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.

Scoping genetic tools, their limitations and applications for wild fisheries management

FRDC has commissioned a review of the role that existing and future genetic technologies may play in addressing critical challenges facing the exploitation of wild fisheries. Wild fisheries management has been assisted by genetic research for over 50 years and in Australia, this research has been largely funded by FRDC. Both fisheries management and the methods of genetic analysis have changed significantly during this time. Given these dynamics, as well as perceptions that communication between fisheries managers and geneticists has been poor in some cases, there is a strong need to reassess the ways in which genetic research can contribute to fisheries and for all stakeholders to critically examine each other's needs and capabilities.

The intrinsic plasticity of farm businesses and their resilience to change. An Australian example.

This paper examines the idea that plasticity in farm management introduces resilience to change and allows farm businesses to perform when operating in highly variable environments. We also argue for the need to develop and apply more integrative assessments of farm performance that combine the use of modelling tools with deliberative processes involving farmers and researchers in a co-learning process, to more effectively identify and implement more productive and resilient farm businesses. In a plastic farming system, farm management is highly contingent on environmental conditions. In plastic farming systems farm managers constantly vary crops and inputs based on the availability of limited and variable resources (e.g. land, water, finances, labour, machinery, etc.), and signals from its operating environment (e.g. climate, markets), with the objective of maximising a number of, often competing, objectives (e.g. maximise profits, minimise risks, etc.). In contrast in more rigid farming systems farm management is more calendar driven and relatively fixed sequences of crops are regularly followed over time and across the farm. Here we describe the application of a whole farm simulation model to (i) compare, in silico, the sensitivity of two farming systems designs of contrasting levels of plasticity, operating in two contrasting environments, when exposed to a stressor in the form of climate change scenarios;(ii) investigate the presence of interactions and feedbacks at the field and farm levels capable of modifying the intensity and direction of the responses to climate signals; and (iii) discuss the need for the development and application of more integrative assessments in the analysis of impacts and adaptation options to climate change. In both environments, the more plastic farm management strategy had higher median profits and was less risky for the baseline and less intensive climate change scenarios (2030). However, for the more severe climate change scenarios (2070), the benefit of plastic strategies tended to disappear. These results suggest that, to a point, farming systems having higher levels of plasticity would enable farmers to more effectively respond to climate shifts, thus ensuring the economic viability of the farm business. Though, as the intensity of the stress increases (e.g. 2070 climate change scenario) more significant changes in the farming system might be required to adapt. We also found that in the case studies analysed here, most of the impacts from the climate change scenarios on farm profit and economic risk originated from important reductions in cropping intensity and changes in crop mix rather than from changes in the yields of individual crops. Changes in cropping intensity and crop mix were explained by the combination of reductions in the number of sowing opportunities around critical times in the cropping calendar, and to operational constraints at the whole farm level i.e. limited work capacity in an environment having fewer and more concentrated sowing opportunities. This indicates that indirect impacts from shifts in climate on farm operations can be more important than direct impacts from climate on the yield of individual crops. The results suggest that due to the complexity of farm businesses, impact assessments and opportunities for adaptation to climate change might also need to be pursued at higher integration levels than the crop or the field. We conclude that plasticity can be a desirable characteristic in farming systems operating in highly variable environments, and that integrated whole farm systems analyses of impacts and adaptation to climate change are required to identify important interactions between farm management decision rules, availability of resources, and farmer's preference.

