Declining soil phosphorus reserves on sustainable agricultural production systems

PhD scholarship investigating the relative sensitivity of nitrogen fixation in adapted grain and ley legume species to low soil phosphorus.

Precision Agriculture and Remote Sensing Technologies in Central Queensland agricultural production systems

Demonstrate potential benefits of various Precision Agricultural technologies to Central Queensland farming community.

Crop sequences to manage soil pathogens and increase northern grain production

This is part of a GRDC funded project led by Dr Jeremy Whish of CSIRO Ecosystem Sciences. The project aims to build a root-lesion nematode module into the crop growth simulation program APSIM (Agricultural Production Systems Simulator). This will utilise existing nematode and crop data from field, glasshouse and laboratory research led by Dr John Thompson. New data will be collected to validate and extend the model.

Implementation costs of Agricultural Management Practices for Water Quality Improvement in the Great Barrier Reef Catchments. CSIRO: Water for Healthy Country National Research Flagship

Executive summary. In this report we analyse implementation costs and benefits for agricultural management practices, grouped into farming systems. In order to do so, we compare plot scale gross margins for the dominant agricultural production systems (sugarcane, grazing and banana cultivation) in the NRM regions Wet Tropics, Burdekin Dry Tropics and Mackay Whitsundays. Furthermore, where available, we present investment requirements for changing to improved farming systems. It must be noted that transaction costs are not captured within this project. For sugarcane, this economic analysis shows that there are expected benefits to sugarcane growers in the different regions through transitions to C and B class farming systems. Further transition to A-class farming systems can come at a cost, depending on the capital investment required and the length of the investment period. Obviously, the costs and benefits will vary for each individual grower and will depend on their starting point and individual property scenario therefore each circumstance needs to be carefully considered before making a change in management practice. In grazing, overall, reducing stocking rates comes at a cost (reduced benefits). However, when operating at low utilisation rates in wetter country, lowering stocking rates can potentially come at a benefit. With win-win potential, extension is preferred to assist farmer in changing management practices to improve their land condition. When reducing stocking rates comes at a cost, incentives may be applicable to support change among farmers. For banana cultivation, the results indicate that the transition to C and B class management practices is a worthwhile proposition from an economic perspective. For a change from B to A class farming systems however, it is not worthwhile from a financial perspective. This is largely due to the large capital investment associated with the change in irrigation system and negative impact in whole of farm gross margin. Overall, benefits will vary for each individual grower depending on their starting point and their individual property scenario. The results presented in this report are one possible set of figures to show the changes in profitability of a grower operating in different management classes. The results in this report are not prescriptive of every landholder. Landholders will have different costs and benefits from transitioning to improved practices, even if similar operations are practiced, hence it is recommended that landholders that are willing to change management undertake their own research and analysis into the expected costs and benefits for their own soil types and property circumstances.

Characterization of north-eastern Australian environments using APSIM for increasing rainfed maize production

Recurring water stresses are a major risk factor for rainfed maize cropping across the highly diverse agro-ecological environments of Queensland (Qld) and northern New South Wales (NNSW). Enhanced understanding of such agro-ecological diversity is necessary to more consistently sample target production environments for testing and targeting release of improved germplasm, and to improve the efficiency of the maize pre-breeding and breeding programs of Qld and New South Wales. Here, we used the Agricultural Production Systems Simulator (APSIM) – a well validated maize crop model to characterize the key distinctive water stress patterns and risk to production across the main maize growing regions of Qld and NNSW located between 15.8° and 31.5°S, and 144.5° and 151.8°E. APSIM was configured to simulate daily water supply demand ratios (SDRs) around anthesis as an indicator of the degree of water stress, and the final grain yield. Simulations were performed using daily climatic records during the period between 1890 and 2010 for 32 sites-soils in the target production regions. The runs were made assuming adequate nitrogen supply for mid-season maize hybrid Pioneer 3153. Hierarchical complete linkage analyses of the simulated yield resulted in five major clusters showing distinct probability distribution of the expected yields and geographic patterns. The drought stress patterns and their frequencies using SDRs were quantified using multivariate statistical methods. The identified stress patterns included no stress, mid-season (flowering) stress, and three terminal stresses differing in terms of severity. The combined frequency of flowering and terminal stresses was highest (82.9%), mainly in sites-soils combinations in the west of Qld and NNSW. Yield variability across the different sites-soils was significantly related to the variability in frequencies of water stresses. Frequencies of water stresses within each yield cluster tended to be similar, but different across clusters. Sites-soils falling within each yield cluster therefore could be treated as distinct maize production environments for testing and targeting newly developed maize cultivars and hybrids for adaptation to water stress patterns most common to those environments.

