OceanCubes

The goal of this project is to develop and deploy seafloor marine observatories called OceanCubes in tropical, mid and high latitudes where upwelling of cold, nutrient rich and hypoxic water is expected on a seasonal basis. The control volume design allows for measurement of the flux of materials and energy from the water column to the benthos at a rate of several times per minute. Currently, OceanCubes are deployed in Japan, Woods hHole and Panama, and being proposed for India, Austrailia, and the Antarctic and Arctic.

Each of the observatories consist of an instrument package on the seafloor ~2 km from a research station at a depth of about 20 m. The package is connected by electro-optical cable to shore providing the capability for internet-based teleoperation by scientists from anywhere in the world. The main observatory node consists of a CTD to measure temperature, salinity, and pressure, and ADCP current meter, sensors for chlorophyll and CDOM fluorescence, oxygen, nitrate, pCO2, pH, a bio-optical package for irradiance and radiance, a Continuous Plankton Imaging and Classification Sensor (CPICS), a phytoplankton and microplankton imaging system, and two panand tilt stereo cameras to observe fish communities. The node is located in the center of a control volume through which the flux of material (plankton, carbon, energy) will be measured. The control volume is established with temperature strings and Acoustic Doppler Current Profiler (ADCP) sensors at each corner 100m on a side.

The node, and its sensors are part of an extensive underwater Local Area Network (LAN) with each sensor provided with an exclusive IP address. All data from the sensors and cameras stream back to shore in Ethernet format where computers will log the data and provide initial processing. The database consists of a database backbone so efficient queries can be made over the internet. A second set of computers accesses the database and images and provide a primary level of Quality Control and processing. All data both raw and processed are accessible over the internet through a web-enabled Graphical User Interface (GUI).

HabCamV4

The HabCamV4 Project

The use of underwater stereo imagery in stock assessment and ecosystem analysis is becoming wide spread as an experimental alternative to pelagic and benthic trawling. For example, the Northeast Fisheries Science Center (NEFSC) and the Woods Hole Oceanographic Institution (WHOI) have developed a towed stereo camera system for estimating scallop and demersal finfish abundance and distribution, together with substrate and habitat assessment. This system was used in the 2012 and 2013 annual scallop survey and will continue to do so in 2014 and for many years to come.

The HabCam imaging system (Howland et al. 2006; Taylor et al, 2008) is “flown” 1.5 to 2.5 meters above the seafloor while being towed at 5 to 6 knots (~2.5 – 3 m/sec), thus a track approximately 100-120 nautical miles is imaged each 24 hours of operations. Optical imagery is collected at a width of approximately 0.75 to 1.25 meters (total ~170,000 - 260,000 square meters/day) and at a rate of 5-6 images per second providing about 50% overlap to aid in mosaicing continuous strips. On the NOAA stereo HabCamV4 system, side by side stereo pair images are fused into a single image at the time of acquisition allowing precise stereo referencing with metadata such as latitude, longitude, temperature, salinity, chlorophyll, light absorption, dissolved oxygen, and other environmental data. In addition, the Teledyne Benthos interferametric C3D side scan acoustic system on the NOAA vehicle collects 3D bathymetry and backscatter to a range of ~200m on either side of the vehicle. 

Habitat Modelling

Habitat Suitability Modelling

Purpose: To develop an approach for analyzing spatial distributional data from HabCam in such a way that species and communities may be predicted with known levels of certainty at locations where HabCam data does not exist. The predictive model, a boosted Generalized Additive Model (GAM), is be based on observations of co-located species/communties, substrate, geomorphology, environmental data, and multi-beam backscatter intensity. Accuracy of the predictions are assessed through cross-validation and receiver Operator Curves. The spatial resolution of the observed and predicted data depend on along track observations of species and substrate, bathymetry grid dimensions (we will start with USGS 10m grids), and the resolution of the MIMES model requiring input from the HabCam GAM model (currently 1 km grid).

Step 1. Decide what predictor variables are worth including in Generalized Additive Model (GAM). For the purpose of predicting the spatial distribution of clustered communities we can use:

* USGS bathymetry on 10m grid

* geomorphology of USGS bathymetry on 10 m grid: 

        *slope 

        *rugosity

        *profile curvature

        *plan curvature

*multi-beam backscatter from Valentine et al 2007

*along track temperature from HabCam

*along track salinity

*along track dominant substrate type 

*along track species presence/absence

Step 2. For each along track observation of a given species, sample the underlying geolocated layers of depth, slope, rugosity, profile curvature, multi-beam intensity, temperature and salinity.

Step 3. Complete the same analysis as in Step 2 for observations where each species was not observed.  The results of Step 2 and 3 will be a table consisting of rows representing each image processed and columns for each species and environmental variable. A given row will have a binary 1 or 0 in each species column and a floating point number for the environmental variables.

Step 4. Perform multi-variate spatial clustering on species associations, including both invertebrates and vertebrates, together with all environmental predictor variables. The result of this step typically is four or more groups of organisms (communities) whos distributions are statistically related to each other and to the environmental variables. Spatial 3D plots can be generated to show the distributions of each community over the bathymetry.

