Common use of Essential data Clause in Contracts

Essential data. At a minimum, a determination of the potential distribution of a marine disease requires the following types of data: Information underpinning correct diagnosis/taxonomic identification Known Australian potential host/s and their range. Data on the types and range of hosts or habitats for determining the potential distribution of marine diseases, provided it is available and incontrovertible Known minimum and maximum temperature and salinity tolerances for the disease agent and host species Knowledge of overseas host/s and geographical ranges of the aetiological agent Sea temperature and salinity for Australian coastal waters. Data on reproductive abilities of the host species and pathogen are valuable. The behaviour of the infected hosts including whether they are potamodromous (migrate within fresh water only); diadromous (travel between salt and fresh water); anadromous (live in the ocean mostly, and breed in fresh water); catadromous (live in fresh water, and breed in the ocean); amphidromous (move between fresh and salt water during their life cycle, but not to breed). Secondary data that directly affect the potential distribution of a disease can be used to determine the potential area of infection. Secondary data will only be used if all parties on the NBMCC agree and only if it is available, highly relevant and incontrovertible. Secondary data includes: Knowledge of overseas hosts and geographical ranges—this can be used to infer temperature and other environmental tolerances if reliable data is not available relating to both the disease agent and potential host species. Evidence for the tolerance of a disease agent to other limiting factors, such as temperature and salinity. If secondary data are known to limit the extent of potential distribution they should be combined with the modelling output to increase the robustness of the conclusions on potential distribution. It may also be useful to analyse a number of factors to establish the timing of management actions and response arrangements. Such factors may include: mechanisms of pathogen transmission knowledge of potential vectors natural barriers. When providing advice to the NMG, the NBMCC will need to advise on the level of confidence it has in the information underpinning its distribution map for a particular disease agent and its host species. The most accurate data available should be used. The best sources of data are: National Information Systems Published, peer-reviewed data. Museum/collection records, unpublished government records including unpublished survey reports, laboratory reports and catch-effort fisheries databases. Expert advice, properly elicited. Other sources of data that may be available are: free databases (e.g. Fishbase, Sealifebase) internet sources, where the level of confidence ranks (highest to lowest): validated data sources with open access validated data sources without open access survey data that uses recognised methods and open access (e.g. Google search). Where data are not validated, these sources should be checked and validated where possible. The data sources listed in item 3.5(d) of this attachment should be assessed according to their confidence rating (see table in item 3.5(h) of this attachment). Assessment of survey data should consider the methodology used in the survey. Where survey methodology is not available, a low confidence rating should be assigned to these data. Surveys which follow international standards, or OIE reporting standards (for animal diseases) should be assigned a higher confidence rating. Note that aquatic organism distribution data and aquatic parasite distribution data are non-parametric. Closely related host and pathogen species information should be used with caution as there is no direct correlation between surrogates and actual disease species. Likewise, host susceptibility data based on laboratory challenge studies should be used with caution. Formal and informal networks of experts are an essential source of information and data. These networks should be encouraged and communicated to ensure timely and effective decision-making. A table outlining the confidence rating of different data sources is provided below. Peer-reviewed scientific paper High High quality science or species specific books, non-peer reviewed scientific paper (e.g. conference proceedings), Personal communications from experts (e.g. PhD, or higher degree on species being assessed), Unpublished reports from highly reliable sources (e.g. commercial reports or honours theses, etc.), Internet information from Herbaria data, or Internet information that cites sources from the ‘Medium/High’ category above. Medium/ High Personal communications from people with experience with the agent/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. If there 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. 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) (▇▇▇.▇▇▇.▇▇▇.▇▇). 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. 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. None available at present. Cases will need to be evaluated as they occur. The potential distribution is the extent (in kilometres) of coast that may potentially be inhabited by hosts of a disease agent, i.e. ‘length of coastline affected’. Noting item 5.2 of this attachment, the following process is recommended to determine the total length of coastline for Australia and for each relevant state/territory: Identify the disease/infectious agent. Identify the potential host(s). Determine the minimum and maximum significant environmental tolerances for the disease agent. The most accurate environmental tolerance range 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 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 using 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 case-by-case 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 significant environmental tolerances for the hosts. The most accurate environmental tolerance range of a potential host/s 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 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 using both high and low confidence data. Other variables that are considered driving factors in the distribution of host/s, may be incorporated into the formula, as decided by the NBMCC on a case-by-case 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 sea temperature for Australian coastal waters. Use appropriate databases. Use the highest spatial resolution possible to allow the greatest possible discrimination between areas that may be, as opposed to those that would not be, within the potential range of a particular species. Using a Range Mapping tool and the data obtained from items 5.1(a) and (b) above to calculate the length of coastline within the range of the disease agent and its host species.

