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Seasonal Patterns of Body Temperature Daily Rhythms in Group-Living Cape Ground Squirrels Xerus inauris

  • Michael Scantlebury ,

    m.scantlebury@qub.ac.uk

    Affiliations Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Pretoria, South Africa, School of Biological Sciences, Queen's University Belfast, Belfast, Northern Ireland, United Kingdom

  • Marine Danek-Gontard,

    Affiliation School of Biological Sciences, Queen's University Belfast, Belfast, Northern Ireland, United Kingdom

  • Philip W. Bateman,

    Affiliation Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Pretoria, South Africa

  • Nigel C. Bennett,

    Affiliation Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Pretoria, South Africa

  • Mary-Beth Manjerovic,

    Affiliation Department of Biology, University of Central Florida, Orlando, Florida, United States of America

  • Kenneth E. Joubert,

    Affiliation Section Pharmacology, Department of Paraclinical Sciences, Faculty of Veterinary Science, University of Pretoria, Pretoria, South Africa

  • Jane M. Waterman

    Affiliations Department of Biology, University of Central Florida, Orlando, Florida, United States of America, Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada

Seasonal Patterns of Body Temperature Daily Rhythms in Group-Living Cape Ground Squirrels Xerus inauris

  • Michael Scantlebury, 
  • Marine Danek-Gontard, 
  • Philip W. Bateman, 
  • Nigel C. Bennett, 
  • Mary-Beth Manjerovic, 
  • Kenneth E. Joubert, 
  • Jane M. Waterman
PLOS
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Correction

8 Aug 2012: Scantlebury M, Danek-Gontard M, Bateman PW, Bennett NC, Manjerovic MB, et al. (2012) Correction: Seasonal Patterns of Body Temperature Daily Rhythms in Group-Living Cape Ground Squirrels Xerus inauris. PLOS ONE 7(8): 10.1371/annotation/65754bea-b508-431f-acf8-6c2a26602f28. https://doi.org/10.1371/annotation/65754bea-b508-431f-acf8-6c2a26602f28 View correction

Abstract

Organisms respond to cyclical environmental conditions by entraining their endogenous biological rhythms. Such physiological responses are expected to be substantial for species inhabiting arid environments which incur large variations in daily and seasonal ambient temperature (Ta). We measured core body temperature (Tb) daily rhythms of Cape ground squirrels Xerus inauris inhabiting an area of Kalahari grassland for six months from the Austral winter through to the summer. Squirrels inhabited two different areas: an exposed flood plain and a nearby wooded, shady area, and occurred in different social group sizes, defined by the number of individuals that shared a sleeping burrow. Of a suite of environmental variables measured, maximal daily Ta provided the greatest explanatory power for mean Tb whereas sunrise had greatest power for Tb acrophase. There were significant changes in mean Tb and Tb acrophase over time with mean Tb increasing and Tb acrophase becoming earlier as the season progressed. Squirrels also emerged from their burrows earlier and returned to them later over the measurement period. Greater increases in Tb, sometimes in excess of 5°C, were noted during the first hour post emergence, after which Tb remained relatively constant. This is consistent with observations that squirrels entered their burrows during the day to ‘offload’ heat. In addition, greater Tb amplitude values were noted in individuals inhabiting the flood plain compared with the woodland suggesting that squirrels dealt with increased environmental variability by attempting to reduce their Ta-Tb gradient. Finally, there were significant effects of age and group size on Tb with a lower and less variable Tb in younger individuals and those from larger group sizes. These data indicate that Cape ground squirrels have a labile Tb which is sensitive to a number of abiotic and biotic factors and which enables them to be active in a harsh and variable environment.

Introduction

Organisms respond to cyclical variation in environmental conditions by entraining their endogenous biological rhythms [1], [2]. One such rhythm in endothermic species is that of body temperature (Tb), which is considered to be a consequence of the balance between heat production and heat dissipation [3]. In many taxa, Tb daily rhythms are influenced by diel and seasonal changes in photoperiod and ambient temperature (Ta) [4][9]. Indeed, the primary cues for seasonal acclimatization of the thermoregulatory system, which include changes in Tb daily rhythms, are photoperiod and temperature [10], [11]. Interestingly, little is known about which selective pressures may affect the evolution of heterothermy in endotherms. Indeed, it is unclear whether one should examine the effects of environmental variation on raw Tb data or use some index which can be comparable across species (e.g. ‘Heterothermy Index’, ‘HI’ [12]). Angilletta et al. (2010) [13] suggest that future empirical work should examine the potential “selective pressures imposed by regional and temporal heterothermy”. They identify several potential candidates which might cause Tb variations to evolve which include food and water availability, Ta and social huddling. For example, restricted food and water supplies and low Ta values should favor energy-saving reductions in Tb and temporal heterothermy. Implicit in their arguments is the fact that extremes of variation in Ta and in particular cyclical variations in Ta may result in adaptive variation in Tb daily rhythms [13][16]. For group-living animals, behaviors such as social huddling may be one mechanism to conserve water and energy [17], [18]. Minimization of thermoregulatory costs and water loss are thus seen as a possible selective pressure for aggregation [19][21]. For instance, huddling in newborn rabbit (Oryctolagus cuniculus) pups not only saves energy but also affects Tb daily rhythms [22]. Hence, Tb daily rhythms are likely to be affected by group size in social animals.

The open thorn scrub savannah ecosystem of southern Africa is subject to wide diel and annual variations in temperature across seasons, often reaching above 40°C during the summer and below freezing during the winter [23]. In this habitat, large open areas are interspersed with occasional stands of trees and bushes that generally concentrate in depressions around pans and dry river beds [24]. These areas are likely to present different microclimatic conditions due in part to differences in exposure to solar radiation [25]. Small mammals that inhabit this region, such as the Cape ground squirrel (Xerus inauris), exhibit typical arid adaptations including a low resting metabolic rate, a high thermal conductance and a concentrated urine [26], [27]. They are active year-round and forage during the heat of the day. It has been suggested that they use both behavioral and physiological means to deal with the extremes of Ta they encounter [28][30]. For example, they may be active during hot summer days because they periodically dissipate body heat by retreating to cooler burrows [31]. Therefore, it is likely that their Tb will vary considerably, both on a daily and a yearly basis, as a physiological adaptation to reduce the Ta-Tb gradient [5], [32], [33]. However, it is unknown how this is related to microhabitat and behavior, such as the time animals emerge in the morning and how they may interact socially with one another.

