The influence of lipid-extraction on the δ¹³C of mesopelagic and demersal fish in the South China Sea: modification and application of lipid normalization models

1. Introduction

Mesopelagic fish dominate (in number and biomass) among open ocean teleostean fish. Most mesopelagic fish exhibit the behavioral trait of daily vertical migration through the water as a refuge against predators during the day and in pursuit of food at night (Olivar et al., 2012; Sutton, 2013). These fish play substantial roles in the active carbon transport process in the water column by carrying ingested zooplankton downward to deeper zones. Thus, these fish are a key factor in the open ocean food-webs and carbon flux (Irigoien et al., 2014). To satisfy the energy requirement for daily vertical migration, mesopelagic fish have a higher content of lipids, with indispensable functions in energy store and buoyancy (Catul et al., 2011; Hudson et al., 2014; Stowasser et al., 2009b; Wang et al., 2019a). Moreover, other mesopelagic fish groups, including non-migrant planktivores, and piscivores, and semi-migrant piscivores, are also essential in indirect carbon transport (Jónasdóttir et al., 2015). Mesopelagic fish also play an important role in marine food webs by providing food resources for the demersal fish (Richards et al., 2019).

Stable isotopes have been used to investigate the trophic ecology of mesopelagic fish in several regions (Eduardo et al., 2021). The carbon isotope content ratio ([¹³C]/[¹²C]), typically notated as δ¹³C, provides a time-integrated measure of carbon transfer to a consumer from their diet (Park et al., 2018; Peterson and Fry, 1987; Post, 2002). However, lipid δ¹³C values are more likely to be depleted than carbon discrimination during synthesis and storage, resulting in negative δ¹³C values (DeNiro and Epstein, 1977; Newsome et al., 2010, 2018). The dietary sources revealed by δ¹³C without lipid extraction are obscure due to the high lipid content in mesopelagic fish. Therefore, it is crucial to eliminate the effect of lipid content on the δ¹³C value in these fish (Wang et al., 2019b). Whether it is appropriate to unify the existing models has not been studied (Cherel et al., 2010; Colaço et al., 2013; Fanelli et al., 2011; McClain-Counts et al., 2017; Olivar et al., 2019; Richards et al., 2019; Valls et al., 2014). Considering that mesopelagic fish tend to have high lipid content, we must cautiously eliminate lipid effects on δ¹³C (Catul et al., 2011).

To eliminate the lipid effect and avoid time-consuming chemical extraction, the lipid normalization model has been recommended as the main method of sample standardization (Weldrick et al., 2019). There are two principal models typically used in studying the relationship between δ¹³C and C/N content ratio in mesopelagic fish (Flynn and Kloser, 2012; Olivar et al., 2019; Valls et al., 2014). A non-linear model, proposed by McConnaughey and Mcroy (1979), focuses on the study of Δδ¹³C (the difference in δ¹³C values before and after lipid removal) in marine invertebrates and vertebrates. The linear model proposed by Post et al. (2007) is based on the relationship between Δδ¹³C and C/N content ratio. Lipids are extracted from fish with a C/N content ratio larger than 3.5 because such tissues are generally regarded as rich in lipid content (Cloyed and Eason, 2016; Post et al., 2007). Although there is a preferable relativity between C/N content ratio and Δδ¹³C, the Post’s model is based on aquatic animals with low lipid content (mainly lower than 20%) relative to mesopelagic fish (Post et al., 2007). Moreover, the effect of lipids on ¹³C, C/N ratio, and Δδ¹³C in tissues vary considerably due to different statuses (Bowen et al., 1987; Fagan et al., 2011). Therefore, there is a demand for more robust lipid-correction models for mesopelagic fish, especially when the C/N content ratio is low level and the lipid content is high (Cloyed and Eason, 2016; Cloyed et al., 2020; McClain-Counts et al., 2017; Post et al., 2007).

