A modelling approach to estimate the effect of exotic pollinators on exotic weed population dynamics: bumblebees and broom in Australia

The role of mutualisms in contributing to species invasions is rarely considered, inhibiting effective risk analysis and management options. Potential ecological consequences of invasion of non-native pollinators include increased pollination and seed set of invasive plants, with subsequent impacts on population growth rates and rates of spread. We outline a quantitative approach for evaluating the impact of a proposed introduction of an invasive pollinator on existing weed population dynamics and demonstrate the use of this approach on a relatively data-rich case study: the impacts on Cytisus scoparius (Scotch broom) from proposed introduction of Bombus terrestris. Three models have been used to assess population growth (matrix model), spread speed (integrodifference equation), and equilibrium occupancy (lattice model) for C. scoparius. We use available demographic data for an Australian population to parameterize two of these models. Increased seed set due to more efficient pollination resulted in a higher population growth rate in the density-independent matrix model, whereas simulations of enhanced pollination scenarios had a negligible effect on equilibrium weed occupancy in the lattice model. This is attributed to strong microsite limitation of recruitment in invasive C. scoparius populations observed in Australia and incorporated in the lattice model. A lack of information regarding secondary ant dispersal of C. scoparius prevents us from parameterizing the integrodifference equation model for Australia, but studies of invasive populations in California suggest that spread speed will also increase with higher seed set. For microsite-limited C. scoparius populations, increased seed set has minimal effects on equilibrium site occupancy. However, for density-independent rapidly invading populations, increased seed set is likely to lead to higher growth rates and spread speeds. The impacts of introduced pollinators on native flora and fauna and the potential for promoting range expansion in pollinator-limited 'sleeper weeds' also remain substantial risks.

Science-policy in environmental and health risk assessment: if we cannot do without, can we do better?

How can empirical evidence of adverse effects from exposure to noxious agents, which is often incomplete and uncertain, be used most appropriately to protect human health? We examine several important questions on the best uses of empirical evidence in regulatory risk management decision-making raised by the US Environmental Protection Agency (EPA)'s science-policy concerning uncertainty and variability in human health risk assessment. In our view, the US EPA (and other agencies that have adopted similar views of risk management) can often improve decision-making by decreasing reliance on default values and assumptions, particularly when causation is uncertain. This can be achieved by more fully exploiting decision-theoretic methods and criteria that explicitly account for uncertain, possibly conflicting scientific beliefs and that can be fully studied by advocates and adversaries of a policy choice, in administrative decision-making involving risk assessment. The substitution of decision-theoretic frameworks for default assumption-driven policies also allows stakeholder attitudes toward risk to be incorporated into policy debates, so that the public and risk managers can more explicitly identify the roles of risk-aversion or other attitudes toward risk and uncertainty in policy recommendations. Decision theory provides a sound scientific way explicitly to account for new knowledge and its effects on eventual policy choices. Although these improvements can complicate regulatory analyses, simplifying default assumptions can create substantial costs to society and can prematurely cut off consideration of new scientific insights (e.g., possible beneficial health effects from exposure to sufficiently low 'hormetic' doses of some agents). In many cases, the administrative burden of applying decision-analytic methods is likely to be more than offset by improved effectiveness of regulations in achieving desired goals. Because many foreign jurisdictions adopt US EPA reasoning and methods of risk analysis, it may be especially valuable to incorporate decision-theoretic principles that transcend local differences among jurisdictions.

