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The energetics of embryonic growth
Respiratory Physiology & Neurobiology 178 (2011) 22–29
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Review
The energetics of embryonic growth夽 Peter Rombough ∗ Department of Biology, Brandon University, Brandon, MB R7A 6A9, Canada
a r t i c l e
i n f o
Article history: Accepted 28 April 2011 Keywords: Embryonic development Bioenergetics Cost of growth Energy partitioning Production efficiency Metabolic scaling Metabolic scope
a b s t r a c t Embryos typically operate under much tighter energy constraints than older animals. This has had a profound impact on how energy is stored, mobilized and partitioned. The result is sometimes quite different ways of doing things. Growth, in particular, is a much more important activity during development. Compared with adults, specific growth rates (g) are extremely high (≥150% day−1 for some fish). Production efficiencies are also much higher, particularly for early stages where values of 80–90% are not uncommon. Higher production efficiencies are possible, in part, because of lower unit costs at high g. Unlike in adults, the unit cost of growth does not appear to be fixed during early life. Energy also tends to be partitioned in a different manner, with compensatory partitioning being much more important during early life. Other differences include much higher routine metabolic intensities, smaller aerobic scopes and approximately isometric scaling of routine metabolism. The implications for ontogenetic growth models are discussed. © 2011 Elsevier B.V. All rights reserved.
1. Introduction Growth is the dominant energy-demanding activity during embryonic and larval development. In cleidoic eggs (enclosed eggs where gases, water and metabolic wastes, but no energy are exchanged with the environment, e.g. birds, most fish), an average of 60% of the initial energy content of the yolk is converted into tissue by the end of yolk absorption (Needham, 1931; Finn and Fyhn, 2010). An additional 20% or so of yolk energy is required to construct the new tissue (Wieser, 1994; Rombough, 2006). In total, about 80% of the initial energy content of the yolk is directed towards growth. If one subtracts the fraction of energy lost in metabolic waste products, about 5%, this leaves only ∼15% of initial yolk energy to support all of the other activities taking place during embryonic/larval development. The speed with which yolk is typically converted into tissue is also noteworthy. Specific growth rates in excess of 150% day−1 have been reported for larvae of some fish species (e.g. Conceic¸ão et al., 1997a; Smith and Ottema, 2006), but even the more typical rates of 10–30% day−1 greatly exceed anything observed in juvenile or adult fish. Such high rates of growth might not be unexpected for cells (e.g. bacteria) or undifferentiated tissue (e.g. during cleavage) but some of the highest specific growth rates in developing fish occur shortly after hatch when most tissues are fully differentiated and the majority of organ systems are formed.
夽 This paper is part of a special issue entitled “Energetics and Oxygen Transport Mechanisms in Embryos”, guest-edited by Dr. Jacopo P. Mortola. ∗ Tel.: +1 204 727 9608. E-mail address: [email protected] 1569-9048/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.resp.2011.04.026
From an evolutionary perspective, it is not surprising that embryonic growth is both highly efficient and rapid. The developing embryo in a cleidoic egg has a limited supply of energy and one would expect natural selection to optimize tissue production so as to produce the largest hatchling possible. All other things being equal, bigger hatchlings have a better chance of survival (Hendry et al., 2001). Predation pressure on hatchlings is usually strongly size-selective (e.g. Pepin, 1991). This tends to select for rapid as well as efficient growth since rapid growth minimizes the amount of time spent in the smaller more vulnerable sizewindows. While the nature of the forces selecting for rapid and efficient embryonic growth seems reasonably clear, the means by which this is accomplished are not. For example, while the average cumulative production efficiency during endogenous feeding is about 60%, there are numerous and apparently reliable reports of instantaneous production efficiencies in the range of 80–90% during the earlier stages of embryonic development (see Rombough, 1996, 2006; Kamler, 2008). How embryos are able to accommodate these high production efficiencies without violating the conservation of energy is a bit of a mystery. There is a similar problem when it comes to fitting activity costs within the aerobic scope of the organism. Developing fish, and presumably other vertebrates, have very limited aerobic scope (Rombough, 1988a; Killen et al., 2007). Hatchling rainbow trout, for example, do not appear to be able to elevate their metabolic rate more than about 20% above the routine level (Ninness et al., 2006). The difficulty is that embryos and larvae are often faced with increases in metabolic demand for energy to support activities like growth or movement which are in excess of what would appear to be able to be accommodated within their metabolic scope. Our current understanding of how developing organisms solve these and other related energetic problems is
P. Rombough / Respiratory Physiology & Neurobiology 178 (2011) 22–29
the subject of this review. Among other things, this review will look at the fuels used to support metabolic activity, how metabolizable energy is allocated, growth efficiencies, and how differences between the ways embryos and adults handle energy complicate attempts to model ontogenetic growth. Emphasis will be placed on evidence obtained from the study of developing fish. Aside from being my area of interest, fish have a number of advantages when it comes to studying developmental energetics. Fish eggs are inexpensive, easy to rear and can be obtained in large numbers. Their transparency makes it relatively easy to stage embryos and monitor physical activity. Most fish eggs are telolecithal (yolk concentrated at one end of the egg) which greatly facilitates separating yolk and tissue components. This permits accurate determination of yolkfree body mass which is critical when it comes to formulating energy budgets and estimating growth and activity costs. 2. Energy budgets In species with cleidoic eggs, the yolk is the only significant source of energy until exogenous feeding begins some time after hatch. There are reports of nutrient uptake directly from the environment for some aquatic species but amounts are small and the strategy does not appear to be widespread (Kamler, 2008). In contrast to exogenous food sources, very close to 100% of the yolk deposited in the egg is assimilated. The assimilated yolk provides both the building materials and the source of energy for growth and development. The balanced energy equation, A=P+R+E
(1)
where A is the assimilated energy, P is the production, R is the metabolism (respiration) and E is the excretion is used to describe how energy is partitioned among these components. The total amount of energy expended in support of metabolism (Rt ) can be further subdivided into that used to support growth (Rg ), tissue maintenance (Rm ) and other assorted activities (Ra ): Rt = Rg + Rm + Ra
(2)
The fraction of total metabolic energy (Rt ) devoted to each of the various activities varies depending on species, stage of development and a variety of environmental and behavioral factors, but averaged over the whole period of endogenous feeding normally Rg > Rm > Ra . Neuromuscular activity usually accounts for most of Ra . Estimates of the fraction of yolk energy lost due to excretion vary from about 2.5 to 16% for fishes (Rombough, 2006). Virtually all of this lost energy is in the form of nitrogenous wastes with the magnitude of the loss depending on whether it is in the form of ammonia, urea or uric acid. In the absence of actual data for a species, a reasonable consensus value for E would be ∼5%A. The law of the conservation of energy requires that energy equations balance on all time scales. This applies to “instantaneous” budgets for a particular moment in time as well as to cumulative budgets (e.g. from fertilization to hatching). In this regard, it is important to distinguish total costs for various activities from the unit costs for those activities and “instantaneous” total costs from summed or time-averaged total costs. 3. Assimilation As would be expected for a closed system with respect to energy, the yolk of cleidoic eggs is energy dense but with more variability than one would expect if the aim was solely to pack as much energy as possible into the space available. The energy density for fish eggs ranges from about 19.5 to 31 J mg dry mass (dm)−1 (mean = 26.9 J mg dm−1 ), a difference of about 59% (Kamler, 1992). This suggests that there are trade-offs between energy density and
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particular classes of nutrients needed to sustain development in different species. Proteins/amino acids, lipids and carbohydrates, in that order, are the major nutrients powering growth and development. Species are even more variable with respect to these nutrients than they are in terms of energy density. Kamler (1992) summarized the proximate composition of yolk for 45 species of fish. Proteins/amino acids ranged from 35 to 89% of dry mass (mean = 66%), lipids from 3 to 54% of dry mass (mean = 19%) and carbohydrates from 0.6 to 8.6% of dry mass (mean = 2.6%). Despite these differences in yolk composition, the end result appears to be about the same in terms of the fraction of energy ending up as tissue. Rombough (1996) reported an average production efficiency (P/A) during endogenous feeding of 60.1 ± 2.9% for 21 species of fish (mean ± 95% CI, n = 92 [many species represented more than once]). This is consistent with the idea that natural selection is acting to maximize tissue production. One particularly notable difference in yolk composition is the high levels of free amino acids in eggs of marine teleosts (up to 50% total dry mass; Finn and Fyhn, 2010). Embryos of marine teleosts use free amino acids as organic osmolytes to help regulate water balance prior to their definitive adult osmoregulatory organs (kidney, gut and gills) coming online (Finn et al., 1995). Free-amino acids have the added advantage that they are more readily incorporated into tissue than yolk proteins (Rojas-Garcia and Ronnestad, 2003) and can be used as fuel. Fuel selection has important energetic implications (Weber, 2011). Among other things the type of fuel determines the rate of power production. ATP can be produced about 50% faster aerobically and 300% faster anaerobically using carbohydrates as fuel rather than lipids. Fish eggs generally have small carbohydrate reserves (∼2.5 mass%), probably because of its low energy density (∼1/5th lipids). What carbohydrate there is appears to be conserved for periods when high metabolic intensities are required, for example during cleavage and epiboly (Smith, 1952; Finn and Fyhn, 2010). Developing trout also have been shown to switch to carbohydrates during the hatching process and near the end of yolk absorption (Smith, 1952), both periods of high physical activity. Overall, lipids are the dominant fuel in freshwater fishes while free amino acids/proteins are the major fuel in marine teleosts (Kamler, 2008; Finn and Fyhn, 2010). What is interesting is that even in freshwater fish a significant fraction of protein is utilized as fuel rather than being conserved for incorporation into tissue. For example, about 32% of total energy expenditure during endogenous feeding in rainbow trout is supplied by protein catabolism (Smith, 1952). There appear to be at least two reasons for this. In the absence of carbohydrates, a certain amount of amino acid catabolism is required to sustain Krebs cycle intermediates (Weber, 2011). Amino acids are intermediate between carbohydrates and lipids in terms of energy density, water solubility and intracellular mobility (Weber, 2011). Depending on the amino acid, this may permit higher rates of ATP generation than would be possible with lipids.
