David English

Toxicity and mutagenicity of Gulf of Mexico waters during and after the deepwater horizon oil spill.

The Deepwater Horizon oil spill is unparalleled among environmental hydrocarbon releases, because of the tremendous volume of oil, the additional contamination by dispersant, and the oceanic depth at which this release occurred. Here, we present data on general toxicity and mutagenicity of upper water column waters and, to a lesser degree, sediment porewater of the Northeastern Gulf of Mexico (NEGOM) and west Florida shelf (WFS) at the time of the Deepwater Horizon oil spill in 2010 and thereafter. During a research cruise in August 2010, analysis of water collected in the NEGOM indicated that samples of 3 of 14 (21%) stations were toxic to bacteria based on the Microtox assay, 4 of 13 (34%) were toxic to phytoplankton via the QwikLite assay, and 6 of 14 (43%) showed DNA damaging activity using the λ-Microscreen Prophage induction assay. The Microtox and Microscreen assays indicated that the degree of toxicity was correlated to total petroleum hydrocarbon concentration. Long-term monitoring of stations on the NEGOM and the WFS was undertaken by 8 and 6 cruises to these areas, respectively. Microtox toxicity was nearly totally absent by December 2010 in the Northeastern Gulf of Mexico (3 of 8 cruises with one positive station). In contrast, QwikLite toxicity assay yielded positives at each cruise, often at multiple stations or depths, indicating the greater sensitivity of the QwikLite assay to environmental factors. The Microscreen mutagenicity assays indicated that certain water column samples overlying the WFS were mutagenic at least 1.5 years after capping the Macondo well. Similarly, sediment porewater samples taken from 1000, 1200, and 1400 m from the slope off the WFS in June 2011 were also highly genotoxic. Our observations are consistent with a portion of the dispersed oil from the Macondo well area advecting to the southeast and upwelling onto the WFS, although other explanations exist. Organisms in contact with these waters might experience DNA damage that could lead to mutation and heritable alterations to the community pangenome. Such mutagenic interactions might not become apparent in higher organisms for years.

VIIRS Observations of a Karenia brevis Bloom in the Northeastern Gulf of Mexico in the Absence of a Fluorescence Band

The Visible Infrared Imager Radiometer Suite (VIIRS) is not equipped with a fluorescence band, which may affect its ability to detect and quantify harmful algal blooms (HABs) in coastal waters rich in colored dissolved organic matter. Such a deficiency has previously been demonstrated for a bloom of the toxic dinoflagellate Karenia brevis in the northeastern Gulf of Mexico (NEGOM) in summer 2014. Here, using data collected in the field and by VIIRS and Moderate Resolution Imaging Spectroradiometer (MODIS), we show that such a deficiency may be partially overcome using a red-green-chlorophyll-a index (RGCI). A relationship between near-concurrent (±4 hours) VIIRS RGCI (Rrs(672)/Rrs(551)) and field-measured chlorophyll-a (Chla; in mg m-3) was developed and evaluated using calibrated Chla obtained by a flowthrough system. A mean relative uncertainty, which was approximately twofold lower than VIIRS OC3M Chla, was obtained for VIIRS RGCI Chla (mean relative error: ~56%) over a large range (0.5-20 mg m -3). Similar spatial patterns between near-concurrent MODIS-Aqua (MODISA) normalized fluorescence line height (nFLH) and VIIRS RGCI Chla imagery indicate that VIIRS RGCI may be used as a surrogate for MODISA nFLH in the absence of a fluorescence band. The success of this newly developed data product may be partially attributed to the 20-nm bandwidth of the VIIRS 672-nm band (662-682 nm) that covers a portion of the solar stimulated fluorescence region. However, whether such observations from a simple case study can be extended to other turbid coastal or inland waters still remains to be tested.

Determining Bottom Reflectance and Water Optical Properties Using Unmanned Underwater Vehicles under Clear or Cloudy Skies

Abstract An unmanned underwater vehicle (UUV) with hyperspectral optical sensors that measure downwelling irradiance and upwelling radiance was deployed over sandy bottoms, sea grass patches, and coral reefs near Lee Stocking Island, Bahamas, during the Coastal Benthic Optical Properties (CoBOP) program of 2000. These deployments occurred during both sunny and cloudy weather. If the rate of irradiance change due to cloud cover is slight, then the inclusion of a variable cloudy-irradiance factor will allow a reasonable estimation of water column absorption. Examination of data from a deployment in May 2000 under cloudy skies shows that the combination of hyperspectral light-field measurements, knowledge of the UUVs position in the water column, and a cloudy-irradiance factor permits consistent estimations of bottom reflectivity to be made from UUV measured reflectances. The spatial distribution of reflectance estimates obtained from a UUV may be useful for validation of airborne ocean color imagery.

