DOI: 10.5061/dryad.zkh1893mf
title: Denning chronology in an Arctic brown bear population

description: Denning is a critical behavioral adaptation for brown bears (Ursus arctos)
 to cope with winter, a period of extended resource scarcity. Bears reduce
 their body temperature, heart rate, and metabolism during this time to
 minimize energy expenditures. The Arctic has among the most pronounced and
 longest period of resource scarcity. Thus, we predicted bears in the
 region would respond by having among the longest recorded denning periods.
 We used GPS data from brown bears to determine the den entry, den exit,
 and denning duration for a population living primarily above the Arctic
 Circle. On average, brown bears in the region denned for 206 days, the
 longest duration reported using GPS data of which we are aware. The
 longest denning duration for any individual bear was a remarkable 233 days
 (64% of the year), which is near the theoretical maximum of 241 days. We
 found that food availability in fall delayed den entrance, with bears that
 appeared to consume more salmon entering their dens later. Bears showed
 greater synchrony in den exiting than den entrance, and female bears with
 cubs exited their dens more than a week after other bears. Later snow melt
 out in spring was also associated with later den exits. Climate change has
 the potential to affect the denning ecology of arctic brown bears by
 altering the availability of food, ambient temperature, and precipitation,
 all of which can alter the costs and benefits of hibernation for brown
 bears.
description: Our objectives were to describe the denning chronology of brown
 bears near the northern extent of their North American range and identify
 links among intrinsic characteristics (e.g., reproductive status, age, and
 body mass), environmental conditions, and the timing of denning behavior
 as a necessary first step to identifying the potential consequences of
 climate change and proposed industrial development on this behavior. We
 hypothesized that (1) sex, reproductive status, and stored energy
 resources, or (2) a combination of intrinsic factors and environmental
 covariates associated with diet and weather would explain the timing of
 den entry and den exit. We predicted that (1a) gestating females would
 enter dens earlier and exit dens later and (1b) body fat would explain
 date of den exit because stored energy would allow longer denning
 duration. We also predicted that (2a) low ambient temperatures and late
 snowmelt in spring would be associated with late den exits, and (2b) bears
 that used salmon in autumn would den later due to increased availability
 of energy-rich food resources.  
 <em>Bear Capture and Tracking</em>
   We captured and collared 51 brown
 bears (32 females and 19 males) between 2014 and 2016 using aerial darting
 techniques. Capture and handling techniques were in accordance with
 guidelines of the American Society of Mammalogists (Sikes and Gannon 2011)
 and were approved by USGS and National Park Service Institutional Animal
 Care and Use Committees (IACUCs; 2014-1 and 2014A2, respectively). We
 fitted bears with Telonics (Mesa, AZ) Gen IV Global Positioning System
 collars. The collars were programmed to obtain a location every 90 minutes
 between March 15 and November 15 and once a day between November 16 and
 March 14. A tri-axial accelerometer housed in the collar was programmed to
 record activity during the five-minute period immediately after a GPS
 location was recorded.  
 <em>Den Locations and Chronologies</em>
   We identified den sites following the
 methods of Sorum et al. (2019a), which involved locating clusters of GPS
 locations prior to den entry and then visiting a subset of dens for
 validation (Pigeon et al. 2014). Across 33 validated dens, Sorum et al.
 (2019a) found that the average den location determined from GPS collars
 was within 25m (SE = 9m) of the actual den location.
   The timing of den entry and exit is
 often inferred from GPS collar data. However, bear behaviors such as
 lingering near the den site before and after the denning period can
 decrease the reliability of location data as an indicator of the timing of
 hibernation. Similarly, some collared bears in dens can continue to record
 GPS locations in shallow dens or with favorable arrangements of overhead
 GPS satellites. To address such shortcomings, we used both GPS fix rate
 and accelerometer activity sensor readings to infer the beginning and end
 of the denning period. Because the patterns of these variables can be
 complex due to situations like a bear briefly entering a den, appearing to
 enter hibernation, then exiting and re-entering a second time, we used a
 manual graphical technique to select the den entry and exit periods.