Simulation of parthenium weed canopy under changing climate using L-systems

Parthenium weed (Parthenium hysterophorus L.) is an erect, branched, annual plant of the family Asteraceae. It is native to the tropical Americas, while now widely distributed throughout Africa, Asia, Oceania, and Australasia. Due to its allelopathic and toxic characteristics, parthenium weed has been considered to be a weed of global significance. These effects occur across agriculture (crops and pastures), within natural ecosystems, and has impacts upon health (human and animals). Although integrated weed management (IWM) for parthenium weed has had some success, due to its tolerance and good adaptability to temperature, precipitation, and CO2, this weed has been predicted to become more vigorous under a changing climate resulting in an altered canopy architecture. From the viewpoint of IWM, the altered canopy architecture may be associated with not only improved competitive ability and replacement but also may alter the effectiveness of biocontrol agents and other management strategies. This paper reports on a preliminary study on parthenium weed canopy architecture at three temperature regimes (day/night 22/15 °C, 27/20 °C, and 32/25 °C in thermal time 12/12 hours) and establishes a threedimensional (3D) canopy model using Lindenmayer-systems (L-systems). This experiment was conducted in a series of controlled environment rooms with parthenium weed plants being grown in a heavy clay soil. A sonic digitizer system was used to record the morphology, topology, and geometry of the plants for model construction. The main findings include the determination of the phyllochron which enables the prediction of parthenium weed growth under different temperature regimes and that increased temperature enhances growth and enlarges the plants canopy size and structure. The developed 3D canopy model provides a tool to simulate and predict the weed growth in response to temperature, and can be adjusted for studies of other climatic variables such as precipitation and CO2. Further studies are planned to investigate the effects of other climatic variables, and the predicted changes in the pathogenic biocontrol agent effectiveness.

Economic aspects of post-border weed risk management

Aim: Decision-making in weed management involves consideration of limited budgets, long time horizons, conflicting priorities, and as a result, trade-offs. Economics provides tools that allow these issues to be addressed and is thus integral to management of the risks posed by weeds. One of the critical issues in weed risk management during the early stages of an invasion concerns feasibility of eradication. We briefly review how economics may be used in weed risk management, concentrating on this management strategy. Location: Australia. Methods: A range of innovative studies that investigate aspects of weed risk management are reviewed. We show how these could be applied to newly invading weeds, focussing on methods for investigating eradication feasibility. In particular, eradication feasibility is analysed in terms of cost and duration of an eradication programme, using a simulation model based on field-derived parameter values for chromolaena, Chromolaena odorata. Results: The duration of an eradication programme can be reduced by investing in progressively higher amounts of search effort per hectare, but increasing search area will become relatively more expensive as search effort increases. When variation in survey and control success is taken into account, increasing search effort also reduces uncertainty around the required duration of the eradication programme. Main conclusions: Economics is integral to the management of the risks posed by weeds. Decision analysis, based on economic principles, is now commonly used to tackle key issues that confront weed managers. For eradication feasibility, duration and cost of a weed eradication programme are critical components; the dimensions of both factors can usefully be estimated through simulation. © 2013 John Wiley & Sons Ltd.

Sustainable management for rangelands in a variable climate: evidence and insights from northern Australia

Inter-annual rainfall variability is a major challenge to sustainable and productive grazing management on rangelands. In Australia, rainfall variability is particularly pronounced and failure to manage appropriately leads to major economic loss and environmental degradation. Recommended strategies to manage sustainably include stocking at long-term carrying capacity (LTCC) or varying stock numbers with forage availability. These strategies are conceptually simple but difficult to implement, given the scale and spatial heterogeneity of grazing properties and the uncertainty of the climate. This paper presents learnings and insights from northern Australia gained from research and modelling on managing for rainfall variability. A method to objectively estimate LTCC in large, heterogeneous paddocks is discussed, and guidelines and tools to tactically adjust stocking rates are presented. The possible use of seasonal climate forecasts (SCF) in management is also considered. Results from a 13-year grazing trial in Queensland show that constant stocking at LTCC was far more profitable and largely maintained land condition compared with heavy stocking (HSR). Variable stocking (VAR) with or without the use of SCF was marginally more profitable, but income variability was greater and land condition poorer than constant stocking at LTCC. Two commercial scale trials in the Northern Territory with breeder cows highlighted the practical difficulties of variable stocking and provided evidence that heavier pasture utilisation rates depress reproductive performance. Simulation modelling across a range of regions in northern Australia also showed a decline in resource condition and profitability under heavy stocking rates. Modelling further suggested that the relative value of variable v. constant stocking depends on stocking rate and land condition. Importantly, variable stocking may possibly allow slightly higher stocking rates without pasture degradation. Enterprise-level simulations run for breeder herds nevertheless show that poor economic performance can occur under constant stocking and even under variable stocking in some circumstances. Modelling and research results both suggest that a form of constrained flexible stocking should be applied to manage for climate variability. Active adaptive management and research will be required as future climate changes make managing for rainfall variability increasingly challenging.