4. Production As mentioned in Section 1, production is more efficient and takes place much more rapidly during embryonic development than it does later in life. Instantaneous production efficiencies are greatest during early embryonic development and tend to decline as development proceeds (Rombough, 1988b; Fig. 1). There are numerous reports for fish of production efficiencies (P/A) in excess of 85% during early embryonic development (see Rombough, 1988a; Yufera et al., 1999). A number of factors appear to contribute to high production efficiencies during these early stages. Freshly laid eggs contain maternally supplied stocks of complex organic molecules, RNA transcripts and growth factors (Finn and Fyhn, 2010). This should reduce the cost of production since these
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P. Rombough / Respiratory Physiology & Neurobiology 178 (2011) 22–29
100 6 ºC 9 ºC 12 ºC 15 ºC
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Age (% yolk utilized) Fig. 1. Changes in yolk conversion efficiency with age for steelhead trout Oncorhynchus mykiss. Data are from Rombough (1988b). P is energy devoted to production and R is energy devoted to respiration both expressed in the same units (i.e. Joules).
compounds would not have to be synthesized de novo. The availability of free amino acids may also play a role. Rojas-Garcia and Ronnestad (2003) reported the tissue assimilation rate in postlarval halibut Hippoglossus hippoglossus was 3 times greater for free amino acids than for amino acids derived from protein. Low maintenance costs are undoubtedly also important. The cost of tissue maintenance is proportional to tissue mass and since tissue mass is initially small, total maintenance costs should be correspondingly small. The decline in instantaneous production efficiencies with age appears to be due mostly to gradually increasing maintenance costs as the embryo becomes larger. Interestingly, in rainbow trout there are two distinct phases to this decline: a sharp decline during the first half of embryonic development and a more gradual decline during the rest of the endogenous feeding period (Fig. 1). The break point occurs near the end of organogenesis suggesting that having functioning organ systems reduces the overall costs of servicing tissues. Another possible reason for higher production efficiencies early in development may be a lower unit cost of assembly. As will be discussed in Section 5.3, there is evidence that the unit cost of producing tissue may be reduced at high specific (relative) growth rates. Specific growth rates (g) in developing fish are highest during early embryogenesis (Rombough, 1994). They appear to be relatively stable until shortly after blastopore closure at which point they begin to decline in a roughly exponential fashion. This decline continues, with a few “bumps”, until exogenous food supplies become available. 5. Metabolism 5.1. Total metabolic rate (Rt ) Embryonic growth and development in fish is powered almost entirely by aerobic metabolism (Rombough, 1988a; Pelster, 2008; Finn and Fyhn, 2010). This is reflected in the small size of glycogen reserves (Kamler, 2008), low activities for glycolytic enzymes (Hinterleitner et al., 1987), and low tissue lactate concentrations even when physically stressed (Ninness et al., 2006). Exotic anaerobic pathways utilizing amino acids appear to play little role (Finn and Fyhn, 2010). Anaerobic metabolism has been shown to be important in some species at specific stages, for example during epiboly (Finn and Fyhn, 2010) and while hatching (Ninness et al., 2006), but even after taking these expenditures into account
the anaerobic contribution to total energy production remains small. Mass-specific metabolic rates (metabolic intensities) are considerably higher during development than they are later in life (Rombough, 1988a). For example, the routine metabolic intensity of a newly hatched zebrafish (Danio rerio) is about 10-times the routine metabolic intensity of an adult (Barrionuevo and Burggren, 1999). To put this in perspective, the routine metabolic intensity of the newly hatched zebrafish (90–105 mol O2 g−1 h−1 , Pelster and Burggren, 1996) is higher than the aerobic maximum for adult yellowfin tuna Thunnus albacares (∼80 mol O2 g−1 h−1 ; Korsmeyer et al., 1996), one of the most metabolically and physically active non-homeothermic vertebrates known. High embryonic/larval metabolic intensities are supported by proportionately high massspecific activities for aerobic mitochondrial enzymes (Hinterleitner et al., 1987). Metabolic intensities vary between about 2- and 6-fold, depending on species and temperature, during the period of endogenous feeding (Rombough, 1988a). The pattern appears to be fairly consistent across fish species with peaks occurring during epiboly and shortly before yolk reserves begin to become limiting. Metabolic intensity is consistently low during mid to late organogenesis. These variations in metabolic intensity do not appear to be correlated with variations in specific growth rate (Rombough, 1994) and, at this point it is not known what is driving them. The overall scaling relationship between metabolic rate and tissue mass appears to be significantly different during embryonic/larval development than it is later in life. There is a fair amount of variability among species, but most estimates place the interspecific mean for the metabolic mass exponent in adult fish at between b = 0.80 (Gollish, 1995; Clarke and Johnston, 1999) and b = 0.88 (White et al., 2006). Estimates for interspecific mean values for fish during early life range from b = 0.9 (Rombough, 1988a) to b = 0.97 (Giguère et al., 1988), with many reliable reports for individual species of values ≥1.0. This led Giguère et al. (1988) to speculate that the underlying relationship during early life is for metabolic rate to scale isometrically with respect to body mass. The fact that oxidative enzymes also appear to scale isometrically for larvae of several fish species (Hinterleitner et al., 1987) tends to support this contention. Detailed examination of individual species indicates that the transition from massindependent metabolic intensity to mass-dependent metabolic intensity takes place fairly abruptly during the early juvenile phase (Post and Lee, 1996). What triggers this shift is not clear. One possible advantage of stable high metabolic intensities throughout the embryonic/larval period is that it permits higher rates of growth than would be possible if metabolic intensity declined with increasing body mass as it does later in life (Rombough, 2006). There is a strong correlation between maximum resting/routine metabolic intensities and growth rates at both the species (Wieser, 1994) and individual levels (Biro and Stamps, 2010). As mentioned in Section 1, hatchlings face particularly strong selective pressures to grow rapidly. Interestingly, metabolic scaling also appears to be close to unity for neonate mammals (Mortola, 2001). Developing fish appear to have very limited capacity to elevate their aerobic metabolic rate above the routine level (Rombough, 1988a, 2006; Killen et al., 2007). This appears to be particularly true during embryonic development. For example, a several hundredfold increase in the frequency of body movements during hatching in rainbow trout resulted in a <20% increase in the rate of oxygen consumption (Ninness et al., 2006). Aerobic scope tends to increase as development proceeds (Post and Lee, 1996; Killen et al., 2007) but even towards the end of yolk absorption factorial scopes (Rmax /Rr ) typically are not much more than 1.5–2.0 (Post and Lee, 1996; Killen et al., 2007). This creates problems when it comes to
trying to fit activity costs into the energy budget using a standard additive model of energy allocation. 5.2. Allocation of metabolic energy Additive models of energy allocation assume that energy costs associated with increased activity are met by proportional increases in the total rate of energy expenditure (Wieser, 1989). The slope of the relationship between activity level and total metabolic rate can then be used as an estimate of the unit cost of that particular activity (see Rombough, 2006 for illustrations of the method). The additive model works reasonably well for most juvenile and adult organisms, where it has been widely used to estimate unit costs for activities such as growth (e.g. Carter and Brafield, 1992) and locomotion (e.g. Brett, 1964). This method of estimating activity costs does not work, however, if total metabolic rate does not increase in direct proportion to amount of energy devoted to the activity (Wieser, 1989). In extreme cases, there may be virtually no increase in total metabolic rate, as appears to happen when newly hatched rainbow trout are forced to swim to exhaustion (Ninness et al., 2006) or salmon larvae have to expend energy continually righting themselves (Peterson and Martin-Robichaud, 1995). According to the additive model, these activities would appear to be essentially “free” (Pedersen, 1997) which of course is a thermodynamic impossibility. The crux of the problem lies in the inability of the organism to increase its metabolic rate enough to accommodate the additional costs. This dilemma can be circumvented, however, if energy is allocated to the task in a compensatory rather than additive fashion. In compensatory partitioning, the energy needed to support one activity is supplied at least in part by reducing energy expenditure in some other area. Wieser (1989) pointed out that this way of allocating energy was first documented more than a century ago and appears to be fairly widespread, if not generally appreciated. This lack of appreciation has led to some unrealistically low estimates for growth (e.g. Marsh et al., 2001) and other costs. Some of the best evidence for compensatory partitioning comes from attempts by Wieser and co-workers to estimate growth costs for rapidly growing cyprinid larvae (Wieser et al., 1988; Wieser and Medgyesy, 1990a,b). They noted that at low growth rates there was a direct correlation between metabolic intensity and specific growth rate as would be expected if partitioning was additive (Fig. 2). At some critical specific growth rate (∼8% day−1 in Fig. 2) however, the relationship changed abruptly to one where the two variables became independent of each other. This sudden plateauing of metabolic intensity was interpreted as indicating the larvae had reached their aerobic maximum. Since larvae could no longer increase their total energy output, they had to meet any additional costs associated with growth either by abruptly reducing the unit cost of growth (unlikely) or by reducing energy expenditures in some other area (i.e. by shifting to compensatory partitioning). Since then uncoupling between metabolic intensity and specific growth rate has been reported for larvae of pike Esox lucius (Wieser et al., 1992), Atlantic herring Clupea harengus (Houlihan et al., 1995), and African catfish Clarias gariepinus (Smith and Ottema, 2006) and for both embryos and endogenous feeding larvae of chinook salmon Oncorhynchus tshawytscha (Rombough, 1994). 5.3. Metabolic cost of growth (Rg ) The production of new tissue requires the expenditure of metabolic energy. Wieser (1994) estimated the theoretical minimum cost of producing tissue in cells at about 32 mg dm mmol−1 ATP. This is equivalent to 5.3 mol O2 mg dm−1 , 2.4 J mg dm−1 or about 11% (J J−1 ) of the energy content of the tissue being formed. Wieser’s (1994) estimate was based on an energy density of
Apparent energy expended to support growth (µmol O2 g-1 h-1)
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Specific growth rate (% day -1) Fig. 2. Apparent energy expended to support growth (Rmax –Rs ) for cyprinid larvae growing at different rates. Rmax = maximum rate of energy expenditure, Rs = standard rate of energy expenditure. Data from Wieser and Medgyesy (1990a).