The South China Sea (SCS) is the largest marginal sea in the western tropical Pacific Ocean with complex physicochemical environments (Su, 2004; Zhang et al., 2018). The physical and biological environments in the northern slope and central SCS are complex (Gong et al., 2015b; Li et al., 2011; Lin and Lin, 2006; Yu et al., 2016). The different aquatic environments where mesopelagic fish reside lead to a different relationship between the C/N content ratio and δ¹³C (Hu et al., 2000). It is currently unclear whether using the existing correction models will affect the results of lipid correction in the fish in these regions. An analysis of trophic interactions among mesopelagic fish in the SCS using stable isotopes has suggested that the effect of lipid content in stable carbon isotopes must be considered (Svensson et al., 2014; Wang et al., 2019a). Additionally, the connection between the C/N content ratio and lipid content indicates the necessity of mathematical normalization methods to account for the effect of lipids on δ¹³C levels.

In summary, a lipid normalization model should be constructed by extracting a sample subset in cases of highly variable lipid content in mesopelagic fish. Therefore, we hypothesize that using the existing linear model from aquatic organisms with different lipid content cannot completely explain the data or disclose the true isotopic changes that fish undergo in different regions. To verify these hypotheses, we compare the δ¹³C values by chemical extraction with the results of the mathematical correction of mesopelagic and demersal fish in the SCS and present the mathematical normalization models for these fish. In particular, we survey the relationship between C/N content ratio, lipid content and Δδ¹³C values to conduct a systematic study on mesopelagic and demersal fish in the north slope and mid-western of the SCS.

2. Materials and methods

2.1 Sample collection and preparation

Fish samples were collected from the continental slope of the SCS during four cruises carried out in October 2014, June 2015 and March 2017, and from the mid-western SCS in October 2016 (Fig. 1; Table 1). The mesopelagic fish samples were obtained using a mid-layer trawl with a mouth perimeter 136.10 m and a headrope length 50.85 m with a trawling speed 3.4–4.5 m/s in 60–120 min. The demersal fish were caught using a bottom trawl with a mouth perimeter 110 m and a headrope length 87.16 m with a trawling speed 3.4–4.1 m/s in 60–120 min.

Figure  1.  Map of sample collection regions in the South China Sea (SCS) (a): the north slope of the SCS (b); the mid-western SCS (c). L1–L10 represent sampling sites of mesopelagic fish on the northern slope of the SCS; D1 and D2 are sampling sites of demersal fish in the continental shelf area and shrimp farm zone of the SCS; S1–S6 represent sampling sites in the mid-western SCS.

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Preliminary catch analysis was performed on board. All specimens were identified, counted, measured, and recorded. Sampling details are described in Zhang et al. (2019). All obvious large specimens and rare species were removed with proportional subsamples. The obtained samples were divided into equal proportions to obtain sample subgroups for measurement. Each specimen and its feeding habits were identified using morphological characteristics and guides to “The Fish of the Japanese Archipelago” (Masuda et al., 1984), “Fish of Taiwan” (Shen, 1993), “Fauna Sinica: Osteichthyes (Myctophiformes, Cetomimiformes and Osteoglossiformes)” (Chen, 2002), “Review of Fish of South China Sea” (Sun and Chen, 2013), and “Marine Fish of China” (Chen and Zhang, 2015). Based on the growth and development logistic curve, the initial sexual maturity body length in mesopelagic fish is larger than 50 mm (Catul et al., 2011; Jin et al., 2011; Gong et al., 2015a; Kong et al., 2016). A total of 127 individuals were used in the subsequent analyses with about 50 mm (43.9–59.1 mm) body length for similar physiological status.

The skin and scales from each sample were removed. And the muscle tissues of samples were taken from the anterior dorsal region. The muscle tissue samples were lyophilized in a freeze dryer (LOC-1, Christ, Germany) and stored at −40℃ until further analysis (Cui et al., 2015). The dried muscle samples were grounded using a mortar and pestle to ensure homogeneity.

