Models for the field-based toxicity of copper and zinc salts to wheat in 11 Australian soils and comparison to laboratory-based models

Laboratory-based relationships that model the phytotoxicity of metals using soil properties have been developed. This paper presents the first field-based phytotoxicity relationships. Wheat(Triticum aestivum L) was grown at 11 Australian field sites at which soil was spiked with copper (Cu) and zinc (Zn) salts. Toxicity was measured as inhibition of plant growth at 8 weeks and grain yield at harvest. The added Cu and Zn EC10 values for both endpoints ranged from approximately 3 to 4760 mg/kg. There were no relationships between field-based 8-week biomass and grain yield toxicity values for either metal. Cu toxicity was best modelled using pH and organic carbon content while Zn toxicity was best modelled using pH and the cation exchange capacity. The best relationships estimated toxicity within a factor of two of measured values. Laboratory-based phytotoxicity relationships could not accurately predict field-based phytotoxicity responses.

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

The sensitivity of updated NIR PLS models for fruit sorting to initial parameter settings

Partial least squares regression models on NIR spectra are often optimised (for wavelength range, mathematical pretreatment and outlier elimination) in terms of calibration terms of validation performance with reference to totally independent populations.

Optimization models for expanding a railway’s theoretical capacity

Changing the topology of a railway network can greatly affect its capacity. Railway networks however can be altered in a multitude of different ways. As each way has significant immediate and long term financial ramifications, it is a difficult task to decide how and where to expand the network. In response some railway capacity expansion models (RCEM) have been developed to help capacity planning activities, and to remove physical bottlenecks in the current railway system. The exact purpose of these models is to decide given a fixed budget, where track duplications and track sub divisions should be made, in order to increase theoretical capacity most. These models are high level and strategic, and this is why increases to the theoretical capacity is concentrated upon. The optimization models have been applied to a case study to demonstrate their application and their worth. The case study evidently shows how automated approaches of this nature could be a formidable alternative to current manual planning techniques and simulation. If the exact effect of track duplications and sub-divisions can be sufficiently approximated, this approach will be very applicable.

Predicting dispersal and recruitment of Miconia calvescens (Melastomataceae) in Australian tropical rainforests

Miconia calvescens (Melastomataceae) is a serious invader in the tropical Pacific, including the Hawaiian and Tahitian Islands, and currently poses a major threat to native biodiversity in the Wet Tropics of Australia. The species is fleshy-fruited, small-seeded and shade tolerant, and thus has the potential to be dispersed widely and recruit in relatively intact rainforest habitats, displacing native species. Understanding and predicting the rate of spread is critical for the design and implementation of effective management actions. We used an individual-based model incorporating a dispersal function derived from dispersal curves for similar berry-fruited native species, and life-history parameters of fecundity and mortality to predict the spatial structure of a Miconia population after a 30 year time period. We compared the modelled population spatial structure to that of an actual infestation in the rainforests of north Queensland. Our goal was to assess how well the model predicts actual dispersion and to identify potential barriers and conduits to seed movement and seedling establishment. The model overpredicts overall population size and the spatial extent of the actual infestation, predicting individuals to occur at a maximum 1,750 m from the source compared with the maximum distance of any detected individual in the actual infestation of 1,191 m. We identify several characteristic features of managed invasive populations that make comparisons between modelled outcomes and actual infestations difficult. Our results suggest that the model’s ability to predict both spatial structure and spread of the population will be improved by incorporating a spatially explicit element, with dispersal and recruitment probabilities that reflect the relative suitability of different parts of the landscape for these processes.

New efforts at biological control of Mikania micrantha H.B.K. (Asteraceae) in Papua New Guinea and Fiji.

New efforts at biological control of Miconia calvescens (Melastomataceae) is a serious invader in the tropical Pacific, including the Hawaiian and Tahitian Islands, and currently poses a major threat to native biodiversity in the Wet Tropics of Australia. The species is fleshy-fruited, small-seeded and shade tolerant, and thus has the potential to be dispersed widely and recruit in relatively intact rainforest habitats, displacing native species. Understanding and predicting the rate of spread is critical for the design and implementation of effective management actions. We used an individual-based model incorporating a dispersal function derived from dispersal curves for similar berry-fruited native species, and life-history parameters of fecundity and mortality to predict the spatial structure of a Miconia population after a 30 year time period. We compared the modelled population spatial structure to that of an actual infestation in the rainforests of north Queensland. Our goal was to assess how well the model predicts actual dispersion and to identify potential barriers and conduits to seed movement and seedling establishment. The model overpredicts overall population size and the spatial extent of the actual infestation, predicting individuals to occur at a maximum 1,750 m from the source compared with the maximum distance of any detected individual in the actual infestation of 1,191 m. We identify several characteristic features of managed invasive populations that make comparisons between modelled outcomes and actual infestations difficult. Our results suggest that the model’s ability to predict both spatial structure and spread of the population will be improved by incorporating a spatially explicit element, with dispersal and recruitment probabilities that reflect the relative suitability of different parts of the landscape for these processes. Mikania micrantha H.B.K. (Asteraceae) in Papua New Guinea and Fiji.

