Components of standard metabolic rate variability in three species of gammarids

Standard metabolic rate is a major functional trait with large inter-individual variability in many groups of aquatic species. Here we present results of an experimental study to address variation in standard metabolic rates, over different scales of organisation and environments, within a specific group of aquatic macro-invertebrates (i.e. gammarid amphipods) that represent the primary consumers in detritus food webs. The study was carried out using flow-through microrespirometric techniques on male specimens of three gammarid species from freshwater, transitional water and marine ecosystems. We examined individual metabolic rate variations at three scales: (1) at the individual level, during an 8 h period of daylight; (2) at the within-population level, along body-size and body-condition gradients; (3) at the interspecific level, across species occurring in the field in the three different categories of aquatic ecosystems, from freshwater to marine.

We show that standard metabolic rates vary significantly at all three scales examined, with the highest variation observed at the within-population level. Variation in individual standard metabolic rates during the daylight hours was generally low (coefficient of variation, CV<10 %) and unrelated to time. The average within-population CV ranged between 30.0 % and 35.0 %, with body size representing a significant source of overall inter-individual variation in the three species and individual body condition exerting only a marginal influence. In all species, the allometric equations were not as steep as would be expected from the 3∕4 power law, with significant variation in mass-specific metabolic rates among populations. The population from the transitional water ecosystem had the highest mass-specific metabolic rates and the lowest within-population variation.

In the gammarid species studied here, body-size-independent variations in standard individual metabolic rates were higher than those explained by allometric body size scaling, and the costs of adaptation to short-term periodic variations in water salinity in the studied ecosystems also seemed to represent a major source of variation.

1 Introduction

Transitional waters are ecotone ecosystems occurring at the interface between terrestrial, marine and freshwater ecosystems (Basset et al., 2013); they are highly productive and valuable aquatic ecosystems (Costanza et al., 2014; Madricardo et al., 2017), shaped by strong contrasting forces (Basset et al., 2013) and subject to multiple disturbance pressures (Elliott and Quintino, 2007).

The spatial and temporal variability of water salinity (Akin et al., 2005; Basset et al., 2013), the high nutrient supply and the strong gradients of both nutrient concentrations (Pérez-Ruzafa et al., 2005; Basset et al., 2013) and dissolved oxygen (Hull et al., 2008; Cozzoli et al., 2013; Shokri et al., 2014) are the main “natural” sources of disturbance. Potential coloniser species, being of freshwater and marine origin (Barnes, 1989; Ciotti et al., 2015), need to cope with these sources of disturbance and particularly with water salinity variability and the related osmoregulation costs, which drive species' standard metabolic rates.

Individual standard metabolic rate in relation to body size has been studied in many aquatic species, especially pelagic and non-pelagic invertebrates (Glazier, 2005) including crustaceans (Ivleva, 1980; Childress et al., 1990), insects (Gutiérrez and Menéndez, 1997) and molluscs (Xiao et al., 2014), as well as fish (Killen et al., 2010; Brucet et al., 2012). Among invertebrate species, the metabolic rates of crustacea such as Cladocera (Hart and Bycheck, 2011) and Amphipoda (mainly gammarids; Dorgelo, 1973) have received particular attention due to the relevance of these groups of species to the ecological status of aquatic ecosystems (Altermatt et al., 2014). Regarding gammarids, on which this study is focused, metabolic rates have primarily been addressed in a small number of species that have been proposed for use in bio-monitoring (e.g. the freshwater Gammarus pulex (Toman and Dall, 1998; Foucreau et al., 2014) and Gammarus minus (Lowenstein, 1935; Dorgelo, 1973); the transitional water Gammarus insensibilis (Gates, 2006); and the marine Gammarus oceanicus (Halcrow and Boyd, 1967)) and have tended to explore average metabolic rates rather than their variations, despite the relevance of gammarids to all types of aquatic ecosystems and the importance of individual metabolic rates as a key individual trait (Speakman et al., 2004). Gammarids include widely distributed amphipod species inhabiting freshwater, brackish and marine ecosystems (Tedengren et al., 1988) that are generally characterised by their higher energy requirements than other closely related Malacostraca (Hamburger and Dall, 1990).

