Browsing by Author "Bernard, Stewart"

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    A novel approach to investigating chlorophyll-a fluorescence quantum yield variability in the Southern Ocean
    (2019) Bone, Emma Lewis; Vichi, Marcello; Thomalla, Sandy J; Bernard, Stewart; Smith, Marié E; Ryan-Keogh, Thomas. J
    The apparent fluorescence quantum yield of chlorophyll-a (ΦF ), i.e. the ratio of photons emitted as chlorophyll-a fluorescence to those absorbed by phytoplankton, serves as a first order measure of photosynthetic efficiency and a photophysiological indicator of the resident phytoplankton community. Drivers of ΦF variability, including taxonomy, nutrient availability, and light history, differ in magnitude of influence across various biogeographic provinces and seasons. A Multi-Exciter Fluorometer (MFL, JFE Advantech Co., Ltd.) was selected for use in in situ ΦF derivation and underwent an extensive radiometric calibration for this purpose. Wavelength-specific ΦF was determined for 66 in situ field stations, sampled in the Atlantic Southern Ocean during the austral winter of 2012 and summer of 2013/ 2014. Phytoplankton pigments, macronutrient concentrations, and light levels were simultaneously measured to investigate their influence on ΦF . While no relationship was observed between macronutrient levels and ΦF , an inverse relationship between light and ΦF was apparent. This was likely due to the influence of speciesspecific fluorescence quenching mechanisms employed by local populations. ΦF derived from ocean colour products (Φsat) from the Moderate Resolution Imaging Spectroradiometer (MODIS) were compared to in situ ΦF to assess the performance of three existing Φsat algorithms. Results indicate that accounting for chlorophyll-a fluorescence reabsorption, the inherent optical properties of the surrounding water column, and the sensor angle of observation, is crucial to reducing Φsat uncertainty. A hybrid combination of two of the algorithms performed best, and was used to derive Φsat for stations co-located to in situ iron measurements in the Atlantic Southern Ocean. A significant negative relationship was observed, indicative of the effects of iron availability on quantum yield and its potential as a proxy for iron limitation. However, separating the individual contributions of light, taxonomy, and iron limitation to Φsat variability remains a challenge. A time series analysis of Φsat was also undertaken, which revealed a prominent Φsat seasonal cycle. Ultimately, increased in situ sampling would expedite the development of improved Φsat algorithms; the routine retrieval of Φsat would offer insight into phytoplankton dynamics in undersampled regions such as the climate relevant Southern Ocean.
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    The bio-optical detection of harmful algal blooms
    (2005) Bernard, Stewart; Probyn, Trevor; Shillington, Frank
    An analytical framework for the simulation and quantitative interpretation of ocean colour data is presented, providing an inverse reflectance algorithm designed for the detection of harmful algal blooms. The adopted framework focuses on establishing quantitative relationships between optically important algal intracellular properties and inherent optical properties (IOPs), such as the absorption and backscattering coefficients, and the resultant effects on remote-sensing reflectance. A principal aim of the study is to establish the determinant variables of the IOPs associated with natural algal assemblages, and provide a means of simulating these IOPs. Algal size is an important determinant of optical properties, and the study demonstrates algal IOP simulation, using equivalent particle size distributions that can be simply parameterised with regard to effective cell diameter. Statistical analyses of causal variability are also conducted on absorption data from a variety of natural algal assemblages, revealing the relative importance of cell size, intracellular Chi a concentration, and accessory pigment complement. An improved understanding of algal angular scattering is regarded as key to the analytical modelling of ocean colour, and the use of two-layered spherical models for the simulation of algal scattering properties is investigated. Preliminary validation of the combined use of the equivalent size and two-layered models indicates that they are capable of adequately simulating the remote-sensing reflectance properties of high biomass bloom waters.
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    The chemical and bio-optical characterisation of gelbstoff in southern African waters : a preliminary analysis
    (1996) Bernard, Stewart; Shillington, Frank
    This study will attempt to begin the bio-optical characterisation of gelbstoff in southern African waters. Gelbstoff is a collective term, in itself perhaps an indication of a poorly understood phenomenon, given to a complex group of macromolecular organic compounds. It is the common bio-optical properties of these compounds that cause such an association, specifically the exponential decrease of absorption with increase in wavelength, resulting in typical absorption spectra decaying exponentially from a maximum in the ultra-violet. It is the accurate measurement or inferral of these spectra that is the primary aim of any bio-optical investigation of gelbstoff.