2.2 Lipid extraction and stable isotope analysis

The lipid content was determined from a known quantity of tissue extracted using a dichloromethane-methanol solvent system (2:1 v/v, including 0.01% butylated hydroxytoluene) based on Floch’s method (Folch et al., 1957, Wan et al., 2010). Approximately 15 mL of dichloromethane:methanol (2:1) was added to 100 mg of the sample. The mixture was extracted and centrifuged (3000 r/min, 10 min). The supernatant was transferred to the flask with a pipette. The solution was evaporated to dryness under an N² flow at indoor temperature and weighed. The lipid content was calculated as the percentage of the mass of freeze-dried tissue without lipid extraction (Svensson et al., 2014). The extracted tissue has been dried under a stream of N₂ at room temperature for measuring the ¹³C value. The bulk sample carbon isotope (δ¹³C_bulk) was detected using the EA-IRMS (Finngan Delt plus XP, Thermo-Fisher, Germany) after weighing 0.2 mg of the freeze-dried sample and placing it in a tin capsule. The extraction carbon isotope (δ¹³C_extraction) was detected by weighting 0.2 mg of the lipid-extracted samples with the same detector method. We measured the C/N content ratio of the fish samples at the same time. The C/N content ratio was expressed as a mass ratio of carbon to nitrogen (C/N_mass) by comparing total organic carbon (TOC) to the total nitrogen (TN) of samples without lipid extraction. The carbon isotope standard used pseudobolite standard from South Carolina, USA (Cherel et al., 2010). Isotope ratios were expressed in the difference between the isotope ratio of a sample and that of an international standard as the following formula (Svensson et al., 2014):

where [¹³C] and [¹²C] mean the contents of ¹³C and ¹²C. The standard deviations of isotopic measurements were less than 0.1‰ at ten sample intervals using the carbon isotope standard.

2.3 Lipid normalizing model

In this study, a mathematical normalization model was performed to determine whether C/N_mass can be used to predict the effect of lipid contents on δ¹³C values. This is typically achieved using Δδ¹³C against the C/N_mass of the sample without lipid extraction to “correct” bulk samples. The lipid normalizing formula proposed by Post et al. (2007) indicated that there was a positive linear relation between C/N_mass and Δδ¹³C:

A relatively popular formula termed “lipid normalized” δ¹³C/‰ was presented by McConnaughey and McRoy (1979), which mainly focused on Δδ¹³C of marine invertebrates and vertebrates. It was described as follows:

where L represents lipid content (percentage of dry weight) of the sample, D is the depletion of ¹³C (‰) in lipid relative to protein and assigned as 6‰. According to Eqs (3) and (4), Δδ¹³C can be combined and transformed as the following formula:

Based on the Eq. (4) and the non-linear relationship modified by Wang et al. (2009), this study used Pacific salmon (Satterfield and Finney, 2002) and fish samples in the East China Sea (Wang et al., 2009) for non-linear fitting together.

2.4 Statistical analysis

Data were presented as the mean±one standard deviation (SD) when more than one sample was analyzed. Paired t-tests were performed to test the effect of lipid extraction. The significant differences in data are expressed using Pearson correlation coefficients. One-way analysis of variance (ANOVA) was used to test for significant differences in mesopelagic fish with different patterns. Results associated with P-values less than 0.05 were considered statistically significant, and P-values higher than 0.05 were not statistically significant. Our systematic error measurement of the instrument was ±0.1‰, which we accounted for to test the accuracy of the corrected model. Data analyses and linear fitting were conducted using the statistical software Origin 2019b (9.26).

3. Results

In this study, 127 fish from the SCS were analyzed. Standard body length had no relevance to lipid content (P=0.15). The Δδ¹³C_theory was calculated using a linear normalization model (Post et al., 2007) and then compared with Δδ¹³C_extraction (difference between the bulk and chemical lipid-extracted δ¹³C). The result was 29.9% Δδ¹³C values in the error range (dots in dash area, Fig. 2). The δ¹³C values of 87% lipid-extracted samples were more negative ​​than the theoretical values (Fig. 2). Additionally, the results showed a certain difference in normalization values between different groups (Fig. 2).

Figure  2.  The difference between Δδ¹³C_extraction and Δδ¹³C_theory in four groups of fish in the SCS. Δδ¹³C_extraction: the difference between bulk and lipid-extracted δ¹³C. Δδ¹³C_theory: Δδ¹³C was calculated using the lipid normalization model (Post et al., 2007). Grey area: ±0.2‰ error range.

