Model for deriving benthic irradiance in the Great Barrier Reef from MODIS satellite imagery

We demonstrate a simple, spectrally resolved ocean color remote sensing model to estimate benthic photosynthetically active radiation (bPAR) for the waters of the Great Barrier Reef (GBR), Australia. For coastal marine environments and coral reefs, the underwater light field is critical to ecosystem health, but data on bPAR rarely exist at ecologically relevant spatio-temporal scales. The bPAR model presented here is based on Lambert-Beer’s Law and uses: (i) sea surface values of the downwelling solar irradiance, Es(λ); (ii) high-resolution seafloor bathymetry data; and (iii) spectral estimates of the diffuse attenuation coefficient, Kd(λ), calculated from GBR-specific spectral inherent optical properties (IOPs). We first derive estimates of instantaneous bPAR. Assuming clear skies, these instantaneous values were then used to obtain daily integrated benthic PAR values. Matchup comparisons between concurrent satellite-derived bPAR and in situ values recorded at four optically varying test sites indicated strong agreement, small bias, and low mean absolute error. Overall, the matchup results suggest that our benthic irradiance model was robust to spatial variation in optical properties, typical of complex shallow coastal waters such as the GBR. We demonstrated the bPAR model for a small test region in the central GBR, with the results revealing strong patterns of temporal variability. The model will provide baseline datasets to assess changes in bPAR and its external drivers and may form the basis for a future GBR water-quality index. This model may also be applicable to other coastal waters for which spectral IOP and high-resolution bathymetry data exist

Phytoplankton composition from sPACE: Requirements, opportunities, and challenges

Ocean color satellites have provided a synoptic view of global phytoplankton for over 25 years through near surface measurements of the concentration of chlorophyll a. While remote sensing of ocean color has revolutionized our understanding of phytoplankton and their role in the oceanic and freshwater ecosystems, it is important to consider both total phytoplankton biomass and changes in phytoplankton community composition in order to fully understand the dynamics of the aquatic ecosystems. With the upcoming launch of NASA\u27s Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) mission, we will be entering into a new era of global hyperspectral data, and with it, increased capabilities to monitor phytoplankton diversity from space. In this paper, we analyze the needs of the user community, review existing approaches for detecting phytoplankton community composition in situ and from space, and highlight the benefits that the PACE mission will bring. Using this three-pronged approach, we highlight the challenges and gaps to be addressed by the community going forward, while offering a vision of what global phytoplankton community composition will look like through the “eyes” of PACE

Optical detection and quantification of Trichodesmium spp. within the Great Barrier Reef

The primary purpose of this PhD project was the development of suitable methods for the optical detection and quantification of the diazotrophic, marine cyanobacteria Trichodesmium within the Great Barrier Reef (GBR), Australia. Within the GBR, Trichodesmium is likely to contribute quantities of new-nitrogen of similar magnitude to that of rivers. However, due to uncertainties regarding the spatial and temporal abundance of Trichodesmium, there is an order of magnitude uncertainty associated with these nitrogen fixation estimates. Thus, improved methods for quantifying Trichodesmium within the GBR are essential. The key objectives of this PhD thesis were to:\ud \ud 1. Study the bio-optical properties of Trichodesmium,\ud \ud 2. Develop a binary flag for its detection using MODIS imagery and\ud \ud 3. Examine hyperspectral radiometric data as a means of positively discriminating and quantifying Trichodesmium.\ud \ud In addition, the bio-optical properties of a senescing surface aggregation of Trichodesmium were studied.\ud \ud Within this PhD thesis, the bio-optical properties of Trichodesmium were studied primarily with discrete water samples analysed using a benchtop spectrophotometer. Particulate and coloured dissolved organic matter (CDOM) absorption coefficients were measured. From this research component, a relationship between the magnitude of the spectral absorption coefficient of Trichodesmium and chlorophyll-a (Chla) specific concentration was established. Results were comparable with those of the literature. The Chla-specific Trichodesmium absorption coefficients were later used as inputs for radiative transfer simulations with Hydrolight. In situ above-water hyperspectral radiometric measurements of Trichodesmium were also collected.\ud \ud A Trichodesmium-specific binary classification algorithm was developed using quasi-250 m MODIS data. Above-water hyperspectral radiometric measurements of dense Trichodesmium surface aggregations (> 30 mg Chla m⁻³) showed that the water leaving radiance at wavelengths greater than 700 nm were ii much higher in magnitude (> 0.05 W m⁻² sr⁻¹) relative to the visible wavelengths 400 - 700 nm (< 0.03 W m⁻² sr⁻¹). This "red-edge" effect agreed with observations of others from the literature. The binary classification algorithm was based on three criteria. The first criteria relied on the difference in magnitude between the MODIS normalised water-leaving radiance (nLw) of band 2 (859 nm) and band 15 (678 nm). The magnitudes of the nLw of band 4 (555 nm) and band 1 (645 nm) relative to band 15 formed the second and third criteria respectively. The classification algorithm was tested on a small subset of 13 MODIS images with corresponding Trichodesmium sea-truths and yielded an 85 % accuracy. Fine scale features consistent with dense Trichodesmium surface aggregations such as eddy swirls and windrows were well represented within the algorithm results. The algorithm was also found to be robust in the presence of highly reflective, potentially confounding affects such as coral reefs, shallow bathymetry and riverine sediment plumes. The suitability of the quasi-analytical algorithm (QAA) for inverting hyperspectral remote sensing reflectance, R(rs)(λ), and quantitatively discriminating Trichodesmium was examined. A technique combining the QAA and a similarity index measure (SIM) was developed using R(rs)(λ)data simulated for examples of Case 1 and Case 2 waters. Hydrolight radiative transfer software was used to model R(rs)(λ)with Trichodesmium Chla specific absorption inherent optical properties. The QAA was used to invert the simulated R(rs)(λ) spectra to yield an estimate of the phytoplankton absorption coefficient a^QAA(0)(λ). To ascertain the presence of Trichodesmium, seven SIM values were derived by comparing a^QAA(0)(λ)with a known Trichodesmium reference absorption spectrum a^ref (tri)(λ), and also with the absorption spectra of six other phytoplankton types. The results found that the SIM could discriminate Trichodesmium from the six other phytoplankton types for concentrations as low as 0.2 mg Chla m⁻³ and 3 mg Chla m⁻³ for the Case 1 and Case 2 scenarios considered. The QAA-SIM method was tested on along-transect R(rs)(λ)data collected within the GBR. Upon identifying the presence of Trichodesmium, the magnitude of a^QAA(0)(λ)was used to determine Chla concentration. The along-transect, QAA derived Chla values were validated with data from a Chla fluorometer within a iii ship-board flow-through system. The predicted Chla values matched well with those fluorometrically measured yielding an R-squared value of 0.805.\ud \ud Two distinct colour modes of Trichodesmium were sampled from a dense surface aggregation within the GBR. The two colour modes were denoted as: orangebrown (OB) and bright green (BG). The spectral particulate and coloured dissolved organic matter (CDOM) absorption coefficients were measured for the OB and BG samples. The absorption properties of the OB sample were consistent with those of Trichodesmium reported within literature. However, the absorption properties of the BG sample were significantly different to those of the OB sample. The particulate and dissolved absorption coefficients of the BG sample revealed that the water soluble red pigments phycourobilin (PUB) and phycoerythrobilin (PEB) had leached into the surrounding seawater. The results suggest that the BG samples were in the process of senescence. Hydrolight radiative transfer modelling was used to simulate the hyperspectral R(rs)(λ)of OB and BG colour modes. The results indicated that the R(rs)(λ)spectra of the OB sample was spectrally distinct from that of the BG sample. Thus, the potential to optically discriminate the physiological state of a Trichodesmium surface aggregation was established

