The Clock Keeps Ticking: Circadian Rhythms of Free-Ranging Polar Bears

Abstract

Life in the Arctic presents organisms with multiple challenges, including extreme photic conditions, cold temperatures, and annual loss and daily movement of sea ice. Polar bears ( Ursus maritimus) evolved under these unique conditions, where they rely on ice to hunt their main prey, seals. However, very little is known about the dynamics of their daily and seasonal activity patterns. For many organisms, activity is synchronized (entrained) to the earth’s day/night cycle, in part via an endogenous (circadian) timekeeping mechanism. The present study used collar-mounted accelerometer and global positioning system data from 122 female polar bears in the Chukchi and Southern Beaufort Seas collected over an 8-year period to characterize activity patterns over the calendar year and to determine if circadian rhythms are expressed under the constant conditions found in the Arctic. We reveal that the majority of polar bears (80%) exhibited rhythmic activity for the duration of their recordings. Collectively within the rhythmic bear cohort, circadian rhythms were detected during periods of constant daylight (June-August; 24.40 ± 1.39 h, mean ± SD) and constant darkness (23.89 ± 1.72 h). Exclusive of denning periods (November-April), the time of peak activity remained relatively stable (acrophases: ~1200-1400 h) for most of the year, suggesting either entrainment or masking. However, activity patterns shifted during the spring feeding and seal pupping season, as evidenced by an acrophase inversion to ~2400 h in April, followed by highly variable timing of activity across bears in May. Intriguingly, despite the dynamic environmental photoperiodic conditions, unpredictable daily timing of prey availability, and high between-animal variability, the average duration of activity (alpha) remained stable (11.2 ± 2.9 h) for most of the year. Together, these results reveal a high degree of behavioral plasticity in polar bears while also retaining circadian rhythmicity. Whether this degree of plasticity will benefit polar bears faced with a loss of sea ice remains to be determined.

Evidence for circadian-based photoperiodic timekeeping in Svalbard ptarmigan, the northernmost resident bird

“…Surveys of diel organization across diverse Arctic species have revealed a diversity of behavioral patterns during the solsticial phases, with rhythmicity largely maintained in some species (e.g., arctic ground squirrel, polar bear, copepod, and several migrating birds) [31][32][33][34][35][36] but largely lost in others (e.g., Svalbard reindeer and Svalbard ptarmigan). 2,4,5,[37][38][39] This diversity indicates that the molding effect of Arctic life on the circadian network in relation to diel patterning is highly life history and ecotype dependent and therefore likely to resist a unifying rationale for involvement or exclusion.…”

Body Temperature and Activity Rhythms Under Different Photoperiods in High Arctic Svalbard ptarmigan (Lagopus muta hyperborea)

“…This is not the case at polar latitudes, which are instead characterized by extended periods of constant light (polar day) and constant darkness (polar night) with short periods of rapidly changing photoperiod in-between. During the polar day and polar night, animals inhabiting these latitudes are either free running, arrhythmic, or entrained to non-photic or photic cues other than photoperiod (Swade and Pittendrigh, 1967;van Oort et al, 2007;Stelzer and Chittka, 2010;Williams et al, 2011;Ashley et al, 2012;Steiger et al, 2013;Arnold et al, 2018;Hüppe et al, 2020;van Beest et al, 2020;Ware et al, 2020). On the Svalbard archipelago, which is among the northernmost landmasses in the Arctic (74°-81°N, Figure 1B), the Sun remains ≥6° below the horizon between mid-November and February but is constantly above the horizon between mid-April and mid-September.…”

Quantifying behavior and life‐history events of an Arctic ungulate from year‐long continuous accelerometer data

“…The model presented here was run on a limited number of individuals and did not account for the spatial variation of snow depth or habitat type at the same resolution as the data, hence could not fully explain the behavioral variation within the data. Changes in climatic conditions (i.e., temperature, photoperiod cycle) and food availability in seasonal environments affect animals' physiology, behavior, and circadian rhythmicity (Signer et al 2011, Arnold et al 2018, Dunn et al 2020, Ware et al 2020. Environmental gradients (e.g., elevation and topography) and spatial heterogeneity in snow accumulation, in particular, affect movements, habitat suitability, and population dynamics of species living in highly seasonal environments (Richard et al 2014, Mysterud et al 2017.…”

“…Devices have become smaller, cheaper, and longer-lasting, recording data at frequencies up to 10,000 Hz and thus generating millions of data points (Brown et al 2013). Due to challenges related to storing, recovering, and analyzing these vast amounts of data, accelerometer data are typically collected over limited periods, in short bursts or internally processed and/or combined in a single activity value (Brown et al 2013, Cox et al 2017, Ware et al 2020.…”