The critical role of extreme heat for maize production in the United States

Statistical studies of rainfed maize yields in the United States(1) and elsewhere(2) have indicated two clear features: a strong negative yield response to accumulation of temperatures above 30 degrees C (or extreme degree days (EDD)), and a relatively weak response to seasonal rainfall. Here we show that the process-based Agricultural Production Systems Simulator (APSIM) is able to reproduce both of these relationships in the Midwestern United States and provide insight into underlying mechanisms. The predominant effects of EDD in APSIM are associated with increased vapour pressure deficit, which contributes to water stress in two ways: by increasing demand for soil water to sustain a given rate of carbon assimilation, and by reducing future supply of soil water by raising transpiration rates. APSIM computes daily water stress as the ratio of water supply to demand, and during the critical month of July this ratio is three times more responsive to 2 degrees C warming than to a 20% precipitation reduction. The results suggest a relatively minor role for direct heat stress on reproductive organs at present temperatures in this region. Effects of elevated CO2 on transpiration efficiency should reduce yield sensitivity to EDD in the coming decades, but at most by 25%.

Agricultural intensification, priming for persistence and the emergence of Nipah virus: a lethal bat-borne zoonosis

Emerging zoonoses threaten global health, yet the processes by which they emerge are complex and poorly understood. Nipah virus (NiV) is an important threat owing to its broad host and geographical range, high case fatality, potential for human-to-human transmission and lack of effective prevention or therapies. Here, we investigate the origin of the first identified outbreak of NiV encephalitis in Malaysia and Singapore. We analyse data on livestock production from the index site (a commercial pig farm in Malaysia) prior to and during the outbreak, on Malaysian agricultural production, and from surveys of NiV's wildlife reservoir (flying foxes). Our analyses suggest that repeated introduction of NiV from wildlife changed infection dynamics in pigs. Initial viral introduction produced an explosive epizootic that drove itself to extinction but primed the population for enzootic persistence upon reintroduction of the virus. The resultant within-farm persistence permitted regional spread and increased the number of human infections. This study refutes an earlier hypothesis that anomalous El Nino Southern Oscillation-related climatic conditions drove emergence and suggests that priming for persistence drove the emergence of a novel zoonotic pathogen. Thus, we provide empirical evidence for a causative mechanism previously proposed as a precursor to widespread infection with H5N1 avian influenza and other emerging pathogens.

APSIM – Evolution towards a new generation of agricultural systems simulation

Agricultural systems models worldwide are increasingly being used to explore options and solutions for the food security, climate change adaptation and mitigation and carbon trading problem domains. APSIM (Agricultural Production Systems sIMulator) is one such model that continues to be applied and adapted to this challenging research agenda. From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond. Keating et al. (2003) described many of the fundamental attributes of APSIM in detail. Much has changed in the last decade, and the APSIM community has been exploring novel scientific domains and utilising software developments in social media, web and mobile applications to provide simulation tools adapted to new demands. This paper updates the earlier work by Keating et al. (2003) and chronicles the changing external challenges and opportunities being placed on APSIM during the last decade. It also explores and discusses how APSIM has been evolving to a “next generation” framework with improved features and capabilities that allow its use in many diverse topics.

Quantifying the response of cotton production in eastern Australia to climate change

Abstract The paper evaluates the effect of future climate change (as per the CSIRO Mk3.5 A1FI future climate projection) on cotton yield in Southern Queensland and Northern NSW, eastern Australia by using of the biophysical simulation model APSIM (Agricultural Production Systems sIMulator). The simulations of cotton production show that changes in the influential meteorological parameters caused by climate change would lead to decreased future cotton yields without the effect of CO2 fertilisation. By 2050 the yields would decrease by 17 %. Including the effects of CO2 fertilisation ameliorates the effect of decreased water availability and yields increase by 5.9 % by 2030, but then decrease by 3.6 % in 2050. Importantly, it was necessary to increase irrigation amounts by almost 50 % to maintain adequate soil moisture levels. The effect of CO2 was found to have an important positive impact of the yield in spite of deleterious climate change. This implies that the physiological response of plants to climate change needs to be thoroughly understood to avoid making erroneous projections of yield and potentially stifling investment or increasing risk.

