Dosidicus gigas specimens were collected by scientific observers during nocturnal jigging operations between February and May 2019 (Figure 1). A total of 50 individuals were collected from the main fishing grounds in the tropical and Southern temperate Pacific (see Supplementary Table S1 for detailed sampling information). Specimens were immediately frozen on board and kept stored at −20°C until further analysis. Dorsal mantle length (ML) was recorded in the laboratory. The stomach was dissected and weighed for further analysis of MP. The stomach fullness index is assigned by visual observation (Breiby and Jobling, 1985): 0 (empty), 1 (few residues), 2 (half full), 3 (almost full), and 4 (full). The outer areas of the stomachs were rinsed with ultrapure water (Milli-Q water) to remove any adhered particles.

Microplastic extraction was performed using the modified method of our previous study (Gong et al., 2021). The stomachs were transferred to Erlenmeyer flasks and treated with 10% KOH (20 mL per Gram of wet tissue), then covered with aluminum foil to avoid contamination. All Erlenmeyer flasks were placed in a constant temperature oscillator (70°C, 150 rpm) until the stomachs were completely digested. Thereafter, about 6 g NaCl per 20 mL mixture was added overnight for density separation. The suspension was vacuum filtered through a glass fiber filter (2.7 μm pore size, 47 mm diameter, Whatman Inc.).

Each filter was placed in a clean Petri dish pending analysis. The stereomicroscope (SZX2-FOF) and a U-TV0.63XC digital camera (both from Olympus, Tokyo, Japan) were used to observe the filters. All suspect MPs (>50 μm) were photographed and measured using ImageJ version 1.50 software. Shape and color were identified based on a visual assessment of the morphometric characteristics.

To confirm polymer composition, each suspected MP was scanned using a Micro-Fourier Transform Infrared Spectroscope (Micro-FTIR, Spotlight 400, PerkinElmer) in Attenuated Total Reflection mode. Spectra were collected over a broad spectral range (650–4,000 cm⁻¹) at a resolution of 4 cm⁻¹ from an average of 32 sample scans (D’Souza et al., 2020; Huang et al., 2022). The resulting spectra were compared to libraries of standard spectra. The polymer composition was only identified when the confidence level of at least a 70% match or reliable spectral match (after visual inspection) was accepted.

Some measures to avoid potential contamination were implemented throughout: all the solvents (including Milli-Q water) used for sample processing and analysis were filtered over a glass fiber filter (2.7 μm pore size, 47 mm diameter, Whatman Inc.), all devices such as tweezers and Erlenmeyer flasks were thoroughly rinsed three times with filtered ultrapure water and dried; nitrile gloves and cotton laboratory clothing were always worn; experiments were conducted in a closed, ultra-clean laboratory to prevent potential airborne MPs. Clean Petri dishes were placed next to the working zone and checked after experiments. Reference materials such as vessel coatings and fishing gear were also collected. In the case of potential airborne contamination, the same characteristics of microparticles, according to size, shape, and color, were not included in this the results.

To the best of our knowledge, there is currently no standardized protocol for systematically evaluating the potential risks of MPs in pelagic squid. As a consequence, we applied MP abundance into consideration to assess the MP pollution risk in the D. gigas.

Risk assessment was expressed as pollution load index (Tomlinson et al., 1980). The formulas employed for PLI were as follows: C F i = C i / C 0 P L I i = C F i where PLI _i is the pollution load index (Tomlinson et al., 1980) for individual i, C _i is the MP abundance for individual i and C ₀ are defined as the baseline MP abundance, which is theoretically a reference value of the minimum average MP abundance in squid species. Given the absence of a reference value for our study area and species, we followed the approach adopted in previous studies (Kabir et al., 2021; Zhang et al., 2022) and assigned C ₀ to the lowest MPs abundance of contaminated D. gigas obtained in this study. Variation in the selected constant does not affect the relative relationships of PLI among individuals, only absolute values, and therefore does not influence the comparison results.

To assess the potential spatial variations in MP characteristics of D. gigas, the specimens were merged into three main groups according to the sampling sites, i.e., Group Ⅰ (G₁, 84°–92°W, N = 17), Group Ⅱ (G₂, 100°–110°W, N = 22), and Group Ⅲ (G₃, 114°–121°W, N = 11) (Figure 1). Comparisons among sampling groups were performed using the Kruskal-Wallis test since the assumptions of normality and homogeneity of the variances were not met. In addition, Spearman’s rank correlation was used to analyze the relationships between ML, stomach weight and fullness index, and distance from coast with MP characteristics. Regarding the relationship between the stomach weight and the number of MPs per Gram of stomach weight, this correlation test was considered eliminated in the analysis. Statistically significant results were indicated with p < 0.05. All results are presented as mean ± standard deviation (SD).

