Sustainable and profitable grazing management in a highly variable environment-evidence and insights from a long term grazing trial in northern Australia.

Rainfall variability is a major challenge to sustainable management in semi-arid rangelands. We present empirical evidence from a large, long-term grazing trial in northern Australia on the relative performance of constant heavy stocking, moderate stocking at long-term carrying capacity and variable stocking in coping with climate variability over a range of rainfall years. Moderate stocking gave good economic returns, maintained pasture condition and minimised soil loss and runoff. Heavy stocking was neither sustainable nor profitable in the long term. Variable stocking generally performed well but suffered economic loss and some decline in pasture condition in the transition from good to poor years. Importantly, our results show that sustainable and profitable management are compatible in semi-arid rangelands.

Net radiation dynamics: performance of 20 daily net radiation models as related to model structure and intricacy in two climates.

We compared daily net radiation (Rn) estimates from 19 methods with the ASCE-EWRI Rn estimates in two climates: Clay Center, Nebraska (sub-humid) and Davis, California (semi-arid) for the calendar year. The performances of all 20 methods, including the ASCE-EWRI Rn method, were then evaluated against Rn data measured over a non-stressed maize canopy during two growing seasons in 2005 and 2006 at Clay Center. Methods differ in terms of inputs, structure, and equation intricacy. Most methods differ in estimating the cloudiness factor, emissivity (e), and calculating net longwave radiation (Rnl). All methods use albedo (a) of 0.23 for a reference grass/alfalfa surface. When comparing the performance of all 20 Rn methods with measured Rn, we hypothesized that the a values for grass/alfalfa and non-stressed maize canopy were similar enough to only cause minor differences in Rn and grass- and alfalfa-reference evapotranspiration (ETo and ETr) estimates. The measured seasonal average a for the maize canopy was 0.19 in both years. Using a = 0.19 instead of a = 0.23 resulted in 6% overestimation of Rn. Using a = 0.19 instead of a = 0.23 for ETo and ETr estimations, the 6% difference in Rn translated to only 4% and 3% differences in ETo and ETr, respectively, supporting the validity of our hypothesis. Most methods had good correlations with the ASCE-EWRI Rn (r2 > 0.95). The root mean square difference (RMSD) was less than 2 MJ m-2 d-1 between 12 methods and the ASCE-EWRI Rn at Clay Center and between 14 methods and the ASCE-EWRI Rn at Davis. The performance of some methods showed variations between the two climates. In general, r2 values were higher for the semi-arid climate than for the sub-humid climate. Methods that use dynamic e as a function of mean air temperature performed better in both climates than those that calculate e using actual vapor pressure. The ASCE-EWRI-estimated Rn values had one of the best agreements with the measured Rn (r2 = 0.93, RMSD = 1.44 MJ m-2 d-1), and estimates were within 7% of the measured Rn. The Rn estimates from six methods, including the ASCE-EWRI, were not significantly different from measured Rn. Most methods underestimated measured Rn by 6% to 23%. Some of the differences between measured and estimated Rn were attributed to the poor estimation of Rnl. We conducted sensitivity analyses to evaluate the effect of Rnl on Rn, ETo, and ETr. The Rnl effect on Rn was linear and strong, but its effect on ETo and ETr was subsidiary. Results suggest that the Rn data measured over green vegetation (e.g., irrigated maize canopy) can be an alternative Rn data source for ET estimations when measured Rn data over the reference surface are not available. In the absence of measured Rn, another alternative would be using one of the Rn models that we analyzed when all the input variables are not available to solve the ASCE-EWRI Rn equation. Our results can be used to provide practical information on which method to select based on data availability for reliable estimates of daily Rn in climates similar to Clay Center and Davis.

Environment characterization as an aid to wheat improvement: interpreting genotype-environment interactions by modelling water-deficit patterns in North-Eastern Australia.

Genotype-environment interactions (GEI) limit genetic gain for complex traits such as tolerance to drought. Characterization of the crop environment is an important step in understanding GEI. A modelling approach is proposed here to characterize broadly (large geographic area, long-term period) and locally (field experiment) drought-related environmental stresses, which enables breeders to analyse their experimental trials with regard to the broad population of environments that they target. Water-deficit patterns experienced by wheat crops were determined for drought-prone north-eastern Australia, using the APSIM crop model to account for the interactions of crops with their environment (e.g. feedback of plant growth on water depletion). Simulations based on more than 100 years of historical climate data were conducted for representative locations, soils, and management systems, for a check cultivar, Hartog. The three main environment types identified differed in their patterns of simulated water stress around flowering and during grain-filling. Over the entire region, the terminal drought-stress pattern was most common (50% of production environments) followed by a flowering stress (24%), although the frequencies of occurrence of the three types varied greatly across regions, years, and management. This environment classification was applied to 16 trials relevant to late stages testing of a breeding programme. The incorporation of the independently-determined environment types in a statistical analysis assisted interpretation of the GEI for yield among the 18 representative genotypes by reducing the relative effect of GEI compared with genotypic variance, and helped to identify opportunities to improve breeding and germplasm-testing strategies for this region.

Climate Change - Risks and Opportunities for the Custard Apple Industry

Climate affects the custard apple industry in a range of ways through impacts on growth, disease risk, fruit set and industry location. Climates in Australia are influenced by surrounding oceans, and are very variable from year to year. However, amidst this variability there are significant trends, with Australian annual mean temperatures increasing since 1910, and particularly since 1950, with night-time temperatures increasing faster (0.11oC/decade) than daytime temperatures (0.06oC/decade). These temperature increases and other climate changes are expected to continue as a result of greenhouse gas emissions, with ongoing impacts on the custard apple industry. Five sites were chosen to assess possible future climate changes : Mareeba, Yeppoon, Bundaberg, Nambour and Lismore, these sites representing the extent of the majority of custard apple production in eastern Australia. A fifth site (Coffs Harbour) was selected as it is south of the current production regions. A mean warming of 0.8 to 1.2oC is anticipated over most of these sites by the year 2030, relative to 1990. This paper assesses the potential effects of climate change on custard apple production, and suggests strategies for adaptation.

Effects of climate change on reproduction,larval development, and adult health of coral trout (Plectropomus spp.)

Climate change is emerging as the single greatest threat to coral-reef ecosystems.The most immediate impacts will be a loss of diversity and changes to fish community composition and may lead to eventual declines in abundance and productivity of key fisheries species. A key component of this research is to assess effects of projected changes in environmental conditions (temperature and ocean acidity) due to climate change on reproduction, growth and development of coral trout (Plectropomus leopardis).Ultimately, this research will fill key knowledge gaps about climate change impacts on larger fishes, which are fundamental to optimizing resilience-based management, and in turn improve the adaptive capacity of industries and communities along the Great Barrier Reef.

Management implications of climate change impacts of fisheries resources

This application was developed in response to the widely recognised concern that climate change will result in changes to marine life and ecosystems, and hence fisheries, throughout Australia with tropical marine ecosystems in northern Australia identified as being particularly vulnerable. These changes are predicted to vary spatially depending on local climate and biophysical processes. Northern Australia is one of three major Australian regions predicted to be impacted. The project addresses the important FRDC strategic challenge of improving the management of aquatic natural resources to ensure their sustainability through research and management that accounts for the effects that climate change may have on the resources.

Test and develop sustainable and profitable grazing strategies to manage for rainfall variability

The Wambiana grazing trial started in 1997 to test and develop sustainable and profitable grazing strategies to manage for rainfall variability. It is important that this trial continue as the results are still relatively short-term relative to rainfall cycles and significant treatment changes are still occurring. This new proposal will maintain baseline treatments but will modify others based on trial learning’s to date. It builds on treatment differences and evidence collected over the last 12 years to deliver evidence-based guidelines and principles for sustainable and productive management. The trial also links to other projects modelling water quality, climate change, methane emissions and soil C sequestration on grazing lands.

Positioning the Cut Flower Industry to Respond to the Climate Change

Contribute to the current understanding of climate impacts on cut flower and foliage growing in Queensland.

GRDC Improving crop and farm water use efficiency in Australia

Project Objectives: 1. Improving yield and water use efficiency of the wheat crop, the backbone of the Australia grains industry, by better matching management, variety, soil and climate. The aim is thus increasing kg grain/ha per mm evapotranspiration and kg grain/ha per mm rain. 2. Improving land and water productivity and profit by better arrangement of the components of the cropping system. This involves better allocation of farm resources (land, water, machinery, labour) and identifying strategies that account for trade-offs between profit and risk. The aim is thus improving $/ha per year and mm rain in a risk framework.

Participatory adaptation and mitigation strategies for climate change on mixed farms

The project uses participatory methods to engage primary producers and advisers in central Queensland, southern Queensland, and north east New South Wales on-farm trials and demonstrations to adapt mixed farming systems to changed climate conditions. The focus is adaptation to climate change but will support abatement of greenhouse gas emissions by building soil carbon, better managing soil nitrogen and soil organic carbon. Data will be collected and integrated with data from Round 1 of the Climate Change Research Program to extend industry understanding beyond a general awareness of ‘climate change’. Nitrous oxide and soil carbon data will help farmers/advisers understand the implications of climate change and develop adaptation strategies for a more sustainable, climate sensitive future.

RWUE4: Responding to Climate in the Central Queensland Irrigation Sector

Increasing the productivity of irrigation water use and reducing energy use in rural irrigation within the Central Highlands and Dawson-Callide irrigation districts.

Climate Q - Develop capacity to adapt to climate change in Queensland

Aims to build adaptive capacity within Qld's mixed farming (cropping/beef) sector.

