Seasonal variation of the daily activity patterns in a subterranean rodent in response to underground temperature fluctuations

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We analysed activity data from free-living silvery mole-rats Heliophobius argenteocinereus radio-tracked over six periods, including the coldest and hottest periods of the year, to investigate whether their activity is concentrated into parts of the day when thermoregulation costs are supposed to be lowest. During the coldest period, mole-rat activity correlated most strongly with the temperature at depths of 5–10 cm (positively), corresponding to the superficially situated burrow branches leading to mounds or food resources located in the shallow soil layers. In contrast, during two hottest periods, activity was more closely related to temperatures at a depth of 25 cm (negatively). While the activity pattern detected during the coldest period aligns with the expected greater daily variation in thermoregulatory costs associated with burrowing closer to the soil surface, the patterns from the hottest periods are more difficult to interpret. We hypothesise that during the hottest periods of the year, mole-rats either (i) preferentially construct and use deeper burrow sections, adjusting their daily activity patterns to small temperature fluctuations found there, or (ii) concentrate their activity to a part of the day when temperatures across a range of soil depths converge, provided they remain below their thermal neutral zone (TNZ). subterranean rodent daily activity pattern radio-tracking behavioural thermoregulation Figures Figure 1 Figure 2 Introduction The activity of most mammals follows a predictable daily pattern that reduces energetic costs including those associated with thermoregulation. These patterns are usually governed by circadian rhythms that are primarily maintained by the natural cycle of light (Bartness and Albers 2000 ), although ambient temperature cycles could also play an important role (Wams et al. 2017). Unsurprisingly, daily activity patterns may vary substantially throughout the year due to seasonal thermoregulatory challenges (van der Vinne et al. 2014 ; Silvério et al. 2024 ). The subterranean way of life, which has evolved independently in various phylogenetically unrelated groups of mammals, provides an opportunity to investigate the daily activity patterns that emerge under largely restricted and irregular exposure to daylight combined with substantially buffered daily—and, to a lesser extent, annual—ambient temperature fluctuations. For this purpose, subterranean rodents serve as an ideal model group. First, they share similar foraging ecology across unrelated taxa, relying primarily on underground plant storage organs reached by burrowing through the soil (Nevo 1999 , Lacey et al. 2000). Second, they have a restricted opportunity for evaporative cooling due to the high humidity in burrow systems, making them susceptible to overheating during burrowing (Luna et. al. 2020 , Okrouhlík et al. 2015 , Walace et al. 2021, Šumbera 2019 , McGowan et al. 2020 ). Given the dark and thermally buffered environment beneath the soil surface, one might assume that free-living subterranean mammals lack predictable daily activity patterns (e.g. Nevo 1979 ). However, this assumption has already been disproven by early telemetry studies on several subterranean and fossorial rodents of temperate zones (Gettinger 1984 ; Rado et al. 1993 ; Benedix 1994 ). These studies demonstrated a clear link between activity and daily variation in burrow or soil temperature. Later, we demonstrated that temperature-driven daily activity patterns also occur in tropical subterranean rodents, such as the silvery mole-rat Heliophobius argenteocinereus from southern Malawi (Šklíba et al. 2007 ). During the coldest period of the year, the proportion of radio-tracked mole-rats active at a given time of the day was positively correlated with temperature at a typical foraging burrow depth. This relationship disappeared a few weeks later when mean daily temperatures increased. Based on these findings, we proposed that the mole-rats concentrate their activity during periods of the day when thermoregulatory costs are minimized due to favourable temperatures. This behaviour can be interpreted as a form of behavioural thermoregulation (Richards 1973 ). Recent studies have further supported the role of ambient temperature in shaping daily activity patterns in subterranean rodents. Laboratory experiments on African mole-rats (e.g., Cryptomys hottentotus mahali in Van Jaarsveld et al. 2019 , Georychus capensis and C. h. mahali in Hart et al. 2021 , Fukomys damarensis in Grenfell et al. 2024 ; see also Oosthuizen and Bennett 2022 for a review) and field studies on free-living populations (e.g., C. h. natalensis in Finn et al. 2022 and Oosthuizen et al. 2021 h. pretoriae in Finn et al. 2024 ) have demonstrated that temperature significantly influences activity rhythms. These findings reinforce the idea that behavioural thermoregulation is a key driver of activity patterns in subterranean rodents. The benefits of such behavioural thermoregulation are likely greatest during periods with extreme annual temperatures or during periods when daily temperature variation is most pronounced. Based on this, we hypothesise that the activity patterns of the silvery mole-rat change predictably throughout the year, with activity concentrated during periods of the day when thermoregulatory costs are minimized due to favourable temperatures. Specifically, the relationship between activity and temperature at typical burrow depths, which was found to be positive during the coldest period of the year (Šklíba et al. 2007 ), is expected to reverse during the hottest periods. Furthermore, as an extension of this hypothesis, we propose that during periods when daily temperature variation at typical burrow depths is more pronounced, silvery mole-rats would exhibit more distinct daily activity patterns. We analysed radio-tracking data from seven silvery mole-rats collected at the end of the hot dry season of 2008, which covers the hottest part of the year. For comparison, we reanalysed similar data from the cold dry season of 2005, which encompasses the coldest part of the year and was largely published in Šklíba et al. ( 2007 ). To test the hypothesis that silvery mole-rats concentrate their activity during parts of the day when thermoregulatory costs are lowest, we formulated the following predictions: 1) The correlation between hourly activity (defined as the proportion of radio-fixes of all individuals radio-tracked during the corresponding period located outside their nests at a given hour of the 24-h day) and the mean hourly temperature (calculated as the mean for the corresponding hour of the 24-h day over the entire period) at typical foraging burrow depths (15–20 cm) will be positive during the coldest period and negative during the hottest periods of the year. 2) The hourly activity will correlate more strongly with the mean hourly temperature at typical foraging burrow depths (15–20 cm) than temperatures at other depths, during both the coldest and hottest periods. 3) Daily activity patterns will be more distinct during periods with greater amplitude of the mean hourly soil temperature, particularly when considering the temperature variation at typical depth of foraging burrows (15–20 cm). We quantified the distinctness of the activity patterns as the difference between the minimum and maximum hourly activity value for a given period. Materials and methods Study species The silvery mole-rat is a solitary bathyergid widely distributed across open canopy woodlands and grasslands in Central and Eastern Africa (Šumbera et al. 2007 ). It constructs dynamic burrow systems where usually a single nest at a time is used for resting. The outside-nest activity of the silvery mole-rat is polyphasic, with variable but generally predictable (unimodal, occasionally bimodal) daily patterns (Šklíba at al. 2007). Soil excavated during burrowing is deposited either into older burrows or in surface mounds (Šklíba et al. 2007 , 2009 , Šumbera et al. 2003 ). Foraging burrows in non-cultivated soil are typically 15–20 cm deep (measured from the tunnel floor to the soil surface), while nest chambers is usually 20–40 cm deep (Šumbera et al. 2004 , 2008 ). Study locality The study was conducted in a fragment of miombo woodland (dominated by Brachystegia spp.) on Mpalanganga estate, Zomba, Southern Malawi (15°27’ S, 35°16’ E, 1070 m a. s. l.). The climate in this region is characterized by rainy season (November–April), cold dry season (May–August), and hot dry season (September–November). Soil temperatures reach their annual minimum in July and maximum just before the onset of the rainy season, typically in late November (Šumbera et al. 2004 ). Capture and marking of study animals Mole-rats were captured in May/June 2005 and September 2008 using Hickman’s traps or by cutting their retreat with a hoe when they come to seal opened sections of their burrow systems. Adults were shortly immobilised using ketamine and xylazine and fitted with radio-collars (G3-1V transmitter with a position-based activity indicator, BR collar, AVM Instrument Company, Colfax, California). The activity indicator altered the signal rate of the transmitter when the collar deviated from a vertical position (e.g. when the animal lowered its head into a curled-up position, such as during sleep). The weight of the radio-collar was less than 5% of smallest animal 's body weight. Animals were returned to their burrow systems after 6 to 12 hours of recovery and accustoming to the collars. Radio-tracking was successfully conducted on 11 individuals (3 males and 8 females) in 2005 and seven individuals (4 males and 3 females) in 2008. After the study, animals were recaptured to remove the collars and released back into their burrows. Radio tracking We used an LA 12-Q receiver (AVM Instrument Company) and a Yagi antenna to fix the position of the animals. Four to five animals were tracked in rotation, with approximately 30-min intervals between successive fixes of the same animal. Tracking started with an observer listening to the signal of the transmitter for 1–2 minutes from a distance greater than 10 m to determine whether the signal rate was slow and stable, indicating curled-up body position or fast and stable, indicating little or no motion in other body position or variable, indicating motion. Then the observer fixed the animal (after careful approaching) from a distance < 4 m. To record positions precisely, we established a geo-referenced grid of landmarks (4 × 4-m cells) above each burrow system before the radio tracking began. The accuracy of fixes was estimated at ≤ 0.5 m by projecting the animal positions onto maps of mapped burrow systems. Radio tracking was performed in sessions lasting 8–48 h, separated by 8–72 h breaks, until a complete 72-h radio-tracking record was obtained for a given group of 3–7 individuals tracked simultaneously. This was completed within 10–12 days in 2005 and within 8 days in 2008. There were three radio-tracking periods in each year: 8 June–7 July 2005; 10 July–5 August 2005; 10–30 August 2005, 13–22 October 2008, 2–9 November 2008, and 23–30 November 2008. Each individual contributed a maximum of one 72-h radio-tracking record per period, consisting of 144 fixes. Of these six periods, one could be denoted as the coldest of the year (period 2) and two as the hottest periods of the year (periods 4 and 5, see Table 1 ). Table 1 List of radio-tracking periods, including the number of individuals radio-tracked and their mean body mass, and temperature characteristics. Mean daily temperature (°C) Mean daily temperature amplitude (°C) Year Period No. of individuals Mean ± SD (range) body mass (g) at soil surface at 15 cm at soil surface at 15 cm 2005 1: 8 June–7 July 7 (2M:5F) 166 ± 18 (147–190) 16.4 18.0 5.3 1.0 2: 10 July–5 August 10 (3M:7F) 166 ± 16 (147–190) 16.3 17.7 5.7 1.7 3: 10–30 August 9 (3M:6F) 160 ± 15 (144–190) 19.5 19.8 8.8 2.7 2008 4: 13–22 October 7 (4M:3F) 176 ± 33 (140–240) 26.3 24.6 21.2 2.0 5: 2–9 November 7 (4M:3F) 176 ± 33 (140–240) 26.3 25.5 17.4 1.8 6: 23–30 November 7 (4M:3F) 176 ± 33 (140–240) 24.6 24.4 12.5 1.8 Processing of radio-tracking data For each of the 144 fixes per individual and period, activity was categorised as either outside or inside the nest and as moving or not, following Šklíba et al. ( 2007 ). A lack of motion was indicated by a predominantly slow and stable signal rate or a fast and stable signal rate while the individual was inside the nest. Motion was indicated by irregular signal rate or a stable fast signal rate while the individual was outside the nest. The