Risk management strategies using seasonal climate forecasting in irrigated cotton production: a tale of stochastic dominance.

Decision-making in agriculture is carried out in an uncertain environment with farmers often seeking information to reduce risk. As a result of the extreme variability of rainfall and stream-flows in north-eastern Australia, water supplies for irrigated agriculture are a limiting factor and a source of risk. The present study examined the use of seasonal climate forecasting (SCF) when calculating planting areas for irrigated cotton in the northern Murray Darling Basin. Results show that minimising risk by adjusting plant areas in response to SCF can lead to significant gains in gross margin returns. However, how farmers respond to SCF is dependent on several other factors including irrigators’ attitude towards risk.

Peanut stripe potyvirus resistance in peanut (Arachis hypogaea L.) plants carrying viral coat protein gene sequences

Peanut (Arachis hypogaea L.) lines exhibiting high levels of resistance to peanut stripe virus (PStV) were obtained following microprojectile bombardment of embryogenic callus derived from mature seeds. Fertile plants of the commercial cultivars Gajah and NC7 were regenerated following co-bombardmentwith the hygromycin resistance gene and one of two forms of the PStV coat protein (CP) gene, an untranslatable, full length sequence (CP2) or a translatable gene encoding a CP with an N-terminal truncation (CP4). High level resistance to PStV was observed for both transgenes when plants were challenged with the homologous virus isolate. The mechanism of resistance appears to be RNA-mediated, since plants carrying either the untranslatable CP2 or CP4 had no detectable protein expression, but were resistant or immune (no virus replication). Furthermore, highly resistant, but not susceptible CP2 T0 plants contained transgene-specific small RNAs. These plants now provide important germplasm for peanut breeding, particularly in countries where PStV is endemic and poses a major constraint to peanut production.

Identification of small juvenile scombrids from northwest tropical Australia using mitochondrial DNA cytochrome b sequences

Small juveniles of the nine species of scombrids in Australian waters are morphologically similar to one another and, consequently, difficult to identify to species level. We show that the sequence of the mitochondrial DNA cytochrome b gene region is a powerful tool for identification of these young fish. Using this method, we identified 50 juvenile scombrids collected from Exmouth Bay, Western Australia. Six species of scombrids were apparent in this sample of fish: narrow-barred Spanish mackerel (Scomberomorus commerson), Indian mackerel (Rastrelliger kanagurta), frigate tuna (Auxis thazard), bullet tuna (Auxis rochei), leaping bonito (Cybiosarda elegans), and kawakawa (Euthynnus affinis). The presence of Indian mackerel, frigate tuna, leaping bonito, and kawakawa is the first indication that coastal waters may be an important spawning habitat for these species, although offshore spawning may also occur. The occurrence of small juvenile S. commerson was predicted from the known spawning patterns of that species, but other mackerel species (Scomberomorus munroi, Scomberomorus queenslandicus, Scomberomorus semifasiciatus) likely to be spawning during the sampling period were not detected among the 50 small juveniles analyzed here.

Stochastic demography and population dynamics in the red kangaroo Macropus rufus

1. Many organisms inhabit strongly fluctuating environments but their demography and population dynamics are often analysed using deterministic models and elasticity analysis, where elasticity is defined as the proportional change in population growth rate caused by a proportional change in a vital rate. Deterministic analyses may not necessarily be informative because large variation in a vital rate with a small deterministic elasticity may affect the population growth rate more than a small change in a less variable vital rate having high deterministic elasticity. 2. We analyse a stochastic environment model of the red kangaroo (Macropus rufus), a species inhabiting an environment characterized by unpredictable and highly variable rainfall, and calculate the elasticity of the stochastic growth rate with respect to the mean and variability in vital rates. 3. Juvenile survival is the most variable vital rate but a proportional change in the mean adult survival rate has a much stronger effect on the stochastic growth rate. 4. Even if changes in average rainfall have a larger impact on population growth rate, increased variability in rainfall may still be important also in long-lived species. The elasticity with respect to the standard deviation of rainfall is comparable to the mean elasticities of all vital rates but the survival in age class 3 because increased variation in rainfall affects both the mean and variability of vital rates. 5. Red kangaroos are harvested and, under the current rainfall pattern, an annual harvest fraction of c. 20% would yield a stochastic growth rate about unity. However, if average rainfall drops by more than c. 10%, any level of harvesting may be unsustainable, emphasizing the need for integrating climate change predictions in population management and increase our understanding of how environmental stochasticity translates into population growth rate.

Evidence for extensive population structure in the white-spotted eagle ray within the Indo-Pacific inferred from mitochondrial gene sequences

The white-spotted eagle ray Aetobatus narinari is a species complex that occurs circumglobally throughout warm-temperate waters. Aetobatus narinari is semi-pelagic and large (up to 300 cm disc width), suggesting high dispersal capabilities and gene flow on a wide spatial scale. Sequence data from two mitochondrial genes, cytochrome b (cytb) and NADH dehydrogenase subunit 4 (ND4), were used to determine the genetic variability within and among 18 sampling locations in the central Indo-Pacific biogeographical region. Populations in the Indo-Pacific were highly genetically structured with c. 70% of the total genetic variation found among three geographical regions (East China Sea, Southeast Asia and Australia). FST was 0.64 for cytb and 0.53 for ND4, with φST values being even larger, that is, 0.78 for cytb and 0.65 for ND4. This high-level genetic partitioning provides strong evidence against extensive gene flow in A. narinari. The degree of genetic population structuring in the Indo-Pacific was similar to that found on a global scale. Global FST was 0.63 for cytb and 0.57 for ND4, and global φST values were 0.94 for cytb and 0.82 for ND4. This suggests that the A. narinari complex may be more speciose than the two or three species proposed to date. Further sampling and genetic analyses are likely to uncover the ‘evolutionarily significant’ and ‘management’ units that are critical to determine the susceptibilities of individual populations to regional fishing pressures and to provide advice on management options. Network analyses showed a close genetic relationship between haplotypes from the central Indo-Pacific and South Africa, providing support for a proposed dispersal pathway from the possible centre of origin of the A. narinari species complex in the Indo-Pacific into the Atlantic Ocean.

