppo Ronkainen, and Markus Suominen for assistance in capturing and collaring the bears. We thank Wolfgang Goy- mann and two anonymous Reviewers for their useful sugges- tions, which helped us to improve our manuscript. Finally, we acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Infor- mation Resources for Research (URICI). Author contributions VP and DF conceived the ideas; DF, VP and MMD designed methodology; IK and SK collected the movement data; DF 10 Journal of Zoology  (2024) – ª 2024 The Author(s). Journal of Zoology published by John Wiley & Sons Ltd on behalf of Zoological Society of London. 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Journal of Zoology published by John Wiley & Sons Ltd on behalf of Zoological Society of London. Movements of male brown bears during mating D. Falcinelli et al. 14697998, 0, D ow nloaded from https://zslpublications.onlinelibrary.w iley.com /doi/10.1111/jzo.13199 by Duodecim Medical Publications Ltd, W iley Online Library on [01/08/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on W iley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License