Relationship between growth and standard metabolic rate ...

Journal of Animal Ecology 2014

doi: 10.1111/1365-2656.12260

REVIEW

Relationship between growth and standard metabolic rate: measurement artefacts and implications for habitat use and life-history adaptation in salmonids Jordan Rosenfeld1*, Travis Van Leeuwen2†, Jeffrey Richards2 and David Allen2 1

Conservation Science Section, B.C. Ministry of Environment, University of British Columbia, 2202 Main Mall, Vancouver, BC V6T 1Z4, Canada; and 2Department of Zoology, University of British Columbia, 6270 University Boulevard, Vancouver, BC V6T 1Z4, Canada

Summary 1. Mass-specific standard metabolic rate (SMR, or maintenance metabolism) varies greatly among individuals. Metabolism is particularly sensitive to variation in food consumption and growth creating the potential for significant bias in measured SMR for animals that are growing (e.g. juveniles) or of uncertain nutritional status. 2. Consequently, interpreting individual variation in metabolism requires a sound understanding of the potentially confounding role of growth and the relative importance of fixed (genetic) vs. environmental drivers of SMR variation. 3. We review the role of growth in measured SMR variation in juvenile salmonids, with the goals of (i) understanding the contribution of growth (and food consumption) to SMR variation through ontogeny, (ii) understanding the relative contributions of tissue maintenance and biosynthesis (overhead costs of growth) to apparent SMR variation, and (iii) using intrinsic growth effects on SMR to model how alternate life-history strategies may influence growth and measured SMR in juvenile salmonids. 4. SMR measures on juveniles, even when post-absorptive, may be inflated by delayed growthassociated overhead costs, unless juveniles are on a maintenance ration (i.e. not growing). Empirical measurements of apparent SMR in food restricted vs. satiated 2–5 g juvenile salmon demonstrate that estimates may be inflated by as much as 67% due to delayed overhead costs of growth, even when SMR measurements are taken 35 h post-feeding. 5. These results indicate that a substantial component of variation in apparent SMR among juvenile salmonids may be associated with (i) environmentally driven variation in ration (where elevated SMR measurements are an artefact of delayed growth overhead costs), (ii) intrinsic (genetic) or plastic organ-system trade-offs related to increasing investment in metabolically expensive digestive tissue responsible for processing food and (iii) intrinsic (genetic) variation in maximum body size and growth among individuals or life-history types. We suggest that selection for differences in adult body size among resident and anadromous forms leading to differences in juvenile growth trajectories may contribute to both SMR variation and habitat segregation in freshwater, where juveniles with higher growth are constrained to foraging in high velocity habitats to meet their greater consumption needs. Key-words: metabolic allometry, organ system tradeoffs, reciprocal life-history constraints, salmonid growth, standard metabolic rate variation, tissue maintenance costs

Introduction *Correspondence author. E-mail: [email protected] †Present address: Scottish Centre for Ecology & The Natural Environment, University of Glasgow, Rowardennan, Glasgow G63 0AW, UK

Standard metabolic rate (SMR) is a direct measure of organism respiration (i.e. whole-body maintenance metabolism). SMR is a fundamental metabolic attribute of

© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society

2 J. Rosenfeld et al. animals, and allometric declines in mass-specific SMR through ontogeny, or across a range of adult body sizes across different taxa, are among the most universal patterns in physiology. In addition to these allometric trends, there is substantial variation in mass-specific SMR (oxygen consumption per g of body tissue) among individuals, often by a factor of 2–3 times (Chappell & Bachman 1995; Tyler & Bolduc 2008; Burton et al. 2011). Intraspecific variation in metabolic rate likely has fitness consequences comparable to the less cryptic morphological differentiation typically studied by ecologists (e.g. Grant & Grant 2006). Although the origins of variation in maintenance metabolism are poorly understood, recent research has highlighted the potential ecological causes and consequences of SMR variation, particularly as a driver of individual personality (Careau et al. 2008; Biro & Stamps 2010) and performance (Piersma & Van Gils 2010; Careau & Garland 2012). SMR in ectotherms (equivalent to basal metabolic rate in birds and mammals) is measured when animals are at rest, post-absorptive, and non-growing (McNab 1997; Clarke & Fraser 2004) and is discrete from both the active components of metabolism (e.g. locomotion, foraging and predator avoidance) and the metabolic costs associated with digestion (specific dynamic action (SDA); McCue 2006; Secor 2009). As an integrated measure of resting metabolic activity, SMR represents the summation of many background metabolic processes that consume oxygen (Darveau et al. 2002), ranging from pathways involved in tissue maintenance to immunoresponse. Factors that influence individual variation in SMR also differ through ontogeny. SMR in adults has been interpreted as broadly reflecting the costs of maintaining the metabolic machinery (organs and tissues) needed to fulfil a particular lifestyle (Killen, Atkinson & Glazier 2010; Piersma & Van Gils 2010). SMR in adults may vary depending on seasonal changes in activity or behaviour related to reproduction (e.g. SMR is elevated in lactating females; Speakman, Krol & Johnson 2004), and SMR will also respond to social factors that influence stress levels (Sloman et al. 2000a,b; Gilmour, Dibattista & Thomas 2005; Millidine, Metcalfe & Armstrong 2009b). Measured SMR in juveniles is additionally strongly affected by growth rate, that is, elevated metabolism associated with tissue synthesis will affect whole-body metabolism even when organisms are at rest (e.g. Pedersen 1997; Van Leeuwen, Rosenfeld & Richards 2011a). Because of the strong influence of growth on SMR, physiologists studying maintenance metabolism in birds and mammals generally work on adults; in contrast, fish physiologists commonly measure SMR on actively growing juveniles in laboratory experiments (e.g. Cutts, Metcalfe & Taylor 2002; Van Leeuwen, Rosenfeld & Richards 2011b), or wild fish experiencing different growth rates (e.g. Rodnick et al. 2004; Rasmussen et al. 2012). In fact, although SMR is an emergent attribute driven by the summation of many physiological pathways, the positive

correlation between measured SMR and juvenile growth or dominance means that SMR is often interpreted as a causative driver of physiological performance (Alvarez & Nicieza 2005). While there is undoubtedly a significant intrinsic (genetic) component to variation in juvenile SMR that influences performance (Metcalfe, Taylor & Thorpe 1995), metabolic theory also indicates that much of the measured variation in juvenile SMR should relate to variation in growth and food consumption (Wieser 1994; West, Brown & Enquist 2001; Hou et al. 2008). Measuring SMR in juveniles also poses methodological challenges because (by definition) SMR can only be measured on non-growing animals; artefacts may arise if recent growth elevates metabolism (e.g. through plastic up-regulation of digestive organs; Ferrell 1988; Piersma & Lindstr€ om 1997; Secor & Diamond 2000), leading to serious bias in SMR estimates that may confound interpretation of metabolic variation. In this paper, we examine the factors that influence variation in measured SMR among individuals and species, with a particular emphasis on the role of growth and food consumption in juveniles, using salmonids as a model. We begin by considering how the ontogeny of juvenile growth affects SMR and bring this full circle by considering how selection on growth and adult body size may potentially constrain juvenile SMR and habitat use. We specifically focus on (i) understanding the contribution of growth and organ allometry to trends in juvenile SMR through ontogeny, (ii) clarifying the relative significance of ration (environment) and genetics (intrinsic differences in growth potential between individuals) to intraspecific variation in juvenile SMR and (iii) using intrinsic growth effects on SMR to explore how alternate life-history strategies may influence growth, SMR, and associated habitat use among juveniles. Our intent is to generate a greater appreciation for how interpretation of SMR variation may be confounded by variation in growth and food consumption, particularly among early life stages. Because of the difficulty in measuring maintenance metabolism in growing juveniles (Makarieva, Gorshkov & Li 2004), we differentiate between true maintenance metabolism (SMRmaint) and empirical measurement of SMR in growing juveniles (which may include a spurious component associated with overhead costs of growth) by referring to the latter as apparent or growth-inflated SMR. We begin below with a brief overview of the relationship between growth and SMR variation through ontogeny.

Drivers of ontogenic allometry of SMR: the role of growth Mass-specific SMR declines as a negative power function of body mass as organisms grow to maturity (Fig. 1; Wieser & Forstner 1986), although SMR may be nearly massindependent very early in ontogeny (Brody 1945; Wieser 1994; Post & Lee 1996). SMR shows a similar decline across a size gradient of adults of different species

© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society, Journal of Animal Ecology

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Fig. 1. Schematic illustrating hypothetical changes in mass-specific standard metabolic rate (SMR) through ontogeny. SMR associated with maintenance (SMRmaint, broken line) represents metabolism in inactive, post-absorbent, non-growing animals, which declines through ontogeny as mass approaches adult size in animals with indeterminate growth. SMRapparent (solid line) represents growth-inflated measures of apparent SMR on postabsorbent juveniles held at a ration in excess of maintenance, with the double-headed black arrow indicating delayed overhead costs of growth. Grey arrows and bands indicate variation in SMR among individuals in a population associated with either genetic (fixed), developmental or ration-dependent effects.

(Glazier 2005). Despite these relationships being among the oldest and best-documented patterns in macrophysiology (e.g. Kleiber 1932), there is still considerable debate as to their origin. One widely accepted mechanism is that body mass increases more quickly than the capacity of fractal-like circulatory networks to transport nutrients to tissues (mass exponent of ~0
75; West, Brown & Enquist 1997), so that organism physiology becomes increasingly limited by transport of nutrients and waste products as size increases (Banavar, Maritan & Rinaldo 1999; West, Brown & Enquist 1999). Competing mechanistic hypotheses suggest that metabolism is ultimately limited by the diffusion rate (supply) of nutrients, oxygen or heat across organ surfaces (e.g. gills, stomach or intestine), rather than transport within networks, and therefore scales to a mass exponent of 2/3 (area : volume; Koojiman 2010; Pauly 2010; Speakman & Kr ol 2010). Glazier (2010) reconciles these extremes by suggesting that organism lifestyle determines metabolic level and whether metabolism is bounded by volume vs. surface-area constraints (e.g. Killen, Atkinson & Glazier 2010). Although these hypotheses provide theoretical mechanisms for generic trends in whole-body SMR through ontogeny, they provide limited insight into the specific developmental processes that alter whole-body metabolism through ontogeny. Post & Lee (1996) identify two candidate proximal reasons for ontogenic declines in SMR: an allometric decrease in respiratory surface area (gills) relative to body mass or an allometric decline in the relative mass and oxygen demand of metabolically active organs and tissues, as proposed by Itazawa & Oikawa (1986). The first hypothesis infers that SMR is supply limited by respiratory surface area; the second that SMR is limited by

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oxygen demand from body tissues, rather than supply (e.g. Pelletier et al. 1994). Falsifying either hypothesis is difficult, because evolutionary design may converge so that oxygen supply capacity matches demand (symmorphosis; Piersma & Van Gils 2010; Weibel, Taylor & Hoppeler 2010). For instance, increased growth of juvenile bass reared on a satiation ration inflates the relative size of both heart and digestive tract (liver and intestine; Goolish & Adelman 1987), suggesting that oxygen demand from greater digestive capacity must be matched by increased investment in organs that limit oxygen supply (e.g. the heart). However, the peak capacity of respiratory structures to deliver oxygen to body tissue is likely determined more by selection on maximum metabolism (e.g. for active predator avoidance, foraging) than maintenance metabolism. Standard metabolic demand is generally well below any ceiling imposed by respiratory structures, and variation in SMR is easily accommodated by altering ventilation rate (e.g. Millidine, Metcalfe & Armstrong 2009b). Although body design will ultimately be an optimization between the benefits of high performance tissues (e.g. for predator avoidance) vs. their high maintenance costs (Armstrong & Schindler 2011), it is most plausible that SMR, in a proximate sense at least, is determined by tissue demand rather than oxygen supply. The relationship between growth and SMR is most easily understood in the context of ontogenic trends in anatomy and energy metabolism. Because organs and tissue types differ greatly in their background metabolic activity and therefore maintenance costs (Gallagher et al. 1998), differences in the relative proportion of high- vs. low-maintenance tissue will result in corresponding changes in whole-body SMR (Itazawa & Oikawa 1986; Mueller & Diamond 2001; M€ uller et al. 2011; Wang et al. 2012). A decreasing proportion of organs with high mass-specific metabolic rates through ontogeny provides a coherent mechanism for ontogenic declines in SMR (Fig. 1). Visceral organs associated with growth (e.g. liver, pancreas, kidneys, alimentary canal) or respiration (heart) have very high mass-specific metabolic rates (i.e. maintenance costs) relative to skeletal muscle, connective tissue and bone (Oikawa & Itazawa 1984, 1993; Elia 1992; Wang et al. 2001, 2012). Allometric declines in the activity and relative proportion of highly active tissues are well documented in mammals (e.g. Fig. 2; Landgraf et al. 2007) and fish (e.g. Fig. 3; Oikawa & Itazawa 2003) and therefore provide a proximate anatomical/physiological mechanism for how whole-body SMR declines through ontogeny, even though declining respiratory area : mass ratios (Post & Lee 1996; Pauly 2010) or transport efficiency through fractal networks (West, Brown & Enquist 1997) may set the ultimate ceiling on active whole-body respiration. However, ontogenic trends in relative organ mass and specific metabolism are ultimately driven by selection on growth trajectories. Juveniles experience very high mass-specific growth (and maximum ration at satiation) which declines through ontogeny (Figs 2 and 3). High

© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society, Journal of Animal Ecology

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Weight (Kg) Fig. 2. Ontogenic allometry of mass-specific basal metabolic rate, consumption and basal metabolism attributable to summed metabolism of major visceral organs in the pig (a). Summed metabolism of visceral organs is estimated as the product of organ mass, which increase with body size, and organ-specific metabolic rates, which are assumed to be constant (see Table 3). The thin broken line illustrates the summed metabolism of visceral organs if mass-specific metabolism of one organ (liver) is assumed to decrease with body size according to the interspecific relationship presented in Wang et al. (2012). Panels (a) and (b) illustrate how the relative proportion of body mass in visceral organs with high mass-specific metabolic rates mirror ontogenic trends in basal metabolism and consumption, supporting the inference that the ontogenic decline in BMR (and growth) is at least partly driven by a decline in the relative proportion of organs with high mass-specific metabolism.

mass-specific growth rates must be supported by a relatively greater investment in digestive and circulatory organs that can process food and transport products and wastes, and the declining proportion of metabolically active tissue needed for growth and respiration – or a decline in their mass-specific activity – represents a significant component of the declining pattern of SMR through ontogeny (Oikawa & Itazawa 1993). A relatively greater investment in organs necessary for growth contributes growth-associated overhead costs that elevate maintenance costs at small size, although elevated size and metabolism of organs unrelated to growth (notably the brain) also contribute to this pattern (e.g. Elia 1992; Oikawa & Itazawa 2003). Wang et al. (2012) have also elegantly demonstrated that a similar pattern is the proximate driver of declining SMR along the mouse–elephant body size continuum – a relatively smaller contribution of visceral organs to total mass in large-bodied species, in conjunction with declining mass-specific organ metabolism.