Issues of Digital Ecosystems Approach to Biological Ecosystem Simulation Model Fit Optimization

This study examines the application of digital ecosystems concepts to a biological ecosystem simulation problem. The problem involves the use of a digital ecosystem agent to optimize the accuracy of a second digital ecosystem agent, the biological ecosystem simulation. The study also incorporates social ecosystems, with a technological solution design subsystem communicating with a science subsystem and simulation software developer subsystem to determine key characteristics of the biological ecosystem simulation. The findings show similarities between the issues involved in digital ecosystem collaboration and those occurring when digital ecosystems interact with biological ecosystems. The results also suggest that even precise semantic descriptions and comprehensive ontologies may be insufficient to describe agents in enough detail for use within digital ecosystems, and a number of solutions to this problem are proposed.

Assessing the sustainability of wheat-based cropping systems using simulation modelling: sustainability

Concepts of agricultural sustainability and possible roles of simulation modelling for characterising sustainability were explored by conducting, and reflecting on, a sustainability assessment of rain-fed wheat-based systems in the Middle East and North Africa region. We designed a goal-oriented, model-based framework using the cropping systems model Agricultural Production Systems sIMulator (APSIM). For the assessment, valid (rather than true or false) sustainability goals and indicators were identified for the target system. System-specific vagueness was depicted in sustainability polygons-a system property derived from highly quantitative data-and denoted using descriptive quantifiers. Diagnostic evaluations of alternative tillage practices demonstrated the utility of the framework to quantify key bio-physical and chemical constraints to sustainability. Here, we argue that sustainability is a vague, emergent system property of often wicked complexity that arises out of more fundamental elements and processes. A 'wicked concept of sustainability' acknowledges the breadth of the human experience of sustainability, which cannot be internalised in a model. To achieve socially desirable sustainability goals, our model-based approach can inform reflective evaluation processes that connect with the needs and values of agricultural decision-makers. Hence, it can help to frame meaningful discussions, from which actions might emerge.

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.

Status, challenges and tools for identification and diagnosis of Peronosclerospora and Sclerophthora of regulatory concern for graminicolous crops

Graminicolous Downy Mildew (GDM) diseases caused by the genera Peronosclerospora (13 spp.) and Sclerophthora (6 spp. and 1 variety) are poorly studied but destructive diseases of major crops such as corn, sorghum, sugarcane and other graminoids. Eight of the 13 described Peronosclerospora spp. are able to infect corn. In particular, P. philippinensis (= P. sacchari), P. maydis, P. heteropogonis, and S. rayssiae var. zeae cause major losses in corn yields in tropical Asia. In 2012 a new species, P. australiensis, was described based on isolates previously identified as P. maydis in Australia; this species is now a pathogen of major concern. Despite the strong impact of GDM diseases, there are presently no reliable molecular methods available for their detection. GDM pathogens are among the most difficult Oomycetes to identify using molecular tools, as their taxonomy is very challenging, and little genetic sequence data are available for development of molecular tools to detect GDM pathogens to species level. For example, from over 15 genes used in identification, diagnostics or phylogeny of Phytophthora, only ITS1 and cox2 show promise for use with GDM pathogens. Multiplex/multigene conventional and qPCR assays are currently under evaluation for the detection of economically important GDM spp. Scientists from the USA, Germany, Canada, Australia, and the Philippines are collaborating on the development and testing of diagnostic tools for these pathogens of concern.

Resting pastures to improve land condition in northern Australia: guidelines based on the literature and simulation modelling