The visual sorting initially identified a total of 197 suspected MPs. Of these, 44 MPs (22.34%) were confirmed to be plastic polymers by Micro-FTIR. Of all D. gigas analyzed, 25/50 (50.00%) specimens contained MPs and had an average abundance of 0.88 ± 1.12 items/individual and 0.24 ± 0.36 items/g tissue wet weight. Three sampling groups had a similar detection rate of MPs, 47.06% (G₁), 50.00% (G₂), and 54.55% (G₃), respectively. The MP abundances for sampling groups were, G₁: 1.00 ± 1.32 items/individual (0.16 ± 0.23 items/g), G₂: 0.68 ± 0.84 items/individual (0.25 ± 0.34 items/g), G₃: 1.09 ± 1.30 items/individual (0.35 ± 0.53 items/g) (Figure 2). Although MP abundances varied inconsistently across the G₁, G₂ and G₃, no difference in MP abundance was observed among sampling groups (Kruskal-Wallis, items/individual: χ² = 0.55, p = 0.76; items/g: χ² = 0.57, p = 0.75). For all individuals, no significant Spearman correlations (0.19 < p < 0.95) were found between the MP abundances and the stomach weight, stomach fullness index, distance from coast, and ML of D. gigas.

Overall, these findings suggest that all sampling groups were influenced by similar level of MPs pollution. This phenomenon possibly due to MPs could be rapidly egested by D. gigas, which has a fast digestion rate (Gao et al., 2022). Until now, no evidence of MP accumulation in large predator has been documented in other studies (Chagnon et al., 2018). Therefore, the similar MP abundance in each group maybe driven by continuous ingestion and egestion of MPs rather than prey items or distance from coast.

The size range of MPs in all individuals was 58.42–2,944.85 μm (685.86 ± 669.87 μm, Figure 2), with the smallest MPs found in the G₂ and the largest found in the G₁. The average size of MPs in each group was 592.37 ± 725.68 μm, 584.24 ± 475.07 μm, and 945.34 ± 774.49 μm, respectively. No difference in the size of MP was observed among sampling groups (Kruskal-Wallis, χ² = 2.54, p = 0.28), possibly due to the significant positive Spearman correlations between MP size and stomach fullness index (0.41 ≤ r _s ≤ 0.42, p < 0.04). In our study, three groups had similar body size as mentioned before and stomach fullness (Kruskal-Wallis, χ² = 0.55, p = 0.76) which could result in the similar size of MP. In contrast, no significant Spearman correlations (0.21 < p < 0.62) were found between the MP size and the stomach weight and distance from coast of D. gigas.

Three shapes of MPs were recorded in all individuals, including fiber, fragment, and film (Figure 3). The most common MP type was fragment (54.55%), which differs from previous studies performed on D.gigas collected from the Southern waters of G₁ (Gong et al., 2021). This inconsistency among studies may be linked to the D.gigas collected in this study had a relatively small body size. The fragments detected maybe came from the fragmentation of large-sized plastics (Yu et al., 2022; Zhang et al., 2022). The percentage of fibers reached 43.18% in all samples and a single piece of film was found in a specimen from G₂. These fibrous MPs maybe sourced from the degradation of fishing gears and ropes, which would be consistent with previous results reported for marine animals from fishing grounds (Zhang et al., 2019; Yu et al., 2022). Fibrous MPs have larger aspect ratios with the rough surface, are easier to embed in tissues, and persist longer, which can cause mechanical damage and more severe toxicological effects on organisms compared to other types of MPs (Rebelein et al., 2021; Zheng et al., 2022). However, the prevalence of fibers in the samples may often be overestimated when the collection and analysis of the samples are not conducted under strictly controlled clean air (Hermsen et al., 2017).

