Particle scattering is an important process that determines both the light penetration through the water column and water‐leaving light. Backscattering, in combination with absorption, determines the remote‐sensing reflectance that is used in ocean color algorithms. Additionally, the wavelength dependence of the backscattering ratio can be related to the particle composition in seawater. Here, we examine the magnitude and the spectral behavior of the backscattering ratio against other bio‐optical properties based on a comprehensive set of continuous measurements collected in coastal waters of the Great Barrier Reef over 3 years. The site is located offshore of a major river, and close to the cross‐shelf transition of bottom sediments from terrigenous muds to marine carbonates. The backscattering ratio measured at 650 nm clearly clustered the data into two types. Type 1, which we identified as terrigenous mud with a low organic fraction, is characterized by backscattering ratio below 0.011 with a mean value of 0.005. Type 2, which we identified as marine carbonate with a higher organic fraction, has backscattering ratio above 0.011 with a mean value of 0.02. Within 3 years, study site was exposed to type 1‐dominated particles 13% of the time, and type 2 87%. The observed changes in the backscattering ratio at this one coastal site are as large as the variability seen throughout the global ocean. This work provides a better understanding of processes determining the optical characteristics and insights into optical parameterizations that can be used in process‐based optical modeling of the Great Barrier Reef.
Abstract:Eutrophication is an increasing problem in coastal waters of the Baltic Sea. Moreover, algal blooms, which occur every summer in the Gulf of Gdansk can deleteriously impact human health, the aquatic environment, and economically important fisheries, tourism, and recreation industries. Traditional laboratory-based techniques for water monitoring are expensive and time consuming, which usually results in limited numbers of observations and discontinuity in space and time. The use of hyperspectral radiometers for coastal water observation provides the potential for more detailed remote optical monitoring. A statistical approach to develop local models for the estimation of optically significant components from in situ measured hyperspectral remote sensing reflectance in case 2 waters is presented in this study. The models, which are based on empirical orthogonal function (EOF) analysis and stepwise multilinear regression, allow for the estimation of parameters strongly correlated with phytoplankton (pigment concentration, absorption coefficient) and coloured detrital matter abundance (absorption coefficient) directly from reflectance spectra measured in situ. Chlorophyll a concentration, which is commonly used as a proxy for phytoplankton biomass, was retrieved with low error (median percent difference, MPD = 17%, root mean square error RMSE = 0.14 in log 10 space) and showed a high correlation with chlorophyll a measured in situ (R = 0.84). Furthermore, phycocyanin and phycoerythrin, both characteristic pigments for cyanobacteria species, were also retrieved reliably from reflectance with MPD = 23%, RMSE = 0.23, R 2 = 0.77 and MPD = 24%, RMSE = 0.15, R 2 = 0.74, respectively. The EOF technique proved to be accurate in the derivation of the absorption spectra of phytoplankton and coloured detrital matter (CDM), with R 2 (λ) above 0.83 and RMSE around 0.10. The approach was also applied to satellite multispectral remote sensing reflectance data, thus allowing for improved temporal and spatial resolution compared with the in situ measurements. The EOF method tested on simulated Medium Resolution Imaging Spectrometer (MERIS) or Ocean and Land Colour Instrument (OLCI) data resulted in RMSE = 0.16 for chl-a and RMSE = 0.29 for phycocyanin. The presented methods, applied to both in situ and satellite data, provide a powerful tool for coastal monitoring and management.
Abstract. Since the mid-1990s, Australia's Commonwealth Science Industry and Research Organisation (CSIRO) has been developing a biogeochemical (BGC) model for coupling with a hydrodynamic and sediment model for application in estuaries, coastal waters and shelf seas. The suite of coupled models is referred to as the CSIRO Environmental Modelling Suite (EMS) and has been applied at tens of locations around the Australian continent. At a mature point in the BGC model's development, this paper presents a full mathematical description, as well as links to the freely available code and user guide. The mathematical description is structured into processes so that the details of new parameterisations can be easily identified, along with their derivation. In EMS, the underwater light field is simulated by a spectrally resolved optical model that calculates vertical light attenuation from the scattering and absorption of 20+ optically active constituents. The BGC model itself cycles carbon, nitrogen, phosphorous and oxygen through multiple phytoplankton, zooplankton, detritus and dissolved organic and inorganic forms in multiple water column and sediment layers. The water column is dynamically coupled to the sediment to resolve deposition, resuspension and benthic–pelagic biogeochemical fluxes. With a focus on shallow waters, the model also includes detailed representations of benthic plants such as seagrass, macroalgae and coral polyps. A second focus has been on, where possible, the use of geometric derivations of physical limits to constrain ecological rates. This geometric approach generally requires population-based rates to be derived from initially considering the size and shape of individuals. For example, zooplankton grazing considers encounter rates of one predator on a prey field based on summing relative motion of the predator with the prey individuals and the search area; chlorophyll synthesis includes a geometrically derived self-shading term; and the bottom coverage of benthic plants is calculated from their biomass using an exponential form derived from geometric arguments. This geometric approach has led to a more algebraically complicated set of equations when compared to empirical biogeochemical model formulations based on populations. But while being algebraically complicated, the model has fewer unconstrained parameters and is therefore simpler to move between applications than it would otherwise be. The version of EMS described here is implemented in the eReefs project that delivers a near-real-time coupled hydrodynamic, sediment and biogeochemical simulation of the Great Barrier Reef, northeast Australia, and its formulation provides an example of the application of geometric reasoning in the formulation of aquatic ecological processes.
