A multi-method assessment of pelagic communities in the remote eastern Pacific Ocean

Characterizing the pelagic habitats of open-ocean ecosystems is a challenging task. These habitats often lie far from land and are expensive to study using conventional ship-based surveys. In addition, variable currents and winds make them dynamic in space and time posing further constraints for ecological studies. The offshore eastern Pacific Ocean region remains largely understudied despite a growing interest in deep-seabed polymetallic nodule mining across much of this area (Lusty and Murton, 2018; Drazen et al., 2020). The Eastern Tropical Pacific has one of the most intense oxygen minimum zones (OMZs) in the open ocean (Paulmier and Ruiz-Pino, 2009). Extending westward to the waters south of Hawai‘i, this extreme hypoxia is believed to exert a strong influence on the diel vertical migrations (DVMs) and community composition of micronekton and zooplankton (Wishner et al., 2013; Sutton et al., 2017; Perelman et al., 2021). However, pelagic communities have rarely been sampled across this expansive and remote region, and only a handful of trawl or bioacoustic studies exist (Clarke, 1987; Irigoien et al., 2014; Maas et al., 2014; Klevjer et al., 2016; Perelman et al., 2021; 2023).

Micronekton communities of open-ocean ecosystems, which are comprised of small (<20 cm), mid-trophic fish and invertebrates, are typically studied using active acoustics, net sampling, optical surveys, and more recently eDNA. Active acoustic techniques are valuable tools for assessing the behavior and vertical migration patterns of pelagic assemblages (e.g., Benoit-Bird and Lawson, 2016; Klevjer et al., 2016). Through the identification and characterization of sound scattering layers (aggregations of pelagic fauna observed using echo sounders), one can observe the depth and strength of vertical migration and changes in backscatter intensity as indicators of changes in micronekton and zooplankton composition or biomass. This method often allows for broader and more extensive surveys than physical sampling, which can be limited due to cost, equipment availability, sample processing time, and accessibility.

Stand-alone acoustic data can be difficult to interpret because backscatter does not easily translate to organism size, abundance, or species composition (Horne, 2000), especially for narrowband surveys. Generally, an organism with a gas inclusion (e.g., gas-bladdered fish and siphonophores) will scatter more sound than one without because the density contrast between a gas and fluid is far greater than that between fluid and body tissue (Simmonds and MacLennan, 2005). Such an organism would be considered resonant when it has a considerably amplified acoustic signal, though resonance depends strongly on size, frequency, and depth (Davison et al., 2015b; Bassett et al., 2020; Escobar-Flores et al., 2020). Given the complexities of interpreting acoustic data, combining observations from several sampling techniques is very useful to providing a more thorough understanding of pelagic communities.

Trawl sampling with nets enables the evaluation of species composition of pelagic fauna (Sutton et al., 2010; Olivar et al., 2012). Trawls are often combined with acoustic surveys (e.g., De Robertis et al., 2019; Escobar-Flores et al., 2019) to allow for identification and estimation of abundance and biomass for acoustically observed organisms. Studies of micronekton assemblages and their spatial distributions have used this combined trawl-acoustics approach (e.g., Escobar-Flores et al., 2022). Changes in micronekton abundance and vertical distribution have been found responsible for variation in acoustic backscatter (Boswell et al., 2020), while in other cases, backscatter differences have been attributed to changes in community composition (e.g., Annasawmy et al., 2019; Dornan et al., 2019). Concurrent sampling with hull-mounted echo sounders and trawls does rely on the assumption that the communities being sampled by each gear type are the same. Avoidance of nets by highly mobile fauna causes all net sampling techniques to be selective in what they catch (Kaartvedt et al., 2012; Sutton, 2013), and gelatinous organisms are easily damaged or extruded and therefore typically underrepresented in nets (Choy et al., 2017; Hetherington et al., 2022). Despite these biases, trawl sampling can add significantly to our interpretations of acoustic surveys and add a complementary perspective.

Video surveys from submersibles or remotely operated vehicles (ROVs) offer a method for observing the more fragile gelatinous organisms destroyed by trawls (Youngbluth et al., 2008; Raskoff et al., 2010). ROVs also provide a different perspective of fish and other taxa. Such surveys are non-destructive and allow for in-situ observations of feeding and swimming behaviors (Robison, 2004; Choy et al., 2017). Like nets, ROVs are likely subject to avoidance (as well as attraction) by highly mobile organisms, as well as organisms sensitive to light and noise (Widder et al., 2005). Nonetheless, when sampling tools such as acoustics, trawling, and ROVs are implemented together, they can offer a more holistic perspective of community distributions and dynamics in pelagic ecosystems. Due largely to costs and logistics, multiple techniques are rarely used concurrently and evaluated together despite the likely advantages when attempting to characterize the faunal distributions of poorly studied regions (e.g., Escobar-Flores et al., 2022).

This research builds from previous acoustic observations to provide a greater understanding of pelagic community dynamics in the remote eastern Pacific Ocean within a contracted mining exploration area. Here, we assess the distributions of backscatter, abundance and biomass, and broad community composition from active acoustics, trawl surveys using a multiple opening/closing net environmental sensing system (MOCNESS), and ROV footage, and explore the similarities and differences between the information they portray. We highlight the potential influence of the OMZ and seasonal variability on micronekton dynamics in this location, and the different perspectives provided by each sampling approach. The intent of this research is to compare sampling methodologies for future baseline assessements and monitoring efforts, whether in the context of mining or other changing ocean conditions.