Allometric variations of metabolic rate with individual body mass have been described (West et al., 1997, 2002; Brown and West 2000; Brown et al., 2004), and the consistency and deviation of the slope of the allometric equations with respect to the expected value of 3∕4 has been discussed with reference to metabolic level (Glazier, 2005, 2009; Duncan et al., 2007; Sieg et al., 2009; White et al., 2009) and, particularly in ectotherms, metabolic state (White et al., 2004). In this regard, researchers have also considered ontogenic shifts in individual body shape (Hirst et al., 2014), the metabolic intensity of growth, reproduction and locomotion (Glazier, 2005), and body-size-dependent biological regulation (Glazier et al., 2015). However, the degree of variability of intra-population standard metabolic rates and the meaning and sources of such variability have received less attention, even when the implications of the allometric scaling of metabolic rates in the context of global warming are addressed (Forster et al., 2012). There is now growing interest in the ecological basis of metabolic rate variability at the individual level, which would allow a more accurate evaluation of the integrated responses of plant and animal communities to global warming (Bruno et al., 2015), ocean acidification (Lannig et al., 2010) and chemical contamination (Johnston et al., 2015). Moreover, there is increasing evidence that very small-scale, intra-individual variation may have manifold ecological consequences for population and community ecology (Herrera, 2017). In most animals, ecologically significant sub-individual variation is mostly sequential in nature, as it generally arises from ontogenetic and/or seasonal changes in individual traits (e.g. behaviour, colouration, digestive organ size) (Piersma and Lindström, 1997; Delhey and Kempenaers, 2006; Stamps et al., 2012; Herrera, 2017). Moreover, intra-individual variation has been observed to increase species' niche width (Sides et al., 2014), enhancing community-wide functional diversity (Siefert et al., 2015).

Here, we address individual-level variability in the metabolic rates of three species of gammarid amphipods: Echinogammarus olivii (H. Milne Edwards, 1830), Gammarus insensibilis (Stock, 1966) and Gammarus aequicauda (Martynov, 1931). The aim of this paper is to address the variability of individual metabolic rates at three different levels: (1) at the individual level, during periods of daylight; (2) within populations, across and within individual body size classes; and (3) among species occurring in the field in the three different categories of aquatic ecosystems, from freshwater to marine.

Within-population variation in standard metabolic rates is expected to be higher than both intra-individual and inter-species variation due to the well-known allometric scaling of metabolism with size (Kleiber, 1932; West et al., 1997; Glazier, 2005). However, earlier studies at the population level in aquatic crustaceans (Vignes et al., 2012) have also shown high intra-population variation that is independent of body size, and the relevance of this to both intra-individual and the inter-species variation is also addressed in this study.

2 Materials and methods

2.1 Study area and gammarid collection

From the taxonomic point of view, the three species selected for this study, i.e. Echinogammarus olivii (Milne Edwards, 1830), Gammarus insensibilis (Stock, 1966) and Gammarus aequicauda (Martynov, 1931), belong to the Gammaroidea superfamily, while in functional terms they are shredders and scrapers. We studied one population per species, which were sampled from coastal marine, transitional water and freshwater ecosystems in the Salentine Peninsula (Fig. 1) in spring 2016 (April until early May).

Figure 1 Map of the study area, Salentine Peninsula, Italy.

Echinogammarus olivii (Milne Edwards, 1830) is considered a marine species (Costello, 2001) inhabiting shallow coastal and transitional ecosystems in the Mediterranean Sea and Black Sea (Gönlügür-Demirci, 2006; Varigin, 2015). The maximum body length in males is 13 mm and females are slightly smaller (Pinkster, 1993). For this study we sampled an E. olivii population colonising – at relatively high densities – coastal marine ecosystems in the area of Sant'Isidoro located on the west coast of the Salentine Peninsula and lying within the Porto Cesareo Marine Protected Area.

Gammarus insensibilis (Stock, 1966) is an Atlantic–Mediterranean species (Costello, 2001) occurring in both marine and brackish ecosystem types (Gilliland and Sanderson, 2000; Prato and Biandolino, 2005); the maximum body length in males is 19 mm and females are slightly smaller (WoRMS, http://www.marinespecies.org/, last access: 1 April 2018). This species was sampled in the Acquatina lagoon which is an artificially embanked, small non-tidal lagoon located on the Adriatic side of the Salentine Peninsula. The lagoon is relatively shallow and linked to the sea and thus to the neighbouring coastal marine ecosystems by two modified channels. To the north is the Giammatteo channel, almost always closed by accumulations of sand and Posidonia oceanica detritus, and to the south is the main channel. Large meadows of Cymodocea nodosa and Ruppia sp. occur on the south side of the lagoon from spring to autumn (Maci and Basset, 2010). Previous studies of nutrient concentrations and primary producer biomass allow Acquatina to be classified as an oligotrophic basin (Fiocca et al., 1998).

