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Basal metabolic rate (BMR) in comparison to field metabolic rate (FMR) for various species of marine mammals expressed as a multiple of Kleiber's (1975) equation. The box plots representing BMR (colored box plots) and FMR (clear box plots) are based on individual study means for each species, as shown in Fig. 2 and Fig. 3, respectively. The calculations for BMR as a proportion of FMR are shown as percentages and are based on species means detailed in Table 1 and Table 2 (which includes references for the original data). The grand mean of BMR as a proportion of FMR (%) across all odontocetes species and across all pinniped species are shown in bolded font. The value for "Other" solely represents the sea otter.
Source publication
Over the past several decades, scientists have constructed bioenergetic models for marine mammals to assess potential population-level consequences following exposure to a disturbance, stressor, or environmental change, such as under the Population Consequences of Disturbance (pCOD) framework. The animal's metabolic rate (rate of energy expenditure...
Context in source publication
Context 1
... there was similarity across taxa, which was surprising since evolutionarily, cetaceans, pinnipeds and mustelids were not derived from a common terrestrial ancestor. Across three odontocete species, BMR represented 56% of FMR, which was similar in value to that found for the three pinniped families, phocid seals (50%; four species), otariids (56%; five species) and walrus (56%), as well as the mustelid the sea otter (57%; Figure 4). There were of course notable exceptions within these overall averages, which included BMR accounting for a higher proportions of FMR for harbor porpoise (73%), Weddell seals (86%) and Steller sea lions (73%). ...
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The recovery of marine mammals from historical over-exploitation in the 1970s represents one of the largest changes in trophic structure in the northeast Pacific Ocean over the last century, for which the impacts on key forage species such as Pacific Herring ( Clupea pallasii ) are poorly understood. This has prompted hypotheses that increasing mar...
Citations
... Whereas energy metabolism has been measured in gray whales and has recently been reviewed for marine mammals 66 , rates of protein catabolism are only available for a few pinnipeds 65 . We used allometric scaling relationships based on estimates of N excretion rates from fasting and fasting-while-lactating elephant seals to estimate nitrogen transport between whale feeding and breeding grounds 15,67 . ...
Baleen whales migrate from productive high-latitude feeding grounds to usually oligotrophic tropical and subtropical reproductive winter grounds, translocating limiting nutrients across ecosystem boundaries in their bodies. Here, we estimate the latitudinal movement of nutrients through carcasses, placentas, and urea for four species of baleen whales that exhibit clear annual migration, relying on spatial data from publicly available databases, present and past populations, and measurements of protein catabolism and other sources of nitrogen from baleen whales and other marine mammals. Migrating gray, humpback, and North Atlantic and southern right whales convey an estimated 3784 tons N yr⁻¹ and 46,512 tons of biomass yr⁻¹ to winter grounds, a flux also known as the “great whale conveyor belt”; these numbers might have been three times higher before commercial whaling. We discuss how species recovery might help restore nutrient movement by whales in global oceans and increase the resilience and adaptative capacity of recipient ecosystems.
... In such a warm environment, very thick blubber could have been counterproductive for large cetaceans, especially basal forms, due to the increasing difficulty of dissipating heat caused by the scaling relationship between body surface area and volume (Schmidt-Nielsen, 1984). Sea cows have unusually low metabolic rates for mammals (Noren and Rosen, 2023), leaving them dangerously vulnerable to hypothermia even in middle latitude winters (Bossart et al., 2002). It is presumed in this study that basilosaur energetics were in the higher cetacean range, in which case fat deposits should not have been heavy and body masses may have been yet lower than the minimum presented here. ...
Extrapolating from skeletal/total mass ratios, the gigantic Paleogene whale Perucetus colossus has been estimated to have massed 85 to 341 tonnes, approaching and even exceeding the blue whale (Balaenoptera musculus). Such a large variation in body mass lacks the precision needed for analytical accuracy and is therefore not of technical value. Despite sufficient remains for a much more accurate volumetric model, none was produced for robust testing their procedure. A subsequent paper downscaled Perucetus to 60 to 70 tonnes as the most probable estimate. To better assess the question, we have produced multiview profile-skeletals for Perucetus and other large marine mammals in the most extensive such effort to date. These include the first accurate restorations of a number of large marine mammals. Perucetus is restored using the proportions of heavy boned pachycetine basilosaurs. Cross comparisons and attempts to illustrate the extinct whale's realistic volume leave no doubt that the Perucetus holotype did not reach the cetacean heavyweight category. A length of 15 to 16 m and a mass of 35 to 40 tonnes is more in line with its known anatomy. This result was affirmed by recalculations of skeletal/total mass relationships in large pachyosteosclerotic marine mammals, which suggest the method can produce useful estimates if conducted properly. Although their initial size expansion was remarkably rapid, basal cetaceans did not balloon to super whale dimensions just a few million years after the initial evolution of the fully marine forms. Evolution of extremely large body size exceeding 50 tonnes did not occur until the late Neogene. The biggest whale of all time, the blue, is not likely to exceed ~30 m and 200 tonnes. It is emphasized that anatomical knowledge translated into technical volumetric models remains the most critical means of restoring the mass of extinct organisms.