Electronic overshoot and other bias in the CZCS Global Data Set: comparison with ground truth from the subarctic Pacific

For an area near Ocean Weather Station P in the eastern subarctic Pacific, in situ observations of surface phytoplankton pigment are compared to pigment concentration estimates from the Coastal Zone Color Scanner (CZCS). CZCS data favourably supplement the in situ data, but a few extreme CZCS estimates have erroneously elevated the temporal composites of the region in the NASA Global Data Set. Effects of CZCS subsampling, atmospheric correction, cloud and systematic error detection on accuracy and variability are examined. For the open ocean, accurate atmospheric correction and detection of cloud contamination are the most important requirements for quantitative application of CZCS data.

Atmospheric Correction of AISA Measurements Over the Florida Keys Optically Shallow Waters: Challenges in Radiometric Calibration and Aerosol Selection

An Airborne Imaging Spectrometer for Applications (AISA) hyperspectral imager was deployed on a manned aircraft flown at 1305-m altitude to collect data over optically shallow waters in the Florida Keys with the ultimate goal of mapping water quality and benthic habitats. As a first step, we developed a practical atmospheric correction (AC) approach to derive surface remote-sensing reflectance (Rrs) from AISA measurements using radiative transfer simulations and constraints obtained from field spectral Rrs measurements. Unlike previously published method, the AC approach removes the surface Fresnel reflection and accounts for aircraft altitude and nonzero near-infrared (NIR) reflectance through iteration over the pre-established lookup tables (LUTs) based on MODTRAN calculations. Simulations and comparison with concurrent in situ Rrs measurements show the feasibility of the approach in deriving surface Rrs with acceptable uncertainties. The possibility of errors in the radiometric calibration of AISA is demonstrated, although a definitive assessment cannot be made due to lack of enough concurrent in situ measurements. The need for noise reduction and the difficulty in carrying out a vicarious calibration are also discussed to help advance the design of future AISA missions.

Short-term changes of remote sensing reflectancein a shallow-water environment: observations from repeated airborne hyperspectral measurements

ABSTRACT An atmospheric correction algorithm has been developed for the Airborne Imaging Spectrometer for Applications (AISA) imagery over optically shallow waters in Sugarloaf Key of the Florida Keys. The AISA data were collected repeatedly during several days in May 2012, October 2012, and May 2013. Non-zero near-infrared (NIR) remote-sensing reflectance (Rrs) was accounted for through iterations, based on the relationship of field-measured Rrs between the NIR and red wavelengths. Validation showed mean ratios of 0.94–1.002 between AISA-retrieved and in situ Rrs in the blue to red wavelengths, with uncertainties generally <0.003 sr–1. Such an approach led to observations of short-term changes in AISA-retrieved Rrs from repeated measurements over waters with bottom types of seagrass meadow, sand, and patch reef. Some of these changes are larger than twofold the Rrs uncertainties from AISA retrievals, therefore representing statistically significant changes that can be well observed from airborne measurements. Through radiative transfer modelling, we demonstrated that short-term Rrs changes within 1 hour resulted primarily from sediment resuspension, while tides played a relatively minor role due to the small variation in tidal heights. A sensitivity analysis indicated that although Rrs generally increases with decreasing tide height but increasing suspended sediments, more changes were observed over sandy bottom than over seagrass. The case study suggests that repeated airborne measurements may be used to study short-term changes in shallow-water environments, and such a capacity may be enhanced with future geostationary satellite missions specifically designed to observe coastal ecosystems.

Vertical migration of Karenia brevis in the northeastern Gulf of Mexico observed from glider measurements

The toxic marine dinoflagellate, Karenia brevis (the species responsible for most of red tides or harmful algal blooms in the Gulf of Mexico), is known to be able to swim vertically to adapt to the light and nutrient environments, nearly all such observations have been made through controlled experiments using cultures. Here, using continuous 3-dimensional measurements by an ocean glider across a K. brevis bloom in the northeastern Gulf of Mexico between 1 and 8 August 2014, we show the vertical migration behavior of K. brevis. Within the bloom where K. brevis concentration is between 100,000 and 1,000,000cellsL-1, the stratified water shows a two-layer system with the depth of pycnocline ranging between 14-20m and salinity and temperature in the surface layer being <34.8 and >28°C, respectively. The bottom layer shows the salinity of >36 and temperature of <26°C. The low salinity is apparently due to coastal runoff, as the top layer also shows high amount of colored dissolved organic matter (CDOM). Within the top layer, chlorophyll-a fluorescence shows clear diel changes in the vertical structure, an indication of K. brevis vertical migration at a mean speed of 0.5-1mh-1. The upward migration appears to start at sunrise at a depth of 8-10m, while the downward migration appears to start at sunset (or when surface light approaches 0) at a depth of ∼2m. These vertical migrations are believed to be a result of the need of K. brevis cells for light and nutrients in a stable, stratified, and CDOM-rich environment.