Here we investigated the role of Tb daily rhythms as a response to seasonal and diel changes in Ta in Cape ground squirrels that inhabit a habitat mosaic exposed to large daily and annual temperature fluctuations. Our hypotheses were related to the middle (mesor); the amplitude and the acrophase (time of the peak) of Tb daily rhythms [34]. We predicted that: (a) seasonal differences in Tb daily rhythms would be apparent with higher mesor values and later acrophase times during the spring and summer; (b) rapid changes in Tb would be apparent in the early mornings (after emergence) and a Tb would be maintained at a constant level throughout the daylight hours because animals will move into and out of cooler locations such as their burrows as part of their thermoregulatory behavior; (c) lower mesor and amplitude values of Tb would be observed in a shaded compared with an open habitat; and (d) winter mesor values would be higher in animals from larger group sizes because of the thermoregulatory benefits gained from huddling at night. In addition, we examined the potential seasonal variation in HI values from individuals inhabiting different locations and from different group sizes to gauge whether or not relationships that emerge when analyzing Tb data are also manifest when using this index.

Materials and Methods

Ethics statement

Permission was granted from South Africa Northwest Parks and Tourism to conduct the field research. The protocol was approved by committee on the ethics of animal experiments of the Universities of Central Florida and Pretoria (permit number UCF IACUC #07-43W). The study was performed in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health.

Animals and study site

Cape ground squirrels are small (∼600 g), non-hibernating, diurnal, social rodents that inhabit arid regions of sub-Saharan Africa [35][37]. They are cooperative breeders with low reproductive skew and a high operational sex ratio. Groups typically consist of 1–6 related females and their sub adult and juvenile offspring, which share a burrow cluster [35], [38]. The study took place at S. A. Lombard Nature Reserve (3,660 ha, 18 km north west of Bloemhof, South Africa, 27°35′S, 25°23′E) as part of an on-going study where squirrels have been studied since 2002. The site comprises Cymbopogon-Themeda veld and Kalahari grasslands, and is situated on a flood plain [24]. Mean annual precipitation is 500 mm [39]. Animals were trapped from groups at two locations: an open unshaded area – “the flood plain” – and a habitat containing Acacia karoo and A. erioloba stands – “the woodland”, which was approximately 2 km away [40]. Tomahawk wire-mesh traps (15×15×50 cm) baited with peanut butter were used to catch animals, after which they were freeze-marked for unique identification (Quick Freeze, Miller-Stephenson Chemical Co., Danbury, CT [41]) and implanted with transponders (PIT tags, AVID Inc., Norco, CA). The sides of animals were also painted with various shapes using black hair dye (Rodol D, Lowenstein & Sons Inc., New York, NY) so their identities could be seen at a distance. Body mass was recorded along with the size of the social groups to which animals belonged. Trapping took place for two one-week periods during May and October. Age was assessed by knowing dates of first emergence from the natal burrow [35], [42]. Behavioral observations, including times of emergence and immergence from burrows were obtained as outlined in Waterman [37]. Briefly, this involved recording time budgets of individual animals by focal sampling in which all-occurrence data were recorded for periods of up to 20 minutes whereas the activities of all the individuals within a group were recorded every five minutes by scan sampling [43]. We were interested in many different aspects, but in particular movement and foraging activities as well as aggressive, reproductive and social/dominance interactions between individuals.

Acquisition of body temperature (Tb) data

Ten squirrels (five sub adults and five adults) were obtained from the flood plain and 10 (also five adults and five sub adults) from the woodland. Sub adults are defined as animals between six months after first emergence from the natal burrow and sexual maturity (around eight months for males and nine months for females); adults are individuals which have reached sexual maturity [38]. Miniature temperature recording iButton® dataloggers (DS1922L±0.0625°C; Thermochron, Dallas Semiconductors, Maxim Integrated Products, Inc., Sunnyvale, CA) were surgically implanted into the peritoneal cavity of each individual under anaesthesia (see below). Prior to surgery, devices were calibrated using an APPA 51 digital thermometer in a water bath. They were set to record every 60 min providing 23 weeks of continuous recordings. Dataloggers were then coated with medical grade surgical wax (ELVAX) [44] and sterilized with formaldehyde vapor. Measurements of Tb were recorded between May 17th and October 28th 2006.

Squirrels were anaesthetized with medetomidine (Domitor, Pfizer Laboratories (PTY) Ltd, Sandton) (67.6±9.2 µg/kg), ketamine (Anaket V, Centaur Laboratories (PTY) Ltd, Isando) (13.6±1.9 mg/kg) and buprenorphine (Temgesic, Ricketts Laboratories, Isando) (0.5±0.06 µg/kg) [45]. Anesthesia was induced after 3.1±1.4 minutes. The abdomen was surgically prepared with a chlorhexidine scrub (Hibiscrub, ICL Laboratories), then with chlorhexidine and alcohol (Hibitane, ICI Laboratories). A midline celiotomy was performed for insertion of the dataloggers. The linea alba was closed with 4/0 polydioxanone (PDS, Ethicon, Midrand) and the skin was closed with an intercuticular suture pattern with 4/0 polydioxanone. The procedure for each individual lasted approximately 20 minutes. At the end of the surgical procedure, anesthesia was reversed with atipamezole (Antisedan, Pfizer Laboratories) (232±92 µg/kg). Recovery occurred within 3.5±2.2 minutes. This procedure was followed for removal of dataloggers for the case of five animals that were recaptured. Three other recaptured animals were euthanized with an overdose of halothane upon recapture as part of a different study [46]. Only eight of the total 20 animals implanted were recaptured. After removal of dataloggers, Tb data were downloaded using iButton®-TMEX software version 3.21 (2004 Dallas Semiconductor MAXIM Corporation). All animals were observed overnight after implantation and removal of dataloggers and returned to their capture site the following morning. No animal died due to surgical procedures during this period.

Ambient temperature and daylight measurements

Ambient air temperature (Ta) was determined using two methods. We set dataloggers to record every hour for the first 84 days (12 weeks) of the sampling period. One datalogger was used per study site. Dataloggers were placed inside Stevenson screens located 90 cm above the ground. To obtain data over a longer time period, we used daily minimum, maximum and mean ambient temperatures recorded at Bloemhof 27.65 S, 25.60 E, GMT +2 (South African Weather Bureau, Pretoria) for the entire 23 weeks of the sampling period; mean hours of sunlight as well as the times of sunrise (civil dawn) and sunset (civil dusk) were also noted. In an attempt to measure underground temperatures, we also placed two dataloggers inside what we thought were disused squirrel burrows. However, these devices did not provide useful information because the burrows were not vacant; squirrels removed them from the burrows and they were found in spoil heaps on the surface.

Data analyses

Cosinor analysis was used to determine the Tb daily rhythms of the individuals measured [34], [47]. The mean mesor, amplitude and acrophase values of the Tb daily rhythms were calculated for every individual for each of the 23 weeks of the study period (‘Tbmesor’, ‘Tbamplitude’ and ‘Tbacrophase’, respectively). The significances of the fitted curves were tested against the null hypothesis that the amplitude was zero [48]. The variability in the data that could be accounted for by the fitted curve (percentage rhythm) was calculated. In addition, we calculated the HI values for each animal for each week of the study and assessed whether there were any relationships between HI and season, age or group size. Statistical analyses were performed using SPSS 17 (SPSS Inc., Chicago, IL, U.S.A.). Mean values are reported ± standard deviations.

