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Metabolic rate thermal plasticity in the marine annelid Ophryotrocha labronica across two successive generations

Published online by Cambridge University Press:  20 June 2022

Gloria Massamba–N'Siala*
Affiliation:
Département de Biologie, Chimie et Géographie, Université du Québec à Rimouski, 300 Allée des Ursulines, Rimouski, QC G5L 3A1, Canada Centre d'Ecologie Fonctionnelle et Evolutive (CEFE‒CNRS), UMR 5175, Montpellier Cedex 5, France
Marie Hélène Carignan
Affiliation:
Département de Biologie, Chimie et Géographie, Université du Québec à Rimouski, 300 Allée des Ursulines, Rimouski, QC G5L 3A1, Canada
Piero Calosi
Affiliation:
Département de Biologie, Chimie et Géographie, Université du Québec à Rimouski, 300 Allée des Ursulines, Rimouski, QC G5L 3A1, Canada
Fanny Noisette
Affiliation:
Département de Biologie, Chimie et Géographie, Université du Québec à Rimouski, 300 Allée des Ursulines, Rimouski, QC G5L 3A1, Canada Institut des Sciences de la Mer, Université du Québec à Rimouski, 310 Allée des Ursulines, Rimouski, QC G5L 3A1, Canada
*
Author for correspondence: Gloria Massamba–N'Siala, E-mail: massamba.gloria@gmail.com
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Abstract

Marine ectotherms have evolved a range of physiological strategies to cope with temperature changes that persist across generations. For example, metabolic rates are expected to increase following an acute exposure to temperature, with potential detrimental impacts for fitness. However, they may be downregulated in the following generation if offspring experience the thermal conditions of their parents, with a resulting decrease in maintenance costs and fitness maximization. Yet, trans-generational studies on metabolic rates are few in marine ectotherms, thus limiting our ability to accurately predict longer-term implications of ocean warming on organisms' performance, metabolic rates being the fundamental pacemaker for all biological processes. This is particularly true for small-size organisms, for which the determination of individual metabolic rates has been historically challenging, and for many groups of marine invertebrates, such as annelids, which are under-represented in physiological investigations. Here, we exposed the subtidal annelid Ophryotrocha labronica (body length: ~4 mm) to a thermal gradient (21, 24, 26, 29°C) and measured, for the first time in this species, the temperature dependence of metabolic rates across two generations. We found that metabolic rates were positively related to temperature, but this relationship did not differ between generations. Our study provides additional evidence for the diversity of temperature-associated physiological responses of marine ectotherms and offers a number of methodological recommendations for unveiling the mechanisms underpinning the observed trans-generational responses of metabolic rates in marine annelid species.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of Marine Biological Association of the United Kingdom

Introduction

Phenotypic plasticity is a ubiquitous mechanism enabling organisms to rapidly respond to environmental changes via modifying their phenotype without changes to their genotype (West-Eberhard, Reference West‒Eberhard1989). Phenotypic plasticity of physiological traits (hereafter physiological plasticity) is increasingly investigated for its key role in mediating marine ectotherms' responses to climate-associated environmental changes, such as the increase in the mean and variation of global, regional and local ocean temperatures. Environmental temperature, in fact, has a primary importance in defining the physiological status of marine ectotherms (Pinsky et al., Reference Pinsky, Eikeset, McCauley, Payne and Sunday2019), and organismal physiology provides in turns the mechanistic link between ecological processes and their susceptibility to ocean warming (Helmuth, Reference Helmuth2009; Somero, Reference Somero2010; Godbold & Calosi, Reference Godbold and Calosi2013; Bozinovic & Pörtner, Reference Bozinovic and Pörtner2015). Accordingly, a greater effort should be devoted to defining the role of physiological plasticity in mitigating, or reversing, the negative effects of ocean warming on marine organisms across generations (Munday et al., Reference Munday, Warner, Monro, Pandolfi and Marshall2013; Calosi et al., Reference Calosi, De Wit, Thor and Dupont2016).

Plasticity in metabolic rates plays a central role for the mechanistic understanding of marine ectotherms' responses to thermal changes. Metabolic rates are the fundamental pacemaker for all biological processes and represent the overall rate of energy uptake, transformation and allocation in living systems (Brown et al., Reference Brown, Gillooly, Allen, Savage and West2004; Glazier, Reference Glazier2015). Consequently, they are among the most representative and historically used proxy for the estimation of the physiological cost of life (Brown et al., Reference Brown, Gillooly, Allen, Savage and West2004). Generally, metabolic rates are strongly affected by temperature variation due to the inherent temperature sensitivity of biochemical reactions that govern the pace of metabolism (Gillooly et al., Reference Gillooly, Brown, West, Savage and Charnov2001; Brown et al., Reference Brown, Gillooly, Allen, Savage and West2004; Clarke, Reference Clarke2004; Clarke & Fraser, Reference Clarke and Fraser2004). This ‘passive’ plasticity is commonly observed under acute temperature exposure (Gillooly et al., Reference Gillooly, Brown, West, Savage and Charnov2001; Havird et al., Reference Havird, Neuwald, Shah, Mauro, Marshall and Ghalambor2020). Under this condition, the rate of metabolic reactions, as well as the associated oxygen demand and uptake which are necessary to support cellular respiration, increase with increasing temperature before rapidly declining when temperature surpasses suboptimal levels: a response best expressed via thermal performance curves (Magozzi & Calosi, Reference Magozzi and Calosi2015; Schulte, Reference Schulte2015). The ecological importance of defining metabolic rates to help assessing species' sensitivity to climate change has been reinforced in the last decades by the discussion around the ‘oxygen and capacity-limited thermal tolerance’ (Pörtner, Reference Pörtner2001). This hypothesis emphasizes the importance of oxygen delivery efficacy in setting organisms' critical temperatures, at which transition between aerobic and anaerobic metabolism occurs and within which trade-offs between reproduction, growth and feeding may happen. Accordingly, ocean warming is expected to severely affect ectotherms' metabolic rates (Dillon et al., Reference Dillon, Wang and Huey2010), potentially resulting in reduced physiological performance and fitness (Pörtner & Farrell, Reference Pörtner and Farrell2008; Dell et al., Reference Dell, Pawar and Savage2011). This said, marine ectotherms have evolved a range of mechanisms to cope with both extreme temperature changes (e.g. heatwaves) and long-lasting warming. If the exposure to the new thermal condition persists, organisms can adjust their metabolic rates through acclimation, an ‘active’ plastic adjustment that can reduce or neutralize the influence of temperature on metabolic rates via compensatory responses (Careau & Garland, Reference Careau and Garland2012; Pettersen et al., Reference Pettersen, Marshall and White2018). The result is a decrease in maintenance costs and re-allocation of energy for the expression of other traits affecting the vital rates of the individual, such as growth and reproduction (Steyermark, Reference Steyermark2002; Shama et al., Reference Shama, Strobel, Mark and Wegner2014). Acclimation responses are particularly important for the resilience of marine ectotherms to ocean warming, as they allow organisms to perform efficiently over a larger thermal range (Einum et al., Reference Einum, Ratikainen, Wright, Pélabon, Bech, Jutfelt, Stawski and Burton2019).

Despite the importance of metabolic rates as predictors of marine ectotherms' capacity to withstand and respond to ongoing ocean warming (Donelson et al., Reference Donelson, Munday, McCormick and Pitcher2012; Magozzi & Calosi, Reference Magozzi and Calosi2015; Putnam & Gates, Reference Putnam and Gates2015), this physiological response has been less frequently characterized in trans-generational studies when compared with life-history traits or other proxies of metabolic adjustment, such as mitochondrial respiration (see Table 1 in Donelson et al., Reference Donelson, Salinas, Munday and Shama2018). What we know from the literature so far is that when temperature increases beyond a species' optimal condition, the consequent increase in metabolic rate is commonly accompanied by a negative impact on individual fitness (e.g. Donelson et al., Reference Donelson, Munday, McCormick and Pitcher2012; Shama et al., Reference Shama, Strobel, Mark and Wegner2014). However, if exposure is extended to the next generation, offspring may have the ability to take advantage of the parental exposure by reducing their metabolic rate – a mechanism known as trans-generational plasticity – with a resulting decrease in the energetic demand necessary for the maintenance of the organism (Donelson et al., Reference Donelson, Munday, McCormick and Pitcher2012; Shama et al., Reference Shama, Strobel, Mark and Wegner2014).

Table 1. Mean metabolic rates of Ophryotrocha labronica expressed as oxygen uptake rates for the parental (F0) and offspring (F1) generations along a gradient of four different temperatures

SE, standard error, N, sample size.

There is a limited number of studies characterizing metabolic rate plasticity across generations in small-size marine ectotherms and, more in general, in marine invertebrates, thus limiting our ability to accurately predict the longer-term implications of ocean warming on marine organisms' performance. To contribute towards filling this gap, we assessed here the thermal plasticity of metabolic rates of the interstitial marine annelid species Ophryotrocha labronica La Greca & Bacci, Reference La Greca and Bacci1962 (Paxton & Åkesson, Reference Paxton and Åkesson2007; adult body size ~4 mm in length) across two successive generations. Specifically, we measured individual metabolic rates, for the first time in this species, following exposure to a gradient of constant temperatures chosen within the species' natural habitat thermal window. Ophryotrocha labronica is a widespread, subtidal species (Simonini et al., Reference Simonini, Massamba–N'Siala, Grandi and Prevedelli2009) that is emerging as a model organism for experimental investigations of multigenerational effects of global changes in marine organisms (Chakravarti et al., Reference Chakravarti, Jarrold, Gibbin, Christen, Massamba–N'Siala, Blier and Calosi2016; Rodríguez-Romero et al., Reference Rodríguez-Romero, Jarrold, Massamba–N'Siala, Spicer and Calosi2016; Gibbin et al., Reference Gibbin, Chakravarti, Jarrold, Christen, Turpin, Massamba–N'Siala, Blier and Calosi2017a, Reference Gibbin, Massamba–N'Siala, Chakravarti, Jarrold and Calosi2017b; Jarrold et al., Reference Jarrold, Chakravarti, Gibbin, Christen, Massamba–N'Siala, Blier and Calosi2019; Thibault et al., Reference Thibault, Massamba–N'Siala, Noisette, Vermandele, Babin and Calosi2020). Based on previous experimental observations on trans-generational metabolic rate changes (Donelson et al., Reference Donelson, Munday, McCormick and Pitcher2012; Shama et al., Reference Shama, Strobel, Mark and Wegner2014), we predict to observe in O. labronica a temperature-dependent increase of metabolic rates in the first generation of exposure, followed by their downregulation in the second generation, a pattern that would suggest the occurrence of a full or partial compensatory response mediated by trans-generational plasticity.

Materials and methods

Specimen collection and maintenance

Ophryotrocha labronica is a gonochoric species that colonizes coastal environments enriched in organic matter (Simonini et al., Reference Simonini, Massamba–N'Siala, Grandi and Prevedelli2009, Reference Simonini, Grandi, Massamba–N'Siala, Martino, Castelli and Prevedelli2010). Females lay eggs in tubular masses that are externally fertilized by males and cared for by at least one parent until they hatch (Paxton & Åkesson, Reference Paxton and Åkesson2007). In this study, we used a laboratory strain descended from ~60 individuals collected in the port of Gela, Italy (37°04′32.52″N 14°14′13.34″E), following the protocol described by Prevedelli et al. (Reference Prevedelli, Massamba–N'Siala and Simonini2005). Prior to the experiment, the collected specimens were kept for four generations at 24°C, a temperature found within the natural thermal range (14–30°C) experienced by this species and considered optimal for laboratory rearing (Prevedelli & Simonini, Reference Prevedelli and Simonini2001; Massamba‒N'Siala et al., Reference Massamba–N'Siala, Simonini, Castelli, Prevedelli, Cossu, Maltagliati, Castelli and Prevedelli2011, Reference Massamba–N'Siala, Calosi, Bilton, Prevedelli and Simonini2012). This exposure aimed to reduce the influence of the thermal history of the experimental individuals on their responses to the experimental temperatures. Conditions of salinity (34‰) and photoperiod regime (12 h:12 h dark:light) were maintained constant throughout the experiment (Massamba‒N'Siala et al., Reference Massamba–N'Siala, Simonini, Castelli, Prevedelli, Cossu, Maltagliati, Castelli and Prevedelli2011, Reference Massamba–N'Siala, Calosi, Bilton, Prevedelli and Simonini2012). Artificial seawater was prepared by mixing distilled water (type II) with artificial sea salt (Instant Ocean™, Blacksburg, VA, USA).

