# The thermal dependence of metabolism in three sea turtle species and the effects of activity

Manfred Enstipp, Virginie Plot, Stéphane Ciccione, Katia Ballorain,

Jean-Yves Georges

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Manfred Enstipp, Virginie Plot, Stéphane Ciccione, Katia Ballorain, Jean-Yves Georges. The thermal dependence of metabolism in three sea turtle species and the effects of activity. Journal of Experimental Biology, 2025, 228, 10.1242/jeb.250844. hal-05244986

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RESEARCH ARTICLE

# The thermal dependence of metabolism in three sea turtle species and the effects of activity

Manfred R. Enstipp<fnref n="1" />*, Virginie Plot<fnref n="1" />,<fnref n="2" />, Stéphane Ciccione³, Katia Ballorain<fnref n="1" />,⁴ and Jean-Yves Georges<fnref n="1" />

## ABSTRACT

Temperature is of central importance to life and structures biological processes across levels of organization. For ectothermic marine turtles, temperature profoundly affects their metabolism, overall physiology, behaviour and distribution. Marine turtles are globally threatened and a detailed understanding of their energy requirements is essential to comprehend their role in marine ecosystems and to guide conservation efforts. We used flow-through respirometry to study the effects of seasonal changes in water temperature ($T_w$) on the resting oxygen consumption rates ($V̇O₂$) of three sea turtle species (green, loggerhead and hawksbill turtles). $T_w$ changes between winter and summer (maximum range: 20.3–31.9°C) had a clear effect on mass-specific $V̇O₂$ ($sV̇O₂$) that increased on average by ~50% across species in summer. Hence, the thermal sensitivity of metabolism was similar in all species with $Q₁₀$ values ranging between 2.1 and 2.7, typical for reptiles. Changes in $sV̇O₂$ were paralleled by changes in respiratory frequency ($f_R$) in all species. In separate trials with loggerhead turtles resting and swimming in a tank, we recorded body acceleration (PDBA) together with $V̇O₂$ to investigate the effects of activity on metabolism and to establish a predictive equation that can be used to estimate turtle energy expenditure at sea from the recording of body acceleration. Moderate swimming activity increased $sV̇O₂$ up to 3.2 times over resting. We found a significant positive relationship between $sV̇O₂$ and PDBA ($r<fnref n="2" />=0.63, P<0.0001$) with small associated error estimates, indicating that body acceleration is a good predictor of $V̇O₂$ in loggerhead turtles, similar to what has previously been reported for green turtles.

**KEY WORDS:** Temperature, Accelerometry, Metabolic rate, Diving, Exercise, Energy expenditure

## INTRODUCTION

Temperature governs all processes that involve the flow of energy (Clarke, 2017). Through its profound effects on chemical/biochemical reactions, temperature structures biological processes across levels of organization, from single molecules to the whole organism (Schulte, 2015). Besides the direct effect on metabolism, temperature determines environmental tolerance limits and activity patterns of organisms, thereby structuring spatial distribution (Somero, 2011).

The distribution of marine turtles, for example, is generally confined to tropical/sub-tropical environments with surface temperatures ~20°C (Davenport, 1997). Exceptions are the loggerhead turtle (*Caretta caretta*) and the Kemp's ridley turtle (*Lepidochelys kempii*), which frequently inhabit warm temperate waters for part of the year (Hawkes et al., 2007; Mansfield et al., 2009; Narazaki et al., 2015; Gitschlag, 1996; Renaud and Williams, 2005). A further exception is the soft-shelled leatherback turtle (*Dermochelys coriacea*) that, because of its large size and behavioural/physiological adjustments (Paladino et al., 1990; Bostrom et al., 2010), can maintain an elevated body temperature, allowing it to even penetrate boreal waters (Ferraroli et al., 2004; James et al., 2006; Casey et al., 2014). Environmental temperature is of central importance to marine turtles and affects all phases of their life history, from egg development and sex determination during the embryonic phase, to the behaviour, physiology, ecology and distribution of juveniles and adults (Mrosovsky, 1980; Spotila and Standora, 1985; Fossette et al., 2009; Plot et al., 2015). During the twentieth century, human activities led to the decline of many marine turtle populations, affecting all seven species. While considerable conservation efforts succeeded in, at least partially, reversing these developments, new threats are on the horizon, such as climate warming and plastic pollution (Fuentes et al., 2023; Hays et al., 2025). To understand the role of sea turtles in marine ecosystems and how it might be impacted by environmental change, a detailed understanding of marine turtle energy requirements during the different phases of their life cycle and how they change with intrinsic (e.g. behaviour, nutritional status) and environmental factors [e.g. water temperature ($T_w$), food availability] is essential. Conservation efforts critically depend on such knowledge, as a number of key demographic parameters are fundamentally linked with their energy balance (Bjorndal, 1985; Hays, 2000, 2008; Plot et al., 2012; Jones and Seminoff, 2013). As ectotherms, the body temperature of marine turtles, with the exception of the leatherback turtle (Frair et al., 1972; Casey et al., 2014), mostly reflects $T_w$ (Heath and McGinnis, 1980; Standora et al., 1982; Sato, 2014). Hence, their metabolism, overall physiology and behaviour might be profoundly affected by seasonal changes in $T_w$, as well as by $T_w$ changes occurring over shorter periods in association with their movement patterns (diving, migration), which is especially relevant in the context of climate warming, which strongly affects ocean temperatures.

Although the effects of $T_w$ on turtle metabolism have been studied in green and loggerhead turtles in captive settings (Kraus and Jackson, 1980; Lutz et al., 1989; Southwood et al., 2003; Hochscheid et al., 2004; Kinoshita et al., 2018, 2021) or even in the wild (Southwood et al., 2006), these studies predominantly concerned juvenile animals (for review, see Southwood-Williard, 2013). In the case of loggerhead turtles, some studies included both juvenile and adult animals (Hochscheid et al., 2004; Kinoshita et al., 2018). Nevertheless, studies on adult turtles are mostly lacking, as

<footnote n="1">¹Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France.</footnote>

<footnote n="2">²Groupe Local d'Observation des Cétacés (GLOBICE) Réunion, 97411 Saint Paul, La Réunion, France. ³Kélonia, l'observatoire des tortues marines, BP 40, 97436 Saint Leu, La Réunion, France. ⁴Centre d'Étude et de Découverte des Tortues Marines, 97424 Piton Saint Leu, La Réunion, France.</footnote>

<footnote>*Author for correspondence (manfred.enstipp@iphc.cnrs.fr)</footnote>

<footnote>© M.R.E., 0000-0002-5080-626X; V.P., 0000-0002-3565-1191; S.C., 0000-0001-7284-8682; K.B., 0009-0004-3265-2932; J.-Y.G., 0000-0003-1161-2275</footnote>
are studies on other species (e.g. hawksbill turtles; Wallace and Jones, 2008). Most of the above studies investigated the effects of acute temperature changes on turtle metabolism (acclimation studies), while Hochscheid et al. (2004) and Southwood et al. (2006) took advantage of the naturally occurring seasonal changes in *T*<sub>w</sub> (long-term exposure). The latter approach might provide greater insights into the physiological responses that remain undetected in acute exposure studies (Southwood-Williard, 2013). Further studies investigated the thermal effects of acute temperature changes on the metabolism of various tissues (e.g. pectoral muscle) of green and leatherback turtles (Penick et al., 1996, 1998; Southwood et al., 2003).

Most of the above studies found moderate temperature effects on whole-animal metabolism of the species investigated. Reported values for the thermal coefficient ($Q_{10}$) fell within the normal range found in reptiles, between 2 and 3 (Bennett and Dawson, 1976), indicating a doubling/tripling of metabolic rate associated with a temperature increase of 10°C. However, juvenile and adult loggerhead turtles from the Mediterranean population showed a relatively strong thermal sensitivity of their metabolism with a mean $Q_{10}$ value of 5.4, ranging from 2.4 to 12.8 (Hochscheid et al., 2004), which contrasts with values reported for loggerhead turtles from other regions, such as the North Pacific or Atlantic Ocean (Lutz et al., 1989; Kinoshita et al., 2018). To some degree, these differences might be related to experimental conditions, as Mediterranean loggerhead turtles could feed *ad libitum* and ingested much less food during winter, so that differences in nutritional status/digestive state between seasons might account for some of the seasonal differences in metabolism (Southwood-Williard, 2013). However, the drastic changes in dive duration with season, observed in the Mediterranean population (Hochscheid et al., 2005, 2007a) but not in the North Pacific population (Narazaki et al., 2015; Kinoshita et al., 2018), suggest that thermal sensitivity truly differs between populations. Whether such differences also exist for other loggerhead populations (e.g. Indian Ocean) is currently unknown. Clearly, a strong thermal sensitivity of metabolism will allow turtles to minimize energetic requirements during the colder winter months, when food availability might be reduced. However, it will also restrict activity patterns and the distribution range for such turtles.

Our understanding of sea turtle energetics is almost entirely based on captive studies, while field studies that achieve reliable estimates of energy expenditure in their natural environment are rare (Enstipp et al., 2011; Southwood-Williard, 2013). Given the great methodological difficulties associated with such an undertaking, this is not surprising. A promising tool to enable such investigations is the accelerometry method. This method has been used to study animal behaviour (e.g. Fossette et al., 2012) and to estimate activity-specific metabolic rates of animals in the wild with a high temporal resolution (Wilson et al., 2006; Halsey et al., 2011a). However, it requires a species-specific calibration that relates the metric derived from the recording of body acceleration [e.g. overall/vectoral dynamic body acceleration (ODBA/VeDBA) or partial dynamic body acceleration (PDBA)] with simultaneously recorded metabolic rate (usually via respirometry). Such calibration studies have been conducted for a range of terrestrial and aquatic species (including marine turtles) and found significant relationships between body acceleration and metabolic rate (Halsey et al., 2009, 2011a,b; Fahlman et al., 2008; Enstipp et al., 2011; Payne et al., 2011). Enstipp et al. (2016) used the accelerometry approach to contrast the energy expenditure of adult green turtles at their foraging ground and during a simulated oceanic migration. Similarly, Wilson et al. (2017) estimated the energy expenditure of female loggerhead turtles during their inter-nesting period using accelerometers.

