INTRODUCTION
The blue shark (Prionace glauca) is an oceanic species distributed globally in temperate and tropical waters (Nakano & Stevens, Reference Nakano, Stevens, Camhi, Pikitch and Babcock2008). Worldwide, it is one of the shark species most frequently captured by fisheries, directly and as bycatch (Stevens, Reference Stevens1976). Due to the nature of this particular fishery and this species’ distribution, the blue shark is one of the most studied species (Nakano & Stevens, Reference Nakano, Stevens, Camhi, Pikitch and Babcock2008). Its feeding habits are no exception: studies have been conducted off the coasts of Santa Catalina Island, California (Tricas, Reference Tricas1979), and Baja California, Mexico (Markaida & Nishizaki, Reference Markaida and Sosa-Nishizaki2010), as well as in the north-east (Kubodera et al., Reference Kubodera, Watanabe and Ichii2007; Preti et al., Reference Preti, Soykan, Dewar, Wells, Spear and Kohin2012) and southern Pacific (Hoyos et al., Reference Hoyos, Marquin and Valle1991; Pardo-Gandarillas et al., Reference Pardo-Gandarillas, Duarte, Chong and Ibañez2007; López et al., Reference López, Meléndez and Barría2010) and in the Atlantic Ocean (Vaske-Junior & Rincón-Filho, Reference Vaske-Junior and Rincon-Filho1998; Henderson et al., Reference Henderson, Dunne and Flannery2001; McCord & Campana, Reference McCord and Campana2003; Bornatowski & Schwingel, Reference Bornatowski and Schwingel2008). Based on stomach content analysis (SCA), the previously cited studies found that blue sharks feed on a wide variety of cephalopods and fishes, suggesting opportunistic behaviour.
Providing taxonomic information on recently consumed prey, SCA offers a window onto the diet of the predator over the short-term. In contrast, stable isotope analysis (SIA) provides insights regarding long-term patterns of trophic interactions (from days to months) (DeNiro & Epstein, Reference DeNiro and Epstein1978; Fry & Parker, Reference Fry and Parker1979; Michener & Schell, Reference Michener, Schell, Lajtha and Michener1994; Fry, Reference Fry2006). The most commonly examined isotopes in trophic studies are δ13C and δ15N (Niño-Torres et al., Reference Niño-Torres, Gallo-Reynoso, Galván-Magaña, Escobar-Briones and Macko2006); δ13C values help identify the carbon source in a trophic web (coastal vs. oceanic habitats) as the consumer's isotope ratio is typically similar to that of its diet (DeNiro & Epstein, Reference DeNiro and Epstein1978), while δ15N values facilitate estimation of the predator's trophic level. If the prey and their corresponding isotopic δ15N and δ13C values are known, SIA can be a useful tool for reconstructing diets, characterizing trophic relationships and constructing food webs (Boecklen et al., Reference Boecklen, Yarnes, Cook and James2011). Stable isotope analysis has previously been used to examine blue sharks in Mexican waters (Polo-Silva et al., Reference Polo-Silva, Galván-Magaña and Delgado-Huertas2012); the authors argue that analysing the stable isotopes in teeth is appropriate for inferring dietary change over a short time period. Polo-Silva et al. (Reference Polo-Silva, Galván-Magaña and Delgado-Huertas2012) found no significant difference in the isotopic signatures of mature and immature females; the opposite was true among males, where significant differences were observed in the isotopic signatures of juvenile and adult males. In the Indian Ocean, Rabehasago et al. (Reference Rabehagasoa, Lorrain, Bach, Potier, Jaquemet, Richard and Ménard2012) argue that body size is one of the most common sources of intraspecific variation in the P. glauca isotopic signature, as large sharks have access to larger prey.
Mixing models have recently been used to estimate the contribution of different prey to a given consumer's diet by assessing the isotope values of the predator and its potential prey species (Phillips & Gregg, Reference Phillips and Gregg2003; Caut et al., Reference Caut, Angulo and Courchamp2008). This combination of methods provides a more detailed description and a more accurate estimation of the relative contribution of different food sources to the diet of a particular predator. In the present study, two complementary techniques (SIA and SCA) were used to describe the trophic ecology of blue sharks off the west coast of Baja California Sur, including information on diet composition and possible variations based on sex and ontogenetic development.