The main freshwater input in Acquatina is a ramification of the Giammatteo channel, fed by precipitation and groundwater (Verschut et al., 2015; Boggero et al., 2017) and characterised by a benthic habitat consisting of rocky boulders and dense accumulations of leaf detritus. It was in this channel that we sampled Gammarus aequicauda (Martynov, 1931), which is one of the most abundant and widely distributed gammarids in the coastal ecosystems of the Mediterranean Sea and Black Sea (Ruffo, 1982). The maximum length is 25 mm in males and 20 mm in females (Kevrekidis and Koukouras, 1988).

Specimens were sampled by hand net (2 mm mesh) and trophic traps, which consisted of plastic mesh bags of reed leaves (Phragmites australis (Cav.) Trin. ex Steud.) that had previously been conditioned for 14 days (Petersen and Cummins, 1974) using three recirculating experimental channels filled with original water from the field collection sites. The conditioned reed leaves were then left for 1 week at their respective field sites before specimen collection. At least 500 individuals per species per site were collected and attributed to a single population per species since the area sampled was relatively small, corresponding to no more than 100 m of coastline per site.

2.2 Laboratory procedures

Specimens of the three gammarid populations were transferred to the lab at the Experimental Research Centre for Biodiversity and Ecosystems (BIOforIU) of Salento University in thermal-insulated containers filled with water from the sampling sites and aerated during transport. In the lab, specimens were then acclimated for at least 1 week and reared using the BIOforIU integrated microcosm system, which consists of blocks of 32 L aquaria fed with three lines of artificial water, i.e. fresh, brackish and marine, in order to set the same water salinity as the three gammarid species were experiencing at the field sampling sites. Decaying reed leaves were supplied as food in the aquaria and renewed at weekly or fortnightly intervals depending on consumption. The microcosms have remote controlled temperature and conductivity, and dissolved oxygen can be manipulated when required (http://bioforiu.unisalento.it/, last access: 1 April 2018). Six microcosms per species were used for acclimating specimens to laboratory conditions. A photoperiod of 12 h : 12 h light–darkness with a constant temperature of 18±0.3 ^∘C was applied to all microcosms, and water salinity was set to the values required by the different species, using artificial fresh water (Naylor et al., 1989) as a source of fresh water (0.3 PSU) and artificial salt water (35 g L⁻¹ of Askoll marine salt) as a source of marine water. Brackish water (21 PSU) was obtained by mixing fresh water and marine water (60 %–40 %). The experimental temperature (18.0 ^∘C) was close to that of the waters of the various field sites at the time of specimen collection (Table 1). The main water parameters for the acclimation period in the aquaria and for metabolic rate assessment are shown in Table 2 for each species.

Table 1 Sampling stations, geographical coordinates and mean annual physico-chemical parameters.

Table 2 Artificial water parameters used for acclimation and experimental assessment.

Before the start of the laboratory experiments, specimens of each species were sorted by sex under a Nikon stereomicroscope (SMZ1270). Only males were selected for laboratory experiments since oocyte production in females has high costs (Glazier, 1991, 2011; Taylor and Leelapiyanart, 2001; Becker, 2016), is brief and is not predictable from an individual's external morphology. Given the high uncertainty in recognising the sex of small individuals, only specimens with a body length of more than 4 mm were used.

2.3 Standard metabolic rate

All the experiments were carried out in a thermostatic room at 18±0.3 ^∘C. A sample of 60 males per population, covering the whole range of male body size in the population of origin, was used to assess individual standard metabolic rate. However, since some individuals moulted and some died either during the assessment or the following day, the final number of individual standard metabolic rates collected per population was slight lower than 60 and differed among populations (E. olivii – n=44, G. insensibilis – n=56; G. aequicauda – n=56).