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    The development of satellite derived nitrate and stratification indices for the southern Benguela ecosystem
    (2013) Khumalo, Madoda Brian; Bernard, Stewart
    An earth observation based study was conducted in the southern Benguela upwelling system, aimed at developing remotely sensed proxies to determine ecological conditions conducive to the formation of harmful algal blooms (HAB) which are endemic to the system. The aim of this study was to identify the relationship between nutrient availability, turbulence and phytoplankton community assemblages using remotely sensed data. Certain phytoplankton functional groups are adapted to a particular environment within an ecological space conceptually based on the nutrient availability and turbulence (Margalef, 1978). Two proxies, representing the nutrient availability, and turbulence or stratification, were created using satellite-derived surface nitrate (NO3) concentrations and the 12ºC isotherm (Iso12) depths, and used to define the ecosystem state through Margalef's Mandala (Margalef, 1978). The approach involved the development of robust algorithms using in situ data collected in the greater St Helena Bay region to estimate the surface NO3 concentrations and the depth of the Iso12 for the southern Benguela, using remotely sensed sea surface temperatures (SST) and wind data. The derivation of the nutrient proxy was based on a model initially developed by Dugdale et al., (1989) then modified by Silió-Calzada et al., (2008) for use in the Benguela. The turbulence proxy was derived using a simple linear regression model to estimate the depth of the Iso12 which was utilized as a proxy for the thermocline depth in the system. The performance of the nutrient and turbulence proxies were assessed on local, meso- and synoptic scales for their ability to resolve the event and seasonal scale variations in the inner shelf environment of the southern Benguela. The derived NO3 and Iso12 products were sufficiently able to resolve the event and mesoscale variability of the system in 2005, 2006 and 2007. The performance of the products at capturing the annual and intra-seasonal variability of the system was satisfactory, displaying an ability to resolve the ecosystem upwelling variability. Using the NO3 and Iso12 products as the nutrient and turbulence proxies was satisfactory as a first attempt at using earth observation to classify the ecosystem according to Margalef's Mandala (Margalef, 1978). The proxies were able to model the ecosystem inner-shelf environment for multiple years and thus create the ability to hypothesize ecosystem sub-habitats occupied by particular life forms of phytoplankton. There were however two concerns that needed further consideration in the approach: 1).The large warm bias discovered between the in situ and remotely sensed temperatures which had a direct influence on the validity of the algorithms in the ecosystem and 2.) The temporal and spatial disconnects between the physical forcing and biological response of the ecosystem and subsequent impact upon the utility of the remotely sensed proxies.
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    Distinguishing cyanobacteria from algae using bio-optical remote sensing
    (2014) Matthews, Mark William; Shillington, Frank; Bernard, Stewart
    This study advances the use of remote sensing for eutrophication and cyanobacterial bloom detection in inland and near-coastal waters. The hypothesis that prokaryotic cyanobacteria can be systematically differentiated from algae (or eukaryotic species) on the basis of their distinctive bio-optical features is tested using a novel in situ bio-optical dataset and remotely sensed data from the Medium Resolution Imaging Spectrometer (MERIS). The in situ dataset was collected between 2010 and 201 2 from three optically-diverse South African inland waters. An empirical algorithm, called the maximum peak-height (MPH) algorithm, was developed for operational determinations of trophic status (chlorophyll-α), cyanobacterial blooms and surface scum from MERIS. The algorithm uses top-of-atmosphere data to avoid the large uncertainties associated with atmospherically corrected water leaving reflectance data in optically-complex and turbid waters. The detailed analysis of the variability of the optical properties of the three diverse reservoirs provides new knowledge of the inherent optical properties of South African inland waters which have previously not been described. The study also provides the first detailed investigation of the effects of intracellular gas vacuoles on the optics of phytoplankton using a two-layered sphere model. The results demonstrate how gas vacuoles impart distinctive bio-optical features to cyanobacteria and cause backscattering to be enhanced. An advanced inversion algorithm is developed for detecting phytoplankton assemblage type and size from water leaving reflectance data. The algorithm, based on a direct solution of the equation of radiative transfer using Ecolight-S radiative transfer model, successfully distinguishes between phytoplankton assemblages dominated by small-celled cyanobacteria and those dominated by large-celled dinoflagellate species. It also provides reliable estimates of phytoplankton biomass (chl-α), and the absorption coeficients of phytoplankton and combined non- phytoplankton particulate and dissolved matter. Finally, the application of the MPH algorithm to a time series of MERIS data from 2002 to 2012 in South Africa's 55 largest reservoirs is likely to be the most comprehensive assessment of eutrophication and cyanobacteria occurrence from earth observation data yet performed. The results confirm that widespread cyanobacterial blooms and eutrophication remain issues of critical concern for water quality in South Africa.