22 J mg dm−1 for the tissue being formed and a P:O ratio of 3.0 using glucose as fuel. He also assumed that preformed monomers were present in excess and included costs associated with RNA synthesis and turnover and monomer and ion transport as well as the direct cost of linking monomers to form polymers. Calow’s (1977) estimate of 4.7% (J J−1 ) is sometimes cited as the theoretical minimum cost of growth but this value does not take into account activities such as RNA synthesis and intracellular transport making it unrealistically low under in vivo conditions. Empirical measurements of the unit cost of growth in organisms are typically about 3-times Wieser’s (1994) theoretical minimum cost. Based on an extensive survey of the literature for bacteria, protozoans and ectothermic metazoans, Wieser (1994) suggested that a reasonable “consensus value” for living organisms was about 16 mol O2 g dm−1 . This is equivalent to an apparent net cost of growth (Rg /P) of 33% and an apparent net growth efficiency [P/(P + Rg )] of 75%. The average cost of growth in fish larvae appears to be close to this consensus value. Wieser (1994) reported an average cost of 16.7 mol O2 g dm−1 for larvae of 10 species of marine teleosts. Rombough (2006) arrived at a mean of 20 mol O2 g dm−1 based on reports for 7 different species. Averaged over the whole period of endogenous feeding, embryos/larvae should have no trouble fitting growth costs into their energy budget. As mentioned in Section 1, cumulative production efficiency (P/A) to the end of yolk absorption averages about 60% (Needham, 1931). Assuming Wieser’s consensus value for Rg /P of 33%, this equates to a total expenditure in support of growth (material + construction costs) of about 80% of the energy content of the yolk (A). A problem arises, however, at higher production efficiencies. At a P/A of 75%, 100% of total yolk energy would have to be devoted to P + Rg leaving no energy for other essential activities (e.g. morphogenetic movements, differentiation, tissue maintenance, physical activity) or for excretory losses. As mentioned in Section 4, there are many reliable reports of production efficiencies greater than 75% at certain stages of development. Organisms must somehow be able to reduce their unit cost of growth below the consensus value to fit into the energy budget during these periods. Reducing COG to Wieser’s theoretical minimum of 11% for Rg /P would permit production efficiencies of up to 90%, which would account for most of the reports of high P/A. This assumes, of course, that the unit cost of growth can be reduced.
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Relative rate of protein synthesis (mg P·g P-1·h-1) Fig. 3. Relationships between unit cost of tissue or protein (P) growth and specific growth rate. (A) Data for various aquatic ectotherms from Wieser (1994). dbm = dry body mass. (B) Data for fish cells and larvae from Smith and Ottema (2006). Solid lines and equations are for the lines of best fit to the data assuming an exponential decline to a minimum. Dashed lines are for total cost of tissue or protein growth calculated by multiplying the unit cost by the rate of growth.
There is evidence that the unit cost of growth is indeed variable. Wieser (1994) reported that the unit cost of growth and specific growth rate appeared to be negatively correlated in small, fast growing vertebrates and invertebrates (Fig. 3A). Smith and Ottema (2006) recently arrived at the same conclusion using data on protein synthesis rates in cultured fish cells and rapidly growing fish larvae (Fig. 3B). Interestingly, both data sets project to similar asymptotic values (11 and 14 mol O2 mg dm−1 , respectively) equivalent to a value for Rg /P of about 24%. Theoretically, this could support production efficiencies of up to 80%, which would be enough to explain some but not all the reports of high P/A. There is obviously more going on than these data indicate but what that is remains unclear. One possibility is that embryos are making use of preformed elements assembled either maternally (many of the reports of high P/A are for early embryogenesis) or during periods of slower growth (e.g. the period just prior to hatch). Two possible mechanisms have been proposed to explain the reduction in unit COG at high specific growth rates. Smith and Ottema (2006), building on the work of Pannevis and Houlihan (1992), have implicated increased RNA translational efficiency. Pannevis and Houlihan (1992) speculated that there were two main components to the cost of protein synthesis (the main driver of tissue growth): (1) fixed costs associated with RNA synthesis and the like and (2) variable costs associated with number of peptide bonds formed. Smith and Ottema (2006) reported a direct relationship between the translational efficiency of RNA (g protein g RNA−1 day−1 ) and specific growth rate (g) in African catfish larvae where a doubling of g resulted in ∼3-fold increase in translational efficiency. The other mechanism that has been pro-
posed to explain decreased unit COG at high specific growth rates is an increase in protein retention efficiency (Pace and Manahan, 2007). Pace and Manahan (2007) reported that the energetic cost of protein synthesis appear to be fixed in larvae of the sea urchin Asterina miniata, but that the unit cost of protein deposition (i.e. growth) could be up to 3-fold lower in rapidly growing larvae than in more slowly growing larvae. This appeared to be a direct reflection of higher protein retention efficiencies (up to 80%) in the more rapidly growing larvae. It is not clear if this applies to fish larvae (embryos have not been looked at). Rombough (2006) surveyed the literature and concluded that, except for one anomalously high value of 94%, there was no significant difference between retention efficiencies in rapidly growing larvae (mean = 55.2%) and much more slowly growing juveniles (mean = 53.1%). To further confuse the issue, the study that reported the 94% value found an inverse relationship between retention efficiency and specific growth rate (Conceic¸ão et al., 1997b). One corollary that appears to arise from an exponential decrease in the unit COG with increasing g is that there may be an optimum or at least a “sweet spot” for minimizing the total cost of growth. The total cost of growth is the product of the unit COG and the rate of growth. Smith and Ottema (2006) reported a distinct minimum with respect to total costs at a protein synthesis rate of about 3 mg P g−1 h−1 (Fig. 3B). Wieser’s (1994) data did not yield a distinct minimum but there was an inflection point at a specific growth rate of 5.4 mg dm g−1 h−1 (Fig. 3A). At present there is no evidence that developing organisms do or even can adjust their growth rates to take advantage of these “minima” (which themselves need to be confirmed). Even if they could, the overall impact on embryonic energetics would likely be small (especially in the case of Wieser’s data) and quickly swamped by the increasing amounts of energy that need to be directed to support tissue once it is formed (i.e. Rm ). 5.4. Maintenance metabolism (Rm ) Organisms have to expend a certain amount of energy maintaining tissue once it has been formed. In cells, the major maintenance costs are those associated with protein turnover, the proton pump, the Na+ and Ca2+ pumps and RNA synthesis, in that order (Siems et al., 1992). The types and ranking of activities supported by maintenance metabolism appear to be similar in whole organisms. Rolfe and Brown (1997) reported that the four most energy demanding activities supported by standard metabolism (Rs ) in adult mammals were protein turnover (19% Rs ), the mitochondrial proton leak (18% Rs ), the maintenance of Na+ gradients (16.5% Rs ) and whole-body service functions (18% Rs ). The situation is probably similar during development in terms of types of activities (Rs in adults is roughly analogous to Rm in embryos, see Rombough, 2006), although the relative amount of energy directed towards each if likely to be somewhat different. The costs associated with service functions (e.g. osmoregulation or gas exchange), for example, are going to vary depending on whether the services are being performed locally (i.e. at the cellular level) or centrally (e.g. in the kidney or gill). The amount of energy devoted to maintenance increases in proportion to tissue mass (Fig. 4). At this point, however, it is not clear precisely what the scaling relationship is for Rm during development. Most investigators have assumed direct proportionality (e.g. Smith, 1957; Rombough, 1994; Mortola and Cooney, 2008), but a value of b = 0.75 based on an assumption of fractal scaling has also been proposed (e.g. Hou et al., 2008). A major problem in settling this dispute is the difficulty of isolating Rm from the other contributors to Rt . Mortola and Cooney (2008) pointed out that the fact that models assuming direct proportionality (i.e. b = 1.0) “work”, in the sense that they give reasonable estimates for things like the cost of growth, is strong evidence for isometric scaling of Rm . Rombough
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Age (days postfertilization) Fig. 4. Main graph: Rates of total oxygen consumption (Rt ) and oxygen consumption associated with tissue maintenance (Rm ) for chicken embryos incubated at 38 ◦ C. Inset: Proportion of total metabolic energy expenditure devoted to maintenance as a function of age. Data from Mortola and Cooney (2008).
