Allometry, Antilog Transformations, and the Perils of Prediction on the Original Scale

Site-specific length-biomass relationships of arctic arthropod families are critical for accurate ecological inferences

Arthropods play a crucial role in terrestrial ecosystems, for instance in mediating energy fluxes and in forming the food base for many organisms. To better understand their functional role in such ecosystem processes, monitoring of trends in arthropod biomass is essential. Obtaining direct measurements of the body mass of individual specimens is laborious. Therefore, these data are often indirectly acquired by utilizing allometric length-biomass relationships based on a correlative parameter, such as body length. Previous studies have often used such relationships with a low taxonomic resolution and/or small sample size and/or adopted regressions calibrated in different biomes. Despite the scientific interest in the ecology of arctic arthropods, no site-specific family-level length-biomass relationships have hitherto been published. Here we present 27 family-specific length-biomass relationships from two sites in the High Arctic: Zackenberg in northeast Greenland and Knipovich in north Taimyr, Russia. We show that length-biomass regressions from different sites within the same biome did not affect estimates of phenology but did result in substantially different estimates of arthropod biomass. Estimates of daily biomass at Zackenberg were on average 24% higher when calculated using regressions for Knipovich compared to using regressions for Zackenberg. In addition, calculations of daily arthropod biomass at Zackenberg based on order-level regressions from frequently cited studies in literature revealed overestimations of arthropod biomass ranging from 69.7% to 130% compared to estimates based on regressions for Zackenberg. Our results illustrate that the use of allometric relationships from different sites can significantly alter the biological interpretation of, for instance, the interaction between insectivorous birds and their arthropod prey. We conclude that length-biomass relationships should be locally established rather than being based on global relationships.

A Revision of the Traditional Analysis Method of Allometry to Allow Extension of the Normality-Borne Complexity of Error Structure: Examining the Adequacy of a Normal-Mixture Distribution-Driven Error Term

Huxley’s model of simple allometry provides a parsimonious scheme for examining scaling relationships in scientific research, resource management, and species conservation endeavors. Factors including biological error, analysis method, sample size, and overall data quality can undermine the reliability of a fit of Huxley’s model. Customary amendments enhance the complexity of the power function-conveyed systematic term while keeping the usual normality-borne error structure. The resulting protocols bear multiple-parameter complex allometry forms that could pose interpretative shortcomings and parameter estimation difficulties, and even being empirically pertinent, they could potentially bear overfitting. A subsequent heavy-tailed Q-Q normal spread often remains undetected since the adequacy of a normally distributed error term remains unexplored. Previously, we promoted the advantages of keeping Huxley’s model-driven systematic part while switching to a logistically distributed error term to improve fit quality. Here, we analyzed eelgrass leaf biomass and area data exhibiting a marked size-related heterogeneity, perhaps explaining a lack of systematization at data gathering. Overdispersion precluded adequacy of the logistically adapted protocol, thereby suggesting processing data through a median absolute deviation scheme aimed to remove unduly replicates. Nevertheless, achieving regularity to Huxley’s power function-like trend required the removal of many replicates, thereby questioning the integrity of a data cleaning approach. But, we managed to adapt the complexity of the error term to reliably identify Huxley’s model-like systematic part masked by variability in data. Achieving this relied on an error term conforming to a normal mixture distribution which successfully managed overdispersion in data. Compared to normal-complex allometry and data cleaning composites present arrangement delivered a coherent Q-Q normal mixture spread and a remarkable reproducibility strength of derived proxies. By keeping the analysis within Huxley’s original theory, the present approach enables substantiating nondestructive allometric proxies aimed at eelgrass conservation. The viewpoint endorsed here could also make data cleaning unnecessary.

Biological scaling analyses are more than statistical line fitting

The magnitude of many biological traits relates strongly and regularly to body size. Consequently, a major goal of comparative biology is to understand and apply these 'size-scaling' relationships, traditionally quantified by using linear regression analyses based on log-transformed data. However, recently some investigators have questioned this traditional method, arguing that linear or non-linear regression based on untransformed arithmetic data may provide better statistical fits than log-linear analyses. Furthermore, they advocate the replacement of the traditional method by alternative specific methods on a case-by-case basis, based simply on best-fit criteria. Here, I argue that the use of logarithms in scaling analyses presents multiple valuable advantages, both statistical and conceptual. Most importantly, log-transformation allows biologically meaningful, properly scaled (scale-independent) comparisons of organisms of different size, whereas non-scaled (scale-dependent) analyses based on untransformed arithmetic data do not. Additionally, log-based analyses can readily reveal biologically and theoretically relevant discontinuities in scale invariance during developmental or evolutionary increases in body size that are not shown by linear or non-linear arithmetic analyses. In this way, log-transformation advances our understanding of biological scaling conceptually, not just statistically. I hope that my Commentary helps students, non-specialists and other interested readers to understand the general benefits of using log-transformed data in size-scaling analyses, and stimulates advocates of arithmetic analyses to show how they may improve our understanding of scaling conceptually, not just statistically.

Allometric growth in mass by the brain of mammals

I re-examined published data for ontogenetic change in relative mass of the brain in six species of mammal (i.e., sheep, pig, cow, horse, rat, cat) to illustrate an insidious problem with conventional analyses of brain-body allometry. Graphical displays of logarithmic transformations of the original data for each species give the appearance of two discrete mathematical distributions, but untransformed observations nonetheless conform to a single distribution that is well described by a single, nonlinear equation. The concept of biphasic, allometric growth by the brain consequently is an artifact of transformation. The notion of Rapid and Slow phases in relative growth by the brain also is an artifact, because the notion is based explicitly on the concept of biphasic growth allometry. Relative growth by the brain in sheep, pigs, cows, and horses follows the path of a power curve with an exponent less than 1, so relative growth declines progressively as animals grow to their maximum size, at which point growth effectively ends for both brain and body. Relative growth by the brain in rats and cats follows the path of an exponential curve and consequently is more like relative growth by the brain of odontocoete cetaceans and primates, with the brain growing rapidly relative to the body early in ontogeny and attaining maximum (cats) or near-maximum (rats) mass well before the body reaches its maximum. An exponential pattern of relative growth by the brain appears to have evolved independently in rodents, carnivores, odontocoetes, and primates.

Modeling allometric variation: lessons from the metabolic allometry of black carp (Mylopharyngodon piceus)

I used linear and nonlinear regression to re-examine published data on the scaling of metabolic rate vs. body mass in an ontogenetic series of black carp (Mylopharyngodon piceus (Richardson, 1846)). My objective was to expose shortcomings of the conventional procedure for fitting statistical models to bivariate observations (i.e., the procedure that is widely attributed to J.S. Huxley) and simultaneously to outline a more general and utilitarian protocol for analyzing bivariate data in studies of allometry. Authors of the original study on carp reported exponents of 0.83 and 0.78 for two-parameter power functions fitted to observations for resting metabolism and maximum metabolism, respectively. However, metabolic scaling in these fishes actually is described best by straight lines having positive intercepts with the Y axis. The allometric exponent is 1 for a straight line, so interpretations from the current analyses differ substantially from those reached in the original investigation. Contemporary theories for the evolution of optimal body size (e.g., the Metabolic Theory of Ecology) are based on patterns of metabolic allometry that have been estimated by the conventional analytical method. Thus, the current investigation raises questions about generally accepted patterns of metabolic allometry and theoretical models based upon them.

The fallacy of biphasic growth allometry for the vertebrate brain

The concept of biphasic, loglinear growth of the vertebrate brain is based on graphical displays of logarithmic transformations of the original measurements. Such displays commonly give the appearance of two distinct mathematical distributions – one set of observations following a steep trajectory at the low end of the size range and another set following a shallow trajectory at the high end. However, the appearance of two distributions is an artefact resulting from the logarithmic transformations. Observations of brain mass vs. body mass in each of the eight vertebrate species examined in the current investigation conform to a single mathematical distribution that is well described by a single equation fitted to the original, untransformed data by non-linear regression. Data for carp, chickens, kangaroos and rabbits are described by three-parameter power equations whereas those for dolphins and primates are described by exponential functions that rise rapidly to a maximum. The brain continues to grow throughout life in carp, chickens, kangaroos and rabbits but not in dolphins and primates. Future investigations of relative growth of the brain should be based on graphical and analytical study of observations expressed on the native mathematical scale.

Effective Network Size Predicted From Simulations of Pathogen Outbreaks Through Social Networks Provides a Novel Measure of Structure-Standardized Group Size

The transmission of infectious disease through a population is often modeled assuming that interactions occur randomly in groups, with all individuals potentially interacting with all other individuals at an equal rate. However, it is well known that pairs of individuals vary in their degree of contact. Here, we propose a measure to account for such heterogeneity: effective network size (ENS), which refers to the size of a maximally complete network (i.e., unstructured, where all individuals interact with all others equally) that corresponds to the outbreak characteristics of a given heterogeneous, structured network. We simulated susceptible-infected (SI) and susceptible-infected-recovered (SIR) models on maximally complete networks to produce idealized outbreak duration distributions for a disease on a network of a given size. We also simulated the transmission of these same diseases on random structured networks and then used the resulting outbreak duration distributions to predict the ENS for the group or population. We provide the methods to reproduce these analyses in a public R package, "enss." Outbreak durations of simulations on randomly structured networks were more variable than those on complete networks, but tended to have similar mean durations of disease spread. We then applied our novel metric to empirical primate networks taken from the literature and compared the information represented by our ENSs to that by other established social network metrics. In AICc model comparison frameworks, group size and mean distance proved to be the metrics most consistently associated with ENS for SI simulations, while group size, centralization, and modularity were most consistently associated with ENS for SIR simulations. In all cases, ENS was shown to be associated with at least two other independent metrics, supporting its use as a novel metric. Overall, our study provides a proof of concept for simulation-based approaches toward constructing metrics of ENS, while also revealing the conditions under which this approach is most promising.

Selection and constraints on offspring size-number trade-offs in sand lizards (Lacerta agilis)

The trade-off between offspring size and number is a central component of life-history theory, postulating that larger investment into offspring size inevitably decreases offspring number. This trade-off is generally discussed in terms of genetic, physiological or morphological constraints; however, as among-individual differences can mask individual trade-offs, the underlying mechanisms may be difficult to reveal. In this study, we use multivariate analyses to investigate whether there is a trade-off between offspring size and number in a population of sand lizards by separating among- and within-individual patterns using a 15-year data set collected in the wild. We also explore the ecological and evolutionary causes and consequences of this trade-off by investigating how a female's resource (condition)- vs. age-related size (snout-vent length) influences her investment into offspring size vs. number (OSN), whether these traits are heritable and under selection and whether the OSN trade-off has a genetic component. We found a negative correlation between offspring size and number within individual females and physical constraints (size of body cavity) appear to limit the number of eggs that a female can produce. This suggests that the OSN trade-off occurs due to resource constraints as a female continues to grow throughout life and, thus, produces larger clutches. In contrast to the assumptions of classic OSN theory, we did not detect selection on offspring size; however, there was directional selection for larger clutch sizes. The repeatabilities of both offspring size and number were low and we did not detect any additive genetic variance in either trait. This could be due to strong selection (past or current) on these life-history traits, or to insufficient statistical power to detect significant additive genetic effects. Overall, the findings of this study are an important illustration of how analyses of within-individual patterns can reveal trade-offs and their underlying causes, with potential evolutionary and ecological consequences that are otherwise hidden by among-individual variation.

Differences in physiological traits associated with water balance among rodents, and their relationship to tolerance of habitat fragmentation

Physiological concepts and tools can help us to understand why organisms and populations respond to habitat fragmentation in the way they do, and allow us to determine the mechanisms or individual characteristics underlying this differential sensitivity. Here, we examine food intake, relative medullary thickness and distribution/expression of water channel aquaporin-1 in three species of South American rodents that have been reported to have different levels of tolerance to habitat fragmentation (Akodon montensis, Oligoryzomys nigripes, and Euryoryzomys russatus), using a classic water deprivation experiment to assess their abilities to cope with water shortage. We believe the mechanisms underlying this differential sensitivity are related to the organisms' capacities to maintain water balance, and therefore the species more tolerant to habitat fragmentation (A. montensis and O. nigripes) should have a higher capacity to maintain water balance. We found that A. montensis and O. nigripes were more tolerant to water deprivation than E. russatus, and this difference appears to be unrelated to differences in food ingestion rate. O. nigripes showed the highest values for RMT, followed by A. montensis and E. russatus. However all species showed RMT values that were 2.2% to 14.1% below the lower prediction limit when compared to other rodents through allometric relationships. Water deprivation seems to trigger changes in the distribution of aquaporin-1, mostly for O. nigripes and E. russatus, which may contribute to water balance maintenance. Our data suggest that these intrinsic physiological differences among these species could provide a mechanism for their differential tolerance of habitat fragmentation. J. Exp. Zool. 323A: 731-744, 2015. © 2015 Wiley Periodicals, Inc.

Body mass estimates of hominin fossils and the evolution of human body size

Body size directly influences an animal's place in the natural world, including its energy requirements, home range size, relative brain size, locomotion, diet, life history, and behavior. Thus, an understanding of the biology of extinct organisms, including species in our own lineage, requires accurate estimates of body size. Since the last major review of hominin body size based on postcranial morphology over 20 years ago, new fossils have been discovered, species attributions have been clarified, and methods improved. Here, we present the most comprehensive and thoroughly vetted set of individual fossil hominin body mass predictions to date, and estimation equations based on a large (n = 220) sample of modern humans of known body masses. We also present species averages based exclusively on fossils with reliable taxonomic attributions, estimates of species averages by sex, and a metric for levels of sexual dimorphism. Finally, we identify individual traits that appear to be the most reliable for mass estimation for each fossil species, for use when only one measurement is available for a fossil. Our results show that many early hominins were generally smaller-bodied than previously thought, an outcome likely due to larger estimates in previous studies resulting from the use of large-bodied modern human reference samples. Current evidence indicates that modern human-like large size first appeared by at least 3-3.5 Ma in some Australopithecus afarensis individuals. Our results challenge an evolutionary model arguing that body size increased from Australopithecus to early Homo. Instead, we show that there is no reliable evidence that the body size of non-erectus early Homo differed from that of australopiths, and confirm that Homo erectus evolved larger average body size than earlier hominins.

Metabolic scaling in animals: methods, empirical results, and theoretical explanations

Life on earth spans a size range of around 21 orders of magnitude across species and can span a range of more than 6 orders of magnitude within species of animal. The effect of size on physiology is, therefore, enormous and is typically expressed by how physiological phenomena scale with mass(b). When b ≠ 1 a trait does not vary in direct proportion to mass and is said to scale allometrically. The study of allometric scaling goes back to at least the time of Galileo Galilei, and published scaling relationships are now available for hundreds of traits. Here, the methods of scaling analysis are reviewed, using examples for a range of traits with an emphasis on those related to metabolism in animals. Where necessary, new relationships have been generated from published data using modern phylogenetically informed techniques. During recent decades one of the most controversial scaling relationships has been that between metabolic rate and body mass and a number of explanations have been proposed for the scaling of this trait. Examples of these mechanistic explanations for metabolic scaling are reviewed, and suggestions made for comparing between them. Finally, the conceptual links between metabolic scaling and ecological patterns are examined, emphasizing the distinction between (1) the hypothesis that size- and temperature-dependent variation among species and individuals in metabolic rate influences ecological processes at levels of organization from individuals to the biosphere and (2) mechanistic explanations for metabolic rate that may explain the size- and temperature-dependence of this trait.

Mathematical model for the contribution of individual organs to non-zero y-intercepts in single and multi-compartment linear models of whole-body energy expenditure

Mathematical models for the dependence of energy expenditure (EE) on body mass and composition are essential tools in metabolic phenotyping. EE scales over broad ranges of body mass as a non-linear allometric function. When considered within restricted ranges of body mass, however, allometric EE curves exhibit ‘local linearity.’ Indeed, modern EE analysis makes extensive use of linear models. Such models typically involve one or two body mass compartments (e.g., fat free mass and fat mass). Importantly, linear EE models typically involve a non-zero (usually positive) y-intercept term of uncertain origin, a recurring theme in discussions of EE analysis and a source of confounding in traditional ratio-based EE normalization. Emerging linear model approaches quantify whole-body resting EE (REE) in terms of individual organ masses (e.g., liver, kidneys, heart, brain). Proponents of individual organ REE modeling hypothesize that multi-organ linear models may eliminate non-zero y-intercepts. This could have advantages in adjusting REE for body mass and composition. Studies reveal that individual organ REE is an allometric function of total body mass. I exploit first-order Taylor linearization of individual organ REEs to model the manner in which individual organs contribute to whole-body REE and to the non-zero y-intercept in linear REE models. The model predicts that REE analysis at the individual organ-tissue level will not eliminate intercept terms. I demonstrate that the parameters of a linear EE equation can be transformed into the parameters of the underlying ‘latent’ allometric equation. This permits estimates of the allometric scaling of EE in a diverse variety of physiological states that are not represented in the allometric EE literature but are well represented by published linear EE analyses.

Evaporative water loss, relative water economy and evaporative partitioning of a heterothermic marsupial, the monito del monte (Dromiciops gliroides)

We examine here evaporative water loss, economy and partitioning at ambient temperatures from 14 to 33°C for the monito del monte (Dromiciops gliroides), a microbiotheriid marsupial found only in temperate rainforests of Chile. The monito's standard evaporative water loss (2.58 mg g(-1) h(-1) at 30°C) was typical for a marsupial of its body mass and phylogenetic position. Evaporative water loss was independent of air temperature below thermoneutrality, but enhanced evaporative water loss and hyperthermia were the primary thermal responses above the thermoneutral zone. Non-invasive partitioning of total evaporative water loss indicated that respiratory loss accounted for 59-77% of the total, with no change in respiratory loss with ambient temperature, but a small change in cutaneous loss below thermoneutrality and an increase in cutaneous loss in and above thermoneutrality. Relative water economy (metabolic water production/evaporative water loss) increased at low ambient temperatures, with a point of relative water economy of 15.4°C. Thermolability had little effect on relative water economy, but conferred substantial energy savings at low ambient temperatures. Torpor reduced total evaporative water loss to as little as 21% of normothermic values, but relative water economy during torpor was poor even at low ambient temperatures because of the relatively greater reduction in metabolic water production than in evaporative water loss. The poor water economy of the monito during torpor suggests that negative water balance may explain why hibernators periodically arouse to normothermia, to obtain water by drinking or via an improved water economy.

Estimating litter decomposition rate in single-pool models using nonlinear beta regression

Litter decomposition rate (k) is typically estimated from proportional litter mass loss data using models that assume constant, normally distributed errors. However, such data often show non-normal errors with reduced variance near bounds (0 or 1), potentially leading to biased k estimates. We compared the performance of nonlinear regression using the beta distribution, which is well-suited to bounded data and this type of heteroscedasticity, to standard nonlinear regression (normal errors) on simulated and real litter decomposition data. Although the beta model often provided better fits to the simulated data (based on the corrected Akaike Information Criterion, AIC_c), standard nonlinear regression was robust to violation of homoscedasticity and gave equally or more accurate k estimates as nonlinear beta regression. Our simulation results also suggest that k estimates will be most accurate when study length captures mid to late stage decomposition (50–80% mass loss) and the number of measurements through time is ≥5. Regression method and data transformation choices had the smallest impact on k estimates during mid and late stage decomposition. Estimates of k were more variable among methods and generally less accurate during early and end stage decomposition. With real data, neither model was predominately best; in most cases the models were indistinguishable based on AIC_c, and gave similar k estimates. However, when decomposition rates were high, normal and beta model k estimates often diverged substantially. Therefore, we recommend a pragmatic approach where both models are compared and the best is selected for a given data set. Alternatively, both models may be used via model averaging to develop weighted parameter estimates. We provide code to perform nonlinear beta regression with freely available software.

Comparative thermoregulatory physiology of two dunnarts, Sminthopsis macroura and Sminthopsis ooldea (Marsupialia : Dasyuridae)

Metabolic rate and evaporative water loss (EWL) were measured to quantify the thermoregulatory patterns of two dasyurids, the stripe-faced dunnart (Sminthopsis macroura) and the Ooldea dunnart (S. ooldea) during acute exposure to Ta between 10 and 35°C. S. macroura maintained consistent Tb across the Ta range, whereas S. ooldea was more thermolabile. The metabolic rate of both species decreased from Ta = 10°C to BMR at Ta = 30°C. Mass-adjusted BMR at Ta = 30°C was the same for the two species, but there was no common regression of metabolic rate below the thermoneutral zone (TNZ). There was no significant difference between the species in allometrically corrected EWL at Ta = 30°C. Total EWL increased significantly at Ta = 10 and 35°C compared with the TNZ for S. macroura, but was consistent across the Ta range for S. ooldea. At any Ta below the TNZ, S. macroura required more energy per gram of body mass than S. ooldea, and had a higher EWL at the lower critical Ta. By being thermolabile S. ooldea reduced its energetic requirements and water loss at low Ta. The more constant thermoregulatory strategy of S. macroura may allow it to exploit a broad climatic envelope, albeit at the cost of higher energetic and water requirements. Since S. ooldea does not expend as much energy and water on thermoregulation this may be a response to the very low productivity, ‘hyperarid’ conditions of its central Australian distribution.

On the use of log-transformation vs. nonlinear regression for analyzing biological power laws

Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.

Energy and water use by invasive goats (Capra hircus) in an Australian rangeland, and a caution against using broad-scale allometry to predict species-specific requirements

Feral goats (Capra hircus) are ubiquitous across much of Australia's arid and semi-arid rangelands, where they compete with domestic stock, contribute to grazing pressure on fragile ecosystems, and have been implicated in the decline of several native marsupial herbivores. Understanding the success of feral goats in Australia may provide insights into management strategies for this and other invasive herbivores. It has been suggested that frugal use of energy and water contributes to the success of feral goats in Australia, but data on the energy and water use of free-ranging animals are lacking. We measured the field metabolic rate and water turnover rate of pregnant and non-pregnant feral goats in an Australian rangeland during late summer (dry season). Field metabolic rate of pregnant goats (601 ± 37 kJ kg(-0.73)d(-1)) was 1.3 times that of non-pregnant goats (456 ± 24 kJ kg(-0.73)d(-1)). The water turnover rate of pregnant goats (228 ± 18 mL kg(-0.79)d(-1)) was also 1.3 times that of non-pregnant goats (173 ± 18 kg(-0.79)d(-1)), but the difference was not significant (P=0.07). There was no significant difference in estimated dry matter digestibility between pregnant and non-pregnant goats (mean ca. 58%), blood or urine osmolality, or urine electrolyte concentrations, indicating they were probably eating similar diets and were able to maintain osmohomeostasis. Overall, the metabolic and hygric physiology of non-pregnant goats conformed statistically to the predictions for non-marine, non-reproductive placental mammals according to both conventional and phylogenetically independent analyses. That was despite the field metabolic rate and estimated dry matter intake of non-pregnant goats being only 60% of the predicted level. We suggest that general allometric analyses predict the range of adaptive possibilities for mammals, but that specific adaptations, as present in goats, result in ecologically significant departures from the average allometric curve. In the case of goats in the arid Australian rangelands, predictions from the allometric regression would overestimate their grazing pressure by about 40% with implications for the predicted impact on their local ecology.

Phylogenetic rate shifts in feeding time during the evolution of Homo

Unique among animals, humans eat a diet rich in cooked and nonthermally processed food. The ancestors of modern humans who invented food processing (including cooking) gained critical advantages in survival and fitness through increased caloric intake. However, the time and manner in which food processing became biologically significant are uncertain. Here, we assess the inferred evolutionary consequences of food processing in the human lineage by applying a Bayesian phylogenetic outlier test to a comparative dataset of feeding time in humans and nonhuman primates. We find that modern humans spend an order of magnitude less time feeding than predicted by phylogeny and body mass (4.7% vs. predicted 48% of daily activity). This result suggests that a substantial evolutionary rate change in feeding time occurred along the human branch after the human-chimpanzee split. Along this same branch, Homo erectus shows a marked reduction in molar size that is followed by a gradual, although erratic, decline in H. sapiens. We show that reduction in molar size in early Homo (H. habilis and H. rudolfensis) is explicable by phylogeny and body size alone. By contrast, the change in molar size to H. erectus, H. neanderthalensis, and H. sapiens cannot be explained by the rate of craniodental and body size evolution. Together, our results indicate that the behaviorally driven adaptations of food processing (reduced feeding time and molar size) originated after the evolution of Homo but before or concurrent with the evolution of H. erectus, which was around 1.9 Mya.

Phenotypic plasticity of gas exchange pattern and water loss in Scarabaeus spretus (Coleoptera: Scarabaeidae): deconstructing the basis for metabolic rate variation

Investigation of gas exchange patterns and modulation of metabolism provide insight into metabolic control systems and evolution in diverse terrestrial environments. Variation in metabolic rate in response to environmental conditions has been explained largely in the context of two contrasting hypotheses, namely metabolic depression in response to stressful or resource-(e.g. water) limited conditions, or elevation of metabolism at low temperatures to sustain life in extreme conditions. To deconstruct the basis for metabolic rate changes in response to temperature variation, here we undertake a full factorial study investigating the longer- and short-term effects of temperature exposure on gas exchange patterns. We examined responses of traits of gas exchange [standard metabolic rate (SMR); discontinuous gas exchange (DGE) cycle frequency; cuticular, respiratory and total water loss rate (WLR)] to elucidate the magnitude and form of plastic responses in the dung beetle, Scarabaeus spretus. Results showed that short- and longer-term temperature variation generally have significant effects on SMR and WLR. Overall, acclimation to increased temperature led to a decline in SMR (from 0.071±0.004 ml CO2 h–1 in 15°C-acclimated beetles to 0.039±0.004 ml CO2 h–1 in 25°C-acclimated beetles measured at 20°C) modulated by reduced DGE frequency (15°C acclimation: 0.554±0.027 mHz, 20°C acclimation: 0.257±0.030 mHz, 25°C acclimation: 0.208±0.027 mHz recorded at 20°C), reduced cuticular WLRs (from 1.058±0.537 mg h–1 in 15°C-acclimated beetles to 0.900±0.400 mg h–1 in 25°C-acclimated beetles measured at 20°C) and reduced total WLR (from 4.2±0.5 mg h–1 in 15°C-acclimated beetles to 3.1±0.5 mg h–1 in 25°C-acclimated beetles measured at 25°C). Respiratory WLR was reduced from 2.25±0.40 mg h–1 in 15°C-acclimated beetles to 1.60±0.40 mg h–1 in 25°C-acclimated beetles measured at 25°C, suggesting conservation of water during DGE bursts. Overall, this suggests water conservation is a priority for S. spretus exposed to longer-term temperature variation, rather than elevation of SMR in response to low temperature acclimation, as might be expected from a beetle living in a relatively warm, low rainfall summer region. These results are significant for understanding the evolution of gas exchange patterns and trade-offs between metabolic rate and water balance in insects and other terrestrial arthropods.

Comparative physiology of Australian quolls (Dasyurus; Marsupialia)

Quolls (Dasyurus) are medium-sized carnivorous dasyurid marsupials. Tiger (3,840 g) and eastern quolls (780 g) are mesic zone species, northern quolls (516 g) are tropical zone, and chuditch (1,385 g) were once widespread through the Australian arid zone. We found that standard physiological variables of these quolls are consistent with allometric expectations for marsupials. Nevertheless, inter-specific patterns amongst the quolls are consistent with their different environments. The lower T (b) of northern quolls (34 degrees C) may provide scope for adaptive hyperthermia in the tropics, and they use torpor for energy/water conservation, whereas the larger mesic species (eastern and tiger quolls) do not appear to. Thermolability varied from little in eastern (0.035 degrees C degrees C(-1)) and tiger quolls (0.051 degrees C degrees C(-1)) to substantial in northern quolls (0.100 degrees C degrees C(-1)) and chuditch (0.146 degrees C degrees C(-1)), reflecting body mass and environment. Basal metabolic rate was higher for eastern quolls (0.662 +/- 0.033 ml O(2) g(-1) h(-1)), presumably reflecting their naturally cool environment. Respiratory ventilation closely matched metabolic demand, except at high ambient temperatures where quolls hyperventilated to facilitate evaporative heat loss; tiger and eastern quolls also salivated. A higher evaporative water loss for eastern quolls (1.43 +/- 0.212 mg H(2)O g(-1) h(-1)) presumably reflects their more mesic distribution. The point of relative water economy was low for tiger (-1.3 degrees C), eastern (-12.5 degrees C) and northern (+3.3) quolls, and highest for the chuditch (+22.6 degrees C). We suggest that these differences in water economy reflect lower expired air temperatures and hence lower respiratory evaporative water loss for the arid-zone chuditch relative to tropical and mesic quolls.