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3.1 Lipid content, C/N_mass, total organic carbon, and total nitrogen

There were significant differences among lipid content, C/N_mass, TN and TOC in the four groups (P<0.01, Fig. 3). Significant differences in lipid content and C/N_mass were found between mesopelagic fish (30.7%±6.4%) and demersal fish (19.6%±7.7%, P<0.01). The C/N_mass ratios of mesopelagic fish varied from 2.6 to 5.7 (mostly from 3.0 to 5.5), which was higher than demersal fish at Site D2 (3.1±0.2, P<0.01) and Site D1 (3.5±0.4, P<0.01). Two mesopelagic fish species (Melamphaes simus, Stomias nebulosus) had a C/N_mass higher than 5.5. The lipid content, C/N_mass and TOC of demersal fish, differed significantly between the two sites (P<0.01, Table 2). However, the δ¹³C has a larger deviation at Site D2 than at Site D1 (Table 2).

Figure  3.  The percentage of lipid content, total nitrogen (TN), and total organic carbon (TOC) in mesopelagic and demersal fish in the South China Sea (SCS).

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Table  1.  Sample information

Sampling period	Region	Habitat	Site	Number
Oct. 2014	north slope	mesopelagic	L1, L4, L5	14
Jun. 2015	north slope	mesopelagic	L2, L6, L8	32
Mar. 2017	north slope	mesopelagic	L3, L7, L9, L10	19
Oct. 2016	mid-west	mesopelagic	S1−S6	24
Oct. 2014	Site D1	demersal	D1	24
Jun. 2015	Site D2	demersal	D2	14

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Table  2.  Mean±SD lipid content, carbon content to nitrogen content ratios (C/N_mass), total nitrogen content (TN), total organic carbon content (TOC), and Δδ¹³C (the difference between bulk and lipid-extracted δ¹³C) in four regions of the SCS. Pearson correlation coefficient tested the correlation between lipid content and C/N_mass, C/N_mass and Δδ¹³C

Region	Lipid content/%	C/Nmass	TN/%	TOC/%	Δδ13C/‰	Lipid content vs. C/Nmass			C/Nmass vs. Δδ13C
						P	Pearson corr.		P	Pearson corr.
North slope	30.4±6.6	3.7±0.6	10.5±1.0	40.7±5.0*	0.9±0.7*	< 0.01	0.38		< 0.01	0.77
Mid-west	31.7±5.9	3.7±0.6	9.2±1.0*	32.9±3.2*	1.2±0.6	0.69	−0.09		< 0.01	0.95
Site D1	16.7±6.9	3.5±0.4	12.8±2.1	43.8±5.9	0.4±0.2	< 0.01	0.86		< 0.01	0.84
Site D2	24.5±6.8	3.1±0.2	12.1±0.3	37.5±1.6	0.9±0.2	0.06	0.53		0.03	0.57
Note: *represents a significant difference in ANOVA for different migration habits in mesopelagic fish with significant value P<0.05.

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For the mesopelagic fish, there were significant differences between these two regions in terms of TN and TOC (P<0.01), but there was no significant difference in lipid content (P=0.39). The migratory fish had a higher lipid content (31.0%±7.0%) and lower C/N_mass (3.8±0.6) and TOC content (39.6%±4.9%) compared to non-migratory fish (lipid content: 29.0%±5.4%, C/N_mass: 4.1±0.4 and TOC content: 42.6%±4.0%) and semi-migratory fish (lipid content: 28.7%±6.7%, C/N_mass: 4.2±0.8 and TOC content: 45.3%±3.8%). These groups differed significantly in their TOC content (ANOVA, P<0.01), but there was no significant difference in C/N_mass (ANOVA, P=0.22) and TN content (ANOVA, P=0.39). There was no significant difference in C/N_mass in fish with different migratory habits in mesopelagic fish in the mid-western SCS (ANOVA, P=0.10).

3.2 Lipid normalization

We applied C/N_mass with Δδ¹³C of all samples to establish a lipid normalization model (${\Delta }{\delta }^{13}{{\rm{C}}} = -1.87 + 0.73{\times {\rm{C}}/{\rm{N}}}_{{\rm{mass}}}$, R²=0.49, P<0.01) , in which only 26.8% of the data was in the error range ±0.2‰ between the theoretical value and the extraction value. We also examined the utility of C/N_mass for predicting the lipid content and found that there was no significant correlation between lipid content and δ¹³C of mesopelagic fish in the mid-west SCS (P=0.69) and demersal fish at Site D2 (P=0.06). However, C/N_mass and δ¹³C were highly correlated in each group (Table 2). The best-fitting result of mesopelagic fish was set up in two groups based on geographical location, including the northern and the mid-western SCS. In the north (Fig. 4a) and mid-west (Fig. 4b), 62.3% and 79.2% of the data were in the error range ±0.2‰, respectively. The correlation of lipid content and C/N_mass was poor among vertical migration species (R²=0.52) compared to the non-migrated species (R²=0.72) and semi-migrated species (R²=0.93). In the mid-west, mesopelagic fish had a great correlation in vertical migration species (R²=0.84), non-migrated species (R²=0.77), and semi-migrated species (R²=0.99) when we divided mesopelagic fish by migration behaviors and reconstructed the correlation model using C/N_mass and lipid content.