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    Phytoplankton community structure determined through remote sensing and in situ optical measurements
    (2014) Evers-King, Hayley Louise; Bernard, Stewart; Henson, Stephanie; Shillington, Frank; Lucas, Mike
    Linking variability in optical signals with phytoplankton community characteristics is important to extend the use of the vast resource that is the satellite ocean colour archive. Detection of species, functional types or size classes has been addressed through a spectrum of empirical to analytical approaches. A key step in developing these techniques is quantifying the sensitivity in reflectance, which can be attributed to phytoplankton characteristics (e.g cell size) under different optical regimes. Ultimately, highly spatially and temporally resolved information on phytoplankton characteristics can help the global scientific community to answer important questions relating to primary ecosystem variability. In the southern Benguela, Harmful Algal Blooms threaten public health and the economic viability of fishery and aquaculture industries in the region. Concurrently, the dominance of phytoplankton biomass amongst optically significant constituents in the southern Benguela makes the region ideal for assessing the extent to which phytoplankton characteristics beyond biomass can influence the ocean colour signal. A forward and inverse approach is presented. Phytoplankton absorption and back scattering are generated from a phytoplankton particle population model coupled to two radiative transfer approaches: a reflectance approximation and the radiative transfer model, EcoLight-S. Non-linear optimisation inversion schemes are then implemented. A simulated dataset is created to investigate how much variability in reflectance can be associated with changes in phytoplankton cell size in different bio-optical water types. This dataset is inverted to investigate the errors inherent in the inversion process as a result of ambiguity. Comparison of the two radiative transfer techniques allows for consideration of the suitability of approximations for bidirection-ality and subsurface propagation. The inversion algorithm is then applied to hyperspectral in situ radiometric data to provide validation and further assessment of errors from all sources. Results indicate that size related sensitivity in reflectance is highly dependent on phytoplank-ton biomass, as determined by the relative phytoplankton contribution to the Inherent Optical Property budget. The algorithm is finally applied to ten years of MERIS data covering the southern Benguela. A time series of biomass and cell size is presented and metrics developed to demonstrate the utility of this approach for identifying previously unobserved interannual variability in Harmful Algal Blooms.
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    Radiometric validation of multi-spectral ocean colour satellite data in high biomass Southern Benguela waters
    (2009) Robertson, Elisabeth; Bernard, Stewart; Shillington, Frank
    This study forms the first step towards a comprehensive ocean colour satellite validation strategy for the Southern Benguela region, and underlines the value of a statistical radiometric validation as a prerequisite to any geophysical validation exercise. A radiometric validation exercise was performed using co-incident MERIS RR data and in situ radiometer data from a mooring in the Southern Benguela near Lambert's Bay during the late summer bloom seasons of 2005 and 2006. The data are typified by very high biomass conditions. Sources of error associated with the in situ data are assessed and the magnitudes quantified. The satellite data is examined with particular reference to uncertainty derived from the atmospheric correction processes, which perform unreliably in many of the matchup instances. Results show that the accuracy of the atmospheric correction does not appear to be related to the in-water constituents and is more likely due to atmospheric variability or aerosol features that are not addressed in the models employed by the correction processes. It is also shown that while the radiometric data display a consistent bias in the red region of the spectrum, good correlation with the satellite measurements is observed here under high biomass conditions, underlining the importance of the red wavebands for coastal remote sensing. Recommendations towards the development of a comprehensive regional validation strategy include the establishment of low-cost measurement protocols for high biomass conditions, as well as further investigations into regional atmospheric variability to improve confidence in the atmospheric correction procedures.