All sampling occurred during two dedicated pelagic environmental baseline surveys in the contract mining exploration area NORI-D (200 km × 100 km), located in the eastern Pacific Ocean (Figure 1a). This area of the eastern Pacific Ocean experiences regular, seasonal anticyclonic eddies and equatorial currents that influence the vertical distribution of micronekton (Perelman et al., 2023). Mesoscale activity is frequent in this region between October and July (Palacios and Bograd, 2005), with anticyclonic eddies that could influence currents nearly down to the seafloor (Aleynik et al., 2017) and affect the distribution of biological communities and mining activities. The sampling expeditions took place during the spring (March–April) and fall (October–November) of 2021 and targeted sites relevant to future mining plans. In this study, we focused on a site near the southwest end of NORI-D where mining is expected to occur. The seafloor depth in this region is >4000 m, and no benthic features extend upward into the upper 1000 m where pelagic sampling occurred.

Active acoustic data were collected using Saildrone uncrewed surface vehicles (USV) during two surveys in March–April and October–November 2021. The USVs were mounted with Simrad WBT Mini (EK80) fisheries echo sounders with ES38-18/200-18C transducers (2 m depth). Data were collected in transects in continuous wave mode at 38 and 200 kHz (500 W/250 W power, 1024 μs pulse duration, 2.25s ping interval) from the surface to 1000 m and 200 m depth, respectively. We focused primarily on 38 kHz backscatter as sufficient acoustic energy penetrates to the depths of most trawl sampling. Prior to each survey, the echo sounders were calibrated, following Demer et al. (2015), with a 38.1 mm tungsten carbide sphere. Survey speeds averaged 1–2 knots, and the number of days spent within the survey site varied between 4–6 days due to strong currents and variable wind conditions.

Upon completion of each survey, we analyzed acoustic data in ESP3, an open-source fisheries acoustics data processing software (Ladroit et al., 2020) developed at the National Institute of Water and Atmospheric Research (NIWA, New Zealand). We used the methods of Francois and Garrison (1982) to calculate sound speed and signal absorption, removed bad pings and dropouts due to surface aeration or internal instrument noise through ESP algorithms and visual scrutiny of echograms, and implemented the ESP3 background noise removal algorithm (De Robertis and Higginbottom, 2007) with a signal-to-noise threshold of 3 dB for 38 kHz and 2 dB for 200 kHz. The upper 10 m of data were excluded from the analysis to avoid interference from surface aeration. We then categorized raw acoustic files as either day or night (excluding ±2 h around sunrise and sunset to avoid migration signals) and echo-integrated 38 kHz area backscatter (s_a) in 50 m deep × 1 km long bins. The s_a profiles (0–1000 m) were averaged for each day and night per depth bin. Finally, we evaluated the frequency response (Escobar-Flores et al., 2019) of shallow daytime scattering layers (<100 m) that were captured by both 38 and 200 kHz backscatter to hypothesize the types of scatterers likely present (i.e., fluid-like versus gas-bearing organisms).

Shipboard biological sampling was conducted aboard the M/V Maersk Launcher simultaneously with Saildrone acoustic surveys. Using a 10 m² MOCNESS (Wiebe et al., 1985) equipped with multiple 3 mm mesh nets, we performed three daytime and three nighttime tows within NORI-D during each seasonal survey. The first net was towed open obliquely from the surface down to depth, and each of the subsequent nets sampled specific depth intervals while ascending (Table 1). The intervals were selected based on OMZ boundaries (Figure 1b) identified from CTD casts and preliminary acoustic backscatter from the Saildrone: 1000–700 m for the lower oxycline, 700–450 m for the OMZ core, 450–90 m (spring) or 70 m (fall) for strong DVM based on Saildrone acoustics, and 90 m (spring) or 70 m (fall) to the surface for epipelagic. Because oxygen availability is a strong driver of vertical distributions in OMZ regions (Maas et al., 2014; Wishner et al., 2018), the two shallowest depth strata differed between the spring and fall surveys by about 20 m to account for slight differences in the upper oxycline depth (Figure 1b). We focus here on depth strata within the upper 1000 m that fall within the depth range of the acoustic data; the full depth range of trawl data is analyzed in a separate paper (Assad et al., in review). Abundance and biomass were standardized by volume and depth filtered and are presented per square meter of surface ocean. Immediately upon completion of each trawl, samples were sorted to the taxonomic level of family or genus at sea and stored in 10% formalin or 95% ethanol for further identification in the laboratory. Gelatinous material was excluded from quantitative analyses as trawl-induced damage made identifying and quantifying these organisms difficult. Small zooplankton (e.g., copepods and pteropods) were also excluded as these were not sampled quantitatively by the 3 mm mesh nor by the 38 kHz acoustic data.