Figure  4.  The linear relationship between C/N_mass and Δδ¹³C of mesopelagic fish in the northern (a), mid-western (b), and demersal fish (c) in two sites of the South China Sea (SCS). Grey area: 95% confidence interval.

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In demersal fish, the linear relationship between C/N_mass and Δδ¹³C had a better fit at Site D1 (R²=0.70, P<0.01) than Site D2 (R²=0.43, P=0.01) (Fig. 4c). The Δδ¹³C values of the demersal fish in the Site D2 were higher than those in the Site D1 (P<0.01). The C/N_mass of the fish in Site D1 (3.5±0.3) was significantly higher than that in Site D2 (3.1±0.2, P<0.01). Compared to C/N_mass, there was a better correlation between lipid and Δδ¹³C. A total of 94.6% of Δδ¹³C values in the two sites were in the error range ±0.2‰.

Based on the non-linear relationship proposed by McConnaughey and Mcroy (1979) and Wang et al. (2009), we compared the C/N_mass and Δδ¹³C with other research on Pacific salmon (Satterfield and Finney, 2002) and fish in the East China Sea (Fig. 5) (Wang et al., 2009). We generated the non-linear model by following:

In the comparative literature, the C/N_mass of mesopelagic fish in the incubation period in this research and liver tissue was typically greater than 5.5 (Satterfield and Finney, 2002; Wang et al., 2009).

Figure  5.  The non-linear relationship between C/N_mass and Δδ¹³C of mesopelagic fish in the northern, mid-western and demersal fish in the South China Sea (SCS).

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4. Discussion

4.1 Sample classification for lipid normalization

On average, using the existing linear lipid correction model causes different deviations in four regions in the SCS (Fig. 2) when considering the significant difference in lipid content between mesopelagic fish (30.7%±6.4%) and demersal fish (19.6%±7.7%). Other studies on mesopelagic and demersal fish found similar content differences, suggesting that lipid content on δ¹³C may differ between these two groups, which need to be discussed separately (Saito and Murata, 1998; Catul et al., 2011). Thus, our results revealed that the sample classification needed to be considered when many fish samples in the SCS were used for lipid calibration with significant differences in lipid content (Abrantes et al., 2012; Hoffman and Sutton, 2010; Logan et al., 2010). Further, we analyzed two specific groups in detail to discuss whether there was a need for further division in each group.

Regarding demersal fish, the influence of biological factors needs to be considered when C/N_mass was lower than 3.5. This showed a greater bias between Δδ¹³C_theory and Δδ¹³C_extraction at Site D2 (blue dots in Fig. 2) than that at Site D1 (green dots in Fig. 2). The high lipid content did not lead to an increase in C/N_mass values (Table 2). The demersal fish at Site D2 presented higher lipid content and lower TOC content than that at Site D1, leading to lower C/N_mass. Previous research suggested that lipid content had little influence on the δ¹³C values when C/N_mass was lower than 3.5, which was not performed in demersal fish (Post et al., 2007). The lipid effect on δ¹³C could not be ignored in demersal fish at Site D2 (Richard et al., 2019). The nutritional structure might be the reason, and lipid metabolism type, should be concerned in these sites because of the difference in TOC (Tocher, 2003). Future studies on lipid structure and metabolism requirements should be conducted to indicate the influence of lipid effect on δ¹³C.