(1) Seasonal variation in Tb daily rhythms.

Linear mixed models were used to examine the variation in Tb cosinor parameters (mesor, amplitude, acrophase) as a function of time (over the 23 week period). Each dependent variable was analyzed separately. ‘Individual ID’ was included as a random factor to avoid pseudoreplication and to correct for repeated measurements. ‘Week’ was included as fixed covariate. As several explanatory terms and their interactions were investigated, models were selected in a stepwise backward fashion, removing the least significant explanatory terms until the most parsimonious model was obtained, determined by Akaike's information criterion (AIC). Interaction terms were only included when they were significant.

(2) Effect of light and ambient temperature (Ta) on body temperature (Tb) daily rhythms.

Linear Mixed Models were used to examine the effects of light and Ta on the mean weekly cosinor parameters. First, we obtained several measures of Ta: the daily minimum (Tamin), the daily maximum (Tamax) and the daily mean value (Tamean) (South African Weather Bureau). We then calculated weekly averages of Tamin, Tamax and Tamean and included each of these in a model with individual identity as a random factor and week as a fixed effect. This corrected for repeated measurements and differences in mean values between individuals. All potential interactions between temperature variables were included. Models were selected by removing the least significant explanatory terms sequentially until the most parsimonious model was obtained using AIC. Each dependent cosinor variable was analyzed separately. Second, we assessed the effects of various ‘light’ variables on the cosinor variable. The light variables we used were: the weekly average time of sunrise, the weekly average time of sunset and the weekly average length of the photophase. As before, models were selected using AIC by removing least significant explanatory terms sequentially. Finally, for each of the dependent cosinor variables, combined models were undertaken which included the factors with most explanatory power from both the individual Ta models and the individual light models. Again, for each analysis the best model was obtained using AIC.

(3) Relationship between emergence and immergence times and Tb daily rhythms.

Emergence and immergence times for the two habitats were calculated as the mean observed emergence and immergence time of groups of squirrels inhabiting both areas [35]. Data were collected over seven months of detailed observation time recording when individual squirrel groups from the two habitats emerged or immerged. An average of 8.1±0.65 squirrels from different groups were observed every week to calculate emergence times and 5.7±0.81 squirrels from different groups were observed every week to calculate immergence times. Temporal variation in mean emergence and immergence times was investigated using linear regressions. In order to determine how daily variations in Tb were related to the times of emergence and whether this differed throughout the year, we computed, for each day, the mean Tb of each individual one hour before the time of emergence and the mean Tb one hour after the time of emergence. The difference in Tb between these two values was then calculated as a percent of the maximum amplitude difference in Tb for that individual for that day. The mean percent Tb change for each individual was then calculated for each week, after which the mean change for all individuals was calculated for the 23 weeks.

(4) Effect of habitat on Ta and Tb daily rhythms.

To examine whether mean daily Ta differed between the flood plain and the woodland we conducted linear mixed models with habitat as a fixed factor, week as time and Ta measured at both study sites as the dependent variable. To determine whether high values of Ta obtained during the day or low values obtained during the night differed between the two habitats we included day/night as an additional fixed factor. The hourly Ta obtained at both study sites were considered as being ‘daytime’ Ta if the measurement was taken between the sunrise and sunset of a given day, and ‘night-time’ Ta if the measure was taken between sunset and sunrise time between two consecutive days. An average Ta was then determined for each daytime and each night-time period for the 84 days (12 weeks) of the sampling period. To examine the effect of habitat on mean weekly Tb values and cosinor parameters, we included ‘habitat’ and ‘day/night’ as a fixed factors, ‘individual’ as random variable and ‘week’ as factor.

(5) Effect of age and group size on Tb daily rhythms.

Effects of age and group size on Tbmean, Tbmesor, Tbamplitude, Tbacrophase and HI were conducted using linear mixed models with ‘individual’ as a random variable and ‘week’ as factor. Models were selected in a stepwise manner using AIC as described previously. Age (adult/sub adult) was included as a categorical factor and group size as a continuous variable.

Results

Of the 20 individuals originally implanted with dataloggers, eight were recaptured; six from the flood plain (two adults, four sub adults) and two from the woodland (two adults). Group sizes (i.e. the sizes of groups in which the eight animals lived) ranged from one to nine individuals. The implanted animals were regularly observed during the two weeks following implantation and no mortality or immigration was observed. We observed no signs of different behavior of the implanted squirrels compared to the others. There were significant daily rhythms of Tb in all of the eight individuals measured (Table 1, Fig. 1) with mean ±SD values of the mesor, amplitude and acrophase for the 23 week measurement period of 37.51±0.15°C, 1.13±0.08°C and 12∶33±2 min, respectively.

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Figure 1. Body temperature (Tb) daily rhythm of an adult Cape ground squirrel (605 g) for the first (21 to 28 May), eighth (09 to 16 July), fifteenth (27 August to 03 September) and twenty-second week (15 to 22 October) of a 23-week measurement period.

‘M’ indicates the mesor (37.41°C), ‘A’ the amplitude (0.92°C) and ‘Ø’ the acrophase (189.11° or 12∶36 h) of the fitted cosine curve. SR and SS show times of sunrise and sunset.

https://doi.org/10.1371/journal.pone.0036053.g001

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Table 1. Mean (±SE) of the mesor (°C), amplitude (°C), acrophase (time hh:mm) and percentage rythmicity obtained from 24 h cosine functions of hourly Tb recordings of eight Cape ground squirrels during a 23-week sampling period.

https://doi.org/10.1371/journal.pone.0036053.t001

(1) Seasonal variation in Tb daily rhythms

There were significant effects of both ‘week’ and ‘individual’ on Tbmesor and Tbacrophase (F1,175 = 35.86, p<0.001 and F7,175 = 8.51, p<0.001 respectively; Fig. 2A, 2C) indicating that mesor values increased significantly and acrophase values became earlier over the time period, and that these values differed between individuals. There was also a significant interaction between individual and week on Tbamplitude (F7,168 = 2.60, p<0.05; Fig. 2B) indicating that changes in amplitude differed between individuals over time.

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Figure 2. Mean ±SE daily rhythm parameters of eight Cape ground squirrels during the 23 week measurement period for: (a) Tb Mesor (°C); (b) Tb Amplitude (°C); (c) Tb Acrophase (time of day and degrees).

Individuals inhabiting the flood plain and the woodland are denoted by solid and open circles. Maximum, minimum and mean Ta values are shown in (d) as top, middle and lower lines.

https://doi.org/10.1371/journal.pone.0036053.g002

(2) Effect of light and Ta on Tb daily rhythms

Mean Ta values ranged from 7.0±1.4°C during the first week to 21.1±0.43°C during the last with daily minimum and maximum values of −3°C and 22°C, and 9°C and 36°C respectively (Fig. 2D). By comparison, mean Tb ranged from 37.37±0.11°C during the first week to 37.70±0.12°C during the last. This corresponded to minimum and maximum Tb values of 34.28 and 40.11°C, and 35.64°C and 41.23°C, respectively (Fig. 2A).

When the effects of ambient conditions on Tb were examined the only ‘temperature’ variable (of Tamin, Tamean and Tamax) that significantly influenced Tbmesor was Tamax (F1,60 = 23.87, p<0.001). Similarly, the only ‘light’ variable that significantly affected Tbmesor was the time of sunset (F1,99 = 23.72, p<0.001). When both explanatory terms were included into the same model, neither had a significant effect (p>0.1 in both cases). In contrast, although Tamax had a significant effect on Tbamplitude (F1,53 = 12.43, p<0.01), Tamean and sunrise were the factors that significantly affected Tbacrophase (F1,64 = 29.80, p<0.001 and F1,78 = 42.05, p<0.001 respectively), with sunrise being the most important factor in the combined model (F1,45 = 10.90, p<0.01).

(3) Relationships between emergence and immergence times and Tb daily rhythms

Animals emerged later in the day at the beginning of the measurement period (07∶44) (May), than at the end (October) (06∶40) (least-squares regression, F1,46 = 63.25, r2 = 0.579, p<0.001). In contrast, immergence times occurred earlier in the day at the beginning of the measurement period (17∶24) than at the end (18∶17) (F1,45 = 103.02, r2 = 0.696, p<0.001)(Fig. 3). There were no differences in emergence and immergence times between animals that inhabited the flood plain and the woodland (emergence: F1,46 = 0.19, p = 0.662; immergence: F1,45 = 0.17, p = 0.685). However, there was an indication that variation in Tb on a day-by-day basis reflected variation in Ta with depressions in Tb occurring at similar times to depressions in Ta (Fig. 4). Changes in Tb over 24 h periods were greatest at around the times of emergence and immergence, sometimes in excess of 5°C, highlighting the potential relationship between Tb and whether or not the animals were above or below ground (Fig. 5). During the winter (week 1), mean increases in Tb for the hour following emergence were +1.10±0.12°C, which were greater than changes in Tb which occurred in the hour preceding emergence of −0.14±0.13°C. During the end of the measurement period at week 22, increases in Tb following emergence were less at +0.77±0.12°C compared to +0.48±0.10°C during the hour prior to emergence, respectively. There was a significant difference in the Tb increase between the beginning and the end of the measurement period, with a 52% increase in Tb during the first hour following emergence (relative to the total change in Tb during that day) during week one and only a corresponding 20% increase in Tb during week 22 (F1,20 = 4.99, r2 = 0.20, p<0.05). Tb values stabilized when animals returned to their burrows in the evening; changes in Tb of −0.01±0.06°C were recorded during the hour post immergence and −0.16±0.06°C during the hour prior to immergence for week 1; this compared to changes of −0.08±0.04°C and −0.20±0.04°C, for post-and pre-immergence times during week 22, respectively.

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Figure 3. Mean ±SE immergence and emergence times in the flood plain (solid circles and bold line) and woodland (open circles and light line).

Mean number of animals observed at any one time was 8.1±4.5 at emergence and 5.6±2.6 at immergence.

https://doi.org/10.1371/journal.pone.0036053.g003

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Figure 4. Tb (open circles) and Ta (solid circles) and fitted cosine curves for a Cape ground squirrel during the 9th week of the sampling period illustrating the variation in Ta and Tb.

The difference between the lowest Tb value recorded (33.39°C at 19:08) and the highest Tb during the previous day (39.32°C at 16:08) was 5.93°C. Over the 23 week period, extreme changes in Tb included one individual that decreased in Tb by 5.56°C and another that increased in Tb by 5.98°C in one hour.

https://doi.org/10.1371/journal.pone.0036053.g004

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Figure 5. Mean ±SE Tb changes between successive hours across all eight individuals during the first, eighth, fifteenth and twenty-second weeks of the measurement period.

Grey bars represent the mean ±SE times of emergence (left-hand bar) and immergence (right-hand bar).

https://doi.org/10.1371/journal.pone.0036053.g005

The mean time at which Tb began to decrease in the mornings across all seasons was 10:13±0:19 minutes and 38.70±0.06°C (Fig. 6). This time became earlier as the measurement period progressed from week 1 to week 22. For the weeks 1, 8, 15 and 22, the mean times when Tb first decreased were 10:59±0:23, 10:14±0:27, 10:22±0:33 and 9:14±0:28 minutes which corresponded to mean Tb values of 38.49±0.07, 38.82±0.11, 38.75±0.14 and 38.72±0.18°C, respectively.

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Figure 6. Mean ±SE Tb of the eight individuals for the first, eighth, fifteenth and twenty-second weeks of the sampling period.

Tb values rose rapidly in the morning before reaching a plateau during the day.

https://doi.org/10.1371/journal.pone.0036053.g006

(4) Effect of habitat on Ta and Tb daily rhythms

Mean daily Ta values were not significantly different between the two habitats (F1,167 = 0.188, P = 0.665). However, there were significant differences between habitats when day and night temperatures were specified in the model (Habitat: F1,335 = 0.939, p = 0.333; Day/night: F1,335 = 1131,p<0.001; Habitat * Day/night: F1,335 = 33.310, p<0.001) indicating that the flood plain was significantly hotter during the day and colder during the night than the woodland. Mean Ta values in the flood plain were 18.00±0.41°C during the day and 2.46±0.42°C during the night which compared with values of 15.34±0.40°C during the day and 4.35±0.37°C during the night in the woodland (Fig. 2D).

There was a significant effect of habitat on Tbmesor and Tbamplitude values. Values recorded for individuals from the flood plain were higher than those from the woodland (F1,150 = 10.23, p<0.01 and F1,159 = 81.58, p<0.001 respectively; Fig. 2A, 2B). However, there was no significant difference between Tbacrophase values of individuals from the two habitats (F1,127 = 1.59, p = 0.210; Fig. 2C).

(5) Effect of age and group size on Tb daily rhythms

There were significant interactions between age and body mass on Tbmesor (F1,111 = 75.8, p<0.001 respectively). Older individuals decreased Tb with increasing mass whereas Tb was independent of body mass in younger animals. There was also a significant effect of group size on Tbmesor with individuals from larger groups having lower Tbmesor values than those from smaller groups (F1,156 = 18.70, p<0.001 respectively; Fig. 7A). There was a significant effect of group size (F1,154 = 22.29, p<0.001) and a significant interaction between age and body mass on Tbamplitude (F1,153 = 9.22, p = 0.003). Individuals from larger group sizes had lower Tbamplitude values and older animals decreased in Tbamplitude with increasing mass whereas Tbamplitude was independent of body mass in younger animals (Fig. 7B).There were significant interactions between age and body mass and between group size and body mass on Tbacrophase (F1,74 = 44.26, p<0.001 and F1,120 = 36.25, p<0.001 respectively; Fig. 7C). Young animals which were large for their age tended to have Tbacrophase values which occurred earlier in the day whereas larger adults had Tbacrophase values which occurred later. Finally, Tbacrophase values tended to occur later in the day as group size increased but was earliest for a group size of nine.

