Delivering a land condition framework for grazing land management education

Project Name:

Delivering a land condition framework for grazing land management education

Rangelands ecosystems, on which pastoral enterprises are based, are relatively sensitive and damage through poor management can be very slow to reverse. Effective monitoring of land condition offers the hope that decline in land condition can be spotted and corrected at an early stage. As land managers come under increasing scrutiny from outside, monitoring can also offer a means of ‘proving’ good land management. However, monitoring is complex and time consuming.

In this project, Dr Terry Beutel and team have drawn together field data, scientific literature and the experiences of land managers and agency staff to develop a new system for monitoring land condition across large tracts of the Mulga and Mitchell grass bioregions. Land condition assessments were made at about 60 sites in Western Queensland and expert advice came from wool producers and agency staff. The final product of this project is a classification system based on a modified index for use on perennial grass basal area. The framework has been designed for producers participating in the Grazing Land Management (GLM) and Stocktake programs.

The new framework replaces an existing system of verbal descriptors in six land zones across the Mulga and Mitchell grass bioregions. It improves on the older system because it relies on the objective measurement of perennial grass basal area (PGBA) and analysis of the 3P (perennial, palatable and productive grasses) and OP (other perennial) status. Extension materials developed as part of the project include a manual for measuring Perennial Cover Index (PCI) in Mitchell grass and Mulga land zones, which can also be used in programs such as GLM and Stocktake.

Other developments undertaken by the project team include customising the Stocktake feed budgeting system to mulga and Mitchell grass regions. As well, economic analysis linking resource condition to profitability has been conducted by trial and amendment of Breedewe and SheepDyn software. Producers can access the model via DPI&F staff if they wish to assess alternative scenarios alternative scenarios to those already developed for GLM.

A range of products and more detailed information sources are listed towards the bottom of this page in the Want to Know More? section, below.

Aims

The project aimed to refine the ABCD framework into a more user friendly and more objective system for assigning land condition classifications to pastoral land in western Queensland. The foundation of Terry’s alternative framework is measurement of the basal area of perennial grass tussocks (or “Perennial Grass Basal Area” — PGBA) and the proportion of this provided by “perennial, palatable and productive” species (the ‘3P’ grasses).

Perennial grass basal area is a useful index of total pasture production in western Queensland, with higher PGBA closely associated with higher pasture production. Perennial grasses however are not all equal in terms of their value as forage, and the 3P grasses are particularly important in terms of their forage production value. Basal Area is the important parameter in the rangelands, rather than ground cover, as ground cover may be temporarily low due to seasonal conditions. Basal area on the other hand remains relatively constant for any particular class, regardless of season.

Ancillary aims in the project were: to develop, test and extend a forage budgeting tool so that producers can more effectively manage grazing pressure; and to link land condition targets to economic outcomes.

Outcomes

At the heart of Terry’s approach is the measurement of two components of PGBA: basal area of the 3P grasses and basal area of other perennial grasses (‘OP’ grasses). Under the new framework OP basal area is discounted to allow for the lower forage value of OP species, and the discounted OP basal area is summed with 3P basal area to provide a perennial cover index (PCI) for the site. ABCD condition for the site is then determined by the ratio of site PCI to a benchmark PCI for that land zone.

This modified framework improves on the previous verbal descriptors in a number of ways. Firstly, it focuses on only two aspects of the rangeland resource (PGBA and tussocks’ 3P status), rather than multiple dimensions of woodland, soil and pasture condition, which should simplify extension of the system to land managers. Secondly, it focuses management attention on perennial grasses, which are not only key forage producers, but also familiar to most producers. These improvements should enhance uptake, and leave less room for mismeasurement of land condition. Finally, and in contrast to the old framework, because the classification is based only on the ratio of site PCI to benchmark PCI, any assessment can have only one classification outcome, which should decrease the likelihood of misinterpreting landscape measurements and wrongly assigning ABCD classifications.

There were several steps in developing the new framework. Firstly Terry and team developed benchmark Perennial Cover Indices (PCIs) for six land zones across the mulga and Mitchell grass regions, by measuring PGBA on 59 sites that were visually assessed to be in A Condition. Next Terry derived discounting factors for the Other Perennials (‘OP’ grasses). The discount factor was developed by referring to previous research (which showed a paucity of quantitative information) and consultation with experts, including agency staff and experienced sheep and cattle producers. Detail on some of the considerable challenges in this endeavour can be found in Terry’s scientific report in the Want to Know More? section below. The next step was to calibrate the PCIs with the forage production classes of the ABCD framework. Once the components of the framework were derived, Terry and team assembled them into a manual called “The ABCD pasture condition guide - Mulga and Mitchell grass”, (see the Want to Know More? section) and tested the approach in the GLM and Stocktake extension programs with 68 producers.

The framework has been developed with ease of use in mind, as Terry says:” the lack of even photographic monitoring on most properties, by far the simplest monitoring approach, suggests that any [monitoring] system … will not be adopted by all producers”. In his scientific paper, Terry suggests a number of areas for more research to refine the framework further.

This project also customised the Stocktake feed budgeting system to the mulga and Mitchell grass regions. Land zone description sheets were developed by experienced scientific and extension staff using data from WARLUS data, and accumulated the experience of agency personnel. Productivity data were modelled using the GRASP pasture production model, in combination with data collected by Dr PW Johnston and colleagues in 1996. A brochure called ‘Mulga as a feed source’ was developed from existing DPI&F web pages, printed materials, and scientific and extension experience, to facilitate discussion on the role of mulga in feed budgets.

The ecomomics module was developed through trial and amendment of the Breedewe and SheepDyn software. Basic flocks were compiled and sheep management scenarios were developed for mulga and Mitchell grass region GLMs. Relationships between land condition, stocking rate, carrying capacity and production were based on consultations with research and extension officers, literature review and the principles and substantiated information outlined in the GLM workshops. The software spreadsheets are now calculating flock structures and financial outcomes correctly. Several management case studies were examined and documented for use within GLM training, and have now been integrated into GLM training. A system was established to ensure producers can access the economics module via DPI&F staff if they wish to assess alternative scenarios to those already developed for GLM.

Background

The project made use of the pre-existing “ABCD” monitoring framework in Queensland, that categorises land condition according to a judgement on its potential to produce useful forage. Class A land is judged to be at least 85% of its productive potential, whilst D is at less than 25% of its potential.

The downside of the framework was that the descriptors used to make the assessment of land condition had several important difficulties. Firstly, the language used in the framework made objective interpretation difficult, with descriptions such as “general”, obvious”, “some”, and “severe” used to describe site characteristics. Secondly, condition classifications are not mutually exclusive; for example, a site can have a few weeds (an A indicator), plus some decline in useful grasses (a B indicator), plus obvious signs of past erosion (a C indicator). Thirdly, the general descriptions make little room for natural variation due to land types, season or geographical location. Furthermore, the framework required measurement of a number of parameters (soils, woodland condition, pastures) that added to the complexity of the framework.

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