nest was considered as a location where an individual was repeatedly fixed while resting in curled-up body position (indicated by a slow and stable signal rate). This was confirmed by excavation of the whole burrow systems in 2005 (Šklíba et al. 2009 ). For each individual and period, the proportion of fixes with motion and proportion of outside-nest fixes was calculated for each hourly interval of the 24-h day (based on 6 fixes per hourly interval). General patterns of motion/presence outside the nest were then derived as arrays of 24 hourly mean values representing the means across all individuals radio-tracked during the corresponding period. The distinctness of an activity pattern was defined as the difference between the minimum and maximum of these 24 hourly mean values comprising that activity pattern. Climatic data logging and processing Temperature data were recorded every 10 minutes using four data loggers (R011E; COMET SYSTEM, Czech Republic). In June–August 2005, three data loggers were buried at a depth of 15 cm at three different places within the study area, while a fourth was placed on the soil surface. In October–November 2008, a set of three data loggers was placed in two places of the study locality at the depths of 10 and 20 cm, and one at the surface. Temperature records were averaged for a corresponding depth and for each radio-tracking period a single mean value was calculated for each 1-h interval of the day resulting in a single 24-hour temperature course. In order to have the 24-h temperature courses from the depths of 0, 5, 10, 15 and 20 cm (and 25 cm for the year 2008 only) for the respective periods, we filled the missing data by interpolation and extrapolation (for detailed description of the procedure see the supplementary materials). Rainfall data were obtained from a nearby weather station operated by the landowner. Statistical analyses As the primary measure of mole-rat activity, we selected the presence outside the nest rather than body motion, as it reflects more accurately the supposed daily variation in the need for a thermally insulated shelter. To examine the relationship between the activity patterns and temperature fluctuations at the respective depths, we used Pearson correlations. The distinctness of daily activity pattern (as defined above) was assessed in relation to the daily temperature amplitude for 0, 5, 10, 15 and 20 cm using a series of Pearson correlations. All statistical analyses were conducted in R (R Core Team 2024 ). Results Climatic conditions during the two study seasons are summarised in Table 1 and Fig. 1 . The cold dry season of 2005 (periods 1–3) was characterised by low soil surface temperatures with small daily amplitudes (Fig. 1 a), while the advanced hot dry season of 2008 (periods 4–6) exhibited the opposite pattern (Fig. 1 b). In both seasons, daily temperature amplitudes decreased with increasing soil depth, but the decrease was steeper in the hot dry season in 2008 (Fig. 2 ). Relationships between hourly activity and mean hourly temperature at the soil surface and various depths are summarised in Table 2 . As predicted, the correlation between activity and temperature at depths of 15 and 20 cm was positive in the coldest period (Period 2) and negative in the hottest periods (Periods 4 and 5). All these relationships were statistically significant, with most of them remaining significant even after applying the Bonferroni correction (α = 0.05/33 = 0.0015). However, temperatures at 15 cm and 20 cm depths never exhibited the strongest correlations (i.e., the highest absolute values of r) with hourly activity. During the coldest period (Period 2), activity was most closely correlated with temperatures at depths of 5 and 10 cm. In contrast, during the hottest periods (Periods 4 and 5), activity was most strongly correlated with temperature at a depth of 25 cm (negatively) and at the soil surface (positively). Table 2 The Pearson correlation between activity, calculated as the hourly proportion of mole-rat radio fixes located outside the nest, and the daily course of temperature at various depths during the six radio-tracking periods. Asterisks denote correlations that remained statistically significant after the Bonferroni correction (α = 0.0015). Year Period Soil surface 5 cm 10 cm 15 cm 20 cm 25 cm 2005 1 r = 0.029 t = 0.14 p = 0.8918 r = 0.175 t = 0.83 p = 0.4137 r = 0.302 t = 1.49 p = 0.1511 r = 0.347 t = 1.73 p = 0.0971 r = 0.399 t = 2.04 p = 0.0536 NA 2 r = 0.664 t = 4.17 p = 0.0004* r = 0.765 t = 5.57 p < 0.0001* r = 0.782 t = 5.89 p < 0.0001* r = 0.724 t = 4.92 p < 0.0001* r = 0.625 t = 3.75 p = 0.0011* NA 3 r = 0.876 t = 8.50 p < 0.0001* r = 0.728 t = 4.98 p < 0.0001* r = 0.524 t = 2.89 p = 0.0086 r = 0.307 t = 1.51 p = 0.1442 r = 0.057 t = 0.27 p = 0.7906 NA 2008 4 r = 0.842 t = 7.31 p < 0.0001* r = 0.443 t = 2.32 p = 0.0301 r =-0.048 t=-0.23 p = 0.8232 r =-0.492 t=-2.65 p = 0.0145 r =-0.677 t=-4.32 p = 0.0002* r =-0.763 t=-5.54 p < 0.0001* 5 r = 0.796 t = 6.16 p < 0.0001* r = 0.475 t = 2.54 p = 0.0189 r = 0.017 t = 0.08 p = 0.9377 r =-0.461 t=-2.43 p = 0.0235 r =-0.708 t=-4.71 p = 0.0001* r =-0.841 t=-7.28 p < 0.0001* 6 r = 0.754 t = 5.38 p < 0.0001* r = 0.595 t = 3.47 p = 0.0022 r = 0.298 t = 1.46 p = 0.1580 r =-0.100 t=-0.47 p = 0.6409 r =-0.312 t=-1.54 p = 0.1374 r =-0.550 t=-3.09 p = 0.0054 The distinctness of the activity pattern was significantly correlated with the mean hourly temperature amplitude at the soil surface and at depths of up to 10 cm but not at the typical burrow depths of 15–20 cm (Pearson correlation, Table 3 ). Table 3 The relationship between the distinctness of the outside-nest activity pattern (defined as the difference between minimum and maximum hourly activity values) recorded during individual test periods (n = 6) and the amplitude of temperature variation at various depth, as revealed by Pearson correlation. Statistics Soil surface 5 cm 10 cm 15 cm 20 cm r 0.94 0.98 0.88 0.49 0.55 p 0.0043 0.0004 0.0205 0.3227 0.259 Discussion Subterranean rodents inhabit burrow systems consisting of tunnels and chambers located across a range of depths; however, most tunnels are situated at a depth that prevents collapse while still providing access to food resources (Hickmann 1990). For instance, the typical burrow depths of H. argenteocinereus in cultivated (i.e. frequently disturbed) soil is considerably deeper than in natural or degraded natural habitats (Šumbera et al. 2004 , 2007 ). Burrows located at such depths are often classified as foraging burrows. Their branches often extend closer to the surface in order to search for shallow food resources or deposit soil into mounds. On the other hand, the deepest tunnels within individual burrow systems likely serve anti-predatory, thermoregulatory, or drainage functions (Nevo 1999 , Hickmann 1990, Šklíba et al. 2008 ). Additionally, some species construct so-called axial or “highway” tunnels at intermediate depths to enable rapid movement across the burrow systems (Lovegrove and Painting 1987 , Scharff et al. 2001 , Šumbera et al. 2012 ). However, such structures have never been reported in H. argenteocinereus . The typical depth of the silvery mole-rat’s foraging tunnels (measured from the tunnel floor to the soil surface) in natural habitats is 15–20 cm (Šumbera et al. 2004 , 2008 ). This is comparable to that of the similar-sized Nannospalax galili (16–17 cm; Lövy et al. 2015 ), considerably deeper than that of the smaller Fukomys anselli (11 cm; Šklíba et al. 2012 ) and the highveld mole-rat Cryptomys hottentotus pretoriae (14 cm; Hickman 1979 ), and much shallower than that of the large-bodied Bathyergus suillus , which inhabits sandy soils (28–48 cm; Thomas et al. 2012 ). It is reasonable to assume that mole-rats spend most of their active time at these typical depths of their foraging burrows, as they must dedicate significant time to excavating, maintaining, patrolling and ultimately backfilling them. We therefore hypothesised that temperature variation at such depths would have the strongest influence on activity timing. This, however, was not confirmed by our results. In line with our first prediction, a positive correlation between activity and temperature at 15–20 cm below the soil surface during the coldest period (Period 2) became negative during the hottest periods (Periods 4–5). However, the temperature at 15 or 20 cm did not exhibit the strongest correlation with activity during any of these periods, failing to support our second prediction. Our data demonstrate that the activity of free-living silvery mole-rats correlated more strongly with the temperature at shallower depths (5–10 cm) during the coldest period (positively) and with the temperature at greater depth (25 cm and possibly deeper) during the hottest periods (negatively). Determining whether this pattern is merely coincidental or indicative of a broader phenomenon among subterranean rodents in seasonal environments would require comparable data from other species. Unfortunately, studies examining activity across contrasting seasons while measuring soil temperatures at various depths are rare. A brief review of such studies follows. Rado et al. ( 1993 ) found that the activity of radio-tracked Middle East blind mole rats Nannospalax ehrenbergii peaked between the time of maximum soil surface temperature and the time of maximum temperature at a depth of 20 cm in winter, while in summer, activity peaked at the time of the lowest temperature at 20 cm. This pattern closely aligns with our findings. A relevant comparison can also be made with Okrouhlík et al. ( 2021 ), who monitored year-round body temperature variations in two South African solitary mole-rat species using implanted temperature loggers. An increase in body temperature is widely considered a reliable proxy for physical activity (Benstaali et al. 2001 ). In July, the coldest month of the year, both Cape mole-rat Georychus capensis and Cape dune mole-rat Bathyergus suilus exhibited peak body temperatures around 17:00, coinciding with the temperature maximum at a depth of 10 cm. In contrast, during January, the hottest period of the year, peak body temperature in both species shifted to 12:00–14:00, corresponding to the temperature minimum at a depth of 30 cm. These findings are again consistent with our results for H. argenteocinereus . Finn et al. ( 2022 ) explored seasonal changes in the daily activity patterns of the social Natal mole-rat Cryptomys hottentotus natalensis using passive transponder implants and RFID readers placed over a frequently used burrow. While this method proved viable for this purpose, pooling data over 3 months and the limited soil temperature monitoring hindered detailed comparisons with our results. During the cold winter, the activity of C. h. natalensis closely correlated with temperatures in shallow soil layers, mirroring our results for H. argenteocinereus . In contrast, during the hot summer, their activity exhibited a bimodal pattern, decreasing during the hottest part of the day. Similar daily patterns of body-core temperature —unimodal T b in winter but bimodal T b in summer — were found in the same species using implanted temperature loggers (Oosthuizen et al. 2021 ). The bimodal activity pattern, which avoids daily temperature extremes has also been described in the plains pocket gopher Geomys bursarius (Benedix 1994 ) and in some individuals of H. argenteocinereus (Šklíba et al. 2007 ). Based on the literature reviewed above, we can conclude that seasonal variation in daily activity patterns in response to daily temperature fluctuations at different soil depths, as described for the silvery mole-rat (i.e. activity correlating positively with near-surface soil temperatures during cold periods and negatively with temperatures at greater depths during hot periods), appears to be consistent across various subterranean rodent species. It is therefore reasonable to seek a biologically meaningful explanation for this phenomenon. Our data show that daily temperature variation at a depth of around 15 cm is already substantially buffered, with an amplitude ranging between 1.0 to 2.7°C, depending on the period of the year (Table 1 and Fig. 1 ). If mole-rats spend even brief periods at shallower depths—such as when pushing soil to form aboveground mounds, digging near the soil surface, or collecting food or nest bedding—the greater temperature variation at these depths would result in significantly higher daily variation in thermoregulatory costs compared to the more stable thermal conditions at depths of 15–20 cm. As a result, the activity of mole-rats could be more strongly corelated with the temperature at shallower layers of soil rather than where the majority of tunnels are situated. This is exactly what we