Fig. 3. Ontogenic trends in estimated standard metabolic rate (SMR), daily consumption (a) and the proportion of body weight as viscera in rainbow trout (b). Although organ-specific metabolic rates are not available for rainbow trout, trends in ration, body composition and metabolism are similar to those in mammals (e.g. Fig. 2) and support the inference that ontogenic declines in SMR and growth are related to a lower relative proportion of tissue with high mass-specific metabolic rates associated with growth and maintenance. Ontogenic trends in visceral mass are from data presented in Weatherley & Gill (1983), SMR is from Post & Lee (1996), and maximum ration is calculated using the model of Hewett & Johnson (1992) with parameter values from Sullivan et al. (2000).

Potential influence of ration and growth on SMR In a more general sense, mechanisms underlying the growth–SMR relationship through ontogeny likely also apply to inter- and intraspecific SMR variation. The positive relationship between growth and SMR provides a cornerstone of the ‘pace-of-life’ hypothesis (Reale et al. 2010), whereby organism falls along a slow–fast metabolic continuum, with organisms at the fast end characterized by high metabolism, rapid growth, reduced investment in maintenance and reduced longevity (Williams et al. 2010; Wiersma, Nowak & Williams 2012). Trade-offs along the fast–slow metabolic continuum may be expected at various levels of taxonomic organization. For instance, the genetic basis of higher SMR and growth among contrasting genotypes is partly rooted in larger digestive tracts and maximum rations that contribute to a higher SMR. This is exemplified by high SMR strains of mice that have larger digestive tracts coupled with higher energy intake (Sadowska, Gebczynski & Konarzewski 2013). Similar patterns are observed in wild rodents (Mueller & Diamond 2001), and among tropical vs. temperate birds, where tropical birds are characterized by lower SMR and proportionally smaller circulatory and visceral organs (but no noticeable difference in digestive tract size; Wiersma, Nowak & Williams 2012). Some of the general variation in growth and SMR among individuals is almost certainly due to individual genetic or developmental differences in maximum consumption and size of the

© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society, Journal of Animal Ecology

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Timing of SMR measurement post-feeding (h) Fig. 4. Frequency distribution of reported time between feeding and initiation of standard metabolic rate (SMR) measurements for 35 studies measuring SMR in juvenile salmonids based on a non-selective literature review (see Appendix S1 for data sources, Supporting information). Shaded area represents the maximum duration of specific dynamic action reported for juvenile salmonids (see Table 3).

Relative change in organ mass (%)

digestive tract. Insofar as these intrinsic differences in organ size and SMR remain even when individuals are on a maintenance (non-growing) ration, they represent real drivers of individual SMR variation and directly link higher SMR to elevated growth potential. However, the size and activity of digestive tracts are also phenotypicaly plastic and respond strongly to consumption and environmental food availability (Starck 1999; Armstrong & Bond 2013). Individuals can upregulate digestive tract function over short to long time-scales (days to weeks); periodic feeders like snakes can rapidly increase the capacity and activity of their digestive tract during a meal and equally rapidly downregulate it to reduce metabolic maintenance costs when fasting (Secor & Diamond 2000). Similarly, under sustained high ration digestive tract size can substantially increase over longer time-scales; for instance, swans have been observed to increase the length of their intestine by over 40% while feeding on rich grass lawns over a period of 4 months (Van Gils et al. 2008). Comparable increases in mass of digestive organs have also been observed in juvenile salmonids during extended pulses of high food availability (Armstrong & Bond 2013). Unlike fixed differences in organ size among individuals, the increased metabolic costs of reversible up-regulation of digestive machinery represent overhead costs of growth that are absent in animals on a maintenance ration and therefore do not contribute to true variation in SMR (which by definition can only be measured on non-growing animals). Below we consider how growth artefacts may influence measured SMR; we focus on juvenile salmonids as a model taxon because of their common use in animal physiology and well-established metabolic protocols (e.g. Cutts, Metcalfe & Taylor 2002).

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Potential for growth-related bias in SMR measurements SMR of juvenile salmonids is often measured as little as 20–24 h after feeding (e.g. Cutts, Metcalfe & Taylor 1998; O’Connor, Taylor & Metcalfe 2000), although longer time intervals tend to be more frequent (Fig. 4). Time intervals as short as 24 h are implicitly assumed sufficient for growth to cease and for the costs of digestion (SDA) to subside without inflating SMR measurements. However, these assumptions may be optimistic, and biases in SMR measurements on growing animals may arise in several ways. First, plastic increases in organ size and activity in response to a sustained ration may persist for days after fish have been switched to a fasting ration (e.g. Krogdahl & Bakke-McKellep 2005), and these delayed overhead costs of growth will likely persist over the short 24-h fasting time frame sometimes used for SMR measurements in juvenile salmon and trout (e.g. Fig. 5, Appendix S1, Supporting information). This is demonstrated by elevation in measured metabolism of juvenile salmonids on high rations relative to fasting conspecifics when metabolism is

Fig. 5. Relative change in organ mass in juvenile Atlantic salmon sampled at various times post-feeding. Time 0 indicates organ mass immediately post-feeding; the first two samples are at 2 and 4 days post-feeding, respectively. Data are from Krogdahl & Bakke-McKellep (2005).

measured within 20–35 h of feeding (e.g. O’Connor, Taylor & Metcalfe 2000; Van Leeuwen, Rosenfeld & Richards 2011a,b). This effect is likely not unique to fishes, as elevation of measured SMR in growing organisms has been documented in a variety of other taxa (e.g. immature marine mammals, Lavigne et al. 1986; algae, Geider & Osborne 1989; stick insects, Roark & Bjorndal 2009). The precise time course over which plastic up-regulation of the digestive tract subsides on fasting is difficult to generalize, but is likely on the order of multiple days to weeks (Piersma & Lindstr€ om 1997; Starck 1999; Blier et al. 2007), re-enforcing the need for animals to be on a near-maintenance ration to produce accurate estimates of SMR. In addition to potential biases from lagged effects of digestive tract down-regulation (i.e. delayed growth

© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society, Journal of Animal Ecology

6 J. Rosenfeld et al. overhead costs), the appropriate time required for SDA to subside before SMR is measured is often unclear. SDA subsumes a variety of processes associated with digestion. These include motor costs of digestive peristalsis (generally considered small), the costs of actually digesting and absorbing food, and costs associated with post-absorptive processes such as protein synthesis, transport and deposition. Post-absorptive processes (largely protein synthesis) are generally thought to constitute much of the oxygen demand during SDA (Carter & Brafield 1992; Lyndon, Houlihan & Hall 1992; McCue 2006). The costs of tissue synthesis (i.e. protein synthesis and deposition) likely contribute particularly to the descending limb of SDA (Fig. 6; Secor 2009; Lyndon, Houlihan & Hall 1992), including the costs of synthesizing basic molecules, transporting them to sites of tissue growth, and organizing and assembling them into new cells. Distinguishing where SDA ends (in the narrow sense of digestion costs) and the costs of tissue synthesis begin may be empirically difficult (Pedersen 1997), particularly as SDA is broadly and variably defined to include a wide range of processes. However, the tissue synthesis phase on the descending limb of SDA has a strong temporal signature, and a measureable elevation of metabolism associated with tissue synthesis on the descending limb of SDA may be detectable for days (Secor 2009). This implies that, for growing organisms, even SMR measurements that begin once organisms are post-absorptive may retain a signature of tissue synthesis metabolism (i.e. SDA) long after the peak absorptive phase of SDA is complete. This is well illustrated in experiments by Lyndon, Houlihan & Hall (1992) who measured the time course of oxygen consumption and protein synthesis following a single meal in juvenile cod. Although oxygen consumption

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Hours post-feeding Fig. 6. Average magnitude and time course of specific dynamic action (SDA) for 26 species of fish ranging from 3 g to 19
8 kg, showing a classic stiletto heel shape with an extended tail. SDA values for each species were standardized to a maximum of 1 by subtracting baseline standard metabolic rate (SMR) and dividing each time series by its’ maximum (peak) elevation of SDA above SMR. Grey shading represents one standard deviation of the data distribution; broken lines represent 95% confidence intervals on the predicted mean (solid line). See Appendices S2 and S5 for data source and details (Supporting information).

peaked 12 h post-feeding, oxygen demand remained elevated above background SMR 24 h post-feeding, 48 h was required for oxygen demand to subside to pre-feeding SMR levels, and protein synthesis remained elevated at 48 h post-feeding. Although this specific example is for juvenile cod, meta-analysis of the time course of SDA from 29 studies (Fig. 6, Appendix S2, Supporting information) indicates that this pattern is not atypical and that SDA may take up to several days to subside, although this will depend on fish and meal size, species and temperature. Given the lags in tissue syntheses costs (SDA) following feeding, delaying SMR measurements 48 h post-feeding would seem appropriate for unbiased estimation of maintenance metabolism in juvenile salmonids (e.g. McCarthy 2000; Alvarez & Nicieza 2005), although it is always best to directly assess the duration of SDA in target animals before measuring SMR. Collectively, these patterns indicate that, at least in juvenile salmonids, estimates of SMR in growing individuals may be inflated by metabolic lags in down-regulation of digestive organ size or activity (overhead costs of growth), or post-absorptive processes associated with tissue synthesis (SDA; also representing overhead costs of growth). This is illustrated in Fig. 1, where the lower line represents the declining power function of true maintenance metabolism with increasing body mass and the upper line represents apparent (growth-inflated) SMR measurements from the inadvertent inclusion of overhead costs of growth (e.g. upregulated digestive tract and/or tissue synthesis costs). While this is an heuristic figure, the degree of bias in measured SMR for animals at high ration can be directly estimated if paired SMR measurements are available for animals on a maintenance or fasting ration (e.g. Jørgensen 1988; Wieser 1994). SMR of animals that are not growing must be entirely due to maintenance costs, while a relative elevation of apparent SMR under high ration in post-absorptive individuals should be directly attributable to the overhead costs of tissue synthesis (see Wieser 1994 for an excellent review). Table 1 shows growth-associated bias in SMR estimated with published data from growth experiments that measured SMR of juvenile coho salmon or steelhead trout reared on either fasting or moderate-to-high rations (Van Leeuwen, Rosenfeld & Richards 2011a,b). In all cases, fish were reared for 2–3 week on either a medium or high food ration, or 1 week on the fasting ration, and SMR was measured 35 h post-feeding. Inflation in estimated SMR was significantly correlated with average growth rate (F1, 3 = 37
2, P < 0
009, n = 5). Fish on the highest ration had an elevation in apparent SMR of up to 67% over SMR estimated for a maintenance ration (Table 1; Appendix S3, Supporting information), indicating a significant potential for growth-related bias in SMR even when measured 35 h post-feeding. It is difficult to determine the proportion of SMR inflation caused by tissue synthesis and deposition (i.e. the tail end of SDA) vs. the overhead costs of organ

© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society, Journal of Animal Ecology

Growth and standard metabolic rate up-regulation resulting from a long-term diet in excess of maintenance. This crucially depends on the timing of SMR measurement relative to the onset of fasting (Fig. 4), the duration of SDA (Fig. 6) and the rate of down-regulation of digestive organ size and activity independent of SDA (e.g. Fig. 5). For juvenile salmonids, the reported maximum duration of SDA is 3–30 h (Table 2), suggesting that most of the growth-related elevation of apparent SMR observed by Van Leeuwen, Rosenfeld & Richards (2011a,b) is associated with delays in the downregulation of digestive organs that have been upregulated while on prolonged high ration. Up- and down-regulation of organs during changes in ration is well documented in birds and mammals and reported to take place over multiple days and weeks (Piersma & Lindstr€ om 1997; Piersma & Van Gils 2010). The limited information available for fishes suggests similar multiday and weekly time courses (Foster, Houlihan & Hall 1993; Krogdahl & BakkeMcKellep 2005; Blier et al. 2007; Gaucher et al. 2012), although effects may be nonlinear with a disproportionate change in organ mass and activity occurring with in the first 48 h (Krogdahl & Bakke-McKellep 2005; Fig. 5). A large increase in gastro-intestinal (GI) mass is well documented as part of the SDA response in periodic feeders like snakes (e.g. Secor 2001), but cyclic up-regulation of GI tract size also appears to be a significant component of SDA in animals with a normal diel feeding periodicity (Fig. 5). If the duration of fasting before SMR measurements is excessively short (e.g. Fig. 4), then SMR may be inflated by both SDA (tissue synthesis) and residual digestive organ up-regulation costs. The best way to avoid including the overhead costs of growth in SMR estimates is to rear fish for an extended period on a maintenance diet prior to SMR measurement, or if this is not possible to have control groups on a true maintenance ration. From a standpoint of interpreting the adaptive significance of individual variation in metabolism (e.g. Reale et al. 2010; Careau & Garland 2012), the main concern here is that observed differences in individual SMR may be an artefact of unknown difference in growth or consumption histories among individuals. This may be

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a concern for SMR measurements on communally reared fish in the laboratory where dominance hierarchies may result in differential energy intake and growth (e.g. Jobling & Koskela 1996) or for wild-caught fish where SMR measurements are taken without multiday acclimation to standard rations (e.g. Rasmussen et al. 2012).

Contribution of body composition to individual variation in SMR (lipid reserves and organsystem trade-offs) The preceding discussion highlights how allometry of growth and associated organ systems may affect SMR through ontogeny. However, adaptive variation in body design (i.e. anatomy) independent of ontogeny will also affect SMR (Daan 1990; Konarzewski & Diamond 1995) because organs and tissues vary in metabolic activity as discussed above. Generally speaking, lipid has low metabolic activity, so that apparent differences in whole-body SMR among individuals may simply reflect differences in lipid stores (i.e. increased lipid lowers average mass-specific SMR, all else being equal). For this reason, estimates of whole-body metabolism are sometimes adjusted to lean body mass, which may eliminate apparent differences in metabolism (Djawdan, Rose & Bradley 1997). Structural tissue (e.g. bones, chitin) is also considered to have relatively low maintenance costs. Key organ systems (often those that retain some level of activity even when organism are at rest, such as the circulatory system) have relatively high repair and maintenance costs; for instance, the brain in humans is ~2% of body mass but is estimated to use ~20% of basal metabolism (Elia 1992). Organs that have particularly high maintenance costs include the brain, digestive tract, circulatory tissue (heart, gills), liver and kidney, and their relative mass will disproportionately influence SMR (Oikawa & Itazawa 1984; Itazawa & Oikawa 1986; Wang et al. 2012). Optimal evolutionary design requires a trade-off among organ systems that must compete for limited metabolic power. Relative organ masses therefore reflect the selective environment that ultimately shapes body design

Table 1. Apparent standard metabolic rate (SMR) of juvenile salmonids reared for 2–3 weeks at moderate–to-high ration compared to control fish fasting for a week (data from Van Leeuwen, Rosenfeld & Richards 2011a,b). SMR was measured at least 35 h post-feeding. Because fasted fish generally lost weight, maintenance metabolism (i.e. SMR for a non-growing fish of stable body weight) was estimated by adjusting mass-specific SMR of fasting treatments upwards in proportion to their weight loss and the difference in SMR between growing and fasted groups (See text and Supplemental material for details)

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h 1)

Percentage growth overhead costs

Maintenance SMR (lmol
g 1
h 1)

4
80 4
75 7
62 5
61 6
39 5
83

3
58 3
52 3
72 2
95 3
27 3
41

19% 33% 67% 49% 63% 46%

4
04 3
58 4
56 3
77 3
93 3
98

© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society, Journal of Animal Ecology

8 J. Rosenfeld et al. Table 2. Duration of specific dynamic action (SDA) reported for salmonids

Species

Food

Avg. weight (g)

SDA duration (h)

Ration (% body weight)

Temperature (°C)

Biwasu Rainbow trout Atlantic salmon Atlantic salmon

Fish Formulated diet Formulated diet Bloodworms

50 3
7 11 7

30 3
5 3 8

2 2
6 3
9 0
3

10 – – 13
5

Coho salmon

Fly larvae

24

4–12

4

Reference Miura et al. (1976) Smith, Rumsey & Scott (1978) Smith, Rumsey & Scott (1978) Millidine, Armstrong & Metcalfe (2009a) Averett (1969)

8–20

Table 3. Relationships describing ontogenetic allometry of organs as a proportion of body weight in the pig (see Fig. 2), and differences in mass-specific metabolic rate among organs. Residual tissues represent primarily muscle, bone and connective tissue. Note that organ allometry is mass-specific, that is, the percent of each organ per gram of body weight. To convert to absolute mass allometry, a value of 1 should be added to the exponent (i.e. mass-specific values should be multiplies by Ma) Gastro-intestinal Tracta Organ allometry (as% body weight) Mass-specific metabolism (kJ
kg 1
day 1)

0
163 M 350

0
24

Liverb 0
098 M 787

Heartb 0
39

0
0136 M 2105

Kidneyb 0
28

0
0135 M 1929

Brainb,c 0
29

0
034 (M
0
55) 941

Residualb 0
7

– 56

a Estimated based on proportionality between reported organ-specific metabolism from Wang et al. (2012) and the proportion of blood flow to the gastro-intestinal tract relative to other organs in sheep Ferrell (1988). bValues from Wang et al. (2012) Table 2. cPig brain allometry from Kruska & R€ ohrs (1974), where M is fat-free mass rather than whole-body weight.

(Ksiazek, Konarzewski & Lapo 2004). Digestive tract size is particularly sensitive to both the mean and variance of resource availability, with intermittent or low-quality resources selecting for larger digestive capacity (Secor & Diamond 2000; Armstrong & Schindler 2011). Similarly, plastic responses to increased food availability and consumption may include large increases in the surface area and microtopography of the intestine. This is pronounced in some snakes that rapidly amplify the microstructure of digestive surfaces after feeding, presumably because of the high costs of maintaining this tissue while fasting (Secor, Stein & Diamond 1994; Secor & Diamond 1997). Plastic reductions in digestive organ mass under food restriction have also been noted in mammals (e.g. Bozinovic et al. 2007), and birds can show extremely high plasticity in digestive organ mass, often to minimize costs of transport due to migration (Piersma & Lindstr€ om 1997). While any fixed effects of trophic strategies on relative organ size are likely most pronounced between species, there is almost certainly genetic variation in organ sizes among individuals within a population, or among different life-history strategies, that may also influence SMR (Sadowska, Gebczynski & Konarzewski 2013). For example, Millidine, Armstrong & Metcalfe (2009a) observed that individual trout with higher SMR digested food more rapidly with a higher peak SDA, indicating that differences in SMR were related to interindividual variation in digestive tract anatomy or physiology that supported faster energy processing. The contribution of intraspecific differences in organ mass to SMR variation is also supported by high

growth and metabolism strains of laboratory mice characterized by disproportionately large visceral organs (Ksiazek, Konarzewski & Lapo 2004; Sadowska, Gebczynski & Konarzewski 2013). A trade-off between maximizing growth vs. resistance to starvation has been proposed as a major driver of individual growth and SMR variation (Biro & Stamps 2010; Dupont-Prinet et al. 2010); this trade-off is implicit in the pace-of-life hypothesis (Lovegrove 2003; Reale et al. 2010) and corresponds to contrasting energetic strategies that maximize energy intake vs. efficiency of energy use (Tucker & Rasmussen 1999; Finstad et al. 2011; Van Leeuwen, Rosenfeld & Richards 2011b; Rosenfeld et al. 2013). These contrasting strategies are based on the assumption that investing in high SMR and growth capacity is beneficial when resources are abundant, but costly when resources are scarce or unpredictable (Arendt 1997; Biro & Stamps 2010). Faster growth of high SMR individuals under resource abundance or slower weight loss of low SMR individuals under resource scarcity broadly supports this inference across a diversity of taxa (larval marine fishes (Bochdansky et al. 2005); ant lions (Scharf, Filin & Ovadia 2009); zebra finches (Mathot et al. 2009). However, the trade-off between growth and starvation resistance is not always clearly related to SMR variation (Djawdan, Rose & Bradley 1997; Dupont-Prinet et al. 2010) and may instead be associated with a simple trade-off between investing in tissue that supports somatic growth (which enhances predator avoidance) vs. lipid stores that support survival during periods of resource

© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society, Journal of Animal Ecology

Growth and standard metabolic rate scarcity (e.g. overwintering; Djawdan, Rose & Bradley 1997; Post & Parkinson 2001). Relative organ mass in adults may also be influenced by foetal or juvenile nutrition and growth (Desai & Hales 1997). Experimental reduction in nutrition of pregnant rats caused a relatively greater reduction in organ mass for liver, pancreas and spleen of juveniles, while brain and lung mass were relatively conserved; these differences persisted into adulthood and were associated with reduced juvenile growth (Desai & Hales 1997). This suggests that reduced foetal or juvenile nutrition may trigger development of a ‘thrifty phenotype’ adapted to low growth in a resource poor environment (Hales & Barker 1992). Although primarily documented in mammals, similar processes may occur in other taxa, where nutritional effects on egg provisioning or environmental effects on early larval growth may generate individual variation in organsystem development, potentially driving subsequent interindividual variation in growth and metabolism. For instance, Burton et al. (2013) show that location effects on maternal provisioning of eggs in the ovary of brown trout affect subsequent juvenile growth and dominance, although the anatomical and physiological differences associated with these developmental effects remain unclear. Although the direction of SMR change is unclear for a thrifty phenotype, it would seem likely that lower juvenile growth associated with reduced digestive organ mass (Desai & Hales 1997) would support lower juvenile metabolism at satiation for a fixed body mass. An organ-system trade-off between digestive capacity and brain size has been suggested as a key adaptation that accelerated evolution of human intelligence (Aiello & Wheeler 1995). Although evidence for this trade-off is equivocal in primates (Navarrete, Van Schaik & Isler 2011), there is some support for it in fishes (Isler 2013). Kotrschal et al. (2013) found that artificial selection for increased brain size in guppies resulted in decreased gut size and lower fecundity, although larger-brained individuals performed better on cognitive tests. Although the broad occurrence of a trade-off between brain size and digestive organs is speculative, it remains plausible, particularly in populations subject to strong artificial selection for high growth (e.g. hatchery fish) where increased investment in digestive capacity could come at a cost of reduced cognitive performance. A significant (~30%) reduction in brain size following domestication is commonly observed in mammals (e.g. Kruska & R€ ohrs 1974); although this is usually attributed to reduced selection on cognitive function, it could also partly represent an organ-system trade-off associated with selection for high growth under domestication. Selection for differences in performance between environments may also alter investment in circulation or musculo-skeletal systems (e.g. Eliason et al. 2011) in ways that influence SMR. For example, pelagic fishes have generally higher SMR than less active benthic or bathyal fishes, which has been attributed to a greater investment

9

in muscular and respiratory tissue in more active pelagic species (Killen, Atkinson & Glazier 2010). A trade-off between swimming ability and maximum growth has also been observed among populations of marine fishes along latitudinal gradients (e.g. Atlantic silversides; Billerbeck, Schultz & Conover 2000). To achieve a threshold body size for overwinter survival, northern populations grow faster and have higher maximum consumption, but poorer swimming performance that elevates vulnerability to predation (Billerbeck, Lankford & Conover 2001). This suggests that faster-swimming southern populations may invest more in muscle or cardio-vascular tissue at the expense of organ systems that maximize growth. A similar apparent trade-off has also been observed between hatchery and wild fishes, where domestication appears to select for higher growth at the expense of reduced swimming ability (Fleming et al. 2002; Reinbold, Thorgaard & Carter 2009). Ultimately, it may be ecological trade-offs between growth and vulnerability to predation (or other ecological traits) that drive apparent trade-offs among organ systems. Because growth rate is a key ecological attribute differentiating individuals, populations and species (Arendt 1997; Dmitriew 2011; Vincenzi et al. 2012), the potential effects of genetic differences in growth on SMR warrant special consideration. Selection on growth may influence SMR through a variety of pathways, including changes in physiology (the intensity of biochemical pathways) and changes in relative organ masses and associated maintenance costs as described above (e.g. through selection on maximum consumption and digestion rates). Below we consider the potential implications of fixed (genetic) differences in growth for variation in SMR among individuals, using contrasting salmonid life histories as a model.

Genetic variation in body size among individuals and life histories: implications for juvenile growth and metabolism The effect of body size at maturity on juvenile growth rate is well documented; for example, among sexually dimorphic species, the larger sex at maturity generally has higher juvenile growth and energy requirements (CluttonBrock, Albon & Guinness 1985). Similarly, body size at maturity will have a dramatic effect on growth and SMR among fish of similar size; a 2 g mature stickleback will have much lower growth and SMR than a 2 g juvenile salmon growing at maximal rates near the beginning of its ontogenic growth trajectory (e.g. far left of Fig. 1). Stickleback vs. salmon represents an extreme contrast in maximum body size between species, but much smaller differences in size at maturity exist that will potentially influence juvenile growth among individuals, sexes, populations and ecotypes (e.g. resident vs. anadromous trout; Hendry et al. 2004). For instance, in common-garden experiments, juvenile limnetic stickleback (adult mass ~1
2 g) grow at half the rate of size matched juvenile ben-

© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society, Journal of Animal Ecology

10 J. Rosenfeld et al. thic stickleback (adult mass ~3 g) which mature at 2–5 times their body mass (Fig. 7a; Velema 2010). Focusing on contrasting salmonid life histories, if we assume for simplicity that resident and anadromous fish mature at the same age (i.e. ignoring precocious males), then larger mature body size (i.e. size at age) must be achieved through selection for faster growth (presumably based on higher environmental prey abundance). The effect of differences in growth rate on SMR among individuals (or ecotypes with different growth trajectories) can be modelled assuming that the relationship between growth and SMR among individuals is the same as that observed through ontogeny. This is likely a reasonable assumption if individuals achieve higher growth using

5

(a)

limnetic benthic

Mass (g)

4

3

2

1

0 0

0·2

0·4

0·6

0·8

1

Age (years) Large

60

(b)

Medium 50

Small

Length (cm)

40 30 20 10 0 0

10

5

15

Age (years) Fig. 7. (a) Composite mass vs. age relationship for limnetic and benthic stickleback with data from several sources. Points separated by the double-headed arrow represent data from a common-garden experiment where stickleback collected in the wild were reared in the laboratory on satiation rations for a 90-day period (Velema 2010). Adult stickleback weights are from Nagel and Schluter (1998). (b) Length vs. age trajectories for sympatric ecotypes of Arctic charr from Alaska (Woods et al. 2013). Note apparent convergence in ecotype sizes at smaller age classes.

strategies that mirror trends through ontogeny, for example, higher maximum ration, larger relative mass of organs active in growth and metabolism, and increased water content. The ontogenic relationship between growth and SMR may be less transferrable to individual variation if higher growth is achieved through reduced maintenance metabolism (i.e. reduced tissue repair or turnover) or lowered tissue quality, strategies that often occur during compensatory growth (Ali, Nicieza & Wootton 2003). For the purposes of subsequent modelling, we also make the simplifying assumption that specific growth rate through ontogeny follows a continuous decline according to a Von Bertalanffy growth function (VBG), that is, that a larger body size at a fixed age of maturity selects for higher growth throughout ontogeny (Fig. 8a). A VBG function may not be the most accurate function for modelling juvenile growth (Day & Taylor 1997; Lester, Shuter & Abrams 2004; Pauly 2010), and recent evidence suggests that a biphasic relationship with linear growth at small size may be more appropriate (Shuter et al. 2005; Quince et al. 2008). However, it is convenient for illustrating the significance of growth variation to SMR for fish of different asymptotic body size (L∞), and linearity of the initial phase would not qualitatively change observed patterns in growth. Most importantly, implicit in the VBG is a positive correlation between juvenile growth (slope of the sizeat-age curve) and adult body size as hypothesized above. To illustrate the potential for differences in growth to influence SMR variation among individuals in a population with a fixed size at maturity, we modelled the effects of assumed genetic differences in body size between two adult sockeye salmon individuals with hypothetical L∞ = 65 cm vs. L∞ = 80 cm (a typical adult size range within a sockeye population); growth is modelled according to Von Bertalanffy functions for length and weight with parameters typical for salmonids (e.g. Pedicillo et al. 2010; Appendix S4, Supporting information). Daily increments in modelled growth (mass) were converted to SMR by combining mass-dependent equations for SMR (SMR = 0
156
M0
846, mg O2
h 1; Brett & Shelbourn 1975) and growth (% growth = 5
58
M 0
43; Brett & Glass 1973), by substitution mass-specific SMR = 4
88
[(5
58/% growth)2
33] 0
154 lmol O2
g 1
h 1. These hypothetical growth trajectories translate into a difference in SMR of c. 9% between the large- and small-bodied adult sockeye as 2 g juveniles (Fig. 8d), based purely on fixed differences in growth rate associated with differences in adult body size. Using a similar approach for ecotypes, we modelled variation in growth and SMR between resident and anadromous brook charr (excluding precocious males) that also differ in size at age, based on length at age data reported in Wiseman (1969) and Ridgway (2008). Resident charr were modelled with an L∞ = 35 cm, and anadromous charr were modelled with L∞ = 50 cm (Appendix S4, Supporting information). For consistency, we used the same relationship as for sockeye salmon to

© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society, Journal of Animal Ecology

Growth and standard metabolic rate 70 (a)

60

Sockeye Length (cm)

50 40

Anadromous

30

trout 20

Resident trout

10 0 0

1

2

3

4

5

6

Age (years) 5·0

(b)

11

Fig. 8. Panels a–d explore the relationship between maximum body size (length, weight), growth, and standard metabolic rate (SMR) for two hypothetical sockeye salmon from the same population assuming fixed (genetic) differences in maximum body length (65 cm vs. 80 cm at L∞; upper dashed lines) and for hypothetical anadromous vs. resident brook charr (50 vs. 35 cm L∞). Growth is modelled using a Von Bertallanffy relationship (see Appendix S4, Supporting information) assuming fixed differences in absolute growth rate associated with differences in terminal body size. Projected growth rates are higher for sockeye than for charr because of their larger size at maturity (panel c), and predicted growth of juvenile anadromous charr is higher than resident charr. The lower panel illustrates the magnitude of differences in the expected SMR between individual sockeye that differ in growth associated with genetic differences in terminal body size (9% of SMR for a 2 g fish) and growth-driven differences in SMR associated with a resident vs. anadromous life history (15% for a 2 g fish).

Weight (kg)

4·0 3·0 2·0 1·0 0·0 0

1

2

3

4

5

6

Age (years) 8

(c)

Growth (% day–1)

7 6 5 4 3 2 1 0 1

2

3

4

5

6

7

8

9

10

Weight (g) 6

SRM (μmol O2 g–1 h–1)

(d)

5 4 3 2 1 0

1

2

3

4

5

6

7

8

9

10

Weight (g) convert percentage growth to predict brook trout SMR. In this example, faster growing anadromous charr had a 15% higher predicted SMR than resident juveniles at 2 g body

size (Fig. 8d). The greater predicted difference in juvenile SMR among charr ecotypes than among sockeye individuals is driven entirely by a greater divergence in body size at maturity (and presumed juvenile growth rates) between resident and anadromous trout, independent of any social or environmental factors that might influence SMR. For the purposes of this modelling, we inferred that maximum growth follows a consistently declining trajectory as fish approach maturity for all life-history scenarios. This implicitly assumes that selection for higher growth at one stage of a life-history trajectory selects for higher growth at other life stages as well. Clearly, this is a simplification; for example, precocious parr may exhibit very high initial growth rates even though they mature at very small size (e.g. Forseth et al. 1999; Tucker & Rasmussen 1999). While it is likely possible for selection to allow variable growth trajectories through ontogeny (Badyaev & Martin 2000; Dmitriew 2011), evidence suggests that selection for consistently higher or lower growth throughout a trajectory is most common (Kirkpatrick, Lofsvold & Bulmer 1990; Kirkpatrick & Lofsvold 1992; Rocchetta, Vanelli & Pancaldi 2000; L~ ohmus et al. 2010). There is also good theoretical and empirical support for the inference that larger adult body size is usually associated with higher juvenile growth rates (e.g. Stearns & Koella 2007; Marty et al. 2011). For example, the smaller taxon within recently evolved stickleback species pairs exhibits reduced growth through much of its’ size-at-age trajectory (Fig. 7a). In the case of limnetic and benthic sticklebacks, growth trajectories diverge within their first growing season in association with different habitats and prey resources (zooplankton in open water vs. benthos in the littoral zone; Schluter 1995). Other ecotypes may show strong evidence of growth differentiation as older juveniles, but may not show consistent differences in early juvenile growth (e.g. arctic charr ecotypes, Fig. 7b; Jonsson et al. 1988; Woods et al. 2013), suggesting convergent selection on juvenile growth irrespective of adult body size. For instance, large and dwarf whitefish ecotypes in some Swedish lakes share a limnetic foraging habitat in

© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society, Journal of Animal Ecology

12 J. Rosenfeld et al. their first year and do not diverge in size until their second year when the larger morph switches to feeding on € the benthos (Ohlund 2012; Olajos 2013). This suggests that the timing of divergence in growth trajectories is strongly dependent on the availability of habitats that differ in productivity and that the timing of habitat shifts and corresponding growth acceleration may be closely linked to thresholds in size-specific predation risk (e.g. Werner et al. 1983). Note that it is also implicit in our modelling that differences in growth trajectories are due to differences in consumption rather than activity costs (e.g. Pazzia et al. 2002). Common-garden experiments with relatively inactive limnetic and benthic stickleback confirm differences in growth at satiation (Fig. 7a; Velema 2010), but this may not necessarily be the case for other ecotypes where differences in activity costs, rather than consumption, may drive divergent growth trajectories (e.g. (Pazzia et al. 2002; Trudel et al. 2001). Regardless, the main point of these examples is to demonstrate that fixed genetic differences in growth and consumption can be expected to contribute to differences in SMR among juveniles of a given body weight, particularly for a fixed age at maturity. Consequently, both environmental and genetic effects on growth and consumption may underlie much of the variation in juvenile SMR observed in field and laboratory studies, although growthrelated SMR variation in itself is unlikely to account for the twofold to threefold variation in SMR sometimes observed. Note that our intention here is not to discount the importance to SMR variation of other factors like elevated immune response (Burton et al. 2011) or stress associated with social interactions in a dominance hierarchy (e.g. Millidine, Metcalfe & Armstrong 2009b), but rather to highlight the role of growth and consumption in SMR variation. The key relevance to metabolism is that SMR variation among juveniles should be sensitive to intrinsic differences in growth trajectories through ontogeny.