Mesopelagic fish were subsampled from the oblique tows for evaluating the presence and condition of a swimbladder. Standard length (SL) and wet weight of fish (WW, using a motion-compensated scale) were recorded immediately post-capture at sea, and we sought to evaluate the full observed size distribution for each taxon. Following the methods of Dornan et al. (2019), fish were dissected under a dissecting microscope and examined for the presence or absence of a swimbladder. If present, the swimbladder was removed and gently ruptured in a container of seawater to assess whether it was gas-filled. Fish were then categorized as having no swimbladder, a gas-filled swimbladder, or a non-gas (i.e., lipid) filled swimbladder. If the swimbladder was visibly ruptured, it was assumed to have undergone barotrauma and characterized as gas-filled. Only fish identified to have a gas-filled swimbladder (including fish with ruptured swimbladders) were considered to be gas-bearing (GB fish). After the fish were classified according to their swimbladder type, they were preserved in 10% formalin. Further species identification took place in the laboratory. Swimbladder dissection data can be found in Table S1.

Day and night ROV video surveys were conducted by the ROV Odysseus (Pelagic Research Services) during the fall sampling occasion. Comprehensive information from ROV surveys will be presented in a separate paper; here we focus on video surveys between 0 and 1000 m. The main video camera was a pan-tilt-unit-mounted Mini Zeus 4K (Insite Pacific, Inc.) with a 1/2.5 inch Exmor R CMOS sensor and a 20× Optical Zoom lens (4.4 mm to 88.4 mm). The horizontal and vertical angles of view in water were 124.1° and 93.3°, respectively. Additionally, a pair of stereo IP Multi SeaCam cameras (model IPMSC-3105, DEEPSEA Power and Light) were mounted with their centers 100 mm apart on a fixed bracket and facing forward. The video from these cameras was streamed to the ship and recorded as QuickTime.mov files. Post-cruise re-annotation was done using video annotation plugins to Squidle+ (SquidVidPro and SqCapture2, GreyBits Engineering) running on a GreyBitsBox system (Greybits Engineering). Organisms were identified to the lowest taxonomic level possible from this video footage and depth of observations were recorded. These surveys provide observational support for the vertical distributions of crustaceans, gelatinous organisms, and fish. Horizontal and vertical (“oblique”) video transect surveys were conducted with the ROV; however, due to inconsistencies in the speed of the vehicle and the duration spent at each depth, we focus here on relative abundances rather than absolute. For schooling fish that followed the ROV (i.e., sternoptychids, phosichthyids, and myctophids), we used the shallowest starting descent depth and the deepest starting ascent depth as the minimum and maximum depths, respectively, to account for the potential range increase introduced by this ROV-following behavior. To ensure that fish were not double counted, individuals were only counted as they entered the field of view from the bottom (descent) or top (ascent) of the frame.

Although acoustic, trawl, and ROV surveys were all performed during the same sampling occasions, the data were only roughly concurrent in space and time because not all operations could occur simultaneously. Therefore, to evaluate micronekton dynamics across these datasets we used daytime and nighttime averages within each of the two sampling occasions. We evaluated acoustic backscatter, MOCNESS trawl abundance and biomass, and broad taxonomic composition from trawls and ROV surveys, as described in the sections above, to evaluate the similarities and differences in observed community dynamics across depth strata. ROV data were used only for qualitative comparisons with trawl and acoustic data as the oblique sampling was variable and unsteady.

Total area backscatter and trawl abundance and biomass were compared between seasonal sampling occasions using Kruskal-Wallis rank sum tests. To evaluate vertical distribution differences between sampling occasions, we used permutational multivariate analyses of variance (PERMANOVA; “vegan” package in R; Anderson, 2001). For these analyses, backscatter, abundance, and biomass within each depth stratum (0–70/90 m, 70/90–450 m, 450–700 m, and 700–1000 m) were scaled to proportions of total daily/nightly values and Euclidean distances between these standardized values were used. Because PERMANOVA tests for trawl data had low statistical power with only three tows per day/night for a given sampling occasion, we evaluated each sampling occasion in relative terms.

The 38 kHz data indicated the consistent presence of distinct daytime mesopelagic scattering layers between around 250 m and 500 m depth throughout the spring and fall surveys, with the strongest layers (>9 dB re 1 m² km^–2) at around 300–400 m (Figure 2). Surface scattering layers were also present in the upper 100 m during the day (5–6 dB re 1 m² km^–2) and were much stronger at night (>14 dB re 1 m² km^–2). Mesopelagic scattering layers were highly migratory, shifting their depths from 300–600 m to shallower than 100 m between each day and night, respectively. Thin nighttime layers formed at night around 200–250 m during the fall survey (Figure 2b). Diffuse nonmigratory scattering layers were present between 200 m and 400 m during the spring surveys (Figure 2a). Deeper, weak nonmigratory layers were sometimes visible around 800 m, particularly during the fall survey (Figure 2b). Further, we observed several strong signals of early downward nighttime migration during the fall survey, particularly when the Saildrone was caught in a strong eastward-flowing current (primarily the North Equatorial Countercurrent; Figure 2d).

We evaluated the frequency responses of daytime scattering layers in the upper 200 m, as these layers were shallow enough to be captured by both 38 and 200 kHz frequencies (Figure 3). Nearly all shallow daytime layers had a stronger response and greater thicknesses at 38 kHz than at 200 kHz. Occasional thin layers below the main shallow scattering layer were also observed; however, these layers were stronger at 200 kHz than at 38 kHz (e.g., Figure 3c).

A total of 22,732 individual micronekton specimens were collected from the day and night MOCNESS trawls between the two sampling occasions (excluding the oblique net tows). During the spring survey, total micronekton abundance was highest in the 90–450 m depth stratum followed by the 700–1000 m stratum, but during the fall surveys abundance was highest in the 700–1000 m stratum (Figure 4a). Micronekton biomass was always highest in the 700–1000 m stratum (Figure 4b).

