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Analysis of Feed-base Audit

The purpose of the Feed Base Audit was to survey the agricultural Statistical Local Areas (SLA) (Australian Bureau of Statistics, 2011) in NSW, Victoria, Tasmania, South Australia and southern Western Australia and map the content and distribution of significant pasture types and species. The study region encompasses the Feed-base Investment Plan (FBIP) Agro-ecological Southern Australian zone (Feed-Base Investment Plan, 2010). A collaborative project between the State DPI’s and agricultural consultants was undertaken to assess the current status of temperate pastures in Southern Australia. Each State was assigned a coordinator who in turn provided information from district agronomists or agricultural consultants located across the States. This region supports approx. 10m cattle and 70m sheep (FBIP, 2010).

A survey that requested information on pasture types, their composition and associated attributes commenced throughout southern Australia in June 2011. The survey was based on 402 SLAs with the SLA as the base geographical unit. Data were based on “desk estimates” by trained agriculturalists. State coordination was conducted by Nigel Phillips (NSW), John Bowman (Victoria), Peter Ball (Tasmania), Tim Prance (SA) and Sue-Ellen Shaw (WA). A full list of the respondents is listed in Appendices (1, 2, 3, 4 and 5). Data from the completed survey database were transcribed into an MS Excel worksheet then into MS Access. Within and between data-tables were checked for consistency. Any outstanding or missing data were referred to the State coordinators for further comment. The survey provides estimates of the percentage each pasture types/class occupies within an SLA. These pasture types are then described in terms of species present, their botanical composition, sown cultivars, carrying capacity, condition of pasture, whether in decline, static or improving, contribution (Survey form, see Table 12). Once the State data were collated maps were produced outlining pasture species content and distribution, these were returned to the State coordinators for validation and a consensus opinion.

In 1993 a similar study, under the guidance of the National Pasture Improvement Committee (NPICC), an assessment of the actual and potential distribution of pasture species was prepared. This survey by Pearson (Pearson et al, 1999) and its subsequent data was compiled into a relational database with major significant pasture species subsequently mapped (Hill & Donald, 1997). These data were made available to MLA, GRDC, DA and AWI.

As part of the NPICC “Determination of Benefits from Pasture Improvement” (Hill, 1996, Hill & Donald 1997, 1999) there was an attempt to model potential zones of the major significant pasture species. These were validated by implementing higher resolution satellite information (Hill et al, 1997, 1999). These data were compiled implementing simple logistic models in response to long term mean climate.

This current report presents a summary of:- 

  • ​the structure of the survey audit database
  • the information about the surveyed database and information available within this database
  • a series of maps describing the distribution of significant pasture species.

The interpretation of the data acquired in this project and summarised here is for the user and reader to undertake. The survey data lend themselves to quite exhaustive analysis, and it is envisaged that they will be put to good use.​

Any publication of information arising from this survey carries a caveat. Users of the surveyed database should be aware that errors may exist due to the nature a “desk based” audit. These data are subjective in nature however they have been formulated by professionally qualified agriculturalists with many years of expert and local knowledge of the respective SLAs. The database will be made available in Microsoft Access Win7.


Title Size Date published
12.2MB 10/07/2012


Contract No. Title Start date End date Funding type
Analysis of Feed-base Audit
20/06/2011 26/03/2012

This page was last updated on 04/09/2018

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