Common use of Medium Clause in Contracts

Medium. Anecdotal data from non-experts, Internet information that cites anecdotal non-expert sources, Internet information from uncertain/uncited sources, Horticultural, nursery notes or general web pages. Medium/Low No data or reference material available. Low Source: Department of Primary Industries, Victoria. 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 there is insufficient data on a particular pest to model the potential range, the NBMCC should provide advice to the NBMG on its best estimate. Preferred datasets Climate data from the Bureau of Meteorology can be used for actual climate variables—as opposed to WorldClim, which tends to be based on averages. Since many incursions originate from ports and airports—a distance to ports and airports is very useful. Similarly, water feature data can be analysed based on, for example, the distance to perennial or ephemeral rivers or lakes. Additional data sets that may be used as secondary data are: Bureau of Rural Sciences (BRS) land use/cover; Heritage features, such protected sites, World Heritage Areas and the national estate; and NVIS data sets for native vegetation; and VAST data to indicate vegetation condition. 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 BRS) 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 match regions of Australia with areas overseas where a pest is already established. This is then a prediction of where it may be possible for the pest to live if able and allowed to spread to all areas. An additional data layer for surface water will also be used for inland water pests. 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 of infestation of an inland water pest The following process is recommended for modelling the likely area of infestation: Identify the pest. Undertake an internet search for information on the pest (accessing both high and lesser quality information), particularly on distribution. Collect overseas and Australian distributional data (both validated and anecdotal, noting that this is for new outbreaks). Undertake Climatch modelling of validated data using: all 16 parameters for rainfall and temperature the agreed, current shapefile worlddata all.txt (or, if necessary, newwrldclm.txt) Euclidian match. Undertake Climatch modelling of anecdotal data using methodology as for item 5(d) of this attachment. Check the data to ensure there are no fundamental errors and validate the outliers, excluding (with an explanation) any errors and anomalies (e.g. non-viable populations). Overlay with surface water data/maps. Check the results with other experts. Include additional layers of data, when they are to be used in the analysis (such as the host species range to give the potential distribution of inland water pathogens, as it is assumed that they would generally require the presence of a suitable host species to survive). Any modifiers that are used must be incontrovertible and fully documented. Produce potential distribution map: ‘clip’ Climatch map in GIS to the overlay of the surface water threshold match of level 5 (Bomford modelling) include a confidence statement on the quality of the data. Attachment 5C Potential distribution of inland water diseases Introduction This attachment provides guidance on the process to be undertaken in determining the total potential distribution of an inland water disease and the potential percentage of the host population(s) that could be affected. The potential distribution of an inland water disease represents the distribution of any and all host species it can infect. This determination relates to calculating, in accordance with clause 7.2(d) of the agreement, what percentage of the total, potentially affected area is represented by a party’s jurisdiction which, in turn leads to a determination of the party’s percentage of risk and, subsequently, the number of people in that jurisdiction affected by a disease occurrence. This process does not include analysis of potential impacts as these would be considered in the risk assessment, technical feasibility and benefit:cost analyses. Fundamental assumptions for determining the potential distribution of inland water diseases In modelling the potential distribution of an inland water disease, the following fundamental assumptions apply: The contemporary situation will continue. The analysis will not include a consideration of possible future factors affecting the projected potential distribution, for example, climate change or changes in management actions. The disease has been evenly spread across susceptible host species in inland waters in Australia. The analysis will not be concerned with the pathway by which a disease might enter or has entered the country, nor with the potential rate of its spread, but, rather, with the areas in which the disease could persist and/or become established. There are no physiological or biological barriers to establishment or spread of the disease (i.e. the model assesses the area of climate match suitability where the disease could become endemic if it could successfully establish in one or several hosts). A general situation is to be relied on. While discussion of exceptions is important, the advice to be provided would be for the general situation. Data requirements for determining the potential distribution of inland water diseases Introduction The information required, or which would be useful, for determining the potential distribution of inland water diseases includes: essential data—a prerequisite for a determination valuable data—which will assist with a determination secondary data—which will also assist with a determination.