The relative abundances and biomass of dominant taxa are presented in Figure 5a and 5b. Fish of the genus Cyclothone (bristlemouths) dominated abundance (ind. m^–2) at depths below 450 m, and largely appeared nonmigratory (i.e., their depths did not change between day and night) from trawl collections. Biomass was generally more evenly distributed across taxa at all depths. Other common nonmigratory taxa below 450 m included fish in the families Neoscopelidae (blackchins), Serrivomeridae (sawtooth eels), and Nemichthyidae (snipe eels), and several crustacean taxa (e.g., mysids, carideans). The dominant fish found in the middle (70/90–450 m; 450–700 m) and shallow (0–70/90 m) depth strata when considering both abundance and biomass were myctophids (lanternfish), melamphaids (ridgeheads), sternoptychids (hatchetfish; particularly in spring), and phosichthyids (lightfish; particularly in fall). Numerous migratory mesopelagic fish, mainly melamphaids and myctophids, were collected with crustaceans within the OMZ core (450–700 m) during the day, but most of these fish migrated above 450 m at night. However, larger adult melamphaids were only caught within and below the OMZ at night and appeared to be nonmigratory. During the fall survey, we additionally caught small and juvenile melamphaids in the 700–1000 m depth stratum in similar abundances during daytime and nighttime trawls (i.e., these appeared nonmigratory). We further observed high abundances of euphausiids (krill) and juvenile sergestids (decapod shrimps) during the spring trawl surveys in the 90–450 m stratum during both daytime and nighttime trawls, with some of these organisms migrating shallower than 90 m at night.

In total, 176 fish were dissected for swimbladder assessments. These evaluations revealed that the presence and condition of this organ varied widely between mesopelagic fish taxa (Table S1). Greater than 90% of Cyclothone (n = 23) contained a regressed swimbladder comprised of oil-like droplets and no gas. More than 90% of sternoptychids (n = 24) and 80% of phosichthyids (n = 11) contained a gas-filled swimbladder. About 55% of melamphaids (n = 29) contained a gas-filled swimbladder, which largely occurred in small and juvenile specimens with the exception of Poromitra sp. (median SL = 3.7cm, median WW = 0.8 g), while larger individuals predominantly had lipid-filled swimbladders (median SL = 5.8 cm, median WW = 3.5 g). Such ontogenetic shifts in swimbladder content from entirely gas as juveniles to entirely lipid as adults have been observed in other families (Dornan et al., 2019). As such, small/juvenile fish in this group (WW = <2 g; 3^rd quartile of gas-bearing melamphaids excluding outlier) were characterized as GB fish and larger/adults as non-GB fish. Roughly 83% of myctophids (n = 54) contained a gas-filled swimbladder, with all others containing a lipid-filled swimbladder. The myctophid genus Lampanyctus showed a trend toward lipid-filled swimbladders in larger individuals.

Abundances and biomasses of GB fish were quite variable throughout the surveys. The highest spring daytime abundances of GB fish varied between the middle depth strata (90–450 m and 450–700 m), while the highest spring daytime GB fish biomass varied between the deepest depth strata (450–700 m and 700–1000 m; Figure 4). Spring nighttime GB fish abundances and biomass were greatest between 90 m and 450 m. In contrast, fall GB fish abundances and biomass were always greatest between 700 m and 1000 m, followed by the shallower depth strata (0–70 m and 70–450 m) for daytime and nighttime abundances and nighttime biomass (Figure 4). The size distribution of GB fish varied across depth strata, and we often caught larger GB fish at deeper depths, including species with an ontogenetic shift in gas content, particularly during the fall (Figure S1). Acoustic backscatter was often strongest at depths with low mean fish sizes.

Abundance and biomass profiles for crustaceans and cephalopods are presented in the supplementary materials (Figures S2 and S3); these taxa are not thought to have contributed significantly to 38 kHz backscatter in our surveys. During the spring trawl surveys, crustacean abundance and biomass were highest in the 90–450 m depth stratum, while during fall surveys they were often greater between 700 m and 1000 m (Figure S2). Cephalopod abundance was highest between 70/90 m and 450 m, particularly during the spring trawl surveys, while cephalopod biomass was always highest in the 700–1000 m depth stratum (Figure S3).

The relative abundances of taxa observed during oblique ROV transects are presented in Figure 5c. Across all depths, gelatinous taxa and other invertebrates (e.g., polychaetes and mollusks) comprised a substantial proportion of all observations, with the greatest proportions observed within the 70–450 m and 700–1000 m strata. During the daytime, gelatinous taxa, crustaceans, fish, and other invertebrates were observed across all depth strata. In the shallow depth stratum (0–70 m), fish observations were dominated by scombrids during the day and phosichthyids at night, with carangids and coryphaenids observed at both times of day. The presence of these epipelagic fish was very likely due to the vessel being stationary and acting as a fish aggregating device. Gelatinous taxa and other invertebrate observations were dominated by salps (tunicate) and solmarisids during the day in the shallow strata, though no single taxon was dominant at night. In the 70–450 m depth stratum, observations of gelatinous taxa were dominated by oikopleurids during both daytime and nighttime transects, crustacean observations were dominated by copepods during both times of day, and fish observations were dominated by sternoptychids and phosichthyids during the daytime. Between 450 m and 700 m at both times of day, fish were largely comprised of melamphaids and Cyclothone while gelatinous taxa and other invertebrates were comprised largely of Medusozoa, oikopleurids, and lopadorhynchids. Decapods comprised most crustaceans during daytime transects within this depth stratum. Finally, observations in the 700–1000 m depth stratum were most heavily dominated by the fish Cyclothone, decapods and copepods (crustaceans), and siphonophores, oikopleurids, Medusozoa, chaetognaths, and lopadorrynchids (gelatinous taxa and other invertebrates).