Different compositions of shapes were found among the sampling groups. MPs in G₁ specimens had a higher proportion of fragments (76.47%), with the remaining fibers (23.53%). For G₂ and G₃ specimens, however, the MPs were dominated by the fibrous form (58.33% and 53.33%), with 41.67% and 40.00% MP fragments, respectively. This pattern might be due to fibrous MPs could easily be transported by ocean currents to offshore areas, which accounts for the higher detection rate of fibers that we observed in G₂ and G₃; however, the exact mechanism of transfer of fibrous MPs in this case remains to be explored.

Although color distributions varied inconsistently in each group, blue was the most dominant color (59.59% of all MPs), scoring 64.71%, 46.67%, and 66.67% in G₁, G₂, and G₃, respectively. These findings match the high detection frequency and high amount of this MP color in the seawater and other squids (Zhang et al., 2019; Daniel et al., 2021; Zhang et al., 2022). The other colors of identified MPs were black, red, yellow, and MP in transparent film form (Figure 4).

Up to eleven polymer types were determined (Supplementary Figure S1). In all samples, polyethylene terephthalate (PET) was identified most frequently at 31.82% and reached 35.29%, 40.00%, and 16.67% in G₁, G₂, and G₃, respectively. PET is employed primarily as a textile, with applications in clothing, ropes, and fishing gears (Šaravanja et al., 2022). The other frequently polymers were cellophane (CP, 18.18%) and polystyrene (PS, 11.36%), and the remaining polymer accounted for less than 10.00% of the MPs detected (Figure 5). These polymers are ubiquitous in the marine environment (Alomar and Deudero, 2017; Li et al., 2019; Liu et al., 2020). PET (1.34 g/cm³), CP (1.42 g/cm³), and PS (1.05 g/cm³) have a higher density than seawater (1.025 g/cm³) and tend to sink into deeper water layers (Woodall et al., 2014), making themselves available to organisms living in these areas. D. gigas spends the vast majority of its time in the deep-sea hypoxic environment may be the cause for the high proportion of these high-density MPs in our study (Stewart et al., 2013). D. gigas is also considered highly migratory, undertake ontogenetic migration between the continental shelf and the open ocean (Gilly et al., 2006; Stewart et al., 2013). They can thus act as important significant bioindicators of MP contamination in a vast three-dimensional space. However, low-density polymers (e.g., polypropylene (PP), 0.90–0.92 g/cm³; polydimethylsiloxane (PDMS), 0.98 g/cm³; and styrene-butadiene rubber (SBR), 0.94 g/cm³), were also found in the D. gigas (Figure 5), possibly because of biofouling and subsequent vertical transport (Kooi et al., 2017; Hipfner et al., 2018; Liu et al., 2020). Interestingly, the low-density polymers were only detected in D. gigas from G₂ and G₃, which were far from the coast than G₁ (Figure 1). Possibly, offshore Ekman transport off Peru could move low-density polymer MPs to relatively farther offshore, and D. gigas feeding in the nearshore waters (i.e., G₁) might be exposed to more high-density polymers than in offshore waters (i.e., G₂ and G₂) (Thiel et al., 2007; Ory et al., 2018). It is noteworthy that the distribution of polymers in seawater of our study area has not yet been published, further efforts are needed to conclude the potential relationship between microplastic transport and Ekman dynamics.

Regarding wild marine organisms, there is currently no standardized method to monitor the risk of MPs, while MP abundance is a useful indicator to assess the potential risks of MPs (Xu et al., 2018; Kabir et al., 2021).

Based on the number of MPs per individual, the PLI values for sampling groups were 0.66 ± 0.77, 0.57 ± 0.61, and 0.75 ± 0.76, respectively. For the number of MPs per Gram of stomach weight, the PLI values were 1.04 ± 1.24, 1.31 ± 1.49, and 1.57 ± 1.77, respectively. No difference in PLI values was found among the sampling groups (Kruskal-Wallis, items/individual: χ² = 0.54, p = 0.76; items/g: χ² = 0.57, p = 0.75). These values indicated that all individuals had a very low risk in the study area (Xu et al., 2018).

Overall, this study is the first record of the intraspecific variation in MP contamination levels in pelagic squid from oceanic habitats and also provides an preliminary examination of the risk assessment of MPs. Spatial diversity of MP shape and polymer type was found. The pollution risk assessment showed that all D. gigas were at low risk of pollution. The site-specific MP contaminants may be used to facilitate priority pollution monitoring. The pollution risk assessment provided insights into pollution and a basis for future comprehensive environmental and human health risk assessments in the context of increased plastic pollution from pelagic squid.