MATERIALS AND METHODS
Samples were obtained from artisanal fisheries at three locations off the west coast of Baja California Sur: Las Barrancas (26°04′N 112°16′W), Punta Belcher (24°15′N 112°05′W), and Punta Lobos (23°25′N 110°15′W) (Figure 1). Sampling was conducted during different years at the three locations: Punta Belcher (February and May 2001), Las Barrancas (May and June 2005) and Punta Lobos (May and June 2006).
The study area, the shark fishing zone in Baja California Sur, Mexico: A. Las Barrancas, B. Punta Belcher and C. Punta Lobos.
Shark captures were made from pangas (motorboats) using simple longline fishing lines equipped with a single hook; mackerel (Scomber japonicus) and Auxis spp. were used as bait. The sex and total length (TL) of each organism were recorded; the stomach was extracted and its contents were fixed in a 10% formaldehyde solution. Muscle tissue from the anterior-dorsal region was recovered, labelled and frozen for isotopic analysis.
Adults (males ≥180 cm TL, females ≥200 cm TL) and juveniles (males <180 cm TL, females <200 cm TL) were identified following Carrera-Fernández et al. (Reference Carrera-Fernández, Galván-Magaña and Ceballos-Vázquez2010).
Stomach content analysis
Each prey item was identified to the lowest possible taxonomic level. Back-calculations were used to estimate cephalopod weights (Kubodera et al., Reference Kubodera, Watanabe and Ichii2007). Other species of relative importance in the diet showed a minimal digestion state (e.g. Pleurocondes planipes). Diet analysis involved calculating the frequency of occurrence (%FO = number of stomachs containing prey i/total number of full stomachs × 100), the percentage of numerical abundance (%N = number of prey i/total number of prey × 100), and weight percentage (%W = weight of prey i/total weight of prey × 100) (Hyslop, Reference Hyslop1980). Once these values were obtained, we calculated the IRI [IRI = (%N + %W)* %FO] (Pinkas et al., Reference Pinkas, Oliphant and Iverson1971), which incorporates the previous indices to evaluate the importance of each item in the species’ trophic spectrum (Liao et al., Reference Liao, Pierce and Larscheid2001). This index is expressed as a percentage following Cortés (Reference Cortés1997).
To determine the diet breadth, Levin's standardized index (Krebs, Reference Krebs1989) was calculated using the following equation:
$$Bi = \displaystyle{1 \over n} - 1\left[ {\left( {\displaystyle{1 \over {\sum {\,pi{\,j^2}}}}} \right) - 1} \right]$$
where Bi = Levin's index, Pij = proportion of prey j in the diet of predator i, and n = number of components in the diet. The values for this index range from 0 to 1. When Bi values are close to zero, the predator is considered a specialist; when Bi values are close to 1, the predator is considered a generalist.
The Morisita-Horn index (Cλ) was used to evaluate diet overlap between sizes (juveniles-adults) and sexes (males-females) (Smith & Zaret, Reference Smith and Zaret1982). This index ranges from 0 (completely different diets) to 1 (similar diets). A biologically significant diet overlap occurs when values are over 0.60; meanwhile, values from 0.30 to 0.59 indicate intermediate overlap, and those ranging from 0.1 to 0.29 reflect minimal overlap (Langton, Reference Langton1982). The Morisita-Horn index is calculated using the following formula:
$$C \lambda = \displaystyle{{2\sum\nolimits_{i = 1}^n {(P_{xi} \times P_{yi})}} \over {(\sum\nolimits_{i = 1}^n {P_{xi}}^{2} + \sum\nolimits_{i = 1}^n {P_{yi}}^2)}} $$
where Cλ is the Morisita–Horn index, P xi is the proportion of the ith prey item of all prey items consumed by predator x, P yi is the proportion of the ith prey item of all prey items consumed by predator y, and n is the total number of prey.
The trophic level based on stomach contents was calculated using Christensen & Pauly's (Reference Christensen and Pauly1992) equation:
$${\rm T}{{\rm L}_{sc}} = 1 + \sum\limits_{i = 1}^n {{\rm D}{{\rm C}_{ij}} \times {\rm T}{{\rm L}_j}} $$
where TL sc is the predator's trophic level, DC j is the proportion of prey j in the diet, and TL j is the standardized trophic level of the jth prey. Trophic levels for the different prey species are from Dambacher et al. (Reference Dambacher, Young, Olson, Allain, Galván-Magaña, Lansdell, Bocanegra-Castillo, Alatorre-Ramírez, Cooper and Duffy2010).