Before the assessment, individuals were kept unfed for 24 h in plastic beakers (200 mL) in the thermostatic room, after which they were transferred to the metabolic measurement system, which contains a glass water tank filled with the same water as the acclimation aquaria, magnetically stirred (using a AREC.X digital ceramic heating magnetic stirrer) and aerated with compressed air. A peristaltic pump (Watson-Marlow 205U) provided constant water flux. Water was pumped into 12 metabolic chambers (6 mL volume), each containing a single individual. Upon exiting the chambers, the water was pumped via silicone tubes to a microelectrode where the oxygen concentration was measured by oxymeter, which transformed the electrical signals into oxygen partial pressure values, which were analysed using Strathkelvin 929 data analysis software. To assess the standard metabolism of individual gammarids, we set the flow rate to approximately 6 mL h⁻¹ in order to ensure a ΔTorr in the experimental chambers of between 4 and 40 Torr, with a residual oxygen saturation of 75 %–80 %. On the basis of the selected flow rate, the water turnover time in the experimental chambers was set at 1 h and, following Lampert (1984), a 3 h equilibration time was fixed as the time required to reach a steady concentration of dissolved oxygen. In any case, the flow rate was deterministically assessed each day on each line by weighing the water flowing out through the syringe in a defined time in order to be able to detect any stochastic variations in the flow rate in specific chambers at specific times, avoiding biases in the dataset. The coefficient of variation of the chambers' control readings was lower than 2 %. The standard metabolism of each individual was assessed three times in an 8 h period, the first assessment at the end of the equilibration time and the other two at 2.5 h intervals. The three repeated measurements were used only to evaluate intra-individual variation and to determine whether the small experimental chambers were causing stress effects on individual standard metabolism. Every day, two blank measurements were performed, at the beginning and at the end of the measurement in the experimental chambers and all components of the system were cleaned.

The oxygen consumed by each individual ($V_{{\mathrm{O}}_{\mathrm{2}}}$) was estimated by calculating the difference between the dissolved oxygen concentration flowing into each experimental chamber and that of the water flowing out of the same experimental chamber, in accordance with the following formula:

$${\displaystyle }{V}_{{\mathrm{O}}_{\mathrm{2}}}=\left(\text{ppin}-\text{ppout}\right){\text{sc}}_{{\mathrm{O}}_{\mathrm{2}}}\text{FR},$$

where ppin is the dissolved oxygen partial pressure in torr of the inflow water (100 % saturation), PPout is that of the outflow water, FR is the water flow rate (µmol h⁻¹) and sc${}_{{\mathrm{O}}_{\mathrm{2}}}$ is the solubility coefficient of dissolved oxygen in water ($\mathrm{\mu }\mathrm{mol}{\mathrm{L}}^{-\mathrm{1}}{\mathrm{Torr}}^{-\mathrm{1}}$) (Cai et al., 1999). The turnover time (J) needed to reach a steady state depends on the system's characteristic flushing time:

$${\displaystyle }J\left(h\right)={\displaystyle \frac{\mathit{\omega }}{U}},$$

where W is the chamber volume (mL) and U is the water flow rate (mL h⁻¹) (Lampert, 1984). Metabolic measurements were performed in three replicates for each individual.

2.4 Specimen body size

After metabolic measurement, we measured the body length and dry weight of each individual.

For measurement of body length (BL), individuals were anaesthetised in carbon-dioxide-saturated water and measured from the base of the antennae to the beginning of the first urosome (Basset and Glazier, 1995) by an image analysis system (Leica QWIN 3) using a stereomicroscope (Leica MZ12) to the nearest 0.01 mm.

For measurement of body dry weight (DW), the animals were dried individually in an oven at 60 ^∘C for 72 h and weighed on a Sartorius MC5 micro balance to the nearest ±0.001 mg.

Weight × length relationships were quantified by fitting the power function: DW=aL^b, where DW is body dry weight (mg) and L is standard body length (in mm).

We also estimated the body condition index (BCI), which reflects an animal's energetic state and is generally considered to be an indicator of its health, quality, and vigour (Rowe and Houle, 1996; Schulte-Hostedde et al., 2005; Peig and Green, 2009; Cox et al., 2014). Here, BCI is expressed as the residuals in log scale of each individual body weight from what was expected from the weight × length relationship (Jakob et al., 1996), in accordance with the following formula:

$${\displaystyle }\text{BCI}=\log \left({\text{DW}}_{\mathrm{i}}\right)-\log \text{Expected(DW)},$$

where Expected(DW) $=\log \left(a\right)-\left(b\right)\log \left(L_{\mathrm{i}}\right)$ is the predicted DW for an average individual of length L_i, obtained from all individuals in a given population.