However, in the absence of a calibration equation for loggerhead turtles, the authors used the equation established for green turtles (Enstipp et al., 2011). While this provided valuable insights, allowing investigation of turtle energetics associated with contrasting conditions, it is clearly desirable to establish species-specific calibrations that cover a wide size range to avoid erroneous estimates.

The south-western Indian Ocean (SWIO) hosts five of the world's seven marine turtle species. It has been recognized as one of the most important nesting areas for green turtles, while it also hosts important nesting sites for hawksbill, loggerhead and even leatherback turtles (Bourjea et al., 2007; Lauret-Stepler et al., 2007; Dalleau et al., 2020; Mortimer et al., 2022). In addition, satellite tracking and genetic studies have identified important foraging areas and migration routes for green, loggerhead and hawksbill turtles throughout the SWIO (Bourjea et al., 2012; Dalleau et al., 2014; Monsinjon et al., 2023; Nivière et al., 2024). Hence, studies investigating the energetic requirements of the various species inhabiting the region during their different life history stages and the effects of environmental factors are of considerable importance for ongoing conservation efforts.

The aim of our study was (1) to investigate the effect of seasonal changes in $T_w$ on the energy expenditure of three sea turtle species, common to the SWIO; (2) to investigate the effect of activity on turtle energy expenditure, using loggerhead turtles as an example; and (3) to investigate the relationship between loggerhead turtle body acceleration and energy expenditure, with the goal of establishing a predictive equation that can be used to estimate energy expenditure of loggerhead turtles in the wild from the recording of body acceleration.

## MATERIALS AND METHODS

### Turtles

We used individuals from three sea turtle species: eight adult female green turtles [*Chelonia mydas* (L. 1758)], five female loggerhead turtles [*Caretta caretta* (L. 1758); 2 adults, 3 sub-adults] and two female hawksbill turtles [*Eretmochelys imbricata* (L. 1766); 1 adult, 1 sub-adult; Tables 1–3]. All green turtles were captured as hatchlings on Tromelin Island in the Western Indian Ocean (15°53' 32"S, 54°31'29"E) during the late 1980s. They were raised and maintained at the former 'Ferme Corail', which is now a public aquarium ('Kelonia'), St Leu, Reunion Island (21°09'09"S, 55°16' 49"E). Green turtles were kept communally inside an uncovered concrete pool (13 m×15 m, 1–2.2 m deep, volume: 300 m³), adjacent to a shallow lagoon, from which pumps continuously supplied sea water at a rate of 150 m³ h⁻¹. All loggerhead turtles were accidental captures by pelagic longliners fishing off Reunion Island and were brought to Kelonia for rehabilitation. They were initially kept individually in round fibreglass tanks (2 m in diameter, ~60 cm water depth), until they had recovered well from the surgical removal of the swallowed fishing hook, upon which they were transferred to one of the large display pools, before eventual release. These turtles had arrived at Kelonia between 1 and 14 months before experimentation. The two hawksbill turtles were accidental captures during recreational fishing and arrived at the Ferme Corail/Kelonia in 1988 (Myriam) and 1998 (Croupette). These turtles were also kept inside the large public display pools. $T_w$ in all turtle pools matched the temperature of the adjacent lagoon and underwent the same seasonal changes (see figure 1 in Enstipp et al., 2011). Given the shallow depth of the adjacent lagoon and the typically strong solar radiation during the day, $T_w$ also underwent considerable daily oscillations, with differences often ~2–3°C between day and night. All turtles were exposed to the natural light cycle, with ~13.5 h light (10.5 h dark) during the austral summer
<table><caption>Table 1. Oxygen consumption rates, respiratory frequency and apnoea duration of 8 adult female green turtles when resting at different water temperatures during the austral summer and winter</caption><thead><tr><th>Turtle</th><th>M<sub>b</sub> (kg)</th><th>CCL (cm)</th><th>T<sub>w</sub> (°C)</th><th>V̇<sub>O<sub>2</sub></sub> (ml min<sup>-1</sup>)</th><th>sV̇<sub>O<sub>2</sub></sub> (ml min<sup>-1</sup> kg<sup>-0.83</sup>)</th><th>f<sub>R</sub> (breaths h<sup>-1</sup>)</th><th>Apnoea (min)</th><th>Min. apnoea (min)</th><th>Max. apnoea (min)</th></tr></thead><tbody><tr><td colspan="10"><strong>Austral summer</strong></td></tr><tr><td>Elisabeth</td><td>117.7</td><td>96</td><td>30.0±0.3</td><td>33.0±2.4</td><td>0.63±0.05</td><td>5.3±0.4</td><td>11.9±1.0</td><td>4.0</td><td>23.5</td></tr><tr><td>Virginie</td><td>140.7</td><td>107</td><td>31.2±0.3</td><td>38.1±1.9</td><td>0.63±0.03</td><td>6.1±0.3</td><td>9.9±0.4</td><td>3.9</td><td>18.8</td></tr><tr><td>Karima</td><td>104.8</td><td>95</td><td>27.9±0.1</td><td>27.3±1.7</td><td>0.58±0.04</td><td>5.1±0.5</td><td>12.0±1.1</td><td>0.7</td><td>28.1</td></tr><tr><td>Monique</td><td>165.7</td><td>108</td><td>28.4±0.2</td><td>49.5±1.1</td><td>0.71±0.02</td><td>8.2±0.3</td><td>7.3±0.3</td><td>4.0</td><td>15.1</td></tr><tr><td>Delphine</td><td>159.0</td><td>109</td><td>30.3±0.0</td><td>56.8±0.9</td><td>0.85±0.01</td><td>9.2±0.1</td><td>6.5±0.0</td><td>4.0</td><td>12.5</td></tr><tr><td>Sandy</td><td>154.5</td><td>107</td><td>30.3±0.5</td><td>55.0±3.6</td><td>0.84±0.06</td><td>9.2±0.1</td><td>6.5±0.1</td><td>4.3</td><td>10.6</td></tr><tr><td>Flavia</td><td>140.3</td><td>103</td><td>29.2±0.4</td><td>40.4±1.5</td><td>0.67±0.03</td><td>7.0±0.2</td><td>8.6±0.2</td><td>3.8</td><td>13.7</td></tr><tr><td>Nadia</td><td>154.9</td><td>107</td><td>29.0±0.3</td><td>29.1±1.2</td><td>0.44±0.02</td><td>4.0±0.3</td><td>15.1±1.2</td><td>0.2</td><td>35.8</td></tr><tr><td>Grand mean</td><td>142.2±7.5</td><td>104.0±2.0</td><td>29.5±0.4</td><td>41.1±4.1</td><td>0.67±0.05</td><td>6.8±0.7</td><td>9.7±1.1</td><td>3.1±0.6</td><td>19.8±3.1</td></tr><tr><td colspan="10"><strong>Austral winter</strong></td></tr><tr><td>Elisabeth</td><td>120.9</td><td>96</td><td>25.8±0.2</td><td>21.6±0.5</td><td>0.40±0.01</td><td>3.7±0.2</td><td>16.7±1.1</td><td>1.0</td><td>36.2</td></tr><tr><td>Virginie</td><td>126.3</td><td>107</td><td>22.3±0.2</td><td>19.4±1.9</td><td>0.35±0.03</td><td>7.7±0.3</td><td>7.8±0.3</td><td>0.3</td><td>26.0</td></tr><tr><td>Karima</td><td>104.4</td><td>95</td><td>23.2±0.1</td><td>18.8±0.3</td><td>0.40±0.01</td><td>2.4±0.1</td><td>24.6±0.5</td><td>2.9</td><td>60.8</td></tr><tr><td>Monique</td><td>170.2</td><td>108</td><td>25.0±0.1</td><td>36.2±1.6</td><td>0.51±0.02</td><td>5.6±0.2</td><td>10.9±0.5</td><td>0.9</td><td>27.1</td></tr><tr><td>Delphine</td><td>156.1</td><td>109</td><td>24.6±0.1</td><td>32.5±1.5</td><td>0.49±0.02</td><td>3.7±0.3</td><td>16.9±1.2</td><td>0.5</td><td>31.1</td></tr><tr><td>Sandy</td><td>155.7</td><td>107</td><td>25.5±0.3</td><td>34.1±1.0</td><td>0.52±0.02</td><td>5.4±0.2</td><td>11.2±0.3</td><td>0.2</td><td>35.5</td></tr><tr><td>Flavia</td><td>138.2</td><td>103</td><td>20.5±0.2</td><td>24.4±1.9</td><td>0.41±0.03</td><td>5.6±0.8</td><td>11.3±1.6</td><td>0.9</td><td>36.8</td></tr><tr><td>Nadia</td><td>151.0</td><td>107</td><td>26.6±0.3</td><td>25.0±0.5</td><td>0.39±0.01</td><td>3.2±0.2</td><td>19.5±1.0</td><td>0.3</td><td>36.4</td></tr><tr><td>Grand mean</td><td>140.4±7.8</td><td>104.0±2.0</td><td>24.2±0.7<sup>a</sup></td><td>26.5±2.4<sup>a</sup></td><td>0.43±0.02<sup>a</sup></td><td>4.7±0.6<sup>a</sup></td><td>14.8±2.0<sup>a</sup></td><td>0.9±0.3</td><td>36.2±3.8</td></tr></tbody></table>

Values are means±s.e.m., except for minimal and maximal apnoea durations. Grand means were established from individual turtle means. Values for each turtle were averaged from a minimum of 3 trials per turtle (range: 3–10) during both seasons, lasting ~4 h. Summer trials were conducted between November and April, while winter trials were conducted between June and October. M<sub>b</sub>, body mass; CCL, curved carapace length; T<sub>w</sub>, water temperature; V̇<sub>O<sub>2</sub></sub>, oxygen consumption rate; sV̇<sub>O<sub>2</sub></sub>, mass-specific oxygen consumption rate; f<sub>R</sub>, respiratory frequency. <sup>a</sup>Significant difference from the austral summer (P<0.05).