Medium. Anecdotal data from non-experts, Internet information that cites anecdotal non-expert sources, Internet information from uncertain/uncited sources, HorticulturalUnpublished reports from uncertain sources, nursery notes or general General web pages. Medium, Literature and data obtained from similar agent/Low No data host species (e.g. the same family or reference material availablegenus). Low Source: Department of Primary Industries, Victoria. 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 there is insufficient data on a particular pest disease agent or its potential hosts to model the potential range, then the NBMCC should provide advice cost-sharing model defaults to a population basis, i.e. the NBMG percentage contributed by each state and the Northern Territory is determined based on its best estimatethe population, where the combined percentages for each state and Northern Territory is equal to 100. Preferred datasets Catchment maps, since incursions move upstream and downstream from the index case. Climate data from the Bureau of Meteorology can be used for actual climate variables—as opposed to WorldClim, which tends to be based on averages. Since many incursions originate from ports and airports—ports, aquaculture facilities or towns, a distance to ports ports, aquaculture facilities and airports towns is very useful. Similarly, water feature data can be analysed based on, for example, the distance to perennial or ephemeral rivers or lakes. Additional data sets that may be used as secondary data are: Australian Bureau of Rural Agricultural and Resource Economics and Sciences (BRSABARES) land use/cover; cover Heritage features, such protected sites, World Heritage Areas and the national estate; and NVIS data sets for native vegetation; and VAST data to indicate vegetation condition. 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 BRSABARES) 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 match regions of Australia with areas overseas where a pest disease is already established. This is then a prediction of where it may be possible for the pest disease to live establish if able and allowed to spread to all areas. An additional data layer for surface water will also be used for inland water pestsdiseases. 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 of infestation of affected by an inland water pest disease Processes and procedures The following process is recommended for modelling the likely area of infestationinfection: Identify the pestdisease/infectious agent. Identify the potential host(s). Determine the minimum and maximum 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 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 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 environmental tolerances for the potential hosts. The most accurate environmental tolerance range of a potential hosts 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 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. Undertake an internet search for information on the pest disease (accessing both high and lesser quality information), particularly on distribution. Collect overseas and Australian distributional data (both validated and anecdotal, noting that this is for new outbreaks). Undertake Climatch modelling of validated data using: all 16 parameters for rainfall and temperature the agreed, current shapefile worlddata all.txt (or, if necessary, newwrldclm.txt) Euclidian match. Undertake Climatch modelling of anecdotal data using methodology as for item 5(d5.113.1(d) of this attachment. Check the data to ensure there are no fundamental errors and validate the outliers, excluding (with an explanation) any errors and anomalies (e.g. non-viable populations). Overlay with surface water data/maps. Check the results with other experts. Include additional layers of data, when they are to be used in the analysis (such as the host species range to give the potential distribution of inland water pathogens, as it is assumed that they would generally require the presence of a suitable host species to survive). Any modifiers that are used must be incontrovertible and fully documented. Produce potential distribution map: ‘clip’ Climatch map in GIS to the overlay of the surface water threshold match of level 5 (Bomford modelling) include a confidence statement on the quality of the data. Attachment 5C Potential distribution of inland water diseases Introduction This attachment provides guidance on the process to be undertaken in determining the total potential distribution of Trigger List Species If an inland water disease agent is currently on the OIE/Australia’s National list, the potential affected waterways for each state should be predetermined as part of preparedness measures. Percentage contribution figures for each state and the potential percentage Northern Territory are maintained by the Sub-Committee on Aquatic Animal Health (SCAAH) secretariat. SCAAH should review the methods, figures and guidelines used for national biosecurity incident response cost sharing analysis every two years. The formula should evolve to incorporate any new technology, data or species identified since the previous review. Parameters for cost-sharing of responses to disease incidents in inland water environments Population parameters With regard to disease incidents in inland water environments, the following parameters will be used to determine the Australian and jurisdictional populations. Each population value used should be the most recent and accurate available. The most recently available Australian Bureau of Statistics Australian Demographic Statistics Population parameters will be used to estimate populations. The New South Wales population will not include Jervis Bay. All population figures will include those of relevant islands in each jurisdiction. The sum of the host population(s) that could populations for the states and the Northern Territory will be affectedused as the total population of Australia. The potential distribution population of an inland water disease represents Jervis Bay is excluded from the distribution of any and all host species it can infect. This determination relates to calculating, in accordance with clause 7.2(d) calculations of the agreement, what percentage New South Wales population as it comes under the jurisdiction of the total, potentially affected area is represented by a party’s jurisdiction which, in turn leads to a determination of the party’s percentage of risk and, subsequently, the number of people in that jurisdiction affected by a disease occurrenceCommonwealth. This process The total Australian population does not include analysis the Australian Capital Territory population. Area of potential impacts as these would waterway parameters For the purposes of disease incidents in inland water environments the following parameters will be considered used. Each value should be the most recent, accurate figure available (see item 3.7 to this attachment). The figures will include inland water catchments on relevant islands in each jurisdiction. The New South Wales figure should not incorporate the risk assessment, technical feasibility and benefit:cost analyses. Fundamental assumptions for determining the potential distribution Australian Capital Territory’s (including Jervis Bay) area of inland water diseases In modelling waters. The sum of the potential distribution surface area of an the inland water disease, as defined by the GEODATA TOPO 250k dataset (see 16.2(d)). Formula for calculating cost-sharing arrangements for disease incidents in inland water environments Cost-sharing for disease incidents in inland water environments is calculated using the following fundamental assumptions apply: The contemporary situation will continue. The analysis will not include a consideration of possible future factors affecting the projected potential distribution, for example, climate change or changes in management actions. The disease has been evenly spread across susceptible host species in inland waters in Australia. The analysis will not be concerned with the pathway by which a disease might enter or has entered the country, nor with the potential rate of its spread, but, rather, with the areas in which the disease could persist and/or become established. There are no physiological or biological barriers to establishment or spread of the disease (i.e. the model assesses the area of climate match suitability where the disease could become endemic if it could successfully establish in one or several hosts). A general situation is to be relied on. While discussion of exceptions is important, the advice to be provided would be for the general situation. Data requirements for determining the potential distribution of inland water diseases Introduction The information required, or which would be useful, for determining the potential distribution of inland water diseases includes: essential data—a prerequisite for a determination valuable data—which will assist with a determination secondary data—which will also assist with a determination.steps: