Monitoring, Predicting, and Managing One of the Seven Natural Wonders of the World

Schiller, A.; Herzfeld, Mike; Brinkman, Richard; Stuart, Greg

doi:10.1175/bams-d-12-00202.1

Cited by 34 publications

(13 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…11). More recently, the EMS BGC has been thoroughly assessed against remotely-sensed and in situ observations on the Great Barrier Reef, as part of the eReefs project (Schiller et al, 2014). The assessment of version B1p0 of the eReefs marine model configuration of the EMS included a 497 page report documenting a range of model configurations (4 km, 1 km and relocatable fine resolution versions) (Herzfeld et al, 2016).…”

Section: Model Evaluationmentioning

confidence: 99%

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

Baird¹,

Wild-Allen²,

Parslow³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Model Evaluationmentioning

confidence: 99%

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

Baird¹,

Wild-Allen²,

Parslow³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…We used the eReefs coupled hydrodynamic, sediment and BGC modelling system (Schiller et al, 2014). The hydrodynamic model is a fully 3-D finite-difference baroclinic model based on the 3-D equations of momentum, continuity and conservation of heat and salt, employing the hydrostatic and Boussinesq assumptions (Herzfeld, 2006;Herzfeld and Gillibrand, 2015).…”

Section: The Ereefs Modelling Systemmentioning

confidence: 99%

Use of remote-sensing reflectance to constrain a data assimilating marine biogeochemical model of the Great Barrier Reef

et al. 2016

View full text Add to dashboard Cite

Abstract. Skillful marine biogeochemical (BGC) models are required to understand a range of coastal and global phenomena such as changes in nitrogen and carbon cycles. The refinement of BGC models through the assimilation of variables calculated from observed in-water inherent optical properties (IOPs), such as phytoplankton absorption, is problematic. Empirically derived relationships between IOPs and variables such as chlorophyll-a concentration (Chl a), total suspended solids (TSS) and coloured dissolved organic matter (CDOM) have been shown to have errors that can exceed 100 % of the observed quantity. These errors are greatest in shallow coastal regions, such as the Great Barrier Reef (GBR), due to the additional signal from bottom reflectance. Rather than assimilate quantities calculated using IOP algorithms, this study demonstrates the advantages of assimilating quantities calculated directly from the less error-prone satellite remote-sensing reflectance (RSR). To assimilate the observed RSR, we use an in-water optical model to produce an equivalent simulated RSR and calculate the mismatch between the observed and simulated quantities to constrain the BGC model with a deterministic ensemble Kalman filter (DEnKF). The traditional assumption that simulated surface Chl a is equivalent to the remotely sensed OC3M estimate of Chl a resulted in a forecast error of approximately 75 %. We show this error can be halved by instead using simulated RSR to constrain the model via the assimilation system. When the analysis and forecast fields from the RSR-based assimilation system are compared with the non-assimilating model, a comparison against independent in situ observations of Chl a, TSS and dissolved inorganic nutrients (NO 3 , NH 4 and DIP) showed that errors are reduced by up to 90 %. In all cases, the assimilation system improves the simulation compared to the non-assimilating model. Our approach allows for the incorporation of vast quantities of remote-sensing observations that have in the past been discarded due to shallow water and/or artefacts introduced by terrestrially derived TSS and CDOM or the lack of a calibrated regional IOP algorithm.

show abstract

“…The model has a horizontal resolution of 167 m, a vertical z-coordinate scheme with 24 fixed zlevels, and includes meteorological, tidal and open ocean forcing. A 1 km resolution three-dimensional (3D) hydrodynamic model of the whole GBR region is used for oceanic boundary conditions (Schiller et al 2014). Heron Island reefʼs biogeography can be divided into four types of coral communities, whose distribution has been obtained from Roelfsema et al (2002) (figure 1).…”

Section: Hydrodynamic and Carbon Chemistry Models And Set-upmentioning

confidence: 99%

Optimising reef-scale CO ₂ removal by seaweed to buffer ocean acidification

Mongin

Baird

Hadley

et al. 2016

Environ. Res. Lett.

View full text Add to dashboard Cite

The equilibration of rising atmospheric CO 2 with the ocean is lowering pH in tropical waters by about 0.01 every decade. Coral reefs and the ecosystems they support are regarded as one of the most vulnerable ecosystems to ocean acidification, threatening their long-term viability. In response to this threat, different strategies for buffering the impact of ocean acidification have been proposed. As the pH experienced by individual corals on a natural reef system depends on many processes over different time scales, the efficacy of these buffering strategies remains largely unknown. Here we assess the feasibility and potential efficacy of a reef-scale (a few kilometers) carbon removal strategy, through the addition of seaweed (fleshy multicellular algae) farms within the Great Barrier Reef at the Heron Island reef. First, using diagnostic time-dependent age tracers in a hydrodynamic model, we determine the optimal location and size of the seaweed farm. Secondly, we analytically calculate the optimal density of the seaweed and harvesting strategy, finding, for the seaweed growth parameters used, a biomass of 42 g N m −2 with a harvesting rate of up 3.2 g N m −2 d −1 maximises the carbon sequestration and removal. Numerical experiments show that an optimally located 1.9 km 2 farm and optimally harvested seaweed (removing biomass above 42 g N m −2 every 7 d) increased aragonite saturation by 0.1 over 24 km 2 of the Heron Island reef. Thus, the most effective seaweed farm can only delay the impacts of global ocean acidification at the reef scale by 7-21 years, depending on future global carbon emissions. Our results highlight that only a kilometer-scale farm can partially mitigate global ocean acidification for a particular reef.

show abstract

Monitoring, Predicting, and Managing One of the Seven Natural Wonders of the World

Cited by 34 publications

References 10 publications

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

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

Use of remote-sensing reflectance to constrain a data assimilating marine biogeochemical model of the Great Barrier Reef

Optimising reef-scale CO ₂ removal by seaweed to buffer ocean acidification

Contact Info

Product

Resources

About

Monitoring, Predicting, and Managing One of the Seven Natural Wonders of the World

Cited by 34 publications

References 10 publications

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

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

Use of remote-sensing reflectance to constrain a data assimilating marine biogeochemical model of the Great Barrier Reef

Optimising reef-scale CO 2 removal by seaweed to buffer ocean acidification

Contact Info

Product

Resources

About

Optimising reef-scale CO ₂ removal by seaweed to buffer ocean acidification