Stable isotope analysis
Muscle samples were collected from Punta Belcher (N = 17; February–July 2001; February, April and May 2002), Punta Lobos (N = 3; December 2000 and June 2001) and Las Barrancas (N = 3; July 2002). Twenty-three sharks of different sizes and both sexes were sampled: seven females, 15 males, one unidentified; 15 juveniles, eight adults. The samples were dried at 45°C and 24–27 × 10−3 MBAR for 24 h using a LABCONCO dry freezer; lipid extraction was carried out using a 1:1 chloroform-methanol solution in a Mars X microwave digestion oven at controlled temperature and pressure for 20 min. Dried samples were then homogenized using an agate mortar and pestle; an analytical balance was used to weigh 0.001 g of the homogenized sample, placed in 8 × 5 mL tin capsules. Stable isotope analysis was carried out at the University of California, Davis, USA, using a mass spectrometer (EMRI) (20–20 mass spectrometer, PDZ Europe, Scientific Sandbach, UK).
The δ15N and δ13C values were calculated using the following equation:
$${\delta ^{15}}{\rm N}\;{\rm or}\;{\delta ^{13}}{\rm C}(\permil) = [({R_{{\rm sample}}}/{R_{{\rm standard}}}) - 1] \times 1000$$
where R sample is the ratio of 15N/14N for δ15N, or the ratio of 13C/12C for δ13C. The standards used for carbon (δ13C) and nitrogen (δ15N) were Pee Dee Belemnite limestone (PDB) and atmospheric nitrogen (AIR), respectively.
Isotope values for the blue shark's main prey were also included in the analysis. These values are from studies carried out in the same area (Velasco-Tarelo, Reference Velasco-Tarelo2005; Richert, Reference Richert2007; Ochoa-Díaz, Reference Ochoa-Díaz2009).
We calculated the relative trophic level (TL p) based on isotope values was using the following equation proposed by Post (Reference Post2002):
$${\rm T}{{\rm L}_{\rm p}} = \lambda + \displaystyle{{{\delta ^{15}}{{\rm N}_{{\rm secondary}\;{\rm consumer}}} - {\delta ^{15}}{{\rm N}_{{\rm base}}}} \over {\Delta n}}$$
where λ is the trophic position of the prey used as δ15Nbase, and Δn is the enrichment in δ15N per trophic level. In this case, we assumed an isotopic enrichment of 3.7‰ for 15N, following Kim et al. (Reference Kim, Casper, Galván-Magaña, Ochoa-Díaz, Hernández-Aguilar and Koch2012). The organism used as δ15Nbase should be an abundant prey species that shares the same habitat as the predator and integrates the isotopic signature of the food web at a time scale large enough to minimize the effects of short-term variation (Post, Reference Post2002). P. planipes (δ15N = 9.3‰; value obtained from Dambacher et al., Reference Dambacher, Young, Olson, Allain, Galván-Magaña, Lansdell, Bocanegra-Castillo, Alatorre-Ramírez, Cooper and Duffy2010) was used as δ15Nbase as this prey meets the criteria proposed by Post (Reference Post2002).
Mixing model
To determine the contribution of each prey item to the predator's diet, we compared the δ13C and δ15N values of the predator and its prey using the SISUS program's mixing model (http://statacumen.com/sisus) (Erhardt, Reference Erhardt2009). This routine is based on a Bayesian approximation, determining the probabilistic distributions of the proportion each prey (source) contributes to the predator's diet (mix). These distributions range from 1 to 99%. To eliminate the effect of the metabolic fractionation that occurs from one trophic level to the next, we employed the isotopic fractionation value proposed by Kim et al. (Reference Kim, Casper, Galván-Magaña, Ochoa-Díaz, Hernández-Aguilar and Koch2012): 3.7‰ enrichment in δ15N values. The prey taxa chosen (Argonauta spp., N = 3; Pleuroncodes planipes, N = 1; Gonatus californicus, N = 1; Scomber japoncus, N = 1; Ancistrocheirus lesueurii, N = 1; Dosidicus gigas, N = 1) for incorporation into the mixing model were the most important prey in the predator's diet based on the IRI (primary and secondary prey).