Step 5.  Develop a correlation matrix for predictor variables to assess how well one variable explains the variance in each of the others. 

Plastics in the Ocean

Raman Spectroscopy of Micro-Plastics in the Ocean

Micro-Plastics in the Ocean- relatively new project (January 2016)

Raman Spectroscopy may be used to effectively qiuantify and qualify various polymers in suspension as well as located on a hard surface. I use two wavelengths: my 532nm Kaiser spectromer is set up on a microscope and robotic stage for scaning large sections or filters with seawater collected from various locations. My 785nm spectrometer is a hand held system, which is being incorporated into a CPICS imaging system to provide one to one correspondense between particulates (eg, marine snow, phyto plankton cells, zooplankton mutilt-cellular organisms - copepods) and their Raman signature. Raman has the potential to provide an extremely large amount of cellular infromation in real-time. 

Micro-plastics are being found in the gut contents of sea scallops (Placopecten magellanicus) living at depths of 40 to 130m. We are collecting scallops as part of the NOAA scallop biomass survey, dissecting their gut contents, and scanning for micro-plastics. Since scallops are suspension feeders they are feeding on particulates between 10 and 500 microns so should be very effective sampling agents for micro-plastics from depth. 

Raman is also being used in my lab to characterize Harmful Algal Bloom dinnoflagellte species, which is detailed on another page on my website.

Plastics Three-Phased Program

Phase I To establish a productive working relationship between WHOI, and several chemical companies centered on the technical feasibility, design and component verification of integrating optical imaging, Raman Spectroscopy and robotics to study micro-Plastic Marine Debris (mPMD) in the coastal and deep ocean. Within the first few months we will (1) hold a workshop with invited attendees from corporations and NGOs to investigate and scope out the scientific rationale, technical approach and feasibility of developing robotic optical and spectroscopic systems for investigating micro-plastic particulate vertical distributions, types and residual materials, (2) develop a library of Raman signatures for plastics and polymers indicating the specificity for a variety of compounds at different wavelengths and laser energies, and (3) produce a working report detailing an approach for development of the identified technology.

 Phase II To develop a working prototype optical imaging and Raman Spectroscopic instrument and deploy it on a selected robotic platform (vertically profiling AUV, for example), conduct surveys of the coastal ocean from neuston (surface) to below the pycnocline (200m), and produce reports on the vertical distribution of specific types of micro-plastics in the ocean. The goal is to develop an optical imaging system, or in water microscope, that provides a high resolution optical image together with a Raman signature for targets between 100 microns and 2 cm in size. Additional technologies could include deep sea sediment prismatic imaging and Raman detection systems

 Phase III  To commercialize the technology through IP agreements with partner corporations. 

Polarized Light Field Imaging to Identify Bivalve Larvae

This project is developing a novel in situ light-field optical microscope that quantifies aragonite, calcite, strontionate, and vaterite in planktonic organisms and inorganic particulates by characterizing the birefringent signal resulting from polarized imaging of biogenic and non-biogenic particles and skeletal forms. The instrument address two major issues in climate change and ocean acidification (OA): (1) How to quantify the impact of OA on plankton that form crystalline structures, and (2) The measurement of particulate biogenic and abiogenic carbon (PIC) as a major component of the carbon cycle.

            With reference to issue (1), in the presence of aragonite, calcite or strontionate under saturation, plankton that form biogenic crystalline structures (shells, tests, spines, etc) are unable to effectively form their crystalline skeleton leading to abnormal development and ultimately death.  The planktonic amoebae Order Acantharia form spine structures of celestite, which is the strontium sulfate equivalent of calcium carbonate for these organisms. The Acantharia depend on these structures for feeding and buoyancy control. With reference to issue (2), there is much confusion as to the partitioning of the total PIC flux and the relative contribution of plankton and particulates. In light of a recent finding that microbial production of CaCO₃ may equal or exceed that of the known sources, it is imperative that the carbonate materials contributing to a downward flux of carbon out of the photic zone, be characterized and quantified along with the biological and environmental factors responsible for their formation. The proposed instrument will measure PIC with high accuracy thereby addressing a major component of the carbon pump.

 Novelty

            The new instrument uses the resulting color interference patterns produced by anisotropic crystalline structures under polarized light to identify the polymorph (calcite, aragonite, strontionate, and vaterite), quantify its mass, and identify the source (biogenic or abiogenic[A1] ). A novel use of light field microscopy will allow an extended depth of field and 3Dimensional reconstruction of an entire volume containing particles and plankton. This, in combination with a free flowing optical window, allows for imaging delicate targets such as marine snow aggregates with carbonate and celestite inclusions, invertebrate larvae, and Acantharia without mechanical disturbance. The new instrument will be tested in Waquoit Bay, MA in collaboration with Geochemist Aleck Wang to quantify and establish exactly under what saturation states do biogenic crystalline structures become abnormal and interfere with survival. The result will be a prototype instrument representing a major advance in quantifying the quantity and quality of biogenic crystalline structures, and survival of plankton under field conditions for varying saturation state.