(November to May) and ~11 h light (13 h dark) during the austral winter (June to October). Green turtles were fed 5 times a day with a diet consisting of vitamin-supplemented fish pellets ('Ecolife 16F N9', BioMar SAS, Nersac, France; ~70 g daily) and plant leaves (tree heliotrope, *Heliotropium foertherianum*; ~300 g daily). All loggerhead turtles and the sub-adult hawksbill turtle were fed a mixture of European pilchard (*Sardinia pilchardus*), yellowfin tuna (*Thunnus albacares*), giant tiger prawn (*Penaeus monodon*) and squid (Argentine shortfin squid, *Illex argentines* or California squid, *Loligo opalescens*), typically alternated between days. Depending on the individual, they received between ~250 and 500 g food once daily, supplemented with vitamins. The mature hawksbill turtle received ~60 g of vitamin-supplemented fish pellets daily. All turtles underwent regular veterinary check-ups

(at least once a month) and were in apparent good health at the time of experimentation.

## Experimental set-up

We set up a round fibreglass tank (2 m in diameter, 0.8 m water depth, ~2600 l, with an underwater viewing window: 40×30 cm) to be used during respirometry trials (Fig. 1). The tank was located beside a small hut, from which turtles could be observed and that also housed all respirometry equipment. Sea water was supplied continuously from the adjacent lagoon. Despite its relatively small size, the round shape of the tank permitted turtles to move freely and to engage in both resting and moderately active behaviour.

For our respirometry trials investigating the effects of T<sub>w</sub> on turtle metabolism, we took advantage of the natural oscillations in sea

<table><caption>Table 2. Oxygen consumption rates, respiratory frequency and apnoea duration of 5 loggerhead turtles (3 sub-adults, 2 adult females) when resting at different water temperatures during the austral summer and winter</caption><thead><tr><th>Turtle</th><th>M<sub>b</sub> (kg)</th><th>CCL (cm)</th><th>T<sub>w</sub> (°C)</th><th>V̇<sub>O<sub>2</sub></sub> (ml min<sup>-1</sup>)</th><th>sV̇<sub>O<sub>2</sub></sub> (ml min<sup>-1</sup> kg<sup>-0.83</sup>)</th><th>f<sub>R</sub> (breaths h<sup>-1</sup>)</th><th>Apnoea (min)</th><th>Min. apnoea (min)</th><th>Max. apnoea (min)</th></tr></thead><tbody><tr><td colspan="10"><strong>Austral summer</strong></td></tr><tr><td>Circle</td><td>53.5</td><td>77</td><td>30.0±0.4</td><td>28.8±1.2</td><td>1.06±0.05</td><td>11.1±0.7</td><td>5.5±0.4</td><td>0.5</td><td>13.8</td></tr><tr><td>Vetiver</td><td>32.6</td><td>64</td><td>30.2±0.5</td><td>19.5±1.9</td><td>1.08±0.10</td><td>20.2±2.9</td><td>3.2±0.6</td><td>0.1</td><td>15.2</td></tr><tr><td>Carotte</td><td>50.45</td><td>73.5</td><td>28.3±0.2</td><td>30.1±2.4</td><td>1.16±0.09</td><td>14.9±2.4</td><td>4.3±0.8</td><td>0.3</td><td>13.4</td></tr><tr><td>Grand mean</td><td>45.5±6.5</td><td>71.5±3.9</td><td>29.5±0.6</td><td>26.1±3.4</td><td>1.10±0.03</td><td>15.4±2.7</td><td>4.3±0.7</td><td>0.3±0.1</td><td>14.1±0.6</td></tr><tr><td colspan="10"><strong>Austral winter</strong></td></tr><tr><td>Puffin</td><td>28.1</td><td>62</td><td>24.0±0.3</td><td>13.0±0.7</td><td>0.81±0.04</td><td>11.8±1.1</td><td>5.3±0.5</td><td>0.1</td><td>41.5</td></tr><tr><td>Vetiver</td><td>36.9</td><td>64</td><td>23.7±0.2</td><td>12.6±1.2</td><td>0.63±0.06</td><td>7.5±0.7</td><td>8.6±0.8</td><td>0.3</td><td>33.3</td></tr><tr><td>Carotte</td><td>51.6</td><td>73.5</td><td>24.7±0.1</td><td>20.3±0.8</td><td>0.77±0.03</td><td>13.8±1.3</td><td>4.5±0.4</td><td>0.2</td><td>30.1</td></tr><tr><td>Louane</td><td>30.6</td><td>64</td><td>24.8±0.2</td><td>15.1±0.2</td><td>0.89±0.01</td><td>21.8±0.5</td><td>2.8±0.1</td><td>0.2</td><td>17.8</td></tr><tr><td>Grand mean</td><td>36.8±5.3</td><td>65.9±2.6</td><td>24.3±0.3<sup>a</sup></td><td>15.2±1.8<sup>a</sup></td><td>0.77±0.05<sup>a</sup></td><td>13.7±3.0<sup>a</sup></td><td>5.3±1.2<sup>a</sup></td><td>0.2±0.0</td><td>30.7±4.9</td></tr></tbody></table>

Values are means±s.e.m., except for minimal and maximal apnoea durations. Grand means were established from individual turtle means. Values for each turtle were averaged from a minimum of 3 trials per turtle (range: 3–8), lasting ~4 h. Summer trials were conducted between February and May, while winter trials were conducted between September and October. Note that not all turtles participated during both seasons. M<sub>b</sub>, body mass; CCL, curved carapace length; T<sub>w</sub>, water temperature; V̇<sub>O<sub>2</sub></sub>, oxygen consumption rate; sV̇<sub>O<sub>2</sub></sub>, mass-specific oxygen consumption rate; f<sub>R</sub>, respiratory frequency. <sup>a</sup>Significant difference from the austral summer (P<0.05).
<table><caption>Table 3. Oxygen consumption rates, respiratory frequency and apnoea duration of 2 hawksbill turtles (sub-adult/adult female) when resting at different water temperatures during the austral summer and winter</caption><thead><tr><th>Turtle</th><th>M<sub>b</sub> (kg)</th><th>CCL (cm)</th><th>T<sub>w</sub> (°C)</th><th>V&#x0307;<sub>O<sub>2</sub></sub> (ml min<sup>-1</sup>)</th><th>sV&#x0307;<sub>O<sub>2</sub></sub> (ml min<sup>-1</sup> kg<sup>-0.83</sup>)</th><th>f<sub>R</sub> (breaths h<sup>-1</sup>)</th><th>Apnoea (min)</th><th>Min. apnoea (min)</th><th>Max. apnoea (min)</th></tr></thead><tbody><tr><td colspan="11"><strong>Austral summer</strong></td></tr><tr><td>Croupette</td><td>28.9</td><td>65</td><td>28.4±1.0</td><td>16.8±0.3</td><td>1.03±0.02</td><td>8.7±0.2</td><td>6.9±0.2</td><td>0.4</td><td>17.2</td></tr><tr><td>Myriam</td><td>58.3</td><td>74</td><td>28.1±0.1</td><td>19.8±0.4</td><td>0.68±0.02</td><td>8.9±0.6</td><td>6.8±0.5</td><td>0.4</td><td>48.4</td></tr><tr><td>Grand mean</td><td>43.6±14.8</td><td>69.5±4.5</td><td>28.3±0.1</td><td>18.3±1.5</td><td>0.85±0.18</td><td>8.8±0.1</td><td>6.9±0.0</td><td>0.4±0.0</td><td>32.8±15.6</td></tr><tr><td colspan="11"><strong>Austral winter</strong></td></tr><tr><td>Croupette</td><td>31.4</td><td>67</td><td>22.4±0.1</td><td>10.8±1.3</td><td>0.62±0.08</td><td>7.9±1.1</td><td>7.9±0.9</td><td>0.5</td><td>56.7</td></tr><tr><td>Myriam</td><td>65.8</td><td>76</td><td>22.6±0.1</td><td>16.0±0.6</td><td>0.49±0.02</td><td>4.6±0.5</td><td>13.3±1.4</td><td>0.6</td><td>80.0</td></tr><tr><td>Grand mean</td><td>48.6±17.2</td><td>71.5±4.5</td><td>22.5±0.1<sup>a</sup></td><td>13.4±2.6<sup>a</sup></td><td>0.56±0.06<sup>a</sup></td><td>6.3±1.6<sup>a</sup></td><td>10.6±2.7<sup>a</sup></td><td>0.6±0.0</td><td>68.3±11.6</td></tr></tbody></table>

Values are means±s.e.m., except for minimal and maximal apnoea durations. Grand means were established from individual turtle means. Values were averaged from 3 trials conducted with each turtle during both seasons (in April and September 2009 for the austral summer and winter, respectively), lasting ~4 h. M<sub>b</sub>, body mass; CCL, curved carapace length; T<sub>w</sub>, water temperature; V&#x0307;<sub>O<sub>2</sub></sub>, oxygen consumption rate; sV&#x0307;<sub>O<sub>2</sub></sub>, mass-specific oxygen consumption rate; f<sub>R</sub>, respiratory frequency. <sup>a</sup>Significant difference from the austral summer (P<0.05).

water temperature. To cover the annual range of T<sub>w</sub> experienced by wild turtles in this region of the Indian Ocean, we subjected turtles to two rounds of trials. The first round was conducted during the austral winter (minimum T<sub>w</sub>: 20.3°C), which was followed by trials during the austral summer (maximum T<sub>w</sub>: 31.9°C). The overall measurement period spanned from February 2009 to January 2010. Turtles were weighed and the curved carapace length (CCL) was measured before participation in each round of experimental trials (Tables 1–3). A turtle was moved into the tank designated for respirometry at least 1 week before experimentation. During that period, the turtle was accustomed to the respirometry setup. Measuring oxygen consumption rates in diving animals requires them to breathe inside a chamber upon surfacing, from which gas samples can be taken. To ensure that the animal can only breathe inside the chamber, the remainder of the tank surface has to be covered. Such an arrangement requires that the animal reliably finds the air chamber for respiration. To achieve the latter, we used a white, round PVC board (3 cm thick) to cover the surface of the tank (exempting a small area into which the chamber could be fitted during trials) for 3–4 h at a time, during the last 5 days preceding respirometry trials. During these training periods, turtles were observed closely to ensure that they reliably surfaced inside the open area to breathe, which was the case for all individuals.

