Marine resources, biophysical processes, and environmental management of a tropical shelf seaway: Torres Strait, Australia-Introduction to the special issue

This special issue of Continental Shelf Research contains 20 papers giving research results produced as part of Australia's Torres Strait Co-operative Research Centre (CRC) Program, which was funded over a three-year period during 2003-2006. Marine biophysical, fisheries, socioeconomic-cultural and extension research in the Torres Strait region of northeastern Australia was carried out to meet three aims: 1) support the sustainable development of marine resources and minimize impacts of resource use in Torres Strait; 2) enhance the conservation of the marine environment and the social, cultural and economic well being of all stakeholders, particularly the Torres Strait peoples; and 3) contribute to effective policy formulation and management decision making. Subjects covered, including commercial and traditional fisheries management, impacts of anthropogenic sediment inputs on seagrass meadows and communication of science results to local communities, have broad applications to other similar environments.

Simple software processes and tests improve the reliability and usefulness of a model.

Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a model.