RESULTS
Stomach content analysis (SCA)
A total of 368 blue shark samples were collected from three fishing locations off the west coast of Baja California Sur; the vast majority (314) was obtained from Punta Belcher, while 37 were obtained from Punta Lobos and 17 from Las Barrancas. Of the 368 blue sharks analysed, 225 were juvenile males, 36 were adult males, 86 were juvenile females and 21 were adult females (Table 1). The minimum and maximum TL recorded were 99 and 269 cm, respectively. Of the 368 stomachs analysed, 57% (N = 210) contained food.
Number of blue shark stomachs analysed by location, month, sex and stage of sexual maturity. Juveniles (J), Adult (A).
A total of 27 different prey items were identified: 13 cephalopods, eight fish, three crustaceans, one bird, one macroalga and one chondrichthyan (Table 2). In total, 736 prey items were recorded: the pelagic red crab P. planipes constituted 52.0% of all prey by number, followed by the cephalopods California armhook squid Gonatus californiensis (11.4%) and Argonauta spp. (8.9%). The prey items that made up most of the biomass were G. californiensis (36.7%), the sharpear enope squid Ancistrocheirus lesueurii (22.4%), and the seven-arm octopus Haliphron atlanticus (18.0%), which together accounted for nearly 80% of the biomass found in stomachs. The total biomass of the recorded prey items was 92,760.86 g. The items most frequently encountered in stomachs were P. planipes (24.3%), G. californiensis (22.9%), Argonauta spp. (17.6%) and A. lesueurii (11.9%).
Diet of the blue shark Prionace glauca caught off the western coast of Baja California Sur, Mexico, in percentage values by number (N), weight (W), frequency of occurrence (FO) and Index of Relative Importance (IRI).
Based on the IRI, the three most important items in the diet were: P. planipes (IRI = 40.0%), G. californiensis (IRI = 34.1%) and A. lesueurii (IRI = 10.4%). The species identified as secondary prey include Argonauta spp. (IRI = 5.1%), H. atlanticus (IRI = 4.5%) and Dosidicus gigas (IRI = 1.6%) (Figure 2).
Variation in the prey species consumed by blue sharks based on the index of relative importance (IRI); (A) females, (B) males, (C) juveniles, (D) adults. Prey items: (Pp) Pleuroncodes planipes, (Al) Ancistrocheirus lesueurii, (Gc) Gonatus californiensis, (Aspp.) Argonauta spp., (Ha) Haliphron atlanticus and (rc) cephalopod remains.
The most important prey items in the diet of males and females were similar; the trophic overlap between the sexes was intermediate (Cλ) of 0.35, with the IRI of some prey items varying by sex (Figure 3). The trophic overlap between juveniles and adults was significant (Cλ = 0.95), as the main prey items were consumed in similar proportions (i.e. Pleuroncodes planipes, Gonatus californiensis and Ancistrocheirus lesueurii) (Figure 3). Levin's index indicated a narrow trophic breadth; therefore, this shark may be categorized as a specialist predator (Bi = 0.08).
Percentage of main prey items (IRI >5%) consumed by blue sharks by sex and maturity stage.
Stable isotope analysis (SIA)
Blue shark δ15N values were normally distributed and ranged from 15.24 to 18.84 (μ = 16.48‰ ± 0.94‰); while δ13C values ranged from −19.37 to −17.22‰ (μ = −18.48 ± 0.63‰) (Figure 4). Similar isotope values were found for males (δ13C μ = −18.66 ± 0.66‰, δ15N μ = 16.45 ± 1.03‰), females (δ13C μ = −18.27 ± 0.38‰, δ15N μ = 16.48 ± 0.95‰), juveniles (δ13C μ = −18.60 ± 0.65‰; δ15N μ = 16.42 ± 1.16‰) and adults (δ13C μ = −18.40 ± 0.54‰; δ15N μ = 16.53 ± 0.49‰).
Distribution of δ15N and δ13C values for blue sharks caught in Mexican waters.
The isotopic contribution of different prey items to the diet ranged from 0% to 60%. Argonauta spp. made the greatest contribution to the blue shark diet (11–41%; δ13C μ = −19.6‰; δ15N μ = 15.9‰), while the contributions of G. californiensis (0–26%; δ13C = 16.3‰; δ15N = 15.6‰), P. planipes (0–60%; δ13C = −19.0‰; δ15N = 12.3‰), A. lesueurii (0–57%; δ13C = −18.0; δ15N = 12.7‰), D. gigas (0–34%; 0–29%; δ13C = −16.7‰; δ15N = 13.5‰) and S. japonicus (0–29%; δ13C = −16.5‰; δ15N = 19.7‰) were lower and not delimited as they were not present in all stomachs (Figure 5).