We further evaluated the depth range of five commonly trawl-collected fish taxa as observed from the fall ROV video surveys (11 dives; Figure 6): sternoptychids (38 observations), Scopelengys tristis (family Neoscopelidae; 27 observations), myctophids (12 observations), melamphaids (92 observations), and phosichthyids (14 observations). Sternoptychids had broad depth ranges, spanning most of the mesopelagic (about 150–850 m) at both times of day. Melamphaids likewise had broad daytime and nighttime ranges but were observed all the way down to 1000 m and were observed 100 m shallower at night compared to daytime. The observed depth ranges of these two families spanned the lower oxycline and OMZ core. Phosichthyids had a much shallower and narrower depth range, being observed only above the OMZ core (<350 m) and were observed about 100 m shallower at night. Scopelengys tristis was always observed below about 650 m, with a slightly narrower nighttime range down to about 850 m. Myctophids were only observed below 575 m during the day but spanned most of the water column during the nighttime. Except for sternoptychids, all fish taxa exhibited at least some diel shallowing in their observed vertical distribution from ROV surveys.

Both acoustic backscatter and trawl-caught micronekton densities exhibited seasonal differences (Figure 7). The median value for total (all depths combined) backscatter, trawl abundance, and trawl biomass were all greater during the spring sampling occasion compared to the fall, though these differences were only significant for trawl data (p < 0.01 and p < 0.05; Figure 7b and 7c, respectively). Similarly, the vertical distributions of backscatter, abundance, and biomass differed between seasonal sampling occasions. Shifts in vertical distribution were driven by a deeper daytime shallow scattering layer and slightly narrower daytime deep scattering layer (PERMANOVA: p = 0.003, pseudo-F = 9.4, R² = 0.51), as well as a deeper nighttime shallow scattering layer (p = 0.004, pseudo-F = 279.2, R² = 0.97) during the spring surveys compared to fall. These differences in backscatter generally align with the spring surveys having considerably more micronekton within the 90–450 m trawl depth stratum compared to fall, which was driven primarily by higher densities of small crustaceans (Figures 4 and 5). Although daytime and nighttime vertical distributions of total abundance and biomass differed between sampling occasions, PERMANOVA results ultimately had weak statistical power due to the limited number of trawls in each group.

In comparison to trawl-caught micronekton, the ROV video surveys provided a fundamentally different representation of pelagic community composition (Figure 5). Most notably, the ROV surveys highlight the abundance and biodiversity of gelatinous taxa that were largely missed or destroyed by trawls across all depth strata. Additionally, whereas the trawls had a high proportion of crustaceans (largely euphausiids) in the upper depth stratum during the fall sampling occasion, crustaceans comprised a much smaller proportion of the community observed from ROV surveys. Despite these strong differences, ROV observations revealed several similarities to trawl catches, including notable proportions of fish (largely Cyclothone and melamphaids) within the OMZ core (450–700 m) and the presence of phosichthyid fish in the 0–70 m depth strata at night. The trawl and ROV observations revealed the presence of GB fish and physonect siphonophores (ROV only) between 70 m and 450 m. These organisms are potential contributors to 38 kHz acoustic scattering layers observed in the surveys.

We used a combination of water column sampling techniques to assess the vertical distribution and DVM behaviors of micronekton within the upper 1000 m of an OMZ-influenced area across two seasonal sampling occasions. By combining acoustic backscatter, abundance, biomass, faunal composition from MOCNESS trawling data, and ROV video observations, we provide the first comprehensive, multi-method assessment of pelagic community structure in a remote part of the eastern Pacific Ocean. These various approaches provided unique perspectives of the micronekton community and highlight the importance of integrating information from multiple sampling techniques to gain a holistic understanding of pelagic ecosystems.

Acoustic surveys conducted by Saildrone USVs provided continuous information on scattering layer vertical migration behaviors from the surface to 1000 m. Trawl and ROV data complemented our acoustic surveys by offering clues as to which micronekton taxa were responsible for the backscatter at 38 kHz. Myctophids, melamphaids, and phosichthyids (fall only) were likely contributors to the highly migratory deep scattering layers (DSLs) within NORI-D, as we observed consistent diel nighttime shallowing of these GB fish in both the trawl surveys and ROV observations (Figures 5 and 6). These taxa could all be strong acoustic targets at 38 kHz (e.g., Godø et al., 2009).

In addition to the main migrating DSLs, we commonly observed broad nonmigratory layers during the spring surveys between 200 m and 400 m (Figure 2a) that were present above the OMZ core (450–700 m; Figure 1b). These scattering layers may have been comprised of sternoptychids (GB fish), as they have been considered nonmigratory in some studies (Davison et al., 2015a) and we consistently captured them in the 70/90–450 m depth trawls during both day and night (Figure 5). However, sternoptychids may also have migrated within the 70/90–450 m depth strata because some studies have suggested they are limited migrators (shallowing 100–200 m; Kinzer and Schulz, 1988).

