Grazing is a major land use in Australia’s rangelands. The ‘safe’ livestock carrying capacity (LCC) required to maintain resource condition is strongly dependent on climate. We reviewed: the approaches for quantifying LCC; current trends in climate and their effect on components of the grazing system; implications of the ‘best estimates’ of climate change projections for LCC; the agreement and disagreement between the current trends and projections; and the adequacy of current models of forage production in simulating the impact of climate change. We report the results of a sensitivity study of climate change impacts on forage production across the rangelands, and we discuss the more general issues facing grazing enterprises associated with climate change, such as ‘known uncertainties’ and adaptation responses (e.g. use of climate risk assessment). We found that the method of quantifying LCC from a combination of estimates (simulations) of long-term (>30 years) forage production and successful grazier experience has been well tested across northern Australian rangelands with different climatic regions. This methodology provides a sound base for the assessment of climate change impacts, even though there are many identified gaps in knowledge. The evaluation of current trends indicated substantial differences in the trends of annual rainfall (and simulated forage production) across Australian rangelands with general increases in most of western Australian rangelands (including northern regions of the Northern Territory) and decreases in eastern Australian rangelands and south-western Western Australia. Some of the projected changes in rainfall and temperature appear small compared with year-to-year variability. Nevertheless, the impacts on rangeland production systems are expected to be important in terms of required managerial and enterprise adaptations. Some important aspects of climate systems science remain unresolved, and we suggest that a risk-averse approach to rangeland management, based on the ‘best estimate’ projections, in combination with appropriate responses to short-term (1–5 years) climate variability, would reduce the risk of resource degradation. Climate change projections – including changes in rainfall, temperature, carbon dioxide and other climatic variables – if realised, are likely to affect forage and animal production, and ecosystem functioning. The major known uncertainties in quantifying climate change impacts are: (i) carbon dioxide effects on forage production, quality, nutrient cycling and competition between life forms (e.g. grass, shrubs and trees); and (ii) the future role of woody plants including effects of fire, climatic extremes and management for carbon storage. In a simple example of simulating climate change impacts on forage production, we found that increased temperature (3°C) was likely to result in a decrease in forage production for most rangeland locations (e.g. –21% calculated as an unweighted average across 90 locations). The increase in temperature exacerbated or reduced the effects of a 10% decrease/increase in rainfall respectively (–33% or –9%). Estimates of the beneficial effects of increased CO2 (from 350 to 650 ppm) on forage production and water use efficiency indicated enhanced forage production (+26%). The increase was approximately equivalent to the decline in forage production associated with a 3°C temperature increase. The large magnitude of these opposing effects emphasised the importance of the uncertainties in quantifying the impacts of these components of climate change. We anticipate decreases in LCC given that the ‘best estimate’ of climate change across the rangelands is for a decline (or little change) in rainfall and an increase in temperature. As a consequence, we suggest that public policy have regard for: the implications for livestock enterprises, regional communities, potential resource damage, animal welfare and human distress. However, the capability to quantify these warnings is yet to be developed and this important task remains as a challenge for rangeland and climate systems science.

Data from 57 permanent monitoring sites are used to document the growth in woody vegetation and estimate the carbon sink in 27 M ha of eucalypt woodlands (savannas), contained within c. 60 M ha of grazed woodlands in Queensland (northeast Australia). The study sites are shown to be representative of the environment and structure of the eucalypt woodlands in the defined study area. Mean basal area increment for all live woody plants in 30 long‐term sites, with an average initial basal area of 11.86 ± 1.38 (SE) m2 ha−1, was 1.06 m2 ha−1 over a mean 14 years timeframe. The majority of the measurement period, commencing between 1982 and 1988, was characterized by below‐average rainfall. The increase in live tree basal area was due primarily to growth of existing trees (3.12 m2 ha−1) rather than establishment of new plants (0.25 m2 ha−1) and was partly offset by death (2.31 m2 ha−1). A simple but robust relationship between stand basal area and stand biomass of all woody species was developed for the eucalypt dominant woodlands. Analysis of above‐ground carbon stocks in live and standing dead woody plants gave a mean net above‐ground annual carbon increment for all 57 sites of 0.53 t C ha−1 y−1, similar to values estimated elsewhere in world savannas. Published root : shoot ratios were used to infer C flux in woody root systems on these sites. This results in an estimated sink in above‐ and below‐ground biomass of 18 Mt C y−1 over the eucalypt woodlands studied, and potentially up to 35 Mt C y−1 if extended to all grazed woodlands in Queensland. It is suggested that introduction of livestock grazing and altered fire regimes have triggered the change in tree‐grass dominance in these woodlands. Thus, change in carbon stocks in the grazed woodlands of Queensland is identified as an important component of human‐induced greenhouse gas flux in Australia, equivalent in magnitude to c. 25% of the most recently published (1999) total estimated national net emissions. The latter inventory takes into account emissions from land clearing, but does not include the sink identified in the present study. This sequestration also represents a small but significant contribution to the global terrestrial carbon sink.

Few tools are available to assist graziers, land administrators and financiers in making objective grazing capacity decisions on Australian rangelands, despite existing knowledge regarding stocking rate theory and the impact of stocking rates on land condition. To address this issue a model for objectively estimating 'safe' grazing capacities on individual grazing properties in south-west Queensland was developed. The method is based on 'safe' levels of utilisation (15%-20%) by domestic livestock of average annual forage grown for each land system on a property. Average annual forage grown (kglha) was calculated as the product of the rainfall use efficiency (kglhdmm) and average annual rainfall (mm) for a land system. This estimate included the impact of tree and shrub cover on forage production. The 'safe' levels of forage utilisation for south- west Queensland pastures were derived from the combined experience of (1) re-analysis of the results of grazing trials, (2) reaching a consensus on local knowledge and (3) examination of existing grazing practice on 'benchmark' grazing properties. We recognise the problems in defining, determining and using grazing capacity values, but consider that the model offers decision makers a tool that can be used to assess the grazing capacity of individual properties.

The 160 million ha of grazing land in Queensland support approximately 10 million beef equivalents (9.8 million cattle and 10.7 million sheep) with treed and cleared native pastures as the major forage source. The complexity of these biophysical systems and their interaction with pasture and stock management, economic and social forces limits our ability to easily calculate the impact of climate change scenarios. We report the application of a systems approach in simulating the flow of plant dry matter and utilisation of forage by animals. Our review of available models highlighted the lack of suitable mechanistic models and the potential role of simple empirical relationships of utilisation and animal production derived from climatic and soil indices. Plausible climate change scenarios were evaluated by using a factorial of rainfall (f 10%) * 3260C temperature increase * doubling CO, in sensitivity studies at property, regional and State scales. Simulation of beef cattle liveweight gain at three locations in the Queensland black speargrass zone showed that a *lo% change in rainfall was magnified to be a f 15% change in animal production (liveweight gain per ha) depending on location, temperature and CO, change. Models of 'safe' carrying capacity were developed from property data and expert opinion. Climate change impacts on 'safe' carrying capacity varied considerably across the State depending on whether moisture, temperature or nutrients were the limiting factors. Without the effect of doubling CO,, warmer temperatures and +lo% changes in rainfall resulted in -35 to +70% changes in 'safe' carrying capacity depending on location. With the effect of doubling CO, included, the changes in 'safe' carrying capacity ranged from -12 to +115% across scenarios and locations. When aggregated to a whole-of-State carrying capacity, the combined effects of warmer temperature, doubling CO, and +lo% changes in rainfall resulted in 'safe' carrying capacity changes of +3 to +45% depending on rainfall scenario and location. A major finding of the sensitivity study was the potential importance of doubling CO, in mitigating or amplifying the effects of warmer temperatures and changes in rainfall. Field studies on the impact of CO, are therefore a high research priority. Keywords: climate change, Queensland, simulation, rangelands, beef production, cattle, carrying capacity, CO,, utilisation

Defining drought, categorising current droughts, and assessing grassland and rangeland sustainability in a quantitative and scienti:fic manner are important national issues for Australian State and Commonwealth governments, landholders and agribusiness. A challenge for ecologists and modellers of Australia's grasslands and rangelands is to integrate biological models, geographic information systems, satellite imagery, economics, climatology and visual high-performance computing into readily available products that can provide monitoring and prediction advice in near real-time.The QDNR systems approach to the management of native grasslands recognises that drought occurs at a regional scale, and that impacts on livestock and natural resources can be forecast using simple models of soil water, plant growth and animal performance. Our vision for a comprehensive Australian Gmssland and Rangeland Assessment System (Aussie GRASS) is one that consists of the best combination of minfall analyses, seasonal climate forecasts, satellite and terrestrial monitoring, and simulation models of relevant biological processes. This will provide a rational basis for largescale management decisions by graziers, extension workers, land resource managers, bureaucmts and politicians. Aussie GRASS products are currently used within the Queensland government for drought declaration assessments and applications for Drought Exceptional Circumstances.The Aussie GRASS national spatial modelling framework allows agricultural simulation models to be run at a continental scale on a 0.05 degree 05 km) grid. The simulation model currently in use by the Aussie GRASS project is the GRASP pasture model developed for tropical native pastures in Queensland by QDPI and QDNR. In the latest Aussie GRASS project, other regional models are being examined for their applicability to areas such as the southem winter perennial grass zone, chenopod shrublands or the high minfall temperate zone. 330 The Queensland version of the Aussie GRASS model is currently used to produce data for a monthly report -A Summary of Seasonal Conditions in Queensland. Model outputs are used in conjunction with recorded and forecast rainfall, satellite imagery, Southern Oscillation Index and current drought declarations to build a comprehensive picture of the current and future seasonal conditions impacting on primary producers. Other numerous outputs from the model can be produced and tailored as required.