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.

Effect of exposure period on degree of dominance of phosphine resistance in adults of Rhyzopertha dominica (Coleoptera: Bostrychidae) and Sitophilus oryzae (Coleoptera: Curculionidae)

Degree of dominance of phosphine resistance was investigated in adults of Rhyzopertha dominica F and Sitophilus oryzae L. Efficacy of the grain fumigant phosphine depends on both concentration and exposure period, which raises the possibility that dominance levels vary with exposure period. New and published data were used to test this possibility in adults of R dominica and S oryzae fumigated for periods of up to 144 h. The concentrations required for control of homozygous resistant and susceptible strains and their F1 hybrids decreased with increasing exposure period. For both species the response lines for the homozygous resistant and susceptible strains and their F1 hybrids were parallel. Therefore, neither dominance level nor resistance factor was affected by exposure period. Resistance was incompletely recessive and the level of dominance, calculated at 50% mortality level, was -0.59 for R dominica and -0.65 for S oryzae. The resistant R dominica strain was 30.9 times more resistant than the susceptible strain, compared with 8.9 times for the resistant S oryzae strain. The results suggest that developing discriminating doses for detecting heterozygote adults of either species will be difficult.

High resolution genetic and physical mapping of the I-3 region of tomato chromosome 7 reveals almost continuous microsynteny with grape chromosome 12 but interspersed microsynteny with duplications on Arabidopsis chromosomes 1, 2 and 3

The tomato I-3 gene introgressed from the Lycopersicon pennellii accession LA716 confers resistance to race 3 of the fusarium wilt pathogen Fusarium oxysporum f. sp. lycopersici. We have improved the high-resolution map of the I-3 region of tomato chromosome 7 with the development and mapping of 31 new PCR-based markers. Recombinants recovered from L. esculentum cv. M82 × IL7-2 F2 and (IL7-2 × IL7-4) × M82 TC1F2 mapping populations, together with recombinants recovered from a previous M82 × IL7-3 F2 mapping population, were used to position these markers. A significantly higher recombination frequency was observed in the (IL7-2 × IL7-4) × M82 TC1F2 mapping population based on a reconstituted L. pennellii chromosome 7 compared to the other two mapping populations based on smaller segments of L. pennellii chromosome 7. A BAC contig consisting of L. esculentum cv. Heinz 1706 BACs covering the I-3 region has also been established. The new high-resolution map places the I-3 gene within a 0.38 cM interval between the molecular markers RGA332 and bP23/gPT with an estimated physical size of 50-60 kb. The I-3 region was found to display almost continuous microsynteny with grape chromosome 12 but interspersed microsynteny with Arabidopsis thaliana chromosomes 1, 2 and 3. An S-receptor-like kinase gene family present in the I-3 region of tomato chromosome 7 was found to be present in the microsyntenous region of grape chromosome 12 but was absent altogether from the A. thaliana genome.

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.

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.

Inheritance and relative dominance, expressed as toxicity response and delayed development, of phosphine resistance in immature stages of Rhyzopertha dominica (F.) (Coleoptera: Bostrichidae)

Fumigation of stored grain with phosphine (PH 3) is used widely to control the lesser grain borer Rhyzopertha dominica. However, development of high level resistance to phosphine in this species threatens control. Effective resistance management relies on knowledge of the expression of resistance in relation to dosage at all life stages. Therefore, we determined the mode of inheritance of phosphine resistance and strength of the resistance phenotype at each developmental stage. We achieved this by comparing mortality and developmental delay between a strongly resistant strain (R-strain), a susceptible strain (S-strain) and their F 1 progenies. Resistance was a maternally inherited, semi-dominant trait in the egg stage but was inherited as an autosomal, incompletely recessive trait in larvae and pupae. The rank order of developmental tolerance in both the sensitive and resistant strains was eggs > pupae > larvae. Comparison of published values for the response of adult R. dominica relative to our results from immature stages reveals that the adult stage of the S-strain is more sensitive to phosphine than are larvae. This situation is reversed in the R-strain as the adult stage is much more resistant to phosphine than even the most tolerant immature stage. Phosphine resistance factors at LC 50 were eggs 400×, larvae 87× and pupae 181× with respect to reference susceptible strain (S-strain) adults indicating that tolerance conferred by a particular immature stage neither strongly nor reliably interacts with the genetic resistance element. Developmental delay relative to unfumigated control insects was observed in 93% of resistant pupae, 86% of resistant larvae and 41% of resistant eggs. Increased delay in development and the toxicity response to phosphine exposure were both incompletely recessive. We show that resistance to phosphine has pleiotropic effects and that the expression of these effects varies with genotype and throughout the life history of the insect. © 2012.

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.