Experimental design

The F0 generation of our experiment was composed of 60 reproductive pairs randomly taken from the cultures at the fourth generation of exposure to the reference conditions and formed before first reproduction occurred. Pairs were equally and randomly assigned to one of four experimental temperatures: 21, 24, 26 and 29°C. Each pair was isolated in one well of a six‒well flat bottom culture plate (Tissue Culture Plates, VWR International, Radnor, PA, USA). After the first egg mass was laid, hatchlings (the F1 generation) were transferred to a new plate immediately after being released from the egg mass and kept in the same conditions as their parents until they produced their first egg mass. Metabolic rates were measured individually on 13–20 specimens per generation per temperature treatment, and employing a similar number of individuals between males and females, immediately after the first reproductive event: ~28 days post-hatch at 21°C, 20 days at 24°C, and 10–15 days at 26 and 29°C. For all measurements, selected females bore no visible eggs in the coelom, thus avoiding confounding effects associated with energy allocation toward reproduction (Ellis et al., Reference Ellis, Davison, Queirós, Kroeker, Calosi, Dupont, Spicer, Wilson, Widdicombe and Urbina2017).

The experimental temperatures were chosen within the thermal range experienced by the studied species at the collection site, and comprised the optimal range for survival, growth and reproduction (Prevedelli & Simonini, Reference Prevedelli and Simonini2001). Constant temperature, salinity and photoperiod conditions were recreated inside environmental climatic chambers (MLR‒352H‒PA, Panasonic Healthcare Co. Ltd, Tokyo, Japan). Initial exposure was achieved by progressively increasing/decreasing temperature by a rate of 1°C h‒1 from the rearing temperature (24°C) (Massamba–N'Siala et al., Reference Massamba–N'Siala, Calosi, Bilton, Prevedelli and Simonini2012). Specimens were fed weekly ad libitum with minced spinach at a frequency and quantity that allowed all the spinach to be eaten, avoiding the accumulation of leftovers, the proliferation of bacteria or the accumulation of undesired compounds. Preliminary trials showed that water changes carried out every 2 days maintained stable salinity conditions and oxygen levels >70%. Temperature and salinity values were also measured every 2 days throughout the experiment with a high accuracy J/K input thermocouple thermometer (type K, HH802U, ± 0.1°C, Saint-Eustache, QC, Canada) and a portable refractometer (DD H2Ocean, ± 1.0, MOPS aquarium supplies, Hamilton, ON, Canada), respectively. Mean environmental values are reported in Supplementary Appendix S1.

Determination of metabolic rates

Metabolic rates (MO2) were determined by using routine oxygen uptake rates as a proxy (Ege & Krogh, Reference Ege and Krogh1914), specifically allowing the specimens to move freely within the vials without any physical constrains causing stressful conditions. Individual MO2 measurements were obtained by miniaturizing a technique based on the optical detection of molecular oxygen (Peck & Moyano, Reference Peck and Moyano2016), already used on larger-sized organisms (Marsh & Manahan, Reference Marsh and Manahan1999; Papkovsky & Dmitriev, Reference Papkovsky and Dmitriev2013; Noisette et al., Reference Noisette, Bordeyne, Davoult and Martin2016). Individuals were transferred to a glass bowl containing filtered seawater to remove food and faecal particles, thus reducing microbial contamination and therefore background respiration. Seawater was filtered through Whatman® glass microfibre filters (grade GF/F 0,7 μm, GE Healthcare, Chicago, IL, USA). Specimens were individually transferred to modified borosilicate glass vials (volume 0.44 ml ± 0.004) with push-in airtight glass caps (Natural SepCap, Thermo Scientific, Waltham, MA, USA). Each vial was then submerged and maintained at the tested temperature over the whole incubation period inside a temperature-controlled shaking water bath (VWR International) to prevent any form of water stratification around and in the vials. The size of each individual was measured after each trial by counting the number of chaetigers, i.e. the metameric segments bearing bristles (Massamba‒N'Siala et al., Reference Massamba–N'Siala, Simonini, Castelli, Prevedelli, Cossu, Maltagliati, Castelli and Prevedelli2011). For each experimental run, 3–5 vials containing only filtered seawater (no individuals inside) were prepared following the same procedure described above. These vials were used as ‘blanks’ to determine background microbial respiration, whose average for each run was subtracted from associated individual MO2 measurements to obtain more accurate estimates for annelids' oxygen uptake rates.

Each incubation lasted no more than 2.5 h and was halted when oxygen levels reached 70% saturation in the vials to avoid exposing specimens to hypoxic conditions. Oxygen measurements were taken at the beginning and at the end of the incubation period using a non-invasive fibre-optical system (FIBOX 4, PreSens, Regensburg, Germany) consisting of an external optical fibre probe and oxygen reactive dots, which were glued to the inner wall of each vial. Temperature was monitored continuously using a thermocouple (type K, HH802U, ± 0.1°C, Saint-Eustache, QC, Canada) mounted on a digital thermometer (HH802U, Omega Eng. Inc.) and it was maintained at the designated experimental condition throughout the incubation.

Individual MO2 (μmol h‒1) were calculated as the difference in oxygen concentration [O2] between the beginning and the end of the incubation using the following equation (1)

(1)$${\rm M}{\rm O}_2 = \displaystyle{{{\rm \Delta }[ {\rm O}_2] \times {\rm V\;}} \over {{\rm \Delta t}}}$$

where ΔO2 (μmol O2 l‒1) is the difference between initial and final [O2], V (L) is the volume of the vial, and Δt (h) is the incubation time.

To assess the reliability of the MO2 measurements taken at two single moments along the incubation period, we evaluated the linearity of the relationship between the annelids' oxygen consumption and incubation time (marginal R 2/Conditional R 2 = 0.91/0.96, df = 1, P < 0.001) for a subset of 18 specimens of O. labronica not used for our experiment (see Supplementary Appendix S2 and Figure S1 for more details). Mean MO2 values obtained from this pre-trial were comparable with those obtained from other temperate marine annelids at similar temperatures, providing a further validation of our data (see Supplementary Appendix S3 and Figure S2).