and Houlihan (reported in Rombough, 2006) attempted to isolate Rm by using inhibitors to block neuromuscular activity and protein synthesis in recently hatched zebrafish. Rm was found to scale isometrically with respect to tissue mass, but the size range examined varied only about 2-fold which begs the question of whether this relationship would hold over a broader size range. Cunha et al. (2007) used starvation and lack of light to suppress Rg and Ra in early turbot (Scophthalmus maximus) larvae. They reported a mass exponent of b = 0.71 for what they termed resting metabolism. This value is not significantly different from the fractal value (b = 0.75) but again the size range was relatively small (∼8-fold, but only 3 sizes) and it is not clear if all stages responded equivalently to the treatment. As an aside, Cunha et al. (2007) found that both Rg and Ra exhibited positive allometry (b = 1.28 and b = 1.30, respectively) suggesting that there may have been a trade-off between Rm and Rg and Ra . The increasing amount of energy devoted to maintenance results in gradually decreasing production efficiencies (P/A) as ever more tissue is deposited (Fig. 1). It also means that species with embryos that develop more slowly or hatch at a larger size tend to require more energy on a mass-specific basis to reach an equivalent stage of development (Fig. 5). This does not necessarily mean that more slowly developing or larger species have lower production efficiencies. What appears to happen is that increases in R are balanced by increases in A such that P/A remains relatively stable. If this did not occur, one would expect to see much lower production efficiencies in species with large eggs (e.g. birds) than in those with small eggs (e.g. fish) not the taxon-independence actually observed (Needham, 1931). A similar balancing occurs in response to temperature-induced changes in the duration of the incubation period. In developing fish, the temperature-sensitivities (measured as Q10 ) for metabolic rate, growth rate and the rate of yolk absorption are all essentially the same (Table 1). The net result is that production efficiency (P/A) is effectively independent of temperature (Rombough, 1996). 5.5. Activity metabolism (Ra ) The amount of energy devoted to activities other than growth and maintenance appears to be the most variable component of
Fig. 5. Cumulative cost of tissue production from fertilization to hatch for various fish and amphibian species. Data from Mueller et al. (2011) are plotted against hatchling yolk-free dry mass (bottom axis) and duration of the incubation period (top axis). Linear regressions relating cumulative cost to hatchling mass (M) and incubation period (D) are shown. Projections of these lines to zero mass or incubation period provides an estimate of ∼11.2 mol O2 mg dtm−1 for the average instantaneous cost of growth (compare with estimates in Fig. 3). dtm = dry tissue mass.
the energy budget. Ra encompasses a variety of different types of activities but the two most energy demanding ones are neuromuscular activity and resisting stress arising from non-optimal conditions. Of these we know most about neuromuscular activity. The total amount of energy devoted to body movements prior to hatch appears to be relatively low based on observations of how often embryos move (e.g. Ninness et al., 2006) and the fact that energy budgets come close to balancing if Ra is completely omitted from the calculation. This is not the case with endogenously feeding larvae which can devote a large fraction of their total energy expenditure to movement. For example, at hatch zebrafish larvae devote about 25% of Rt to locomotion; this proportion increases to about 50% by the end of yolk absorption (Rombough, 2006). Because of the relatively small aerobic scope of most larvae, increasing Ra typically requires some kind of trade-off. With zebrafish (Rombough, 2006) and Atlantic salmon Salmo salar (Peterson and Martin-Robichaud, 1995) larvae, the trade-off is with energy normally devoted to growth. The result is smaller larvae. The trade-off in turbot appears to involve a reduction in resting metabolism, which is similar but not identical to Rm (Cunha et al., 2007). 6. Modeling Because the egg is a closed system with respect to energy, it would appear to be a relatively simple task to develop accurate energetic models for embryonic growth. Indeed, over the past Table 1 Temperature sensitivities (Q10 s) for various embryonic rate functions in developing fish. Mean values are from Rombough (1996) except that for the rate of yolk absorption which is from Heming and Buddington (1988). Rate function
Development rate (to hatch) Metabolic rate (mass-specific) Growth rate (mass-specific) Yolk absorption rate
Q10 Within species mean
Cross-species mean
3.7 (n = 37) 3.0 (n = 34) 3.0 (n = 19) 2.9 (n = 23)
3.1 (n = 171) 2.0 (n = 100) 1.9 (n = 106)
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P. Rombough / Respiratory Physiology & Neurobiology 178 (2011) 22–29
50–60 years there have been numerous attempts to do just that. Some of the earliest models, for example those of von Bertalanffy (1957) and Smith (1957), are still relevant today. In general, the models fall into two categories: (1) descriptive models that do a good job of accurately predicting events but provide little insight and (2) mechanistic models that attempt to provide insight but sometimes yield questionable results. In recent years the pendulum has swung towards mechanistic models (e.g. West et al., 2001; Makarieva et al., 2004; Hou et al., 2008). Many of these mechanistic models are developed from “1st principles”; unfortunately these “principles” do not always reflect biological reality as it plays out during early life. All the models to date that I know of assume that energy is partitioned in an additive fashion. As I have tried to point out in this review, there is strong evidence that this is not always, or even normally, the case. Embryos and larvae appear to use a combination of additive and compensatory partitioning. Existing models also assume a constant unit cost for growth. Again, this does not always appear to be so. Many of the models assume that metabolic rate scales with tissue mass according to the 3/4 power “law”. This is demonstrably not true for routine metabolism and may or may not be true for maintenance metabolism. Finally, the majority of ontogenetic growth models treat organisms as only being capable of reacting to the physical environment in a simple monotonic fashion. This ignores the vast body of literature dealing with how natural selection has given rise to adaptations that allow organisms to “escape the tyranny” of physical factors such as temperature and geometry (e.g. Makarieva et al., 2005). Evolution, if nothing else, has proven to be ingenious. We will have to be equally ingenious when it comes to incorporating the complexities of embryonic life into models of ontogenetic growth.
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Hou, C., Zuo, W., Moses, M.E., Woodruff, W.H., Brown, J.H., West, G.B., 2008. Energy uptake and allocation during ontogeny. Science 322, 736–739. Houlihan, D.R., Pedersen, B.H., Steffensen, J.F., Brechin, J., 1995. Protein synthesis, growth and energetics in larval herring (Clupea harengus) at different feeding regimes. Fish Physiol. Biochem. 14, 195–208. Kamler, E., 1992. Early Life History of Fish: An Energetics Approach. Chapman & Hall, London, 267 pp. Kamler, E., 2008. Resource allocation in yolk-feeding fish. Rev. Fish Biol. Fish. 18, 143–200. Killen, S.S., Costa, I., Brown, J.A., Gamperl, A.K., 2007. Little left in the tank: metabolic scaling in marine teleosts and its implications for aerobic scope. Proc. R. Soc. 274B, 431–438. Korsmeyer, K.E., Dewar, H., Lai, N.C., Graham, J.B., 1996. The aerobic capacity of tunas: adaptations for multiple metabolic demands. Comp. Biochem. Physiol. 113A, 17–24. Makarieva, A.M., Gorshkov, V.G., Li, B.-L., 2004. Ontogenetic growth: models and theory. Ecol. Model. 176, 15–26. Makarieva, A.M., Gorshkov, V.G., Li, B.-L., 2005. Energetics of the smallest: do bacteria breathe at the same rate as whales? Proc. R. Soc. 272B, 2325–2328. Marsh, A.G., Maxson Jr., R.E., Manahan, D.T., 2001. High macromolecular synthesis with low metabolic cost in Antarctic sea urchin embryos. Science 291, 1950–1952. Mortola, J.P., 2001. Respiratory Physiology of Newborn Mammals. The Johns Hopkins University Press, Baltimore, MD. Mortola, J.P., Cooney, E., 2008. Cost of growth and maintenance in chicken embryos during normoxic or hypoxic conditions. Respir. Physiol. Neurobiol. 162, 223–229. Mueller, C.A., Joss, J.M.P., Seymour, R.S., 2011. The energy cost of embryonic development in fishes and amphibians, with emphasis on new data from the Australian lungfish, Neoceratodus fosteri. J. Comp. Physiol. 181B, 43–52. Needham, N.J., 1931. Chemical Embryology (With Appendices by Dorothy Moyle Needham and Muriel Elaine Robinson), 3 vols. Cambridge University Press, Cambridge, pp. xxi, xiv, xiv, 2021, pl. XII. Ninness, M.M., Stevens, E.D., Wright, P.A., 2006. Energy expenditure during hatching in rainbow trout (Oncorhynchus mykiss) embryos. Can. J. Fish. Aquat. Sci. 63, 1405–1413. Pace, D.A., Manahan, D.T., 2007. Efficiencies and costs of larval growth in different food environments (Asteroidea: Asterina miniata). J. Exp. Mar. Biol. Ecol. 353, 89–106. Pannevis, M.C., Houlihan, D.F., 1992. The energetic cost of protein synthesis in isolated hepatocytes of rainbow trout (Oncorhynchus mykiss). J. Comp. Physiol. 