Infusing the use of seasonal climate forecasting into crop management practice in North East Australia using discussion support software

Seasonal climate forecasting offers potential for improving management of crop production risks in the cropping systems of NE Australia. But how is this capability best connected to management practice? Over the past decade, we have pursued participative systems approaches involving simulation-aided discussion with advisers and decision-makers. This has led to the development of discussion support software as a key vehicle for facilitating infusion of forecasting capability into practice. In this paper, we set out the basis of our approach, its implementation and preliminary evaluation. We outline the development of the discussion support software Whopper Cropper, which was designed for, and in close consultation with, public and private advisers. Whopper Cropper consists of a database of simulation output and a graphical user interface to generate analyses of risks associated with crop management options. The charts produced provide conversation pieces for advisers to use with their farmer clients in relation to the significant decisions they face. An example application, detail of the software development process and an initial survey of user needs are presented. We suggest that discussion support software is about moving beyond traditional notions of supply-driven decision support systems. Discussion support software is largely demand-driven and can compliment participatory action research programs by providing cost-effective general delivery of simulation-aided discussions about relevant management actions. The critical role of farm management advisers and dialogue among key players is highlighted. We argue that the discussion support concept, as exemplified by the software tool Whopper Cropper and the group processes surrounding it, provides an effective means to infuse innovations, like seasonal climate forecasting, into farming practice. Crown Copyright (C) 2002 Published by Elsevier Science Ltd. All rights reserved.

Growth Response of Various Perennial Grasses to Increasing Salinity

Although the effect of salinity on plant growth has been the focus of a substantive research effort, much of this research has failed to adequately separate the various growth limiting aspects of salinity; thus the results are confounded by multiple factors. Eight perennial grass species were grown in a sand culture system dominated by NaCl (electrical conductivities (ECs) between 1.4 and 38 dS m 1), with sufficient Ca added to each treatment to ensure that Na-induced Ca deficiency did not reduce growth. Of the eight perennial grass species examined, Chloris gayana cv. Pioneer (Rhodes grass) was the most salt tolerant species, whilst in comparison, Chrysopogon zizanioides cv. Monto (vetiver) was of only moderate tolerance. However, observed salinity tolerances tended to be lower than those expected from published values based on the threshold salinity model (bent stick model). This discrepancy may be due in part to differences in the evapotranspirational demand between studies; an increase in demand accelerating the accumulation of Na in the shoots and hence decreasing apparent salinity tolerance. It was also observed that the use of a non-saline growth period to allow seed germination and establishment results in the overestimation of vegetative salinity tolerance if not taken into consideration. This is particularly true for species of low salt tolerance due to their comparatively rapid growth in the non-saline medium compared to that at full salinity.

Improving wheat simulation capabilities in Australia from a cropping systems perspective - III. The integrated wheat model (I_WHEAT)

Previous work has identified several short-comings in the ability of four spring wheat and one barley model to simulate crop processes and resource utilization. This can have important implications when such models are used within systems models where final soil water and nitrogen conditions of one crop define the starting conditions of the following crop. In an attempt to overcome these limitations and to reconcile a range of modelling approaches, existing model components that worked demonstrably well were combined with new components for aspects where existing capabilities were inadequate. This resulted in the Integrated Wheat Model (I_WHEAT), which was developed as a module of the cropping systems model APSIM. To increase predictive capability of the model, process detail was reduced, where possible, by replacing groups of processes with conservative, biologically meaningful parameters. I_WHEAT does not contain a soil water or soil nitrogen balance. These are present as other modules of APSIM. In I_WHEAT, yield is simulated using a linear increase in harvest index whereby nitrogen or water limitations can lead to early termination of grainfilling and hence cessation of harvest index increase. Dry matter increase is calculated either from the amount of intercepted radiation and radiation conversion efficiency or from the amount of water transpired and transpiration efficiency, depending on the most limiting resource. Leaf area and tiller formation are calculated from thermal time and a cultivar specific phyllochron interval. Nitrogen limitation first reduces leaf area and then affects radiation conversion efficiency as it becomes more severe. Water or nitrogen limitations result in reduced leaf expansion, accelerated leaf senescence or tiller death. This reduces the radiation load on the crop canopy (i.e. demand for water) and can make nitrogen available for translocation to other organs. Sensitive feedbacks between light interception and dry matter accumulation are avoided by having environmental effects acting directly on leaf area development, rather than via biomass production. This makes the model more stable across environments without losing the interactions between the different external influences. When comparing model output with models tested previously using data from a wide range of agro-climatic conditions, yield and biomass predictions were equal to the best of those models, but improvements could be demonstrated for simulating leaf area dynamics in response to water and nitrogen supply, kernel nitrogen content, and total water and nitrogen use. I_WHEAT does not require calibration for any of the environments tested. Further model improvement should concentrate on improving phenology simulations, a more thorough derivation of coefficients to describe leaf area development and a better quantification of some processes related to nitrogen dynamics. (C) 1998 Elsevier Science B.V.

Analysis of long-term light-trap data for Helicoverpa spp. (Lepidoptera : Noctuidae) in Australia: the effect of climate and crop host plants

Regression analyses of a long series of light-trap catches at Narrabri, Australia, were used to describe the seasonal dynamics of Helicoverpa armigera (Hubner). The size of the second generation was significantly related to the size of the first generation, to winter rainfall, which had a positive effect, and to spring rainfall which had a negative effect. These variables accounted for up to 96% of the variation in size of the second generation from year to year. Rainfall and crop hosts were also important for the size of the third generation. The area and tonnage of many potential host crops were significantly correlated with winter rain. When winter rain was omitted from the analysis, the sizes of both the second and third generations could be expressed as a function of the size of the previous generation and of the areas planted to lucerne, sorghum and maize. Lucerne and maize always had positive coefficients and sorghum a negative one. We extended our analysis to catches of H. punctigera (Wallengren), which declines in abundance after the second generation. Winter rain had a positive effect on the sizes of the second and third generations, and rain in spring or early summer had a negative effect. Only the area grown to lucerne had a positive effect on abundance. Forecasts of pest levels from a few months to a few weeks in advance are discussed, along with the improved understanding of the seasonal dynamics of both species and the significance of crops in the management of insecticide resistance for H. armigera.

Postural activity of the diaphragm is reduced in humans when respiratory demand increases

1. Respiratory activity of the diaphragm and other respiratory muscles is normally co-ordinated with their other functions, such as for postural control of the trunk when the limbs move. The integration may occur by summation of two inputs at the respiratory motoneurons. The present study investigated whether postural activity of the diaphragm changed when respiratory drive increased with hypercapnoea. 2. Electromyographic (EMG) recordings of the diaphragm and other trunk muscles were made with intramuscular electrodes in 13 healthy volunteers. Under control conditions and while breathing through increased dead-space,subjects made rapid repetitive arm movements to disturb the stability of the spine for four periods each lasting 10 s, separated by 50 s. 3. End-tidal CO2, and ventilation increased for the first 60-120 s of the trial then reached a plateau. During rapid arm movement at the start of dead-space breathing, diaphragm EMG became tonic with superimposed modulation at the frequencies of respiration and arm movement. However, when the arm was moved after 60 s of hypercapnoea, the tonic diaphragm EMG during expiration and the phasic activity with arm movement were reduced or absent. Similar changes occurred for the expiratory muscle transversus abdominis, but not for the erector spinae. The mean amplitude of intra-abdominal pressure and the phasic changes with arm movement were reduced after 60 s of hypercapnoea. 4. The present data suggest that increased central respiratory drive may attenuate the postural commands reaching motoneurons. This attenuation can affect the key inspiratory and expiratory muscles and is likely to be co-ordinated at a pre-motoneuronal site.

Applying linear time-varying constraints to econometric models: With an application to demand systems

When linear equality constraints are invariant through time they can be incorporated into estimation by restricted least squares. If, however, the constraints are time-varying, this standard methodology cannot be applied. In this paper we show how to incorporate linear time-varying constraints into the estimation of econometric models. The method involves the augmentation of the observation equation of a state-space model prior to estimation by the Kalman filter. Numerical optimisation routines are used for the estimation. A simple example drawn from demand analysis is used to illustrate the method and its application.

Forecasting regional crop production using SOI phases: an example for the Australian peanut industry

Using peanuts as an example, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing bodies. The industry could profitably use forecasts of likely production to adjust their operations strategically. Significant, physically based lag-relationships exist between an index of ocean/atmosphere El Nino/Southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.

Effect of specific leaf nitrogen on radiation use efficiency and growth of sunflower

Specific leaf nitrogen (SLN, g/m(2)) is known to affect radiation use efficiency (RUE, g/MJ) in different crops, However, this association and importance have not been well established over a range of different nitrogen regimes for held-grown sunflower (Helianthus annuus L.). An experiment was conducted to investigate different combinations and rates of applied nitrogen on SLN, RUE, and growth of sunflower, A fully irrigated crop was sown on an alluvial-prairie soil (Fluventic Haplustoll) and treated with five combinations of applied nitrogen, Greater nitrogen increased biomass, grain number, and yield, but did not affect harvest index energy-corrected for oil (0.4) or canopy extinction coefficient (0.88), Decreases in biomass accumulation under low nitrogen treatments were associated,vith reductions in leaf area index (LAI) and light interception, When SLN and RUE were examined together, both were less in the anthesis to physiological maturity period, but relatively stable between bud visible and anthesis, However, the effects of canopy SLN on RUE were confounded by high SLN in the top of the canopy and the crop maintaining SLN by reducing LAI, Measurements of leaf CO2 assimilation and theoretical analyses of RUE supported that RUE was related to SLN, The major effect of nitrogen on early growth of sunflower was mediated by leaf area and the distribution of SLN in the canopy rather than direct effects of canopy SLN on RUE alone. Greater responses of RUE to SLN are more evident later in growth, and may be related to the demand of nitrogen by the grain.

Potential demand for hedging by Australian wheat producers

The potential for hedging Australian wheat with the new Sydney Futures Exchange wheat contract is examined using a theoretical hedging model parametised from previous studies. The optimal hedging ratio for an 'average' wheat farmer was found to be zero under reasonable assumptions about transaction costs and based on previously published measures of risk aversion. The estimated optimal hedging ratios were found by simulation to be quite sensitive to assumptions about the degree of risk aversion. If farmers are significantly more risk averse than is currently believed, then there is likely to be an active interest in the new futures market.