The development and deployment of autonomous instrumentation in the aquatic sciences, which has rapidly expanded during the last decade, has led to fantastic new insights into unexplored waters, increased understanding of temporal and spatial dynamics, and amazing discoveries across the aquatic sciences. These tools have allowed us to acquire more data, at higher frequency in time and space, and at a lower cost. Sensors deployed on gliders, autonomous underwater vehicles, and buoyed and float-based profilers have permitted near-real time, high-temporal and -spatial resolution observation of water physics (e.g., temperature, turbulence, currents, optics), chemistry (e.g., dissolved oxygen, pH, major and trace nutrients), and biology (e.g., plankton, environmental DNA, algal toxins). These technologies have led to unprecedented opportunities and understanding of numerous and complex properties of aquatic systems, including oceanic circulation patterns and interactions with the atmosphere, temporal, vertical and horizontal dynamics of plankton and associated biogeochemistry, and physical-chemical-biological interactions in both pelagic and benthic environments. In this special session, we welcome the submission of studies from all fields of oceanography and limnology, from physics to biology, which rely on the use of autonomous instrumentation and/or Big Data to make significant advancement in the understanding of key aquatic processes. Contributions may include studies at global to local scales with broad implications across the aquatic sciences and beyond. A special issue on this topic is expected for Fall 2024 in Limnology and Oceanography .
Lead Organizer: Steeve Comeau, Sorbonne Université - CNRS (steeve.comeau@obs-vlfr.fr)
Co-organizers:
David Hambright, The University of Oklahoma (dhambright@ou.edu)
Julia Mullarney, University of Waikato (julia.mullarney@waikato.ac.nz)
Elisa Schaum, University of Hamburg (elisa.schaum@uni-hamburg.de)
Presentations
03:00 PM
Enhancing phytoplankton biomass and community structure observations from BGC-Argo floats using machine learning (5950)
Primary Presenter: Flavien Petit, Sorbonne Université (flavien.petit@imev-mer.fr)
Phytoplankton play a key role in the regulation of numerous biogeochemical cycles. Their role varies depending on their biomass, but also on their community structure. Therefore, monitoring phytoplankton biomass and community structure over large spatial, vertical and temporal scales is a key challenge. BGC Argo floats, equipped with fluorometer, hydrological and optical sensors, provide a great opportunity to develop new methods for assessing phytoplankton biomass and community structure. In parallel, the recent development of machine learning methods makes it increasingly possible to derive biological and ecological variables from a set of environmental variables. We have therefore assembled a dataset of simultaneous measurements of phytoplankton biomass and community composition with BGC-Argo variables. In this study, we present how we can use two different machine learning methods to improve phytoplankton biomass and community structure from BGC-Argo float observations. The first one allows to infer particulate organic carbon from the standard BGC-Argo variables, making it potentially applicable to the whole BGC-Argo fleet. The second uses in addition the particle beam attenuation measured on a large number of floats, which allows to discriminate the particulate organic carbon stock into four different plankton groups, i.e. bacteria, pico-, nano- and micro-phytoplankton. Finally, the combination of these two methods allows the organic carbon stock of these four plankton groups to be estimated from BGC Argo floats.
03:15 PM
SPACE VERSUS TIME: DECORRELATION SCALES OF PHYSICAL AND BIOLOGICAL VARIABLES IN AN UPWELLING BAY (7136)
Primary Presenter: Monique Messié, Monterey Bay Aquarium Research Institute (monique@mbari.org)
How oceanic properties and biological communities are distributed in time and space can have significant implications for trophic transfer, harmful algal bloom monitoring, observation strategies, and ecological forecasting. Satellites provide a synoptic view of the ocean surface, but lack the high-resolution, depth-resolved observations needed to characterize smaller-scale patchiness. Here we use an ongoing time series of autonomous underwater vehicle transects in Monterey Bay, California (2016-present, ~ monthly) that covers most of the bay in a diamond pattern. The dataset includes continuous measurements of physical (temperature, salinity), chemical (oxygen, nitrate), and biological (fluorescence, optical backscatter, bioluminescence) parameters, as well as information on biological community composition from machine-learning derived proxies and environmental DNA samples. The combination of space-time coverage, high resolution, and broad range of oceanic properties provides an unprecedented opportunity to understand what determines the spatiotemporal distribution of physical and biological variables. We use various distance metrics as a function of time and space to identify decorrelation scales and assess whether biological community primarily vary in time or space in an upwelling-influenced bay.
03:30 PM
Temporal evolution of particles and plankton distributions across a mesoscale front during the spring bloom (6500)
Primary Presenter: Jean-Olivier Irisson, Sorbonne Université (irisson@normalesup.org)
The effect of mesoscale features on the distribution of planktonic organisms are well documented. Yet, the interaction between these spatial features and the temporal scale, which can result in sudden increases of the planktonic biomass, is less known and not described at high resolution. We targeted a permanent mesoscale front in the Ligurian Sea (NW Mediterranean) that we repeatedly sampled between January and June 2021 using a SeaExplorer glider equipped with a UVP6, a versatile in situ imager. We aimed to resolve mesoscale distribution of plankton and particle distribution during the spring bloom, to assess whether the front was a location of increased concentration of zooplankton, and if it constrained the distribution of particles. During the 5 months, the glider conducted more than 5,000 dives and the UVP6 collected 1.1 million images. We focused our analysis on shallow (300 m) transects, which gave a horizontal resolution of 900 m. About 13,000 images of planktonic organisms were retained. Ordination methods applied to particles and plankton concentrations revealed contrasted periods during the bloom, in which changes in particle abundance and size could be explained by changes in the plankton community. The front had a strong influence on particle distribution, while the signal was not as clear for plankton, probably because of the relatively small number of imaged organisms. This work confirms the need to sample both plankton and particles at fine scale to understand their interaction, a task for which automated in situ imaging is particularly adapted.
03:45 PM
High-throughput imaging sheds light on marine particle in situ sinking behavior in the Mediterranean Sea (5096)
Primary Presenter: Manon Laget, LOG, Laboratoire d’Océanologie et de Géosciences, Université du Littoral Côte d’Opale, Université de Lille, CNRS, IRD, UMR 8187, Wimereux, France (manon.laget@univ-littoral.fr)
Particles sinking from the surface to the deep ocean play a key role in the biological carbon pump, of which efficiency depends on their concentration and sinking velocities. Over the last decade, in situ imaging has enabled critical advances in the quantification of vertical carbon fluxes. Yet, in situ velocity measurements are scarce and often limited to the bulk population of particles only. Here, we introduce the VisuTrap, consisting of an Underwater Vision Profiler 6 camera inserted in a cylindro-conical sediment trap which isolates a water volume. This system was attached to a sediment trap free-drifting line for 2-day quasi-lagrangian experiments at 2 sites in the Mediterranean Sea. High frequency image acquisition (1.3 Hz) allows reconstruction of a few hundred particle tracks and estimation of their in situ velocities. Images are continuously recorded throughout 42h-long lagrangian cycle, giving an unprecedented overview of particle fluxes temporal dynamics. In the studied area, particles covering a size range from 600 µm to 2 mm sink at a speed up to 1000 m d-1, with an average of 200 m d-1. We observed a substantial, yet variable, proportion of suspended and ascending material, for which we hypothesize that biological activity modifies the normal sinking behavior of particles. First analyses show weak yet significant link with several particle morphological properties, suggesting that particle sinking behavior results from multiple factors. Thus, these patterns should be kept in mind when deriving carbon fluxes from particle size spectra and bulk concentration only.
04:00 PM
The importance of seasonality in the relationship between Line Height Absorption and chlorophyll concentration: a case study from the Northern Gulf of Alaska (5009)
Primary Presenter: Benjamin Lowin, Skidaway Institute of Oceanography (ben.lowin@gmail.com)
As autonomous instruments are becoming typical tools to explore the ocean’s chlorophyll variability, scientists are adopting common-practice methods to cross-calibrate and validate different chlorophyll concentration estimates. Roesler and Barnard’s Line Height Absorption (LHA) method developed in year 2013 is a popular method often used to estimate chlorophyll concentrations from high frequency absorption measurements. The slope of the relationship between absorption and chlorophyll concentration is known as the chlorophyll-specific absorption line height (aLH*). The aLH* varies with phytoplankton community composition and pigment packaging, and while the importance of regional tuning is accounted for, the effect of seasonality on aLH* is not. The following evaluates the impact of temporal or seasonal variability on the LHA. The study was carried out in the Northern Gulf of Alaska (NGA), which is intensely seasonal. It was found that the aLH* for the NGA ranged between 0.0108 and 0.0136, with the highest values occurring in summer and the lowest in spring. This translates into a non-negligible 26% variability in chlorophyll estimates. The size fractionated chlorophyll data strongly suggests that a shift in the phytoplankton size is a major driver of the aLH* variability between spring and summer. Given these results, we encourage others to consider the seasonality factor when using the LHA method to obtain chlorophyll estimates from absorption measurements.
SS094B Autonomous Instrumentation and Big Data: New Windows, Knowledge, and Breakthroughs in the Aquatic Sciences
Description
Time: 3:00 PM
Date: 5/6/2023
Room: Sala Santa Catalina