While we observed relatively high numbers of crustaceans (primarily euphausiids and sergestids) in the 70/90–450 m depth strata that matched peaks in acoustic backscatter, particularly during the spring surveys (Figures 5 and S2), these taxa are unlikely to have contributed to the daytime DSLs or nonmigratory scattering layers. These organisms are often grouped in the “fluid-like” gross anatomical class in acoustic studies (Stanton et al., 1994; 1996), and are weak targets at 38 kHz unless densely aggregated. The density of these 1–2 cm crustaceans required to produce significant backscatter at 38 kHz is orders of magnitude greater than we observed from MOCNESS trawls in this part of the remote eastern Pacific Ocean (Stanton et al., 1996). Further, the frequency responses of most shallow daytime scattering layers were stronger at 38 kHz compared to 200 kHz (Figure 3), suggesting that backscatter in these layers was driven by gas-bearing organisms. Secondary shallow scattering layers were occasionally detected with stronger responses at 200 kHz; these responses could be indicative either of gas-bearing organisms observed in the Rayleigh scattering regime at 38 kHz and in the resonance or geometric scattering regime at 200 kHz, or non-gaseous organisms (Greenlaw, 1979; Proud et al., 2019).

During the fall surveys, thin nighttime layers appeared around 200–250 m, perhaps consisting of DSL organisms performing limited migrations toward the surface (Figure 2b). These layers might have contained bregmacerotids (GB fish), as we observed similar abundances of these fish in the 90–450 m depth stratum during day and night trawls. Deep, weaker nonmigratory layers were also observed around 800 m during the fall acoustic surveys (Figure 2b). These layers might have consisted of small and juvenile melamphaids (GB fish) that were caught in much higher abundances in the 700–1000 m depth strata during the fall surveys relative to spring, and which had consistent daytime and nighttime relative abundances (i.e., no apparent migration) at these depths during the fall. These layers may also have consisted of larger, more mobile species that we were unable to catch with the MOCNESS due to net avoidance. While Cyclothone were always caught in this deep stratum at high abundances and have previously been found to occupy lower oxycline waters in the Eastern Tropical Pacific (Maas et al., 2014), these fish all appear to lack a gas-filled swimbladder and therefore did not contribute significantly to 38 kHz backscatter. If they had contributed, then deep, nonmigratory layers would be a consistent and prominent feature across all acoustic surveys. Physonect siphonophores may have also contributed to these deep nonmigratory layers as they were observed in the 700–1000 m depth stratum during both the daytime and nighttime fall ROV surveys (Figure 5c). However, whether siphonophores were important contributors to the deep nonmigratory layers here is not clear, as they were observed only sporadically. Finally, several strong, early (nighttime) DVM signals were apparent in the survey area (Figure 2d), and while which micronekton taxa might be involved in these migrations is unclear, such observations provide further insight into the variability of pelagic community migration behaviors in the eastern Pacific.

Broadly, our acoustic and trawl results were similar to the limited number of other studies across the eastern Pacific Ocean and showed similar seasonal trends. As we observed here, mesopelagic scattering layers have been found to be relatively shallow and exhibit strong DVM signals in and around the NORI-D area due to the strong OMZ present in this region (Klevjer et al., 2016; Perelman et al., 2021). As expected, these layers were stronger and shallower than those recently observed from Saildrone acoustic surveys further west (southeast of Hawai‘i) in an area with higher midwater oxygen and lower surface productivity (Perelman et al., 2023). Similarly, we found that mean integrated micronekton trawl abundances (10–50 ind. m^–2) and biomass (5–10 g m^–2) in the upper 1000 m were up to five (abundance) and two (biomass) times higher in NORI-D compared to previous surveys in more oligotrophic waters near Hawai‘i that used a similar net system to ours (7.7 m² Isaacs-Kidd Midwater Trawl with 4.75 mm mesh; Maynard et al., 1975).

Across sampling occasions, we observed significantly higher total abundance and biomass, and marginally higher total backscatter, during the spring surveys compared to fall (Figure 7a–7c). This pattern was likely due to seasonal reproduction and recruitment during the spring when productivity was highest (Fernández-Álamo and Färber-Lorda, 2006; Figure S4), as we observed a significant number of juvenile crustaceans and juvenile fish in the spring trawl surveys. The timing of species life history events could have played a role in these seasonal differences. For instance, some gas-bearing fish might shift ontogenetically to more lipid-filled swimbladders in the timespan between the two sampling occasions, which would lead to differences in backscatter. Higher oxygen availability in the upper 450 m during the spring may have also played a role in the higher observed numbers of micronekton (Figure 1b). The higher spring trawl values derive largely from the higher abundance and biomass observed within the 90–450 m depth stratum, though backscatter vertical distributions were more variable. Using depth-integrated metrics, both acoustic and trawl approaches showed the same broad patterns between sampling occasions.