observed during the coldest period of the year (Period 2), when the activity of silvery mole-rats was most closely associated with the temperature at 5–10 cm below the soil surface. Similarly, activity patterns of N. ehrenbergii and N. galili during cold Mediterranean winters were closely related to the temperatures measured between the typical burrow depth and the soil surface (Rado et al. 1993 ; Šklíba et al. 2016 ). In contrast, our data from the hottest periods show no negative correlation between mole-rat activity and the temperature near the soil surface. Instead, activity was most strongly correlated with the temperature at a depth of 25 cm (negatively) and with surface temperature (positively). Surface temperature is unlikely to have a direct effect on mole-rat activity during the peak dry season, as they are not active on the surface. During advanced dry seasons, subterranean and fossorial rodents even cease pushing soil into aboveground mounds (which is sometimes misinterpreted as an indication of decreased overall activity) and instead backfill existing burrows (Miller 1948 ; Jarvis 1973 ; Lovegrove and Painting 1978; Jarvis et al. 1998 ; Šumbera et al. 2003 , Herbst and Bennett 2006 ; Šklíba et al. 2009 ). On the contrary, some effect of the daily temperature cycle at a depth of 25 cm (and possibly deeper) on the timing of activity in the silvery mole-rats is theoretically possible if they would preferentially excavate and/or use deeper parts of burrow systems rather than extending and backfilling foraging tunnels at the usual depth of 15–20 cm in the peak hot dry season. Nevertheless, this scenario seems unlikely given the minimal daily temperature variation at the depth of 25 cm and deeper. Unfortunately, we could not determine the depth at which radio-collared mole-rats were active, as radio-tracking did not allow for depth estimation, and burrow depths was not surveyed during the corresponding radio-tracking periods. Theoretically, mole-rats might be forced to burrow deeper due to the increasing hardness of shallower soil layers and the challenges associated with transporting loose, dry soil and depositing it into mounds. The energetic cost of burrowing in dry, hard soils is significantly higher than in damp soils, as demonstrated in fossorial tuco-tuco (Luna and Antinuchi 2006 ). Additionally, mole-rats might prefer to use deeper sections of their burrow systems to facilitate heat dissipation during the hottest periods, as their body heat is effectively transferred by conduction through their feet and ventral thermal window, particularly when in contact with moist soil (Šumbera et al. 2007 , McGowan et al. 2020 , Okrouhlík et al. 2015 , Vejmělka et al. 2021 ). Notably, temperature typically decreases with depth during the hottest part of the year and increases during the coldest one, as the annual temperature cycle is phase-shifted with depth, similar to the daily temperature cycle (see Fig. 2 ). During the hottest periods, the daily temperature amplitude at 25 cm was around 1°C, with a mean temperature around 1.7°C lower than at the surface (see Fig. 2 ). However, evidence for seasonal variation in burrowing depth among subterranean rodents is limited. Foraging burrows were found to be 7.6–15.2 cm deeper during warm seasons compared to cold seasons in Geomys pinetis (Brown and Hickman 1973 ) and 2.5 cm deeper cm in Geomys attwateri (Williams and Cameron 1990 ). In contrast, no seasonal change in burrow depth was found in H. argenteocinereus by Šumbera et al. ( 2004 , unpublished data). Another plausible explanation for the observed activity patterns during the hottest periods relates to the fact that around midday, mean temperatures across depths of approximately 15–25 cm were nearly uniform (Fig. 3). During these periods, such temperatures were at or just below the lower critical temperature of the silvery mole-rat’s thermoneutral zone (25–33°C; Zelová et al. 2007 ). These conditions may be suitable for activity, or at least for moderate levels of physical exertion, such as walking and patrolling the burrow system. It remains possible that activities producing substantial metabolic heat, which require heat dissipation to avoid overheating (Okrouhlík et al. 2015 , Vejmělka et al. 2021 ), occur at different times of the day or in short bouts throughout the whole 24-h day. Unfortunately, our method of studying mole-rat activity does not differentiate between varying levels of physical activity. Implementing new biologging tools could provide better insights into the temporal distribution of different levels of physical activity and its relation with daily temperature fluctuations at various depths. A pioneering study in this area of research is Finn et al. ( 2024 ), which monitored the activity of free-ranging highveld mole-rats Cryptomys hottentotus pretoriae fitted with accelerometers. Although this study did not differentiate between activity levels, its findings remain highly relevant to the present study, as the daily activity pattern detected differs markedly from what we describe for H. argenteocinereus. Even during the hot late summer (February to March), highveld mole-rats exhibited a clear daily activity peak coinciding with the highest soil temperature at a depth of 10 cm – a depth that roughly represents a typical burrow depth. The authors proposed that the ideal temperature for activity, including digging, in C. h. pretoriae can be as high as 30°C and attributed this to its unusual physiological traits such as unusual physiological traits, such as high body temperature, narrow TNZ, low metabolic rate, and high thermal conductance. Interestingly, 30°C also corresponds to the lower critical temperature of its TNZ (Haim and Fairall 1986 ). In contrast, the silvery mole-rat which has well-insulating fur that does not allow for very effective heat dissipation during intensive physical activity like digging (Šumbera et al. 2007 ), is more susceptible to overheating. Consequently, its behavioural thermoregulation during the hottest periods of the year likely involves avoiding high temperatures rather than preferring them, as seen in C. h. pretoriae (Finn et al. 2024 ). Our last prediction stated that activity patterns would become more distinct during periods with greater daily temperature variation (i.e. amplitude) at the typical burrow depths. However, it was not supported by our data. While activity pattern distinctness was closely correlated with daily temperature amplitude at the soil surface and at depths up to 10 cm, the correlation was no longer significant at 15 and 20 cm (Table 3 ). This result should be interpreted with caution, as the six radio-tracking periods were unevenly distributed during the year. Nevertheless, it suggests that the temperature variation closer to the surface, and not necessarily at the usual burrow depth, might induce the need for greater regularity in activity timing. Data from Okrouhlík et al. ( 2021 ) further allow comparisons of the “distinctness” of daily body temperature patterns in two solitary bathyergids, Georychus capensis and Bathyergus suilus , throughout the whole year. In both species the patterns were most distinct during the hottest months (January and February), flattened in May, reemerged as distinct in the coldest month (July), and flattened again in October. The daily activity patterns of the silvery mole-rat can be compared to those of other subterranean and fossorial rodents using comparable methodological approaches to identify factors determining the distinctness of the patterns (see Table 4 ). Species with distinct activity patterns include Fukomys anselli , Nannospalax ehrenbergii and Tachyoryctes macrocephalus . Of these, T. macrocephalus inhabits the Afroalpine ecosystem, characterised by a large daily temperature amplitude (up to 24°C at the surface, Vlasatá et al. 2017 ). Unlike strictly subterranean species, it feeds on the ground surface, likely increasing its daily thermoregulatory costs of its activity. On the contrary, F. anselli is a small-bodied social species with a relatively high thermal conductance (Marhold and Nagel 1995 ) and relatively shallow burrow systems (Šklíba et al. 2012 ), factors that likely contribute to its high distinctness of its activity pattern. Very distinct patterns were also detected in N. ehrenbergii from Israel’s coastal plain (Rado et al. 1993 ) but not in N. galili from the more mesic Israeli highlands (though the latter species was not studied in summer) (Šklíba et al. 2016 ). The least distinct daily activity pattern was found in F. mechowii , a large-bodied social mole-rat. However, this finding applied to individuals living in a family, whereas a solitary-living female of the same species exhibited a distinct daily activity pattern strongly correlated with temperature, resembling that of H. argenteocinereus (Lövy et al. 2013 ). Table 4 Distinctness of activity patterns in radio-tracked subterranean rodents (defined as the difference between minimum and maximum hourly activity values). Species Season or period of the year Mean daily surface temperature range Range of hourly % outside-nest fixes Activity pattern distinctness T. macrocephalus a) Early dry season 3.0–17.4 0–73.5 0.74 T. macrocephalus a) Late dry season 0.6–24.8 0–67.7 0.68 N. ehrenbergii b) Winter 7–20 8–76 0.68 N. ehrenbergii b Summer 20–31 10–92 0.82 N. galili on basalt c) Winter 4.1–7.5 0–57.5 0.58 N. galili on chalk c) Winter 4.3–11.2 1.4–45.8 0.44 F. anselli (nonbreeders) d) Cold dry season 14.3–28.9 6.8–93.2 0.86 F. mechowii (nonbreeders) e) Cold dry season 14.1–28.3 11.1–43.1 0.32 H. argenteocinereus f) The coldest period of the year 14.0–19.7 10–58.3 0.48 H. argenteocinereus f) The hottest periods of the year 18.5–39.0 20.7–38.0 16.7–83.3 14.3–76.2 0.62 0.67 a) Vlasatá et al. 2017 , b) Rado et al. 1993 , c) Šklíba et al. 2016 , d) Šklíba et al. 2014 , e)vy et al. 2013, f) the present study To conclude, the silvery mole-rat, like most other subterranean rodents, adjust its activity timing in response to daily temperature fluctuations. However, temperature fluctuation at typical foraging burrow depths does not appear to be the primary factor influencing activity timing. Instead, temperature cycles closer to the soil surface seem to play a more important role, particularly during the coldest periods of the year. In contrast, interpreting the biological significance of activity patterns observed during the hottest periods is more challenging, although these patterns were notably distinct. We propose that during the hottest periods, mole-rats may preferentially construct or just move within deeper sections of their burrow systems or time their activity to coincide with a part of the day when soil temperatures across a range of depths (e.g. 15–25 cm) converge—provided these temperatures still remain below the lower critical temperature of their TNZ. To further verify and elaborate our conclusions, further research should focus on subterranean rodents inhabiting a broad range of ambient temperatures. Ideal candidates include common mole-rats of the genus Cryptomys from Southern Africa, which occupy habitats ranging from hot coastal plains to the cold Drakensberg Mountains. Additionally, studies employing accelerometers to classify various activity types —such as digging, walking, and soil transport —under different climatic conditions throughout the year could provide valuable insights into their behavioural and thermoregulatory adaptations. Importantly, these studies should include precise temperature measurements at multiple soil depths and, if possible, accurate measurements of burrow depth. Declarations Acknowledgements We thank the Genetic Resources and Biotechnology Committee and the Technical Committee of the National Research Council of Malawi for a permission to conduct our research in Malawi. We are deeply grateful to Tamsin and Stephen Christie, owners of the Mpalanganga Estate, for their hospitality and generous support. We thank Jitka Malá (née Zelová), Stephan Koeppen, Aphiri, Charles, and Moren for their invaluable assistance in the field. The study was funded by GAAV (KJB601410826 and IAA601410802). Author contributions All authors contributed to the organization and execution of the field research, as well as writing of the manuscript. JS conceived the study and prepared the first draft. ML conducted the final statistical analyses. ML and RS provided critical input into the interpretation of results. WNC facilitated the acquisition of fieldwork permits and managed field logistics. Statement of animal ethics All procedures involving wild-caught animals were performed in a humane manner. These procedures were approved by the National Research Council of Malawi (NRCM), the Research and Publications Committee of the University of Malawi, Chancellor College, and the Control Commission for Ethical Treatment of Animals of the University of South Bohemia, Faculty of Biological Sciences, Czech Republic. Conflict of interest statement On behalf of all authors, the corresponding author states that there is no conflict of interest. References Bartness TJ, Albers HE (2000) Activity patterns and the biological clock in mammals. In: Halle S, Stenseth NC (eds) Activity patterns in small mammals: an ecological approach. Springer, Berlin, pp 23–47 Benedix JH (1994) A predictable pattern of daily activity by the pocket gopher Geomys bursarius . Anim Behav 48:501–509. https://doi.org/10.1006/anbe.1994.1271 Benstaali C, Mailloux A, Bogdan A, Auzeby A, Touitou Y (2001) Circadian rhythms of body temperature and motor activity in rodents: their relationships with the light-dark cycle. Life Sci 68(24):2645–2656. https://doi.org/10.1016/S0024-3205(01)01081-5 Brown LN, Hickman GC (1973) Tunnel system structure of the southeastern pocket gopher. 