... Bioenergetics modeling is a key tool used to study and understand these dynamic processes, and such methods have long been used to examine energy balance in marine mammals. Several recent papers have reviewed bioenergetics modeling in marine mammals (Pirotta, 2002), provided guidance for estimating key parameters (Booth et al., 2003), reviewed available metabolic rates (Noren and Rosen, 2023) and growth patterns (Adamczak et al., 2023), and identified pressing data needs for improving our understanding of marine mammal bioenergetics and bioenergetic modeling (McHuron et al., 2022). These and other recent papers outline a rich history in, and promising future for marine mammal bioenergetics research. ...
... As the smallest marine mammal, balancing bioenergetic priorities is especially important for sea otters and must be done on much smaller time scales than other marine mammals. Due to their small body size and aquatic lifestyle, it has been proposed that sea otters have one of the highest mass-specific metabolic rates of any marine mammal (Yeates et al., 2007;Thometz et al., 2014;Noren and Rosen, 2023). Their relatively high metabolism means that adult sea otters must consume roughly one quarter of their body weight in food daily (Costa and Kooyman, 1982), resulting in rapid depletion of local prey resources as population densities increase (Tinker et al., 2008(Tinker et al., , 2012. ...
Sea otters are keystone predators whose recovery and expansion from historical exploitation throughout their range can serve to enhance local biodiversity, promote community stability, and buffer against habitat loss in nearshore marine systems. Bioenergetics models have become a useful tool in conservation and management efforts of marine mammals generally, yet no bioenergetics model exists for sea otters. Previous research provides abundant data that can be used to develop bioenergetics models for this species, yet important data gaps remain. Here we review the available data that could inform a bioenergetics model, and point to specific open questions that could be answered to more fully inform such an effort. These data gaps include quantifying energy intake through foraging by females with different aged pups in different quality habitats, the influence of body size on energy intake through foraging, and determining the level of fat storage that is possible in sea otters of different body sizes. The more completely we fill these data gaps, the more confidence we can have in the results and predictions produced by future bioenergetics modeling efforts for this species.
... The ecological significance of the evolution of low metabolic rate in sirenians compared to terrestrial mammalian herbivores is unclear, with some studies suggesting that large marine mammals might have lower metabolic rates than equivalent-sized terrestrial mammals because they do not use energy to support their body weight due to the buoyant force of water (Boyd, 2002;Innes, 1986). However, a more recent review found that to the contrary, carnivorous marine mammals have higher metabolic rates than their terrestrial counterparts, but that sirenians (as represented by manatees) have conspicuously lower metabolic rates compared to other marine mammals (Noren & Rosen, 2023). Noren and Rosen (2023) suggested that the low metabolic rate of manatees is likely related to their herbivorous and sedentary lifestyle in a warm water environment. ...
... However, a more recent review found that to the contrary, carnivorous marine mammals have higher metabolic rates than their terrestrial counterparts, but that sirenians (as represented by manatees) have conspicuously lower metabolic rates compared to other marine mammals (Noren & Rosen, 2023). Noren and Rosen (2023) suggested that the low metabolic rate of manatees is likely related to their herbivorous and sedentary lifestyle in a warm water environment. We agree but suggest further that herbivory on its own does not explain the extremely low metabolic rates of sirenians because their metabolic rates are also low compared to equivalent-sized terrestrial herbivorous mammals (Table 5). ...
... As reviewed by Noren and Rosen (2023), comparing metabolic rates of marine mammals to terrestrial mammals is complicated by the difficulty of meeting the basal metabolic rate measurement criteria when measuring metabolic rate in marine mammals. The critical assumptions for measuring basal metabolic rate (BMR) include being adult (nongrowing), nonreproductive, healthy, quiescent, at rest within the animal's thermal neutral zone, and postabsorptive. ...
