Benchmarking to improve long-term carrying capacity estimates for extensive grazing properties in Queensland

Safe carrying capacity information can assist producers in making stocking rate decisions to ensure minimal decline in land condition over the long-term. FORAGE, a modelling framework which uses the GRASP pasture growth model, spatial data, remote sensing and climate data, provides long-term carrying capacities for individual paddocks and land types for grazing properties in Queensland. Applying the framework across Queensland’s diverse grazing lands and capturing the large range of land types and climates is challenging. To overcome this challenge, we will collate on-ground data and expert-knowledge for reference properties to help validate the modelling framework and ensure the best-available safe carrying capacity information is provided

Incorporating expert opinion and fine-scale vegetation mapping into statistical models of faunal distribution

1. Abiotic environmental predictors and broad-scale vegetation have been used widely to model the regional distributions of faunal species within forested regions of Australia. These models have been developed using stepwise statistical procedures but incorporate only limited expert involvement of the type sometimes advocated in distribution modelling. The objectives of this study were twofold. First, to evaluate techniques for incorporating fine-scaled vegetation and growth-stage mapping into models of species distribution. Secondly, to compare methods that incorporate expert opinion directly into statistical models derived using stepwise statistical procedures. 2. Using faunal data from north-east New South Wales, Australia, logistic regression models using fine-scale vegetation and expert opinion were compared with models employing only abiotic and broad vegetation variables. 3. Vegetation and growth-stage information was incorporated into models of species distribution in two ways, both of which used expert opinion to derive new explanatory variables. The first approach amalgamated fine-scaled vegetation classes into broader classes of ecological relevance to fauna. In the second approach, ordinal habitat indices were derived from vegetation and growth-stage mapping using rules specified by an expert panel. These indices described habitat features thought to be relevant to the faunal groups studied (e.g. tree hollow availability, fleshy fruit production). Landscape composition was calculated using these new variables within a 500-m and 2-km radius of each site. Each habitat index generated a spatially neutral variable and two spatial context variables. 4. Expert opinion was incorporated during the pre-modelling, model-fitting and post -modelling stages. At the pre-modelling stage experts developed new explanatory variables based on mapped fine-scale vegetation and growth-stage information. At the model-fitting stage an expert panel selected a subset of potential explanatory variables from the available set. At the post-modelling stage expert opinion modified or refined maps of predicted species distribution generated by statistical models. For comparative purposes expert opinion was also used to develop maps of species distribution by defining rules within a geographical information system, without the aid of statistical modelling. 5. Predictive accuracy was not improved significantly by incorporating habitat indices derived by applying expert opinion to fine-scaled vegetation and growth-stage mapping. Use of expert input at the pre-modelling stage to derive and select potential explanatory variables therefore does not provide more information than that provided by remotely mapped vegetation. 6. The incorporation of expert opinion at the model-fitting or post-modelling stages resulted in small but insignificant gains in predictive accuracy. The predictive accuracy of purely expert models was less than that achieved by approaches based on statistical modelling. 7. The study, one of few available evaluations of expert opinion in models of species distribution, suggests that expert modification of fitted statistical models should be confined to species for which models are grossly in error, or for which insufficient data exist to construct solely statistical models

Impacts of Projected Climate Change on Pasture Growth and Safe Carrying Capacities for Three Extensive Grazing Land Regions in Northern Australia

The northern beef industry is a major component of the regional economies of Queensland, Northern Territory and northern Western Australia, and has contributed an estimated $5 billion to Australia’s economy in 2009-10. Projected climate change will have an adverse impact on Australia’s agricultural production (McKeon et al. 2008) with an expected 3.5% decline in beef production in northern Australia by 2030 (Heyhoe et al. 2008). The GRASP pasture production model (McKeon et al. 2000) has been used to evaluate impacts of climate change in Australia’s rangelands (Crimp et al. 2002, McKeon et al. 2008), with the positive effects of higher carbon dioxide (CO2) on pasture growth likely to be offset by reductions in pasture productivity and digestibility due to lower rainfall and higher temperatures (Crimp et al. 2002). The impacts of three projected future climates on livestock carrying capacity of grazing lands in Fitzroy, Maranoa-Balonne and Victoria River District regions were assessed using GRASP