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Figure 7. Mean ±SE values of the mesor, amplitude and acrophase shown per age class (subadults and adults) and for different group sizes (1, 3, 4, 5 and 9).

The number of individuals in each category is indicated above the error bars. The parameters have been averaged for the level of individual (per category) and then for all weeks, hence SE is non-zero even when only data from one individual is presented.

https://doi.org/10.1371/journal.pone.0036053.g007

(6) Effect of season, age and group size on the heterothermy index (HI)

Mean HI value across all individuals was 1.23±0.29°C and ranged from 0.68 to 2.32°C. While there were significant differences in HI values between individuals, there was no significant effect of ‘week’ (F7,175 = 22.91, p<0.001 and F1,175 = 1.15, p = 0.286). However, individuals from larger group sizes had lower HI values (least squares regression F1,182 = 20.33, p<0.001) and there was a significant interaction between age and group size on HI (F1,180 = 15.03, p<0.001); older animals decreased in HI with increasing group size whereas for young animals HI was independent of group size.

Discussion

Living in hot arid environments can be stressful for small diurnal mammals since the availability of free water necessary to reduce body heat by evaporation is limited [49]. Consequently, evaporative cooling is often accompanied by behavioral and physiological mechanisms to dissipate heat such as the use of a thermal refuge or substrate [50] or heterothermy [13], [51][53]. In the current study, Cape ground squirrels were exposed to a wide seasonal and daily range of Ta and the Tbmesor of all individuals increased significantly as the season progressed. This indicates that Tb values, including both maximal and minimal Tb's were higher on average when Ta values were higher. This will presumably serve to conserve their water and energy as a reduced Ta-Tb temperature gradient minimizes the need to keep cool by evaporation [15], [54], [55]. In addition, acrophase values became earlier over the measurement period, indicating that activity periods also became earlier [28], [56]. Ground squirrels in general have labile Tb's [2], [5], [57][61], Tbamplitudes of different species may vary by 4–5°C and be accompanied by bouts of torpor or hibernation. This compares with Tb amplitude values of up to 4.1°C in Arabian oryx (Oryx leucoryx) [51] and 2.6°C in Arabian sand gazelles (Gazella subgutturosa marica) [52]. We found no evidence of torpor and recorded daily variation in Tb, of 5–6°C, which is greater than that noted in most other species and greater than noted by Wilson et al. (2010) [33] for Cape ground squirrels in a more mesic area (3.8°C amplitude); hence this probably reflects adaptation to an environment with high Ta values and large daily variations in Ta.

(3) Relationship between Tb daily rhythms, Ta and daylight

Peak ambient temperature (Tamax) was the primary factor that explained both Tbmean and Tbamplitude, which suggests that this is the most thermally challenging period of the day. By comparison, sunrise provided the greatest explanatory power defining Tbacrophase which may suggest that sunrise acted to temporally entrain the thermoregulatory system [62]. Indeed Tbmean increased rapidly (4–5°C) post-emergence. The sensitivity of organisms to the timing of first light is exemplified by the fact that light ‘pollution’ during the dark phase can alter the seasonal acclimation of thermoregulatory, reproductive and immune systems of small mammals [63], [64]. Interestingly, increases in Tb during the first hour post-emergence were faster and greater earlier in the measurement period, indicating that animals gained thermal energy more rapidly during the winter. This indicates that as well as endogenous rhythms, mechanisms such as sun-basking might also be important in raising Tb [28], [31], [65], [66]. Whether or not squirrels preferentially orientate themselves to maximize heat uptake whilst basking, for example as in Raccoon dogs (Nyctereutes procyonoides) [67], remains unclear. By comparison, after initial increases, the time at which Tb stabilized in the mid-morning is likely to be indicative of another regulatory behavior: seeking shelter in burrows or in shade [31], [68]. This effect also became earlier as the season progressed (Fig. 7) suggesting that animals were using thermal refuges to offload heat earlier, allowing periodic bouts of foraging. There was also an indication that Tb tracked Ta (Fig. 4) highlighting the thermal lability of these animals. It is likely that Cape ground squirrels were allowing their Tb to vary to defend both water loss and energy expenditure as the greatest amplitudes of variation were noted during the winter. Alpine ibex (Capra ibex ibex) also show the greatest amplitude of variation of Tb during the winter which the authors suggested promoted a ‘thrifty’ use of body reserves [9]. By comparison, desert ungulates showed the greatest daily variation in Tb during the summer (2.6±0.8°C in Arabian sand gazelles and 4.1±1.7°C in Arabian oryx); this is the season that is most stressful for them when they benefit most by minimizing evaporative water loss [51], [52]. It is noteworthy that Tbmean decreased just before evening immergence and remained steady once the squirrels were within their burrows. It seems that the major stimulus to enter burrows could be the prevention of a further decrease in Tb or an increase in energy expenditure due to increased thermoregulation, rather than other possible cues, such as light intensity.

(4) Influence of habitat on Tb daily rhythms

As expected, Ta was more variable in the flood plain than in the woodland, with the former habitat exhibiting both colder nights and hotter days. Although the sample size was reduced because we were not able to capture many of the individuals that were implanted, the results obtained suggest that Tbamplitude values were also greater in animals inhabiting the flood plain than the woodland. This may reflect a physiological strategy to minimize the Ta-Tb temperature gradient and save on thermoregulatory costs [55]. There were also significant differences between Tbmesor values of animals inhabiting the two habitats, with higher values recorded in those from the flood plain. This is interesting because Tamesor values did not differ between the two habitats. Therefore, the high Ta experienced during the day must have had a greater effect on the squirrels' physiology than the Ta experienced during the night in their burrows; moreover the flood plain was more thermally challenging than the woodland. Presumably squirrels are not exposed to the lowest Ta values during the night because they shelter in burrows, whereas they are exposed to high Ta values during the day even though they may use of temporary thermal refuges [68]. This corroborates our previous finding that Tamax held the greatest explanatory power for and Tbmesor.