Environmental conditions may exert important influences on the nutritional traits of marine organisms, which might lead to differences in carbon and nitrogen composition in mesopelagic fish (Molina-Valdivia et al., 2021). The northern region was mainly influenced by Pacific water masses, while the mid-western regions were mainly affected by upwelling water masses in different water environments (water temperatures and primary productivity) (Hu et al., 2000; Yu et al., 2016). The bias between Δδ¹³C_theory and Δδ¹³C_extraction were higher in mesopelagic fish in the mid-west SCS (red dots in Fig. 2) than that in the northern SCS (black dots in Fig. 2). Meanwhile, the mesopelagic fish in the northern SCS had higher contents of TN and TOC with similar C/N_mass (Fig. 3). Thus, the mesopelagic fish in the mid-western and northern SCS should be lipid corrected separately. In particular, it was also worth noting that migrating behavior had to be considered during lipid correction, which may be attributed to their poor correlations in C/N_mass and lipid content in the mesopelagic fish in the northern SCS. This finding demonstrates that the migration strategies of fish should be considered during lipid correction (Svensson et al., 2014).

The C/N_mass ratios require special classification, with 3.7 being the main boundary for lipid correction (McClain-Counts et al., 2017; Quintana-Rizzo et al., 2015). Based on the non-linear relationship proposed by McConnaughey and Mcroy (1979) and Wang et al. (2009), we found that the non-linear relationship is more likely to reflect the relationship between C/N_mass and Δδ¹³C when the C/N_mass value was larger than 5.5 and the large C/N_mass could be samples of fish livers or samples in special life stage, which is also consistent with the results of other literatures after combining and analyzing the fish in the SCS and literature data (Logan et al., 2008; Yurkowski et al., 2015). The effect of lipid content on δ¹³C might differ in demersal fish at Site D2 and mesopelagic fish in the mid-western SCS. It was found that the existing C/N_mass results are mainly lower than 5.5 for mesopelagic fish in the muscle (Cherel et al., 2010; Hoffman and Sutton, 2010; Valls et al., 2014; Richards et al., 2019). For some specific species, classification may be required for eliminating the lipid effect on δ¹³C by using non-linear model or lipid extraction, like Benthosema glaciale (C/N_mass was 7.8±1.0) in Olivar et al. (2019). Although the approach classified in the same species and life period produced the least error, best fit, and smallest bias in the model prediction, these correction methods produced similar and well results under proper sample classification.

4.2 The variation of C/N_mass and lipid correction

The differences in the composition of lipids can lead to changes in C/N_mass (Yurkowski et al., 2015). The predictive ability of tested linear lipid correction models available in the literature for mesopelagic fish in the mid-west and demersal fish at Site D2 were poor (Fig. 2). Significance analysis results indicated that significant correlations in C/N_mass and Δδ¹³C, but no common inconsistency was found between lipids and C/N_mass (Table 2), which means C/N_mass cannot be a reasonable indicator of lipid content in the two groups (Fagan et al., 2011). The suggested models could not accurately predict lipid content from bulk C/N_mass. However, bulk C/N_mass had shown a significant correlation with Δδ¹³C, which can still eliminate δ¹³C deviation, except for the demersal fish at Site D2. The inconsistency between lipids and C/N_mass in these fish might reflect spurious results in lipid categories, like that carbon mostly be stored as glycogen in oysters, which has a high C/N_mass but is not depleted in ¹³C, as mentioned in Patterson and Carmichael (2016).

Previous studies considered that the δ¹³C values were lipid normalized following the model of Post et al. (2007) when C/N_mass was larger than 3.5 in mesopelagic fish (Valls et al., 2014; Olivar et al., 2019). However, lipid correction was not well performed when the C/N_mass of mesopelagic fish was mainly less than 3.5 (McClain-Counts et al., 2017), indicating that C/N_mass were different of mesopelagic fish in regions. The C/N_mass was fitted well with Δδ¹³C, when we divided mesopelagic fish into north and mid-west SCS for lipid correction by using C/N_mass to Δδ¹³C (Figs 4a, b), in which the slope and intercept of the lipid correction model in the north are similar to those of the existing linear models (Post et al., 2007). Nevertheless, the linear regression for mesopelagic fish in the mid-west of the SCS has higher slopes and intercepts, suggesting that the relationships between C/N_mass and lipid correction may differ regionally and could be predictable in mesopelagic fish. We recommend that relationships over different regions should be developed in situations where lipid prediction is needed, rather than directly relying on published models.

