Body surface area of the golden Syrian hamster.

The body surface areas (BSAs) of 30 Syrian hamsters were actually measured. From these areas, the Mass Coefficients (K values) for the Dubois and Dubois equation (5.31) and for the Meeh-Rubner equation (11.89), were computed. These values were independent of weight and sex. To verify the applicability of the Mass Coefficients, the BSAs of another 20 animals were calculated and compared with the actually measured BSAs. The difference between measured and calculated BSAs was not significant. Therefore, these values can be used with their respective equations to compute BSA in Golden Syrian hamsters.     

Body Surface Area Prediction in Odorrana grahami

Body surface area（BSA）was regarded as a more readily quantifiable parameter relative to body mass in the normalization of comparative biochemistry and physiology.The BSA prediction has attracted unceasing research back more than a century on animals,especially on humans and rats.Few studies in this area for anurans were reported,and the equation for body surface area（S）and body mass（W）：S=9.9 W 0.56,which was concluded from toads of four species in 1969,was generally adopted to estimate the body surface areas for anurans until recent years.However,this equation was not applicable to Odorrana grahami.The relationship between body surface area and body mass for this species was established as：S=15.4 W 0.579.Our current results suggest estimation equations should be used cautiously across different species and body surface area predictions on more species need to be conducted.     

Technical note: Criterion validity of whole body surface area equations: a comparison using 3D laser scanning

Measurements of whole body surface area (WBSA) have important applications in numerous fields including biological anthropology, clinical medicine, biomechanics, and sports science. Currently, WBSA is most often estimated using predictive equations due to the complex and time consuming methods required for direct measurement. The main aim of this study was to identify whether there were significant and meaningful differences between WBSA measurements taken using a whole body three-dimensional (3D) scanner (criterion measure) and the estimates derived from each WBSA equation identified from a systematic review. The study also aimed to determine whether differences varied according to body mass index (BMI), sex, or athletic status. Fifteen WBSA equations were compared with direct measurements taken on 1,714 young adult subjects, aged 18-30 years, using the Vitus Smart 3D whole body scanner, including 1,452 subjects (753 males, 699 females) from the general Australian population and 262 rowers (148 males, 114 females). Mixed-design analysis of variances determined significant differences and accuracy was quantified using Bland-Altman analysis and effect sizes. Thirteen of the 15 equations overestimated WBSA. With a few exceptions, equations were accurate with a low-systematic error (bias ≤2%) and low-random error (standard deviation of the differences 1.5-3.0%). However, BMI did have a substantial impact with the accuracy of some WBSA equations varying between the four BMI categories. The Shuter and Aslani: Eur J Appl Physiol 82 (2000) 250-254 equation was identified as the most accurate equation and should be used for Western populations 18-30 years of age. Care must be taken when deciding which equation to use when estimating WBSA.     

Body surface area of Africans: a study based on direct measurements of Nigerian males

Direct measurement of body surface area (Ab) was made on 20 male adult Nigerians of African descent by coating and planimetry. The results were compared with estimated Ab values obtained using six widely accepted height and weight prediction equations. The results show that existing formulas do not predict surface areas of our subjects accurately. Measured Ab values of our subjects were 6-22% greater than predicted values obtained from non-African nomograms. Using these results, we computed new variables for height and weight formulas that accurately predict the surface area of Africans. The closest fit to measured values is given by the equation Ab(m2) = 0.001315 x Height 1.2139 (cm) x weight 0.2620 (kg) +/- 0.04815 (SEE). The new variables are significantly different from those of existing equations. Our height variable is several times greater than the weight variable and reflects a greater importance of height than weight in determining the surface area of Africans than is the case with Caucasians.     