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    The use of operational harmful algal bloom monitoring systems in South Africa to assess long term changes to bloom occurrence & impacts for aquaculture
    (2021) Mtetandaba, Aphiwe; Vichi, Marcello; Bernard, Stewart; Smith, Marie
    The south coast of South Africa is a very dynamic, productive, high energy environment and is considered to be a generally challenging setting for in-water aquaculture. One of the largest environmental threats to aquaculture are harmful algal blooms (HABs), a natural ecological phenomenon often accompanied by severe impacts on coastal resources and local economies. There is a wide variety of potentially harmful blooming species in the region, with impacts resulting from both toxicity and the negative effects associated with high biomass. While HABs are fairly well documented around the southern Benguela area, the primary concern is the lack of long-term data showing if blooms are becoming more frequent, persistent or are having greater impact over the last decades, consistent with environmental change experienced in the region. For this study, high-resolution satellite remote sensing observations from 16 years of MODIS-Aqua (1 km) and one month of Sentinel-3 OLCI (300 m), using regionally optimised blended algorithms, were used to investigate the spatial distribution and temporal variability of chlorophyll-a (Chl-a) along the south coast of South Africa. A Chl-a threshold of 27 mg m−3 was used as an analytic to identify the occurrence of high biomass blooms in the remote sensing data. Phytoplankton count data from aquaculture farms are used to provide information corresponding to changes in phytoplankton community structure, and to investigate the distribution and seasonal trends of HABs along the south coast. To further explore the spatial and temporal distribution, phytoplankton species considered harmful for this study were identified and classified to their seasonal occurrence: some species were consistently present throughout the years, however each region showed contrasting seasonality. A second interest of this study is linked to assessing the capacity of the aquaculture industry to make profitable use of existing observational and early warning tools. The impact of HABs on the environment or in aquaculture facilities can be potentially mitigated by increasing the industry awareness and early warnings of HAB development. In this regard, the Fisheries and Aquaculture Decision Support Tool (DeST) was used in order to develop short term alerts on HAB development. The EO analyses conducted here specifically use the same methods used by this DeST to demonstrate the use of this tool for historical analysis in addition to real time alerting. In order to evaluate the effectiveness of the tool and how the aquaculture farmers use the ABSTRACT information provided on the DeST, an online user feedback was generated, and distributed to all stakeholders via email
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    Towards high fidelity mapping of global inland water quality using earth observation data
    (2021) Kravitz, Jeremy; Matthews, Mark; Bernard, Stewart; Fawcett, Sarah
    This body of work aims to contribute advancements towards developing globally applicable water quality retrieval models using Earth Observation data for freshwater systems. Eutrophication and increasing prevalence of potentially toxic algal blooms among global inland water bodies have become a major ecological concersn and require direct attention. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products. This study provides one of the first assessments of the state-ofthe-art for trophic status (chlorophyll-a) retrievals for small water bodies using Sentinel-3 Ocean and Land Color Imager (OLCI). Multiple fieldwork campaigns were undertaken for the collection of common aquatic biogeophysical and bio-optical parameters that were used to validate current atmospheric correction and chlorophyll-a retrieval algorithms. The study highlighted the difficulties of obtaining robust retrieval estimates from a coarse spatial resolution sensor from highly variable eutrophic water bodies. Atmospheric correction remains a difficult challenge to operational freshwater monitoring, however, the study further validated previous work confirming applicability of simple, empirically derived retrieval algorithms using top-of-atmosphere data. The apparent scarcity of paired in-situ optical and biogeophysical data for productive inland waters also hinders our capability to develop and validate robust retrieval algorithms. Radiative transfer modeling was used to fill this gap through the development of a novel synthetic dataset of top-of-atmosphere and bottom-of-atmosphere reflectances, which attempts to encompass the immense natural optical variability present in inland waters. Novel aspects of the synthetic dataset include: 1) physics-based, two-layered, size and type specific phytoplankton IOPs for mixed eukaryotic/cyanobacteria 6 assemblages, 2) calculations of mixed assemblage chl-a fluorescence, 3) modeled phycocyanin concentration derived from assemblage based phycocyanin absorption, 4) and paired sensor-specific TOA reflectances which include optically extreme cases and contribution of green vegetation adjacency. The synthetic bottom-of-atmosphere reflectance spectra were compiled into 13 distinct optical water types similar to those discovered using in-situ data. Inspection showed similar relationships and ranges of concentrations and inherent optical properties of natural waters. This dataset was used to calculate typical surviving water-leaving signal at top-of-atmosphere, as well as first order calculations of the signal-to-noise-ratio (SNR) for the various optical water types, a first for productive inland waters, as well as conduct a sensitivity analysis of cyanobacteria detection from top-of-atmosphere. Finally, the synthetic dataset was used to train and test four state-of-the-art machine learning architectures for multi-parameter retrieval and cross-sensor capability. Initial results provide reliable estimates of water quality parameters and inherent optical properties over a highly dynamic range of water types, at various spectral and spatial sensor resolutions. It is hoped the results of this work incrementally improves inland water Earth observation on multiple aspects of the forward and inverse modelling process, and provides an improvement in our capabilities for routine, global monitoring of inland water quality.