 Abrupt decreases in both GPS fix rates and activity rates were used to
 infer the beginning of denning, while abrupt increases in both fix rates
 and activity rates were used to infer den exit timing (see Supporting
 Information).   We estimated
 denning duration as the number of days between den entrance and exit for
 each bear. Because two bears moved between multiple dens in a single
 winter, we identified the interval from the date of entrance at the first
 den to date of emergence at the last den as the denning period for these
 individuals (Waller et al. 2012). To understand bear behavior following
 den emergence, we also calculated the post-emergence period, which we
 defined as the number of days it took each bear to first move 1km from
 their dens (Anderson et al. 2024).  
 <em>Intrinsic Covariates</em>
   We tested the effect of six intrinsic
 covariates on the date of den entry and exit: reproductive status and sex
 (combined), bear age, percent body fat, body mass, den elevation, and a
 measure of salmon use in September (Table 1). We determined the
 reproductive status of females via observations during telemetry flights
 or capture events. We used activity sensors in collars to detect birth
 events during denning by identifying short spikes of activity, which have
 been shown to reliably indicate birth (similar to Lemeire et al. 2022 but
 as in Roberts et al. *in prep*). Females with no cubs observed during at
 least 2 repeated aerial observations before denning and who did not give
 birth to cubs in the den were labelled as lone females. Females observed
 with at least 1 older cub (1- or 2-year-olds) after den exit were
 classified as females with cub at the time of den entry. To simplify
 analyses, we generated a variable combining sex and the reproductive
 status of females (RS), which had 4 classes during den entry (male, solo
 female, pregnant, female with cub) and 3 classes during den exit (male,
 solo female, and female with cub). RS information was missing for one
 individual which was excluded from analyses including RS.
   Age was estimated by highly
 experienced biologists from tooth wear at capture (Hilderbrand et al.
 2018) and projected forward throughout the study. This method has similar
 accuracy and is much less invasive than aging based on teeth annuli
 (Hilderbrand et al. 2018). However, inaccurate age estimates may have
 persisted and prevented us from detecting a true effect of age on den
 entrance or exit, but we did not have a way to address this issue. Body
 mass (to nearest 0.5 kg) was determined by using an electronic load cell
 (MSI-7200, Measurement Systems International, Seattle, WA, USA;
 Hilderbrand et al. 2018). Percent body fat was estimated at capture by
 bioelectric impedance analyses (RJL Systems, Clinton Township, MI, USA;
 Farley and Robbins 1994, Hilderbrand et al. 1998, Hilderbrand et al.
 2018). Den elevation was extracted from a Digital Elevation Model with 20m
 resolution.   We estimated
 each bear’s use of salmon as a food resource before den entry based on
 their proximity to salmon-bearing streams. Previous studies in Alaska have
 found that time spent near streams is a reliable predictor of salmon
 consumption because bears respond to seasonal changes in salmon
 availability: 70% of the variation in the percent of assimilated bear
 diets consisting of salmon was explained by the amount of time GPS
 collared bears spent near streams (Deacy et al. 2016, 2018). Bears are
 mostly absent from salmon streams when salmon are not spawning but become
 ephemerally super abundant during salmon runs (Schindler et al. 2013,
 Deacy et al. 2016). We used the Alaska Anadromous Streams Catalog (AASC)
 and field observations to identify the water bodies in north-central
 Alaska where bears have access to salmon (Figure 1). We included all
 portions of streams where salmon are considered present. Although Deacy et
 al. (2016, 2018) used a 50m buffer to identify GPS locations associated
 with salmon fishing, that research occurred on small high-gradient streams
 with well-defined channels. Upon viewing satellite imagery with the AASC
 line features, we identified many clusters of GPS points on off-channel
 habitat that was up to 1000m from the line feature which defined the main
 channel. In other areas, the main channel was distant from its associated
 line feature, possibly because channels tend to migrate in dynamic flood
 plain rivers. To account for these issues, we considered individuals to be
 foraging for salmon when their GPS locations were &lt;1000m from a
 salmon stream. Although some of these locations are likely associated with
 activities other than catching and eating salmon (e.g. travel, eating
 other foods), we found that the percent of individual brown bear GPS
 locations within 1000m of streams in September was positively correlated
 (r&gt;0.64) with percent of salmon and terrestrial meat in the diet of
 individual bears documented by Mangipane et al. (2020), which lends
 support for our approach. Following these procedures, we defined the
 variable ‘September salmon use’ as the percentage of a bear’s September
 GPS locations within 1000m of salmon streams.
   <em>Environmental
 Covariates</em>   We
 tested the effect of four environmental covariates on the date of den exit
 (snow depth, mean air temperature, maximum air temperature, and the end of
 the continuous snow season; Table 1). We also included ‘year’ as a
 covariate to account for unexplained environmental variation. We did not
 test for the effect of these variables (except for year) on den entry
 because in this strongly seasonal system, environmental variables are all
 highly correlated with date and confounded by the movement of bears. For
 example, a bear that climbs to higher elevations intending to den may
 enter a location with deeper snow and cold temperatures, a change
 resulting from the movement and probably unrelated to the initiation of
 denning. In contrast, a bear in a den is stationary, which prevents
 movements from confounding tests for effects of environment on den
 exit.   To test whether
 den-specific weather conditions affected den exit timing, we attributed
 mean snow depth, mean surface temperature, and maximum surface temperature
 to den locations using the track annotation service Env-Data (Dodge et al.
 2013) on Movebank (movebank.org, Wikelski et al. 2022). Mean snow depth
 (m), mean air temperature (C), and maximum air temperature (C) were
 derived from the National Center for Environmental Predictions’ North
 American Regional Reanalysis, which has a 3-hour frequency and 0.3-degree
 spatial resolution (National Centers for Environmental Prediction et al.
 2005). To limit temperature variables to periods most likely to influence
 den exit timing, we averaged the mean and maximum temperatures from March
 31- April 9th, the ten days prior to the earliest den exit.  
   Bilinear interpolation was used for
 all attributes in Env-DATA. Weather reanalysis data have been found to
 have good agreement with weather station data in other studies in the
 Alaskan Arctic (Cameron et al. 2021). We sourced continuous snow season
 data from the Geographic Information Network of Alaska (GINA) at the
 University of Alaska Fairbanks, which derived the metric from MODIS Terra
 Snow Cover Daily L3 Global 500m Grid data (MtOD10A1.v005) from the
 National Snow and Ice Data center (Lindsay et al. 2015). End of continuous
 snow season is a measure of the first melt date at a location, which
 excludes the influence of spring snow fall.
description: # Denning chronology in an Arctic brown bear population
 [https://doi.org/10.5061/dryad.zkh1893mf](https://doi.org/10.5061/dryad.zkh1893mf) ## Description of the data and file structure ### Files and variables #### File: fall\_enter.csv **Description:**  ##### Variables * id: numeric variable to distinguish among bears * year: year of record * id.year: concatenation of id and year * julian: ordinal date of den entry * sex: sex of bear * age: age of bear in years * rep.stat: categorical variable indicating bear reproductive status * bodyfat: % of bodyfat for each bear. NA for missing values. * bodymass: mass in kg * Sept_Salmon_Use: Percentage of GPS locations in September within 1000m of salmon streams. * den.elev: den elevation in meters #### File: spring\_exit.csv **Description:**  ##### Variables * id:numeric variable to distinguish among bears * year: year of record * id.year: concatenation of id and year * julian: ordinal date of den exit * snowdepth: snow depth at den site, in meters * surftemp: temperature at den site, in Celsius * mean.snowdepth: mean snow depth at den site, in meters * mean.surftemp: temperature at den site, in Celsius * sex: sex of bear * age: age of bear in years, NA for missing data * rep.stat: categorical reproductive status * bodyfat: % of bodyfat for each bear. NA for missing values. * bodymass: mass in kg * Sept_Salmon_Use: Percentage of GPS locations in September within 1000m of salmon streams. * den.elev.ft: den elevation in feet * end.css: The end of the continuous snow season; ordinal date. #### File: picked.dendates.csv **Description:**  ##### Variables * index: index of record * id.year: concatenation of id and year * id: unique bear id * year: year of record * exit.date.pick: ordinal date of den exit, NA for missing data * enter.date.pick: ordinal date of den entrance, NA for missing data * prior.year.enter: ordinal date of prior year den entrance, NA for missing data ## Code/software NA ## Access information Other publicly accessible locations of the data: * None Data was derived from the following sources: * NA