In separate trials with four loggerhead turtles, conducted during the austral winter (September to October 2009; same experimental set-up), we investigated the effect of activity on turtle metabolism

and tested the hypothesis that turtle body acceleration can be used as a proxy for oxygen consumption rate (V&#x0307;<sub>O<sub>2</sub></sub>).

Respirometry system

Open-circuit respirometry was used to measure oxygen consumption rates (V&#x0307;<sub>O<sub>2</sub></sub>) of turtles when resting within the water tank. Turtles had been accustomed to breathe within a transparent Plexiglas chamber in the shape of a truncated pyramid (bottom: 38×38 cm, top: 19×19 cm, height: 24 cm, volume: 20 l) that was submerged at its bottom. During a trial, air was sucked into the chamber through small holes near its bottom (equally spaced on all sides) and left the chamber through a centrally placed outflow tube at its top (Fig. 1). The primary flow control unit (FK-100; mass flow controller) of a ‘TurboFOX-RM’ integrated field respirometry system (Sable Systems International, Las Vegas, NV, USA), placed in the adjacent hut, generated and controlled a flow rate of 20 l min<sup>-1</sup> through the chamber (automatically corrected to STP, 273 K and 101.3 kPa). The integrated flow control system of the TurboFOX-RM unit pulled a subsample (200 ml min<sup>-1</sup>) from the main flow through a humidity meter (RH-300) and scrubbing columns (Drierite, soda lime, Drierite) to remove water vapour and CO<sub>2</sub>, before it entered the fuel-cell oxygen analyser. Oxygen concentration within the chamber, main flow rate through the chamber, humidity of the gas sample and barometric pressure were recorded every second onto a laptop computer using Expedata (Sable Systems). As all measurements were conducted over seawater with its great affinity for CO<sub>2</sub>, we did not measure the

<figure><img src="image_2.png" /><figcaption>Fig. 1. Experimental set-up. The round fibreglass tank was covered at its surface with a PVC board, except for a small area in front of the underwater viewing window, into which a Plexiglas dome was fitted. The observation hut, housing all respirometry equipment, was positioned adjacent to the tank and allowed close observation of turtle behaviour. During a trial, a turtle would typically rest at the bottom of the tank and frequently rise to the surface to breathe inside the Plexiglas dome.</figcaption></figure>
latter but scrubbed it from the subsample using soda lime. Given the forceful exhalation of turtles upon surfacing, their large tidal volume and the relatively small size of our chamber, the chamber was fitted with a latex breathing bag (6.1 l; Deltalyo & Valmy, Roanne, France) to receive overflow expired gas, while a unidirectional breathing valve (Smiths, Rungis, France) was fitted to the inflow opening, ensuring that expired gas would not escape. During exhalation, the breathing bag inflated but as soon as exhalation stopped, it deflated and its contents were pushed back into the chamber. A small fan inside the chamber provided rapid mixing of expired gas. All connections between the various components of the respirometry system were made using gas-impermeable Bev-a-Line or Tygon tubing. The oxygen analyser was calibrated before each trial using outside air scrubbed of water vapour and CO₂ (set to 20.95% O₂; the zero point was fixed and not subjected to drift). The humidity meter was calibrated weekly according to recommendations of the manufacturer. We used dry 99.995% pure N₂ (Air Liquide, Le Port, Reunion Island) and a water-saturated air sample to calibrate the water vapour pressure reading (kPa). Before a trial the entire system was tested for leaks by infusing pure N₂ gas. The time delay between an exhalation into the chamber and a change in oxygen concentration being registered by the gas analyser was ~25 s, while it took ~4 min for the O₂ signal to return to baseline after a disturbance (i.e. exhalation).

## Experimental trials

### Temperature effects on resting metabolism

At the start of a trial, once the respirometry system was ready for recording, the surface of the tank was covered with the PVC board. The Plexiglas dome was placed in the remaining opening, which was positioned towards the periphery of the round tank (Fig. 1). During the trial, the turtle was observed from the adjacent hut and breathing events were marked on the respirometry recording. Trials lasted ~4 h, during which the turtle typically rested motionless and breathed regularly within the dome. Throughout trials, T<sub>w</sub> in the tank was recorded hourly with an electronic thermometer at 30 cm depth ('Thermelec1', C.O.F.A., Paris, France; resolution: 0.1°C; accuracy: ±0.5%). From these hourly measurements, we calculated a mean temperature attributed to a trial. Given the T<sub>w</sub> fluctuations throughout the daily cycle (especially during the austral summer), all recordings were conducted during the same period of the day (early morning: 07:00–11:00 h). The maximum T<sub>w</sub> fluctuation that occurred during a single respirometry trial was 1.3°C but fluctuations were typically much smaller (<0.5°C). In total, we conducted 84 trials with green turtles (32 summer/52 winter; 3–10 trials per individual/season), 35 with loggerhead turtles (10 summer/25 winter; 3–8 trials per individual/season) and 12 trials with hawksbill turtles (6 summer/6 winter; 3 trials per individual/season).

### The effects of activity on turtle metabolism and its link with body acceleration

In separate trials with four loggerhead turtles (1 adult, 3 sub-adults; n=22 trials of ~4 h each), we deployed a bi-axial acceleration data logger (M190L-D2GT; length: 53 mm, diameter: 15 mm, mass: 17 g; 12-bit resolution; recording range: ±3 g; Little Leonardo, Tokyo, Japan) to record body acceleration of turtles, in parallel with respirometry. The logger was set to record heave and surge at a frequency of 16 Hz. Before deployment, the logger was fitted snugly into a custom-made base (made from rubber and lined with Velcro™). A Velcro patch was glued to the centre of the second vertebral scute of a turtle in the anterior-posterior direction, before a series of trials started. This allowed for the easy attachment of the

streamlined logger base to a turtle before a trial and for its quick removal afterwards. Care was taken to attach the logger in the same position during all trials. After a trial, data from the logger were downloaded onto a PC.

At the start of these trials, loggerhead turtles would typically either float within the chamber or sink to the bottom of the tank, often resting motionless for long periods, only periodically floating upward into the chamber to breathe (Fig. 1). However, during trials, turtles often started to paddle around the tank spontaneously for extended periods (up to ~30 min), allowing us to investigate the relationship between oxygen consumption rate (V̇O₂) and body acceleration (PDBA) during these periods with different activity levels (i.e. resting/low activity periods and swim periods).

## Data analysis

Respirometry data were analysed using Expedata. During analysis, oxygen analyser drift and lag time of the respirometry system were corrected for. Main flow rate was corrected to STP dry (STPD) using equation 8.6 in Lighton (2008):

$$FR_c = FR(BP - WVP)/BP, \quad (1)$$

where FR<sub>c</sub> is the dry-corrected flow rate, FR is the uncorrected flow rate, BP is the barometric pressure (kPa) and WVP is the water vapor pressure (kPa). V̇O₂ was calculated using equation 4b in Withers (1977), which corresponds to equation 11.3 in Lighton (2008) and is nearly independent of the respiratory quotient (RQ):

$$\dot{V}_{O_2} = FR_e(F_{1O_2} - F''_{E_{O_2}})/[1 - F_{1O_2} + RQ(F_{1O_2} - F''_{E_{O_2}})], \quad (2)$$

where FR<sub>e</sub> is the excurrent flow rate, F<sub>1O₂</sub> is the fractional concentration of the incurrent O₂, and F''<sub>E<sub>O₂</sub></sub> is the fractional concentration of the excurrent O₂ (scrubbed of water vapour and CO₂). We assumed an RQ of 0.85.

### Resting metabolism

Oxygen consumption rate, V̇O₂ (ml min⁻¹), during a dive cycle (dive+surface interval) was calculated as the total oxygen uptake following a dive (integrating the area under the relevant part of the calculated V̇O₂ trace), when the turtles breathed at the surface, divided by dive cycle duration. Mean resting V̇O₂ was calculated for each trial, based on turtle oxygen consumption during all dive cycles of a trial, during which animals rested (with no or little movement), either at the tank bottom or at the surface. As our aim was to record resting metabolic rate of turtles over a range of T<sub>w</sub>, periods during which turtles were active, if they occurred, were excluded from the analysis. However, there might have been carry over effects from active periods that extended into resting periods, which might account for some of the individual variation observed. For green turtles, on average, 16.1±3.1 (mean+s.e.m., summer) and 11.9±2.1 dive cycles per trial (winter) were included in the analysis. The breathing pattern of green turtles consisted mostly of a single breath upon surfacing, regardless of the length of the preceding apnoea period. In rare cases, green turtles breathed 2 to 3 times after an extended apnoea period. However, both loggerhead and hawksbill turtles showed a different breathing pattern. Both species conducted longer apnoea periods that were followed by a period when the turtles remained at the surface and respired multiple times. These breathing events were often separated by short apnoea periods (typically <1 min). Upon completion of gas exchange, turtles submerged again for a longer apnoea period. On average, 7.5±1.9 (summer) and 10.4±2.6 (winter) long apnoea periods of loggerhead turtles per trial were included in the analysis. These longer apnoea periods were
followed, on average, by 3.8±1.8 (summer) and 2.7±0.5 (winter) breaths at the surface. For hawksbill turtles, we included, on average, 7.5±0.2 (summer) and 6.0±1.3 (winter) long apnoea periods per trial in the analysis, which were followed by 3.9±0.8 (summer) and 2.2±0.3 (winter) breaths at the surface.

