The systematic application of x-ray micro-computed tomography (mu CT) and conventional thin-section micromorphology to unconsolidated sediments remains challenging, as existing sample preparation methods are largely limited to thin-section production. We present an integrated mu CT and thin-section method based on a newly designed 3D-printed subsampler that (1) enables precise extraction of areas of interest from soft sediment cores, (2) stabilizes unconsolidated wet sediments during mu CT scanning, and (3) allows dehydration and resin impregnation within the subsampler, thereby minimizing sediment disturbance prior to thin-section preparation. The method was applied to sediment cores from lakes in Alaska and Chile. Two subsamples (8.0 & times; 1.5 & times; 1.5 cm; L & times; W & times; H), representing distinct depositional environments, were analyzed using high-resolution mu CT and thin-section micromorphology. Thin-section analysis, although limited to two dimensions, provides highly detailed characterization of sediment texture and composition at the grain scale. mu CT yields complementary three-dimensional (3D) information on the geometry, distribution, and orientation of sedimentary features, enabling quantitative analysis at resolutions comparable to those of thin sections. A key advantage of this approach is the direct comparability of datasets obtained from both techniques. This integrated mu CT and thin-section method enables high-resolution 3D analysis of sediment microstructures, providing new insights into sedimentary processes across a wide range of depositional environments and allowing quantitative comparisons among sedimentological studies.
Increasing evidences show that fauna living in deep-sea ecosystems exhibit various complex behaviors that remain understudied. Although several in situ observatories have been set up around the globe, the use of their imagery data to gain insights into animal behavior across temporal scales remains constrained by the labor-intensive nature of the analyses. Here, we developed an automated deep-learning-based pipeline with multi-target tracking. Our pipeline integrates YOLOv8 object detection with category-specific approaches to characterize spatial-temporal behavior patterns (i.e., mobility and trajectory). This pipeline was applied to video imagery from the Lucky Strike hydrothermal vent field, Mid-Atlantic Ridge as a case study. We tailored tracking methods to three functional mobility groups: Sedentary, Simple Motile, and Complex Motile, represented by the mussel Bathymodiolus azoricus, the shrimp Mirocaris fortunata, and the crab Segonzacia mesatlantica, respectively. Tracking performance was evaluated using standardized multi-object tracking metrics: the Hungarian algorithm showed strong manual agreement for Sedentary taxa (r = 0.792), BoTSORT excelled for Simple Motile (HOTA = 0.956, 0.012% identity switches), and DeepSORT achieved best HOTA = 0.727 for Complex Motile. Our results reveal: (1) daily displacement of the mussels, (2) a potential semi-lunar rhythmic pattern in the movement of the shrimps (14.76-day periodicity) modulated by the proximity to vent emissions and seasonal factors, and (3) acute stress responses in the crabs linked to localized thermal exposure to hot vent fluids. Our pipeline provides a scalable detection-tracking-behavior analysis framework, enabling statistical identification of infra-monthly behavioral patterns that are difficult to quantify through manual annotations alone. As a result, it can be readily adapted to other deep-sea ecosystems for standardized multi-species behavioral monitoring.
Accurate length data underpin many ecological and physiological analyses, from assessing population size structure to parameterizing biomass and bioenergetic models. Stereo-baited remote underwater video systems (stereo-BRUVs) provide a non-intrusive means of collecting these data in situ, supporting management and conservation of motile marine assemblages. These systems are used across a range of habitats; however, their effectiveness in turbid waters is limited when using standard stereo-BRUV configurations, designed to maintain accuracy at greater distances under good visibility. Under turbid conditions, individuals are usually only visible within the first few meters of the cameras, often falling outside the stereo-overlap area, preventing measurements. To address this limitation, we characterized how camera horizontal field of view (H-FOV) affects the minimum distance and area of stereo-overlap, as well as measurement accuracy, using GoPro Hero 9 cameras across narrow, linear, and wide lens settings between ranges of 0.5-4.0 m. Wider H-FOVs substantially increased the usable overlap area and improved nearfield coverage, although distortion at image peripheries reduced accuracy with distance. Spatial error mapping showed high accuracy across most of the overlap (< 1% at 4 m), with pronounced error (> 14%) confined to extreme edges. We recommend selecting the wide H-FOV to increase the likelihood individuals fall within the stereo-overlap in turbid conditions, while applying spatial constraints to exclude measurements from image peripheries beyond 2.5 m. This approach expands the effective measurement zone under reduced visibility without compromising accuracy, supporting robust length-based biomass estimates and improving the applicability of stereo-BRUV data for downstream ecological analyses in turbid environments.
Flow cytometry measures the optical properties of individual cells and has become essential for enumerating and characterizing marine phytoplankton. Yet systematic comparison of measurements across instruments remains limited, hampering data comparison across laboratories and long-term time series. Here, we used 10 flow cytometers from seven manufacturers to analyze population concentration and optical properties of polystyrene beads, cultured phytoplankton, and natural phytoplankton. Light-scatter signals varied by more than two orders of magnitude across flow cytometers, reflecting differences in optical design and detector sensitivity. Light scattering calibration reduced this variability, lowering coefficients of variation from nearly 100% to below 15% in some cases, although small inter-instrument differences remained. Despite these optical corrections, concentration measurements across instruments were highly variable, with coefficients of variation ranging from 10% to 133%, which can obscure ecological signals in phytoplankton distributions. Population gating contributed minimally to this variability, with no significant difference between expert and novice users (ANOVA, F < 0.001, p > 0.99). Among laboratory culture and field samples, Prochlorococcus concentrations had the highest variability (CV = 56%) and Synechococcus the lowest (CV = 20%). Variance decomposition attributed similar to 80% of concentration variability to hardware characteristics, including optical design, detector sensitivity, and volume-measurement methodology. These findings show that while optical properties can be standardized through calibration, instrument differences still dominate uncertainty in concentration estimates. With shared calibration tools for both optical and concentration measurements, marine flow cytometry could achieve the consistency needed to enable global, long-term syntheses of phytoplankton optical properties and abundance.
Assigning taxonomic identity and thus assessing taxonomic diversity in gelatinous zooplankton is challenging due to their fragility and difficult preservation. Formalin fixation compromises DNA integrity, while flash-freezing, ethanol, and acetone preservation affect morphological features. In this study, we developed a methodological protocol to optimize morphological and molecular identification of pelagic cnidarians and tunicates from the Gulf of Naples (Mediterranean Sea). Specimens were identified while fresh and preserved using four methods: liquid nitrogen (N), ethanol (EtOH), ethanol replaced with acetone (EA), and formalin followed by ethanol and acetone (FEA). Genomic DNA was extracted and PCR-amplified targeting the 18S rRNA gene, being subsequently assessed for concentration, integrity, and sequence quality. FEA specimens retained better morphology compared to N, EtOH, or EA samples, while sequencing performance was comparable between methods. DNA concentrations did not significantly differ among treatments (range: 139-1645 ng ind(-1)) and smaller taxa showed higher values per unit size compared to larger ones. DNA integrity was lower in N and FEA samples, and often undetectable in EA and FEA when assessed by gel electrophoresis. Although 18S : gDNA ratio decreased in some FEA samples, this method still produced high-quality reads (> 500 nucleotides). Our findings show that formalin fixation followed by ethanol and acetone does not compromise molecular analysis, even for species with low DNA content. Unlike other methods, this optimized protocol preserves essential morphological features for accurate taxonomic identification of gelatinous zooplankton while substantially reducing molecular processing time. Overall, the adoption of the proposed protocol could significantly enhance biodiversity assessments of gelatinous taxa.