3 Data analysis

The mass-specific standard metabolic rate (mass-specific SMR) at the individual level, defined as the resting energy expenditure per unit body mass per day, was computed here with individual body mass expressed as individual dry weight (Wilhelm et al., 2006; Glazier et al., 2011; Lagos et al., 2017), in accordance with the following formula:

$$\begin{array}{}\text{(1)}& {\displaystyle }\text{mass-specific standard metabolic rate}={\displaystyle \frac{M_{{\mathrm{O}}_{\mathrm{2}}}}{\text{DW}}},\end{array}$$

where $M_{{\mathrm{O}}_{\mathrm{2}}}$ is the individual standard metabolic rate and DW is the individual dry weight. The coefficient of variation was calculated from daily replicate SMR measurements for each species, and compared among species with one-way ANOVA.

We used parametric statistics (one-way ANOVA) to compare the mean values for weight, length and standard metabolic rates among the three species, considering that these tests were statistically independent and, therefore, individual p values were interpreted with caution.

Standard metabolic rates were compared among populations using ANCOVA with log-transformed data in order to linearise the relationship with body dry weight (covariable) and to meet model assumptions of the normality of residuals and homogeneity of variance. The assumption of slope homogeneity (interaction between populations and slope) was tested before conducting comparisons among populations.

Standard OLS regression analyses were used to measure the linear dependency of mass-specific standard individual metabolic rates on individual body condition (BCI) and body dry weight (DW), respectively.

4 Results

4.1 Individual body size

The body length of male individuals ranged from 4.4 to 13.0 mm and their body weight from 0.59 to 8.21 mg. The average individual body length differed significantly among species (one-way ANOVA: $F_{\mathrm{2},\mathrm{133}}=\mathrm{4.619}$, P<0.05), with E. olivii individuals smaller than those of G. aequicauda (post hoc Student's t test, P<0.05), while individual body weight did not differ among species ($F_{\mathrm{2},\mathrm{133}}=\mathrm{1.596}$, P>0.05).

For all three species, significant weight × length relationships were observed. They explained 55.4 % and 91.0 % of body weight variation for E. olivii and G. insensibilis respectively (Fig. 2). Overall, the slopes of the weight–length relationships differed significantly among species (ANCOVA: $F_{\mathrm{2},\mathrm{130}}=\mathrm{7.23}$, P<0.05). Regarding species pairs, the slope of the G. insensibilis weight × length relationship was higher than those of G. aequicauda and E. olivii (a post-hoc ANOVA, Tukey's multiple comparison: $F_{\mathrm{2},\mathrm{130}}=\mathrm{7.23}$, P<0.0001). The slopes of the G. aequicauda and E. olivii weight × length relationships did not differ, allowing a comparison between the intercepts, which were higher in the latter than the former (ANCOVA: $F_{\mathrm{1},\mathrm{78}}=\mathrm{5.35}$, P<0.05). The unexplained variance of the weight × length relationships was assumed to be due to differences in body condition between individuals. The intra-population variation in body condition was higher in E. olivii than in G. insensibilis (two-tailed F test =1.94; d.f. =90; P<0.05), while there were no differences between the other species pairs.

Figure 2 Weight × length allometric relationships in species sampled in freshwater (a), brackish (b) and marine (c) ecosystems.

4.2 Individual standard metabolic rates

The standard metabolic rate of the individuals of the three species ranged between 0.42 and 3.71 J d⁻¹, considering differences in standard metabolic rate over time for each individual, among individuals of the same population and among the three species.

The differences in the standard metabolic rate of each individual during the 8 h period are expressed as the coefficient of variation (CV %). The intra-individual CV % was generally low and independent of the time spent by individuals in the experimental chambers. In only 4 % of the tested individuals did their average standard metabolic rates have coefficients of variation higher than 20 %, and the average CV % at the population level lay within in a very restricted range: from 8.94 % ±5.91 % (Gammarus aequicauda) to 9.68 % ±5.41 % (Gammarus insensibilis) (Fig. 3). Moreover, standard metabolic rates at the individual level showed no pattern of variation among repeated measurements of the same individual (paired Student's t test, not significant for all comparisons). Hereafter, only the values of individual average standard metabolic rate were used for analyses.

Figure 3 Coefficient of variation of the standard metabolic rate of the three species at the individual level during the experimental period (confidence interval: 95 %).

Overall, while individual body mass did not vary significantly among species, average standard metabolic rates were higher in Gammarus aequicauda (1.55±0.49 J d⁻¹) than Gammarus insensibilis (1.46±0.50 J d⁻¹) and Echinogammarus olivii (1.11±0.36 J d⁻¹), (ANOVA: $F_{\mathrm{2},\mathrm{150}}=\mathrm{12.711}$, P<0.05) (Fig. 4).