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    The use of reflectance classification for chlorophyll algorithm application across multiple optical water types in South African coastal waters
    (2016) Smith, Marié; Vichi, Marcello; Bernard, Stewart; Matthews, Mark
    Ocean colour remote sensing is a valuable tool for deriving information about key biogeochemical variables over inland, coastal and ocean waters at scales unachievable via in situ techniques. However, broader use of ocean colour data is still limited by the need for users to choose among a seemingly complicated range of available satellite products and to understand the limitations and constraints of these products across a wide range of water types. This issue could benefit from the capability to seamlessly apply and blend watertype appropriate algorithms into a single output product that provides optimal retrievals over a wide range of water types. The assessment of the fuzzy membership of satellite remote sensing reflectance (Rᵣₛ) to pre-defined regional optical water types (OWTs) provides a framework for application and blending of OWT-appropriate algorithms on a per-pixel basis. This study presents the first characterization of the OWTs in the coastal waters of South Africa. The OWTs are determined through stepwise fuzzy c-means clustering of a systematically expanding and modified database constructed from in situ, synthetic and regionally extracted Medium Resolution Imaging Spectrometer (MERIS) Rᵣₛ. A database division allows separate and more detailed clustering of phytoplankton-dominated Rᵣₛ and backscattering-dominated Rᵣₛ into six and five classes respectively. Chlorophyll α (Chl α) algorithms are assigned per OWT based on lowest error and uncertainty. The blended Chl α product consists of weighted retrievals from five different algorithms, including two 4th order polynomial exponential algorithms utilizing the blue-green spectral region, two red-NIR band ratio algorithms, and a neural network. The algorithm blending procedure retrieves satellite-derived Chl α concentration ([Chl α]) with lower RMS error and uncertainty compared to individual algorithms and provides improved capability to retrieve [Chl α] for different South African water types with a single product over a range spanning almost four orders of magnitude. The eleven OWTs are utilized in the classification and algorithm blending framework and applied to the full archive of MERIS Level 2 reflectance between the years 2002 and 2012 over South Africa's coastal waters. The persistence of the OWTs is presented and linked to the prominent environmental and physical drivers, whilst regions with low total class membership sums are discussed in terms of satellite data coverage and data quality. A time series of the blended [Chl α] product displays improved capability to capture the ranges of variability observed in the coastal, shelf and offshore environment compared to currently available regional and standard MERIS Level 2 products.