We observed very different patterns in micronekton vertical distributions from individual survey techniques. Acoustic data during the spring and fall showed that most backscatter was above roughly 600 m, while trawl sampling suggested that there was significant abundance and biomass below 700 m in addition to high abundances from 70/90–450 m during the spring (Figure 4). These discrepancies largely arise from different gear selectivity among the sampling techniques. Non-GB fish (Cyclothone sp.) dominated abundance and contributed significantly to biomass below 700 m but were acoustically undetectable at 38 kHz due to their lack of a gas-filled swimbladder. Cyclothone are likely the most abundant vertebrates in the ocean (Nelson, 2006) and are important members of meso- and bathypelagic ecosystems, yet deeper-living, non-gas-bearing members of this genus may be completely overlooked by surface-based acoustic surveys. We observed relatively high micronekton abundances in the 70/90–450 m depth strata during the spring daytime trawl surveys that coincided with the depth of the daytime DSL (Figure 4). However, these high abundances were dominated by euphausiids that probably did not contribute significantly to 38 kHz backscatter.

Our trawl estimates of GB fish abundances and biomass were higher within the OMZ core (450–700 m) than they were within the strata containing the main daytime DSLs (70/90–450 m), particularly in spring. The variability between daytime DSL and GB fish depths might suggest that resonance played a role here, such that a fewer number of small GB fish were primary contributors to the DSL and that GB fish residing deeper were weaker targets likely in the geometric scattering regime. Small and juvenile GB fish might not need to be particularly abundant (though they often are) to be the dominant scatterers at a given depth, whereas biomass can be dominated by larger, weaker scattering species or adults (Cox et al., 2013; Davison et al., 2015a). Net avoidance also likely played a role in this discrepancy. Stronger light intensity allows more GB fish to avoid capture at shallower depths (e.g., Heino et al., 2011; Kaartvedt et al., 2012), and we observed numerous GB fish near the depths of daytime DSLs in ROV footage (Figure 6). Net avoidance by larger, more mobile GB fish (especially at shallower daytime depths) may have also influenced their observed size distribution across depths, as the GB fish we sampled were generally larger in deeper trawl samples (Figure S1).

During nighttime trawls, GB fish abundance and biomass were higher within the two shallowest depth strata compared to the OMZ core, and the main nighttime scattering layers (as well as daytime shallow scattering layers) fell within the upper 100 m and often overlapped the upper two trawl strata (Figure 4). Consequently, GB fish taxa captured within both shallow strata may have contributed to backscatter in surface layers. The shallow trawl strata were selected based on upper oxycline depths (Figure 1 and Table 1), which led to instances of surface scattering layers overlapping the boundary between the upper two trawl strata, limiting our ability to better identify which taxa contributed to these scattering layers. In future integrated assessments such as this one, selecting stratified trawl depths that allow for differentiation between the primary acoustic features would be ideal.

The discrepancies we observed between acoustic and trawl data are not uncommon. In the North Atlantic, acoustic estimates of mesopelagic fish abundance have been observed at two orders of magnitude greater than trawl abundance estimates, clearly due to trawl avoidance behaviors (Kaartvedt et al., 2012). Trawl capture efficiency, net retention characteristics, and fish behavior during capture have all been found to bias trawl sampling when related to acoustically estimated fish densities (Somerton et al., 2011). We did explore adjusting the trawl data to account for lower capture efficiencies of more mobile organisms (i.e., large fish) similarly to Davison et al. (2015a), but this effort did not significantly alter the vertical distributions of abundance and biomass. Attributing backscatter to specific taxa is further complicated in areas of high species diversity when evaluating mixed assemblages such as we observed here (Domokos, 2021).

Any single ecological survey method presents one perspective of a community with certain limitations or biases, and the approaches we used here are no exception. For our Saildrone active acoustic surveys, we were limited to only a single frequency that spans the 0–1000 m depth range and 38 kHz in particular is most sensitive to gas-bearing organisms like fish and siphonophores (Kloser et al., 2016; Proud et al., 2019). Higher frequencies would be necessary to better evaluate weakly scattering organisms (e.g., crustaceans, salps, Cyclothone sp., gastropods) throughout the water column (Stanton et al., 1996), but high frequency sound waves attenuate at shorter distances and would not provide the full depth range from a surface-mounted transducer. Thus, understanding the sensitivities and limitations of working with surface-based and single frequency acoustic data is important.

In terms of trawling, a limitation here is the inability to quantify gelatinous taxa as soft-bodied organisms are largely destroyed by the mesh nets. Removal of gelatinous material certainly reduced our biomass and abundance observations, and this bias may have been particularly great above 450 m where the nets captured larger quantities of gelatinous fragments indicating a robust community. The gelatinous community observed in fall ROV surveys comprised a substantial proportion of total observations above 450 m, including some physonect siphonophores observed within the depth range of daytime deep scattering layers that could be strong acoustic targets at 38 kHz (Proud et al., 2019). The perspectives provided by these video surveys enabled us to detect the size and diversity of this essential and robust component of the pelagic community. In contrast, ROVs can bias observations of more mobile organisms including fish. Due to lights and noise, fish have been observed to be attracted to or disturbed by an approaching vehicle (Ayma et al., 2016). Here, we observed DVM fish following the vehicle as it descended and ascended through the water column, which can skew their natural vertical distributions. While these complexities demonstrate the limitations of every sampling technique, they also highlight that each approach provides a unique and important perspective of pelagic communities.