Reconfiguring agriculture through the relocation of production systems for water, environment and food security under climate change

The prospect of climate change has revived both fears of food insecurity and its corollary, market opportunities for agricultural production. In Australia, with its long history of state-sponsored agricultural development, there is renewed interest in the agricultural development of tropical and sub-tropical northern regions. Climate projections suggest that there will be less water available to the main irrigation systems of the eastern central and southern regions of Australia, while net rainfall could be sustained or even increase in the northern areas. Hence, there could be more intensive use of northern agricultural areas, with the relocation of some production of economically important commodities such as vegetables, rice and cotton. The problem is that the expansion of cropping in northern Australia has been constrained by agronomic and economic considerations. The present paper examines the economics, at both farm and regional level, of relocating some cotton production from the east-central irrigation areas to the north where there is an existing irrigation scheme together with some industry and individual interest in such relocation. Integrated modelling and expert knowledge are used to examine this example of prospective climate change adaptation. Farm-level simulations show that without adaptation, overall gross margins will decrease under a combination of climate change and reduction in water availability. A dynamic regional Computable General Equilibrium model is used to explore two scenarios of relocating cotton production from south east Queensland, to sugar-dominated areas in northern Queensland. Overall, an increase in real economic output and real income was realized when some cotton production was relocated to sugar cane fallow land/new land. There were, however, large negative effects on regional economies where cotton production displaced sugar cane. It is concluded that even excluding the agronomic uncertainties, which are not examined here, there is unlikely to be significant market-driven relocation of cotton production.

Simulating crop-parasitic weed interactions using APSIM: Model evaluation and application

The parasitic weed Orobanche crenata inflicts major damage on faba bean, lentil, pea and other crops in Mediterranean environments. The development of methods to control O. crenata is to a large extent hampered by the complexity of host-parasite systems. Using a model of host-parasite interactions can help to explain and understand this intricacy. This paper reports on the evaluation and application of a model simulating host-parasite competition as affected by environment and management that was implemented in the framework of the Agricultural Production Systems Simulator (APSIM). Model-predicted faba bean and O. crenata growth and development were evaluated against independent data. The APSIM-Fababean and -Parasite modules displayed a good capability to reproduce effects of pedoclimatic conditions, faba bean sowing date and O. crenata infestation on host-parasite competition. The r(2) values throughout exceeded 0.84 (RMSD: 5.36 days) for phenological, 0.85 (RMSD: 223.00 g m(-2)) for host growth and 0.78 (RMSD: 99.82 g m(-2)) for parasite growth parameters. Inaccuracies of simulated faba bean root growth that caused some bias of predicted parasite number and host yield loss may be dealt with by more flexibly simulating vertical root distribution. The model was applied in simulation experiments to determine optimum sowing windows for infected and non-infected faba bean in Mediterranean environments. Simulation results proved realistic and testified to the capability of APSIM to contribute to the development of tactical approaches in parasitic weed control.

Using APSIM-soiltemp to simulate soil temperature in the podding zone of peanut

Measurement or accurate simulation of soil temperature is important for improved understanding and management of peanuts (Arachis hypogaea L.), due to their geocarpic habit. A module of the Agricultural Production Systems Simulator Model (APSIM), APSIM-soiltemp, which uses input of ambient temperature, rainfall and solar radiation in conjunction with other APSIM modules, was evaluated for its ability to simulate surface 5 cm soil temperature in 35 peanut on-farm trials conducted between 2001 and 2005 in the Burnett region (25°36'S to 26°41'S, 151°39'E to 151°53'E). Soil temperature simulated by the APSIM-soiltemp module, from 30 days after sowing until maturity, closely matched the measured values (R2 ≥ 0.80)in the first three seasons (2001-04). However, a slightly poorer relationship (R2 = 0.55) between the observed and the simulated temperatures was observed in 2004-05, when the crop was severely water stressed. Nevertheless, over all the four seasons, which were characterised by a range of ambient temperature, leaf area index, radiation and soil water, each of which was found to have significant effects on soil temperature, a close 1:1 relationship (R2 = 0.85) between measured and simulated soil temperatures was observed. Therefore, the pod zone soil temperature simulated by the module can be generally relied on in place of measured input of soil temperature in APSIM applications, such as quantifying climatic risk of aflatoxin accumulation.