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.

Stochastic growth of the Eastern King Prawn (melicertus plebejus (hess, 1865)) harvested off Eastern Australia

Stochastic growth models were fitted to length-increment data of eastern king prawns, Melicertus plebejus (Hess, 1865), tagged across eastern Australia. The estimated growth parameters and growth transition matrix are for each sex representative of the species' geographical distribution. Our study explicitly displays the stochastic nature of prawn growth. Capturing length-increment growth heterogeneity for short-lived exploited species such as prawns that cannot be readily aged is essential for length-based modelling and improved management.

Stochastic model for simulating maize yield

Maize is one of the most important crops in the world. The products generated from this crop are largely used in the starch industry, the animal and human nutrition sector, and biomass energy production and refineries. For these reasons, there is much interest in figuring the potential grain yield of maize genotypes in relation to the environment in which they will be grown, as the productivity directly affects agribusiness or farm profitability. Questions like these can be investigated with ecophysiological crop models, which can be organized according to different philosophies and structures. The main objective of this work is to conceptualize a stochastic model for predicting maize grain yield and productivity under different conditions of water supply while considering the uncertainties of daily climate data. Therefore, one focus is to explain the model construction in detail, and the other is to present some results in light of the philosophy adopted. A deterministic model was built as the basis for the stochastic model. The former performed well in terms of the curve shape of the above-ground dry matter over time as well as the grain yield under full and moderate water deficit conditions. Through the use of a triangular distribution for the harvest index and a bivariate normal distribution of the averaged daily solar radiation and air temperature, the stochastic model satisfactorily simulated grain productivity, i.e., it was found that 10,604 kg ha(-1) is the most likely grain productivity, very similar to the productivity simulated by the deterministic model and for the real conditions based on a field experiment. © 2012 American Society of Agricultural and Biological Engineers.

Large-chamber methane and nitrous oxide measurements are comparable to the backward Lagrangian stochastic method

Measurement of individual emission sources (e.g., animals or pen manure) within intensive livestock enterprises is necessary to test emission calculation protocols and to identify targets for decreased emissions. In this study, a vented, fabric-covered large chamber (4.5 × 4.5 m, 1.5 m high; encompassing greater spatial variability than a smaller chamber) in combination with on-line analysis (nitrous oxide [N2O] and methane [CH4] via Fourier Transform Infrared Spectroscopy; 1 analysis min-1) was tested as a means to isolate and measure emissions from beef feedlot pen manure sources. An exponential model relating chamber concentrations to ambient gas concentrations, air exchange (e.g., due to poor sealing with the surface; model linear when ≈ 0 m3 s-1), and chamber dimensions allowed data to be fitted with high confidence. Alternating manure source emission measurements using the large-chamber and the backward Lagrangian stochastic (bLS) technique (5-mo period; bLS validated via tracer gas release, recovery 94-104%) produced comparable N2O and CH4 emission values (no significant difference at P < 0.05). Greater precision of individual measurements was achieved via the large chamber than for the bLS (mean ± standard error of variance components: bLS half-hour measurements, 99.5 ± 325 mg CH4 s-1 and 9.26 ± 20.6 mg N2O s-1; large-chamber measurements, 99.6 ± 64.2 mg CH4 s-1 and 8.18 ± 0.3 mg N2O s-1). The large-chamber design is suitable for measurement of emissions from manure on pen surfaces, isolating these emissions from surrounding emission sources, including enteric emissions. © © American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.

Identifying risk-efficient strategies using stochastic frontier analysis and simulation: An application to irrigated cropping in Australia

In irrigated cropping, as with any other industry, profit and risk are inter-dependent. An increase in profit would normally coincide with an increase in risk, and this means that risk can be traded for profit. It is desirable to manage a farm so that it achieves the maximum possible profit for the desired level of risk. This paper identifies risk-efficient cropping strategies that allocate land and water between crop enterprises for a case study of an irrigated farm in Southern Queensland, Australia. This is achieved by applying stochastic frontier analysis to the output of a simulation experiment. The simulation experiment involved changes to the levels of business risk by systematically varying the crop sowing rules in a bioeconomic model of the case study farm. This model utilises the multi-field capability of the process based Agricultural Production System Simulator (APSIM) and is parameterised using data collected from interviews with a collaborating farmer. We found sowing rules that increased the farm area sown to cotton caused the greatest increase in risk-efficiency. Increasing maize area also improved risk-efficiency but to a lesser extent than cotton. Sowing rules that increased the areas sown to wheat reduced the risk-efficiency of the farm business. Sowing rules were identified that had the potential to improve the expected farm profit by ca. $50,000 Annually, without significantly increasing risk. The concept of the shadow price of risk is discussed and an expression is derived from the estimated frontier equation that quantifies the trade-off between profit and risk.

Two Complete Genome Sequences of Phasey Bean Mild Yellows Virus, a Novel Member of the Luteoviridae from Australia

We present here the complete genome sequences of a novel polerovirus from Trifolium subterraneum (subterranean clover) and Cicer arietinum (chickpea) and compare these to a partial viral genome sequence obtained from Macroptilium lathyroides (phasey bean). We propose the name phasey bean mild yellows virus for this novel polerovirus.