Identifying and Addressing Sustainable Pasture and Grazing Management Options for a Major Economic Sector–The North Australian Beef Industry

Sustainable use of the northern grazing lands is a long-standing issue for management and policy, heightened by projections of increased climatic variability, uncertainty on forage supplies, vegetation complexes, and weeds and diseases. Meat and Livestock Australia has supported a large study to explore sustainable grazing management strategies and increase the capacity of the sector to address climate change. Potential options were explored by bio-economic modeling of ‘representative’ beef enterprises defined by pastoralists and supported by regional research and extension specialists. Typical options include diversification, infrastructure, flexible stocking rates, wet season resting, and prescribed fire. Concurrent activities by another team included regional impact assessments and surveys of pastoralists’ understanding and attitudes towards climate change and adaptive capacity. The results have been widely canvassed and a program of on-ground demonstrations of various options implemented. The paper describes the structure of this program and highlights key results indicating considerable scope to address sustainability challenges

Systematic Management of Stocking Rates Improves Performance of Northern Australian Cattle Properties in a Variable Climate

The risks for extensive cattle properties in the rangelands of northern Australia arising from high inter-annual rainfall variability are predominantly managed through adjustments in stocking rates (SR). This modelling study compared the performance of SR strategies that varied considerably in the extent that they adjusted SR annually at three locations in northern Australia. At all locations, land types and pasture condition states, the SR strategies that achieved the best pasture condition were those that least increased and most decreased SR annually in response to changes in forage availability. At Donors Hill (Qld), these conservative strategies also achieved the highest cattle live-weight gains per hectare (LWG/ha). While conservative strategies produced the highest percent perennials at Fitzroy Crossing (WA), strategies which allowed larger increases and decreases in SR also performed well, enabling them to also achieve high LWG/ha with little deterioration of pasture condition. A similar trend occurred at Alice Springs (NT), although at this location the strategies with even larger annual increases and decreases in SR achieved relatively high percent perennials and the highest LWG/ha. While systematic management of SR appears to perform better than a constant SR strategy when rainfall variability is high, it is unclear if the magnitude of annual adjustments in SR needs to increase with increasing rainfall variability

Improved grazing management practices in the catchments of the Great Barrier Reef, Australia: Does climate variability influence their adoption by landholders?

Rolfe, JC ORCiD: 0000-0001-7659-7040The declining health of the Great Barrier Reef from diffuse source pollutants has resulted in substantial policy attention on increasing the adoption of improved management practices by agricultural producers. Although economic modelling indicates that many improved management practices are financially rewarding, landholders with dated management practices remain hesitant to change. This research involved bio-economic modelling to understand the variance in private returns for grazing enterprises across a climate cycle. Results show that financial returns to landholders can vary substantially across different 20-year periods of a climate cycle, demonstrating that the variability in expected returns may be an important reason why landholders are cautious about changing their management practices. Although previous research has separately identified financial returns and attitudes to risk and uncertainty of landholders as key influences on decisions concerning adoption of improved management practices, this research demonstrates that it is the interaction between these factors that is important to understand when designing policy settings

Targeting resource investments to achieve sediment reduction and improved Great Barrier Reef health

Rolfe, JC ORCiD: 0000-0001-7659-7040Concerns about excessive sediment loads entering the Great Barrier Reef (GBR) lagoon in Australia have led to a focus on improving ground cover in grazing lands. Ground cover has been identified as an important factor in reducing sediment loads, but improving ground cover has been difficult for reef stakeholders in major catchments of the GBR. To provide better information an optimising linear programming model based on paddock scale information in conjunction with land type mapping was developed for the Fitzroy, the largest of the GBR catchments. This identifies at a catchment scale which land types allow the most sediment reduction to be achieved at least cost. The results suggest that from the five land types modelled, the lower productivity land types present the cheapest option for sediment reductions. The study allows more informed decision making for natural resource management organisations to target investments. The analysis highlights the importance of efficient allocation of natural resource management funds in achieving sediment reductions through targeted land type investments