Statistical analyses

To investigate the temperature-dependence of metabolic rates over two successive generations in O. labronica, we fitted a multiple linear model with individual MO2 as the dependent variables and the terms ‘Generation’ (categorical), ‘Temperature’ (continuous), and their interaction, as explanatory variables. The additive effect of the term ‘Sex’ (categorical) was included in the models to account for the effect of physiological differences between females and males (Ellis et al., Reference Ellis, Davison, Queirós, Kroeker, Calosi, Dupont, Spicer, Wilson, Widdicombe and Urbina2017). Finally, ‘Body size’ was included as covariate in all models for MO2 to control for the effect of size on metabolic rates (Clarke & Fraser, Reference Clarke and Fraser2004).

Statistical model selection was performed by removing progressively non-significant interactions (Generations × Temperature) or predictive variables (Generations, Temperature, Sex) from the full model and comparing the Akaike Information Criterion (AIC) of the different models, following the procedure of Burnham & Anderson (Reference Burnham and Anderson2002). Briefly, models were considered different when their AIC differed more than two AIC units (delta AIC), and the lowest AIC indicated the best-fit model/models.

For all models, residuals were normally distributed and met the assumption of homogeneity of variance (P > 0.05), tested by Shapiro and Bartlett's tests, respectively. All statistical analyses were performed using the R software, version 4.0.0 (R Core Team, 2013).

Results

Mean MO2 (± SE) ranged between 4.48 ± 0.48 10‒3 and 7.83 10‒3 ± 0.87 10‒3 μmol O2 h‒1 at 21 and 26°C, respectively, both measured in the F0 (Table 1). Metabolic rates significantly increased with temperature (maximum t-value = 2.90, P = 0.004; Figure 1), as indicated by the most parsimonious models explaining the observed variation in MO2 (maximum F 2,123 = 7.89, P = 0.001, adjusted-R 2 = 0.1; Table 2a–c). In addition, body size had a significant positive relationship with MO2 (maximum t-value = 2.93, P = 0.004). No significant effect of the interaction between the terms ‘Generation’ and ‘Temperature’ was found, and mean MO2 did not differ between sexes (Supplementary Appendix S4).

Fig. 1. Relationship between metabolic rates (MO2), measured as oxygen uptake rates, and seawater temperature in the annelid O. labronica across two generations of exposure to a thermal gradient. Solid and empty circles represent individual MO2 measurements for the F0 and F1, respectively. The black continuous and dotted lines represent the regression lines for the F0 and F1, respectively, and the grey shaded areas represent their 95% confidence interval.

Table 2. Results of the best–fitted linear regression models investigating the relationship between metabolic rates (MO2) and temperature (continuous variable) across two successive generations in O. labronica, controlling for the effect of sex and body size

Values of delta AIC (dAIC) are provided relative to the most parsimonious model (a). Results for models with dAIC ⩾ 2 are shown in Appendix S4.

DF, Degrees of Freedom (numerator; denominator); R2, adjusted R–squares.

Discussion

Our results demonstrate that individual metabolic rates have a positive relationship with temperature in the marine annelid Ophryotrocha labronica, but the strength and shape of this relationship does not change significantly across generations. The importance of habitat temperature in shaping metabolic rates is well documented across a variety of taxonomic groups (Fry & Hart, Reference Fry and Hart1948; Brown et al., Reference Brown, Gillooly, Allen, Savage and West2004; Clarke & Fraser, Reference Clarke and Fraser2004). Indeed, the strongest evidence for the temperature-dependence of metabolic rates comes from studies on marine ectotherms (Clarke & Fraser, Reference Clarke and Fraser2004). For example, temperature was found to account for more than 90% of variation in metabolic rates measured as resting oxygen uptake in 43 species of marine copepods collected across a latitudinal gradient (Ikeda, Reference Ikeda1985; Ikeda et al., Reference Ikeda, Kanno, Ozaki and Shinada2001). Similarly, a meta-analysis revealed that metabolic rates, again measured as resting oxygen uptake in both invertebrates (molluscs, echinoderms, cnidarians and crustaceans) and fish, increased with increasing temperature in most marine species investigated (Lefevre, Reference Le Moullac, Quéau, Le Souchu, Pouvreau, Moal, Le Coz J and Samain2016). The positive relationship between temperature and metabolic rates is assumed to approximate an exponential shape following an acute thermal exposure, a time frame during which the control of metabolic pathways is passively shaped by thermodynamic principles (Gillooly et al., Reference Gillooly, Brown, West, Savage and Charnov2001; Brown et al., Reference Brown, Gillooly, Allen, Savage and West2004). In some marine ectotherms, metabolic rates double or even triple following a rapid 10°C increase in temperature (Q 10 > 2, Ikeda et al., Reference Ikeda, Kanno, Ozaki and Shinada2001; Castellani et al., Reference Castellani, Robinson, Smith and Lampitt2005; Scheffler et al., Reference Scheffler, Barreto and Mueller2019). In our study, the temperature–metabolic rates relationship in the first generation of exposure is not as strong as we expected (Q 10 = 1.3, calculated according to Semsar-Kazerouni & Verberk, Reference Semsar-Kazerouni and Verberk2018), suggesting that an acclimation response may have already occurred in the individuals exposed to the experimental temperature conditions when metabolic rates were measured. In fish, for example, acclimation does not completely remove the effect of temperature on metabolic rates, leaving post-acclimation Q 10 values between 1.0 and 2.0 (Jutfelt, Reference Jutfelt2020), a result that supports our hypothesis. Indeed, measurements of metabolic rates at the F0 were taken between 2–4 weeks after the acute temperature exposure, a time period sufficient for many marine ectotherms to reduce the thermal sensitivity of metabolic rates through acclimation (Marshall et al., Reference Marshall, Perissinotto and Holley2003; Scheffler et al., Reference Scheffler, Barreto and Mueller2019), and likely more so for small-size (i.e. small surface to volume ratios), short-generation time species as O. labronica. For example, in the supratidal copepod Tigriopus californicus Baker, 1912, a small-size species colonizing splash pools, metabolic rates significantly increased with temperature when measured within 6 h immediately after the acute exposure to an elevated temperature, but they were unaffected by this thermal change just after 48 h of chronic exposure (Scheffler et al., Reference Scheffler, Barreto and Mueller2019). The capacity for within-generational acclimation via the weakening or disappearance of the thermal dependence of metabolic rates, known as ‘metabolic temperature compensation’ (Bullock, Reference Bullock1955; Precht, Reference Precht and Prosser1958; Somero, Reference Somero1969) allows an increase in energy efficiency by minimizing maintenance costs and maximizing energy allocation to other functions, such as survival, growth and reproduction, under varying temperatures (Robinson & Davison, Reference Robinson and Davison2008; Angilletta, Reference Angiletta2009). As such, the rapid activation of reversible compensatory responses is considered an adaptive response to temperature variation in several marine species colonizing thermal fluctuating environments, such as intertidal and subtidal zones, or shallow waters (Le Moullac et al., Reference Lefevre2007; Schaefer & Walters, Reference Schaefer and Walters2010; Healy & Schulte, Reference Healy and Schulte2012; White et al., Reference White, Alton and Frappell2012). In the opossum shrimp Gastrosaccus brevifissura Tattersall, 1952, for example, metabolic rates increased with an acute increase in temperature, but were unaffected after seven days of acclimation (Marshall et al., Reference Marshall, Perissinotto and Holley2003). Similarly, the eastern oyster Crassostrea virginica Gmelin, 1791, and the hard-shell clams Mercenaria Linnaeus, 1758, showed a lack of temperature-dependence of aerobic metabolic rates already after respectively 2 weeks and after 8–15 weeks of exposure to a 5°C increase in temperature (Matoo et al., Reference Matoo, Ivanina, Ullstad, Beniash and Sokolova2013). Finally, in the supratidal copepod T. californicus, among three populations tested, one did not increase its metabolic rates even few hours immediately after the temperature change, suggesting an even faster compensatory response to temperature increase (Scheffler et al., Reference Scheffler, Barreto and Mueller2019). Rapid within-generational adjustments of metabolic rates are plausibly adaptive also in O. labronica, a subtidal species commonly found in temperate shallow waters (Prevedelli & Simonini, Reference Prevedelli and Simonini2003; Massamba–N'Siala et al., Reference Massamba–N'Siala, Simonini, Castelli, Prevedelli, Cossu, Maltagliati, Castelli and Prevedelli2011).