Figure 4 Average standard metabolic rates of the three species. For each species the box represents the interquartile (confidence interval: 95 %).

The standard individual metabolic rates of all species showed significant allometric variation, and the linear fits were significant (ANOVA^a: G. aequicauda – $F_{\mathrm{2},\mathrm{54}}=\mathrm{11.27}$, P<0.05; G. insensibilis – $F_{\mathrm{2},\mathrm{54}}=\mathrm{38.67}$, P<0.05; E. olivii – $F_{\mathrm{2},\mathrm{42}}=\mathrm{5.86}$, P<0.05; Fig. 5), with slopes ranging from 0.36±0.050 to 0.32±0.095 and explained variation ranging from 12.2 % to 41.7 %. All the slopes were significantly lower than b=0.75 (ANCOVA: Gammarus aequicauda – $F_{\mathrm{1},\mathrm{42}}=\mathrm{5.87}$, P<0.01; Gammarus insensibilis – $F_{\mathrm{1},\mathrm{54}}=\mathrm{36.67}$, P<0.001; Echinogammarus olivii – $F_{\mathrm{1},\mathrm{54}}=\mathrm{11.27}$, P<0.001). The differences among the slopes were not significant (ANCOVA: $F_{\mathrm{2},\mathrm{150}}=\mathrm{0.466}$, P>0.05), while the intercepts differed significantly (ANCOVA: $F_{\mathrm{2},\mathrm{150}}=\mathrm{14.86}$, P<0.0001), with higher intercepts in Gammarus aequicauda (y intercept; 0.062±0.11, d.f. =54) than Gammarus insensibilis (y intercept; 0.03±0.06, d.f. =54) and Echinogammarus olivii (y intercept; $-\mathrm{0.246}\pm \mathrm{0.133}$, d.f. =42). The mass-specific variation of standard individual metabolic rates was not related to individual body size, while it was marginally related to individual body condition, since body-size-independent standard metabolic rates, as residuals from the allometric scaling equations, decreased with body condition in Gammarus aequicauda (Fig. 6; $y=-\mathrm{1.085}x+\mathrm{0.631}$; d.f. =42; P<0.05), although the explained variance was only 9.4 %.

Figure 5 The relationship of body dry weight to standard metabolic rate in the three species.

Figure 6 The relationship of body condition index to mass-specific standard metabolic rate in the three species.

5 Discussion

Since the first few decades of the 20th century (Kleiber, 1932), it has been observed that common body-size-dependent scaling patterns of basal and standard metabolism, from unicellular to multicellular organisms and homeotherms, are established when global-scale patterns or large body size ranges are considered (Tilman et al., 2004). However, at the population and within-population scales, where body size ranges are small, deviations from the observed body-size scaling patterns are commonly observed. Specifically, both scaling coefficients (Vignes et al., 2012) and individual metabolic rates deviate from the best approximation of the body-size scaling patterns (Tilman et al., 2004).

Concerning the components of body-size scaling patterns at the intra-species and inter-species levels for the three gammarid species considered in the study, the results presented in this paper show the following:

• 1.

  The short-term stochasticity of individual metabolic rates is low.

• 2.

  Large body-size independent variation occurs in standard individual metabolic rates within populations, with deviation of the observed scaling coefficient from the expected patterns.

• 3.

  Standard metabolic rates vary among species that are morphologically closely related, but interspecific variation of average individual metabolic rates is low.

