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.

A semi-empirical theory of molten salts

A semi-empirical model is presented for describing the interionic interactions in molten salts using the experimentally available structure data. An extension of Bertaut's method of non-overlapping charges is used to estimate the electrostatic interaction energy in ionic melts. It is shown, in agreement with earlier computer simulation studies, that this energy increases when an ionic salt melts. The repulsion between ions is described using a compressible ion theory which uses structure-independent parameters. The van der Waals interactions and the thermal free energy are also included in the total energy, which is minimised with respect to isostructural volume variations to calculate the equilibrium density. Detailed results are presented for three molten systems, NaCl, CaCl2 and ZnCl2, and are shown to be in satisfactory agreement with experiments. With reliable structural data now being reported for several other molten salts, the present study gains relevance.

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.

Evolution of texture during equal channel angular extrusion of commercially pure aluminum: Experiments and simulations

The evolution of crystallographic texture has been comprehensively studied for commercially pure Al as a function of amount of ECAE deformation for the three major routes of ECAE processing. It has been observed that processing through different routes leads to different type of texture, in both qualitative as well as quantitative sense. The results have been analyzed on the basis of existing concepts on ECAE deformation and simulations have been carried out using the simple shear model of ECAE implemented into the Viscoplastic Self Consistent model of polycrystal plasticity. The simulations revealed that non-octahedral slip is needed to reproduce the experimental texture development.

APSIM – Evolution towards a new generation of agricultural systems simulation

Agricultural systems models worldwide are increasingly being used to explore options and solutions for the food security, climate change adaptation and mitigation and carbon trading problem domains. APSIM (Agricultural Production Systems sIMulator) is one such model that continues to be applied and adapted to this challenging research agenda. From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond. Keating et al. (2003) described many of the fundamental attributes of APSIM in detail. Much has changed in the last decade, and the APSIM community has been exploring novel scientific domains and utilising software developments in social media, web and mobile applications to provide simulation tools adapted to new demands. This paper updates the earlier work by Keating et al. (2003) and chronicles the changing external challenges and opportunities being placed on APSIM during the last decade. It also explores and discusses how APSIM has been evolving to a “next generation” framework with improved features and capabilities that allow its use in many diverse topics.

Sympatric prey responses to lethal top-predator control: predator manipulation experiments

Introduction Many prey species around the world are suffering declines due to a variety of interacting causes such as land use change, climate change, invasive species and novel disease. Recent studies on the ecological roles of top-predators have suggested that lethal top-predator control by humans (typically undertaken to protect livestock or managed game from predation) is an indirect additional cause of prey declines through trophic cascade effects. Such studies have prompted calls to prohibit lethal top-predator control with the expectation that doing so will result in widespread benefits for biodiversity at all trophic levels. However, applied experiments investigating in situ responses of prey populations to contemporary top-predator management practices are few and none have previously been conducted on the eclectic suite of native and exotic mammalian, reptilian, avian and amphibian predator and prey taxa we simultaneously assess. We conducted a series of landscape-scale, multi-year, manipulative experiments at nine sites spanning five ecosystem types across the Australian continental rangelands to investigate the responses of sympatric prey populations to contemporary poison-baiting programs intended to control top-predators (dingoes) for livestock protection. Results Prey populations were almost always in similar or greater abundances in baited areas. Short-term prey responses to baiting were seldom apparent. Longer-term prey population trends fluctuated independently of baiting for every prey species at all sites, and divergence or convergence of prey population trends occurred rarely. Top-predator population trends fluctuated independently of baiting in all cases, and never did diverge or converge. Mesopredator population trends likewise fluctuated independently of baiting in almost all cases, but did diverge or converge in a few instances. Conclusions These results demonstrate that Australian populations of prey fauna at lower trophic levels are typically unaffected by top-predator control because top-predator populations are not substantially affected by contemporary control practices, thus averting a trophic cascade. We conclude that alteration of current top-predator management practices is probably unnecessary for enhancing fauna recovery in the Australian rangelands. More generally, our results suggest that theoretical and observational studies advancing the idea that lethal control of top-predators induces trophic cascades may not be as universal as previously supposed.

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.

Efficient simulation of unsaturated flow in heterogeneous soils using an exponential integrator

- Provided a practical variable-stepsize implementation of the exponential Euler method (EEM). - Introduced a new second-order variant of the scheme that enables the local error to be estimated at the cost of a single additional function evaluation. - New EEM implementation outperformed sophisticated implementations of the backward differentiation formulae (BDF) of order 2 and was competitive with BDF of order 5 for moderate to high tolerances.

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.

Assessment of functional forms of crop yield loss models of invasive plant species applied in decision support tools and bioeconomic modelling

AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.

Hybrid Simulation of Queuing-System Dynamics

This paper presents a simple hybrid computer technique to study the transient behaviour of queueing systems. This method is superior to stand-alone analog or digital solution because the hardware requirement is excessive for analog technique whereas computation time is appreciable in the latter case. By using a hybrid computer one can share the analog hardware thus requiring fewer integrators. The digital processor can store the values, play them back at required time instants and change the coefficients of differential equations. By speeding up the integration on the analog computer it is feasible to solve a large number of these equations very fast. Hybrid simulation is even superior to the analytic technique because in the latter case it is difficult to solve time-varying differential equations.