The level of metabolic rate acclimation achieved in the F0 is maintained unchanged after one additional generation of exposure to the same thermal conditions. Our results diverge from previous findings reporting the occurrence of adaptive trans-generational responses to temperature increase mediated by metabolic compensation via trans-generational plasticity (Donelson et al., Reference Donelson, Munday, McCormick and Pitcher2012; Miller et al., Reference Miller, Watson, Donelson, McCormick and Munday2012; Shama et al., Reference Shama, Strobel, Mark and Wegner2014). In the tropical damselfish Acanthochromis polyacanthus, individuals exposed for two generations to elevated temperatures ( + 1.5 and + 3.0°C) showed a reduction in resting metabolic rates compared with the parental generation at the highest temperature (Donelson et al., Reference Donelson, Munday, McCormick and Pitcher2012). Similarly, metabolic compensation mediated by the maternal environment was observed in marine sticklebacks (Shama et al., Reference Shama, Strobel, Mark and Wegner2014). In this latest case, the optimization of the metabolic performance at the warmest condition was associated with the production of larger offspring than those produced by mothers exposed to cooler temperatures (Shama et al., Reference Shama, Strobel, Mark and Wegner2014). Following this line of evidence, we may suppose that the activation of trans-generational plastic responses may not be always necessary to cope with thermal changes. Similar conclusions were drawn from a trans-generational experiment with the water flea Daphnia pulex Leydig, 1860, where the beneficial effect of metabolic rate adjustment activated in the first generation of exposure to new temperature conditions extended across generations and was sufficient to maximize fitness in the new thermal environment (Kielland et al., Reference Kielland, Bech and Einum2017). Altogether, the literature on the role of metabolic rate plasticity in mediating organismal thermal responses, to which our study contributes, highlights that there is a range of different phenotypic responses to thermal variation in marine ectotherms, and points to the need for further experiments on a wider array of taxa to reach a more accurate understanding of the mechanisms that will allow species to cope with ongoing climate changes.

Our study also offers a basis for future methodological and technical improvements for the investigation of trans-generational changes in metabolic rates in this small-size, annelid species. First, a higher level of replication per treatment and a continuous monitoring of oxygen levels during the incubation period may counterbalance the high inter-individual variation of metabolic rates that we observed in our study. We found in fact a 5-fold to an 83-fold increase between minimum and maximum individual metabolic rates at 21°C in the F0 and F1, respectively. There was no clear pattern in the magnitude of inter-individual variation, being 54 and 18 at 24°C, 8 and 37 at 26°C and 38 and 6 at 29°C in the parental and offspring generation, respectively. The behavioural habits of these interstitial errant annelid species, coupled with the methodological approach used – i.e. the measurement of individual routine oxygen uptake as proxy for metabolic rates – could have been responsible for this irregular variation. In particular, the transfer of the experimental individuals into a new vial for the metabolic rate measurements, with no food or substrate to hide in, could have been stressful. These annelids can respond to disturbance by either strongly swimming in the water, slowly crawling along the vial walls, or staying immobile in the vial's bottom fold (Massamba–N'Siala, pers. obs.), a variety of behaviours that can have significant different implications for individual metabolic rates. Secondly, the implementation of full factorial designs where offspring from the same brood are assigned to different treatments, while recording any selective mortality, can help to more accurately characterize the mechanisms involved in cross-generational responses of metabolic rates, and distinguish between the contribution of genetic changes and non-genetic responses such as within- and trans-generational plasticity (Kielland et al., Reference Kielland, Bech and Einum2017; Donelson et al., Reference Donelson, Salinas, Munday and Shama2018). In fact, we cannot discard the possibility that the different genotype composition within each treatment or the potential effect of different levels of selective mortality between treatments or across generations, which we did not record, may have favoured rapid evolutionary changes in metabolic rates (Kielland et al., Reference Kielland, Bech and Einum2017; Norin & Metcalfe, Reference Norin and Metcalfe2019). The use of iso-female lines could help minimize the contribution of genetic variation in determining patterns of trans-generational changes in a sexually reproducing species as O. labronica.

