Energy Expenditure In Animals Research Articles

Evidence for SARS-CoV-2 infected Golden Syrian hamsters (Mesocricetus auratus) reducing daily energy expenditure and body core temperature

Golden Syrian hamsters (Mesocricetus auratus) are a well-established animal model for human infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) due to their susceptibility to SARS-CoV-2 infection, robust virus replication and pathological manifestations similar to human COVID-19 pneumonia. To investigate the physiological changes upon infection in this animal model, we explored the alterations in daily energy expenditure (DEE), water turnover, body mass, body temperature, and locomotor activity in non-infected and SARS-CoV-2 infected Golden Syrian hamsters for four days post SARS-CoV-2. DEE was measured using the doubly labelled water method, which allows for the accurate estimation of carbon dioxide production and, consequently, energy expenditure in animals. Additionally, we investigated total water intake (TWI), which comprises drinking water, preformed water in food, and metabolic water. Using intraperitoneally implanted data loggers, we also monitored body core temperature and locomotor activity in some of the animals. Here we provide evidence for infected hamsters exhibiting significantly lower DEE and TWI compared to non-infected animals. We also observed an increase in body weight in the non-infected animals, while infected animals experienced weight loss. Further, infected animals showed a significantly decreased body temperature, indicating a generally lowered metabolic rate.

Time-energy budgets outperform dynamic body acceleration in predicting daily energy expenditure in kittiwakes, and estimate a very low cost of gliding flight relative to flapping flight.

Energy is a common currency for any living organism, yet estimating energy expenditure in wild animals is challenging. Accelerometers are commonly used to estimate energy expenditure, via a dynamic body acceleration (DBA) or time-energy budget approach. The dynamic body acceleration approach estimates energy expenditure directly from acceleration but may lead to erroneous estimates during inactivity when acceleration is zero but energy expenditure is not. The time-energy budget approach uses accelerometers and other data streams to assign a behaviour to each time step, and then calculates energy expenditure based on activity-specific metabolic rates assigned to each behaviour. Here, used GPS-accelerometry in breeding black-legged kittiwakes (Rissa tridactyla, n=80) to calculate DBA and time-energy budgets derived from simple biologging metrics (speed, wing beat frequency, GPS position). We then compared these two approaches to estimates of energy expenditure from doubly-labelled water. Energy expenditure estimated from DLW correlated with DBA, but the best model to estimate energy expenditure was based on time-energy budgets. Energy costs of flapping flight were higher than all other kittiwake behaviours (5.54 x basal metabolic rate, BMR). Energetic costs of gliding flight (0.80 x BMR) were the lowest of all behaviours, and equivalent to the cost of resting at the colony. DEE for our birds estimated from our calibration coefficients are similar to DEE for our birds estimated with the model coefficient published using different methods. We conclude that once calibrated with DLW, GPS-accelerometry provides a simple method for measuring energy expenditure in wild kittiwakes based on time-energy budgets.

Dynamic soaring decouples dynamic body acceleration and energetics in albatrosses.

Estimates of movement costs are essential for understanding energetic and life-history trade-offs. Although overall dynamic body acceleration (ODBA) derived from accelerometer data is widely used as a proxy for energy expenditure (EE) in free-ranging animals, its utility has not been tested in species that predominately use body rotations or exploit environmental energy for movement. We tested a suite of sensor-derived movement metrics as proxies for EE in two species of albatrosses, which routinely use dynamic soaring to extract energy from the wind to reduce movement costs. Birds were fitted with a combined heart-rate, accelerometer, magnetometer and GPS logger, and relationships between movement metrics and heart rate-derived V̇O2, an indirect measure of EE, were analyzed during different flight and activity modes. When birds were exclusively soaring, a metric derived from angular velocity on the yaw axis provided a useful proxy of EE. Thus, body rotations involved in dynamic soaring have clear energetic costs, albeit considerably lower than those of the muscle contractions required for flapping flight. We found that ODBA was not a useful proxy for EE in albatrosses when birds were exclusively soaring. As albatrosses spend much of their foraging trips soaring, ODBA alone was a poor predictor of EE in albatrosses. Despite the lower percentage of time flapping, the number of flaps was a useful metric when comparing EE across foraging trips. Our findings highlight that alternative metrics, beyond ODBA, may be required to estimate energy expenditure from inertial sensors in animals whose movements involve extensive body rotations.

456 Allocating distribution of pasture utilization across the grazing landscape in grazing steers equipped with virtual fencing collars

Abstract Spatial utilization of pasture landscapes by grazing animals is often heterogeneous and driven by complex environmental and physiological interactions between plants and animals. Synergistic energy pathways can be modeled using mechanistic relationships describing resource distribution, animal behavior, metabolic energy rate, and pasture utilization using biometric sensors. The objective of this study was to demonstrate the ability to measure the energy landscape by mapping fine-scale contributions to animal energy expenditure, nutrient acquisition, growth, and overall economic profitability. We utilized animal trajectories and location fixes recorded by virtual fencing collars (Vence) daily body weight (BW) using precision livestock scales (Smartscale, C-Lock Inc.) and oxygen consumption (GreenFeeds, C-Lock Inc.) on steers (n = 127), managed as part of a broader project to evaluate environmental synergies in extensive grazing systems. Steers were allocated to one of six native grass pastures assigned to either rotational or continuous grazing strategies, and one of three stocking rates (low, moderate, high) in a 2 x 3 factorial arrangement. Space utilization was quantified as the frequency of fixes located within each cell of a 5 x 5-meter Grid and the distance between grid cells and water was calculated using the Pythagorean theorem. Movement behavior was quantified using Program R to calculate step length, the distance between two temporally continuous fix points utilizing the Pythagorean Theorem, and turn angles calculated as the cosine of the pre- and pro-ceeding step lengths where larger values indicated greater deviation from a straight trajectory. A mixed linear regression model was fitted using the lmer function in the lme4 package. Space utilization decreased with increased distance from water (P < 0.05), with rotational grazing strategies increasing concentration around water sources (P < 0.05). This indicates an opportunity to utilize precision livestock technology to facilitate pasture management and increase space utilization in grazing cattle.

Estimating the Energy Expenditure of Grazing Farm Animals Based on Dynamic Body Acceleration.

Indirect methods of measuring the energy expenditure of grazing animals using heartbeat variation or accelerometers are very convenient due to their low cost and low intrusiveness, allowing animals to maintain their usual routine. In the case of accelerometers, it is possible to use them to measure activity, as well as to classify animal behavior, allowing their usage in other scenarios. Despite the obvious convenience of use, it is important to evaluate the measurement error and understand the validity of the measurement through a simplistic method. In this paper, data from accelerometers were used to classify behavior and measure animal activity, and an algorithm was developed to calculate the energy expended by sheep. The results of the energy expenditure calculations were subsequently compared with the values reported in the literature, and it was verified that the values obtained were within the reference ranges. Although it cannot be used as a real metering of energy expended, the method is promising, as it can be integrated with other complementary sources of information, such as the evolution of the animal's weight and ingestion time, thus providing assistance in animals' dietary management.

Filtering heart rates using data densities: The boxfilter R package

Abstract Over the past decades, there has been a growing interest in long‐term heart rate records, especially from free‐living animals. Largely, this increase is because most of the metabolic activity of tissues is based on oxygen delivery by the heart. Therefore, heart rate has served as a proxy for energy expenditure in animals. However, heart rates or other physiological variables recorded in humans and animals using loggers often contain noise. False measurements are sometimes eliminated by hand or by filters that reject variables based on the shape or frequency of the signal. Occasionally, outliers are rejected because they occur a long distance from genuine data. We introduce an R package, boxfilter, which enables users to eliminate noise based on counting the number of close neighbours inside a gliding window. Depending on the cut‐off value chosen, a focal point with a low proportion of neighbours will be rejected as noise. All three parameters, namely window width and height, as well as the cut‐off value, can be computed automatically. The choice of the clip‐off value beyond which data points are discarded is crucial. The package boxfilter cannot, of course, solve problems caused by completely erroneous measurements. Like the human eye, this filter prefers points that are part of a pattern, such as a dense band, and rejects isolated values. The boxfilter may also be applied to other measures than heart rate that do not change instantaneously, such as body temperature, blood pressure or sleep parameters.

Dynamic, sex- and diet-specific pleiotropism in the PAC1 receptor-mediated regulation of arcuate proopiomelanocortin and Neuropeptide Y/Agouti related peptide neuronal excitability by anorexigenic ventromedial nucleus PACAP neurons.

This study furthers the investigation of how pituitary adenylate cyclase activating polypeptide (PACAP) and the PAC1 receptor (PAC1R) regulate the homeostatic energy balance circuitry. We hypothesized that apoptotic ablation of PACAP neurones in the hypothalamic ventromedial nucleus (VMN) would affect both energy intake and energy expenditure. We also hypothesized that selective PAC1R knockdown would impair the PACAP-induced excitation in anorexigenic proopiomelanocortin (POMC) neurones and inhibition of orexigenic neuropeptide Y (NPY)/agouti-related peptide (AgRP) neurones in the hypothalamic arcuate nucleus (ARC). The results show CASPASE-3-induced ablation of VMN PACAP neurones leads to increased energy intake and meal frequency as well as decreased energy expenditure in lean animals. The effects were more robust in obese males, whereas we saw the opposite effects in obese females. We then utilized visualized whole-cell patch clamp recordings in hypothalamic slices. PAC1R knockdown in POMC neurones diminishes the PACAP-induced depolarization, increase in firing, decreases in energy intake and meal size, as well as increases in CO2 production and O2 consumption. Similarly, the lack of expression of the PAC1R in NPY/AgRP neurones greatly attenuates the PACAP-induced hyperpolarization, suppression of firing, decreases in energy intake and meal frequency, as well as increases in energy expenditure. The PACAP response in NPY/AgRP neurones switched from predominantly inhibitory to excitatory in fasted animals. Finally, the anorexigenic effect of PACAP was potentiated when oestradiol was injected into the ARC in ovariectomized females. This study demonstrates the critical role of anorexigenic VMN PACAP neurones and the PAC1R in exciting POMC and inhibiting NPY/AgRP neurons to control homeostatic feeding.

The secret life of wild animals revealed by accelerometer data: how landscape diversity and seasonality influence the behavioural types of European hares

ContextLandscape composition and configuration, as well as seasonal landscape dynamics shape the behaviour, movement and energy expenditure of animals, i.e. foraging, hiding or fleeing, and ultimately survival. Especially in highly modified agricultural systems, it is crucial to understand how animal behaviour is influenced by landscape context to develop sustainable land management concepts.ObjectivesWe show how landscape composition and configuration, together with seasonal dynamics affect animal behavioural types, accounting for the different life-history events in both sexes.MethodsWe investigated 34 European hares in two contrasting agricultural landscapes (a simple and a complex landscape) by using tri-axial accelerometer data to classify the animals’ behaviour into five categories: resting, foraging, moving, grooming and standing upright (i.e. vigilance behaviour). We tested whether the amount of behaviours per category changed with landscape composition and configuration, season and sex.ResultsDuring peak breeding, hares in areas of high habitat diversity rested more, moved less and spent less time searching for resources. During winter, hares moved more and rested less. Females rested less and foraged more in areas with large agricultural fields.ConclusionsA complex landscape is particularly important during the breeding season, allowing animals to allocate enough energy into reproduction. In winter, hares in areas of low habitat diversity may not find enough thermal and anti-predator shelter to move as much as they would need to meet their requirements. Hence, high habitat diversity and small field sizes guarantee species persistence in human-altered agricultural areas throughout the year.

Vitis vinifera L. Bioactive Components Modulate Adipose Tissue Metabolic Markers of Healthy Rats in a Photoperiod-Dependent Manner.

The beneficial health effects of (poly)phenol-rich foods such as red grapes mainly depend on both the type and concentration of (poly)phenols. Since fruit (poly)phenol content is influenced by growing conditions, the study examines the seasonal effects of red grapes (Vitis vinifera L.), grown under various cultivation conditions, on metabolic markers of adipose tissue in healthy rats. For this purpose, Fischer 344 rats are exposed into three different light-dark cycles and daily supplemented with 100mgkg-1 of either conventionally or organically grown red grapes for 10 weeks (n=6). Seasonal consumption of organic grapes (OGs), which are richer in anthocyanins, increases energy expenditure (EE) of animals exposed to long photoperiod and enhances uncoupling protein 1 (UCP1) protein expression in brown adipose tissue of animals under standard photoperiod. Additionally, red grape consumption affects the gene expression profile of white adipose tissue (WAT), upregulating browning markers of subcutaneous WAT in 12h light (L12) and 18h light (L18) photoperiods, and downregulating adipogenic and lipolytic markers of visceral WAT in 6h light (L6) and L12 photoperiods. These results clearly show that bioactive compounds of grapes can modulate the metabolic markers of white and brown adipose tissues in a photoperiod and depot-dependent manner, partly affecting EE when consumed out of season.

Energy expenditure of southern right whales varies with body size, reproductive state and activity level.

Quantifying the energy expenditure of animals is critical to understand the cost of anthropogenic disturbance relative to their overall energy requirements. We used novel drone focal follows (776 follows, 185 individuals) and aerial photogrammetry (5,372 measurements, 791 individuals) to measure the respiration rate and body condition loss of southern right whales (Eubalaena australis) on a breeding ground in Australia. Respiration rates were converted to oxygen consumption and field metabolic rates (FMR) using published bioenergetic models. The intra-seasonal loss in body condition of different reproductive classes (calves, juveniles, adults, pregnant and lactating) was converted to blubber energy loss and total energy expenditure (TEE). Using these two metrics, we tested the effects of body size, reproductive state and activity level on right whale energy expenditure. Respiration rates and mass-specific FMR decreased exponentially with an increase in body size, as expected based on allometric scaling. FMR increased curvilinearly with an increase in swim speed, likely as a result of increased drag and increased locomotion costs. Respiration rates and FMR were 44% higher for pregnant and lactating females compared to adults, suggesting significant costs of foetal maintenance and milk production, respectively. The estimated FMR of adults based on their respiration rates, corresponded well with the estimated TEE based on body condition loss. The rate of decline in body condition of pregnant and lactating females was considerably higher than expected based on respiration rates, which likely reflects the milk energy transfer from mothers to calves, which is not reflected in their FMR.

A previously uncharacterized Factor Associated with Metabolism and Energy (FAME/C14orf105/CCDC198/1700011H14Rik) is related to evolutionary adaptation, energy balance, and kidney physiology

In this study we use comparative genomics to uncover a gene with uncharacterized function (1700011H14Rik/C14orf105/CCDC198), which we hereby name FAME (Factor Associated with Metabolism and Energy). We observe that FAME shows an unusually high evolutionary divergence in birds and mammals. Through the comparison of single nucleotide polymorphisms, we identify gene flow of FAME from Neandertals into modern humans. We conduct knockout experiments on animals and observe altered body weight and decreased energy expenditure in Fame knockout animals, corresponding to genome-wide association studies linking FAME with higher body mass index in humans. Gene expression and subcellular localization analyses reveal that FAME is a membrane-bound protein enriched in the kidneys. Although the gene knockout results in structurally normal kidneys, we detect higher albumin in urine and lowered ferritin in the blood. Through experimental validation, we confirm interactions between FAME and ferritin and show co-localization in vesicular and plasma membranes.

The role of individual variability on the predictive performance of machine learning applied to large bio-logging datasets

Animal-borne tagging (bio-logging) generates large and complex datasets. In particular, accelerometer tags, which provide information on behaviour and energy expenditure of wild animals, produce high-resolution multi-dimensional data, and can be challenging to analyse. We tested the performance of commonly used artificial intelligence tools on datasets of increasing volume and dimensionality. By collecting bio-logging data across several sampling seasons, datasets are inherently characterized by inter-individual variability. Such information should be considered when predicting behaviour. We integrated both unsupervised and supervised machine learning approaches to predict behaviours in two penguin species. The classified behaviours obtained from the unsupervised approach Expectation Maximisation were used to train the supervised approach Random Forest. We assessed agreement between the approaches, the performance of Random Forest on unknown data and the implications for the calculation of energy expenditure. Consideration of behavioural variability resulted in high agreement (> 80%) in behavioural classifications and minimal differences in energy expenditure estimates. However, some outliers with < 70% of agreement, highlighted how behaviours characterized by signal similarity are confused. We advise the broad bio-logging community, approaching these large datasets, to be cautious when upscaling predictions, as this might lead to less accurate estimates of behaviour and energy expenditure.

How much does it cost? Teaching physiology of energy metabolism in mice using an indirect calorimetry system in a practical course for veterinary students.

In endothermic mammals total energy expenditure (EE) is composed of basal metabolic rate (BMR), energy spent for muscle activity, thermoregulation, any kind of production (such as milk, meat, or egg production), and the thermic effect of feeding. The BMR is predominantly determined by body mass and the surface-to-volume ratio of the body. The EE can be quantified by either direct or indirect calorimetry. Direct calorimetry measures the rate of heat loss from the body, whereas indirect calorimetry measures oxygen consumption and carbon dioxide production and calculates heat production from oxidative nutrient combustion. A deep and sustainable understanding of EE in animals is crucial for veterinarians to properly calculate and evaluate feed rations during special circumstances such as anesthesia or in situations with increased energy demands as commonly seen in high-yielding livestock. The practical class described in this article provides an experimental approach to understanding how EE can be measured and calculated by indirect calorimetry. Two important factors that affect the EE of animals (the thermic effect of feeding and the effect of ambient temperature) are measured. A profound knowledge about the energy requirements of animal life and its measurement is also relevant for education in general biology, animal and human physiology, and nutrition. Therefore, this teaching unit can equally well be implemented in other areas of life sciences.

Increased energy expenditure is an indirect effect of habitat structural complexity loss

Abstract The deterioration of coastal habitats cascades to the decline of associated fauna by reducing trophic resource availability, shelter from predators and nursery grounds. The decline of biogenic habitat structure, such as in kelp forests, coral reefs, mangroves or seagrass beds, often causes a local increase in water flow velocity and wave exposure. The impact of this change in hydrodynamics on the energy expenditure of animals is largely unknown. Here we demonstrate that loss of seagrass beds increases water current velocity, which impacts associated pipefishes through increased energy expenditure. We correlated ventilation frequency with metabolic rate in four pipefish species, to be able to estimate metabolic rates in free‐swimming fish. Using a hydrodynamic flume, we then experimentally tested the effect of current velocity and substrate (seagrass or sand) on ventilation frequency and behaviour. Ventilation frequency was consistently higher when they swam on sand substratum compared to seagrass substratum for all species, and this was especially noticeable for the species with prehensile tails (i.e. Nerophis ophidion). Seagrass canopies reduced flow velocities by 7%–44%, which increased the overall current exposure that pipefish tolerated. N. ophidion, Syngnathus rostellatus and Syngnathus typhle showed two behavioural responses to currents: holding on to the seagrass canopy, and moving to areas where the current was lower (i.e. bottom) in trials without seagrass. Most of the individuals of all species were unable to maintain position in velocities of 15–18 cm/s on sand substratum. In this work, we demonstrate the reliance on seagrass hydrodynamic shelter of four species of pipefish. Among them, N. ophidion showed the highest seagrass shelter dependence and vulnerability, while S. rostellatus and S. typhle are potentially more resilient to vegetation changes. Increased energy expenditure is thus another impact on fishes as seagrass beds and other structural habitats continue to decline in coastal areas. A free Plain Language Summary can be found within the Supporting Information of this article.

STAT3 but Not ERK2 Is a Crucial Mediator Against Diet-Induced Obesity via VMH Neurons.

Leptin plays an important role in the protection against diet-induced obesity (DIO) by its actions in ventromedial hypothalamic (VMH) neurons. However, little is known about the intracellular mechanisms involved in these effects. To assess the role of the STAT3 and ERK2 signaling in neurons that express the steroidogenic factor 1 (SF1) in the VMH in energy homeostasis, we used cre-lox technology to generate male and female mice with specific disruption of STAT3 or ERK2 in SF1 neurons of the VMH. We demonstrated that the conditional knockout of STAT3 in SF1 neurons of the VMH did not affect body weight, food intake, energy expenditure, or glucose homeostasis in animals on regular chow. However, with high-fat diet (HFD) challenge, loss of STAT3 in SF1 neurons caused a significant increase in body weight, food intake, and energy efficiency that was more remarkable in females, which also showed a decrease in energy expenditure. In contrast, deletion of ERK2 in SF1 neurons of VMH did not have any impact on energy homeostasis in both regular diet and HFD conditions. In conclusion, STAT3 but not ERK2 signaling in SF1 neurons of VMH plays a crucial role in protection against DIO in a sex-specific pattern.

Validating accelerometry-derived proxies of energy expenditure using the doubly labelled water method in the smallest penguin species.

ABSTRACTUnderstanding energy use is central to understanding an animal's physiological and behavioural ecology. However, directly measuring energy expenditure in free-ranging animals is inherently difficult. The doubly labelled water (DLW) method is widely used to investigate energy expenditure in a range of taxa. Although reliable, DLW data collection and analysis is both financially costly and time consuming. Dynamic body acceleration (e.g. VeDBA) calculated from animal-borne accelerometers has been used to determine behavioural patterns, and is increasingly being used as a proxy for energy expenditure. Still its performance as a proxy for energy expenditure in free-ranging animals is not well established and requires validation against established methods. In the present study, the relationship between VeDBA and the at-sea metabolic rate calculated from DLW was investigated in little penguins (Eudyptula minor) using three approaches. Both in a simple correlation and activity-specific approaches were shown to be good predictors of at-sea metabolic rate. The third approach using activity-specific energy expenditure values obtained from literature did not accurately calculate the energy expended by individuals. However, all three approaches were significantly strengthened by the addition of mean horizontal travel speed. These results provide validation for the use of accelerometry as a proxy for energy expenditure and show how energy expenditure may be influenced by both individual behaviour and environmental conditions.

Proxy problems: Why a calibration is essential for interpreting quantified changes in energy expenditure from biologging data

Abstract We do not yet have the means to directly measure the energy expenditure of wild animals, particularly at a high temporal resolution. However, we can instead measure factors that correlate with energy expenditure, such as heart rate or accelerometry, that is, energy expenditure proxies. To estimate the magnitude of differences in energy expenditure between contexts (such as day and night, or travelling singly vs. in a group), our energy expenditure proxy must be calibrated. However, perhaps because of the logistical challenges of conducting such calibrations and the observation that most calibrations are linear, researchers sometimes interpret the degree of change in energy expenditure between contexts based on uncalibrated proxy data. When doing so, they implicitly assume that the ratio of the proxy values between contexts represents the ratio of energy expenditure values between those contexts. This approach, however, is usually spurious because unless the relationship between energy expenditure and proxy passes through the origin (i.e. y‐intercept = 0), the ratio of change in the proxy between contexts does not represent the ratio of change in energy expenditure. We model the error induced when data from an uncalibrated proxy are used to interpret changes in energy expenditure. We also estimate the errors made in published articles that employ this approach, by comparing the claimed change in energy expenditure between two contexts with the change in energy expenditure estimated by applying the best available calibrations now available. As predicted by the models we developed, the apparent size of the error in published articles is related to the relative size of the calibration y‐intercept. Species‐ and activity‐specific empirical calibrations are the best option for interpreting proxies of energy expenditure. However, for mammals and birds, enough data have been amassed such that energy expenditure can be predicted from measures of heart rate by knowing animal heart mass or even body mass; perhaps a somewhat analogous predictive tool will be available in the future for accelerometry. A free Plain Language Summary can be found within the Supporting Information of this article.

Bone metastases induce metabolic changes and mitophagy in mice.

What is the central question of this study? Cachexia causes severe changes in skeletal muscle metabolism and function and is a key predictor of negative outcomes in cancer patients: what are the changes in whole animal energy metabolism and mitochondria in skeletal muscle? What is the main finding and its importance? There is decreased whole animal energy expenditure in mice with cachexia. They displayed highly dysmorphic mitochondria and mitophagy in skeletal muscle. Cachexia causes changes in skeletal muscle metabolism. Mice with MDA-MB-231 breast cancer bone metastases and cachexia have decreased whole animal energy metabolism and increased skeletal muscle mitophagy. We examined whole animal energy metabolism by indirect calorimetry in mice with MDA-MB-231 breast cancer bone metastases, and showed decreased energy expenditure. We also examined skeletal muscle mitochondria and found that mitochondria in mice with MDA-MB-231 bone metastases are highly dysmorphic and have altered protein markers of mitochondrial biogenesis and dynamics. In addition, LC3B protein was increased in mitochondria of skeletal muscle from cachectic mice, and colocalized with the mitochondrial protein Tom20. Our data demonstrate the importance of mitophagy in cachexia. Understanding these changes will help contribute to defining treatments for cancer cachexia.

Respiratory quotient and the stoichiometric approach to investigating metabolic energy substrate use in aquatic ectotherms

AbstractThe respiratory quotient (RQ) has been used extensively as an index to evaluate metabolic energy expenditure in terrestrial animals including humans. In contrast, RQ use in understanding physiology and nutrition of aquatic ectotherms has been restricted due to technical challenges in measuring total CO2in water. With technical advances in measuring total CO2in water, RQ in aquatic ectotherms can be accurately determined and is potentially available as a valuable method. Here, we provide a comprehensive review of studies on RQ and metabolic energy substrate use in aquatic ectotherms. Metabolic energy substrate use is evaluated by a reliable stoichiometric bioenergetic approach, based on measuring RQ and nitrogen quotient (NQ) simultaneously. Stoichiometry provides a non‐destructive and unequivocal way to quantify the instantaneous oxidation of each major energy substrate (protein, lipid or carbohydrate). This review aims to refine knowledge about bioenergetics of aquatic ectotherms under different conditions including nutritional aspects of sustainable aquaculture. Notably, stoichiometry provides a promising approach to optimize feeds and feeding regimes to realize sustainable aquaculture under differing conditions and with differing feed ingredients. It also provides an approach to consider climate change impacts and physiological adaptation mechanisms for survival and development in farmed environments and natural ecosystems. Stoichiometric bioenergetics knowledge in aquatic ectotherms has relevance to commercial impacts in the face of overfishing and food security, and ecological significance in the face of environmental change scenarios. We suggest expanding the use of stoichiometry in future bioenergetic research in emerging aquaculture species.

No energetic cost of tuberculosis infection in European badgers (Meles meles).

Energy availability and energy use directly influence an organism's life history, fitness and ecological function. In wild animals, abiotic factors such as ambient temperature, season and rainfall, and biotic factors such as body mass, age, social group size and disease status, all potentially influence energy balance. Relatively few studies have examined the effects of disease on the energy expenditure of wild animals. Such studies could further our understanding of factors influencing the transmission of zoonotic diseases. The European badger (Meles meles) is a medium-sized carnivore that occurs in mixed-sex, familial groups across much of its range. In the UK, they are a protected species but are also involved in the epidemiology of bovine tuberculosis (TB) in cattle. We measured the daily energy expenditure (DEE) and resting metabolic rate (RMR) of wild badgers and related this to their TB infection status and a range of other interacting factors including season, group size, disease status, sex, age, body mass and body fat. Individuals were larger and fatter when they were older, and fatter during the winter. Males were also heavier than females during the summer. In addition, individuals from smaller groups that were exposed to TB tended to have lower body mass. There were no direct effects of disease status on DEE or RMR; however, there was a significant interaction whereby DEE increased with body mass in small groups but decreased with body mass in large groups. Results are consistent with the costs of TB infection being met by compensatory mechanisms enabling badgers to survive for extended periods without exhibiting measurable energetic consequences.