Parameter estimation and sensitivity analysis of fat deposition models in beef steers using acslXtreme.

The Davis Growth Model (a dynamic steer growth model encompassing 4 fat deposition models) is currently being used by the phenotypic prediction program of the Cooperative Research Centre (CRC) for Beef Genetic Technologies to predict P8 fat (mm) in beef cattle to assist beef producers meet market specifications. The concepts of cellular hyperplasia and hypertrophy are integral components of the Davis Growth Model. The net synthesis of total body fat (kg) is calculated from the net energy available after accounting tor energy needs for maintenance and protein synthesis. Total body fat (kg) is then partitioned into 4 fat depots (intermuscular, intramuscular, subcutaneous, and visceral). This paper reports on the parameter estimation and sensitivity analysis of the DNA (deoxyribonucleic acid) logistic growth equations and the fat deposition first-order differential equations in the Davis Growth Model using acslXtreme (Hunstville, AL, USA, Xcellon). The DNA and fat deposition parameter coefficients were found to be important determinants of model function; the DNA parameter coefficients with days on feed >100 days and the fat deposition parameter coefficients for all days on feed. The generalized NL2SOL optimization algorithm had the fastest processing time and the minimum number of objective function evaluations when estimating the 4 fat deposition parameter coefficients with 2 observed values (initial and final fat). The subcutaneous fat parameter coefficient did indicate a metabolic difference for frame sizes. The results look promising and the prototype Davis Growth Model has the potential to assist the beef industry meet market specifications.

A mechanism for the west-north-west movement of monsoon depressions

The monsoon depressions intensify over the Bay of Bengal, move in a west-north-west (WNW) direction and dissipate over the Indian continent. No convincing physical explanation for their observed movement has so far been arrived at, but here, I suggest why the maximum precipitation occurs in the western sector of the depression and propose a feedback mechanism for the WNW movement of the depressions. We assume that a heat source is created over the Bay of Bengal due to organization of cumulus convection by the initial instability. In a linear sense, heating at this latitude (20° N), produces an atmospheric response mainly in the form of a stationary Rossby–gravity wave to the west of the heat source. The low-level vorticity (hence the frictional convergence) and the vertical velocity associated with the steady-state response is such that the maximum moisture convergence (and precipitation) is expected to occur in the WNW sector at a later time. Thus, the heat source moves to the WNW sector at a later time and the feedback continues resulting in the WNW movement of the depressions.

Management of plant invasions mediated by frugivore interactions

1. Some of the most damaging invasive plants are dispersed by frugivores and this is an area of emerging importance in weed management. It highlights the need for practical information on how frugivores affect weed population dynamics and spread, how frugivore populations are affected by weeds and what management recommendations are available. 2. Fruit traits influence frugivore choice. Fruit size, the presence of an inedible peel, defensive chemistry, crop size and phenology may all be useful traits for consideration in screening and eradication programmes. By considering the effect of these traits on the probability, quality and quantity of seed dispersal, it may be possible to rank invasive species by their desirability to frugivores. Fruit traits can also be manipulated with biocontrol agents. 3. Functional groups of frugivores can be assembled according to broad species groupings, and further refined according to size, gape size, pre- and post-ingestion processing techniques and movement patterns, to predict dispersal and establishment patterns for plant introductions. 4. Landscape fragmentation can increase frugivore dispersal of invasives, as many invasive plants and dispersers readily use disturbed matrix environments and fragment edges. Dispersal to particular landscape features, such as perches and edges, can be manipulated to function as seed sinks if control measures are concentrated in these areas. 5. Where invasive plants comprise part of the diet of native frugivores, there may be a conservation conflict between control of the invasive and maintaining populations of the native frugivore, especially where other threats such as habitat destruction have reduced populations of native fruit species. 6. Synthesis and applications. Development of functional groups of frugivore-dispersed invasive plants and dispersers will enable us to develop predictions for novel dispersal interactions at both population and community scales. Increasingly sophisticated mechanistic seed dispersal models combined with spatially explicit simulations show much promise for providing weed managers with the information they need to develop strategies for surveying, eradicating and managing plant invasions. Possible conservation conflicts mean that understanding the nature of the invasive plant-frugivore interaction is essential for determining appropriate management.

