Due to the scale of the input data, the analysis should be made at the native resolution level and presented as a 10 km x 10 km grid. Modelling software Climatch (Euclidian matching as implemented by ABARES) is the preferred climate modelling software. While Climatch, like all models, has limitations, its overall logic is sound and it has the advantage of producing a single, reproducible climate match output from a set of agreed inputs. While it is acknowledged that the predictions have uncertainty attached to them, there will be no systematic errors that consistently disadvantage a particular jurisdiction. Climatch uses a number of data parameters, such as temperature and rainfall, to regions of Australia with areas overseas where a disease is already established. This is then a prediction of where it may be possible for the disease to establish if able and allowed to spread to all areas. An additional data layer for surface water will also be used for inland water diseases. Suitable habitat will be wherever surface water occurs in an area of suitable climate. For cost-sharing purposes a threshold of climate match level 5 and higher will be used for Climatch modelling. Processes and procedures for modelling the likely area affected by an inland disease Processes and procedures The following process is recommended for modelling the likely area of infection: Identify the disease/infectious agent. Identify the potential host(s). Determine the minimum and maximum environmental tolerances for the disease agent. The most accurate environmental tolerance of a disease agent should be used when determining the potential distribution. Dependent on the species information available, this will be determined by combining environmental tolerance data on a host species, noting that the environmental tolerance data used may still overestimate the potential range. Only if the abovementioned option is not available should low confidence data be used (in order of preference). Environmental data should be sourced from a literature review process both high and low confidence data. Other variables that are considered driving factors in the distribution of a disease may be incorporated into the formula, as decided by the NBMCC on a basis. Where additional layers of data are to be used in the analysis they will also need to be scientifically determined. Any modifiers that are used must be incontrovertible and fully documented. Determine the minimum and maximum environmental tolerances for the potential hosts.
Personal communications from people with experience with the agent/host species under assessment, Information from general reference books Data that relates to indirect tolerance ranges (n.b. this includes laboratory testing, in situ environmental ranges) Internet information that cites sources from the ‘Medium’ category, or Internet information from government or university websites (e.g. Australian state governments, or the USDA) Medium Anecdotal data from non-experts, Internet information that cites anecdotal non-expert sources, Internet information from uncertain/uncited sources, Unpublished reports from uncertain sources, General web pages. Literature and data obtained from similar agent/host species (e.g. the same family or genus). Low There is a risk that increasing the acceptable level of confidence in the quality of the data will reduce the quality of a prediction by reducing representativeness. Sensitivity analysis is needed to determine the influence of poor quality data. Effort can then be directed to verifying influential, poor quality data. Insufficient data If is insufficient data on a particular disease agent or its potential hosts to model the potential range, then the cost-sharing model defaults to a population basis, i.e. the percentage contributed by each state and the Northern Territory is determined based on the population, where the combined percentages for each state and Northern Territory is equal to 100. Preferred datasets The most recently available Australian Bureau of Statistics parameters will be used to estimate the length of coastline. They are published in the 1301.0 Year Book Australia, Geography of Australia section (or the superseding document) (www.abs.gov.au). The New South Wales coastline will not include the Jervis Bay territory. Temperature tolerance data should be obtained from a literature review process using both high and low confidence data. The most appropriate sources of data will be used to determine sea temperatures, bearing in mind that sea surface temperatures change seasonally, are influenced by local weather and that differences occur with changing depth. Additional data sets that may be used as secondary data are: ABARES Heritage features, such protected sites, World Heritage Areas and the national estate. (e) Due to the scale of the input data, the analysis should be made at the native resolution level and presented as a 10 km x 10 km grid. Modelling software for determining the potential distribution of hosts of marine diseases None available at present. Cases will need to be evaluated as they occur.