162B, 393–400. Pedersen, B.H., 1997. The cost of growth in young fish larvae, a review of new hypotheses. Aquaculture 155, 259–269. Pelster, B., Burggren, W.W., 1996. Disruption of hemoglobin in oxygen transport does not impact oxygen dependent physiological processes in developing embryos of zebrafish (Danio rerio). Circ. Res. 79, 358–363. Pelster, B., 2008. Gas exchange. In: Finn, R.N., Kapoor, B.G. (Eds.), Fish Larval Physiology. Science Publishers, Enfield, NH, USA, pp. 91–117. Pepin, P., 1991. Effect of temperature and size on development, mortality and survival rates of the pelagic early life history stages of marine fish. Can. J. Fish. Aquat. Sci. 58, 503–518. Peterson, R.H., Martin-Robichaud, D.J., 1995. Yolk utilization by Atlantic salmon (Salmo salar L.) alevins in response to temperature and substrate. Aquacult. Eng. 14, 85–99. Post, J.R., Lee, J.A., 1996. Metabolic ontogeny of teleost fishes. Can. J. Fish. Aquat. Sci. 53, 910–923. Rojas-Garcia, C.R., Ronnestad, I., 2003. Assimilation of dietary free amino acids, peptides and protein in post-larval Atlantic halibut (Hippoglossus hippoglossus). Mar. Biol. 142, 801–808. Rolfe, D.R.S., Brown, G.C., 1997. Cellular energy utilization and molecular origin of standard metabolic rate in mammals. Physiol. Rev. 77, 731–758. Rombough, P.J., 1988a. Respiratory gas exchange, aerobic metabolism and effects of hypoxia during early life. In: Hoar, W.S., Randall, D.J. (Eds.), Fish Physiology. Academic Press, San Diego, pp. 59–161. Rombough, P.J., 1988b. Growth, aerobic metabolism, and dissolved oxygen requirements of embryos and alevins of steelhead, Salmo gairndneri. Can. J. Zool. 66, 651–660. Rombough, P.J., 1994. Energy partitioning during fish development: additive or compensatory allocation of energy to support growth? Funct. Ecol. 8, 178– 186. Rombough, P.J., 1996. The effects of temperature on embryonic and larval development. In: Wood, C.M., McDonald, D.G. (Eds.), Global Warming: Implications for Freshwater and Marine Fish. Cambridge University Press, Cambridge, pp. 177–223. Rombough, P.J., 2006. Developmental costs and partitioning of metabolic energy. In: Warburton, S.J., Burggren, W.W., Pelster, B., Reiber, C.L., Spicer, J. (Eds.), Comparative Developmental Physiology Contributions, Tools and Trends. 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Wieser, W., Forstner, H., Schiemer, F., Mark, W., 1988. Growth-rates and growth efficiencies in larvae and juveniles of Rutilus rutilus and other cyprinids: effects of temperature and food in the field. Can. J. Fish. Aquat. Sci. 45, 943–950. Wieser, W., Laich, A., Medgyesy, N., 1992. Energy allocation and yield and cost of growth in young Esox lucius and Coregonus lavaretus (Teleostei): influence of species, prey type and body size. J. Exp. Biol. 169, 165–179. Wieser, W., Medgyesy, N., 1990a. Aerobic maximum for growth in the larvae and juveniles of a cyprinid fish Rutilus rutilus (L.): implications for energy budgeting in small poikilotherms. Funct. Ecol. 4, 233–242. Wieser, W., Medgyesy, N., 1990b. Cost and efficiency of growth in the larvae of two species of fish with widely different metabolic rates. Proc. R. Soc. 242B, 51–56. Yufera, M., Parra, G., Santiago, R., Carrascosa, M., 1999. Growth, carbon, nitrogen and caloric content of Solea senegalensis (Pisces: Soleidae) from egg fertilization to metamorphosis. Mar. Biol. 134, 43–49.
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Review
The energetics of embryonic growth夽 Peter Rombough ∗ Department of Biology, Brandon University, Brandon, MB R7A 6A9, Canada
a r t i c l e
i n f o
Article history: Accepted 28 April 2011 Keywords: Embryonic development Bioenergetics Cost of growth Energy partitioning Production efficiency Metabolic scaling Metabolic scope
a b s t r a c t Embryos typically operate under much tighter energy constraints than older animals. This has had a profound impact on how energy is stored, mobilized and partitioned. The result is sometimes quite different ways of doing things. Growth, in particular, is a much more important activity during development. Compared with adults, specific growth rates (g) are extremely high (≥150% day−1 for some fish). Production efficiencies are also much higher, particularly for early stages where values of 80–90% are not uncommon. Higher production efficiencies are possible, in part, because of lower unit costs at high g. Unlike in adults, the unit cost of growth does not appear to be fixed during early life. Energy also tends to be partitioned in a different manner, with compensatory partitioning being much more important during early life. Other differences include much higher routine metabolic intensities, smaller aerobic scopes and approximately isometric scaling of routine metabolism. The implications for ontogenetic growth models are discussed. © 2011 Elsevier B.V. All rights reserved.
1. Introduction Growth is the dominant energy-demanding activity during embryonic and larval development. In cleidoic eggs (enclosed eggs where gases, water and metabolic wastes, but no energy are exchanged with the environment, e.g. birds, most fish), an average of 60% of the initial energy content of the yolk is converted into tissue by the end of yolk absorption (Needham, 1931; Finn and Fyhn, 2010). An additional 20% or so of yolk energy is required to construct the new tissue (Wieser, 1994; Rombough, 2006). In total, about 80% of the initial energy content of the yolk is directed towards growth. If one subtracts the fraction of energy lost in metabolic waste products, about 5%, this leaves only ∼15% of initial yolk energy to support all of the other activities taking place during embryonic/larval development. The speed with which yolk is typically converted into tissue is also noteworthy. Specific growth rates in excess of 150% day−1 have been reported for larvae of some fish species (e.g. Conceic¸ão et al., 1997a; Smith and Ottema, 2006), but even the more typical rates of 10–30% day−1 greatly exceed anything observed in juvenile or adult fish. Such high rates of growth might not be unexpected for cells (e.g. bacteria) or undifferentiated tissue (e.g. during cleavage) but some of the highest specific growth rates in developing fish occur shortly after hatch when most tissues are fully differentiated and the majority of organ systems are formed.
夽 This paper is part of a special issue entitled “Energetics and Oxygen Transport Mechanisms in Embryos”, guest-edited by Dr. Jacopo P. Mortola. ∗ Tel.: +1 204 727 9608. E-mail address: [email protected] 1569-9048/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.resp.2011.04.026
From an evolutionary perspective, it is not surprising that embryonic growth is both highly efficient and rapid. The developing embryo in a cleidoic egg has a limited supply of energy and one would expect natural selection to optimize tissue production so as to produce the largest hatchling possible. All other things being equal, bigger hatchlings have a better chance of survival (Hendry et al., 2001). Predation pressure on hatchlings is usually strongly size-selective (e.g. Pepin, 1991). This tends to select for rapid as well as efficient growth since rapid growth minimizes the amount of time spent in the smaller more vulnerable sizewindows. While the nature of the forces selecting for rapid and efficient embryonic growth seems reasonably clear, the means by which this is accomplished are not. For example, while the average cumulative production efficiency during endogenous feeding is about 60%, there are numerous and apparently reliable reports of instantaneous production efficiencies in the range of 80–90% during the earlier stages of embryonic development (see Rombough, 1996, 2006; Kamler, 2008). How embryos are able to accommodate these high production efficiencies without violating the conservation of energy is a bit of a mystery. There is a similar problem when it comes to fitting activity costs within the aerobic scope of the organism. Developing fish, and presumably other vertebrates, have very limited aerobic scope (Rombough, 1988a; Killen et al., 2007). Hatchling rainbow trout, for example, do not appear to be able to elevate their metabolic rate more than about 20% above the routine level (Ninness et al., 2006). The difficulty is that embryos and larvae are often faced with increases in metabolic demand for energy to support activities like growth or movement which are in excess of what would appear to be able to be accommodated within their metabolic scope. Our current understanding of how developing organisms solve these and other related energetic problems is
P. Rombough / Respiratory Physiology & Neurobiology 178 (2011) 22–29
the subject of this review. Among other things, this review will look at the fuels used to support metabolic activity, how metabolizable energy is allocated, growth efficiencies, and how differences between the ways embryos and adults handle energy complicate attempts to model ontogenetic growth. Emphasis will be placed on evidence obtained from the study of developing fish. Aside from being my area of interest, fish have a number of advantages when it comes to studying developmental energetics. Fish eggs are inexpensive, easy to rear and can be obtained in large numbers. Their transparency makes it relatively easy to stage embryos and monitor physical activity. Most fish eggs are telolecithal (yolk concentrated at one end of the egg) which greatly facilitates separating yolk and tissue components. This permits accurate determination of yolkfree body mass which is critical when it comes to formulating energy budgets and estimating growth and activity costs. 2. Energy budgets In species with cleidoic eggs, the yolk is the only significant source of energy until exogenous feeding begins some time after hatch. There are reports of nutrient uptake directly from the environment for some aquatic species but amounts are small and the strategy does not appear to be widespread (Kamler, 2008). In contrast to exogenous food sources, very close to 100% of the yolk deposited in the egg is assimilated. The assimilated yolk provides both the building materials and the source of energy for growth and development. The balanced energy equation, A=P+R+E
(1)
where A is the assimilated energy, P is the production, R is the metabolism (respiration) and E is the excretion is used to describe how energy is partitioned among these components. The total amount of energy expended in support of metabolism (Rt ) can be further subdivided into that used to support growth (Rg ), tissue maintenance (Rm ) and other assorted activities (Ra ): Rt = Rg + Rm + Ra