Contributions of six food sources to the Prionace glauca diet based on the results of the mixing models, showing the per cent of each food source (range: 1–99%): Pplan (P. planipes), Ales (A. lesueurii), Arg (Argonauta spp.), Sjap (S. japonicus), Gcal (G. californiensis), Dgig (D. gigas).
Trophic level
The blue shark's trophic level was estimated using both SCA and SIA, obtaining levels of 4.05 and 3.9, respectively. The SIA value (3.9) was obtained using the 3.7‰ δ15N enrichment factor proposed by Kim et al. (Reference Kim, Casper, Galván-Magaña, Ochoa-Díaz, Hernández-Aguilar and Koch2012).
DISCUSSION
Both the stable isotope analysis (SIA) and stomach content analysis (SCA) indicated that blue sharks from oceanic waters consumed organisms associated with the pelagic food chain, mainly epipelagic cephalopods; they may also consume mesopelagic and bathypelagic cephalopods. The SIA and SCA provided different types of information regarding the contributions of different prey items to the blue shark diet. The SCA indicated that the pelagic red crab P. planipes was the most important prey (IRI = 40%), whereas mixing models based on a probabilistic approach to isotope analysis indicated that the prey item most assimilated by blue sharks was the cephalopod Argonauta spp. These contrasting results reflect the variety of possible diet combinations.
Relative to other food components (i.e. cephalopods and fishes), the pelagic red crab P. planipes does not provide much energy (Abitia-Cárdenas et al., Reference Abitia-Cárdenas, Galván-Magaña and Rodríguez-Romero1997); however, it represents an abundant and available food source, as reflected by the mass strandings of these organisms off the west coast of the Baja California Peninsula (Aurioles-Gamboa et al., Reference Aurioles-Gamboa, Castro-González and Pérez-Flores1994). The feeding strategy of blue sharks is therefore influenced by the abundance of different prey items, as confirmed by the relatively narrow breadth of their trophic niche. This phenomenon has been observed in other sharks, where the dominance of one species in the predator's diet is closely related to the abundance of that species in the ecosystem (Escobar-Sánchez et al., Reference Escobar-Sánchez, Abitia-Cárdenas and Galván-Magaña2006; Blanco-Parra et al., Reference Blanco-Parra, Galván-Magaña, Marquez-Farías and Niño-Torres2011). Blue sharks consumed the most abundant and available prey during winter in the study area, indicating an opportunistic strategy. A greater abundance of squid has been reported at the start of the warm season (Galván-Magaña et al., Reference Galvan-Magaña, Polo-Silva, Hernández-Aguilar, Sandoval-Londoño, Ochoa-Díaz, Aguilar-Castro, Castañeda-Suárez, Cabrera-Chávez-Costa, Baigorrí-Santacruz, Torres-Rojas and Abitia-Cárdenas2013); blue sharks may take advantage of the abundance of different food items; thus, their trophic behaviour may be related to natural fluctuations in the abundance of potential prey.
Other researchers have characterized blue sharks as teutophagous, due to both the large number of cephalopods they consume and the considerable biomass these prey items represent in this predator's diet (Vaske-Junior & Rincón-Filho, Reference Vaske-Junior and Rincon-Filho1998; Henderson et al., Reference Henderson, Dunne and Flannery2001; Kubodera et al., Reference Kubodera, Watanabe and Ichii2007). In the present study, cephalopods were an important group in the stomach contents of blue sharks (~10 cephalopod species). They are considered an important food source for large predators in marine environments, including other shark species and billfish (Amaratunga, Reference Amaratunga1983; Galván-Magaña et al., Reference Galvan-Magaña, Polo-Silva, Hernández-Aguilar, Sandoval-Londoño, Ochoa-Díaz, Aguilar-Castro, Castañeda-Suárez, Cabrera-Chávez-Costa, Baigorrí-Santacruz, Torres-Rojas and Abitia-Cárdenas2013).