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    Using cell size to represent phytoplankton diversity in studies of nitrogen dynamics in the southern Benguela
    (2017) Atkins, Josephine ffion; Moloney, Coleen L; Bernard, Stewart; Machu, Eric
    Phytoplankton are a key component in the functioning of marine ecosystems and play a central role in the cycling of nitrogen and other elements. Metrics that can adequately represent the biogeochemical processes associated with phytoplankton diversity are needed in order to make use of remote sensing and modeling platforms. A single-value size proxy, effective diameter (Deff ), represents the mean volume to surface area ratio across the nano and micro plankton size fraction (2-200µm) in the southern Benguela, but has yet to be tested regarding its biogeochemical relevance. Cell size imposes overarching constraints on phytoplankton metabolism; there are therefore strong grounds for evaluating the usefulness of the metric (Deff ) in studies of nitrogen dynamics in diverse, natural assemblages. Three case studies were used to explore the nitrogen dynamics in naturally occurring assemblages and to evaluate the relationships between Deff and the uptake of the different sources of nitrogen. Two of the case studies comprised high biomass, harmful algal blooms observed off Lamberts Bay during an upwelling/downwelling cycle. The third case study used bi-monthly sampling over a full year in Saldanha Bay. The Lamberts Bay case studies involved blooms occasionally dominated by HAB-forming species: a mixotrophic ciliate, Myrionecta rubra, and a dinoflagellate, Prorocentrum triestinum. The nitrogen uptake rates followed the well observed pattern of high nitrate uptake by large cells and regenerated nitrogen uptake by small cells. Myrionecta rubra had a wide range of nitrate (O₃⁻ ) uptake rates (0.02-0.3 µmol N L⁻¹ h⁻¹). Prorocentrum triestinum showed slower rates of O₃⁻ uptake (0.01-0.2 µmol N L⁻¹ h⁻¹) and dominated in low O₃⁻ , stratified conditions. Diatoms were the most efficient utilisers of O₃⁻ and total nitrogen in these cases. The effective diameter was significantly related to the uptake rates of ammonium (NH₄⁺ ) (r=-0.54, p<0.005) and urea (r=-0.59, p<0.005), but not O₃⁻ (r=0.27, p=0.11). This was attributed to some instances of bi-modality in observed size distributions as well as potentially specialist nutrient uptake strategies employed by diatoms. The year-round data from Saldanha Bay indicated the system was diatom-dominated and was used to assess 1 how well Deff could represent the nitrogen uptake strategies employed by the diverse diatom assemblages. The Saldanha Bay system has O₃⁻ limited surface waters during summer, and light-limited bottom waters during winter. No significant relationship was found between Deff and the mass-specific uptake rates of the different nitrogen species in this data set. This was attributed to the complex shapes of the size distributions and the comparatively low biomass observed. Uptake kinetic experiments revealed high variability for maximum uptake rates (Vmax) and half saturation values (Ks) for both O₃⁻ and NH₄⁺ . For O₃⁻ : Vmax ranged 0.007-0.17 µmol N L⁻¹ h⁻¹, and Ks ranged between 0.2-42.5 µmol N L⁻¹. For NH₄⁺ Vmax was observed between 0.02-2.7 µmol N L⁻¹ h⁻¹; and Ks values ranged 0.1- 14.02 µmol N L⁻¹. Variability was observed in association with the availability of the ambient sources of nitrogen, but some variation was accounted for by the presence of different diatom species. From these three case studies it was concluded that the single-value size proxy was an adequate metric to quantify the uptake of regenerated nitrogen in scenarios of high biomass algal blooms. Such blooms are a pervasive feature in the southern Benguela Ecosystem. For lower biomass blooms, however, Deff did not adequately represent the nutrient dynamics of diverse diatomdominated assemblages. The variable shape of the size spectrum is an important factor in determining the rates of nutrient uptake and, in cases of bi- or multi-modality, this information could be lost when represented by a single descriptor such as Deff . It was subsequently hypothesised that size spectra could be used to accurately represent the nitrogen dynamics in diverse phytoplankton assemblages. This was tested by comparing the observed uptake rates of the three case studies to estimated uptake rates based on size spectra. Observed particle size distributions were used to estimate the uptake of O₃⁻ and NH₄⁺ , based on theoretical relationships to calculate size-dependent values of Vmax and Ks. Michaelis-Menten models were applied to measured ambient nutrient concentrations and particle size distributions, generating size-integrated estimates of O₃⁻ , NH₄⁺ and total N uptake rates. The variability in the estimated uptake rates was similar to that of the measured values. It was thus concluded that the representation of phytoplankton diversity by size spectra allowed modification of model parameters, such that improved estimates of uptake rates of O₃⁻ and NH₄⁺ could be obtained for a dynamic eutrophic environment.