Assessing the sustainability of wheat-based cropping systems using APSIM: Model parameterisation and evaluation

Assessing the sustainability of crop and soil management practices in wheat-based rotations requires a well-tested model with the demonstrated ability to sensibly predict crop productivity and changes in the soil resource. The Agricultural Production Systems Simulator (APSIM) suite of models was parameterised and subsequently used to predict biomass production, yield, crop water and nitrogen (N) use, as well as long-term soil water and organic matter dynamics in wheat/chickpea systems at Tel Hadya, north-western Syria. The model satisfactorily simulated the productivity and water and N use of wheat and chickpea crops grown under different N and/or water supply levels in the 1998-99 and 1999-2000 experimental seasons. Analysis of soil-water dynamics showed that the 2-stage soil evaporation model in APSIM's cascading water-balance module did not sufficiently explain the actual soil drying following crop harvest under conditions where unused water remained in the soil profile. This might have been related to evaporation from soil cracks in the montmorillonitic clay soil, a process not explicitly simulated by APSIM. Soil-water dynamics in wheat-fallow and wheat-chickpea rotations (1987-98) were nevertheless well simulated when the soil water content in 0-0.45 m soil depth was set to 'air dry' at the end of the growing season each year. The model satisfactorily simulated the amounts of NO3-N in the soil, whereas it underestimated the amounts of NH 4-N. Ammonium fixation might be part of the soil mineral-N dynamics at the study site because montmorillonite is the major clay mineral. This process is not simulated by APSIM's nitrogen module. APSIM was capable of predicting long-term trends (1985-98) in soil organic matter in wheat-fallow and wheat-chickpea rotations at Tel Hadya as reported in literature. Overall, results showed that the model is generic and mature enough to be extended to this set of environmental conditions and can therefore be applied to assess the sustainability of wheat-chickpea rotations at Tel Hadya.

Fox management in south-eastern Australia: management strategies and cost-efficiencies

The European red fox is one of Australia´s most devastating vertebrate affecting both biodiversity and agricultural production. Fox management strategies rely heavily on poisoning using baits impregnated with sodium fluoroacetate (1080). Factors such as the ability of foxes to locate bait, palatability and toxicity of bait, pattern and density of bait distribution, and cost/benefits of specific use patterns all affect the overall efficiency of management programs. It is essential to examine and refine all such factors to manage the damaging impacts of this pest species. This book examines the problems associated with management of the fox in south-eastern Australia, highlights deficiencies in ´best-practice´ baiting techniques, and provides recommendations to improve current management strategies and guide future research.

Validating economic and environmental sustainability of a short-term summer forage legume in dryland wheat cropping systems in south-west Queensland.

The present study set out to test the hypothesis through field and simulation studies that the incorporation of short-term summer legumes, particularly annual legume lablab (Lablab purpureus cv. Highworth), in a fallow-wheat cropping system will improve the overall economic and environmental benefits in south-west Queensland. Replicated, large plot experiments were established at five commercial properties by using their machineries, and two smaller plot experiments were established at two intensively researched sites (Roma and St George). A detailed study on various other biennial and perennial summer forage legumes in rotation with wheat and influenced by phosphorus (P) supply (10 and 40 kg P/ha) was also carried out at the two research sites. The other legumes were lucerne (Medicago sativa), butterfly pea (Clitoria ternatea) and burgundy bean (Macroptilium bracteatum). After legumes, spring wheat (Triticum aestivum) was sown into the legume stubble. The annual lablab produced the highest forage yield, whereas germination, establishment and production of other biennial and perennial legumes were poor, particularly in the red soil at St George. At the commercial sites, only lablab-wheat rotations were experimented, with an increased supply of P in subsurface soil (20 kg P/ha). The lablab grown at the commercial sites yielded between 3 and 6 t/ha forage yield over 2-3 month periods, whereas the following wheat crop with no applied fertiliser yielded between 0.5 to 2.5 t/ha. The wheat following lablab yielded 30% less, on average, than the wheat in a fallow plot, and the profitability of wheat following lablab was slightly higher than that of the wheat following fallow because of greater costs associated with fallow management. The profitability of the lablab-wheat phase was determined after accounting for the input costs and additional costs associated with the management of fallow and in-crop herbicide applications for a fallow-wheat system. The economic and environmental benefits of forage lablab and wheat cropping were also assessed through simulations over a long-term climatic pattern by using economic (PreCAPS) and biophysical (Agricultural Production Systems Simulation, APSIM) decision support models. Analysis of the long-term rainfall pattern (70% in summer and 30% in winter) and simulation studies indicated that ~50% time a wheat crop would not be planted or would fail to produce a profitable crop (grain yield less than 1 t/ha) because of less and unreliable rainfall in winter. Whereas forage lablab in summer would produce a profitable crop, with a forage yield of more than 3 t/ha, ~90% times. Only 14 wheat crops (of 26 growing seasons, i.e. 54%) were profitable, compared with 22 forage lablab (of 25 seasons, i.e. 90%). An opportunistic double-cropping of lablab in summer and wheat in winter is also viable and profitable in 50% of the years. Simulation studies also indicated that an opportunistic lablab-wheat cropping can reduce the potential runoff+drainage by more than 40% in the Roma region, leading to improved economic and environmental benefits.