Similar values were observed by category (sex and size) using both methods. SCA indicated that blue sharks of both sexes and of different sizes preyed on the same species: P. planipes, G. californiensis and A. lesueurii. Although the same food components were recorded for males and females, the proportion of each prey item consumed varied by sex (IRI). This translated to moderate trophic overlap as females fed mostly on the crustacean P. planipes, while males preferred the squid G. californiensis. Sex and size segregation has been suggested for elasmobranchs (Blanco-Parra et al., Reference Blanco-Parra, Galván-Magaña, Marquez-Farías and Niño-Torres2011); however, the blue sharks sampled in this study were caught in the same area. Thus, we argue that the presence of the same prey items in the diet of both sexes and in individuals of different sizes may be associated with prey abundance. The lack of differences between categories in the isotopic analysis may mean that the same prey items were assimilated. Polo-Silva et al. (Reference Polo-Silva, Galván-Magaña and Delgado-Huertas2012) report that males and females feed on prey with similar isotope values, as reflected in the lack of variation in the SIA. In the present study, some shark categories (e.g. adults) were represented by small sample sizes; therefore, it is difficult to determine the influence of sex or maturity on dietary habits.
The results obtained from the mixing model were variable, likely due to the fact that different prey species from the same area with similar feeding habits tend to have similar isotope values, leading to inconclusive mixing model results (Newsome et al., Reference Newsome, Martinez del Rio, Bearhop and Phillips2007). However, the mixing model supported the SCA results; the most important prey items identified by the SCA were within the range of viable contributions of each prey identified by the mixing model. Histograms of the distributions of feasible contributions suggest that the cephalopod Argonauta spp. should be the prey most assimilated by blue sharks; other prey items did not display a restricted distribution in the mixing model.
The mixing model results were not conclusive due to the probabilistic approach distributions of some blue shark prey species, namely P. planipes and G. californiensis, the most important prey based on stomach contents. The relatively small contribution by pelagic red crab to blue shark muscle growth was also observed by Kim et al. (Reference Kim, Casper, Galván-Magaña, Ochoa-Díaz, Hernández-Aguilar and Koch2012) using isotopic analysis.
The blue shark's trophic levels based on both the SIA (TLp = 3.9, interval 3.6–4.6; using the 3.7‰ enrichment value published by Kim et al., Reference Kim, Casper, Galván-Magaña, Ochoa-Díaz, Hernández-Aguilar and Koch2012) and the SCA were similar (TLsc = 4.05), making blue sharks tertiary consumers. This value is slightly lower than that reported by Froese & Pauly (Reference Froese and Pauly2015) on the Fishbase website (TLsc = 4.4), but close to that reported by Cortés (Reference Cortés1999) for the Atlantic Ocean (TLsc = 4.1). In the present study, blue sharks also consumed carnivorous prey (squid), but there was a high prevalence of pelagic red crabs, a prey with a low trophic level that may have influenced the overall trophic level. In a study in the Atlantic Ocean, Estrada et al. (Reference Estrada, Rice, Lutcavage and Skomal2003) assigned a trophic level of 3.8 (TLp) to blue sharks based on stable isotopes (with a range of 3.7–4.0), which is in accordance with the present study in the Mexican Pacific.
SIA has proven particularly useful in the study of animal trophic ecology, trophic interactions, habitat use and movements (Rabehagasoa et al., Reference Rabehagasoa, Lorrain, Bach, Potier, Jaquemet, Richard and Ménard2012). The stable isotope composition of an organism depends on its diet; thus, SCA is a useful tool that provides taxon-specific sources for the most important prey, providing the biomass, abundance and frequency of occurrence for each prey item. The importance of both complementary techniques allows the integration of information on the trophic ecology of a particular species, in this case blue sharks. Although a considerable number of samples are necessary to correct for bias and further elucidate variation by category or season.
ACKNOWLEDGEMENTS
We would like to thank the Mexican fishermen from Baja California Sur for providing the samples.
FINANCIAL SUPPORT
We wish to thank the Consejo Nacional de Ciencia y Tecnología (CONACYT; National Council of Science and Technology) through the economic support for the Sistema Nacional de Investigadores (SIN; National System of Researchers). O.E.S. thanks CONACyT for funding through the CONACyT assistantship programme ‘Cátedra CONACyT, project 2137, FACIMAR-UAS’. F.G.M. and L.A.A.C. thank the Instituto Politécnico Nacional (IPN; National Polytechnic Institute) for financial support to develop this study. The authors also thank the Estímulo al Desempeño de los Investigadores (EDI; Performance Incentives) and the Comisión de Operación y Fomento de Actividades Académicas (COFAA; Commission for the Advancement of Academic Activities) for fellowships.