To account for the variation in $\dot{V}_{O_2}$ between individuals associated with differences in body mass ($M_b$), we also report $\dot{V}_{O_2}$ independent of body mass as $s\dot{V}_{O_2}$ (ml min$^{-1}$ kg$^{-0.83}$). The scaling exponent of 0.83 has been commonly used in turtle literature (Prange and Jackson, 1976; Southwood et al., 2003; Enstipp et al., 2011). Respiratory frequency, $f_R$ (breaths h$^{-1}$), was determined as the number of breaths divided by the length of the measurement period.

To investigate the effect of $T_w$ on turtle metabolism, we calculated $Q_{10}$ values according to equation 4.2 in McNab (2002):

$$Q_{10} = (\dot{V}_{O_{2,2}}/\dot{V}_{O_{2,1}})^{[10/(T_2-T_1)]}, \quad (3)$$

where the $\dot{V}_{O_2}$ term refers to the $O_2$ consumption rate during the austral summer and winter, respectively, and T specifies the corresponding $T_w$.

## Activity metabolism and its link with body acceleration

From the recorded acceleration data (surge and heave) we calculated a trace of PDBA for each trial following Wilson and colleagues (2006), as described previously (Enstipp et al., 2011). Briefly, recorded data from both axes were first converted into absolute acceleration values (g) using our calibration equations. We removed the static/low-frequency component of acceleration (due to animal posture) by smoothing each axis using running means over 4 s, based on observed flipper beat cycle durations (Shepard et al., 2008), which were then subtracted from the unsmoothed data of both axes to produce an approximation of dynamic acceleration (high-frequency component; due to the active movement of the animal). After converting these derived values into absolute positive units, values from both axes were summed to produce a trace of PDBA, which was synchronized with the respirometry trace.

Within each trial, multiple periods of resting/low activity and swim/active periods were identified, based on behavioural observations and acceleration recordings. Periods with contrasting activity levels were grouped into resting versus swim categories for each trial. Only periods that consisted of multiple dive cycles with the same activity status (resting versus swimming) were considered for analysis, excluding periods of mixed activity during a trial. For each trial, a mean value for $\dot{V}_{O_2}$ and PDBA was calculated for each category (resting versus swimming). For this, each of the multiple periods within a category was weighed according to its relative contribution to the overall duration of that category.

## Statistical analysis

All statistical analyses were conducted using JMP (v.8.0.2.2, SAS Institute Inc.). Differences in oxygen consumption rates ($\dot{V}_{O_2}$ and $s\dot{V}_{O_2}$) and respiratory frequency ($f_R$/apnoea duration during different seasons (austral summer versus winter) were tested for all three species using linear mixed-effects (LME) models (standard least squares regression fitted by REML) (Tables 1–3). Season was included as a fixed effect, while turtle ID was included as a random effect to account for repeated measures. LME models were also used to investigate the relationship between $s\dot{V}_{O_2}$ and $T_w$, as well as $f_R$ and $T_w$ across the temperature range recorded. In these models, $T_w$ was included as a fixed effect, while turtle ID was again included as a

random effect. To test whether these relationships differed between species, we also included the interaction term ($T_w$×species). Similarly, the relationship between $f_R$ and $s\dot{V}_{O_2}$ as well as $T_w$ was investigated using LME analysis, where the latter two terms were included as fixed effects and turtle ID as a random effect; we also included interaction terms, which were removed from the model in the case of non-significance.

A LME model was also used to investigate the relationship between $s\dot{V}_{O_2}$ and PDBA during diving in loggerhead turtles and to test whether this varied between individuals and with $T_w$ ($s\dot{V}_{O_2}$~PDBA+$T_w$+turtleID[random]+PDBA×$T_w$+PDBA×turtleID+$T_w$×turtleID). We then ran the model without the interaction terms to produce a common predictive equation for $s\dot{V}_{O_2}$ based on PDBA and $T_w$. However, as these trials were conducted only during the austral winter over a limited $T_w$ range (maximum difference: 2.1°C), $T_w$ was not significant in that model and was consequently removed. Hence, the final model used for the predictive equation was $s\dot{V}_{O_2}$~PDBA+turtleID[random]. We used a jack-knife procedure to validate the common predictive equation calculating $s\dot{V}_{O_2}$ from PDBA (Sokal and Rohlf, 1981; Halsey and White, 2010; Enstipp et al., 2011). Data for one individual were removed from the dataset and a new predictive equation was calculated from the remaining dataset. PDBA recorded during trials of the excluded individual were fed into the new predictive equation to estimate its $s\dot{V}_{O_2}$. These $s\dot{V}_{O_2}$ estimates were compared with the $s\dot{V}_{O_2}$ values measured concurrently with PDBA for that individual. This procedure was conducted sequentially for all individuals and mean algebraic error, mean absolute error and the range of errors for individuals were computed as percentage errors [(estimated value–observed value)×100/observed value].

Significance for all statistical tests was accepted at $P<0.05$. All values presented are grand means±s.e.m., established from individual turtle means, unless specified differently.

## Ethics statement

All experimental procedures were carried out under Kelonia institutional licence (no. 09-1405/SG/DRCTCV) and were approved by the ‘Comité National pour la Protection de la Nature’ of the French Ministry in charge of Environmental Affairs and adhered to all institutional guidelines and the legal requirements of the country in which the work was carried out.

## RESULTS

### Seasonal effects of $T_w$ on the metabolism of three sea turtle species

The temperature range investigated was largest for the green turtles, where it spanned ~11.5°C (20.3–31.9°C), while it spanned ~8°C for the other two species (Figs 2 and 3). Seasonal changes in water temperature had a clear effect on the metabolism of all turtle species investigated. In general, the magnitude of the temperature effect on metabolism was similar in all species. On average, $s\dot{V}_{O_2}$ was ~50% higher during the austral summer, when compared with winter conditions. For the eight green turtles, a mean increase in $T_w$ of 5.3°C during the austral summer over winter conditions resulted in a mean increase in $s\dot{V}_{O_2}$ of 54.1±7.4% (Table 1; $P<0.0001$). Similarly, when $T_w$ increased on average by 5.2°C during the austral summer, $s\dot{V}_{O_2}$ of five loggerhead turtles was on average 42.2% higher than during the winter (Table 2; $P<0.0001$). However, only two of the five loggerhead turtles participated in both summer and winter trials. A direct comparison between winter and summer conditions for these two individuals revealed an increase in $s\dot{V}_{O_2}$ of 61.4±10.7% for an average increase in $T_w$ of 5.0°C. Finally, as $T_w$
<figure><img src="image_3.png" /><figcaption>**Fig. 2.** Mass-specific oxygen consumption rate (sV̇O₂) versus water temperature (T_w) during resting trials with three sea turtle species. (A) Green turtles (N=8 females, n=84 trials), (B) loggerhead turtles (N=5, n=35 trials) and (C) hawksbill turtles (N=2, n=12 trials). Solid lines indicate significant relationships, based on linear mixed-effects (LME) models.</figcaption></figure>

increased from winter to summer conditions (mean increase: 5.8°C), the sV̇O₂ of two hawksbill turtles increased on average by 52.1±15.0% (Table 3; P<0.001).

LME analysis revealed significant relationships between T_w and sV̇O₂ for all three species (Fig. 2). The intercept of this relationship for the loggerhead turtles differed from that of the other turtle species (F=24.45, P<0.0001), while the slope of the relationship for

loggerhead turtles differed from that of green turtles (F=14.46, P<0.001).

Q₁₀ values, calculated from changes in sV̇O₂ with T_w changes (grand means, calculated from individual turtle means), were similar for all three species. Q₁₀ values were highest in loggerhead turtles (2.7±0.4), slightly lower in green turtles (2.3±0.2) and lowest in hawksbill turtles (2.1±0.3).
<figure><img src="image_4.png" /><figcaption>**Fig. 3.** Relationship between respiratory frequency ($f_R$) and $T_w$ during resting trials with three sea turtle species. (A) Green turtles ($N=8$ females, $n=84$ trials), (B) loggerhead turtles ($N=5$, $n=35$ trials) and (C) hawksbill turtles ($N=2$, $n=12$ trials). Solid lines indicate significant relationships, based on LME models.</figcaption></figure>

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

## Seasonal effects of $T_w$ on turtle apnoea duration/respiratory frequency

For green turtles, mean apnoea duration declined from winter to summer by 29.5±9.3%, so that mean $f_R$ increased by 56.2±18.4%. In particular, maximum apnoea duration differed between seasons and greatly increased during the winter, on average by 105.2±27.1% (Table 1). Mean apnoea duration of loggerhead turtles declined

from winter to summer conditions on average by 18.4%, resulting in an increase of $f_R$ by 12.5%. Maximum apnoea duration in loggerhead turtles occurred during winter and was on average 117.2% longer than during the summer (Table 2). For hawksbill turtles, changes in apnoea duration/$f_R$ with $T_w$ changes were particularly pronounced in the adult female (Myriam) that also engaged in the longest apnoea duration displayed by any turtle
during experimentation (80 min). On average, mean apnoea duration of hawksbill turtles decreased by 30.3±18.2% from winter to summer, so that $f_R$ increased by 50.5±40.2%. Maximum apnoea duration increased by 147.1±82.0% from summer to winter conditions (Table 3). As outlined in Materials and Methods, the respiration pattern differed between species. While green turtles mostly respired only once after an apnoea period, regardless of apnoea duration, both loggerhead and hawksbill turtles showed a different respiration pattern. For these turtles, a longer apnoea period was typically followed by a period at the surface, when turtles respired multiple times, interspersed with short apnoea periods.