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Comp Biochem Physiol A 147:412–419. https://doi.org/10.1016/j.cbpa.2007.01.002 Supplementary Files Supplmat02.pdf Cite Share Download PDF Status: Published Journal Publication published 10 Sep, 2025 Read the published version in Mammalian Biology → Version 1 posted Reviewers agreed at journal 20 Mar, 2025 Reviewers invited by journal 20 Mar, 2025 Editor assigned by journal 28 Feb, 2025 First submitted to journal 27 Feb, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6120103","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":431458005,"identity":"870df83e-4b59-419b-a29d-399f95e4803f","order_by":0,"name":"Jan Šklíba","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYBACxgY2xgOJDQxyDAw8xGthAGkxJl4LAwNQC2MDA1AXsVqY+48lHHi4wy59w/GzBx98YLCT020g5LAZaQcOJJ5Jzt1wJi/ZcAZDsrHZAYJa2BsOJLYx5244kGMmzQP01zaCWvqPg7TUpxucf0OslgaQw9oOJxjcINqWGWkJQL8cN5x5442x4QwDIvxi2H/M8OHPHdXyfOdzDB98qLCTI6ylAcpQAKs0IKAcBOThjAY8qkbBKBgFo2BkAwBpFEqT++77AwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-0567-9302","institution":"University of South Bohemia: Jihoceska Univerzita v Ceskych Budejovicich","correspondingAuthor":true,"prefix":"","firstName":"Jan","middleName":"","lastName":"Šklíba","suffix":""},{"id":431458006,"identity":"48ba3984-a3d5-485b-a578-bd8f77b8a2d7","order_by":1,"name":"Matěj Lövy","email":"","orcid":"","institution":"University of South Bohemia: Jihoceska Univerzita v Ceskych Budejovicich","correspondingAuthor":false,"prefix":"","firstName":"Matěj","middleName":"","lastName":"Lövy","suffix":""},{"id":431458007,"identity":"4df27952-e5b5-43d4-9a63-27c08cd6e805","order_by":2,"name":"Wilbert Newton Chitaukali","email":"","orcid":"","institution":"University of Malawi Chancellor College","correspondingAuthor":false,"prefix":"","firstName":"Wilbert","middleName":"Newton","lastName":"Chitaukali","suffix":""},{"id":431458008,"identity":"a121595e-2d5e-4a9a-ae2b-9ad7617ac57b","order_by":3,"name":"Radim Šumbera","email":"","orcid":"","institution":"University of South Bohemia: Jihoceska Univerzita v Ceskych Budejovicich","correspondingAuthor":false,"prefix":"","firstName":"Radim","middleName":"","lastName":"Šumbera","suffix":""}],"badges":[],"createdAt":"2025-02-27 10:37:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6120103/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6120103/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s42991-025-00513-y","type":"published","date":"2025-09-10T15:57:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79451640,"identity":"418e5f6e-38ef-4b41-bc8e-c170cd0fdfeb","added_by":"auto","created_at":"2025-03-28 15:07:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":114679,"visible":true,"origin":"","legend":"\u003cp\u003eMean, minimum and maximum daily temperature on the soil surface and rainfall pattern (blue columns) during cold dry season 2005 (a) and end of hot dry season 2008 (b) in the study locality. Horizontal orange bars mark the radio-tracking periods 1–6.\u003c/p\u003e","description":"","filename":"figure1letters2.png","url":"https://assets-eu.researchsquare.com/files/rs-6120103/v1/b19bef3c9a2dcdf5a56b4943.png"},{"id":79451644,"identity":"de32e44c-6abc-4c62-95e1-1b1c29e836aa","added_by":"auto","created_at":"2025-03-28 15:07:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":122859,"visible":true,"origin":"","legend":"\u003cp\u003eActivity patterns of mole-rats (left) and corresponding daily temperature course at various depths under the soil surface (left) in 6 radio-tracking periods: a) Period 1: 8 June–7 July 2005, b) Period 2: 10 July–5 August 2005, c) Period 3: 10–30 August 2005, d) Period 4: 13–22 October 2008, e) Period 5: 2–9 November 2008, and f) Period 6: 23–30 November 2008. Black bars represent mean proportion of individuals being outside the nest, grey bars show mean proportion of individuals in motion.\u003c/p\u003e","description":"","filename":"figure1letters1.png","url":"https://assets-eu.researchsquare.com/files/rs-6120103/v1/3259efe4004f8725dc5f3235.png"},{"id":91359175,"identity":"3072a11c-c227-40d9-9c58-791bbff5434c","added_by":"auto","created_at":"2025-09-15 16:05:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1098986,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6120103/v1/3f2c0398-b704-4384-ac88-30c1ead47276.pdf"},{"id":79452663,"identity":"9f4d1ae9-ac47-4733-971f-453dd5861209","added_by":"auto","created_at":"2025-03-28 15:15:05","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":212647,"visible":true,"origin":"","legend":"","description":"","filename":"Supplmat02.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6120103/v1/5611e21ba82336a83b330e88.pdf"}],"financialInterests":"","formattedTitle":"Seasonal variation of the daily activity patterns in a subterranean rodent in response to underground temperature fluctuations","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe activity of most mammals follows a predictable daily pattern that reduces energetic costs including those associated with thermoregulation. These patterns are usually governed by circadian rhythms that are primarily maintained by the natural cycle of light (Bartness and Albers \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), although ambient temperature cycles could also play an important role (Wams et al. 2017). Unsurprisingly, daily activity patterns may vary substantially throughout the year due to seasonal thermoregulatory challenges (van der Vinne et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Silv\u0026eacute;rio et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe subterranean way of life, which has evolved independently in various phylogenetically unrelated groups of mammals, provides an opportunity to investigate the daily activity patterns that emerge under largely restricted and irregular exposure to daylight combined with substantially buffered daily\u0026mdash;and, to a lesser extent, annual\u0026mdash;ambient temperature fluctuations. For this purpose, subterranean rodents serve as an ideal model group. First, they share similar foraging ecology across unrelated taxa, relying primarily on underground plant storage organs reached by burrowing through the soil (Nevo \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1999\u003c/span\u003e, Lacey et al. 2000). Second, they have a restricted opportunity for evaporative cooling due to the high humidity in burrow systems, making them susceptible to overheating during burrowing (Luna et. al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Okrouhl\u0026iacute;k et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, Walace et al. 2021, Šumbera \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, McGowan et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven the dark and thermally buffered environment beneath the soil surface, one might assume that free-living subterranean mammals lack predictable daily activity patterns (e.g. Nevo \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1979\u003c/span\u003e). However, this assumption has already been disproven by early telemetry studies on several subterranean and fossorial rodents of temperate zones (Gettinger \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Rado et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Benedix \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). These studies demonstrated a clear link between activity and daily variation in burrow or soil temperature. Later, we demonstrated that temperature-driven daily activity patterns also occur in tropical subterranean rodents, such as the silvery mole-rat \u003cem\u003eHeliophobius argenteocinereus\u003c/em\u003e from southern Malawi (Škl\u0026iacute;ba et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). During the coldest period of the year, the proportion of radio-tracked mole-rats active at a given time of the day was positively correlated with temperature at a typical foraging burrow depth. This relationship disappeared a few weeks later when mean daily temperatures increased. Based on these findings, we proposed that the mole-rats concentrate their activity during periods of the day when thermoregulatory costs are minimized due to favourable temperatures. This behaviour can be interpreted as a form of behavioural thermoregulation (Richards \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1973\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecent studies have further supported the role of ambient temperature in shaping daily activity patterns in subterranean rodents. Laboratory experiments on African mole-rats (e.g., \u003cem\u003eCryptomys hottentotus mahali\u003c/em\u003e in Van Jaarsveld et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cem\u003eGeorychus capensis\u003c/em\u003e and \u003cem\u003eC. h. mahali\u003c/em\u003e in Hart et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cem\u003eFukomys damarensis\u003c/em\u003e in Grenfell et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; see also Oosthuizen and Bennett \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e for a review) and field studies on free-living populations (e.g., \u003cem\u003eC. h. natalensis\u003c/em\u003e in Finn et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e and Oosthuizen et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e h. \u003cem\u003epretoriae\u003c/em\u003e in Finn et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) have demonstrated that temperature significantly influences activity rhythms. These findings reinforce the idea that behavioural thermoregulation is a key driver of activity patterns in subterranean rodents.\u003c/p\u003e \u003cp\u003eThe benefits of such behavioural thermoregulation are likely greatest during periods with extreme annual temperatures or during periods when daily temperature variation is most pronounced. Based on this, we hypothesise that the activity patterns of the silvery mole-rat change predictably throughout the year, with activity concentrated during periods of the day when thermoregulatory costs are minimized due to favourable temperatures. Specifically, the relationship between activity and temperature at typical burrow depths, which was found to be positive during the coldest period of the year (Škl\u0026iacute;ba et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), is expected to reverse during the hottest periods. Furthermore, as an extension of this hypothesis, we propose that during periods when daily temperature variation at typical burrow depths is more pronounced, silvery mole-rats would exhibit more distinct daily activity patterns.\u003c/p\u003e \u003cp\u003eWe analysed radio-tracking data from seven silvery mole-rats collected at the end of the hot dry season of 2008, which covers the hottest part of the year. For comparison, we reanalysed similar data from the cold dry season of 2005, which encompasses the coldest part of the year and was largely published in Škl\u0026iacute;ba et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). To test the hypothesis that silvery mole-rats concentrate their activity during parts of the day when thermoregulatory costs are lowest, we formulated the following predictions:\u003c/p\u003e \u003cp\u003e1) The correlation between hourly activity (defined as the proportion of radio-fixes of all individuals radio-tracked during the corresponding period located outside their nests at a given hour of the 24-h day) and the mean hourly temperature (calculated as the mean for the corresponding hour of the 24-h day over the entire period) at typical foraging burrow depths (15\u0026ndash;20 cm) will be positive during the coldest period and negative during the hottest periods of the year.\u003c/p\u003e \u003cp\u003e2) The hourly activity will correlate more strongly with the mean hourly temperature at typical foraging burrow depths (15\u0026ndash;20 cm) than temperatures at other depths, during both the coldest and hottest periods.\u003c/p\u003e \u003cp\u003e3) Daily activity patterns will be more distinct during periods with greater amplitude of the mean hourly soil temperature, particularly when considering the temperature variation at typical depth of foraging burrows (15\u0026ndash;20 cm). We quantified the distinctness of the activity patterns as the difference between the minimum and maximum hourly activity value for a given period.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy species\u003c/h2\u003e \u003cp\u003eThe silvery mole-rat is a solitary bathyergid widely distributed across open canopy woodlands and grasslands in Central and Eastern Africa (Šumbera et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). It constructs dynamic burrow systems where usually a single nest at a time is used for resting. The outside-nest activity of the silvery mole-rat is polyphasic, with variable but generally predictable (unimodal, occasionally bimodal) daily patterns (Škl\u0026iacute;ba at al. 2007). Soil excavated during burrowing is deposited either into older burrows or in surface mounds (Škl\u0026iacute;ba et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Šumbera et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Foraging burrows in non-cultivated soil are typically 15\u0026ndash;20 cm deep (measured from the tunnel floor to the soil surface), while nest chambers is usually 20\u0026ndash;40 cm deep (Šumbera et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy locality\u003c/h3\u003e\n\u003cp\u003eThe study was conducted in a fragment of miombo woodland (dominated by \u003cem\u003eBrachystegia\u003c/em\u003e spp.) on Mpalanganga estate, Zomba, Southern Malawi (15\u0026deg;27\u0026rsquo; S, 35\u0026deg;16\u0026rsquo; E, 1070 m a. s. l.). The climate in this region is characterized by rainy season (November\u0026ndash;April), cold dry season (May\u0026ndash;August), and hot dry season (September\u0026ndash;November). Soil temperatures reach their annual minimum in July and maximum just before the onset of the rainy season, typically in late November (Šumbera et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eCapture and marking of study animals\u003c/h3\u003e\n\u003cp\u003eMole-rats were captured in May/June 2005 and September 2008 using Hickman\u0026rsquo;s traps or by cutting their retreat with a hoe when they come to seal opened sections of their burrow systems. Adults were shortly immobilised using ketamine and xylazine and fitted with radio-collars (G3-1V transmitter with a position-based activity indicator, BR collar, AVM Instrument Company, Colfax, California). The activity indicator altered the signal rate of the transmitter when the collar deviated from a vertical position (e.g. when the animal lowered its head into a curled-up position, such as during sleep). The weight of the radio-collar was less than 5% of smallest animal 's body weight. Animals were returned to their burrow systems after 6 to 12 hours of recovery and accustoming to the collars. Radio-tracking was successfully conducted on 11 individuals (3 males and 8 females) in 2005 and seven individuals (4 males and 3 females) in 2008. After the study, animals were recaptured to remove the collars and released back into their burrows.\u003c/p\u003e\n\u003ch3\u003eRadio tracking\u003c/h3\u003e\n\u003cp\u003eWe used an LA 12-Q receiver (AVM Instrument Company) and a Yagi antenna to fix the position of the animals. Four to five animals were tracked in rotation, with approximately 30-min intervals between successive fixes of the same animal. Tracking started with an observer listening to the signal of the transmitter for 1\u0026ndash;2 minutes from a distance greater than 10 m to determine whether the signal rate was slow and stable, indicating curled-up body position or fast and stable, indicating little or no motion in other body position or variable, indicating motion. Then the observer fixed the animal (after careful approaching) from a distance\u0026thinsp;\u0026lt;\u0026thinsp;4 m. To record positions precisely, we established a geo-referenced grid of landmarks (4 \u0026times; 4-m cells) above each burrow system before the radio tracking began. The accuracy of fixes was estimated at \u0026le;\u0026thinsp;0.5 m by projecting the animal positions onto maps of mapped burrow systems.\u003c/p\u003e \u003cp\u003eRadio tracking was performed in sessions lasting 8\u0026ndash;48 h, separated by 8\u0026ndash;72 h breaks, until a complete 72-h radio-tracking record was obtained for a given group of 3\u0026ndash;7 individuals tracked simultaneously. This was completed within 10\u0026ndash;12 days in 2005 and within 8 days in 2008. There were three radio-tracking periods in each year: 8 June\u0026ndash;7 July 2005; 10 July\u0026ndash;5 August 2005; 10\u0026ndash;30 August 2005, 13\u0026ndash;22 October 2008, 2\u0026ndash;9 November 2008, and 23\u0026ndash;30 November 2008. Each individual contributed a maximum of one 72-h radio-tracking record per period, consisting of 144 fixes. Of these six periods, one could be denoted as the coldest of the year (period 2) and two as the hottest periods of the year (periods 4 and 5, see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of radio-tracking periods, including the number of individuals radio-tracked and their mean body mass, and temperature characteristics.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eMean daily temperature (\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eMean daily temperature amplitude (\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo. of individuals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (range) body mass (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eat soil surface\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eat 15 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eat soil surface\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eat 15 cm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1: 8 June\u0026ndash;7 July\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (2M:5F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e166\u0026thinsp;\u0026plusmn;\u0026thinsp;18 (147\u0026ndash;190)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2: 10 July\u0026ndash;5 August\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (3M:7F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e166\u0026thinsp;\u0026plusmn;\u0026thinsp;16 (147\u0026ndash;190)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3: 10\u0026ndash;30 August\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (3M:6F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160\u0026thinsp;\u0026plusmn;\u0026thinsp;15 (144\u0026ndash;190)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4: 13\u0026ndash;22 October\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (4M:3F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e176\u0026thinsp;\u0026plusmn;\u0026thinsp;33 (140\u0026ndash;240)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5: 2\u0026ndash;9 November\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (4M:3F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e176\u0026thinsp;\u0026plusmn;\u0026thinsp;33 (140\u0026ndash;240)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6: 23\u0026ndash;30 November\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (4M:3F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e176\u0026thinsp;\u0026plusmn;\u0026thinsp;33 (140\u0026ndash;240)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eProcessing of radio-tracking data\u003c/h3\u003e\n\u003cp\u003eFor each of the 144 fixes per individual and period, activity was categorised as either outside or inside the nest and as moving or not, following Škl\u0026iacute;ba et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). A lack of motion was indicated by a predominantly slow and stable signal rate or a fast and stable signal rate while the individual was inside the nest. Motion was indicated by irregular signal rate or a stable fast signal rate while the individual was outside the nest. The nest was considered as a location where an individual was repeatedly fixed while resting in curled-up body position (indicated by a slow and stable signal rate). This was confirmed by excavation of the whole burrow systems in 2005 (Škl\u0026iacute;ba et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). For each individual and period, the proportion of fixes with motion and proportion of outside-nest fixes was calculated for each hourly interval of the 24-h day (based on 6 fixes per hourly interval). General patterns of motion/presence outside the nest were then derived as arrays of 24 hourly mean values representing the means across all individuals radio-tracked during the corresponding period. The distinctness of an activity pattern was defined as the difference between the minimum and maximum of these 24 hourly mean values comprising that activity pattern.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eClimatic data logging and processing\u003c/h2\u003e \u003cp\u003eTemperature data were recorded every 10 minutes using four data loggers (R011E; COMET SYSTEM, Czech Republic). In June\u0026ndash;August 2005, three data loggers were buried at a depth of 15 cm at three different places within the study area, while a fourth was placed on the soil surface. In October\u0026ndash;November 2008, a set of three data loggers was placed in two places of the study locality at the depths of 10 and 20 cm, and one at the surface. Temperature records were averaged for a corresponding depth and for each radio-tracking period a single mean value was calculated for each 1-h interval of the day resulting in a single 24-hour temperature course. In order to have the 24-h temperature courses from the depths of 0, 5, 10, 15 and 20 cm (and 25 cm for the year 2008 only) for the respective periods, we filled the missing data by interpolation and extrapolation (for detailed description of the procedure see the supplementary materials). Rainfall data were obtained from a nearby weather station operated by the landowner.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStatistical analyses\u003c/h3\u003e\n\u003cp\u003eAs the primary measure of mole-rat activity, we selected the presence outside the nest rather than body motion, as it reflects more accurately the supposed daily variation in the need for a thermally insulated shelter. To examine the relationship between the activity patterns and temperature fluctuations at the respective depths, we used Pearson correlations. The distinctness of daily activity pattern (as defined above) was assessed in relation to the daily temperature amplitude for 0, 5, 10, 15 and 20 cm using a series of Pearson correlations. All statistical analyses were conducted in R (R Core Team \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eClimatic conditions during the two study seasons are summarised in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The cold dry season of 2005 (periods 1\u0026ndash;3) was characterised by low soil surface temperatures with small daily amplitudes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea), while the advanced hot dry season of 2008 (periods 4\u0026ndash;6) exhibited the opposite pattern (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). In both seasons, daily temperature amplitudes decreased with increasing soil depth, but the decrease was steeper in the hot dry season in 2008 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRelationships between hourly activity and mean hourly temperature at the soil surface and various depths are summarised in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. As predicted, the correlation between activity and temperature at depths of 15 and 20 cm was positive in the coldest period (Period 2) and negative in the hottest periods (Periods 4 and 5). All these relationships were statistically significant, with most of them remaining significant even after applying the Bonferroni correction (α\u0026thinsp;=\u0026thinsp;0.05/33\u0026thinsp;=\u0026thinsp;0.0015). However, temperatures at 15 cm and 20 cm depths never exhibited the strongest correlations (i.e., the highest absolute values of r) with hourly activity. During the coldest period (Period 2), activity was most closely correlated with temperatures at depths of 5 and 10 cm. In contrast, during the hottest periods (Periods 4 and 5), activity was most strongly correlated with temperature at a depth of 25 cm (negatively) and at the soil surface (positively).