Heat Production in Nocturnal (<i>Praomys Natalensis</i>) and Diurnal (<i>Rhabdomys pumilio</i>) South African Murids

Haim, Abraham; Fourie, F. Le R.

doi:10.1080/02541858.1980.11447692

Cited by 32 publications

(14 citation statements)

References 3 publications

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“…The various methods we examined for investigating spatiotemporal avoidance and temporal segregation are based on time and location of species records exclusively and thereby cannot distinguish between the ecological mechanisms underlying the observed patterns. The observed patterns could be the result interactions, or they may reflect other aspects of the species' ecology, such as differences in physiological adjustments to fluctuating ambient environmental conditions (Haim and Fourie 1980;Fuller et al 2010). Interspecific interactions are complex, and species have a wide array of behavioural responses at their disposal to avoid interactions, for example by partitioning space or resources instead of time.…”

Section: Discussionmentioning

confidence: 99%

Assessing analytical methods for detecting spatiotemporal interactions between species from camera trapping data

Niedballa

Wilting

Sollmann

et al. 2019

Remote Sens Ecol Conserv

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Assessing spatiotemporal interactions between species is of fundamental interest to behavioural and community ecology. Observer‐independent methods such as camera trapping facilitate the study of interactions, but analyses are hampered by the lack of comparative assessment of available approaches. We present a flexible and expandable framework to simulate and explore spatiotemporal interactions between species from camera trapping data with well‐defined properties, and compare methods to detect such interactions in a two‐species system with two types of (spatio)temporal interactions: spatiotemporal avoidance (of a site by a species after the presence of another species) and temporal segregation (shifts in daily activity patterns between species), across a range of daily activity patterns and interaction strengths. For spatiotemporal avoidance, we analysed time intervals between species records using linear models, the Mann–Whitney U‐test, a permutation test and a test based on randomly generated records. For temporal segregation, we applied a permutation test. Statistical power (the ability to detect an existing effect) for detecting spatiotemporal avoidance between species was strongly affected by interaction strength, highest for linear models and reliable above 50 records per species. Reliably detecting strong temporal segregation required fewer records (10–20 records) but depended heavily on the underlying activity pattern. All tests were valid (uniform distribution of P‐values under the null hypothesis) even at low sample sizes above a minimum of 10 records per species. Linear models were the most suitable approach to analyse spatiotemporal avoidance and can easily correct for other sources of variation in interactions. The framework presented here can help to improve survey design in camera trapping and be extended to more complex settings (e.g. with imperfect detection). In addition, it allows researchers to validate the methods used for inference of spatiotemporal interactions from camera trapping data in their specific circumstances.

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Section: Discussionmentioning

confidence: 99%

Assessing analytical methods for detecting spatiotemporal interactions between species from camera trapping data

Niedballa

Wilting

Sollmann

et al. 2019

Remote Sens Ecol Conserv

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“…The temperatures selected spanned a large part of the natural daily variation in ambient temperature experienced by the mice, during the winter, at the time of study (Cowling et al . 1999): 5 °C is approximately the minimal expected nest temperature (C. Schradin and N. Pillay, unpublished data) and 30 °C is just below the thermoneutral zone (Haim & Fourie 1980), beyond which thermoregulatory benefits of huddling cease. Measurements took place during the night (approx.…”

Section: Methodsmentioning

confidence: 99%

Huddling in groups leads to daily energy savings in free‐living African Four‐Striped Grass Mice, Rhabdomys pumilio

et al. 2006

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Summary1. Free-living animals make complex decisions associated with optimizing energy and nutrient intake. In environments where ambient temperatures fall below the thermoneutral zone, homeotherms must choose whether or not to forage, how long and what to forage for, and whether or not to perform activities that conserve energy. 2. Huddling in groups has long been thought of as a possible means of conserving energy. Laboratory studies have shown that at low ambient temperatures individuals in groups expend less energy than individuals by themselves. However, studies have yet to demonstrate that thermoregulatory savings can have an impact on the overall daily energy expenditure (DEE) of free-living animals. 3. Here we show that, in the laboratory, African Four-Striped Grass Mice ( Rhabdomys pumilio ) expend less energy per individual in large groups than smaller groups. We also show that when free-living groups were experimentally reduced to one-half of their original size, DEE and water turnover increased by 19% and 37%, respectively. 4. The magnitudes of the reduction in free-living DEE were comparable with calculated energy savings from the laboratory. One of the reasons why this species may sometimes occur in groups is that energetic benefits can be gained through huddling in habitats in which food and water are scarce.

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“…M. natalensis are primarily distributed in the mesic eastern parts of southern Africa, while M. coucha are abundant in the more arid central parts (Smit et al, 2001;Venturi et al, 2004). Therefore, Haim and Fourie (1980, 1981 and Fourie and Haim (1981) incorrectly refer to M. coucha collected outside Pretoria, as Praomys natalensis. The mice they studied did respond to changes in photoperiod through changes in heat production (VO 2 ) at different ambient temperatures and in their nonshivering thermogenesis (NST) capacity (Haim andFourie, 1980, 1981).…”

Section: Introductionmentioning

confidence: 99%

Daily rhythms of body temperature and heat production of sibling mastomys species from different ecosystems — The response to photoperiod manipulations

Haim

Zubidat

Aarde

2008

Comparative Biochemistry and Physiology Part A: Molecular &

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We compared body temperature (T b ) and metabolic rates, measured as oxygen consumption (VO 2 ), daily rhythms of two sibling species of the genus Mastomys. We also studied their responses to long day (16L: 8D, LD) and short day (8L: 16D, SD) photoperiod manipulations at a constant ambient temperature of 26 + 1°C. We noted significant differences in T b and VO 2 daily rhythm patterns, under SD and LD-acclimation between the sibling species. These differences explain adaptation to the climatic conditions that prevail in the different ecosystems where these species live. To the best of our knowledge, this is the first time that physiological differences between the two siblings are measured by using chronobiological methods.

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Heat Production in Nocturnal (Praomys Natalensis) and Diurnal (Rhabdomys pumilio) South African Murids

Cited by 32 publications

References 3 publications

Assessing analytical methods for detecting spatiotemporal interactions between species from camera trapping data

Assessing analytical methods for detecting spatiotemporal interactions between species from camera trapping data

Huddling in groups leads to daily energy savings in free‐living African Four‐Striped Grass Mice, Rhabdomys pumilio

Daily rhythms of body temperature and heat production of sibling mastomys species from different ecosystems — The response to photoperiod manipulations

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