Abstract. Since the mid 1990s, Australia's Commonwealth Science Industry and Research Organisation (CSIRO) has developed a biogeochemical (BGC) model for coupling with a hydrodynamic and sediment model for application in estuaries, coastal waters and shelf seas. The suite of coupled models is referred to as the CSIRO Environmental Modelling Suite (EMS) and has been applied at tens of locations around the Australian continent. At a mature point in the BGC model's development, this paper presents a full mathematical description, as well as links to the freely available code and User Guide. The mathematical description is structured into processes so that the details of new parameterisations can be easily identified, along with their derivation. The EMS BGC model cycles carbon, nitrogen, phosphorous and oxygen through multiple phytoplankton, zooplankton, detritus and dissolved organic and inorganic forms in multiple water column and sediment layers. The underwater light field is simulated by a spectrally-resolved optical model that includes the calculation of water-leaving reflectance for validation with remote sensing. The water column is dynamically coupled to the sediment to resolve deposition, resuspension and benthic-pelagic biogeochemical fluxes. With a focus on shallow waters, the model also includes particularly-detailed representations of benthic plants such as seagrass, macroalgae and coral polyps. A second focus has been on, where possible, the use of geometric derivations of physical limits to constrain ecological rates, which generally requires population-based rates to be derived from initially considering the size and shape of individuals. For example, zooplankton grazing considers encounter rates of one predator on a prey field based on summing relative motion of the predator with the prey individuals and the search area, chlorophyll synthesis includes a geometrically-derived self-shading term, and the bottom coverage of benthic plants is generically-related to their biomass using an exponential form derived from geometric arguments. This geometric approach has led to a more algebraically-complicated set of equations when compared to more empirical biogeochemical model formulations. But while being algebraically-complicated, the model has fewer unconstrained parameters and is therefore simpler to move between applications than it would otherwise be. The version of the biogeochemistry described here is implemented in the eReefs project that is delivering a near real time coupled hydrodynamic, sediment and biogeochemical simulation of the Great Barrier Reef, northeast Australia, and its formulation provides an example of the application of geometric reasoning in the formulation of aquatic ecological processes.
Mass coral bleaching has emerged in the 21st century as the greatest threat to the health of the world's reefs. A sophisticated process understanding of bleaching at the polyp scale has now been achieved through laboratory and field studies, but this knowledge is yet to be applied in mechanistic models of shelf-scale reef systems. In this study we develop a mechanistic model of the coral-symbiont relationship that considers temperature-mediated build-up of reactive oxygen species due to excess light, leading to zooxanthellae expulsion. The model explicitly represents the coral host biomass, as well as zooxanthellae biomass, intracellular pigment concentration, nutrient status, and the dynamics of reaction centres and the xanthophyll cycle. Photophysiological processes represented include photoadaptation, xanthophyll cycle dynamics, and reaction centre state transitions. The mechanistic model of the coral-symbiont relationship is incorporated into a $\sim$1 km resolution coupled hydrodynamic - biogeochemical model that encompasses the entire $\sim$2000 km length of the Great Barrier Reef. A simulation of the 2016 bleaching event shows the model is able to capture the broadscale features of the observed bleaching, but fails to capture bleaching on offshore reefs due to the model's grid being unable to resolve the bathymetry of shallow platforms surrounded by deep water. To further analyse the model behaviour, a $\sim$200 m resolution nested simulation of Davies Reef (18$^{\circ}$49'S, 147$^{\circ}$38'E) is undertaken. We use this nested model to demonstrate the depth gradient in zooxanthellae response to thermal stress. Finally, we discuss the uncertainties in the bleaching model, which lie primarily in quantifying the link between reactive oxygen build-up and the expulsion process. Through the mechanistic representation of environmental forcing, this model of coral bleaching applied in realistic environmental conditions has the potential to generate more detailed predictions than the presently-available satellite-based coral bleaching metrics, and can be used to evaluate proposed management strategies.
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