The key results presented in the present paper do not seem to depend on methodological bias. The individual metabolic rates of aquatic organisms are assessed in the literature by various methods including flow through (Vignes et al., 2012), closed system (Toman and Dall, 1998; Remy et al., 2017) and intermittent flow (Svendsen et al., 2016). The latter two methods have been shown to be more sensitive than the former to oxygen stress and accumulation of individual excretion products (Franke, 1977; Gnaiger, 1983; Lampert, 1984). An experiment conducted in a closed chamber with flowing water found that the metabolic rate of Gammarus fossarum directly after transfer was twice as high as it was 4 h later (Franke, 1977). Moreover, excretory products, which can accumulate in closed and intermittent systems, have been found to be harmful for lotic fauna (Gnaiger, 1983; Lampert, 1984). In the present study, we cleaned the whole apparatus every day and ran checks on blank lines twice a day to monitor eventual background shifts due to bacterial growth, but no background shift was observed. Finally, we did not conduct preliminary experiments to determine the gammarid individuals' optimal time of acclimation to the flow rate in the experimental chamber, assuming that 3 h was enough. We acknowledge that gammarids were potentially exposed to multiple stresses when in the experimental chamber, due to water flow, limited space and starvation, but the lack of any pairwise difference between repeated assessment times and across the whole period indicates that if stress responses did occur, they must have been very weak. The limited variation across repeated measurements of single individual standard metabolism and the procedure used in the measurement of partial oxygen pressure in the experimental chambers, performed only after a stabilisation of the readings, suggest that consistent measurement errors can be excluded. Therefore, the accuracy and precision of the method we used are strongly supported by the results of the present study. Indeed, the differences between the metabolic rates of individuals from one replicate to another during the experimental period were small, as also seen in Basset and Montalenti (1990) and Wrona and Davies (1984).

Our first conclusion above is supported by the lack of any significant temporal variation in individual metabolic rates during the experiment and by the very low average coefficient of variation of individual metabolic rates among replicated assessments of the same individuals. Flow-through techniques have been used in order to allow experimental measurement of the individual “resting” standard metabolic rate at fixed temperatures (Wrona and Davies, 1984). In our study, the experimental chambers allowed active swimming on the part of the individuals, which is a potential source of variability in individual standard metabolic rates, but generally the chambers were not large enough to exclude stress, which could also affect the standard metabolism of individuals.

Analyses of variation in the standard metabolic rate of single individuals during daylight periods are not common in the literature, since most papers, regardless of the methodology used, perform a single measurement per individual per day. However, our observations are consistent with those of Basset and Montalenti (1990) concerning Gammarus pulex, which also found a low coefficient of variation of metabolic rate among replicates and suggest that the experimental conditions and individual swimming behaviour allowed by the chamber size do not constitute substantial sources of variation in individual standard metabolic rates in the three species of gammarids considered in this study.

Our second conclusion is supported by the fact that body size explained only 12.2 % to 41.7 % of overall inter-individual variance in standard metabolic rates in the three studied species. Despite significant differences in both the intercepts of the allometric equations at the population level and the residuals of the pooled allometric regressions, the body weight of each of the three species exerted a strong influence on standard metabolism. Individuals of the two larger species, i.e. G. aequicauda and G. insensibilis, have significantly higher standard metabolic rates than those of the smaller species, i.e. E. olivii, which is supported by the global rule that the metabolic rate is higher in larger animals than smaller ones (Lampert, 1984). Based on the different intercepts of the weight–length relationships and the better body condition in E. olivii than the others, species shape could potentially interfere with metabolic rate.

Typically, the relationship between metabolic (respiration) rate (R) and body mass (M) is expressed as a power function, R=αM^b. It is widely accepted that the scaling exponent, b, is 3∕4, the so-called 3/4 power law (Brody, 1945; Hemmingsen, 1960; Kleiber, 1962; McMahon and Bonner, 1983; Peters, 1983; Calder, 1984; Schmidt-Nielsen, 1984; Blaxter, 1989; Brown and West, 2000; Savage et al., 2004). The results of this study confirm the size dependency of the metabolic rates of all the studied species in accordance with the allometric scaling model, with scaling coefficients ranging from 0.32 to 0.36. These scaling coefficients do not differ from each other, but they are significantly lower than the 0.75 value commonly observed (Kleiber, 1932; Peters, 1983) when interspecific comparisons are performed. Similar results to ours have also been observed in Lekanesphaera monodi along habitat productivity gradients (Vignes et al., 2012). Some of the most convincing evidence against the universality of 3∕4 power scaling comes from studies of intraspecific (ontogenetic) metabolic scaling (Glazier, 2005). Indeed, at the intraspecific level the size range is much smaller than in interspecific comparisons, and it has already been shown that under such conditions, factors other than body mass can affect individual metabolic rates (West et al., 1997). Based on a review of the literature, Glazier (2005) found that scaling coefficients show departures from the Kleiber–Peters scaling exponent (b=0.75) even for species with a wide range of body sizes (up to 5 orders of magnitude). He also found a wide range of variation of the scaling coefficient, from $b=-\mathrm{1.20}$ to b=2.05, for invertebrate species (Glazier, 2005). The metabolic rate allometric scaling coefficients observed for the three species in this study are well within this range, although they are lower than the average values that have been observed for amphipods generally.