The fact that variation in physiological characteristics occurred within a small geographical area suggests that Cape ground squirrels are able to regulate their Tb according to local environmental conditions. Similar patterns have been recorded in other small mammals albeit over different scales. Common spiny mouse (Acomys cahirinus) populations a mere 2–300 m apart on either side of a valley in the Mediterranean ecosystem exhibit a suite of physiological differences which include variations in their chronobiology [15], [69], as do populations of the broad-toothed field mouse (Apodemus mystacinus) from different sides of the African Great Rift valley [70], [71]. A. cahirinus inhabiting a xeric environment had later Tbacrophase and greater Tbamplitude values than those inhabiting a mesic cooler environment [15]. It was suggested that individuals from the former population allowed their Tb to vary considerably, rather than waste water by controlling Tb through evaporation or waste energy using endogenous heat sources, a strategy noted elsewhere [72][74]. Since no physical barrier exists between the two sites in the current study, one can assume that there is relatively high within-site fidelity [40].

(5) Effects of age and group size on Tb variation

Across taxa, younger animals generally have less prominent Tb daily rhythms than older animals, in part because Tb daily rhythms need time to mature [75], [76]. Larger animals also tend to have smaller Tbamplitude values as a presumed consequence of their greater thermal inertia and reduced susceptibility to changes in food availability [76], [77]. Although our results must be interpreted with caution because of the small sample sizes, these relationships are corroborated as a negative correlation was noted between Tbmean and body mass in older but not in younger animals. In our case, heavy young animals also tended to have earlier Tbacrophase values, indicating earlier activity periods in these individuals. If emergence times are driven by thermoregulatory constraints, it is possible that older individuals and those large for their age may emerge earlier because of their lower surface area to volume ratios and greater thermal capacities. An alternative explanation might be that larger animals might simply have more fat reserves, allowing them to emerge earlier and expend more energy on thermoregulation.

The fact that Tbmesor values decreased with increasing group size suggests that squirrels were expending less energy on thermoregulation in larger groups. Previous studies have suggested that aggregation/huddling behavior can significantly reduce thermoregulatory costs [17], [78] and daily averaged energy expenditure [79] in some groups of small mammals. For example, Tb values were found to be lower in large groups of roosting bats Noctilio albiventris [80]. It was suggested that individual bats in larger groups might be less prone to predation and hence could benefit by lowering their Tb's further than those within smaller groups. In contrast, for two species of African mole-rat (Cryptomys hottentotus natalensis and Fukomys damarensis), individuals in experimentally increased group sizes had greater Tb values [78]. In this case a crowded burrow which is thermally buffered might make it difficult to cool down and consequently Tb values are greater. Because Cape ground squirrels forage during the day as a spaced group [35], any thermoregulatory benefits of group size would presumably occur during the night [68] and hence a larger group size could facilitate a lower and more stable Tb.

Finally, both Tbamplitude and HI were negatively associated with group size and older animals had lower HI values in larger group sizes whereas younger animals did not. This is also consistent with our predictions that individuals in larger groups benefit by being thermally buffered and that older animals are better at regulating their Tb. In this instance, both metrics (Tbamplitude and HI) appear to provide similar results, i.e. that there are significant effects of age and group size on Tb variation. Overall, these data confirm that the thermal physiology of Cape ground squirrels is sensitive to changes both in the abiotic and biotic environment. Many factors are observed to affect their Tb, which can be modified, enabling them to survive in arid, hostile environments.

Acknowledgments

We would like to thank Northwest Parks and Tourism and the staff of S.A. Lombard Nature Reserve for their help and permission to conduct this research. We would also like to thank Prof. J.W. Ferguson for helpful discussions and providing programs to analyse Tb data as well as Justin Boyles and an anonymous reviewer for valuable comments on an earlier draft of the manuscript. Tania Serfontein helped with surgical procedures whilst Lydia Belton, Johannie Caldo, Melissa Hillegass, Tambudzani Mulaudzi, Joe Osbourne and Beth Pettitt provided valuable assistance in the field.

Author Contributions

Conceived and designed the experiments: MS. Performed the experiments: MS MBM KEJ. Analyzed the data: MS MDG. Contributed reagents/materials/analysis tools: NCB JMW. Wrote the paper: MS MDG PWB NCB MBM KEJ JMW.