(2)
The fraction of total metabolic energy (Rt ) devoted to each of the various activities varies depending on species, stage of development and a variety of environmental and behavioral factors, but averaged over the whole period of endogenous feeding normally Rg > Rm > Ra . Neuromuscular activity usually accounts for most of Ra . Estimates of the fraction of yolk energy lost due to excretion vary from about 2.5 to 16% for fishes (Rombough, 2006). Virtually all of this lost energy is in the form of nitrogenous wastes with the magnitude of the loss depending on whether it is in the form of ammonia, urea or uric acid. In the absence of actual data for a species, a reasonable consensus value for E would be ∼5%A. The law of the conservation of energy requires that energy equations balance on all time scales. This applies to “instantaneous” budgets for a particular moment in time as well as to cumulative budgets (e.g. from fertilization to hatching). In this regard, it is important to distinguish total costs for various activities from the unit costs for those activities and “instantaneous” total costs from summed or time-averaged total costs. 3. Assimilation As would be expected for a closed system with respect to energy, the yolk of cleidoic eggs is energy dense but with more variability than one would expect if the aim was solely to pack as much energy as possible into the space available. The energy density for fish eggs ranges from about 19.5 to 31 J mg dry mass (dm)−1 (mean = 26.9 J mg dm−1 ), a difference of about 59% (Kamler, 1992). This suggests that there are trade-offs between energy density and
23
particular classes of nutrients needed to sustain development in different species. Proteins/amino acids, lipids and carbohydrates, in that order, are the major nutrients powering growth and development. Species are even more variable with respect to these nutrients than they are in terms of energy density. Kamler (1992) summarized the proximate composition of yolk for 45 species of fish. Proteins/amino acids ranged from 35 to 89% of dry mass (mean = 66%), lipids from 3 to 54% of dry mass (mean = 19%) and carbohydrates from 0.6 to 8.6% of dry mass (mean = 2.6%). Despite these differences in yolk composition, the end result appears to be about the same in terms of the fraction of energy ending up as tissue. Rombough (1996) reported an average production efficiency (P/A) during endogenous feeding of 60.1 ± 2.9% for 21 species of fish (mean ± 95% CI, n = 92 [many species represented more than once]). This is consistent with the idea that natural selection is acting to maximize tissue production. One particularly notable difference in yolk composition is the high levels of free amino acids in eggs of marine teleosts (up to 50% total dry mass; Finn and Fyhn, 2010). Embryos of marine teleosts use free amino acids as organic osmolytes to help regulate water balance prior to their definitive adult osmoregulatory organs (kidney, gut and gills) coming online (Finn et al., 1995). Free-amino acids have the added advantage that they are more readily incorporated into tissue than yolk proteins (Rojas-Garcia and Ronnestad, 2003) and can be used as fuel. Fuel selection has important energetic implications (Weber, 2011). Among other things the type of fuel determines the rate of power production. ATP can be produced about 50% faster aerobically and 300% faster anaerobically using carbohydrates as fuel rather than lipids. Fish eggs generally have small carbohydrate reserves (∼2.5 mass%), probably because of its low energy density (∼1/5th lipids). What carbohydrate there is appears to be conserved for periods when high metabolic intensities are required, for example during cleavage and epiboly (Smith, 1952; Finn and Fyhn, 2010). Developing trout also have been shown to switch to carbohydrates during the hatching process and near the end of yolk absorption (Smith, 1952), both periods of high physical activity. Overall, lipids are the dominant fuel in freshwater fishes while free amino acids/proteins are the major fuel in marine teleosts (Kamler, 2008; Finn and Fyhn, 2010). What is interesting is that even in freshwater fish a significant fraction of protein is utilized as fuel rather than being conserved for incorporation into tissue. For example, about 32% of total energy expenditure during endogenous feeding in rainbow trout is supplied by protein catabolism (Smith, 1952). There appear to be at least two reasons for this. In the absence of carbohydrates, a certain amount of amino acid catabolism is required to sustain Krebs cycle intermediates (Weber, 2011). Amino acids are intermediate between carbohydrates and lipids in terms of energy density, water solubility and intracellular mobility (Weber, 2011). Depending on the amino acid, this may permit higher rates of ATP generation than would be possible with lipids.
4. Production As mentioned in Section 1, production is more efficient and takes place much more rapidly during embryonic development than it does later in life. Instantaneous production efficiencies are greatest during early embryonic development and tend to decline as development proceeds (Rombough, 1988b; Fig. 1). There are numerous reports for fish of production efficiencies (P/A) in excess of 85% during early embryonic development (see Rombough, 1988a; Yufera et al., 1999). A number of factors appear to contribute to high production efficiencies during these early stages. Freshly laid eggs contain maternally supplied stocks of complex organic molecules, RNA transcripts and growth factors (Finn and Fyhn, 2010). This should reduce the cost of production since these
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100 6 ºC 9 ºC 12 ºC 15 ºC
Conversion efficiency -1 [100 (P(P+R) )]
80
60
40
20
0 0
20
40
60
80
100
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Age (% yolk utilized) Fig. 1. Changes in yolk conversion efficiency with age for steelhead trout Oncorhynchus mykiss. Data are from Rombough (1988b). P is energy devoted to production and R is energy devoted to respiration both expressed in the same units (i.e. Joules).
compounds would not have to be synthesized de novo. The availability of free amino acids may also play a role. Rojas-Garcia and Ronnestad (2003) reported the tissue assimilation rate in postlarval halibut Hippoglossus hippoglossus was 3 times greater for free amino acids than for amino acids derived from protein. Low maintenance costs are undoubtedly also important. The cost of tissue maintenance is proportional to tissue mass and since tissue mass is initially small, total maintenance costs should be correspondingly small. The decline in instantaneous production efficiencies with age appears to be due mostly to gradually increasing maintenance costs as the embryo becomes larger. Interestingly, in rainbow trout there are two distinct phases to this decline: a sharp decline during the first half of embryonic development and a more gradual decline during the rest of the endogenous feeding period (Fig. 1). The break point occurs near the end of organogenesis suggesting that having functioning organ systems reduces the overall costs of servicing tissues. Another possible reason for higher production efficiencies early in development may be a lower unit cost of assembly. As will be discussed in Section 5.3, there is evidence that the unit cost of producing tissue may be reduced at high specific (relative) growth rates. Specific growth rates (g) in developing fish are highest during early embryogenesis (Rombough, 1994). They appear to be relatively stable until shortly after blastopore closure at which point they begin to decline in a roughly exponential fashion. This decline continues, with a few “bumps”, until exogenous food supplies become available. 5. Metabolism 5.1. Total metabolic rate (Rt ) Embryonic growth and development in fish is powered almost entirely by aerobic metabolism (Rombough, 1988a; Pelster, 2008; Finn and Fyhn, 2010). This is reflected in the small size of glycogen reserves (Kamler, 2008), low activities for glycolytic enzymes (Hinterleitner et al., 1987), and low tissue lactate concentrations even when physically stressed (Ninness et al., 2006). Exotic anaerobic pathways utilizing amino acids appear to play little role (Finn and Fyhn, 2010). Anaerobic metabolism has been shown to be important in some species at specific stages, for example during epiboly (Finn and Fyhn, 2010) and while hatching (Ninness et al., 2006), but even after taking these expenditures into account