Maximising profitability with limited water in cotton farming systems

Diminishing water supply, changing weather patterns and pressure to enhance environmental flows are making it imperative to optimise water use efficiency (WUE) on cotton/grain farming systems. Growers are looking for better strategies to make the best use of limited water, but it is still not clear how to best use the available water at farm and field scale. This research project investigated the impact of management strategies to deal with limited water supplies on the yield and quality of irrigated cotton and wheat. The objectives were: (1) to develop irrigation management guidelines for the main irrigated crops on the Darling Downs for full- and deficitirrigation scenarios, taking into account the critical factors that affect irrigation decisions at the local level, (2) to quantify the evapotranspiration (ET) of Bollgard II cotton and wheat and its relationship to yield and quality under full- and deficit-irrigation scenarios, and (3) to increase industry awareness and education of farming systems practises for optimised economic water use efficiency.Objective (1) was addressed by (A) collaborating with ASPRU to develop the APSFarm model within APSIM to be able to perform multi-paddock simulations. APSFarm was then tested by conducting a case study at a farm near Dalby, and (B) conducting semi-structured interviews with individual farmers and crop consultants on the Darling Downs to document the strategies they are using to deal with limited water. Objective (2) was addressed by (A) building and installing 12 large (1 m x 1m x 1.5 m) weighing lysimeters to measure crop evapotranspiration. The lysimeters were installed at the Agri-Science Queensland research station at Kingsthorpe in November 2008, (B) conducting field experiments to measure crop evapotranspiration and crop development under four irrigation treatments, including dryland, deficit-irrigation, and full irrigation. Field experiments were conducted with cotton in 2007-08 and 2008-09, and with wheat in 2008 and 2009, and (C) collaborating with USQ on a PhD thesis to quantify the impact of crop stress on crop evapotranspiration and canopy temperature. Glasshouse experiments were conducted with wheat in 2008 and with cotton in 2008-09. Objective (3) was addressed by (A) conducting a field day at Kingsthorpe in 2009, which was attended by 80 participants, (B) presenting information in conferences in Australia and overseas, (D) presenting information at farmers meeting, (E) making presentations to crop consultants, and (F) preparing extension publications.As part of this project we contributed to the development of APSfarm, which has been successfully applied to evaluate the feasibility of practices at the whole-farm scale. From growers and crop consultants interviews we learned that there is a great variety of strategies, at different scales, that they are using to deal with limited water situation. These strategies will be summarised in the "e;Limited Water Guidelines for the Darling Downs"e; that we are currently preparing. As a result of this project, we now have a state-of-the-art lysimeter research facility (23 large weighing lysimeters) to be able to conduct replicated experiments to investigate daily water use of a variety of crops under different irrigation regimes and under different environments. Under this project, a series of field and glasshouse experiments were conducted with cotton and wheat, investigating aspects like: (A) quantification of daily and seasonal crop water use under nonstressed and stressed conditions, (B) impact of row configuration on crop water use, (C) impact of water stress on yield, evapotranspiration, crop vegetative and reproductive development, soil water extraction pattern, yield and yield quality. The information obtained from this project is now being used to develop web-based tools to help growers make planning and day-to-day irrigation decisions.

ACIAR Feasibility of farmers managing climate related crop production risk in India

Validation of new Indian seasonal climate forecasting products. In the Indian state of Andhra Pradesh (AP) kharif crops are heavily dependent on summer monsoon rains, where the timing and intensity of the rains affects crop yield. The majority of farms in AP are small and marginal, making them very vulnerable to yield reductions. Farmers also lack access to relevant information that might enable them to respond to seasonal conditions. Enabling farmers to utilise seasonal climate forecasting would allow them to respond to seasonal variability. To do this, farmers need a forecasting system that indicates a specific management strategy for the upcoming season, and effective and timely communication of the forecast information. Current agro-meteorological advisories in AP are issued on a bi-weekly basis, and they are relevant to an agro-climatic zone scale which may not be sufficiently relevant at a village level. Also, the information in the advisories may not be necessarily packaged in way relevant to cropping decisions by farmers. The objectives of this project are to evaluate the skill of seasonal climate forecasts to be issued for the 2008 monsoon season, to assess crop management options in response to seasonal scenarios that capture the range of seasonal climatic variability, to develop and evaluate options for effective communication and adoption of climate forecasts and agricultural advisories, and to synthesise and report on options for future research investments into seasonal climate forecasting.

A multi-field bio-economic model of irrigated grain-cotton farming systems.

We present a participatory modelling framework that integrates information from interviews and discussions with farmers and consultants, with dynamic bio-economic models to answer complex questions on the allocation of limited resources at the farm business level. Interviews and discussions with farmers were used to: describe the farm business; identify relevant research questions; identify potential solutions; and discuss and learn from the whole-farm simulations. The simulations are done using a whole-farm, multi-field configuration of APSIM (APSFarm). APSFarm results were validated against farmers' experience. Once the model was accepted by the participating farmers as a fair representation of their farm business, the model was used to explore changes in the tactical or strategic management of the farm and results were then discussed to identify feasible options for improvement. Here we describe the modelling framework and present an example of the application of integrative whole farm system tools to answer relevant questions from an irrigated farm business case study near Dalby (151.27E - 27.17S), Queensland, Australia. Results indicated that even though cotton crops generates more farm income per hectare a more diversified rotation with less cotton would be relatively more profitable, with no increase in risk, as a more cotton dominated traditional rotation. Results are discussed in terms of the benefits and constraints from developing and applying more integrative approaches to represent farm businesses and their management in participatory research projects with the aim of designing more profitable and sustainable irrigated farming systems.