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe Pearson correlation between activity, calculated as the hourly proportion of mole-rat radio fixes located outside the nest, and the daily course of temperature at various depths during the six radio-tracking periods. Asterisks denote correlations that remained statistically significant after the Bonferroni correction (α\u0026thinsp;=\u0026thinsp;0.0015).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeriod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSoil surface\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 cm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 cm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15 cm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20 cm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25 cm\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;0.14\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.8918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.175\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;0.83\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.4137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.302\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;1.49\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.347\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;1.73\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.399\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;2.04\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.664\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;4.17\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0004*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.765\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;5.57\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.782\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;5.89\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.724\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;4.92\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.625\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;3.75\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0011*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.876\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;8.50\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.728\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;4.98\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.524\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;2.89\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.307\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;1.51\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.057\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;0.27\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.7906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.842\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;7.31\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.443\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;2.32\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e=-0.048\u003c/p\u003e \u003cp\u003et=-0.23\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.8232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e=-0.492\u003c/p\u003e \u003cp\u003et=-2.65\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e=-0.677\u003c/p\u003e \u003cp\u003et=-4.32\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0002*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e=-0.763\u003c/p\u003e \u003cp\u003et=-5.54\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.796\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;6.16\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.475\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;2.54\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;0.08\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.9377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e=-0.461\u003c/p\u003e \u003cp\u003et=-2.43\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e=-0.708\u003c/p\u003e \u003cp\u003et=-4.71\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e=-0.841\u003c/p\u003e \u003cp\u003et=-7.28\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.754\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;5.38\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.595\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;3.47\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.298\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;1.46\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e=-0.100\u003c/p\u003e \u003cp\u003et=-0.47\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.6409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e=-0.312\u003c/p\u003e \u003cp\u003et=-1.54\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e=-0.550\u003c/p\u003e \u003cp\u003et=-3.09\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe distinctness of the activity pattern was significantly correlated with the mean hourly temperature amplitude at the soil surface and at depths of up to 10 cm but not at the typical burrow depths of 15\u0026ndash;20 cm (Pearson correlation, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe relationship between the distinctness of the outside-nest activity pattern (defined as the difference between minimum and maximum hourly activity values) recorded during individual test periods (n\u0026thinsp;=\u0026thinsp;6) and the amplitude of temperature variation at various depth, as revealed by Pearson correlation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSoil surface\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 cm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 cm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15 cm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20 cm\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.0043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.3227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.259\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSubterranean rodents inhabit burrow systems consisting of tunnels and chambers located across a range of depths; however, most tunnels are situated at a depth that prevents collapse while still providing access to food resources (Hickmann 1990). For instance, the typical burrow depths of \u003cem\u003eH. argenteocinereus\u003c/em\u003e in cultivated (i.e. frequently disturbed) soil is considerably deeper than in natural or degraded natural habitats (Šumbera et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Burrows located at such depths are often classified as foraging burrows. Their branches often extend closer to the surface in order to search for shallow food resources or deposit soil into mounds. On the other hand, the deepest tunnels within individual burrow systems likely serve anti-predatory, thermoregulatory, or drainage functions (Nevo \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1999\u003c/span\u003e, Hickmann 1990, Škl\u0026iacute;ba et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Additionally, some species construct so-called axial or \u0026ldquo;highway\u0026rdquo; tunnels at intermediate depths to enable rapid movement across the burrow systems (Lovegrove and Painting \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1987\u003c/span\u003e, Scharff et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2001\u003c/span\u003e, Šumbera et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). However, such structures have never been reported in \u003cem\u003eH. argenteocinereus\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eThe typical depth of the silvery mole-rat\u0026rsquo;s foraging tunnels (measured from the tunnel floor to the soil surface) in natural habitats is 15\u0026ndash;20 cm (Šumbera et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). This is comparable to that of the similar-sized \u003cem\u003eNannospalax galili\u003c/em\u003e (16\u0026ndash;17 cm; L\u0026ouml;vy et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), considerably deeper than that of the smaller \u003cem\u003eFukomys anselli\u003c/em\u003e (11 cm; Škl\u0026iacute;ba et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and the highveld mole-rat \u003cem\u003eCryptomys hottentotus pretoriae\u003c/em\u003e (14 cm; Hickman \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1979\u003c/span\u003e), and much shallower than that of the large-bodied \u003cem\u003eBathyergus suillus\u003c/em\u003e, which inhabits sandy soils (28\u0026ndash;48 cm; Thomas et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). It is reasonable to assume that mole-rats spend most of their active time at these typical depths of their foraging burrows, as they must dedicate significant time to excavating, maintaining, patrolling and ultimately backfilling them. We therefore hypothesised that temperature variation at such depths would have the strongest influence on activity timing. This, however, was not confirmed by our results.\u003c/p\u003e \u003cp\u003eIn line with our first prediction, a positive correlation between activity and temperature at 15\u0026ndash;20 cm below the soil surface during the coldest period (Period 2) became negative during the hottest periods (Periods 4\u0026ndash;5). However, the temperature at 15 or 20 cm did not exhibit the strongest correlation with activity during any of these periods, failing to support our second prediction. Our data demonstrate that the activity of free-living silvery mole-rats correlated more strongly with the temperature at shallower depths (5\u0026ndash;10 cm) during the coldest period (positively) and with the temperature at greater depth (25 cm and possibly deeper) during the hottest periods (negatively). Determining whether this pattern is merely coincidental or indicative of a broader phenomenon among subterranean rodents in seasonal environments would require comparable data from other species. Unfortunately, studies examining activity across contrasting seasons while measuring soil temperatures at various depths are rare. A brief review of such studies follows.\u003c/p\u003e \u003cp\u003eRado et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) found that the activity of radio-tracked Middle East blind mole rats \u003cem\u003eNannospalax ehrenbergii\u003c/em\u003e peaked between the time of maximum soil surface temperature and the time of maximum temperature at a depth of 20 cm in winter, while in summer, activity peaked at the time of the lowest temperature at 20 cm. This pattern closely aligns with our findings. A relevant comparison can also be made with Okrouhl\u0026iacute;k et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), who monitored year-round body temperature variations in two South African solitary mole-rat species using implanted temperature loggers. An increase in body temperature is widely considered a reliable proxy for physical activity (Benstaali et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). In July, the coldest month of the year, both Cape mole-rat \u003cem\u003eGeorychus capensis\u003c/em\u003e and Cape dune mole-rat \u003cem\u003eBathyergus suilus\u003c/em\u003e exhibited peak body temperatures around 17:00, coinciding with the temperature maximum at a depth of 10 cm. In contrast, during January, the hottest period of the year, peak body temperature in both species shifted to 12:00\u0026ndash;14:00, corresponding to the temperature minimum at a depth of 30 cm. These findings are again consistent with our results for \u003cem\u003eH. argenteocinereus\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eFinn et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) explored seasonal changes in the daily activity patterns of the social Natal mole-rat \u003cem\u003eCryptomys hottentotus natalensis\u003c/em\u003e using passive transponder implants and RFID readers placed over a frequently used burrow. While this method proved viable for this purpose, pooling data over 3 months and the limited soil temperature monitoring hindered detailed comparisons with our results. During the cold winter, the activity of \u003cem\u003eC. h. natalensis\u003c/em\u003e closely correlated with temperatures in shallow soil layers, mirroring our results for \u003cem\u003eH. argenteocinereus\u003c/em\u003e. In contrast, during the hot summer, their activity exhibited a bimodal pattern, decreasing during the hottest part of the day. Similar daily patterns of body-core temperature \u0026mdash;unimodal T\u003csub\u003eb\u003c/sub\u003e in winter but bimodal T\u003csub\u003eb\u003c/sub\u003e in summer \u0026mdash; were found in the same species using implanted temperature loggers (Oosthuizen et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The bimodal activity pattern, which avoids daily temperature extremes has also been described in the plains pocket gopher \u003cem\u003eGeomys bursarius\u003c/em\u003e (Benedix \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) and in some individuals of \u003cem\u003eH. argenteocinereus\u003c/em\u003e (Škl\u0026iacute;ba et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on the literature reviewed above, we can conclude that seasonal variation in daily activity patterns in response to daily temperature fluctuations at different soil depths, as described for the silvery mole-rat (i.e. activity correlating positively with near-surface soil temperatures during cold periods and negatively with temperatures at greater depths during hot periods), appears to be consistent across various subterranean rodent species. It is therefore reasonable to seek a biologically meaningful explanation for this phenomenon.