Reciprocal life-history constraints In the previous section, we explicitly assume a significant level of genetic covariance in growth along salmonid growth trajectories, inferring that selection for large adult size (e.g. to maximize migration and reproductive success in anadromous ecotypes) results in selection for higher juvenile growth. If this is the case, then lower productivity in freshwater (e.g. Gross, Coleman & McDowall 1988) may create the potential for conflicting selection (Schluter, Price & Rowe 1991) between freshwater and marine lifehistory stages. We label this phenomena reciprocal lifehistory or habitat constraints, whereby strong selection for attributes in one life stage (e.g. adult body size) may select for attributes that strongly influence or constrain habitat use in another life stage (e.g. juvenile growth in freshwater). There is some qualitative evidence that this does in fact occur. Morinville & Rasmussen (2003, 2006) showed that higher velocity stream habitats that deliver a

greater total flux of prey were preferentially used by juvenile anadromous brook trout, while resident juveniles occupied slower velocity pools; this difference in habitat use among ecotypes is broadly consistent with the expectation of a niche shift to higher productivity habitats by juveniles of larger-bodied anadromous trout. Similar differences in habitat use have been observed between species; for example, higher growth and consumption by juvenile Atlantic salmon relative to sympatric juvenile brook trout matches use of higher velocity stream habitats and larger adult body size of Atlantic salmon (Tucker & Rasmussen 1999). Selection can minimize conflict between life stages if habitat variation allows juveniles to match realized growth rates to an optimal growth trajectory that may be imposed by selection on adult body size. For anadromous salmonids, this implies that selection for large adult body size will indirectly shift the freshwater niche of juveniles towards higher productivity freshwater habitats, which should result in effective habitat partitioning between low and high growth/SMR individuals, ecotypes or species (e.g. Forseth et al. 1999; Tucker & Rasmussen 1999; Morinville & Rasmussen 2003, 2006). This supports the notion that habitat selection, in addition to minimizing mortality rates, may represent an adaptive response to maintain individuals on an optimal growth trajectory by reducing potential conflict in selection on growth between life stages.

Summary In this review, we highlight the contribution of growth and food consumption to individual variation in juvenile SMR and the potential for biases in SMR measurement from overhead costs associated with juvenile growth. Ontogenic trends in growth and consumption match allometry of organ mass and activity that underlies much of the allometric decline in SMR through ontogeny. Similarly, differences in the relative size and specific activity of visceral organs related to energy processing may drive much of the individual variation in juvenile SMR related to growth and may arise from (i) genetic differences in anatomy/physiology related to selection on growth and consumption (e.g. organ-system trade-offs related to maximizing growth vs. starvation resistance or swimming performance) (Killen, Marras & McKenzie 2011; Sadowska, Gebczynski & Konarzewski 2013); (ii) developmental responses induced by environmental resource abundance (thrifty phenotype hypothesis; Hales & Barker 1992, 2001); or (iii) differences in the location of individuals along their ontogenic growth trajectory, which determines allometry of organs and SMR. Long-term up-regulation of digestive tract size of individuals on high ration may persist over the short 1to 2-day fasting period often used before SMR is measured (Fig. 4), leading to inflation of apparent SMR (defined here as the post-absorptive inactive metabolism of juvenile fish reared on a ration in excess of

© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society, Journal of Animal Ecology

Growth and standard metabolic rate maintenance, i.e. including partial overhead costs of growth). Consequently, variation in apparent SMR may arise if individuals differ in their recent energy intake history, either from stochastic environmental opportunities or from monopolization of resources by dominant individuals. Options for avoiding these growth-related artefacts may include ensuring that individuals are on a near-maintenance ration when SMR is measured, or to have a control group of animals on a maintenance ration to account for inflation of SMR in growing animals. Although the effects of growth and consumption on apparent SMR are most likely to arise in organisms that show indeterminate growth, growth-inflated SMR may also be present in growing juveniles of animals with determinate growth (e.g. mammals, Lavigne et al. 1986; stick insects, Roark & Bjorndal 2009). The degree to which growth inflation of SMR may alter interpretation of metabolic data and causative associations remains somewhat unclear; for example, if dominance is also correlated with growth, a systematic growth-related bias in SMR might not change relative SMR rankings in a dominance hierarchy, but would introduce uncertainty in the degree to which elevation in measured SMR reflects true differences in metabolism vs. delayed overhead costs of growth. Stress associated with social hierarchies (reviewed elsewhere; e.g. Sloman et al. 2000a,b; Gilmour, Dibattista & Thomas 2005) can also be expected to cause substantial variation in SMR (Burton et al. 2011). Differentiating the effects of varying consumption vs. intrinsic differences in metabolism vs. stress may remain a difficult challenge for animals reared in social hierarchies in the laboratory or in the wild. We introduce the idea of reciprocal habitat constraints, whereby fixed differences in growth trajectories (size at age) between different species or ecotypes may constrain juveniles of larger-bodied adults to forage in higher energy habitats (or higher risk environments) to track their optimal growth trajectory. In this sense, selection for a larger size at age (or adult body size for a fixed age of maturity) may indirectly constrain juvenile growth and habitat use. Alternatively, different ecotypes (e.g. resident vs. anadromous) may represent a plastic response of individuals within a population to different environmental growth opportunities, that is, a condition-dependent phenotypic response that can switch individuals onto different growth trajectories. In this latter scenario, the reciprocity of life-history constraint is reversed, and it is in the juvenile life-history stage that may determine adult habitat use. In this sense juvenile growth, metabolism, and habitat use are more likely to be constrained by adult attributes when growth trajectories are relatively fixed with limited plasticity in adult body size. In contrast, juvenile constraints on adult habitat use may be most pronounced in developmentally flexible species where alternate life histories (e.g. residency vs. anadromy) allow a flexible

13

phenotypic response to environmental variation in juvenile growth opportunities. As an emergent physiological attribute, SMR is probably rarely under direct selection (Careau & Garland 2012) and more likely varies as a result of selection on a suite of ecological or life-history traits that affect body design and metabolism. Consequently, individual variation in SMR may be related to trade-offs among different organ systems (digestive, circulatory, musculo-skeletal, cognitive) related to ecological trade-offs between growth and other attributes (e.g. maximizing growth vs. swimming performance, predator avoidance or starvation resistance (Billerbeck, Lankford & Conover 2001; Killen, Marras & McKenzie 2011; Kotrschal et al. 2013). Variation in juvenile SMR is probably best understood within the ecological context set by resource availability, social interactions and the evolutionary forces that shape body design, organ-system trade-offs and growth trajectories. Broader insights will require explicitly considering how SMR variation relates to adaptive trade-offs among ecological and physiological traits along a slow–fast metabolic continuum (Lovegrove 2003; Careau et al. 2010). However, there are multiple axes of both ecological variation and metabolic response, and the pursuit of a single dominant adaptive axis to explain all variation may prove elusive (Careau & Garland 2012). A more promising approach may be to identify whether discrete ecological and physiological trade-offs are consistently associated with specific ecological contexts, in support of a coherent framework for organizing the diversity of growth-related metabolic responses observed in nature.

Acknowledgements We would like to thank Shaun Killen, John R. Post, and several anonymous reviewers for insightful comments that greatly improved the manuscript.

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© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society, Journal of Animal Ecology

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Supporting Information Additional Supporting Information may be found in the online version of this article. Appendix S1. This includes supporting data and references for Fig. 4. Appendix S2. This includes supporting data and references for Fig. 6. Appendix S3. This includes supporting data for Table 1, and a brief description of methods and analysis for calculating the extent of SMR inflation for fish reared at different rations. Appendix S4. This includes parameter values for the Von Bertalanffy growth equations used in Fig. 8. Appendix S5. SDA Duration Main data file MARCH 2014.

© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society, Journal of Animal Ecology