LME analysis revealed significant relationships between $T_w$ and $f_R$ for all three species (Fig. 3). Both the intercept ($F=9.07, P=0.005$)

and the slope ($F=17.62, P<0.0001$) of this relationship for the loggerhead turtles differed from that of the other turtle species. LME analysis also showed significant relationships between $s\dot{V}_{O_2}$ and $f_R$ in green turtles ($F=126.68, P<0.0001$; Fig. 4) and in loggerhead turtles ($F=30.17, P<0.0001$), but not in hawksbill turtles, probably because of the small sample size for the last species.

**The effects of activity on loggerhead turtle metabolism and its link with body acceleration**

The oxygen consumption rate of loggerhead turtles increased significantly with activity level ($F=59.62, P<0.0001$), so that during swimming, $s\dot{V}_{O_2}$ increased on average by 71.6±17.6% (mean factorial increase: 1.8±0.2; maximum: 3.2), when compared with

<figure><img src="image_7.png" /><figcaption>Fig. 4. Relationship between $f_R$ and $s\dot{V}_{O_2}$ during resting trials with green and loggerhead turtles.</figcaption></figure>

(A) Green turtles ($N=8$ females; $n=84$ trials; $T_w$ range: 20.3–31.9°C). The line indicates the common relationship, established from a LME model and is best described by: $f_R=9.06s\dot{V}_{O_2}+0.498$ ($r^2=0.76, F=126.70, P<0.0001$). (B) Loggerhead turtles ($N=5$; $n=35$ trials; $T_w$ range: 22.9–31.1°C). The common relationship is best described by: $f_R=16.11s\dot{V}_{O_2}-0.091$ ($r^2=0.71, F=30.17, P<0.0001$).

<figure><img src="image_8.png" /></figure>
resting. Similarly, $f_R$ also increased significantly with activity level ($F=47.98, P<0.0001$). The LME model indicated a significant relationship between $s\dot{V}_{O_2}$ and PDBA ($F=59.62, P<0.0001$) as well as $T_w$ ($F=5.06, P=0.03$), while none of the interaction terms were significant. After removing the interaction terms, the same model was run again but because of the limited range of $T_w$ during trials, the latter was not significant in the model. Hence, we used $s\dot{V}_{O_2} \sim$PDBA+turtleID(random] as the final model to generate a common predictive equation, which is given by:

$$s\dot{V}_{O_2} = 16.419(\text{PDBA}) + 0.644, \quad (4)$$

where $s\dot{V}_{O_2}$ is in $ml \min^{-1} kg^{-0.83}$ and PDBA is in $g$ ($r^2=0.63, N=4$ turtles, $n=40$ observations during 22 trials; $F=59.62, P<0.0001$; Fig. 5). The validation exercise (Table 4) returned a mean algebraic error of 1.7% (range: -6.8-8.9%) and a mean absolute error of 15.2% (range: 9.4-19.3%).

## DISCUSSION

Our study investigated the effects of seasonal changes in $T_w$ on the resting $\dot{V}_{O_2}$ of three sea turtle species common to the SWIO using flow-through respirometry. $s\dot{V}_{O_2}$ was greatest in loggerhead turtles and lowest in the larger green turtles. Our study reports the first measurements of metabolic rate for hawksbill turtles, whose $s\dot{V}_{O_2}$ was intermediate between that of the other two species (Tables 1–3, Fig. 2). Although hawksbill turtles in our study were of similar $M_b$ to loggerhead turtles, their $s\dot{V}_{O_2}$ was on average ~25% lower than that of loggerhead turtles. Hence, apart from the effect of body mass, other factors, such as food habits and lifestyle might contribute to species differences in metabolism. Seasonal $T_w$ changes (maximum $T_w$ range: 20.3–31.9°C) were associated with changes in $\dot{V}_{O_2}$ in all turtles, which were paralleled by changes in $f_R$. In addition, activity trials showed that moderate swimming activity increased $s\dot{V}_{O_2}$ of loggerhead turtles up to 3.2 times over resting. The predictive equation, relating turtle body acceleration (PDBA) and $s\dot{V}_{O_2}$, established from these trials, will be important for investigations of loggerhead turtle energy expenditure at sea.

## Seasonal effects of $T_w$ on the metabolism of three sea turtle species

The seasonal changes in $T_w$ had a clear effect on the metabolism of the three sea turtle species investigated (Tables 1–3, Fig. 2). Overall, the thermal sensitivity of metabolism was similar in all species, with $Q_{10}$ values typical for reptiles. Accordingly, given the temperature range typically encountered in the SWIO, green, loggerhead and hawksbill turtles should remain active year-round. In the following we will discuss seasonal changes for each species investigated separately. For a review of sea turtle metabolic rates and the effects of temperature, see also Wallace and Jones (2008) and Southwood-Williard (2013).

Metabolic rate measurements for adult green turtles in water are rare, as most studies have focused on juveniles/immature turtles. In two acclimation studies, resting $s\dot{V}_{O_2}$ of juvenile/immature green turtles declined by ~30% and 40%, when $T_w$ declined by 9°C and 10°C, respectively (Southwood et al., 2003; Kinoshita et al., 2021). $Q_{10}$ values were similar in the two studies, ranging between 1.4 and 1.7. A field study with juvenile green turtles in Australia reported a decline in mass-specific field metabolic rate by 43% from summer to winter ($T_w$: 25.8 versus 21.4°C; Southwood et al., 2006). In another field study, Enstipp et al. (2016) used the accelerometry technique to estimate the daily energy expenditure (DEE) of adult green turtles at their foraging site across seasons. In parallel with a seasonal $T_w$ decline of 3.2°C (from 28.9 to 25.7°C), they found a moderate (~19%) decline in the DEE of turtles from summer to winter, corresponding to a $Q_{10}$ of 1.7. Hence, while there are subtle differences between studies, the overall picture, supported by the current study, is that of a moderate decline in metabolism during the cooler winter months.

Seasonal changes in $T_w$ and metabolic rate are accompanied by changes in the dive behaviour of green turtles. For example, adult green turtles at a foraging site in the Indian Ocean (N'Gouja, Mayotte Island) increased the duration of shallow dives (2–4 m) from summer to winter between 46% and 65% (Ballorain et al., 2013; Enstipp et al., 2016), while the recovery period spent at the surface between dives remained unchanged. Similarly, dive duration of shallow dives (3–5 m) conducted by juvenile green turtles at a foraging site in Australia increased by 81% from summer

<figure><img src="image_9.png" /><figcaption>Fig. 5. $s\dot{V}_{O_2}$ versus partial dynamic body acceleration (PDBA) for loggerhead turtles over a range of activity levels. Body mass ($M_b$): 28.0–51.7 kg; $N=4$ turtles; $n=40$ observations during $n=22$ trials. Mean $T_w$ during trials, conducted during the austral winter, was 24.3°C (range: 23.1–25.2°C). The line indicates the common relationship, established from a LME model, and is best described by: $s\dot{V}_{O_2}=16.419PDBA+0.644$ ($r^2=0.63, F=59.62, P<0.0001$).</figcaption></figure>
<table><caption>Table 4. Results of validation exercise</caption><thead><tr><th>Turtle</th><th>Observed<br>sV̇<sub>O₂</sub> (ml min<sup>-1</sup> kg<sup>-0.83</sup>)</th><th>Estimated<br>sV̇<sub>O₂</sub> (ml min<sup>-1</sup> kg<sup>-0.83</sup>)</th><th>Est.-obs.<br>sV̇<sub>O₂</sub> (ml min<sup>-1</sup> kg<sup>-0.83</sup>)</th><th>Algebraic<br>error (%)</th><th>Absolute<br>error (%)</th></tr></thead><tbody><tr><td>Carotte</td><td>1.01</td><td>1.05</td><td>0.05</td><td>8.9</td><td>18.4</td></tr><tr><td>Louane</td><td>1.06</td><td>0.98</td><td>-0.08</td><td>-6.8</td><td>13.7</td></tr><tr><td>Puffin</td><td>0.98</td><td>0.93</td><td>-0.05</td><td>-4.0</td><td>9.4</td></tr><tr><td>Vetiver</td><td>1.22</td><td>1.23</td><td>0.02</td><td>8.6</td><td>19.3</td></tr><tr><td>Grand mean</td><td>1.07±0.05</td><td>1.05±0.07</td><td>-0.02±0.03</td><td>1.7</td><td>15.2</td></tr></tbody></table>

Shown are the observed and estimated mass-specific oxygen consumption rates (sV̇O₂) of loggerhead turtles during activity and associated error estimates (see Materials and Methods for details). Values are means calculated from 40 observations during 22 trials (5–6 trials per turtle). Grand means (±s.e.m.) were established from individual turtle means. The mean algebraic error takes the difference of the sign into account, while the mean absolute error does not.

to winter (Southwood et al., 2006). Interestingly, in that study, post-dive surface interval duration tripled from summer to winter. Strong effects of T<sub>w</sub> on green turtle dive duration were also reported more recently by Madrak et al. (2022), when dive duration increased significantly after a power plant closure, whose effluent waters had significantly elevated T<sub>w</sub>.