Pasture rest is a possible strategy for improving land condition in the extensive grazing lands of northern Australia. If pastures currently in poor condition could be improved, then overall animal productivity and the sustainability of grazing could be increased. The scientific literature is examined to assess the strength of the experimental information to support and guide the use of pasture rest, and simulation modelling is undertaken to extend this information to a broader range of resting practices, growing conditions and initial pasture condition. From this, guidelines are developed that can be applied in the management of northern Australia’s grazing lands and also serve as hypotheses for further field experiments. The literature on pasture rest is diverse but there is a paucity of data from much of northern Australia as most experiments have been conducted in southern and central parts of Queensland. Despite this, the limited experimental information and the results from modelling were used to formulate the following guidelines. Rest during the growing season gives the most rapid improvement in the proportion of perennial grasses in pastures; rest during the dormant winter period is ineffective in increasing perennial grasses in a pasture but may have other benefits. Appropriate stocking rates are essential to gain the greatest benefit from rest: if stocking rates are too high, then pasture rest will not lead to improvement; if stocking rates are low, pastures will tend to improve without rest. The lower the initial percentage of perennial grasses, the more frequent the rests should be to give a major improvement within a reasonable management timeframe. Conditions during the growing season also have an impact on responses with the greatest improvement likely to be in years of good growing conditions. The duration and frequency of rest periods can be combined into a single value expressed as the proportion of time during which resting occurs; when this is done the modelling suggests the greater the proportion of time that a pasture is rested, the greater is the improvement but this needs to be tested experimentally. These guidelines should assist land managers to use pasture resting but the challenge remains to integrate pasture rest with other pasture and animal management practices at the whole-property scale.

Modelling the manager: Representing rule-based management in farming systems simulation models

We trace the evolution of the representation of management in cropping and grazing systems models, from fixed annual schedules of identical actions in single paddocks toward flexible scripts of rules. Attempts to define higher-level organizing concepts in management policies, and to analyse them to identify optimal plans, have focussed on questions relating to grazing management owing to its inherent complexity. “Rule templates” assist the re-use of complex management scripts by bundling commonly-used collections of rules with an interface through which key parameters can be input by a simulation builder. Standard issues relating to parameter estimation and uncertainty apply to management sub-models and need to be addressed. Techniques for embodying farmers' expectations and plans for the future within modelling analyses need to be further developed, especially better linking planning- and rule-based approaches to farm management and analysing the ways that managers can learn.

Boosting the productivity and profitability of northern Australian beef enterprises: Exploring innovation options using simulation modelling and systems analysis

The financial health of beef cattle enterprises in northern Australia has declined markedly over the last decade due to an escalation in production and marketing costs and a real decline in beef prices. Historically, gains in animal productivity have offset the effect of declining terms of trade on farm incomes. This raises the question of whether future productivity improvements can remain a key path for lifting enterprise profitability sufficient to ensure that the industry remains economically viable over the longer term. The key objective of this study was to assess the production and financial implications for north Australian beef enterprises of a range of technology interventions (development scenarios), including genetic gain in cattle, nutrient supplementation, and alteration of the feed base through introduced pastures and forage crops, across a variety of natural environments. To achieve this objective a beef systems model was developed that is capable of simulating livestock production at the enterprise level, including reproduction, growth and mortality, based on energy and protein supply from natural C4 pastures that are subject to high inter-annual climate variability. Comparisons between simulation outputs and enterprise performance data in three case study regions suggested that the simulation model (the Northern Australia Beef Systems Analyser) can adequately represent the performance beef cattle enterprises in northern Australia. Testing of a range of development scenarios suggested that the application of individual technologies can substantially lift productivity and profitability, especially where the entire feedbase was altered through legume augmentation. The simultaneous implementation of multiple technologies that provide benefits to different aspects of animal productivity resulted in the greatest increases in cattle productivity and enterprise profitability, with projected weaning rates increasing by 25%, liveweight gain by 40% and net profit by 150% above current baseline levels, although gains of this magnitude might not necessarily be realised in practice. While there were slight increases in total methane output from these development scenarios, the methane emissions per kg of beef produced were reduced by 20% in scenarios with higher productivity gain. Combinations of technologies or innovative practices applied in a systematic and integrated fashion thus offer scope for providing the productivity and profitability gains necessary to maintain viable beef enterprises in northern Australia into the future.

Investigation of an emerging bacterial disease in wild Queensland groper, marine fish and stingrays with production of diagnostic tools to reduce the spread of disease to other states of Australia : final report

This project describes how Streptococcus agalactiae can be transmitted experimentally in Queensland grouper. The implications of this research furthers the relatedness between Australian S. agalactiae strains from animals and humans. Additionally, this research has developed diagnostic tools for Australian State Veterinary Laboratories and Universities, which will assist in State and National aquatic animal disease detection, surveillance, disease monitoring and reporting