Open-ocean ecosystems are intrinsically difficult to study, and pelagic communities of the remote eastern Pacific Ocean in particular remain minimally sampled despite an evolving deep-sea mining industry across this region (Drazen et al., 2020). Our results showed that a single survey approach is insufficient to characterize such dynamic assemblages. When limited sampling methods are available, caution should be taken in the interpretation of pelagic community structure and dynamics. We found that vertical distributions of acoustic backscatter were much shallower than those of trawl-estimated micronekton abundance and biomass, though each metric provided valuable information about community behaviors when integrated. Saildrone USVs could be a useful tool for remote acoustic surveys of pelagic fauna, but without sample collection to ground truth backscatter, knowing what is driving observed behavioral patterns is difficult, and the importance of deeper, acoustically cryptic yet high biomass assemblages may be missed. Here, we were able to use MOCNESS trawl and ROV video data to evaluate the diversity of pelagic communities and identify the taxa most likely responsible for observed scattering layer behaviors. Conversely, we were able to use acoustic observations to better understand the finer DVM patterns of fauna collected within very broad trawl and ROV strata. Both trawl and video footage greatly expanded perceived micronekton distributions suggested by surface-based acoustic profiles. Further, as previously documented, trawls miss many important gelatinous and fragile taxa such as siphonophores and medusae that are only appropriately surveyed with visual transects. Notably, these approaches highlighted the significant abundance and biomass within and below the OMZ core that was not apparent in 38 kHz backscatter collected from the surface.

While this work provides a case study of methods integration for pelagic sampling, several improvements could be made in future studies to better characterize pelagic communities. Targeted strength scattering models could be developed from trawl-sampled species composition to predict acoustic responses and quantify differences between trawl and acoustic sampling methods. Such an approach could identify additional biases in both trawl and acoustic sampling and highlight increased uncertainty associated with highly diverse ecosystems (Barbin et al., 2024). Additionally, sampling designs could be improved to enable more explicit and rigorous statistical comparisons between trawl, acoustic, and video methods. Emerging sampling techniques such as eDNA (Govindarajan et al., 2021\) could also be considered in future comparison studies to highlight broader perspectives of pelagic community diversity. Such approaches were conducted at our sampling site and are the focus of a forthcoming publication (Stedman-Ellis et al., in prep). Furthermore, other studies from this sampling program will present environmental data that can be used to evaluate the drivers of vertical distribution and community composition through space and time. More mining companies may begin midwater research soon as interest expands. The research presented here ultimately highlights the crucial importance of combining perspectives from multiple techniques when characterizing a pelagic habitat, especially for ecosystem baseline characterization and environmental monitoring in relation to industrial activities like deep-sea mining, offshore wind, and fishing.

Data files are available at https://github.com/jnperelm/multi_method_NORID.

The supplemental files for this article can be found as follows:

Supplemental material (docx)

We would like to thank everyone involved with the two oceanographic campaigns in NORI-D, including the crew of the Maersk Launcher and the entire science team. We thank Jesse van der Grient, Elizabeth Miller, Gina Selig, Andrés Salazar Estrada, Shelby Gunnels, Michael Dowd, Nicolas Storie, and Mario Kaluhiokalani for their contributions to MOCNESS operations and shipboard micronekton sorting. We also thank the MOCNESS technicians, Royhon Agostine, Mason Schettig, Jeff Martin, and Gray Lawson for their excellent and tireless support. We thank Pelagic Research Services, as well as Erik Thuesen and Tiffany Bachtel for conducting, leading, and managing ROV operations during the spring expedition. We would like to acknowledge Saildrone, Inc., and their entire operations team for remotely managing all acoustic data collection and ensuring a successful mission despite difficult ocean conditions. We additionally thank Sebastian Martinez, Samantha Rickle, Ande Westerhausen, and Quinn Moon for assistance with onshore micronekton identification and sample sorting, and Kyle Edwards for his statistical input to data analyses. We also thank Bruce Mundy for his input on mesopelagic fish identification.

Authors JNP, VEA, LAB, DJL, and JCD have received support from The Metals Company, Inc. (TMC) through its subsidiary Nauru Ocean Resources Inc. (NORI). NORI holds exploration rights to the NORI-D contract area in the CCZ regulated by the International Seabed Authority and sponsored by the government of Nauru. This is contribution TMC/NORI/D/011 and SOEST contribution #11885. JNP was additionally supported by the ARCS Foundation Honolulu Chapter and the Watumull Scholarship.

The authors declare that they have no conflicts of interest.

JNP and JCD designed the research. JNP, VEA, DJL, and LAB conducted the analyses. JNP, YL, PCE-F, and JCD contributed to survey planning and design and data interpretation. JNP wrote the first draft and all authors read and edited the paper. All authors approved the submission of this manuscript.

How to cite this article: Perelman, JN, Assad, VE, Ladroit, Y, Escobar-Flores, PC, Lindsay, DJ, Bergman, LA, Drazen, JC. 2025. A multi-method assessment of pelagic communities in the remote eastern Pacific Ocean. Elementa: Science of the Anthropocene 13(1). DOI: https://doi.org/10.1525/elementa.2024.00037

Domain Editor-in-Chief: Jody W. Deming, University of Washington, Seattle, WA, USA

Guest Editor: Jeroen Ingels, National Institute of Water and Atmospheric Research (NIWA), Wellington, New Zealand

Knowledge Domain: Ocean Science

Part of an Elementa Special Feature: Deep-Sea Mining of Polymetallic Nodules: Environmental Baselines and Mining Impacts from the Surface to the Seafloor