Reconciling transport models across scales: The role of volume exclusion

Diffusive transport is a universal phenomenon, throughout both biological and physical sciences, and models of diffusion are routinely used to interrogate diffusion-driven processes. However, most models neglect to take into account the role of volume exclusion, which can significantly alter diffusive transport, particularly within biological systems where the diffusing particles might occupy a significant fraction of the available space. In this work we use a random walk approach to provide a means to reconcile models that incorporate crowding effects on different spatial scales. Our work demonstrates that coarse-grained models incorporating simplified descriptions of excluded volume can be used in many circumstances, but that care must be taken in pushing the coarse-graining process too far.

Information-movement Coupling as a Hallmark of Sport Expertise

Expert interceptive actions are grounded in both perceptual judgment and movement control, yet research has largely focused on the role of anticipation. More recently, the emergence of ecological psychology has provided movement scientists with opportunities to develop further understanding of the processes underpinning the development of expert information-movement couplings. In this chapter we discuss key research that has enhanced our understanding of perceptual learning with specific focus on the concepts of education of attention and calibration. We conclude by discussing the practical implications of this research in the study of expertise highlighting the need for future research using sporting tasks.

The effect of data sources and quality on the predictive capacity of CLIMEX models: an assessment of Teleonemia scrupulosa and Octotoma scabripennis for the biocontrol of Lantana camara in Australia

Understanding the effects of different types and quality of data on bioclimatic modeling predictions is vital to ascertaining the value of existing models, and to improving future models. Bioclimatic models were constructed using the CLIMEX program, using different data types – seasonal dynamics, geographic (overseas) distribution, and a combination of the two – for two biological control agents for the major weed Lantana camara L. in Australia. The models for one agent, Teleonemia scrupulosa Stål (Hemiptera:Tingidae) were based on a higher quality and quantity of data than the models for the other agent, Octotoma scabripennis Guérin-Méneville (Coleoptera: Chrysomelidae). Predictions of the geographic distribution for Australia showed that T. scrupulosa models exhibited greater accuracy with a progressive improvement from seasonal dynamics data, to the model based on overseas distribution, and finally the model combining the two data types. In contrast, O. scabripennis models were of low accuracy, and showed no clear trends across the various model types. These case studies demonstrate the importance of high quality data for developing models, and of supplementing distributional data with species seasonal dynamics data wherever possible. Seasonal dynamics data allows the modeller to focus on the species response to climatic trends, while distributional data enables easier fitting of stress parameters by restricting the species envelope to the described distribution. It is apparent that CLIMEX models based on low quality seasonal dynamics data, together with a small quantity of distributional data, are of minimal value in predicting the spatial extent of species distribution.

Reassessing spatial and temporal dynamics of kangaroo populations

Long-running datasets from aerial surveys of kangaroos (Macropus giganteus, Macropus [uliginosus, Macropus robustus and Macropus rufus) across Queensland, New South Wales and South Australia have been analysed, seeking better predictors of rates of increase which would allow aerial surveys to be undertaken less frequently than annually. Early models of changes in kangaroo numbers in response to rainfall had shown great promise, but much variability. We used normalised difference vegetation index (NDVI) instead, reasoning that changes in pasture condition would provide a better predictor than rainfall. However, except at a fine scale, NDVI proved no better; although two linked periods of rainfall proved useful predictors of rates of increase, this was only in some areas for some species. The good correlations reported in earlier studies were a consequence of data dominated by large droughtinduced adult mortality, whereas over a longer time frame and where changes between years are less dramatic, juvenile survival has the strongest influence on dynamics. Further, harvesting, density dependence and competition with domestic stock are additional and important influences and it is now clear that kangaroo movement has a greater influence on population dynamics than had been assumed. Accordingly, previous conclusions about kangaroo populations as simple systems driven by rainfall need to be reassessed. Examination of this large dataset has permitted descriptions of shifts in distribution of three species across eastern Australia, changes in dispersion in response to rainfall, and an evaluation of using harvest statistics as an index of density and harvest rate. These results have been combined into a risk assessment and decision theory framework to identify optimal monitoring strategies.