Comparison of an In Situ Imaging Device and Net-Based Method to Study Mesozooplankton Communities in an Oligotrophic System

Abstract

In the past several years, the capabilities of optical tools and in situ imaging devices have greatly expanded and are now revolutionizing the field of plankton research. These tools have facilitated the discovery of new plankton and enhanced the understanding of populations of fragile and gelatinous zooplankton. Imaging devices are becoming more accessible and regularly deployed on oceanographic studies and monitoring efforts. However, despite the increasing use of these tools, there are few studies which offer direct comparisons between in situ imaging devices and traditional-net based methods, especially in open-ocean, oligotrophic systems where plankton are sparser and less intensively sampled. This study compares estimates of mesozooplankton abundance calculated by net-tows and an Underwater Vision Profiler 5 (UVP5HD-DEEP) imaging system. Net tows were conducted with a Multiple Opening and Closing Nets with Environmental Sensing System (MOCNESS) device equipped with 153µm mesh. In total, four tows, each sampling eight distinct depth bins, were conducted aboard two cruises in the Sargasso Sea. Along each cruise, in situ images were collected using an Underwater Vison Profiler 5 (UVP5HD-DEEP). Using these methods, we estimated abundance of different mesozooplankton groups (>0.5 mm). Using established biovolume-biomass conversions, we also estimated the dry mass of certain zooplankton taxa. Furthermore, we address two methods for calculating density and biomass concentration from UVP data. Estimates of mesozooplankton abundance and biomass concentration were generally higher from MOCNESS methods than the UVP estimates across all taxa. It was found that there is not a reliable relationship between UVP estimates and MOCNESS estimates when directly comparing similar depth bins. Nonetheless, when integrating density and biomass concentrations throughout the water column, estimates are not significantly different between the methodology. This study addresses several important considerations for using in situ imaging tools and how to reconcile findings with traditional net-based methods.

Size and transparency influence diel vertical migration patterns in copepods

“…In situ images of plankton were acquired using an Underwater Vision Profiler 5 (UVP5) (Picheral et al 2010). The original sampling methodology and instrument specification followed details described in Barth and Stone (2022). The UVP was attached to the Conductivity‐Temperature‐Depth profiling rosette (CTD) and deployed regularly on cruises to the Sargasso Sea from June 2019 to December 2021.…”

“…In this study, we investigated general trends in DVM by pooling together casts across multiple cruises. This approach is necessitated by the small sampling volume of the UVP (1.1 liters per image) and low abundance of plankton which requires aggregation of data to resolve trends ( see details in Barth and Stone 2022). Although there was minor variation between cruises (Supplementary Fig.…”

“…The UVP records images of large particles (> 600 μ m equivalent spherical diameter [ESD]). However, living particles are not reliably identifiable below 900 μ m (Barth and Stone 2022). All recorded images were processed using Zooprocess (Gorsky et al 2010), which provides several metrics related to size, gray value, and shape complexity.…”

“…This large variation was expected. There can be considerable variation between UVP estimates of zooplankton abundance (Barth and Stone 2022). In addition, in this study we pooled casts across multiple seasons.…”

Deep focus-extended darkfield imaging for in situ observation of marine plankton

“…Based on our experience in IPP nearshore deployment, this will result in a total water volume enlargement from 388.8L to 2592L per day at an imaging frame rate of 3FPS. This is expected to further fill the gap in seawater sampling throughput and plankton quantification between the traditional methods and the in situ imagers (Barth and Stone, 2022;Le et al, 2022).…”