Essential data. At a minimum, a determination of the potential distribution of a marine disease requires the following types of data: Information underpinning correct diagnosis/taxonomic identification Known Australian potential host/s and their range. Data on the types and range of hosts or habitats for determining the potential distribution of marine diseases, provided it is available and incontrovertible Known minimum and maximum temperature and salinity tolerances for the disease agent and host species Knowledge of overseas host/s and geographical ranges of the aetiological agent Sea temperature and salinity for Australian coastal waters. Data on reproductive abilities of the host species and pathogen are valuable. The behaviour of the infected hosts including whether they are potamodromous (migrate within fresh water only); diadromous (travel between salt and fresh water); anadromous (live in the ocean mostly, and breed in fresh water); catadromous (live in fresh water, and breed in the ocean); amphidromous (move between fresh and salt water during their life cycle, but not to breed). Secondary data that directly affect the potential distribution of a disease can be used to determine the potential area of infection. Secondary data will only be used if all parties on the NBMCC agree and only if it is available, highly relevant and incontrovertible. Secondary data includes: Knowledge of overseas hosts and geographical ranges—this can be used to infer temperature and other environmental tolerances if reliable data is not available relating to both the disease agent and potential host species. Evidence for the tolerance of a disease agent to other limiting factors, such as temperature and salinity. If secondary data are known to limit the extent of potential distribution they should be combined with the modelling output to increase the robustness of the conclusions on potential distribution. It may also be useful to analyse a number of factors to establish the timing of management actions and response arrangements. Such factors may include: mechanisms of pathogen transmission knowledge of potential vectors natural barriers. When providing advice to the NMG, the NBMCC will need to advise on the level of confidence it has in the information underpinning its distribution map for a particular disease agent and its host species. The most accurate data available should be used. The best sources of data are: National Information Systems Published, peer-reviewed data. Museum/collection records, unpublished government records including unpublished survey reports, laboratory reports and catch-effort fisheries databases. Expert advice, properly elicited. Other sources of data that may be available are: free databases (e.g. Fishbase, Sealifebase) internet sources, where the level of confidence ranks (highest to lowest): validated data sources with open access validated data sources without open access survey data that uses recognised methods and open access (e.g. Google search). Where data are not validated, these sources should be checked and validated where possible. The data sources listed in item 3.5(d) of this attachment should be assessed according to their confidence rating (see table in item 3.5(h) of this attachment). Assessment of survey data should consider the methodology used in the survey. Where survey methodology is not available, a low confidence rating should be assigned to these data. Surveys which follow international standards, or OIE reporting standards (for animal diseases) should be assigned a higher confidence rating. Note that aquatic organism distribution data and aquatic parasite distribution data are non-parametric. Closely related host and pathogen species information should be used with caution as there is no direct correlation between surrogates and actual disease species. Likewise, host susceptibility data based on laboratory challenge studies should be used with caution. Formal and informal networks of experts are an essential source of information and data. These networks should be encouraged and communicated to ensure timely and effective decision-making. A table outlining the confidence rating of different data sources is provided below. Peer-reviewed scientific paper High High quality science or species specific books, non-peer reviewed scientific paper (e.g. conference proceedings), Personal communications from experts (e.g. PhD, or higher degree on species being assessed), Unpublished reports from highly reliable sources (e.g. commercial reports or honours theses, etc.), Internet information from Herbaria data, or Internet information that cites sources from the ‘Medium/High’ category above. Medium/ High Personal communications from people with experience with the agent/species under assessment, Information from general reference books, 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 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. If there 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. 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) (▇▇▇.▇▇▇.▇▇▇.▇▇). 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. 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. None available at present. Cases will need to be evaluated as they occur. The potential distribution is the extent (in kilometres) of coast that may potentially be inhabited by hosts of a disease agent, i.e. ‘length of coastline affected’. Noting item 5.2 of this attachment, the following process is recommended to determine the total length of coastline for Australia and for each relevant state/territory: Identify the disease/infectious agent. Identify the potential host(s). Determine the minimum and maximum significant environmental tolerances for the disease agent. The most accurate environmental tolerance range 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 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 using 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 case-by-by- case 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 significant environmental tolerances for the hosts. The most accurate environmental tolerance range of a potential host/s 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 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 using both high and low confidence data. Other variables that are considered driving factors in the distribution of host/s, may be incorporated into the formula, as decided by the NBMCC on a case-by-case 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 sea temperature for Australian coastal waters. Use appropriate databases. Use the highest spatial resolution possible to allow the greatest possible discrimination between areas that may be, as opposed to those that would not be, within the potential range of a particular species. Using a Range Mapping tool and the data obtained from items 5.1(a) and (b) above to calculate the length of coastline within the range of the disease agent and its host species.