Deterioration of seagrass beds worldwide has raised concern about the future of dugongs because almost all aspects of their life history depend on availability of seagrass. Understanding their energy metabolism and consequently how much seagrass they need will inform protective conservation strategies for dugongs. This study determined resting metabolic rate (RMR) in five wild‐caught adult dugongs by measuring oxygen consumption (O 2 ). Measurement conditions met assumptions for RMR, except that dugongs were not postabsorptive, thus a postprandial (pp) allometric equation for herbivorous mammals of similar size was used to predict an expected RMR pp for dugongs of known mass. O 2 was measured for 30 min in a metabolic tank after brief habituation. Dugongs' RMR pp was approximately half that predicted for their body mass but was higher than for manatees. Based on dugongs' RMR pp and considering plant caloric and water content, the daily minimum intake of fresh weight seagrass was 40–65 kg Halophila ovalis , or 20–40 kg Halodule spp. Greater seagrass intake would be required for growing and reproducing dugongs. Slow growth and protracted reproductive rates of dugongs are likely related to limitations in seagrass energy and nutrients. To ensure viability of this vulnerable species, it is critically important to conserve extensive healthy seagrass beds.
... Field metabolic rates are notoriously difficult to determine, especially when integrated at the population level and over annual time scales, as is the case here. We used multiple sources to calculate metabolic losses (Gillooly et al., 2001;Karamushko and Christiansen, 2002;Makarieva et al., 2008;Noren and Rosen, 2023;Savage et al., 2004;Williams et al., 2006;Yodzis and Innes, 1992) or derived these values from other food-web models (e.g. ecotrophic efficiency in Ecopath can be converted to other losses in RCaN, see Planque et al., 2014). ...
The Norwegian and Barents Seas host large commercial fish populations that interact with each other, as well as
marine mammal populations that feed on plankton and fish. Quantifying the past dynamics of these interacting
species, and of the associated fisheries in the Norwegian and Barents Sea is of high relevance to support
ecosystem-based management. The purpose of this work is to develop a food-web model of intermediate
complexity and perform a quantitative assessment of the Norwegian and Barents Sea ecosystems in the period
1988–2021 in a manner that is consistent with existing data and expert knowledge, and that is internally
coherent. For this purpose, we use the modelling framework of chance and necessity (CaN). The model construction
follows an iterative process that allows to confront, discuss, and resolve multiple issues as well as to
recognise uncertainties in expert knowledge, data, and input parameters. We show that it is possible to reconstruct
the past dynamics of the food-web only if recognising that some data and assumptions are more uncertain
than originally thought. According to this assessment, consumption by commercial fish and catch by fisheries
jointly increased until the early 2010s, after which consumption by fish declined and catches by fisheries stabilised.
On an annual basis, fish have consumed an average of 135.5 million tonnes of resources (including 9.5
million tonnes of fish), marine mammals have consumed an average of 22 million tonnes of which 50 % (11
million tonnes) were fish. Fisheries and hunting have captured an average of 4.4 million tonnes of fish and 7
thousand tonnes of marine mammals.
... Metabolic rates were modified by ±10%, ± 20%, and ±40%. Except for +40%, which was just outside of the reported range for marine mammals, this resulted in adult metabolic rates within the range documented for marine mammals (Noren and Rosen, 2023). These values were used due to the lack of certainty in the baseline metabolic rates used in the model since these were derived from related species from a different environment (Williams et al., 2007;McDonald et al., 2012;McHuron, 2016). ...
... Likewise, methods used to measure metabolic rates can vary in reliability and in what energetic costs (e.g. thermoregulation, digestion, etc.) are encapsulated in the estimate (Noren and Rosen, 2023). Nonetheless, the model was most sensitive to large changes in the metabolic rates. ...
... Nonetheless, the model was most sensitive to large changes in the metabolic rates. While the majority of metabolic rates assessed were within the range reported for marine mammals (Noren and Rosen, 2023), the extremes (± 40%) are unlikely to be representative of the metabolic costs for AUFS. The model was also moderately sensitive to the shape of the recruitment curve used and, as such, data linking pup weaning mass, weaning age, and recruitment success should be obtained for the species. ...
Introduction
Human-induced environmental change is driving a global redistribution of biodiversity, resulting in shifting prey and predation landscapes. These shifting landscapes can lead to changes in behavior, health, and vital rates, with potential implications for population dynamics.
Methods
In the present study, a state-dependent life-history theory model was developed to investigate the individual- and population-level responses of Australian fur seals (Arctocephalus pusillus doriferus) to changes in prey availability and at-sea mortality risk.
Results
Rates of pregnancy, pup nursing, and abortion were unaffected by prey availability in the simulated population. Likewise, on-land and at-sea durations were largely unaffected by prey availability, with more pronounced affects for nonreproductive and pregnant females than for lactating females. There was a strong influence of prey availability on the proportion of females that were concurrently pregnant and lactating, largely due to an increase in pup abandonments under low prey availability scenarios. This effect on pup abandonments also had flow on effects for pup recruitment. Increasing at-sea mortality risk resulted in greater offspring losses due to maternal death. The combined impact of prey availability and at-sea mortality risk on the number of simulated female offspring reaching sexual maturity was substantial.
