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.

Marine resources, biophysical processes, and environmental management of a tropical shelf seaway: Torres Strait, Australia-Introduction to the special issue

This special issue of Continental Shelf Research contains 20 papers giving research results produced as part of Australia's Torres Strait Co-operative Research Centre (CRC) Program, which was funded over a three-year period during 2003-2006. Marine biophysical, fisheries, socioeconomic-cultural and extension research in the Torres Strait region of northeastern Australia was carried out to meet three aims: 1) support the sustainable development of marine resources and minimize impacts of resource use in Torres Strait; 2) enhance the conservation of the marine environment and the social, cultural and economic well being of all stakeholders, particularly the Torres Strait peoples; and 3) contribute to effective policy formulation and management decision making. Subjects covered, including commercial and traditional fisheries management, impacts of anthropogenic sediment inputs on seagrass meadows and communication of science results to local communities, have broad applications to other similar environments.

Processes leading to the detection of tropical weed infestations during an eradication program.

The authors identify and track processes that have resulted in the detection of six tropical weeds targeted for eradication. The habitats and distributions of these species make detection by field officers and members of the public more likely than targeted searches. The eradication program is increasing the scope of detection processes by conducting and documenting activities to improve weed recognition amongst public, government and industry stakeholders.

Will biological control of Lantana camara ever succeed? Patterns, processes & prospects

Despite biocontrol research spanning over 100 years, the hybrid weed, commonly referred to as Lantana camara, is not under adequate control. Host specificity and varietal preference of released agents, climatic suitability of a region for released agents, number of agents introduced and range or area of infestation appear to play a role in limiting biocontrol success. At least one of 41 species of mainly leaf- or flower-feeding insects has been introduced, or spread, to 41 of the 70 countries or regions where lantana occurs. Over half (26) of these species have established, achieving varying levels of herbivory and presumably some degree of control. Accurate taxonomy of the plant and adaptation of potential agents to the host plant are some of the better predictors of at least establishment success. Retrospective analysis of the hosts of introduced biocontrol agents for L. camara show that a greater proportion of agents that were collected from L. camara or Lantana urticifolia established, than agents that were collected from other species of Lantana. Of the introduced agents that had established and were oligophagous, 18 out of 22 established. The proportion of species establishing, declined with the number of species introduced. However, there was no trend when oceanic islands were treated separately from mainland areas and the result is likely an artefact of how introductions have changed over time. A calculated index of the degree of herbivory due to agents known to have caused some damage per country, was not related to land area infested with lantana for mainlands nor for oceanic islands. However, the degree of herbivory is much higher on islands than mainlands. This difference between island and mainland situations may reflect population dynamics in patchy or metapopulation landscapes. Basic systematic studies of the host remain crucial to successful biocontrol, especially of hybrid weeds like L. camara. Potential biocontrol agents should be monophages collected from the most closely related species to the target weed or be phytophages that attack several species of lantana. Suitable agents should be released in the most ideal ecoclimatic area. Since collection of biocontrol agents has been limited to a fraction of the known number of phytophagous species available, biocontrol may be improved by targeting insects that feed on stems and roots, as well as the agents that feed on leaves and flowers.

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.

Impacts of improved grazing land management on sediment yields, Part 1: Hillslope processes.

Summary Poor land condition resulting from unsustainable grazing practices can reduce enterprise profitability and increase water, sediment and associated nutrient runoff from properties and catchments. This paper presents the results of a 6 year field study that used a series of hillslope flume experiments to evaluate the impact of improved grazing land management (GLM) on hillslope runoff and sediment yields. The study was carried out on a commercial grazing property in a catchment draining to the Burdekin River in northern Australia. During this study average ground cover on hillslopes increased from ~35% to ~75%, although average biomass and litter levels are still relatively low for this landscape type (~60 increasing to 1100 kg of dry matter per hectare). Pasture recovery was greatest on the upper and middle parts of hillslopes. Areas that did not respond to the improved grazing management had <10% cover and were on the lower slopes associated with the location of sodic soil and the initiation of gullies. Comparison of ground cover changes and soil conditions with adjacent properties suggest that grazing management, and not just improved rainfall conditions, were responsible for the improvements in ground cover in this study. The ground cover improvements resulted in progressively lower runoff coefficients for the first event in each wet season, however, runoff coefficients were not reduced at the annual time scale. The hillslope annual sediment yields declined by ~70% on two out of three hillslopes, although where bare patches (with <10% cover) were connected to gullies and streams, annual sediment yields increased in response to higher rainfall in latter years of the study. It appears that bare patches are the primary source areas for both runoff and erosion on these hillslopes. Achieving further reductions in runoff and erosion in these landscapes may require management practices that improve ground cover and biomass in bare areas, particularly when they are located adjacent to concentrated drainage lines.

Simple software processes and tests improve the reliability and usefulness of a model.

Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a 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.

How weed control and fertilisation influence tree physiological processes and growth at early establishment in an exotic F1 hybrid pine plantation of subtropical Australia

Purpose This study investigated how nitrogen (N) nutrition and key physiological processes varied under changed water and nitrogen competition resulting from different weed control and fertilisation treatments in a 2-year-old F1 hybrid (Pinus elliottii Engelm var. elliottii × P. caribaea var. hondurensis Barr. ex Golf.) plantation on a grey podzolic soil type, in Southeast Queensland. Materials and methods The study integrated a range of measures including growth variables (diameter at ground level (DGL), diameter at breast height (DBH) and height (H)), foliar variables (including foliar N concentration, foliar δ13C and δ15N) and physiological variables (including photosynthesis (An), stomatal conductance (gs), transpiration (E), intrinsic water use efficiency (WUEi) (A/gs) and xylem pressure potential (ΨXPP)) to better understand the mechanisms influencing growth under different weed control and fertilisation treatments. Five levels of weed control were applied: standard (routine), luxury, intermediate, mechanical and nil weed control, all with routine fertilisation plus an additional treatment, routine weed control and luxury fertilisation. Relative weed cover was assessed at 0.8, 1.1 and 1.6 years after plantation establishment to monitor the effectiveness of weed control treatments. Soil investigation included soil ammonium (NH4 +-N), nitrate (NO3 −-N), potentially mineralizable N (PMN), gravimetric soil moisture content (MC), hot water extractable organic carbon (HWETC), hot water extractable total N (HWETN), total C, total N, stable C isotope composition (δ13C), stable N isotope composition (δ15N), total P and extractable K. Results and discussion There were significant relationships between foliar N concentrations and relative weed cover and between tree growth and foliar N concentration or foliar δ15N, but initial site preparation practices also increased soil N transformations in the planting rows reducing the observable effects of weed control on foliar δ15N. A positive relationship between foliar N concentration and foliar δ13C or photosynthesis indicated that increased N availability to trees positively influenced non-stomatal limitations to photosynthesis. However, trees with increased foliar N concentrations and photosynthesis were negatively related to xylem pressure potential in the afternoons which enhanced stomatal limitations to photosynthesis and WUEi. Conclusions Luxury and intermediate weed control and luxury fertilisation positively influenced growth at early establishment by reducing the competition for water and N resources. This influenced fundamental key physiological processes such as the relationships between foliar N concentration, A n, E, gs and ΨXPP. Results also confirmed that time from cultivation is an important factor influencing the effectiveness of using foliar δ15N as an indicator of soil N transformations.

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.

The plasticity of NBS resistance genes in sorghum is driven by multiple evolutionary processes

Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.