the anaerobic contribution to total energy production remains small. Mass-specific metabolic rates (metabolic intensities) are considerably higher during development than they are later in life (Rombough, 1988a). For example, the routine metabolic intensity of a newly hatched zebrafish (Danio rerio) is about 10-times the routine metabolic intensity of an adult (Barrionuevo and Burggren, 1999). To put this in perspective, the routine metabolic intensity of the newly hatched zebrafish (90–105 mol O2 g−1 h−1 , Pelster and Burggren, 1996) is higher than the aerobic maximum for adult yellowfin tuna Thunnus albacares (∼80 mol O2 g−1 h−1 ; Korsmeyer et al., 1996), one of the most metabolically and physically active non-homeothermic vertebrates known. High embryonic/larval metabolic intensities are supported by proportionately high massspecific activities for aerobic mitochondrial enzymes (Hinterleitner et al., 1987). Metabolic intensities vary between about 2- and 6-fold, depending on species and temperature, during the period of endogenous feeding (Rombough, 1988a). The pattern appears to be fairly consistent across fish species with peaks occurring during epiboly and shortly before yolk reserves begin to become limiting. Metabolic intensity is consistently low during mid to late organogenesis. These variations in metabolic intensity do not appear to be correlated with variations in specific growth rate (Rombough, 1994) and, at this point it is not known what is driving them. The overall scaling relationship between metabolic rate and tissue mass appears to be significantly different during embryonic/larval development than it is later in life. There is a fair amount of variability among species, but most estimates place the interspecific mean for the metabolic mass exponent in adult fish at between b = 0.80 (Gollish, 1995; Clarke and Johnston, 1999) and b = 0.88 (White et al., 2006). Estimates for interspecific mean values for fish during early life range from b = 0.9 (Rombough, 1988a) to b = 0.97 (Giguère et al., 1988), with many reliable reports for individual species of values ≥1.0. This led Giguère et al. (1988) to speculate that the underlying relationship during early life is for metabolic rate to scale isometrically with respect to body mass. The fact that oxidative enzymes also appear to scale isometrically for larvae of several fish species (Hinterleitner et al., 1987) tends to support this contention. Detailed examination of individual species indicates that the transition from massindependent metabolic intensity to mass-dependent metabolic intensity takes place fairly abruptly during the early juvenile phase (Post and Lee, 1996). What triggers this shift is not clear. One possible advantage of stable high metabolic intensities throughout the embryonic/larval period is that it permits higher rates of growth than would be possible if metabolic intensity declined with increasing body mass as it does later in life (Rombough, 2006). There is a strong correlation between maximum resting/routine metabolic intensities and growth rates at both the species (Wieser, 1994) and individual levels (Biro and Stamps, 2010). As mentioned in Section 1, hatchlings face particularly strong selective pressures to grow rapidly. Interestingly, metabolic scaling also appears to be close to unity for neonate mammals (Mortola, 2001). Developing fish appear to have very limited capacity to elevate their aerobic metabolic rate above the routine level (Rombough, 1988a, 2006; Killen et al., 2007). This appears to be particularly true during embryonic development. For example, a several hundredfold increase in the frequency of body movements during hatching in rainbow trout resulted in a <20% increase in the rate of oxygen consumption (Ninness et al., 2006). Aerobic scope tends to increase as development proceeds (Post and Lee, 1996; Killen et al., 2007) but even towards the end of yolk absorption factorial scopes (Rmax /Rr ) typically are not much more than 1.5–2.0 (Post and Lee, 1996; Killen et al., 2007). This creates problems when it comes to
trying to fit activity costs into the energy budget using a standard additive model of energy allocation. 5.2. Allocation of metabolic energy Additive models of energy allocation assume that energy costs associated with increased activity are met by proportional increases in the total rate of energy expenditure (Wieser, 1989). The slope of the relationship between activity level and total metabolic rate can then be used as an estimate of the unit cost of that particular activity (see Rombough, 2006 for illustrations of the method). The additive model works reasonably well for most juvenile and adult organisms, where it has been widely used to estimate unit costs for activities such as growth (e.g. Carter and Brafield, 1992) and locomotion (e.g. Brett, 1964). This method of estimating activity costs does not work, however, if total metabolic rate does not increase in direct proportion to amount of energy devoted to the activity (Wieser, 1989). In extreme cases, there may be virtually no increase in total metabolic rate, as appears to happen when newly hatched rainbow trout are forced to swim to exhaustion (Ninness et al., 2006) or salmon larvae have to expend energy continually righting themselves (Peterson and Martin-Robichaud, 1995). According to the additive model, these activities would appear to be essentially “free” (Pedersen, 1997) which of course is a thermodynamic impossibility. The crux of the problem lies in the inability of the organism to increase its metabolic rate enough to accommodate the additional costs. This dilemma can be circumvented, however, if energy is allocated to the task in a compensatory rather than additive fashion. In compensatory partitioning, the energy needed to support one activity is supplied at least in part by reducing energy expenditure in some other area. Wieser (1989) pointed out that this way of allocating energy was first documented more than a century ago and appears to be fairly widespread, if not generally appreciated. This lack of appreciation has led to some unrealistically low estimates for growth (e.g. Marsh et al., 2001) and other costs. Some of the best evidence for compensatory partitioning comes from attempts by Wieser and co-workers to estimate growth costs for rapidly growing cyprinid larvae (Wieser et al., 1988; Wieser and Medgyesy, 1990a,b). They noted that at low growth rates there was a direct correlation between metabolic intensity and specific growth rate as would be expected if partitioning was additive (Fig. 2). At some critical specific growth rate (∼8% day−1 in Fig. 2) however, the relationship changed abruptly to one where the two variables became independent of each other. This sudden plateauing of metabolic intensity was interpreted as indicating the larvae had reached their aerobic maximum. Since larvae could no longer increase their total energy output, they had to meet any additional costs associated with growth either by abruptly reducing the unit cost of growth (unlikely) or by reducing energy expenditures in some other area (i.e. by shifting to compensatory partitioning). Since then uncoupling between metabolic intensity and specific growth rate has been reported for larvae of pike Esox lucius (Wieser et al., 1992), Atlantic herring Clupea harengus (Houlihan et al., 1995), and African catfish Clarias gariepinus (Smith and Ottema, 2006) and for both embryos and endogenous feeding larvae of chinook salmon Oncorhynchus tshawytscha (Rombough, 1994). 5.3. Metabolic cost of growth (Rg ) The production of new tissue requires the expenditure of metabolic energy. Wieser (1994) estimated the theoretical minimum cost of producing tissue in cells at about 32 mg dm mmol−1 ATP. This is equivalent to 5.3 mol O2 mg dm−1 , 2.4 J mg dm−1 or about 11% (J J−1 ) of the energy content of the tissue being formed. Wieser’s (1994) estimate was based on an energy density of
Apparent energy expended to support growth (µmol O2 g-1 h-1)
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Specific growth rate (% day -1) Fig. 2. Apparent energy expended to support growth (Rmax –Rs ) for cyprinid larvae growing at different rates. Rmax = maximum rate of energy expenditure, Rs = standard rate of energy expenditure. Data from Wieser and Medgyesy (1990a).
22 J mg dm−1 for the tissue being formed and a P:O ratio of 3.0 using glucose as fuel. He also assumed that preformed monomers were present in excess and included costs associated with RNA synthesis and turnover and monomer and ion transport as well as the direct cost of linking monomers to form polymers. Calow’s (1977) estimate of 4.7% (J J−1 ) is sometimes cited as the theoretical minimum cost of growth but this value does not take into account activities such as RNA synthesis and intracellular transport making it unrealistically low under in vivo conditions. Empirical measurements of the unit cost of growth in organisms are typically about 3-times Wieser’s (1994) theoretical minimum cost. Based on an extensive survey of the literature for bacteria, protozoans and ectothermic metazoans, Wieser (1994) suggested that a reasonable “consensus value” for living organisms was about 16 mol O2 g dm−1 . This is equivalent to an apparent net cost of growth (Rg /P) of 33% and an apparent net growth efficiency [P/(P + Rg )] of 75%. The average cost of growth in fish larvae appears to be close to this consensus value. Wieser (1994) reported an average cost of 16.7 mol O2 g dm−1 for larvae of 10 species of marine teleosts. Rombough (2006) arrived at a mean of 20 mol O2 g dm−1 based on reports for 7 different species. Averaged over the whole period of endogenous feeding, embryos/larvae should have no trouble fitting growth costs into their energy budget. As mentioned in Section 1, cumulative production efficiency (P/A) to the end of yolk absorption averages about 60% (Needham, 1931). Assuming Wieser’s consensus value for Rg /P of 33%, this equates to a total expenditure in support of growth (material + construction costs) of about 80% of the energy content of the yolk (A). A problem arises, however, at higher production efficiencies. At a P/A of 75%, 100% of total yolk energy would have to be devoted to P + Rg leaving no energy for other essential activities (e.g. morphogenetic movements, differentiation, tissue maintenance, physical activity) or for excretory losses. As mentioned in Section 4, there are many reliable reports of production efficiencies greater than 75% at certain stages of development. Organisms must somehow be able to reduce their unit cost of growth below the consensus value to fit into the energy budget during these periods. Reducing COG to Wieser’s theoretical minimum of 11% for Rg /P would permit production efficiencies of up to 90%, which would account for most of the reports of high P/A. This assumes, of course, that the unit cost of growth can be reduced.
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Relative rate of protein synthesis (mg P·g P-1·h-1) Fig. 3. Relationships between unit cost of tissue or protein (P) growth and specific growth rate. (A) Data for various aquatic ectotherms from Wieser (1994). dbm = dry body mass. (B) Data for fish cells and larvae from Smith and Ottema (2006). Solid lines and equations are for the lines of best fit to the data assuming an exponential decline to a minimum. Dashed lines are for total cost of tissue or protein growth calculated by multiplying the unit cost by the rate of growth.
There is evidence that the unit cost of growth is indeed variable. Wieser (1994) reported that the unit cost of growth and specific growth rate appeared to be negatively correlated in small, fast growing vertebrates and invertebrates (Fig. 3A). Smith and Ottema (2006) recently arrived at the same conclusion using data on protein synthesis rates in cultured fish cells and rapidly growing fish larvae (Fig. 3B). Interestingly, both data sets project to similar asymptotic values (11 and 14 mol O2 mg dm−1 , respectively) equivalent to a value for Rg /P of about 24%. Theoretically, this could support production efficiencies of up to 80%, which would be enough to explain some but not all the reports of high P/A. There is obviously more going on than these data indicate but what that is remains unclear. One possibility is that embryos are making use of preformed elements assembled either maternally (many of the reports of high P/A are for early embryogenesis) or during periods of slower growth (e.g. the period just prior to hatch). Two possible mechanisms have been proposed to explain the reduction in unit COG at high specific growth rates. Smith and Ottema (2006), building on the work of Pannevis and Houlihan (1992), have implicated increased RNA translational efficiency. Pannevis and Houlihan (1992) speculated that there were two main components to the cost of protein synthesis (the main driver of tissue growth): (1) fixed costs associated with RNA synthesis and the like and (2) variable costs associated with number of peptide bonds formed. Smith and Ottema (2006) reported a direct relationship between the translational efficiency of RNA (g protein g RNA−1 day−1 ) and specific growth rate (g) in African catfish larvae where a doubling of g resulted in ∼3-fold increase in translational efficiency. The other mechanism that has been pro-
posed to explain decreased unit COG at high specific growth rates is an increase in protein retention efficiency (Pace and Manahan, 2007). Pace and Manahan (2007) reported that the energetic cost of protein synthesis appear to be fixed in larvae of the sea urchin Asterina miniata, but that the unit cost of protein deposition (i.e. growth) could be up to 3-fold lower in rapidly growing larvae than in more slowly growing larvae. This appeared to be a direct reflection of higher protein retention efficiencies (up to 80%) in the more rapidly growing larvae. It is not clear if this applies to fish larvae (embryos have not been looked at). Rombough (2006) surveyed the literature and concluded that, except for one anomalously high value of 94%, there was no significant difference between retention efficiencies in rapidly growing larvae (mean = 55.2%) and much more slowly growing juveniles (mean = 53.1%). To further confuse the issue, the study that reported the 94% value found an inverse relationship between retention efficiency and specific growth rate (Conceic¸ão et al., 1997b). One corollary that appears to arise from an exponential decrease in the unit COG with increasing g is that there may be an optimum or at least a “sweet spot” for minimizing the total cost of growth. The total cost of growth is the product of the unit COG and the rate of growth. Smith and Ottema (2006) reported a distinct minimum with respect to total costs at a protein synthesis rate of about 3 mg P g−1 h−1 (Fig. 3B). Wieser’s (1994) data did not yield a distinct minimum but there was an inflection point at a specific growth rate of 5.4 mg dm g−1 h−1 (Fig. 3A). At present there is no evidence that developing organisms do or even can adjust their growth rates to take advantage of these “minima” (which themselves need to be confirmed). Even if they could, the overall impact on embryonic energetics would likely be small (especially in the case of Wieser’s data) and quickly swamped by the increasing amounts of energy that need to be directed to support tissue once it is formed (i.e. Rm ). 5.4. Maintenance metabolism (Rm ) Organisms have to expend a certain amount of energy maintaining tissue once it has been formed. In cells, the major maintenance costs are those associated with protein turnover, the proton pump, the Na+ and Ca2+ pumps and RNA synthesis, in that order (Siems et al., 1992). The types and ranking of activities supported by maintenance metabolism appear to be similar in whole organisms. Rolfe and Brown (1997) reported that the four most energy demanding activities supported by standard metabolism (Rs ) in adult mammals were protein turnover (19% Rs ), the mitochondrial proton leak (18% Rs ), the maintenance of Na+ gradients (16.5% Rs ) and whole-body service functions (18% Rs ). The situation is probably similar during development in terms of types of activities (Rs in adults is roughly analogous to Rm in embryos, see Rombough, 2006), although the relative amount of energy directed towards each if likely to be somewhat different. The costs associated with service functions (e.g. osmoregulation or gas exchange), for example, are going to vary depending on whether the services are being performed locally (i.e. at the cellular level) or centrally (e.g. in the kidney or gill). The amount of energy devoted to maintenance increases in proportion to tissue mass (Fig. 4). At this point, however, it is not clear precisely what the scaling relationship is for Rm during development. Most investigators have assumed direct proportionality (e.g. Smith, 1957; Rombough, 1994; Mortola and Cooney, 2008), but a value of b = 0.75 based on an assumption of fractal scaling has also been proposed (e.g. Hou et al., 2008). A major problem in settling this dispute is the difficulty of isolating Rm from the other contributors to Rt . Mortola and Cooney (2008) pointed out that the fact that models assuming direct proportionality (i.e. b = 1.0) “work”, in the sense that they give reasonable estimates for things like the cost of growth, is strong evidence for isometric scaling of Rm . Rombough
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Age (days postfertilization) Fig. 4. Main graph: Rates of total oxygen consumption (Rt ) and oxygen consumption associated with tissue maintenance (Rm ) for chicken embryos incubated at 38 ◦ C. Inset: Proportion of total metabolic energy expenditure devoted to maintenance as a function of age. Data from Mortola and Cooney (2008).
and Houlihan (reported in Rombough, 2006) attempted to isolate Rm by using inhibitors to block neuromuscular activity and protein synthesis in recently hatched zebrafish. Rm was found to scale isometrically with respect to tissue mass, but the size range examined varied only about 2-fold which begs the question of whether this relationship would hold over a broader size range. Cunha et al. (2007) used starvation and lack of light to suppress Rg and Ra in early turbot (Scophthalmus maximus) larvae. They reported a mass exponent of b = 0.71 for what they termed resting metabolism. This value is not significantly different from the fractal value (b = 0.75) but again the size range was relatively small (∼8-fold, but only 3 sizes) and it is not clear if all stages responded equivalently to the treatment. As an aside, Cunha et al. (2007) found that both Rg and Ra exhibited positive allometry (b = 1.28 and b = 1.30, respectively) suggesting that there may have been a trade-off between Rm and Rg and Ra . The increasing amount of energy devoted to maintenance results in gradually decreasing production efficiencies (P/A) as ever more tissue is deposited (Fig. 1). It also means that species with embryos that develop more slowly or hatch at a larger size tend to require more energy on a mass-specific basis to reach an equivalent stage of development (Fig. 5). This does not necessarily mean that more slowly developing or larger species have lower production efficiencies. What appears to happen is that increases in R are balanced by increases in A such that P/A remains relatively stable. If this did not occur, one would expect to see much lower production efficiencies in species with large eggs (e.g. birds) than in those with small eggs (e.g. fish) not the taxon-independence actually observed (Needham, 1931). A similar balancing occurs in response to temperature-induced changes in the duration of the incubation period. In developing fish, the temperature-sensitivities (measured as Q10 ) for metabolic rate, growth rate and the rate of yolk absorption are all essentially the same (Table 1). The net result is that production efficiency (P/A) is effectively independent of temperature (Rombough, 1996). 5.5. Activity metabolism (Ra ) The amount of energy devoted to activities other than growth and maintenance appears to be the most variable component of
Fig. 5. Cumulative cost of tissue production from fertilization to hatch for various fish and amphibian species. Data from Mueller et al. (2011) are plotted against hatchling yolk-free dry mass (bottom axis) and duration of the incubation period (top axis). Linear regressions relating cumulative cost to hatchling mass (M) and incubation period (D) are shown. Projections of these lines to zero mass or incubation period provides an estimate of ∼11.2 mol O2 mg dtm−1 for the average instantaneous cost of growth (compare with estimates in Fig. 3). dtm = dry tissue mass.
the energy budget. Ra encompasses a variety of different types of activities but the two most energy demanding ones are neuromuscular activity and resisting stress arising from non-optimal conditions. Of these we know most about neuromuscular activity. The total amount of energy devoted to body movements prior to hatch appears to be relatively low based on observations of how often embryos move (e.g. Ninness et al., 2006) and the fact that energy budgets come close to balancing if Ra is completely omitted from the calculation. This is not the case with endogenously feeding larvae which can devote a large fraction of their total energy expenditure to movement. For example, at hatch zebrafish larvae devote about 25% of Rt to locomotion; this proportion increases to about 50% by the end of yolk absorption (Rombough, 2006). Because of the relatively small aerobic scope of most larvae, increasing Ra typically requires some kind of trade-off. With zebrafish (Rombough, 2006) and Atlantic salmon Salmo salar (Peterson and Martin-Robichaud, 1995) larvae, the trade-off is with energy normally devoted to growth. The result is smaller larvae. The trade-off in turbot appears to involve a reduction in resting metabolism, which is similar but not identical to Rm (Cunha et al., 2007). 6. Modeling Because the egg is a closed system with respect to energy, it would appear to be a relatively simple task to develop accurate energetic models for embryonic growth. Indeed, over the past Table 1 Temperature sensitivities (Q10 s) for various embryonic rate functions in developing fish. Mean values are from Rombough (1996) except that for the rate of yolk absorption which is from Heming and Buddington (1988). Rate function
Development rate (to hatch) Metabolic rate (mass-specific) Growth rate (mass-specific) Yolk absorption rate
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Cross-species mean
3.7 (n = 37) 3.0 (n = 34) 3.0 (n = 19) 2.9 (n = 23)
3.1 (n = 171) 2.0 (n = 100) 1.9 (n = 106)
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50–60 years there have been numerous attempts to do just that. Some of the earliest models, for example those of von Bertalanffy (1957) and Smith (1957), are still relevant today. In general, the models fall into two categories: (1) descriptive models that do a good job of accurately predicting events but provide little insight and (2) mechanistic models that attempt to provide insight but sometimes yield questionable results. In recent years the pendulum has swung towards mechanistic models (e.g. West et al., 2001; Makarieva et al., 2004; Hou et al., 2008). Many of these mechanistic models are developed from “1st principles”; unfortunately these “principles” do not always reflect biological reality as it plays out during early life. All the models to date that I know of assume that energy is partitioned in an additive fashion. As I have tried to point out in this review, there is strong evidence that this is not always, or even normally, the case. Embryos and larvae appear to use a combination of additive and compensatory partitioning. Existing models also assume a constant unit cost for growth. Again, this does not always appear to be so. Many of the models assume that metabolic rate scales with tissue mass according to the 3/4 power “law”. This is demonstrably not true for routine metabolism and may or may not be true for maintenance metabolism. Finally, the majority of ontogenetic growth models treat organisms as only being capable of reacting to the physical environment in a simple monotonic fashion. This ignores the vast body of literature dealing with how natural selection has given rise to adaptations that allow organisms to “escape the tyranny” of physical factors such as temperature and geometry (e.g. Makarieva et al., 2005). Evolution, if nothing else, has proven to be ingenious. We will have to be equally ingenious when it comes to incorporating the complexities of embryonic life into models of ontogenetic growth.
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