The C/N_mass values of the demersal fish at Site D2 in the SCS were slightly lower than those in the continental Site D1 (Fig. 4c). However, the Δδ¹³C value of the demersal fish at Site D2 was higher than that in the Site D1, which can be explained by the fact that high lipid composition could maintain its periodical physiological requirements (Tocher, 2003). However, high lipid content did not lead to an increase in C/N_mass. On the contrary, the C/N_mass values of the demersal fish with high lipid content were relatively low, leading to a poor linear relationship between the C/N_mass value and Δδ¹³C (Yurkowski et al., 2015). However, the fitting result at Site D1 had a lower slope and higher intercept than the model, suggesting that the change of δ¹³C could be underestimated when C/N_mass was low and be overestimated when the C/N_mass was getting larger in this region. A growing body of evidence suggests that relying on C/N_mass ratios to determine the necessity of lipid content is overly simplistic (Cloyed et al., 2020; Fagan et al., 2011; Patterson and Carmichael, 2016; Wilson et al., 2014). Thus, the C/N_mass is not always a good predictor of lipid content in these species at Site D2. In the demersal fish at Site D2, where sound relationships cannot be estimated, chemical treatment was the most suitable method to determine δ¹³C values, due to a better fitting curve between lipid and Δδ¹³C (Stowasser et al., 2009a). Mathematical methods did not perform consistently by using C/N_mass ratios in those species (De Lecea and De Charmoy, 2015).

Lipid, carbon, and nitrogen variations in muscle tissues were significant (Cloyed et al., 2020; Fagan et al., 2011). Thus, the C/N_mass is inappropriate for lipid correction in special fish. The effect of lipids on δ¹³C might need careful consideration when C/N_mass is less than 3.5. Several researchers only proceeded with lipid-extract tissues when C/N_mass was larger than 3.5 due to such tissues being generally lipid-rich (Olivar et al., 2019). Our results show that the influence of biological factors needs to be considered to a certain extent when C/N_mass was lower than 3.5. Thus, the C/N_mass should be used more cautiously when establishing the lipid normalization model for the demersal fish in the SCS (Cloyed et al., 2020). Lipid extraction is recommended in these fish.

The mesopelagic fish were analyzed in the SCS with the literature data based on the fitting models and non-linear correction model of McConnaughey and McRoy (1979) and Wang et al. (2009). The δ¹³C variation equaled to zero when C/N_mass was 3.02 and assumed a linear relationship when C/N_mass was less than 5.5 (Eq. (5)) (Wang et al., 2009). As for mesopelagic fish in the SCS, lipid had little effect on C/N_mass values when C/N_mass less than 3.3. When the C/N_mass was 3.3−5.5, the linear correction models can be used to correct δ¹³C values with similar species and close life stages to this study. When C/N_mass was larger than 5.5, it had a non-linear correlation between C/N_mass and Δδ¹³C and the δ¹³C values for samples, such as reproduction period fish and fish livers, which could be normalized by non-linear models (Wang et al., 2009).

5. Conclusions

The lipid content varies between mesopelagic and demersal fish in the SCS. We should consider the lipid effect in stable carbon isotopes when studying the trophic interactions of these fish. It is essential to eliminate the effect of lipid content by separating the fish into different groups when using δ¹³C to study trophic interactions among these fish. Additionally, we establish the lipid normalization model with the relationship of the C/N_mass and Δδ¹³C. However, the C/N_mass should be used more cautiously, especially for migratory mesopelagic fish and demersal fish in the SCS. The samples have to be categorized according to geographical regions and trophic specificity. This indicates that the single mathematical normalization model is not appropriate for correcting lipids of the mesopelagic and demersal fish in different regions and lifestyles in the SCS. This might be because of the differences in a geographical area, metabolic mechanism and lipid class.

We recommend that our models are applied to similar regions and life stages. It is important to note that sex gender and life stage may influence stable isotope values, which also impact lipid correction due to the premise hypothesis of our study. Subsequent refinement experiments for these factors might be necessary for analyzing more specific samples. In addition, future studies of lipid normalization in particular regions are necessary to take account of more subtle effects, such as environmental factors (water depth, temperature, and other factors) and different lipid types in metabolic processes.

Acknowledgements

We thank Guosen Zhang for measuring stable isotopes. We greatly appreciate the help of the crew of the R/V Nan Feng.