In conclusion, our results provide additional evidence for the diversity of climate-associated physiological responses of marine ectotherms and suggest that the capacity, or need, for trans-generational adjustment of metabolic rates is not ubiquitous but context-dependent. Further experiments may unveil, for example, whether the level of heat stress caused by the acclimation temperature plays a role in activating trans-generational changes in metabolic rates, these changes having been often observed after exposure to suboptimal thermal conditions (e.g. Donelson et al., Reference Donelson, Munday, McCormick and Pitcher2012). Finally, our study contributes to the understanding of annelids' physiological thermal plasticity, a phylum characterized by great biodiversity, particularly in the marine environment, but still under-represented in eco-physiological investigations and global change studies.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0025315422000303

Acknowledgements

The authors would like to thank Francis Beaudet and Juliette Debacker for their help in determining the mass of the annelids and Jonathan Coudé for his technical support in the development of our method. We would like to thank Dr Daniel Small for the linguistic revision of the manuscript.

Author contributions

The experimental design has been conceived and planned by M.H.C. and F.N. with the help of G.M.N. and P.C. Experimental measurements were carried out by M.H.C. and F.N. G.M.N. conducted statistical analyses with advice from F.N. and P.C. G.M.N. and M.H.C wrote the first draft of this manuscript. All authors contributed to the final version of the manuscript.

Financial support

This work was funded by the European Union through the Marie Skłodowska-Curie Actions under the Horizon 2020 Framework Programme (G.M.N., grant number 659359), NSERC Discovery Program grant (P.C., grant number RGPIN–2015–06500, RGPIN–2020–05627), the Programme Établissement de nouveaux chercheurs universitaires of the Fonds de Recherche du Québec – Nature et Technologies (P.C., grant number 199173), and the Fonds Institutionnel de Recherche of the Université du Québec à Rimouski (P.C.).

Conflict of interest

The authors declare none.

Ethical standards

All applicable institutional and/or national guidelines for the care and use of animals were followed [Canadian Council on Animal Care].