\u003c/p\u003e \u003cp\u003eOur data show that daily temperature variation at a depth of around 15 cm is already substantially buffered, with an amplitude ranging between 1.0 to 2.7\u0026deg;C, depending on the period of the year (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). If mole-rats spend even brief periods at shallower depths\u0026mdash;such as when pushing soil to form aboveground mounds, digging near the soil surface, or collecting food or nest bedding\u0026mdash;the greater temperature variation at these depths would result in significantly higher daily variation in thermoregulatory costs compared to the more stable thermal conditions at depths of 15\u0026ndash;20 cm. As a result, the activity of mole-rats could be more strongly corelated with the temperature at shallower layers of soil rather than where the majority of tunnels are situated. This is exactly what we observed during the coldest period of the year (Period 2), when the activity of silvery mole-rats was most closely associated with the temperature at 5\u0026ndash;10 cm below the soil surface. Similarly, activity patterns of \u003cem\u003eN. ehrenbergii\u003c/em\u003e and \u003cem\u003eN. galili\u003c/em\u003e during cold Mediterranean winters were closely related to the temperatures measured between the typical burrow depth and the soil surface (Rado et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Škl\u0026iacute;ba et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn contrast, our data from the hottest periods show no negative correlation between mole-rat activity and the temperature near the soil surface. Instead, activity was most strongly correlated with the temperature at a depth of 25 cm (negatively) and with surface temperature (positively). Surface temperature is unlikely to have a direct effect on mole-rat activity during the peak dry season, as they are not active on the surface. During advanced dry seasons, subterranean and fossorial rodents even cease pushing soil into aboveground mounds (which is sometimes misinterpreted as an indication of decreased overall activity) and instead backfill existing burrows (Miller \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1948\u003c/span\u003e; Jarvis \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1973\u003c/span\u003e; Lovegrove and Painting 1978; Jarvis et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Šumbera et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2003\u003c/span\u003e, Herbst and Bennett \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Škl\u0026iacute;ba et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). On the contrary, some effect of the daily temperature cycle at a depth of 25 cm (and possibly deeper) on the timing of activity in the silvery mole-rats is theoretically possible if they would preferentially excavate and/or use deeper parts of burrow systems rather than extending and backfilling foraging tunnels at the usual depth of 15\u0026ndash;20 cm in the peak hot dry season. Nevertheless, this scenario seems unlikely given the minimal daily temperature variation at the depth of 25 cm and deeper. Unfortunately, we could not determine the depth at which radio-collared mole-rats were active, as radio-tracking did not allow for depth estimation, and burrow depths was not surveyed during the corresponding radio-tracking periods.\u003c/p\u003e \u003cp\u003eTheoretically, mole-rats might be forced to burrow deeper due to the increasing hardness of shallower soil layers and the challenges associated with transporting loose, dry soil and depositing it into mounds. The energetic cost of burrowing in dry, hard soils is significantly higher than in damp soils, as demonstrated in fossorial tuco-tuco (Luna and Antinuchi \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Additionally, mole-rats might prefer to use deeper sections of their burrow systems to facilitate heat dissipation during the hottest periods, as their body heat is effectively transferred by conduction through their feet and ventral thermal window, particularly when in contact with moist soil (Šumbera et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2007\u003c/span\u003e, McGowan et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Okrouhl\u0026iacute;k et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, Vejmělka et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Notably, temperature typically decreases with depth during the hottest part of the year and increases during the coldest one, as the annual temperature cycle is phase-shifted with depth, similar to the daily temperature cycle (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). During the hottest periods, the daily temperature amplitude at 25 cm was around 1\u0026deg;C, with a mean temperature around 1.7\u0026deg;C lower than at the surface (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). However, evidence for seasonal variation in burrowing depth among subterranean rodents is limited. Foraging burrows were found to be 7.6\u0026ndash;15.2 cm deeper during warm seasons compared to cold seasons in \u003cem\u003eGeomys pinetis\u003c/em\u003e (Brown and Hickman \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1973\u003c/span\u003e) and 2.5 cm deeper cm in \u003cem\u003eGeomys attwateri\u003c/em\u003e (Williams and Cameron \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). In contrast, no seasonal change in burrow depth was found in \u003cem\u003eH. argenteocinereus\u003c/em\u003e by Šumbera et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, unpublished data).\u003c/p\u003e \u003cp\u003eAnother plausible explanation for the observed activity patterns during the hottest periods relates to the fact that around midday, mean temperatures across depths of approximately 15\u0026ndash;25 cm were nearly uniform (Fig.\u0026nbsp;3). During these periods, such temperatures were at or just below the lower critical temperature of the silvery mole-rat\u0026rsquo;s thermoneutral zone (25\u0026ndash;33\u0026deg;C; Zelov\u0026aacute; et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). These conditions may be suitable for activity, or at least for moderate levels of physical exertion, such as walking and patrolling the burrow system. It remains possible that activities producing substantial metabolic heat, which require heat dissipation to avoid overheating (Okrouhl\u0026iacute;k et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, Vejmělka et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), occur at different times of the day or in short bouts throughout the whole 24-h day. Unfortunately, our method of studying mole-rat activity does not differentiate between varying levels of physical activity. Implementing new biologging tools could provide better insights into the temporal distribution of different levels of physical activity and its relation with daily temperature fluctuations at various depths. A pioneering study in this area of research is Finn et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), which monitored the activity of free-ranging highveld mole-rats \u003cem\u003eCryptomys hottentotus pretoriae\u003c/em\u003e fitted with accelerometers. Although this study did not differentiate between activity levels, its findings remain highly relevant to the present study, as the daily activity pattern detected differs markedly from what we describe for \u003cem\u003eH. argenteocinereus.\u003c/em\u003e Even during the hot late summer (February to March), highveld mole-rats exhibited a clear daily activity peak coinciding with the highest soil temperature at a depth of 10 cm \u0026ndash; a depth that roughly represents a typical burrow depth. The authors proposed that the ideal temperature for activity, including digging, in \u003cem\u003eC. h. pretoriae\u003c/em\u003e can be as high as 30\u0026deg;C and attributed this to its unusual physiological traits such as unusual physiological traits, such as high body temperature, narrow TNZ, low metabolic rate, and high thermal conductance. Interestingly, 30\u0026deg;C also corresponds to the lower critical temperature of its TNZ (Haim and Fairall \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1986\u003c/span\u003e). In contrast, the silvery mole-rat which has well-insulating fur that does not allow for very effective heat dissipation during intensive physical activity like digging (Šumbera et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), is more susceptible to overheating. Consequently, its behavioural thermoregulation during the hottest periods of the year likely involves avoiding high temperatures rather than preferring them, as seen in \u003cem\u003eC. h. pretoriae\u003c/em\u003e (Finn et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur last prediction stated that activity patterns would become more distinct during periods with greater daily temperature variation (i.e. amplitude) at the typical burrow depths. However, it was not supported by our data. While activity pattern distinctness was closely correlated with daily temperature amplitude at the soil surface and at depths up to 10 cm, the correlation was no longer significant at 15 and 20 cm (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This result should be interpreted with caution, as the six radio-tracking periods were unevenly distributed during the year. Nevertheless, it suggests that the temperature variation closer to the surface, and not necessarily at the usual burrow depth, might induce the need for greater regularity in activity timing. Data from Okrouhl\u0026iacute;k et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) further allow comparisons of the \u0026ldquo;distinctness\u0026rdquo; of daily body temperature patterns in two solitary bathyergids, \u003cem\u003eGeorychus capensis\u003c/em\u003e and \u003cem\u003eBathyergus suilus\u003c/em\u003e, throughout the whole year. In both species the patterns were most distinct during the hottest months (January and February), flattened in May, reemerged as distinct in the coldest month (July), and flattened again in October.\u003c/p\u003e \u003cp\u003eThe daily activity patterns of the silvery mole-rat can be compared to those of other subterranean and fossorial rodents using comparable methodological approaches to identify factors determining the distinctness of the patterns (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Species with distinct activity patterns include \u003cem\u003eFukomys anselli\u003c/em\u003e, \u003cem\u003eNannospalax ehrenbergii\u003c/em\u003e and \u003cem\u003eTachyoryctes macrocephalus\u003c/em\u003e. Of these, \u003cem\u003eT. macrocephalus\u003c/em\u003e inhabits the Afroalpine ecosystem, characterised by a large daily temperature amplitude (up to 24\u0026deg;C at the surface, Vlasat\u0026aacute; et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Unlike strictly subterranean species, it feeds on the ground surface, likely increasing its daily thermoregulatory costs of its activity. On the contrary, \u003cem\u003eF. anselli\u003c/em\u003e is a small-bodied social species with a relatively high thermal conductance (Marhold and Nagel \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1995\u003c/span\u003e) and relatively shallow burrow systems (Škl\u0026iacute;ba et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), factors that likely contribute to its high distinctness of its activity pattern. Very distinct patterns were also detected in \u003cem\u003eN. ehrenbergii\u003c/em\u003e from Israel\u0026rsquo;s coastal plain (Rado et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) but not in \u003cem\u003eN. galili\u003c/em\u003e from the more mesic Israeli highlands (though the latter species was not studied in summer) (Škl\u0026iacute;ba et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The least distinct daily activity pattern was found in \u003cem\u003eF. mechowii\u003c/em\u003e, a large-bodied social mole-rat. However, this finding applied to individuals living in a family, whereas a solitary-living female of the same species exhibited a distinct daily activity pattern strongly correlated with temperature, resembling that of \u003cem\u003eH. argenteocinereus\u003c/em\u003e (L\u0026ouml;vy et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistinctness of activity patterns in radio-tracked subterranean rodents (defined as the difference between minimum and maximum hourly activity values).