Our third conclusion is supported by the comparison of residuals, which were calculated for the three species using a single pooled equation, demonstrating that the metabolic rate of E. olivii was significantly lower than those of G. aequicauda and G. insensibilis. The difference among species might be attributable to different osmoregulation and energetic costs along the salinity gradient between freshwater and marine ecosystems. This explanation was also proposed by Sutcliffe (1984). Glazier and Sparks (1997) showed that freshwater and estuarine gammarid species have significantly higher metabolic rates than those of marine species. In general, the mean metabolic rate of freshwater species is 60 %–65 % higher than that of brackish–marine species (Sutcliffe, 1984). Thienemann (1928) suggested that oxygen uptake is easier in water with higher salinity. Schlieper (1929) measured the metabolic rate of several brackish water animals at various salinities and found that the oxygen consumption of Carcinus generally increased with salinity. Within the gammarids, the brackish water species Gammarus chevreuxi has a higher metabolic rate than the marine Marinogammarus marinus (currently Echinogammarus marinus (Leach, 1815) according to the World Register of Marine Species , WoRMS), while the freshwater Gammarus pulex has a higher metabolic rate than either of them (Potts and Parry, 1964). Therefore, the results found in this paper are in agreement with most of the available evidence on amphipod gammarid species.

The metabolic rate per unit of mass in Echinogammarus olivii, which lives in marine ecosystems, was lower than other species in fresh and brackish waters. This could be related to their osmoregulation energy cost because the haemolymph of marine species is closer to seawater than fresh water, so species living in freshwater ecosystems usually consume more energy for osmoregulation. Similar results were also found by the Graetz (1931) study of the euryhaline stickleback, Gasterosteus, which, despite living for a long period in fresh water, has a higher metabolic rate in fresh water than in isosmotic seawater, where blood chloride equals environmental chloride. Wolvekamp and Waterman (1960) showed that oxygen uptake in freshwater, brackish and marine Gammarus species falls progressively while the salinity of their respective habitats rises.

Water salinity is only one of several abiotic factors that have been observed to affect individual metabolic rates in various species of Crustacea. These include the following: (i) water temperature, including short-term and prolonged fluctuations (Newell, 1969), e.g. various Idotea species (Adcock, 1982; Meyer and Phillipson, 1983; Vetter et al., 1999; Salomon and Buchholz, 2000); (ii) water salinity, with a direct response in terms of standard metabolic rates to increasing water salinity, e.g. Palaemon peringueyi (Allan et al., 2006) and Uca pugnax (Shock et al., 2009), but see also Gammarus oceanicus (Normant et al., 2004); (iii) dissolved oxygen concentration, e.g. Gammarus pseudolimnaeus (Hoback and Barnhart, 1996; a curvilinear “bell-shaped” relationship was observed); (iv) habitat productivity, with a direct response of standard metabolic rates to increasing habitat productivity, e.g. Lekanesphaera monodi (Vignes et al., 2012); and (v) resource quality, with a direct response of standard metabolic rates to increasing resource quality, e.g. Gammarus aequicauda fed on live prey or Flabellia petiolata or P. oceanica leaves (Remy et al., 2017).

6 Conclusion

The results of this paper show that most variation in the standard metabolic rates of gammarids occurs at the within-population level and is large enough to determine significant deviations from the expected 3∕4 metabolic theory law, with much lower scaling coefficients for all species. Standard metabolic rate variation within individuals and between species was lower than within populations, probably since the three selected species were similar in size. The difference standard metabolic rates might also be due to non-adaptive reasons in the three studied species (Garland and Adolph, 1994). However, the lower metabolic cost of E. olivii with respect to both G. insensibilis and G. aequicauda might also suggest the need for a greater focus on osmoregulation costs for gammarid species along salinity gradients in order to explain the relevance of marine species as colonisers of transitional water ecosystems (Ciotti et al., 2015).

The results of this study seem to support the arguments of Glazier (2005), i.e. that it is essential to look beyond the 3∕4 power law and consider the great diversity of metabolic scaling relationships that exist in the living world and that changes in metabolic rate with individual age can occur due to ontogenetic shifts in individual growth and locomotion costs. Additional studies, disentangling the influence of individual body size and age, are required in order to deepen our understanding of the causes of the observed deviation in the metabolic scaling coefficients of the three gammarid species studied here and more generally the observed deviations in studies at the population level.