For loggerhead turtles, a number of metabolic rate measurements using respirometry in captive settings have been conducted, spanning all life-history stages, from hatchlings to adults (for review, see table 2 in Wallace and Jones, 2008; Kinoshita et al., 2018). For a comparison with our study, the investigations by Hochscheid et al. (2005) and Kinoshita et al. (2018) are the most relevant, as they also include immature and adult animals. Resting sV̇O₂ at a similar T<sub>w</sub> of ~25°C was 0.46, 0.63 and 0.77 ml min⁻¹ kg⁻⁰.⁸³, for the Mediterranean (calculated from equation 6 in Hochscheid et al., 2004), North Pacific (Kinoshita et al., 2018) and Indian Ocean loggerhead turtles (current study; Table 2), respectively. Hence, the resting metabolic rate (RMR) of Mediterranean loggerhead turtles appears to be considerably lower than that of the North Pacific (factorial increase: 1.4) and Indian Ocean turtles (factorial increase: 1.7). The temperature dependence of metabolism appears to be greatest in the Mediterranean turtles (mean Q₁₀ value: 5.4, range: 2.4–12.8), intermediate in the Indian Ocean turtles (mean Q₁₀ value: 2.7) and lowest in the North Pacific turtles (mean Q₁₀ value: 1.8), though the T<sub>w</sub> range to which turtles were exposed differed between studies. In addition, Kinoshita et al. (2018) used an acclimation study design, while the other studies took advantage of the seasonal changes in T<sub>w</sub>.

Loggerhead turtles in the Indian Ocean might experience a wide range of T<sub>w</sub>. Turtles tracked from Reunion Island roamed throughout the Western Indian Ocean, from south of South Africa, along the coast of East Africa, to the Arabian Sea in the north (Bourjea et al., 2012; Dalleau et al., 2014; Laforge et al., 2023; Monsinjon et al., 2023). The range of sea surface temperatures (SSTs) encountered spanned from 14.6°C in the south to 33.1°C in the north (Monsinjon et al., 2023). While the loggerhead turtles tracked from Reunion Island were rehabilitated turtles, accidentally captured in longline fishery, post-nesting movements of loggerhead turtles from the Maputaland coast of KwaZulu-Natal in South Africa showed that turtles hugged the Mozambique coast, reaching their foraging grounds after a migration of ~500–900 km (Luschi et al., 2006). For Pacific loggerhead turtles, Kinoshita et al. (2018) argued that the higher RMRs in combination with a low thermal dependence of metabolism can support their active overwintering behaviour. While dive duration also differed with T<sub>w</sub> between seasons in these turtles (Narazaki et al., 2015; Kinoshita et al., 2018), the effect was considerably less than in the Mediterranean loggerhead turtles, which became effectively dormant at winter temperatures as low as 11.8°C (Hochscheid et al., 2005, 2007a). The greater thermal sensitivity of metabolism in the Mediterranean loggerhead turtles

might constrain activity levels during winter, while it will also reduce energy requirements during a potentially unfavourable period (e.g. reduced food availability). In comparison with other ocean basins, tracking data for Indian Ocean loggerhead turtles are rare, so detailed information on their dive behaviour across seasons is lacking. However, the SSTs encountered by tracked Indian Ocean loggerhead turtles reported in Monsinjon et al. (2023) and the high RMR measured in the current study suggest that Indian Ocean loggerhead turtles, just like those in the Pacific Ocean, will remain active year-round.

To the best of our knowledge, no metabolic rate measurements exist for hawksbill turtles. Mass-specific metabolic rates (sV̇O₂) of hawksbill turtles in our study were intermediate between those of green and loggerhead turtles (Tables 1–3, Fig. 2). Although mean M<sub>b</sub> was similar in hawksbill and loggerhead turtles in our study, their sV̇O₂ was on average ~25% lower than that of loggerhead turtles. However, the slightly lower T<sub>w</sub> during hawksbill trials might have contributed to that difference. Thermal sensitivity was lowest in hawksbill turtles, though overall differences between species were rather small.

Numerous studies have investigated the dive behaviour of juvenile/immature and adult hawksbill turtles, especially in the Caribbean (van Dam et al., 1996, 1997; Storch et al., 2005; Blumenthal et al., 2009; Witt et al., 2010; Walcott et al., 2013) but also in other regions, such as the Indian Ocean (von Brandis et al., 2010; Hamann et al., 2022) and Pacific Ocean (Okuyama et al., 2010; Gaos et al., 2012). These studies found clear behavioural patterns of shorter/shallower diurnal dives, when turtles are foraging, and longer/deeper nocturnal dives, when turtles rest. Unfortunately, most of these studies did not record T<sub>w</sub> concurrently. However, the few studies that did, found a clear thermal dependence of dive duration (Storch et al., 2005; Gaos et al., 2012). More recently, strong relationships between hawksbill turtle dive duration and T<sub>w</sub> were also reported by Stokes et al. (2023). These authors also modelled the relationship between dive depth and duration for hawksbill turtles in comparison with loggerhead and green turtles. This showed that hawksbill turtles dive for considerably longer than the latter two species (42–286% elevation), when depth and T<sub>w</sub> are accounted for. A number of hypotheses were advanced to explain these findings, among them the suggestion that mass-specific metabolic rate might be lower in hawksbill than in loggerhead and green turtles. Conversely, our results clearly show that hawksbill mass-specific RMR is intermediate between that of green and loggerhead turtles (Tables 1–3, Fig. 2). However, given its much smaller size and M<sub>b</sub> than that of green turtles, whole-animal metabolic rate is indeed lowest in hawksbill turtles. Another interesting species in this context is the olive ridley turtle (*Lepidochelys olivacea*), which shows the capacity for extended dives (maximum: 220 min) at water temperatures comparable to
those of our winter trials, suggesting low metabolic rate (Fukuoka et al., 2022). Apart from body size/mass, other factors might contribute to differences in metabolic rate between species. For example, different feeding habits (quality of food, e.g. energy density, and availability) might have affected the evolution of higher or lower standard metabolic rate (McNab, 2002). Hence, the low mass-specific metabolic rate of green turtles might also be, at least partially, associated with their herbivory, as they predominately feed on seagrass and algae (Ballorain et al., 2010; Esteban et al., 2020). Hawksbill turtles are spongivores, which also feed on other invertebrates, algae and seagrass (Meylan and Whiting, 2008; Reynolds et al., 2023), while loggerhead turtles are considered as carnivorous generalists, favouring crustaceans and molluscs, while also taking fish, if available (Jones and Seminoff, 2013; Baldi et al., 2023). Hence, the typically greater energy density of loggerhead food, when compared with that of hawksbill turtles, might have contributed to the evolution of higher metabolic rates of loggerhead turtles.

Although low water temperatures during winter might limit the activity patterns of marine turtles and restrict their distribution ranges, the high water temperatures experienced by marine turtles of the Indian Ocean during summer (e.g. T<sub>w</sub> in our study reached 31.9°C during summer) might require behavioural thermoregulation and affect their foraging behaviour. For example, when foraging during hot summer days at low tide at a foraging site in Mayotte, green turtles frequently interrupt feeding activity and move to deeper, cooler water, where they rest until conditions become tolerable again, thereby reducing diurnal foraging duration (Ballorain et al., 2013; Enstipp et al., 2016). An extreme case might be the SST range experienced by marine turtles across seasons in the Persian/Arabian Gulf. Annual SST fluctuations might exceed 21°C between the winter (13.7°C) and summer (34.9°C; Pilcher et al., 2014; Rees et al., 2019; Marshall et al., 2020). In consequence, hawksbill turtles have been reported to move away from their original foraging grounds to deeper and cooler waters during prolonged periods of high SSTs (Pilcher et al., 2014; Marshall et al., 2020) and such avoidance behaviour might also occur in green turtles of the region (Pilcher et al., 2021). In another study, Rees et al. (2019) did not find evidence for such evasive behaviour of hawksbill turtles, despite SSTs in excess of 33°C. The authors attributed this to the behavioural plasticity of turtles nesting in the Persian/Arabian Gulf, so that a potential trade off between attractive foraging sites and thermal stress might alter the response of individual turtles. Nevertheless, a recent study suggested that by 2100, globally more than two-thirds of vital foraging habitats for marine turtles will experience SSTs that will potentially expose them to thermal risks (Goudarzi et al., 2024).

## Seasonal effects of T<sub>w</sub> on turtle apnoea duration/respiratory frequency

In our study, loggerhead turtles showed the highest mass-specific metabolic rate of the species investigated and, not surprisingly, their breathing frequency was also considerably higher than that of green and hawksbill turtles (Tables 1–3). We found significant relationships between T<sub>w</sub> and f<sub>R</sub> for all three species during resting trials, so that f<sub>R</sub> increased with T<sub>w</sub> from winter to summer (Fig. 3). Thermal dependency of breathing rate was greatest in loggerhead turtles, as indicated by the significantly greater slope when compared with the other species (Fig. 3B). In general, changes in metabolic demand for oxygen associated with changes in temperature and/or activity can be met through changes in ventilation and perfusion. If we focus on the former, the ventilatory flow can be changed by altering the breathing

frequency and/or tidal volume. Previous studies with green and loggerhead turtles have shown that increases in oxygen consumption with activity are accompanied by an increase in breathing frequency, while the scope to increase tidal volume appears limited (Jackson and Prange, 1979; Butler et al., 1984; Lutz et al., 1989; Lutcavage and Lutz, 1997). By contrast, changes in oxygen consumption with temperature alone (resting turtles) are presumably facilitated by changes in tidal volume, breathing frequency and oxygen extraction per breath (Kraus and Jackson, 1980; Lutz et al., 1989). In this context, it is interesting that we also found significant relationships between f<sub>R</sub> and sV̇O₂ in green and loggerhead turtles (Fig. 4), while this relationship was absent in hawksbill turtles, probably because of the small sample size. This suggests that most changes in sV̇O₂ that we observed as a consequence of changes in T<sub>w</sub> were facilitated via alterations in f<sub>R</sub>. Accordingly, though the robustness of the relationship between metabolic rate and f<sub>R</sub> for sea turtles needs to be further explored in future studies, the recording of f<sub>R</sub>, if technically feasible, might also allow us to estimate field energy expenditure of free-ranging turtles.

