Does terrestrial epidemiology apply to marine systems?

Most of epidemiological theory has been developed for terrestrial systems, but the significance of disease in the ocean is now being recognized. However, the extent to which terrestrial epidemiology can be directly transferred to marine systems is uncertain. Many broad types of disease-causing organism occur both on land and in the sea, and it is clear that some emergent disease problems in marine environments are caused by pathogens moving from terrestrial to marine systems. However, marine systems are qualitatively different from terrestrial environments, and these differences affect the application of modelling and management approaches that have been developed for terrestrial systems. Phyla and body plans are more diverse in marine environments and marine organisms have different life histories and probably different disease transmission modes than many of their terrestrial counterparts. Marine populations are typically more open than terrestrial ones, with the potential for long-distance dispersal of larvae. Potentially, this might enable unusually rapid propagation of epidemics in marine systems, and there are several examples of this. Taken together, these differences will require the development of new approaches to modelling and control of infectious disease in the ocean.

Towards intelligent aquaculture. Development of an early Biological Warning System to monitor exposure to contaminants and fish welfare: from artificial vision to systems modelling

161 p.

An overview of the marine systems simulator (MSS) : a Simulink toolbox for marine control systems

The Marine Systems Simulator (MSS) is an environment which provides the necessary resources for rapid implementation of mathematical models of marine systems with focus on control system design. The simulator targets models¡Xand provides examples ready to simulate¡Xof different floating structures and its systems performing various operations. The platform adopted for the development of MSS is Matlab/Simulink. This allows a modular simulator structure, and the possibility of distributed development. Openness and modularity of software components have been the prioritized design principles, which enables a systematic reuse of knowledge and results in efficient tools for research and education. This paper provides an overview of the structure of the MSS, its features, current accessability, and plans for future development.

Systems modelling of mine water and energy tradeoffs

In the coming decades, the mining industry faces the dual challenge of lowering both its water and energy use. This presents a difficulty since technological advances that decrease the use of one can increase the use of the other. Historically, energy and water use have been modelled independently, making it difficult to evaluate the true costs and benefits from water and energy improvements. This paper presents a hierarchical systems model that is able to represent interconnected water and energy use at a whole of site scale. In order to explore the links between water and energy four technologies advancements have been modelled: use of dust suppression additives, the adoption of thickened tailings, the transition to dry processing and the incorporation of a treatment plant. The results show a synergy between decreased water and energy use for dust suppression additives, but a trade-off for the others.

Frequency-motivated observer design for the prediction of parametric roll resonance control applications in marine systems

This work deals with estimators for predicting when parametric roll resonance is going to occur in surface vessels. The roll angle of the vessel is modeled as a second-order linear oscillatory system with unknown parameters. Several algorithms are used to estimate the parameters and eigenvalues of the system based on data gathered experimentally on a 1:45 scale model of a tanker. Based on the estimated eigenvalues, the system predicts whether or not parametric roll occurred. A prediction accuracy of 100% is achieved for regular waves, and up to 87.5% for irregular waves.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

Predicting risk and benefit a priori in biological control of invasive plant species: a systems modelling approach

While the method using specialist herbivores in managing invasive plants (classical biological control) is regarded as relatively safe and cost-effective in comparison to other methods of management, the rarity of strict monophagy among insect herbivores illustrates that, like any management option, biological control is not risk-free. The challenge for classical biological control is therefore to predict risks and benefits a priori. In this study we develop a simulation model that may aid in this process. We use this model to predict the risks and benefits of introducing the chrysomelid beetle Charidotis auroguttata to manage the invasive liana Macfadyena unguis-cati in Australia. Preliminary host-specificity testing of this herbivore indicated that there was limited feeding on a non-target plant, although the non-target was only able to sustain some transitions of the life cycle of the herbivore. The model includes herbivore, target and non-target life history and incorporates spillover dynamics of populations of this herbivore from the target to the non-target under a variety of scenarios. Data from studies of this herbivore in the native range and under quarantine were used to parameterize the model and predict the relative risks and benefits of this herbivore when the target and non-target plants co-occur. Key model outputs include population dynamics on target (apparent benefit) and non-target (apparent risk) and fitness consequences to the target (actual benefit) and non-target plant (actual risk) of herbivore damage. The model predicted that risk to the non-target became unacceptable (i.e. significant negative effects on fitness) when the ratio of target to non-target in a given patch ranged from 1:1 to 3:2. By comparing the current known distribution of the non-target and the predicted distribution of the target we were able to identify regions in Australia where the agent may be pose an unacceptable risk. By considering risk and benefit simultaneously, we highlight how such a simulation modelling approach can assist scientists and regulators in making more objective decisions a priori, on the value of releasing specialist herbivores as biological control agents.

A complex systems modelling approach for decentralized simulation of electrical microgrids

ICECCS 2010

Report of the sub-regional workshop to validate the scoping study of nutrient pollution on the coastal and marine systems of South Asia, Colombo, Sri Lanka, 21-22 May, 2014

The workshop agenda included: presentations from collaborative institutions, national governments and resource persons; a draft scoping study on nutrient loading; and an ecosystem approach to pollution management was tested.