Three decades of ocean-color remote-sensing Trichodesmium spp. in the world's oceans: a review

Ocean-color sensors have provided the necessary platform for synoptic-scale detection and monitoring of the nitrogen-fixing marine cyanobacterium Trichodesmium spp. Such information is invaluable to global biogeochemical studies which require accurate estimates of atmospherically-fixed nitrogen. This article reviews literature from the past three decades and discusses the development of Trichodesmium-specific remote-sensing methods and how these have been revised with improved knowledge of bio-optical properties and remote-sensing technologies. Overall, the majority of Trichodesmium-specific detection methods have been non-quantitative and developed primarily for mapping the occurrence of dense surface aggregations of the cyanobacteria. The ability to positively discriminate and quantify low background concentrations of Trichodesmium (e.g. <3200 trichomes L-1) dispersed within the water column still remains an intractable problem. Furthermore, the spectral and spatial resolutions of existing ocean-color sensors are presently a limiting factor for quantitative Trichodesmium remote sensing. It is noted that planned next-generation sensors with higher spectral resolutions, in both low earth and geostationary orbits, are likely to enhance efforts to remotely-sense global Trichodesmium abundance

A simple, binary classification algorithm for the detection of Trichodesmium spp. within the Great Barrier Reef using MODIS imagery

A binary classification algorithm to detect the presence of high surface concentrations of the nitrogen-fixing cyanobacterium Trichodesmium spp. was developed for high spatial resolution (250 m) imagery of the Moderate-resolution Imaging Spectroradiometer (MODIS). Above-water hyperspectral radiometric measurements of dense Trichodesmium surface aggregations (>10 µg L Chlorophyll a) showed that the water-leaving radiance Lw at wavelengths greater than 700 nm were much higher in magnitude (>0.05 W m2sr-1) relative to the visible wavelengths 400-700 nm (<0.03 W m2sr-1). The binary classification algorithm is based on three criteria. The first criteria relied on the difference in magnitude between the MODIS normalized water-leaving radiance (nLw) at the 859 and 678 nm wavebands. The magnitude of the nLw at the 555 and 645 nm wavebands relative to nLw 678 nm waveband formed the second and third criteria, respectively. The classification algorithm was tested on a small subset of 13 MODIS images with corresponding Trichodesmium sea-truths and yielded an 85% accuracy. Fine-scale features consistent with dense Trichodesmium surface aggregations, such as eddy swirls and windrows, appear to be well represented with the algorithm results. The algorithm was also found to be robust in the presence of highly reflective, potential confounding effects

A benthic light index of water quality in the Great Barrier Reef, Australia

Good water quality is essential to the health of marine ecosystems, yet current metrics used to track water quality in the Great Barrier Reef are not strongly tied to ecological outcomes. There is a need for a better water quality index (WQI). Benthic irradiance, the amount of light reaching the seafloor, is critical for coral and seagrass health and is strongly affected by water quality. It therefore represents a strong candidate for use as a water quality indicator. Here, we introduce a new index based on remote sensing benthic light (bPAR) from ocean color. Resulting bPAR index timeseries, based on the extent to which the observed bPAR fell short of the locally- and seasonally-specific optimum, showed strong spatial and temporal variability, which was consistent with the dynamics that govern changes in water clarity in the Great Barrier Reef. Our new index is ecologically relevant, responsive to changes in light availability and provides a robust metric that may complement current Great Barrier Reef water quality metrics