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

References

Angiletta, MJ (2009) Thermal Adaptation: A Theoretical and Empirical Synthesis. Oxford: Oxford University Press.CrossRefGoogle Scholar
Bozinovic, F and Pörtner, HO (2015) Physiological ecology meets climate change. Ecology and Evolution 5, 10251030.CrossRefGoogle ScholarPubMed
Brown, JH, Gillooly, JF, Allen, AP, Savage, VM and West, GB (2004) Toward a metabolic theory of ecology. Ecology 85, 17711789.CrossRefGoogle Scholar
Bullock, TH (1955) Compensation for temperature in the metabolism and activity of poikilotherms. Biological Reviews 30, 311342.CrossRefGoogle Scholar
Burnham, KP and Anderson, DR (2002) A Practical Information–Theoretic Approach: Model Selection and Multimodel Inference, 2nd Edn. New York, NY: Springer.Google Scholar
Calosi, P, De Wit, P, Thor, P and Dupont, S (2016) Will life find a way? Evolution of marine species under global change. Evolutionary Applications 9, 10351042.Google ScholarPubMed
Careau, V and Garland, T Jr (2012) Performance, personality, and energetics: correlation, causation, and mechanism. Physiological and Biochemical Zoology 85, 543571.CrossRefGoogle ScholarPubMed
Castellani, C, Robinson, C, Smith, T and Lampitt, RS (2005) Temperature affects respiration rate of Oithona similis. Marine Ecology Progress Series 285, 129135.CrossRefGoogle Scholar
Chakravarti, LJ, Jarrold, MD, Gibbin, EM, Christen, F, Massamba–N'Siala, G, Blier, PU and Calosi, P (2016) Can trans-generational experiments be used to enhance species resilience to ocean warming and acidification? Evolutionary Applications 9, 11331146.CrossRefGoogle ScholarPubMed
Clarke, A (2004) Is there a universal temperature dependence of metabolism? Functional Ecology 18, 252256.Google Scholar
Clarke, A and Fraser, KPP (2004) Why does metabolism scale with temperature? Functional Ecology 18, 243251.CrossRefGoogle Scholar
Dell, AI, Pawar, S and Savage, VM (2011) Systematic variation in the temperature dependence of physiological and ecological traits. Proceedings of the National Academy of Sciences USA 108, 1059110596.Google ScholarPubMed
Dillon, ME, Wang, G and Huey, RB (2010) Global metabolic impacts of recent climate warming. Nature 467, 704.CrossRefGoogle ScholarPubMed
Donelson, JM, Munday, PL, McCormick, MI and Pitcher, CR (2012) Rapid transgenerational acclimation of a tropical reef fish to climate change. Nature Climate Change 2, 3032.CrossRefGoogle Scholar
Donelson, JM, Salinas, S, Munday, PL and Shama, LNS (2018) Transgenerational plasticity and climate change experiments: where do we go from here? Global Change Biology 24, 1334.Google Scholar
Ege, R and Krogh, A (1914) On the relation between the temperature and respiratory exchange in fishes. Internationale Revue der gesamten Hydrobiologie und Hydrographie 7, 4855.CrossRefGoogle Scholar
Einum, S, Ratikainen, I, Wright, J, Pélabon, C, Bech, C, Jutfelt, F, Stawski, C and Burton, T (2019) How to quantify thermal acclimation capacity? Global Change Biology 25, 18931894.CrossRefGoogle ScholarPubMed
Ellis, RP, Davison, W, Queirós, AM, Kroeker, KJ, Calosi, P, Dupont, S, Spicer, JI, Wilson, RW, Widdicombe, S and Urbina, MA (2017) Does sex really matter? Explaining intra–species variation in ocean acidification responses. Biological Letters 13, 20160761.CrossRefGoogle Scholar
Fry, F and Hart, JS (1948) The relation of temperature to oxygen consumption in the goldfish. The Biological Bulletin 94, 6677.CrossRefGoogle ScholarPubMed
Gibbin, EM, Chakravarti, LJ, Jarrold, MD, Christen, F, Turpin, V, Massamba–N'Siala, G, Blier, PU and Calosi, P (2017 a) Can multi-generational exposure to ocean warming and acidification lead to the adaptation of life history and physiology in a marine metazoan? Journal of Experimental Biology 220, 551563.Google Scholar
Gibbin, EM, Massamba–N'Siala, G, Chakravarti, LJ, Jarrold, MD and Calosi, P (2017 b) The evolution of phenotypic plasticity under global change. Scientific Reports 7, 17253.CrossRefGoogle ScholarPubMed
Gillooly, JF, Brown, JH, West, GB, Savage, VM and Charnov, EL (2001) Effects of size and temperature on metabolic rate. Science 293, 22482251.CrossRefGoogle ScholarPubMed
Glazier, DS (2015) Is metabolic rate a universal “pacemaker” for biological processes? Biological Reviews 90, 377407.CrossRefGoogle Scholar
Godbold, JA and Calosi, P (2013) Ocean acidification and climate change: advances in ecology and evolution. Philosophical Transactions of the Royal Society B 368, 20120448.CrossRefGoogle ScholarPubMed
Havird, JC, Neuwald, JL, Shah, AA, Mauro, A, Marshall, CA and Ghalambor, CK (2020) Distinguishing between active plasticity due to thermal acclimation and passive plasticity due to Q10 effects: why methodology matters. Functional Ecology 34, 10151028.CrossRefGoogle Scholar
Healy, TM and Schulte, PM (2012) Thermal acclimation is not necessary to maintain a wide thermal breadth of aerobic scope in the common killifish (Fundulus heteroclitus). Physiological and Biochemical Zoology 85, 107119.CrossRefGoogle Scholar
Helmuth, B (2009) From cells to coastlines: how can we use physiology to forecast the impacts of climate change? Journal of Experimental Biology 212, 753760.CrossRefGoogle ScholarPubMed
Ikeda, T (1985) Metabolic rates of epipelagic marine zooplankton as a function of body mass and temperature. Marine Biology 85, 111.CrossRefGoogle Scholar
Ikeda, T, Kanno, Y, Ozaki, K and Shinada, A (2001) Metabolic rates of epipelagic marine copepods as a function of body mass and temperature. Marine Biology 139, 587596.CrossRefGoogle Scholar
Jarrold, MD, Chakravarti, LJ, Gibbin, EM, Christen, F, Massamba–N'Siala, G, Blier, PU and Calosi, P (2019) Life-history trade-offs and limitations associated with phenotypic adaptation under future ocean warming and elevated salinity. Philosophical Transactions of the Royal Society B 374, 20180428.CrossRefGoogle ScholarPubMed
Jutfelt, F (2020) Metabolic adaptation to warm water in fish. Functional Ecology 34, 11381141.CrossRefGoogle Scholar
Kielland, ØN, Bech, C and Einum, S (2017) No evidence for thermal transgenerational plasticity in metabolism when minimizing the potential for confounding effects. Proceedings of the Royal Society B: Biological Sciences 284, 20162494.CrossRefGoogle ScholarPubMed
La Greca, M and Bacci, G (1962) Una nuova specie di Ophryotrocha delle coste tirreniche (Annelida, Polychaeta). Italian Journal of Zoology 29, 718.Google Scholar
Lefevre, S (2016) Are global warming and ocean acidification conspiring against marine ectotherms? A meta-analysis of the respiratory effects of elevated temperature, high CO2 and their interaction. Conservation Physiology 4, cow009.Google ScholarPubMed
Le Moullac, G, Quéau, I, Le Souchu, P, Pouvreau, S, Moal, J, Le Coz J, R and Samain, JF (2007) Metabolic adjustments in the oyster Crassostrea gigas according to oxygen level and temperature. Marine Biology Research 3, 357366.CrossRefGoogle Scholar
Magozzi, S and Calosi, P (2015) Integrating metabolic performance, thermal tolerance, and plasticity enables for more accurate predictions on species vulnerability to acute and chronic effects of global warming. Global Change Biology 21, 181194.Google ScholarPubMed
Marsh, AG and Manahan, DT (1999) A method for accurate measurements of the respiration rates of marine invertebrate embryos and larvae. Marine Ecology Progress Series 184, 110.CrossRefGoogle Scholar
Marshall, DJ, Perissinotto, R and Holley, JF (2003) Respiratory responses of the mysid Gastrosaccus brevifissura (Peracarida: Mysidacea), in relation to body size, temperature and salinity. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology 134, 257266.Google ScholarPubMed
Massamba–N'Siala, G, Calosi, P, Bilton, DT, Prevedelli, D and Simonini, R (2012) Life-history and thermal tolerance traits display different thermal plasticities and relationships with temperature in the marine polychaete Ophryotrocha labronica La Greca and Bacci (Dorvilleidae). Journal of Experimental Marine Biology and Ecology 438, 109117.CrossRefGoogle Scholar