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeason or period of the year\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean daily surface temperature range\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRange of hourly % outside-nest fixes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eActivity pattern distinctness\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eT. macrocephalus\u003c/em\u003e\u003csup\u003ea)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEarly dry season\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.0\u0026ndash;17.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026ndash;73.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eT. macrocephalus\u003c/em\u003e\u003csup\u003ea)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLate dry season\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6\u0026ndash;24.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026ndash;67.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eN. ehrenbergii\u003c/em\u003e \u003csup\u003eb)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWinter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u0026ndash;76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eN. ehrenbergii\u003c/em\u003e \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSummer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u0026ndash;31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u0026ndash;92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eN. galili\u003c/em\u003e on basalt\u003csup\u003ec)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWinter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.1\u0026ndash;7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026ndash;57.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eN. galili\u003c/em\u003e on chalk \u003csup\u003ec)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWinter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.3\u0026ndash;11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4\u0026ndash;45.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF. anselli\u003c/em\u003e (nonbreeders)\u003csup\u003ed)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCold dry season\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.3\u0026ndash;28.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.8\u0026ndash;93.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF. mechowii\u003c/em\u003e (nonbreeders) \u003csup\u003ee)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCold dry season\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.1\u0026ndash;28.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.1\u0026ndash;43.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eH. argenteocinereus\u003c/em\u003e\u003csup\u003ef)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe coldest period of the year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.0\u0026ndash;19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u0026ndash;58.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eH. argenteocinereus\u003c/em\u003e\u003csup\u003ef)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe hottest periods of the year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.5\u0026ndash;39.0\u003c/p\u003e \u003cp\u003e20.7\u0026ndash;38.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.7\u0026ndash;83.3\u003c/p\u003e \u003cp\u003e14.3\u0026ndash;76.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003ea) Vlasat\u0026aacute; et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, b) Rado et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1993\u003c/span\u003e, c) Škl\u0026iacute;ba et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, d) Škl\u0026iacute;ba et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, e)vy et al. 2013, f) the present study\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo conclude, the silvery mole-rat, like most other subterranean rodents, adjust its activity timing in response to daily temperature fluctuations. However, temperature fluctuation at typical foraging burrow depths does not appear to be the primary factor influencing activity timing. Instead, temperature cycles closer to the soil surface seem to play a more important role, particularly during the coldest periods of the year. In contrast, interpreting the biological significance of activity patterns observed during the hottest periods is more challenging, although these patterns were notably distinct. We propose that during the hottest periods, mole-rats may preferentially construct or just move within deeper sections of their burrow systems or time their activity to coincide with a part of the day when soil temperatures across a range of depths (e.g. 15\u0026ndash;25 cm) converge\u0026mdash;provided these temperatures still remain below the lower critical temperature of their TNZ. To further verify and elaborate our conclusions, further research should focus on subterranean rodents inhabiting a broad range of ambient temperatures. Ideal candidates include common mole-rats of the genus \u003cem\u003eCryptomys\u003c/em\u003e from Southern Africa, which occupy habitats ranging from hot coastal plains to the cold Drakensberg Mountains. Additionally, studies employing accelerometers to classify various activity types \u0026mdash;such as digging, walking, and soil transport \u0026mdash;under different climatic conditions throughout the year could provide valuable insights into their behavioural and thermoregulatory adaptations. Importantly, these studies should include precise temperature measurements at multiple soil depths and, if possible, accurate measurements of burrow depth.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the Genetic Resources and Biotechnology Committee and the Technical Committee of the National Research Council of Malawi for a permission to conduct our research in Malawi. We are deeply grateful to Tamsin and Stephen Christie, owners of the Mpalanganga Estate, for their hospitality and generous support. We thank Jitka Mal\u0026aacute; (n\u0026eacute;e Zelov\u0026aacute;), Stephan Koeppen, Aphiri, Charles, and Moren for their invaluable assistance in the field. The study was funded by GAAV (KJB601410826 and IAA601410802).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the organization and execution of the field research, as well as writing of the manuscript. JS conceived the study and prepared the first draft. ML conducted the final statistical analyses. ML and RS provided critical input into the interpretation of results. WNC facilitated the acquisition of fieldwork permits and managed field logistics.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatement of animal ethics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures involving wild-caught animals were performed in a humane manner. These procedures were approved by the National Research Council of Malawi (NRCM), the Research and Publications Committee of the University of Malawi, Chancellor College, and the Control Commission for Ethical Treatment of Animals of the University of South Bohemia, Faculty of Biological Sciences, Czech Republic.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConflict of interest statement\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOn behalf of all authors, the corresponding author states that there is no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBartness TJ, Albers HE (2000) Activity patterns and the biological clock in mammals. In: Halle S, Stenseth NC (eds) Activity patterns in small mammals: an ecological approach. Springer, Berlin, pp 23\u0026ndash;47\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenedix JH (1994) A predictable pattern of daily activity by the pocket gopher \u003cem\u003eGeomys bursarius\u003c/em\u003e. Anim Behav 48:501\u0026ndash;509. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1006/anbe.1994.1271\u003c/span\u003e\u003cspan address=\"10.1006/anbe.1994.1271\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenstaali C, Mailloux A, Bogdan A, Auzeby A, Touitou Y (2001) Circadian rhythms of body temperature and motor activity in rodents: their relationships with the light-dark cycle. 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Comp Biochem Physiol A 147:412\u0026ndash;419. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cbpa.2007.01.002\u003c/span\u003e\u003cspan address=\"10.1016/j.cbpa.2007.01.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"mammalian-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mamb","sideBox":"Learn more about [Mammalian Biology](https://link.springer.com/journal/42991)","snPcode":"42991","submissionUrl":"https://www.editorialmanager.com/mamb/default2.aspx","title":"Mammalian Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"subterranean rodent, daily activity pattern, radio-tracking, behavioural thermoregulation","lastPublishedDoi":"10.21203/rs.3.rs-6120103/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6120103/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDaily activity patterns of free-living subterranean rodents have often been associated with temperature fluctuations in shallow soil layers, but their seasonal variation has been poorly studied. We analysed activity data from free-living silvery mole-rats \u003cem\u003eHeliophobius argenteocinereus\u003c/em\u003e radio-tracked over six periods, including the coldest and hottest periods of the year, to investigate whether their activity is concentrated into parts of the day when thermoregulation costs are supposed to be lowest. During the coldest period, mole-rat activity correlated most strongly with the temperature at depths of 5\u0026ndash;10 cm (positively), corresponding to the superficially situated burrow branches leading to mounds or food resources located in the shallow soil layers. In contrast, during two hottest periods, activity was more closely related to temperatures at a depth of 25 cm (negatively). While the activity pattern detected during the coldest period aligns with the expected greater daily variation in thermoregulatory costs associated with burrowing closer to the soil surface, the patterns from the hottest periods are more difficult to interpret. We hypothesise that during the hottest periods of the year, mole-rats either (i) preferentially construct and use deeper burrow sections, adjusting their daily activity patterns to small temperature fluctuations found there, or (ii) concentrate their activity to a part of the day when temperatures across a range of soil depths converge, provided they remain below their thermal neutral zone (TNZ).\u003c/p\u003e","manuscriptTitle":"Seasonal variation of the daily activity patterns in a subterranean rodent in response to underground temperature fluctuations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-28 15:07:01","doi":"10.21203/rs.3.rs-6120103/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-03-20T13:04:42+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-20T08:47:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-02-28T11:04:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Mammalian Biology","date":"2025-02-27T05:36:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"mammalian-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mamb","sideBox":"Learn more about [Mammalian Biology](https://link.springer.com/journal/42991)","snPcode":"42991","submissionUrl":"https://www.editorialmanager.com/mamb/default2.aspx","title":"Mammalian Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7bea1261-b8ae-4a3d-8cf9-6a9796b96874","owner":[],"postedDate":"March 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-15T16:04:23+00:00","versionOfRecord":{"articleIdentity":"rs-6120103","link":"https://doi.org/10.1007/s42991-025-00513-y","journal":{"identity":"mammalian-biology","isVorOnly":false,"title":"Mammalian Biology"},"publishedOn":"2025-09-10 15:57:02","publishedOnDateReadable":"September 10th, 2025"},"versionCreatedAt":"2025-03-28 15:07:01","video":"","vorDoi":"10.1007/s42991-025-00513-y","vorDoiUrl":"https://doi.org/10.1007/s42991-025-00513-y","workflowStages":[]},"version":"v1","identity":"rs-6120103","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6120103","identity":"rs-6120103","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}