The differences in respiration patterns (single versus multiple breaths at the surface) we found between green turtles on the one hand and loggerhead/hawksbill turtles on the other might be related to the artificial conditions of captivity, where shallow tanks allow easy access to air. In the wild, sea turtles adjust their lung volume before resting dives so that neutral buoyancy is achieved at the desired depth, typically considerably deeper than that possible in our set-up (Hays et al., 2004, 2024; Hochscheid et al., 2007b). The greater lung volume and, hence, oxygen store enables long dives, after which turtles rest at the surface to replenish their oxygen stores, which will require multiple breathing cycles. Why breathing dynamics differed between species in our study is not clear but might be associated with size differences. Predominately single breath patterns have also been observed in other captive studies with green and loggerhead turtles, where multiple breaths rarely occurred and only after long dives (Lutz and Bentley, 1985).

## The effects of activity on loggerhead turtle metabolism and its link with body acceleration

We found a clear increase in sV̇O₂ and f<sub>R</sub> of loggerhead turtles as a consequence of increases in activity level. We also found a significant positive relationship between PDBA and sV̇O₂ in these loggerhead turtles (Fig. 5), suggesting that body acceleration can serve as a good proxy of turtle energy expenditure. Unfortunately, as these activity trials were only conducted during the austral winter and, hence, over a limited temperature range (maximum difference: 2.1°C), the combined effects of T<sub>w</sub> and activity on turtle sV̇O₂ could not be investigated. Nevertheless, it was possible to generate a significant predictive equation (Eqn 4) that allows the estimation of turtle sV̇O₂ from the recording of PDBA. A validation exercise returned mean algebraic and absolute errors that are small (Table 4) and similar to a previous investigation concerning green turtles (Enstipp et al., 2011). They are also comparable with other studies that deployed the accelerometry and/or heart rate method to estimate the energy expenditure of both terrestrial and semi-aquatic/aquatic animals (Fahlman et al., 2008; Green et al., 2009; Halsey et al., 2009; Halsey and White, 2010; Payne et al., 2011) and even hatchling loggerhead/immature green turtles (Halsey et al., 2011b). Hence, this confirms the promise of the accelerometry method to allow detailed investigations of marine turtle energy expenditure at sea.

There are some caveats when using the acceleration method to estimate energy expenditure in animals that have to be considered (for review, see Wilson et al., 2019). Most importantly, this method
assumes that the major part of the energy expenditure above the resting
metabolism of the animal is due to movement, as it quantifies the
energy-consuming movements of an animal. By contrast, if an animal
engages in energetically costly processes while resting (e.g.
thermoregulation, digestion), this will probably not be reflected in
the acceleration signal (but see Green et al., 2009). If such periods
account for a non-negligible part of the considered period, the
acceleration method will probably underestimate energy expenditure.
Furthermore, the recorded acceleration must be derived from the
muscle-powered movement of the animal. If, for example, an animal
spends long periods at the sea surface floating, i.e. not moving actively
(like many seabirds), differences in wave action associated with
different sea states are likely to affect the calculated acceleration
metric, leading to erroneous energy expenditure estimates (see figure 3
in Wilson et al., 2019). If we consider the above limitations with
respect to sea turtles, we suggest that they are well suited to estimation
of their energy expenditure at sea using the acceleration method. First,
apart from through behavioural means (Hochscheid et al., 2010),
chelonid sea turtles, as ectotherms, do not thermoregulate like
endotherms, i.e. they do not use metabolic means to maintain an
elevated body temperature. However, the situation differs for soft-
shelled leatherback turtles, which can use the metabolic heat generated
by vigorous swimming activity to maintain an elevated and stable
body temperature (Bostrom and Jones, 2007; Bostrom et al., 2010).
Second, while digestive costs might not get picked up by
accelerometry, our turtles were maintained on their usual daily
feeding schedule and were, hence, in an absorptive state, so that
digestive costs were included in the respiratory measurements and
should therefore be incorporated into our predictive equation. Third,
unlike many seabird species that might spend extended periods
floating passively at the sea surface, marine turtles are ‘surfacers’
(Kramer, 1988) that live submerged within the water column, only
returning to the surface to breathe. Exceptions are, of course, extended
basking periods, when turtles absorb solar radiation, supposedly to
warm up and accelerate digestive processes (Hochscheid et al., 2010).
However, extended basking periods will presumably not occur during
agitated sea states. Hence, differences in sea state are unlikely to affect
the recorded acceleration metric and energy expenditure estimations.

Unfortunately, we could not include the effect of T<sub>w</sub> in the predictive equation. However, the temperature effect on metabolism will probably be strongest during resting periods. Hence, one could use the acceleration signal to ascertain resting periods and incorporate the temperature effect on turtle metabolism established during resting trials (Fig. 2B). Although our calibration study relating PDBA with sV̇<sub>O₂</sub> will enable researchers to gain reliable estimates of loggerhead turtle energy expenditure during natural activities, it is important to consider the limitations of our study. First, we used both adult and sub-adult loggerhead turtles in our trials covering a M<sub>b</sub> range of 28 to 52 kg and our predictive equation will only provide reliable estimates within that range (to emphasize that point, see Okuyama et al., 2014, and Enstipp et al., 2016). Second, our study was restricted to a relatively small pool, similar to other studies (e.g. Halsey et al., 2011b). This is unlike our previous calibration study with green turtles, where animals could swim within a 13 m-long channel (Enstipp et al., 2011). Hence, the overall calibration range of PDBA is slightly smaller than that for green turtles, and loggerhead turtles swimming at sea could potentially surpass the calibration range. The importance of using species-specific calibrations is also illustrated by the study of Wilson et al. (2017). In the absence of an established calibration for loggerhead turtles, the authors used a predictive equation established for green turtles. While this certainly allowed them to contrast different

conditions (the authors compared the dive behaviour and energetics
before and after a tropical storm), the absolute values for turtle
energetics are likely to be erroneous. Using the equation established
for green turtles will clearly underestimate the metabolic rate of
loggerhead turtles, as we have shown that the sV̇<sub>O₂</sub> of the latter is
~64% and 79% greater than that of the former for summer and winter
conditions, respectively, at comparable mean T<sub>w</sub> (Tables 1 and 2).

In conclusion, our investigation showed that the thermal sensitivity of metabolism is comparable in all three sea turtle species studied. Similar to Atlantic and Pacific Ocean loggerhead turtles, Indian Ocean loggerhead turtles show moderate thermal sensitivity of their metabolism, enabling them to remain active throughout the year. This is unlike the situation in the Mediterranean loggerhead turtles, where low water temperatures during winter greatly reduce their metabolic rate and activity patterns, enabling them to overcome unfavourable conditions at that time of year but leaving them potentially vulnerable to predation/anthropogenic disturbances. Conversely, predicted increases in T<sub>w</sub> across globally important foraging habitats of sea turtles will increase their energy requirements and might expose them to thermal stress. Hence, turtles might have to choose between staying in warmer areas (where energy expenditure will be increased but food availability might be better) or moving to cooler waters (where foraging opportunities might be reduced). Such a potential trade off might affect their energy balance, which in turn might affect reproductive capacity and demographic development. However, how the predicted increases in T<sub>w</sub> will affect sea turtle foraging behaviour and energy balance might differ between species and populations and will also depend on food preferences. For example, increases in T<sub>w</sub> will probably decrease seagrass productivity, so that grazing species face an energetic dilemma in warmer areas.

Acknowledgements

We are greatly indebted to everyone at Kelonia, particularly to the animal care staff: Eric Hoareau, Bernardin Ouaratta, Jean-Marie Marivan, David Atrigo, Alain Rocrou, Kevin Certat and Mathieu Barret, who took care of the turtles and to Francis Schneider, who provided veterinary support. Claire Jean and Henri Sequeira provided practical help during experimentation, while Gunna Weingartner helped during experimentation and with data analysis. Benoit Gineste and Myriam Milbergue conducted some of the respirometry trials with green turtles, as part of their MSc projects. We wish to thank them all kindly. We are also grateful to Akiko Kato and Yan Ropert-Coudert for lending us the acceleration loggers. Finally, we thank Graeme Hays and David Booth for their many helpful comments.

Competing interests

The authors declare no competing or financial interests.

Author contributions

Conceptualization: M.R.E., V.P., K.B., J.-Y.G., S.C.; Data curation: M.R.E., V.P.; Formal analysis: M.R.E.; Funding acquisition: J.-Y.G., S.C.; Investigation: M.R.E., V.P.; Methodology: M.R.E., V.P., K.B., J.-Y.G., S.C.; Project administration: M.R.E., J.-Y.G., S.C.; Resources: M.R.E., J.-Y.G., S.C.; Software: M.R.E.; Supervision: M.R.E., J.-Y.G., S.C.; Validation: M.R.E.; Visualization: M.R.E.; Writing – original draft: M.R.E.; Writing – review & editing: M.R.E., V.P., K.B., J.-Y.G., S.C.

Funding

This study was part of the project ESTVOI (Ecologie Spatiale des Tortues Vertes de l'Océan Indien) and supported by a grant from the Agence National de la Recherche (ANR-07-BLAN-0220) to Simon Benhamou and J.-Y.G.

Data and resource availability

All relevant data can be found within the article.

References

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