Massamba–N'Siala, G, Simonini, R, Castelli, A, Prevedelli, D, Cossu, P, Maltagliati, F, Castelli, A and Prevedelli, D (2011) Life‒history and demographic spatial variation in Mediterranean populations of the opportunistic polychaete Ophryotrocha labronica (Polychaeta, Dorvilleidae). Marine Biology 158, 15231535.CrossRefGoogle Scholar
Matoo, OB, Ivanina, AV, Ullstad, C, Beniash, E and Sokolova, IM (2013) Interactive effects of elevated temperature and CO2 levels on metabolism and oxidative stress in two common marine bivalves (Crassostrea virginica and Mercenaria mercenaria). Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology 164, 545553.CrossRefGoogle ScholarPubMed
Miller, GM, Watson, SA, Donelson, JM, McCormick, MI and Munday, PL (2012) Parental environment mediates impacts of increased carbon dioxide on a coral reef fish. Nature Climate Change 2, 858861.CrossRefGoogle Scholar
Munday, PL, Warner, RR, Monro, K, Pandolfi, JM and Marshall, DJ (2013) Predicting evolutionary responses to climate change in the sea. Ecology letters 16, 14881500.CrossRefGoogle ScholarPubMed
Noisette, F, Bordeyne, F, Davoult, D and Martin, S (2016) Assessing the physiological responses of the gastropod Crepidula fornicata to predicted ocean acidification and warming. Limnology and Oceanography 61, 430444.Google Scholar
Norin, T and Metcalfe, NB (2019) Ecological and evolutionary consequences of metabolic rate plasticity in response to environmental change. Philosophical Transactions of the Royal Society B 374, 20180180.CrossRefGoogle ScholarPubMed
Papkovsky, DB and Dmitriev, RI (2013) Biological detection by optical oxygen sensing. Chemical Society Reviews 42, 87008732.CrossRefGoogle ScholarPubMed
Paxton, H and Åkesson, B (2007) Redescription of Ophryotrocha puerilis and O. labronica (Annelida, Dorvilleidae). Marine Biology Research 3, 319.CrossRefGoogle Scholar
Peck, M and Moyano, M (2016) Measuring respiration rates in marine fish larvae: challenges and advances. Journal of Fish Biology 88, 173205.CrossRefGoogle ScholarPubMed
Pettersen, AK, Marshall, DJ and White, CR (2018) Understanding variation in metabolic rate. Journal of Experimental Biology 221, jeb166876.Google ScholarPubMed
Pinsky, ML, Eikeset, AM, McCauley, DJ, Payne, JL and Sunday, JM (2019) Greater vulnerability to warming of marine vs terrestrial ectotherms. Nature 569, 108111.CrossRefGoogle Scholar
Pörtner, H (2001) Climate change and temperature-dependent biogeography: oxygen limitation of thermal tolerance in animals. Naturwissenschaften 88, 137146.Google ScholarPubMed
Pörtner, HO and Farrell, AP (2008) Physiology and climate change. Science 322, 690692.Google ScholarPubMed
Precht, H (1958) Concepts of the temperature adaptations of unchanging reaction systems of cold-blooded animals. In Prosser, CL (ed.), Physiological Adaptation. Washington, DC: American Physiological Society, pp. 5078.Google Scholar
Prevedelli, D, Massamba–N'Siala, G and Simonini, R (2005) The seasonal dynamics of six species of Dorvilleidae (Polychaeta) in the harbour of La Spezia (Italy). Marine Ecology 26, 286293.CrossRefGoogle Scholar
Prevedelli, D and Simonini, R (2001) Effect of temperature on demography of Ophryotrocha labronica (Polychaeta: Dorvilleidae). Vie et Milieu 51, 173180.Google Scholar
Prevedelli, D and Simonini, R (2003) Life cycles in brackish habitats: adaptive strategies of some polychaetes from the Venice lagoon. Oceanologica Acta 26, 7784.Google Scholar
Putnam, HM and Gates, RD (2015) Preconditioning in the reef-building coral Pocillopora damicornis and the potential for trans-generational acclimatization in coral larvae under future climate change conditions. Journal of Experimental Biology 218, 23652372.CrossRefGoogle ScholarPubMed
R Core Team (2013) R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. Available at https://www.R–project.org/.Google Scholar
Robinson, E and Davison, W (2008) The Antarctic notothenioid fish Pagothenia borchgrevinki is thermally flexible: acclimation changes oxygen consumption. Polar Biology 31, 317326.CrossRefGoogle Scholar
Rodríguez-Romero, A, Jarrold, MD, Massamba–N'Siala, G, Spicer, JI and Calosi, P (2016) Multi-generational responses of a marine polychaete to a rapid change in seawater pCO2. Evolutionary Applications 9, 10821095.CrossRefGoogle Scholar
Schaefer, J and Walters, A (2010) Metabolic cold adaptation and developmental plasticity in metabolic rates among species in the Fundulus notatus species complex. Functional Ecology 24, 10871094.CrossRefGoogle Scholar
Scheffler, ML, Barreto, FS and Mueller, CA (2019) Rapid metabolic compensation in response to temperature change in the intertidal copepod, Tigriopus californicus. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology 230, 131137.Google ScholarPubMed
Schulte, PM (2015) The effects of temperature on aerobic metabolism: towards a mechanistic understanding of the responses of ectotherms to a changing environment. Journal of Experimental Biology 218, 18561866.Google ScholarPubMed
Semsar-Kazerouni, M and Verberk, WC (2018) It's about time: linkages between heat tolerance, thermal acclimation and metabolic rate at different temporal scales in the freshwater amphipod Gammarus fossarum Koch, 1836. Journal of Thermal Biology 75, 3137.CrossRefGoogle ScholarPubMed
Shama, LNS, Strobel, A, Mark, FC and Wegner, KM (2014) Transgenerational plasticity in marine sticklebacks: maternal effects mediate impacts of a warming ocean. Functional Ecology 28, 14821493.CrossRefGoogle Scholar
Simonini, R, Grandi, V, Massamba–N'Siala, G, Martino, MP, Castelli, A and Prevedelli, D (2010) Diversity, habitat affinities and diet of Ophryotrocha species (Polychaeta, Dorvilleidae) living in Mediterranean harbour habitats. Vie et Milieu 60, 2738.Google Scholar
Simonini, R, Massamba–N'Siala, G, Grandi, V and Prevedelli, D (2009) Distribution of the genus Ophryotrocha (Polychaeta) in Italy: new reports and comments on the biogeography of Mediterranean species. Vie et Milieu 59, 7988.Google Scholar
Somero, GN (1969) Enzymic mechanisms of temperature compensation: immediate and evolutionary effects of temperature on enzymes of aquatic poikilotherms. The American Naturalist 103, 517530.CrossRefGoogle Scholar
Somero, GN (2010) The physiology of climate change: how potentials for acclimatization and genetic adaptation will determine ‘winners’ and ‘losers’. Journal of Experimental Biology 213(6), 912920. doi:10.1242/jeb.037473.CrossRefGoogle ScholarPubMed
Steyermark, AC (2002) A high standard metabolic rate constrains juvenile growth. Zoology 105, 147151.CrossRefGoogle ScholarPubMed
Thibault, C, Massamba–N'Siala, G, Noisette, F, Vermandele, F, Babin, M and Calosi, P (2020) Within- and trans-generational responses to combined global changes are highly divergent in two congeneric species of marine annelids. Marine Biology 167, 17.CrossRefGoogle Scholar
West‒Eberhard, MJ (1989) Phenotypic plasticity and the origins of diversity. Annual Review of Ecology and Systematics 20, 249278.CrossRefGoogle Scholar
White, CR, Alton, LA and Frappell, PB (2012) Metabolic cold adaptation in fishes occurs at the level of whole animal, mitochondria and enzyme. Proceedings of the Royal Society B: Biological Sciences 279, 17401747.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Mean metabolic rates of Ophryotrocha labronica expressed as oxygen uptake rates for the parental (F0) and offspring (F1) generations along a gradient of four different temperatures

Figure 1

Fig. 1. Relationship between metabolic rates (MO2), measured as oxygen uptake rates, and seawater temperature in the annelid O. labronica across two generations of exposure to a thermal gradient. Solid and empty circles represent individual MO2 measurements for the F0 and F1, respectively. The black continuous and dotted lines represent the regression lines for the F0 and F1, respectively, and the grey shaded areas represent their 95% confidence interval.

Figure 2

Table 2. Results of the best–fitted linear regression models investigating the relationship between metabolic rates (MO2) and temperature (continuous variable) across two successive generations in O. labronica, controlling for the effect of sex and body size

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