A Cochrane review (update 2004): Hylan G-F 20 vs placebo for knee OA

Aim of study: As part of a Cochrane review of viscosupplementation in knee OA, randomised controlled trials (RCT) were reviewed to evaluate evidence for the efficacy of viscosupplementation with Hylan G-F 20 compared to placebo. Methods: Electronic searches were conducted of MEDLINE, EMBASE, Premedline, Current Contents, and CENTRAL. Human, RCT involving Hylan G-F 20 compared to placebo, published prior to 1Q2004, were included. Trials were selected and data extracted by two independent reviewers. Methodological quality was assessed with the Jadad criteria by two reviewers. Data on the OARSI and OMERACT core set clinical outcome measures were extracted where possible. Weighted mean difference (WMD), based on post-test scores, and 95% confidence intervals (CI) were calculated for continuous outcome measures and relative risk (RR) for dichotomous outcome measures. Results: Seven RCT met the inclusion criteria. Median methodological quality was 4 (range 1–5). A further two studies were only reported in abstract form (Jadad score Z 1) and contained insufficient extractable data for inclusion in the analysis. Nine RCT, which compared Hylan G-F 20 to other interventions such as intra-articular corticosteroid, physiotherapy, NSAID, appropriate care, intra-articular gaseous oxygen and other hyaluronan, are not reported here. Twenty-three studies failed to meet inclusion criteria and were excluded. Hylan G-F 20 was more efficacious than placebo at 1–4 weeks post-injection for pain on weight-bearing WMD (random effects [RE]) 13 mm on a 0–100 mm VAS (P Z 0.002) based on 6 RCT. This difference was even greater at 5–13 weeks post-injection, 22 m (RE) (P Z 0.001) based on 5 RCT, and at 14–6 weeks postinjection, 21 m (RE) (P Z 0.006) based on 4 RCT. Hylan G-F 20 was more efficacious than placebo at 1–4 weeks post-injection for pain at night, WMD 7 mm on a 0–100 mm VAS (P Z 0.003) based on 5 RCT. This difference was even greater at 5–13 weeks post-injection, 11 mm (P Z 0.008) based on 4 RCT, and at 14–26 weeks post-injection, 17 mm (P ! 0.00001) based on 3 RCT. There was no significant difference (WMD 8 mm) between Hylan G-F 20 C oral placebo and arthrocentesis C oral placebo at 5–13 weeks post-injection for WOMAC Pain, but Hylan G-F 20 C oral placebo was more efficacious than arthrocentesis C oral placebo for WOMAC Function, WMD 9 mm on a 0–100 mm VAS (P Z 0.01) (Dickson, 2001). Hylan G-F 20 was more effective than placebo at 1–4 weeks postinjection for the variable designed treatment efficacy, WMD 22 mm on a 0–100 mm VAS (P ! 0.00001) based on improvement in 4 RCT. This difference was even greater at 5–13 weeks post injection, 35 mm (P ! 0.00001). Conclusions: Evidence from this updated Cochrane review supports the superior efficacy of Hylan G-F 20 compared to placebo on weight-bearing pain, night pain, function and treatment efficacy in the treatment of knee OA.

Evolving genetic regulatory networks using an artificial genome

Boolean models of genetic regulatory networks (GRNs) have been shown to exhibit many of the characteristic dynamics of real GRNs, with gene expression patterns settling to point attractors or limit cycles, or displaying chaotic behaviour, depending upon the connectivity of the network and the relative proportions of excitatory and inhibitory interactions. This range of behaviours is only apparent, however, when the nodes of the GRN are updated synchronously, a biologically implausible state of affairs. In this paper we demonstrate that evolution can produce GRNs with interesting dynamics under an asynchronous update scheme. We use an Artificial Genome to generate networks which exhibit limit cycle dynamics when updated synchronously, but collapse to a point attractor when updated asynchronously. Using a hill climbing algorithm the networks are then evolved using a fitness function which rewards patterns of gene expression which revisit as many previously seen states as possible. The final networks exhibit “fuzzy limit cycle” dynamics when updated asynchronously.

Returns to farm-level soil conservation on tropical steep slopes: The case of the Eritrean highlands

This study conducts an economic analysis of investment in simple soil conservation technologies in the highlands of Eritrea. The data used in the analysis were obtained from a farm survey and supplemented with data from secondary sources. Risk analysis techniques are used to take account of the uncertainties regarding the relationship between soil erosion and crop yield. The financial analysis reveals negative net present values (NPVs) and internal rates of return (IRRs) below 12 per cent for various slope categories. On the other hand, the economic analysis returns positive NPVs and IRRs of over 20 per cent. The results clearly indicate that in-vestment in soil conservation technology may not be a viable short-term proposition from the farmer's point of view and yet the net social benefits are positive. There is a strong case for government to provide incentives for soil conservation in view of the economic benefits.

Reliability factors in business software: volatility, requirements and end-users

Many business-oriented software applications are subject to frequent changes in requirements. This paper shows that, ceteris paribus, increases in the volatility of system requirements decrease the reliability of software. Further, systems that exhibit high volatility during the development phase are likely to have lower reliability during their operational phase. In addition to the typically higher volatility of requirements, end-users who specify the requirements of business-oriented systems are usually less technically oriented than people who specify the requirements of compilers, radar tracking systems or medical equipment. Hence, the characteristics of software reliability problems for business-oriented systems are likely to differ significantly from those of more technically oriented systems.

New product warranty: A literature review

Warranty is an important element of marketing new products as better warranty signals higher product quality and provides greater assurance to customers. Servicing warranty involves additional costs to the manufacturer and this cost depends on product reliability and warranty terms. Product reliability is influenced by the decisions made during the design and manufacturing of the product. As such warranty is very important in the context of new products. Product warranty has received the attention of researchers from many different disciplines and the literature on warranties is vast. This paper carries out a review of the literature that has appeared in the last ten years. It highlights issues of interest to manufacturers in the context of managing new products from an overall business perspective. (C) 2002 Elsevier Science B.V. All rights reserved.