Discussion
Consequently, our results suggest high vulnerability of the Australian fur seal population to shifting prey and predation landscapes. These results indicate a need for continued monitoring of Australian fur seal pup production and population dynamics in the face of rapid environmental change.
... These varying assumptions will influence the results of the bioenergetics models in which they are used, especially those intended to estimate the prey biomass consumed. These uncertainties underscore the need for better empirical estimates of energetics of large whales (Noren & Rosen, 2023). Our results indicate that sperm whales can survive, exploit their habitat and obtain enough energy to fulfil their energetic demands with lower FSR than has been previously assumed in bioenergetics studies. ...
Determining how animals allocate energy, and how external factors influence this allocation, is crucial to understand species' life history requirements and response to disturbance. This response is driven in part by individuals' energy balance, prey characteristics, foraging behaviour and energy required for essential functions. We developed a bioenergetic model to estimate minimum foraging success rate (FSR), that is, the lowest possible prey capture rate for individuals to obtain the minimum energy intake needed to meet daily metabolic requirements, for female sperm whale (Physeter macrocephalus). The model was based on whales' theoretical energetic requirements using foraging and prey characteristics from animal-borne tags and stomach contents, respectively. We used this model to simulate two prey structure change scenarios: (1) decrease in mean prey size, thus lower prey energy content and (2) decrease in prey size variability, reducing the variability in prey energy content. We estimate the whales need minimum of ~14% FSR to meet their energetic requirements, and energy intake is more sensitive to energy content changes than a decrease in energy variability. To estimate vulnerability to prey structure changes, we evaluated the compensation level required to meet bioenergetic demands. Considering a minimum 14% FSR, whales would need to increase energy intake by 21% (5–35%) and 49% (27–67%) to compensate for a 15% and 30% decrease in energy content, respectively. For a 30% and 50% decrease in energy variability, whales would need to increase energy intake by 13% (0–23%) and 24% (10–35%) to meet energetic demands, respectively. Our model demonstrates how foraging and prey characteristics can be used to estimate impact of changing prey structure in top predator energetics, which can help inform bottom-up effects on marine ecosystems. We showed the importance of considering different FSR in bioenergetics models, as it can have decisive implications on estimates of energy acquired and affect the conclusions about top predator's vulnerability to possible environmental fluctuations.
Nutrient foramina are small openings in the periosteal surface of the mid-shaft region of long bones that traverse the cortical layer and reach the medullary cavity. They are important for the delivery of nutrients and oxygen to bone tissue and are crucial for the repair and remodeling of bones over time. The nutrient foramina in the femur's diaphysis are related to the energetic needs of the femur and have been shown to be related to the maximum metabolic rate (MMR) of taxa. Here, we investigate the relationship between nutrient foramen size and body mass as a proxy to the aerobic capacity of taxa in living and extinct xenarthrans, including living sloths, anteaters, and armadillos, as well as extinct xenarthrans such as glyptodonts, pampatheres, and ground sloths. Seventy femora were sampled, including 20 from extant taxa and 50 from extinct taxa. We obtained the blood flow rate (Q) based on foramina area and performed PGLS and phylogenetic ANCOVA in order to explore differences among mammalian groups. Our results show that, among mammals, taxa commonly associated with lower metabolism like living xenarthrans showed relatively smaller foramina, while the foramina of giant extinct xenarthrans like ground sloths and glyptodonts overlapped with non-xenarthran placentals. Consequently,Q estimations indicated aerobic capacities comparable to other placental giant taxa like elephants or some ungulates. Furthermore, the estimation of the MMR for fossil giant taxa showed similar results, with almost all taxa showing high values except for those for which strong semi-arboreal or fossorial habits have been proposed. Moreover, the results are compatible with the diets predicted for extinct taxa, which indicate a strong consumption of grass similar to ungulates and in contrast to the folivorous or insectivorous diets of extant xenarthrans. The ancestral reconstruction of the MMR values indicated a lack of a common pattern for all xenarthrans, strongly supporting the occurrence of low metabolic rates in extant forms due to their particular dietary preferences and arboreal or fossorial habits. Our results highlight the importance of considering different evidence beyond the phylogenetic position of extinct taxa, especially when extinct forms are exceptionally different from their extant relatives. Future studies evaluating the energetic needs of giant extinct xenarthrans should not assume lower metabolic rates for these extinct animals based solely on their phylogenetic position and the observations on their extant relatives.
