Scaling of organ masses in mammals and birds: phylogenetic signal and implications for metabolic rate scaling

Inferring the metabolic rate of bone

The bone organ is poorly represented in comparative research on mammalian mass-specific metabolic rates. As a first order attempt to remedy this, from the literature we collected mass-specific metabolic rates for all major organs except for the bone organ, and by subtraction infer the rate for the bone organ. The scaling relationships are given of each whole-organ mass-specific metabolic rate and of the relationship between whole-organ metabolic rate and body mass. Scaling of the lung, adipose depot and bone organ with body mass is higher than would be expected by ¾ power scaling. We interpret the similar scalings of bone and the adipose depot in light of their evolved regulation of whole-body metabolism. We also briefly examine the supra-¾ power scaling of the lung as well as the independence of the mass-specific metabolic rate of the heart from body mass. The bone organ exhibits relatively high energy expenditure with increasing body size. The bone marrow and its medullary adipocyte store may be responsible for engendering the greater share of the bone organ's energetic cost.

Data needs for sea otter bioenergetics modeling

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.

Endocrine gland size is proportional to its target tissue size

Endocrine glands secrete hormones into the circulation to target distant tissues and regulate their functions. The qualitative relationship between hormone-secreting organs and their target tissues is well established, but a quantitative approach is currently limited. Quantification is important, as it could allow us to study the endocrine system using engineering concepts of optimality and tradeoffs. In this study, we collected literature data on 24 human hormones secreted from dedicated endocrine cells. We find that the number of endocrine cells secreting a hormone is proportional to the number of its target cells. A single endocrine cell serves approximately 2,000 target cells, a relationship that spans 6 orders of magnitude of cell numbers. This suggests an economic principle of cells working near their maximal capacity, and glands that are no bigger than they need to be.

Functional similarity affects similarity in partner composition in flea-mammal networks

Functional signal in an interaction network is a phenomenon in which species resembling each other in their traits interact with similar partners. We tested the functional signal concept in realm-specific and regional flea-host networks from four biogeographic realms and asked whether the species composition of (a) host spectra and (b) flea assemblages is similar between functionally similar flea and host species, respectively. Analogously to testing for phylogenetic signal, we applied Mantel tests to investigate the correlation between flea or host functional distances calculated from functional dendrograms and dissimilarities in sets of interacting partners. In all realm-specific networks, functionally similar fleas tended to exploit similar hosts often belonging to the same genus, whereas functionally similar hosts tended to harbour similar fleas, again often belonging to the same genus. The strength of realm-specific functional signals and the frequency of detecting a significant functional signal in the regional networks differed between realms. The frequency of detecting a significant functional signal in the regional networks correlated positively with the network size for fleas and with the number of hosts in a network for hosts. A functional signal in the regional networks was more frequently found for hosts than for fleas. We discuss the mechanisms behind the functional signal in both fleas and their hosts, relate geographic functional signal patterns to the historic biogeography of fleas and conclude that functional signals in the species composition of host spectra for fleas and of flea assemblages for hosts result from the interplay of evolutionary and ecological processes.

Relationships between functional alpha and beta diversities of flea parasites and their small mammalian hosts

We studied the relationships between functional alpha and beta diversities of fleas and their small mammalian hosts in 4 biogeographic realms (the Afrotropics, the Nearctic, the Neotropics and the Palearctic), considering 3 components of alpha diversity (functional richness, divergence and regularity). We asked whether (a) flea alpha and beta diversities are driven by host alpha and beta diversities; (b) the variation in the off-host environment affects variation in flea alpha and beta diversities; and (c) the pattern of the relationship between flea and host alpha or beta diversities differs between geographic realms. We analysed alpha diversity using modified phylogenetic generalized least squares and beta diversity using modified phylogenetic generalized dissimilarity modelling. In all realms, flea functional richness and regularity increased with an increase in host functional richness and regularity, respectively, whereas flea functional divergence correlated positively with host functional divergence in the Nearctic only. Environmental effects on the components of flea alpha diversity were found only in the Holarctic realms. Host functional beta diversity was invariantly the best predictor of flea functional beta diversity in all realms, whereas the effects of environmental variables on flea functional beta diversity were much weaker and differed between realms. We conclude that flea functional diversity is mostly driven by host functional diversity, whereas the environmental effects on flea functional diversity vary (a) geographically and (b) between components of functional alpha diversity.

How Metabolic Rate Relates to Cell Size

Metabolic rate and its covariation with body mass vary substantially within and among species in little understood ways. Here, I critically review explanations (and supporting data) concerning how cell size and number and their establishment by cell expansion and multiplication may affect metabolic rate and its scaling with body mass. Cell size and growth may affect size-specific metabolic rate, as well as the vertical elevation (metabolic level) and slope (exponent) of metabolic scaling relationships. Mechanistic causes of negative correlations between cell size and metabolic rate may involve reduced resource supply and/or demand in larger cells, related to decreased surface area per volume, larger intracellular resource-transport distances, lower metabolic costs of ionic regulation, slower cell multiplication and somatic growth, and larger intracellular deposits of metabolically inert materials in some tissues. A cell-size perspective helps to explain some (but not all) variation in metabolic rate and its body-mass scaling and thus should be included in any multi-mechanistic theory attempting to explain the full diversity of metabolic scaling. A cell-size approach may also help conceptually integrate studies of the biological regulation of cellular growth and metabolism with those concerning major transitions in ontogenetic development and associated shifts in metabolic scaling.