Formula and scale for body surface area estimation in high-risk infants

Advances in medical technology and the health sciences have lead to a rapid increase in the prevalence and morbidity of high-risk infants with chronic or permanent sequels such as the birth of early preterm infants. A suitable formula is therefore needed for body surface area (BSA) estimation for high-risk infants to more accurately devise therapeutic regimes in clinical practice. A cohort study involving 5014 high-risk infants was conducted to develop a suitable formula for estimating BSA using four of the existing formulas in the literature. BSA of high-risk infants was calculated using the four BSA equations (Boyd-BSA, Dubois-BSA, Meban-BSA, Mosteller-BSA), from which a new calculation, Mean-BSA, was arithmetically derived as a reference BSA measure. Multiple-regression was performed using nonlinear least squares curve fitting corresponding to the trend line and the new equation, Neo-BSA, developed using Excel and SPSS 17.0. The Neo-BSA equation was constructed as follows: Neo-BSA = 5.520 x W(0.5526) x L(0.300). With the assumption of the least square root relation between weight and length, a BSA scale using only weight was fabricated specifically for clinical applications where weight is more available in high-risk infant populations than is length. The validity of Neo-BSA was evaluated against Meban-BSA, the best of the four equations for high-risk infants, as there is a similarity of subjects in the two studies. The other formulas revealed substantial variances in BSA compared to Neo-BSA. This study developed a new surface area equation, Neo-BSA, as the most suitable formula for BSA measurement of high-risk infants in modern-day societies, where an emerging population of newborns with shorten gestational ages are becoming more prevalent as a result of new advances in the health sciences and new development of reproductive technologies. In particular, a scale for 400-7000 g body weight babies derived from the Neo-BSA equation has the clinical advantage of using only weight as a measurement, since length is often not feasible as a measurement due to the newborn's body posture. Further studies are required to confirm our findings for the application of Neo-BSA and the BSA scale (based on weight) for various populations and ethnicities under different clinical conditions.     

Analysis of body segment parameter differences between four human populations and the estimation errors of four popular mathematical models

Calculating the kinetics of motion using inverse or forward dynamics methods requires the use of accurate body segment inertial parameters. The methods available for calculating these body segment parameters (BSPs) have several limitations and a main concern is the applicability of predictive equations to several different populations. This study examined the differences in BSPs between 4 human populations using dual energy x-ray absorptiometry (DEXA), developed linear regression equations to predict mass, center of mass location (CM) and radius of gyration (K) in the frontal plane on 5 body segments and examined the errors produced by using several BSP sources in the literature. Significant population differences were seen in all segments for all populations and all BSPs except hand mass, indicating that population specific BSP predictors are needed. The linear regression equations developed performed best overall when compared to the other sources, yet no one set of predictors performed best for all segments, populations or BSPs. Large errors were seen with all models which were attributed to large individual differences within groups. Equations which account for these differences, including measurements of limb circumferences and breadths may provide better estimations. Geometric models use these parameters, however the models examined in this study did not perform well, possibly due to the assumption of constant density or the use of an overly simple shape. Creating solids which account for density changes or which mimic the mass distribution characteristics of the segment may solve this problem. Otherwise, regression equations specific for populations according to age, gender, race, and morphology may be required to provide accurate estimations of BSPs for use in kinetic equations of motion.     

Validation of tetrapolar bioelectrical impedance method to assess human body composition

This study was conducted to validate the relationship between bioelectrical conductance (ht2/R) and densitometrically determined fat-free mass, and to compare the prediction errors of body fatness derived from the tetrapolar impedance method and skinfold thicknesses, relative to hydrodensitometry. One-hundred and fourteen male and female subjects, aged 18-50 yr, with a wide range of fat-free mass (34-96 kg) and percent body fat (4-41%), participated. For males, densitometrically determined fat-free mass was correlated highly (r = 0.979), with fat-free mass predicted from tetrapolar conductance measures using an equation developed for males in a previous study. For females, the correlation between measured fat-free mass and values predicted from the combined (previous and present male data) equation for men also was strong (r = 0.954). The regression coefficients in the male and female regression equations were not significantly different. Relative to hydrodensitometry, the impedance method had a lower predictive error or standard error of the estimates of estimating body fatness than did a standard anthropometric technique (2.7 vs. 3.9%). Therefore this study establishes the validity and reliability of the tetrapolar impedance method for use in assessment of body composition in healthy humans.     

How accurately can we estimate energetic costs in a marine top predator,the king penguin?

King penguins (Aptenodytes patagonicus) are one of the greatest consumers of marine resources. However, while their influence on the marine ecosystem is likely to be significant, only an accurate knowledge of their energy demands will indicate their true food requirements. Energy consumption has been estimated for many marine species using the heart rate-rate of oxygen consumption (f(H) - V(O2)) technique, and the technique has been applied successfully to answer eco-physiological questions. However, previous studies on the energetics of king penguins, based on developing or applying this technique, have raised a number of issues about the degree of validity of the technique for this species. These include the predictive validity of the present f(H) - V(O2) equations across different seasons and individuals and during different modes of locomotion. In many cases, these issues also apply to other species for which the f(H) - V(O2) technique has been applied. In the present study, the accuracy of three prediction equations for king penguins was investigated based on validity studies and on estimates of V(O2) from published, field f(H) data. The major conclusions from the present study are: (1) in contrast to that for walking, the f(H) - V(O2) relationship for swimming king penguins is not affected by body mass; (2) prediction equation (1), log(V(O2) = -0.279 + 1.24log(f(H) + 0.0237t - 0.0157log(f(H)t, derived in a previous study, is the most suitable equation presently available for estimating V(O2) in king penguins for all locomotory and nutritional states. A number of possible problems associated with producing an f(H) - V(O2) relationship are discussed in the present study. Finally, a statistical method to include easy-to-measure morphometric characteristics, which may improve the accuracy of f(H) - V(O2) prediction equations, is explained.     

A morphometric study of the lungs of different sized bats: correlations between structure and function of the chiropteran lung.

1. The lungs of four species of bats, Phyllostomus hastatus (PH, mean body mass, 98 g), Pteropus lylei (PL, 456 g), Pteropus alecto (PA, 667 g), and Pteropus poliocephalus (PP, 928 g) were analysed by morphometric methods. These data increase fivefold the range of body masses for which bat lung data are available, and allow more representative allometric equations to be formulated for bats. 2. Lung volume ranged from 4.9 cm3 for PH to 39 cm3 for PP. The volume density of the lung parenchyma (i.e. the volume proportion of the parenchyma in the lung) ranged from 94% in PP to 89% in PH. Of the components of the parenchyma, the alveoli composed 89% and the blood capillaries about 5%. 3. The surface area of the alveoli exceeded that of the blood-gas (tissue) barrier and that of the capillary endothelium whereas the surface area of the red blood cells as well as that of the capillary endothelium was greater than that of the tissue barrier. PH had the thinnest tissue barrier (0.1204 microns) and PP had the thickest (0.3033 microns). 4. The body mass specific volume of the lung, that of the volume of pulmonary capillary blood, the surface area of the blood-gas (tissue) barrier, the diffusing capacity of the tissue barrier, and the total morphometric pulmonary diffusing capacity in PH all substantially exceeded the corresponding values of the pteropid species (i.e. PL, PA and PP). This conforms with the smaller body mass and hence higher unit mass oxygen consumption of PH, a feature reflected in the functionally superior gas exchange performance of its lungs. 5. Morphometrically, the lungs of different species of bats exhibit remarkable differences which cannot always be correlated with body mass, mode of flight and phylogeny. Conclusive explanations of these pulmonary structural disparities in different species of bats must await additional physiological and flight biomechanical studies. 6. While the slope, the scaling factor (b), of the allometric equation fitted to bat lung volume data (b = 0.82) exceeds the value for flight VO2max (b = 0.70), those for the surface area of the blood-gas (tissue) barrier (b = 0.74), the pulmonary capillary blood volume (b = 0.74), and the total morphometric lung diffusing capacity for oxygen (b = 0.69) all correspond closely to the VO2max value. 7. Allometric comparisons of the morphometric pulmonary parameters of bats, birds and non-flying mammals reveal that superiority of the bat lung over that of the non-flying mammal.(ABSTRACT TRUNCATED AT 400 WORDS)     

Body surface area prediction in normal-weight and obese patients

None of the equations frequently used to predict body surface area (BSA) has been validated for obese patients. We applied the principles of body size scaling to derive an improved equation predicting BSA solely from a patient's weight. Forty-five patients weighing from 51.3 to 248.6 kg had their height and weight measured on a calibrated scale and their BSA calculated by a geometric method. Data were combined with a large series of published BSA estimates. BSA prediction with the commonly used Du Bois equation underestimated BSA in obese patients by as much as 20%. The equation we derived to relate BSA to body weight was a power function: BSA (m(2)) = 0.1173 x Wt (kg)(0.6466). Below 10 kg, this equation deviated significantly from the BSA vs. body weight curve, necessitating a different set of coefficients: BSA (m(2)) = 0.1037 x Wt (kg)(0.6724). Covariance of height and weight for patients weighing <80 kg reduced the Du Bois BSA-predicting equation to a power function, explaining why it provides good BSA predictions for normal-size patients but fails with obesity.     

A Review of Methods for Measuring the Surface Area of Stream Substrates

Surface area measurement is a common component of benthic research, especially in the quantification of chlorophyll. Multiple techniques are available and 10 are described: artificial substrates, area-specific sampling, geometric approximation, stone shape equations, foil wrapping, grids, stamps, wetted layer, particle layer, and planar area measurement. A literature search of 130 papers indicated the most common methods: using artificial substrates of known area, subsampling a specific area using a template or sampler, measuring stone dimensions and using an equation to derive area, and using the weight of foil wrapped on stones. Methods were compared using spheres of known area, smooth and rough granite stones, and plastic macrophytes. Most methods produced highly correlated measurements and accurately estimated surface area. The wetted layer method was sensitive to stone roughness and plant complexity, but may overestimate the area of complex surfaces. Replication of one method by 10 biologists indicated that individual differences in technique can affect surface area values. Factors to consider in choosing an appropriate method include ease of use, characteristics of the substrates (e.g., porosity and flexibility), fineness of scale in measuring area, and whether methods must be field-based or can include laboratory techniques.     

Developmental causes of allometry: new models and implications for phenotypic plasticity and evolution

Shapes change during development because tissues, organs, and various anatomical features differ in onset, rate, and duration of growth. Allometry is the study of the consequences of differences in the growth of body parts on morphology, although the field of allometry has been surprisingly little concerned with understanding the causes of differential growth. The power-law equation y?=?ax(b), commonly used to describe allometries, is fundamentally an empirical equation whose biological foundation has been little studied. Huxley showed that the power-law equation can be derived if one assumes that body parts grow with exponential kinetics, for exactly the same amount of time. In life, however, the growth of body parts is almost always sigmoidal, and few, if any, grow for exactly the same amount of time during ontogeny. Here, we explore the shapes of allometries that result from real growth patterns and analyze them with new allometric equations derived from sigmoidal growth kinetics. We use an extensive ontogenetic dataset of the growth of internal organs in the rat from birth to adulthood, and show that they grow with Gompertz sigmoid kinetics. Gompertz growth parameters of body and internal organs accurately predict the shapes of their allometries, and that nonlinear regression on allometric data can accurately estimate the underlying kinetics of growth. We also use these data to discuss the developmental relationship between static and ontogenetic allometries. We show that small changes in growth kinetics can produce large and apparently qualitatively different allometries. Large evolutionary changes in allometry can be produced by small and simple changes in growth kinetics, and we show how understanding the development of traits can greatly simplify the interpretation of how they evolved.     

Respiratory surface areas of an air-breathing siluroid fish Saccobranchus (Heteropneustes) fossilis in relation to body size

The surface area of the gills, air sacs and skin have been measured in specimens of different body size and their relationship to body weight fits the equation: area= aW^b . The slopes ( b ) of the double logarithmic plots are 0.746 (gills), 0.662 (air sacs) and 0.684 (skin). The gills are poorly developed and their average weight specific area is less than figures obtained for sluggish marine fishes. The skin has an area about 70% of the total respiratory surfaces (gills+air sac+skin). Nevertheless the greater thickness of the skin leads to a smaller diffusing capacity of the tissue barrier ( D_t ) as compared with the gills and air sac. The air sac area for each ml of air that it contains is about 10.5 cm² which is much lower than figures obtained for lungs of other air-breathing fish and for tetrapods.     

Evaluation of surface colonization kinetics in continuous culture

Two equations, describing surface colonization, were evaluated and compared using suspended glass slides in a continuous culture ofPseudomonas aeruginosa. These equations were used to determine surface growth rates from the number and distribution of cells present on the surface after incubation. One of these was the colonization equation which accounts for simultaneous attachment and growth of bacteria on surfaces: $$N = (A/\mu )e^{\mu t} - A/\mu $$ where N=number of cells on surface (cells field^?1); A=attachment rate (cells field^?1h^?1);μ=specific growth rate (h^?1); t=incubation period (h). The other was the surface growth rate equation which assumes that the number of colonies of a given size (C_i) will reach a constant value (C_max) which is equal to A divided byμ: $$\mu = \frac{{\ln \left( {\frac{N}{{C_i }} + 1} \right)}}{t}$$ Both equations gave similar results and the time required to approximate C_max may not be as long as was previously thought. In all cases both A andμ continuously decreased throughout the incubation period. These decreases may be due to various effects of microbial accumulation on the surface. Both equations accurately determined surface growth rates despite highly variable attachment rates. Growth rates were similar for both the liquid phase of the culture and the solid-liquid interface (0.4 h^?1). Use of the surface growth rate equation is favored over the use of the colonization equation since the former does not require a computer to solve forμ and the counting procedure is simplified.     

Sensitivity of bioelectrical impedance to detect changes in human body composition

The purpose of this study was to compare the estimates of lean body mass (LBM) and percent body fat (%BF), as predicted by bioelectrical impedance (BIA) and sum of skinfolds (SF), with those derived by hydrostatic weighing (HW) obtained before and after a 10-wk diet and exercise regimen. The experimental (E) group consisted of 17 healthy male subjects; 20 healthy males served as the control (C) group. Post hoc Scheffé contrasts computed on E group data indicated that, for both LBM and %BF, the Lukaski and Segal BIA equations, as well as the Durnin SF equation, derived mean values that were not significantly different (0.05 significance level) from HW in both pre- and postregimen conditions. For LBM, the same equations derived the following significant (P less than 0.01) correlation coefficients for both pre- and postregimen data: Lukaski, 0.87 and 0.85; Segal, 0.89 and 0.87; and Durnin, 0.90 and 0.88. For %BF, the correlation coefficients were slightly lower but remained statistically significant (P less than 0.01). The findings of this study suggest that the BIA method, by use of either the Lukaski or Segal prediction equations, is a valid means of predicting changes in human body composition as measured by the Siri transformation of body density.     

A simple function for maternal-age-specific rates of Down syndrome in the 20-to-49-year age range and its biological implications.

The familial increase in the rate of Down syndrome with maternal age can be represented by a simple equation, consisting of the sum of a constant term plus an exponential term that is a first-order function of masternal age: y = a + exp (b + cx), where y is the rate in live births, x is maternal age, and a, b, and c are constants. Unlikely analyses in which two separate equations were derived from different segments of the 20 to 49 maternal age range, this single, simple equation can be applied to the entire range. An unlike previous complex equations that were derived by regression analysis for the entire age range, the component terms can be readily understood as contributions by different etiologic categories. This model fits the data recently available by 1-year intervals about as well as the approach that used separate equations, but it has fewer parameters and requires no ad hoc division of the age range. However, it does not postulate a sharp transition in biological processes around maternal age 30, but, rather, a process continuously accumulating at a constant exponential rate (analogous to that produced by an infectious mechanism), superimposed upon a constant background rate.     

Modelling inert gas exchange in tissue and mixed-venous blood return to the lungs

Inert gas exchange in tissue has been almost exclusively modelled by using an ordinary differential equation. The mathematical model that is used to derive this ordinary differential equation assumes that the partial pressure of an inert gas (which is proportional to the content of that gas) is a function only of time. This mathematical model does not allow for spatial variations in inert gas partial pressure. This model is also dependent only on the ratio of blood flow to tissue volume, and so does not take account of the shape of the body compartment or of the density of the capillaries that supply blood to this tissue. The partial pressure of a given inert gas in mixed-venous blood flowing back to the lungs is calculated from this ordinary differential equation. In this study, we write down the partial differential equations that allow for spatial as well as temporal variations in inert gas partial pressure in tissue. We then solve these partial differential equations and compare them to the solution of the ordinary differential equations described above. It is found that the solution of the ordinary differential equation is very different from the solution of the partial differential equation, and so the ordinary differential equation should not be used if an accurate calculation of inert gas transport to tissue is required. Further, the solution of the PDE is dependent on the shape of the body compartment and on the density of the capillaries that supply blood to this tissue. As a result, techniques that are based on the ordinary differential equation to calculate the mixed-venous blood partial pressure may be in error.     

Evaluation of a method for determining the length of sperm whales (Physeter catodon) from their vocalizations

The click vocalizations of sperm whales often contain several regularly-spaced, discrete pulses of sound. Norris & Harvey (1972) hypothesized that these were caused as a single pulse of sound produced at the front of the whale's head bounced between reflective air sacs at either end of the spermaceti organ. Thus the interval between pulses will be twice the travel time for sound along the length of the spermaceti organ. It should therefore be possible to determine spermaceti organ length and thence total body length by measuring the interval between these pulses. Several workers have used an equation relating inter-pulse interval (IPI) to body length to estimate sperm whale body lengths acoustically.
In this paper, aspects of this technique are examined in some detail. In particular, variability in IPIs and trends in IPI with time and depth are investigated. Most importantly, for the first time IPIs in the vocalizations of whales of known lengths have been measured.
Variability in IPIs in the clicks of a single whale is acceptably low though there is a tendency for low and high values to occur in runs. There is no clear trend for IPI to alter significantly with the whale's depth or with the time since leaving the surface.
IPIs are positively correlated with body length though not as predicted by the equations used by previous workers. Some likely errors in these equations are discussed. A new empirically derived relationship between IPI and body length has been calculated, though more data are desirable to obtain a more accurate and reliable equation.     

A comparative investigation of certain difference equations and related differential equations: Implications for model-building

Many mathematical models for physical and biological problems have been and will be built in the form of differential equations or systems of such equations. With the advent of digital computers one has been able to find (approximate) solutions for equations that used to be intractable. Many of the mathematical techniques used in this area amount to replacing the given differential equations by appropriate difference equations, so that extensive research has been done into how to choose appropriate difference equations whose solutions are “good” approximations to the solutions of the given differential equations. The present paper investigates a different, although related problem. For many physical and biological phenomena the “continuum” type of thinking, that is at the basis of any differential equation, is not natural to the phenomenon, but rather constitutes an approximation to a basically discrete situation: in much work of this type the “infinitesimal step lengths” handled in the reasoning which leads up to the differential equation, are not really thought of as infinitesimally small, but as finite; yet, in the last stage of such reasoning, where the differential equation rises from the differentials, these “infinitesimal” step lengths are allowed to go to zero: that is where the above-mentioned approximation comes in. Under this kind of circumstances, it seems more natural tobuild themodel as adiscrete difference equation (recurrence relation) from the start, without going through the painful, doubly approximative process of first, during the modeling stage, finding a differential equation to approximate a basically discrete situation, and then, for numerical computing purposes, approximating that differential equation by a difference scheme. The paper pursues this idea for some simple examples, where the old differential equation, though approximative in principle, had been at least qualitatively successful in describing certain phenomena, and shows that this idea, though plausible and sound in itself, does encounter some difficulties. The reason is that each differential equation, as it is set up in the way familiar to theoretical physicists and biologists, does correspond to a plethora of discrete difference equations, all of which in the limit (as step length→0) yield the same differential equation, but whose solutions, for not too small step length, are often widely different, some of them being quite irregular. The disturbing thing is that all these difference equations seem to adequately represent the same (physical or biological) reasoning as the differential equation in question. So, in order to choose the “right” difference equation, one may need to draw upon more detailed (physical or) biological considerations. All this does not say that one should not prefer discrete models for phenomena that seem to call for them; but only that their pursuit may require additional (physical or) biological refinement and insight. The paper also investigates some mathematical problems related to the fact of many difference equations being associated with one differential equation.     

Allometric changes during growth and reproduction in Eleutheria dichotoma (hydrozoa,athecata) and the problem of estimating body size in a microscopic animal

Changes in body morphology during growth and reproduction in the hydromedusa Eleutheria dichotoma are described in terms of variations in eight different characters: umbrella diameter, total surface area, tentacle area, umbrella area, tentacle knob diameter, number of embryos, and diameter and area of buds. Sexually (sex) and vegetatively (veg) reproducing medusae differ significantly in their body morphometrics. Statistically significant allometric relations exist between umbrella diameter and (1) central area (sex and veg); (2) tentacle area (veg); (3) total area (veg); (4) tentacle knob diameter (veg); (5) bud diameter; and (6) number of embryos. A significant correlation between umbrella diameter and area is also found in undetached buds. During sexual reproduction, umbrella area shows positive allometry and loses its correlations to total area, tentacle area, and tentacle knob diameter. Linear and nonlinear bivariate allometric coefficients allow estimation of total body size from only one or two easily measurable attributes, e.g., umbrella and tentacle knob diameter. Curve fitting by the classic allometric equation (y = bx^c) is only negligibly worse than that obtained with a “full” equation (y = a + ^c), and statistical confidence is better. Chemical analyses for carbon and nitrogen content allow estimation of biomass from the projection area of the body surface. The relation factors are 1.06 μgC mm^?2 (sex) and 1.14 μgC mm^?2 (veg) for carbon and 0.293 μgN mm^?2 (sex) and 0.287 μgN mm^?2 (veg) for nitrogen. The C:N ratios are 3.6 and 4.0 for sexual and vegetative medusae, respectively. The use of allometric regression formulas to calculate surface areas and to relate these to carbon content provides quick estimations of body size in a microscopic animal.