References

  1. 1. Kenagy GJ, Vleck D (1982) Daily temporal organization of metabolism in small mammals: adaptation and diversity. In: Aschoff J, Dean S, Groos G, editors. Vertebrate Circadian Systems. Berlin: Springer.
  2. 2. Refinetti R (1999) Amplitude of the daily rhythm of body temperature in eleven mammalian species. J Therm Biol 24: 477–481.
  3. 3. Aschoff J (1982) The circadian rhythms of body temperature as a function of body size. In: Taylor CR, Johanson K, Bolis L, editors. A Companion to Animal Physiology. Cambridge: Cambridge University Press. pp. 173–188.
  4. 4. Haim A, Rubal A (1994) Seasonal acclimatization of daily rhythms of body temperature in two rodent species of different origins inhabiting Mediterranean woodland. Pol Ecol Stud 20: 357–363.
  5. 5. Golightly RT Jr, Ohmart RD (1978) Heterothermy in free ranging Albert's squirrels (Sciurus aberti). Ecology 59: 897–909.
  6. 6. Wollnik F, Schmidt B (1995) Seasonal and daily rhythms of body temperature in the European hamster (Cricetus cricetus) under semi-natural conditions. J Comp Physiol B 165: 171–182.
  7. 7. Kenagy GJ, Nespolo RF, Vásquez RA, Bozinovic F (2002) Daily and seasonal limits of time and temperature to activity of degus. Rev Chil Hist Nat 75: 567–581.
  8. 8. Yerushalmi S, Green RM (2009) Evidence for the adaptive significance of circadian rhythms. Ecol Lett 12: 970–981.
  9. 9. Signer C, Ruf T, Arnold W (2011) Hypometabolism and basking: the strategies of Alpine ibex to endure harsh over-wintering conditions. Funct Ecol 25: 537–547.
  10. 10. Heldmaier G, Steinlechner S, Ruf T, Wiesinger H, Klingenspor M (1989) Photoperiod and thermoregulation in vertabrates: body temperature rhythms and thermogenic acclimation. J Biol Rhythm 4: 251–256.
  11. 11. Haim A (1996) Food and energy intake, non-shivering thermogenesis and daily rhythm of body temperature in the bushy-tailed gerbil Sekeetamys calurus: the role of photoperiod manipulations. J Therm Biol 21: 37–42.
  12. 12. Boyles JG, Smit B, McKechnie AE (2010) A new metric for estimating heterothermy in endotherms. Physiol Biochem Zool 84: 115–123.
  13. 13. Angilletta MJ, Cooper BS, Schuler MS, Boyles JG (2010) The evolution of thermal physiology in endotherms. Frontiers in Bioscience E2: 861–881.
  14. 14. Haim A, Levi G (1990) Role of body temperature in seasonal acclimatization: Photoperiod-induced rhythms and heat production in Meriones crassus. J Exp Zool 256: 237–241.
  15. 15. Shanas U, Afik D, Scantlebury M, Haim A (2002) The effects of season and dietary salt content on body temperature daily rhythms of common spiny mice from different micro-habitats. Comp Biochem Physiol A 132: 287–295.
  16. 16. Levy O, Dayan T, Kronfeld-Schor N (2011) Adaptive thermoregulation in golden spiny mice: the influence of season and food availability on body temperature. Physiol Biochem Zool 84: 175–184.
  17. 17. Hayes JP, Speakman JR, Racey PA (1992) The Contributions of local heating and reducing exposed surface area to the energetic benefits of huddling by short-tailed field voles (Microtus agrestis). Physiol Zool 65: 742–762.
  18. 18. Kaufman AS, Paul MJ, Butler MP, Zucker I (2003) Huddling, locomotor, and nest-building behaviors of furred and furless Siberian hamsters. Physiol Behav 79: 247–256.
  19. 19. Madison DM, FitzGerald RW, McShea WJ (1984) Dynamics of social nesting in overwintering meadow voles (Microtus pennsylvanicus): possible consequences for population cycling. Behav Ecol Sociobiol 15: 9–17.
  20. 20. Berteaux D, Bergeron J-M, Thomas DW, Lapierre H (1996) Solitude versus gregariousness: do physical benefits drive the choice in overwintering meadow voles? OIKOS 76: 330–336.
  21. 21. Canals M, Rosenmann M, Novoa FF, Bozinovic F (1998) Modulating factors of the energetic effectiveness of huddling in small mammals. Acta Theriol 43: 337–348.
  22. 22. Gilbert C, Blanc S, Giroud S, Trabalon M, Le Maho Y, et al. (2007) Role of huddling on the energetic of growth in a newborn altricial mammal. Am J Physiol 293: R867–R876.
  23. 23. Cowling RM, Richardson DM, Pierce SM (2004) Vegetation of Southern Africa. Cambridge: Cambridge University Press.
  24. 24. van Zyl JHM (1965) The vegetation of the S. A. Lombard nature reserve and its utilisation by certain antelope. Zool Afr 1: 55–71.
  25. 25. Pavlícek T, Sharon D, Kravchenko V, Saaroni H, Nevo E (2003) Microclimatic interslope differences underlying biodiversity contrasts in “Evolution Canyon”, Mt. Carmel, Israel. Israel J Earth Sci 52: 1–9.
  26. 26. Haim A, Skinner JD, Robinson TJ (1987) Bioenergetics, thermoregulation and urine analysis of squirrels of the genus Xerus from an arid environment. S Afr J Zool 22: 45–49.
  27. 27. van Heerden J, Dauth J (1987) Aspects of adaptation to an arid environment in free-living ground squirrels Xerus inauris. J Arid Environ 13: 83–89.
  28. 28. Herzig-Straschil B (1978) On the biology of Xerus inauris (Zimmermann, 1780) (Rodentia, Sciuridae). Z Säugetierkunde 43: 262–278.
  29. 29. Bennett AF, Huey RB, John-Alder H, Nagy KA (1984) The parasol tail and thermoregulatory behavior of the Cape ground squirrel Xerus inauris. Physiol Zool 57: 57–62.
  30. 30. Huey RB, Bennett AF (1990) Physiological adjustments to fluctuating thermal environments: An ecological and evolutionary perspective. In: Morimoto R, Tissieres A, Georgopoulos C, editors. Stress Proteins in Biology and Medicine. New York: Cold Spring Harbour Press. pp. 37–59.
  31. 31. Fick LG, Kicio TA, Fuller A, Matthee A, Mitchell D (2009) The relative roles of the parasol-like tail and burrow shuttling in thermoregulation of free-ranging Cape ground squirrels, Xerus inauris. Comp Biochem Physiol A 152: 334–340.
  32. 32. Wooden KM, Walsberg GE (2002) Effect of environmental temperature on body temperature and metabolic heat production in a heterothermic rodent, Spermophilus tereticaudus. J Exp Biol 205: 2099–2105.
  33. 33. Wilson WA, O'Riain MJ, Hetem RS, Fuller A, Fick L (2010) Winter body temperature patterns in free-ranging Cape ground squirrel, Xerus inauris: no evidence for torpor. J Comp Physiol B 180: 1099–1110.
  34. 34. Halberg F, Johnson EA, Nelson W, Kunge W, Sothen RB (1972) Autorhythmometry procedures for physiological self measurements and their analysis. Physiol Teach 1: 1–11.
  35. 35. Waterman JM (1995) The social organization of the Cape ground squirrel (Xerus inauris; Rodentia: Sciuridae). Ethology 101: 130–47.
  36. 36. Waterman JM (1997) Why do male Cape ground squirrels live in groups? Anim Behav 56: 459–66.
  37. 37. Waterman JM (1998) Mating tactics of male Cape ground squirrels, Xerus inauris: consequences of year-round breeding. Anim Behav 56: 459–466.
  38. 38. Hillegass MA, Waterman JM, Roth JD (2008) The influence of sex and sociality on parasite loads in an African ground squirrel. Behav Ecol 19: 1006–1011.
  39. 39. Pettitt BA, Waterman JM, Wheaton CJ (2008) Assessing the effects of resource availability and parity on reproduction in female Cape ground squirrels: resources do not matter. J Zool Lond 276: 291–298.
  40. 40. Unck CE, Waterman JM, Verburgt L, Bateman PW (2009) Quantity versus quality: How does level of predation threat affect Cape ground squirrel vigilance? Anim Behav 78: 625–632.
  41. 41. Rood JP, Nellis D (1980) Freeze-marking mongooses. J Wildl Manag 44: 500–502.
  42. 42. Waterman JM (1996) Reproductive biology of a tropical, non-hibernating ground squirrel. J Mamm 77: 134–146.
  43. 43. Altmann J (1974) Observational study of behavior: sampling methods. Behaviour 49: 227–267.
  44. 44. Lovegrove BG (2009) Modification and miniaturization of Thermochron iButtons for surgical implantation into small animals. J Comp Physiol B 179: 451–458.
  45. 45. Joubert KE, Serfontein T, Scantlebury M, Manjerovic MB, Bateman PW, et al. (2011) Determination of an optimal dose of medetomidine-ketamine-buprenorphine for anaesthesia in the Cape ground squirrel (Xerus inauris). J S Afr Ves Ass 82: 94–96.
  46. 46. Manjerovic MB (2010) The influence of sexual selection on behavioral and physiological mechanisms underlying reproductive success in male Cape ground squirrels (Xerus inauris). PhD Dissertation. Orlando, FL: University of Central Florida.
  47. 47. Nelson W, Tong YL, Lee J-K, Halberg F (1979) Methods for cosinor rhythmicity. Chronobiologia 6: 305–23.
  48. 48. Minors DS, Waterhouse JM (1989) Analysis of biological time series. In: Minors DS, Waterhouse JM, editors. Biological Rhythms in Clinical Practice. London: Wright. pp. 272–284.
  49. 49. Walsberg GE (2000) Small mammal in hot deserts: some generalisations revisited. Bioscience 50: 109–120.
  50. 50. Türk A, Arnold W (1988) Thermoregulation as a limit to habitat use in alpine marmots (Marmota marmota). Oecologia 76: 544–548.
  51. 51. Ostrowski S, Williams JB, Ismael K (2003) Heterothermy and the water economy of free-living Arabian oryx (Oryx leucoryx). J Exp Biol 206: 1471–1478.
  52. 52. Ostrowski S, Williams JB (2006) Heterothermy of free-living Arabian sand gazelles (Gazella subgutturosa marica) in a desert environment. J Exp Biol 209: 1421–1429.
  53. 53. Hetem RS, Strauss WM, Fick LG, Maloney SK, Meyer LCR, et al. (2010) Variation in the daily rhythm of body temperature of free-living Arabian oryx (Oryx leucoryx): does water limitation drive heterothermy? J Comp Physiol B 180: 1111–1119.
  54. 54. Lovegrove BG, Heldmaier G, Knight M (1991) Seasonal and circadian energetic patterns in an arboreal rodent, Thallomys paedulcus, and a burrow-dwelling rodent, Aethomys namaquensis, from the Kalahari desert. J Therm Biol 16: 199–209.
  55. 55. Lovegrove BG, Heldmaier G (1994) The amplitude of circadian body temperature rhythms in three rodents along an arboreal-subterranean gradient. Austral J Zool 42: 65–78.
  56. 56. Refinetti R, Menaker M (1992) The circadian rhythm of body temperature. Physiol Behav 51: 613–637.
  57. 57. Hudson JW, Deavers DR, Bradley SR (1972) A comparative study of temperature regulation in ground squirrels with special reference to desert species. Symp Zool Soc Lond 31: 191–213.
  58. 58. Long RA, Martin TJ, Barnes BM (2005) Body temperature and activity patterns in free-living arctic ground squirrels. J Mamm 86: 314–322.
  59. 59. Sharpe PB, Van Horne B (1999) Relationships between the thermal environment and activity of Piute ground squirrels (Spermophilus mollis). J Therm Biol 24: 265–278.
  60. 60. Wooden KM, Walsberg GE (2004) Body temperature and locomotor capacity in a heterothermic rodent. J Exp Biol 207: 41–46.
  61. 61. Gür H, Gür MK (2010) Analtolian ground squirrels (Spermophilus xanthoprymnus): Hibernation and geographic variation of body size in a species of old World ground squirrels. Hacettepe J Biol & Chem 38: 247–253.
  62. 62. Morgan E (2004) Ecological significance of biological clocks. Biol Rhythm Res 35: 3–12.
  63. 63. Haim A, Shanas U, Zubidad AE, Scantlebury M (2005) Seasonality and seasons out of time - The thermoregulatory effects of light interference. Chronobiol Int 22: 59–66.
  64. 64. Schwimmer H, Mursu N, Haim A (2010) Effects of light and melatonin treatment on body temperature and melatonin secretion daily rhythms in a diurnal rodent, the fat sand rat. Chronobiol Int 27: 1401–1419.
  65. 65. Straschil B (1975) Sandbathing and marking in Xerus inauris. (Zimmerman, 1870)(Rodentia, Sciuridae). S Afr J Sci 71: 215–216.
  66. 66. Scantlebury M, Krackow S, Pillay N, Bennett NC, Schradin C (2010) Basking is affected by season and influences oxygen consumption in desert-living striped mice. J Zool Lond 281: 132–139.
  67. 67. Harri M, Korhonen H (1988) Thermoregulatory significance of basking behaviour in the raccoon dog (Nyctereutes procyonoides). J Therm Biol 13: 169–174.
  68. 68. Herzig-Straschil B (1979) Xerus inauris (Rodentia, Sciuridae) - an inhabitant of the arid regions of Southern Africa. Folia Zool 28: 119–124.
  69. 69. Scantlebury M, Shanas U, Speakman JR, Kupshtein H, Afik D, et al. (2003) Energetics and water economy of common spiny mice Acomys cahirinus from north- and south-facing slopes of a Mediterranean valley. Funct Ecol 17: 178–185.
  70. 70. Spiegel M, Haim A (2004) Daily rhythms of nonshivering thermogenesis and responses to photoperiod manipulations in Apodemus mystacinus from two different ecosystems. J Therm Biol 29: 635–640.
  71. 71. Scantlebury M, Shanas U, Or-Chen K, Haim A (2009) Osmoregulatory traits of broad-toothed field mouse (Apodemus mystacinus) populations from different habitats. Comp Biochem Physiol A 154: 551–556.
  72. 72. Scantlebury M, Lovegrove BG, Jackson CR, Bennett NC, Lutermann H (2008) Hibernation and non-shivering thermogenesis in the Hottentot golden mole (Amblysomus hottentottus longiceps). J Comp Physiol B 178: 887–897.
  73. 73. Warnecke L, Turner JM, Geiser F (2008) Torpor and basking in a small arid zone marsupial. Naturwissenschaften 95: 73–78.
  74. 74. Jackson CR, Setsaas TH, Robertson MP, Scantlebury N, Bennett NC (2009) Insights into torpor and behavioural thermoregulation of the endangered Juliana's golden mole. J Zool Lond 278: 299–307.
  75. 75. Piccione G, Caola G, Refinetti R (2002) Maturation of the daily body temperature rhythm in sheep and horse. J Therm Biol 27: 333–336.
  76. 76. Piccione G, Fazio F, Giudice E, Refinetti R (2009) Body size and the daily rhythm of body temperature in dogs. J Therm Biol 34: 171–175.
  77. 77. Kinahan AA, Kotze A, Bateman PW, Scantlebury M (2007) Daily body temperature rhythms in the African savanna elephant, Loxodonta africana. Physiol Behav 92: 560–565.44. Lovegrove BG (2009) Modification and miniaturization of Thermochron iButtons for surgical implantation into small animals. J Comp Physiol B 179: 451–458.
  78. 78. Kotze J, Bennett NC, Scantlebury M (2008) The energetics of huddling in two species of mole-rat (Rodentia: Bathyergidae). Physiol Behav 93: 215–221.
  79. 79. Scantlebury M, Bennett NC, Speakman JR, Pillay N, Schradin C (2006) Huddling in groups leads to daily energy savings in free-living African four-striped grass mice, Rhabdomys pumilio. Funct Ecol 20: 166–173.
  80. 80. Roverud RC, Chapell MA (1991) Energetic and thermoregulatory aspects of clustering behavior in the neotropical bat Noctilio albiventris. Physiol Zool 64: 1527–1541.