A mechanistic model of coral bleaching due to temperature-mediated light-driven reactive oxygen build-up in zooxanthellae.

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

CSIRO Environmental Modelling Suite (EMS): Scientific description of the optical and biogeochemical models (vB3p0)

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. </p