Events in Indonesia: exploring the limits to formal tourism trends forecasting methods in complex crisis situations

The desire to know the future is as old as humanity. For the tourism industry the demand for accurate foretelling of the future course of events is a task that consumes considerable energy and is of great significance to investors. This paper examines the issue of forecasting by comparing forecasts of inbound tourism made prior to the political and economic crises that engulfed Indonesia from 1997 onwards with actual arrival figures. The paper finds that current methods of forecasting are not able to cope with unexpected crises and other disasters and that alternative methods need to be examined including scenarios, political risk and application of chaos theory. The paper outlines a framework for classifying shocks according to a scale of severity, probability, type of event, level of certainty and suggested forecasting tools for each scale of shock. (C) 2003 Elsevier Science Ltd. All rights reserved.

Predictive vaccinology: Optimisation of predictions using support vector machine classifiers

Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidden Markov models and artificial neural networks as prediction algorithms. We report a system based on support vector machines that outperforms previously published methods. Preliminary testing showed that it can predict peptides binding to HLA-A2 and -A3 super-type molecules with excellent accuracy, even for molecules where no binding data are currently available.

A simulation model of cereal-legume intercropping systems for semi-arid regions II. Model application

Smallholder farmers in Africa practice traditional cropping techniques such as intercropping. Intercropping is thought to offer higher productivity and resource milisation than sole cropping. In this study, risk associated with maize-bean intercropping was evaluated by quantifying long-term yield in both intercropping and sole cropping in a semi-arid region of South Africa (Bloemfontein, Free State) with reference to rainfall variability. The crop simulation model was run with different cultural practices (planting date and plant density) for 52 summer crop growing seasons (1950/1951-2001/2002). Eighty-one scenarios, consisted of three levels of initial soil water, planting date, maize population, and bean population, were simulated. From the simulation outputs, the total land equivalent ratio (LER) was greater than one. The intercrop (equivalent to sole maize) had greater energy value (EV) than sole beans, and the intercrop (equivalent to sole beans) had greater monetary value (MV) than sole maize. From these results, it can be concluded that maize-bean intercropping is advantageous for this semi-arid region. Soil water at planting was the most important factor of all scenario factors, followed by planting date. Irrigation application at planting, November/December planting and high plant density of maize for EV and beans for MV can be one of the most effective cultural practices in the study region. With regard to rainfall variability, seasonal (October-April) rainfall positively affected EV and MV, but not LER. There was more intercrop production in La Nina years than in El Nino years. Thus, better cultural practices may be selected to maximize maize-bean intercrop yields for specific seasons in the semi-arid region based on the global seasonal outlook. (c) 2004 Elsevier B.V. All rights reserved.

Modelling, nitrogen dynamics in sugarcane systems: Recent advances and applications

Substantial amounts of nitrogen (N) fertiliser are necessary for commercial sugarcane production because of the large biomass produced by sugarcane crops. Since this fertiliser is a substantial input cost and has implications if N is lost to the environment, there are pressing needs to optimise the supply of N to the crops' requirements. The complexity of the N cycle and the strong influence of climate, through its moderation of N transformation processes in the soil and its impact on N uptake by crops, make simulation-based approaches to this N management problem attractive. In this paper we describe the processes to be captured in modelling soil and plant N dynamics in sugarcane systems, and review the capability for modelling these processes. We then illustrate insights gained into improved management of N through simulation-based studies for the issues of crop residue management, irrigation management and greenhouse gas emissions. We conclude by identifying processes not currently represented in the models used for simulating N cycling in sugarcane production systems, and illustrate ways in which these can be partially overcome in the short term. (c) 2005 Elsevier B.V. All rights reserved.

Early warning signs in postgraduate research education: a different approach to ensuring timely completions

Recent government intervention in research higher degree policy across the globe has sharpened universities' focus on the quality of their students' research education experience and on timely completion rates. Studies have sought to highlight the factors that predict research students' timely completion of their studies. Many universities have sought to tighten their selection processes as a way of improving completion rates, even verging on adopting a risk analysis approach to selecting students. Instead this paper takes a preventative, interventionist approach to improving timely completions. It explores how experienced supervisors detect and deal with early warning signs that their research students are experiencing difficulty. It also investigates the wide range of reasons some students nominate for not discussing these difficulties directly with their supervisors. It proposes that supervisors may be able to improve timely completions if they are aware of these reasons and if they adopt a range of explicit pedagogical strategies to support students' learning.

Dynamics of gene expression in an artificial genome

Complex systems techniques provide a powerful tool to study the emergent properties of networks of interacting genes. In this study we extract models of genetic regulatory networks from an artificial genome, represented by a sequence of nucleotides, and analyse how variations in the connectivity and degree of inhibition of the extracted networks affects the resulting classes of behaviours. For low connectivity systems were found to be very stable. Only with higher connectivity was a significant occurrence of chaos found. Most interestingly, the peak in occurrence of chaos occurs perched on the edge of a phase transition in the occurrence of attractors.

Analysis of dynamic process models for structural insight and model reduction .1. Structural identification measures

An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd