Energetics underlies many aspects of a species' biology, including reproduction (e.g. McAllan 2003), population dynamics and population density (e.g. Millar & Hickling 1990, 1992), ecological niche and many aspects of behaviour including movement throughout the landscape (e.g. Darling 1938). Field metabolic rate (FMR) measures the rate of energy use that has direct relevance to a species' biology and is particularly relevant ecologically because it is measured in the natural environment. Quantifying FMR has revolutionised the understanding and relevance of ecological energetics in general and ecophysiology in particular. The doubly labelled water (DLW) method is the most commonly used technique for measuring FMR, using the differential fractional turnovers of heavy isotopes of hydrogen (deuterium 2H, or tritium 3H) and oxygen (18O) to measure CO2 production (Lifson & McClintock 1966; Nagy 1983; Speakman 1997). Although DLW has revolutionised the measurement of energy use by free-ranging animals, validations of its accuracy are relatively rare in comparison with the large number of studies that have used the technique (see Williams & Nagy 1984; Williams 1985; Nagy et al. 1990; Tiebout & Nagy 1991; Bevan, Speakman & Butler 1995b; Bevan et al. 1995a; Speakman 1998; Jones et al. 2009). Validation for different taxa is important because there are several requirements for reliability of the technique that are not always easy to meet (Nagy & Costa 1980; Speakman 1997). The easiest of these assumptions to violate is ‘Assumption Three’ (Speakman 1997), that body water pool size (N) is constant throughout the measurement period. Further, because the estimation of CO2 efflux depends on subtracting the efflux of 18O as H2O from overall 18O losses (as CO2 and H2O), the method becomes unreliable for species with a high water efflux relative to metabolic CO2 production, such as amphibians (Hillman et al. 2009) and diving species (Bevan, Speakman & Butler 1995b; Bevan et al. 1995a). ‘Assumption Five’ (Speakman 1997), that all substances entering the animal are labelled at background levels, can also create problems for the DLW technique with species living in atmospheres that can become isotopically enriched by exhaled CO2 and H2O (such as fossorial rodents) because the re-influx of labelled CO2 and H2O can underestimate the fractional turnover rates (Nagy 1980). Furthermore, the most reliable FMR results are measured within one-to-two biological half-lives of the 18O isotope. For large animals, this is a week to 10 days (Speakman 1997), when the isotope concentration falls close to background levels and reliable measurements are no longer possible (Nagy 1983). For small animals this temporal window is much shorter (e.g. as little as 36 h for Tarsipes rostratus; Bradshaw & Bradshaw 2007), meaning that a large proportion of the measurement period is potentially compromised by capture and experimental procedures. Notwithstanding innovations by Anava et al. (2002), blood sampling is the most common and efficacious way of measuring DLW turnover, but Bradshaw & Bradshaw (1999, 2007) note that the stress of repeated blood sampling to measure isotope turnover may influence the subjects' metabolism (especially for small animals). Finally, the 18O-isotope is expensive to procure and analyse (Nagy 1983; Speakman 1997), and these costs can be prohibitive (Speakman 1997). While substantial effort has been expended to overcome or account for these errors using DLW, often very successfully (see Speakman 1997 and references therein), other techniques have been proposed to measure FMR that avoid these limitations.
Other methods that have been used to measure or infer FMR, including heart rate as an index of metabolic rate (see Cooke et al. (2004) and Green (2011) for review), labelled bicarbonate turnover (Hambly, Harper & Speakman 2002), and time/budget analyses (Buttemer et al. 1986). The most common alterative to DLW is heart rate biotelemetry, whereby the heart rate of a free-ranging animal is converted to FMR using a previously derived correlation of heart rate and MR of the animal (in the laboratory). Reservations have been expressed concerning the accuracy of this approach, based on the variability in stroke volume and/or extraction of oxygen by the tissues which will confound the relationship between heart rate and metabolic rate (Gessaman 1980; Green 2011 and references therein). Further, many approaches fail to quantify anaerobic activity, an important component of energy budgets (Cooke et al. 2004). The necessity to measure heart rate precludes its use in invertebrates with multiple cardiac pumps, and intake requires the O2 demand of tissues to be supplied by the heart exclusively (which is not the case in fish, for which the technique has had limited success; Thorarensen, Gallaugher & Farrrel 1996; Green 2011). The method is also very size-limited, because heart rate logger size should not exceed 2–5% of body mass (Caccamise & Hedin 1985; Gursky 1998; Cooke et al. 2004). Even the smallest heart rate monitors have focussed on fish of 200–250 g (Preide & Tytle 1977), and 17 g birds (Cochran & Wikelski 2005). Although telemeters are now small enough to measure the heart rate of small individuals, the battery life of such small units is short (Cooke et al. 2004), leading to similar potential compromising of the data by capture and experimental procedures, as already discussed for the DLW technique. Finally, despite its widespread use, Green (2011) notes that the validation of predictions using the heart rate method are still required to address the substantial variability in the response of heart rate to different environmental and physiological stimuli. The technique does, however, allow scope to identify the costs of specific behaviours (Bevan, Speakman & Butler 1995b; Bevan et al. 1995a, 2002; Green 2011) and to potentially correlate these behaviours to a species' ecology in such paradigms as dynamic energy budgets (Kooijman 2000), thus providing useful management information.
Another approach to the measurement of FMR relates the elimination of a radioactive isotope to metabolic rate (Odum & Golley 1963). Several isotopes, including 32P (Wagner 1970), 137Ce and 59Fe (Baker & Dunaway 1975), 22Na, 51Cr, 54Mn, 60Co, 65Zn and 86Rb (Peters et al. 1995; Peters 1996), have been investigated in this regard. Of these, 86Rb had the strongest correlation with the rate of carbon dioxide production (), with an r of 0·96 for Dipsosaurus dorsalis (Peters et al. 1995), 0·82 for Bufo terrestris (Peters 1996) and 0·93 for T. rostratus (Bradshaw & Bradshaw 2007). Rubidium is an alkali metal that appears to be handled by the body in a similar manner to K+ (Adam & Craik 1989). If the biological turnover of 86Rb (86Rb kb) is proportional to metabolic rate, then measuring 86Rb kb offers the advantages for small animals of not requiring blood collection because the whole animal can be scanned for emissions and measurement can continue over a longer time span and at less expense than for DLW (Bradshaw & Bradshaw 2007). Limitations of the 86Rb technique are a paucity of validation data comparing 86Rb turnovers to for various taxa (Bradshaw & Bradshaw 2007) and a lack of understanding of the mechanism(s) of 86Rb turnover. At present, general inferences about 86Rb kb and FMR cannot be made, and further validation studies are required to show whether FMR can be estimated from 86Rb kb for more than the few species studied so far (Peters et al. 1995; Peters 1996; Bradshaw & Bradshaw 2007).
Here, we report a laboratory study of the relationship between [measured by DLW and by flow-through respirometry (FTR)] and 86Rb kb for two species of small marsupial, Sminthopsis ooldea and S. macroura (Marsupialia; Dasyuridae). If there is a good correlation between and 86Rb kb for these dunnarts, then we can establish a predictive regression that could be used to calculate the FMR of free-ranging individuals. We also examine whether there is a general relationship between and 86Rb kb for small vertebrates (using published data from other taxa).