Developing Hyperspectral Vegetation Indices for Identifying Seagrass Species and Cover Classes

ABSTRACT Pu, R.; Bell, S., and English, D., 2015. Developing hyperspectral vegetation indices for identifying seagrass species and cover classes. Seagrass habitats are characteristic features of shallow waters worldwide and provide a variety of ecosystem functions. To date, few studies have evaluated the efficiency of spectral vegetation indices (VIs) for characterizing aquatic plants. Here we evaluate the use of in situ hyperspectral data and hyperspectral VIs for distinguishing among seagrass species and levels of percentage submerged aquatic vegetation (%SAV) cover in a subtropical shallow water setting. Analysis procedures include (1) retrieving bottom reflectance, (2) calculating correlation matrices of VIs with %SAV cover and F value matrices from analysis of variance among species, (3) testing the difference of VIs between levels of %SAV cover and between species, and (4) discriminating levels of %SAV cover and species by using linear discriminant analysis (LDA) and classification and regression trees (CART) classifiers with selected VIs as input. The experimental results indicated that (1) the best VIs for discriminating the four levels of %SAV cover were simple ratio (SR) VI, normalized difference VI (NDVI), modified simple ratio VI, and NDVI × SR, whereas the best VIs for distinguishing the three seagrass species included the weighted difference VI, soil-adjusted VI (SAVI), SAVI × SR and transformed SAVI; (2) the optimal central wavelengths for constructing the best VIs were 460, 500, 610, 640, 660, and 690 nm with spectral regions ranging from 3 to 20 nm at band width 3 nm, most of which were associated with absorption bands by photosynthetic and other accessory pigments in the visible spectral range. Compared with LDA, CART performed better in discriminating the four levels of %SAV cover and identifying the three seagrass species.

Beyond the first optical depth: fusing optical data from ocean color imagery and gliders

Optical properties derived from ocean color imagery represent vertically-integrated values from roughly the first attenuation length in the water column, thereby providing no information on the vertical structure. Robotic, in situ gliders, on the other hand, are not as synoptic, but provide the vertical structure. By linking measurements from these two platforms we can obtain a more complete environmental picture. We merged optical measurements derived from gliders with ocean color satellite imagery to reconstruct vertical structure of particle size spectra (PSD) in Antarctic shelf waters during January 2007. Satellite-derived PSD was estimated from reflectance ratios using the spectral slope of particulate backscattering (γbbp). Average surface values (0-20 m depth) of γbbp were spatially coherent (1 to 50 km resolution) between space and in-water remote sensing estimates. This agreement was confirmed with shipboard vertical profiles of spectral backscattering (HydroScat-6). It is suggested the complimentary use of glider-satellite optical relationships, ancillary data (e.g., wind speed) and ecological interpretation of spatial changes on particle dynamics (e.g., phytoplankton growth) to model underwater light fields based on cloud-free ocean color imagery.

An Autonomous Marine Optical System (AMOS) for monitoring the optical properties of port and harbor waters

The Autonomous Marine Optical System (AMOS) measures remote sensing reflectance (Rrs) above the water surface and subsurface optical properties (irradiance at depth, beam attenuation, chlorophyll fluorescence, and light backscattering) at predetermined times throughout the day. Data are transmitted back by radio to a networked archival and processing station. AMOS was created to routinely monitor the optical properties of near-surface waters, and make those measurements available to researchers over an Ethernet connection with minimal delay. The Rrs measurements can be used not only to validate satellite and airborne remote sensing imagery, but also to be combined with the in situ measurements so that other water column properties can be estimated. The performance of visible and machine-aided hull inspection is strongly affected by the optical properties of the water. AMOS estimates of these optical properties can be used by optical models to predict both subsurface visibility and the amount of ambient light beneath ships at port inspection sites. An example of the application of an inverse hyperspectral Rrs model to AMOS data from the Port of St. Petersburg (FL) is shown to accurately estimate light absorption due to phytoplankton and colored dissolved organic matter (CDOM), and backscattering due to particles.