Predicting population dynamics of weed biological control agents: science or gazing into crystal balls?

Various factors can influence the population dynamics of phytophages post introduction, of which climate is fundamental. Here we present an approach, using a mechanistic modelling package (CLIMEX), that at least enables one to make predictions of likely dynamics based on climate alone. As biological control programs will have minimal funding for basic work (particularly on population dynamics), we show how predictions can be made using a species geographical distribution, relative abundance across its range, seasonal phenology and laboratory rearing data. Many of these data sets are more likely to be available than long-term population data, and some can be incorporated into the exploratory phase of a biocontrol program. Although models are likely to be more robust the more information is available, useful models can be developed using information on species distribution alone. The fitted model estimates a species average response to climate, and can be used to predict likely geographical distribution if introduced, where the agent is likely to be more abundant (i.e. good locations) and more importantly for interpretation of release success, the likely variation in abundance over time due to intra- and inter-year climate variability. The latter will be useful in predicting both the seasonal and long-term impacts of the potential biocontrol agent on the target weed. We believe this tool may not only aid in the agent selection process, but also in the design of release strategies, and for interpretation of post-introduction dynamics and impacts. More importantly we are making testable predictions. If biological control is to become more of a science making and testing such hypothesis will be a key component.

The DVD animal model of schizophrenia: Effects of low maternal vitamin D on brain dopamine

Background: We have previously shown that the offspring of vitamin D3 depleted rats have enlarged ventricles and altered neurotrophin profiles (reduced NGF and GDNF). These findings enhance the biological plausibility that low prenatal vitamin D may be a risk factor for schizophrenia. Our recent behavioural studies have found that adult rats with developmental vitamin D deficiency (DVD) have a subtle increase in baseline locomotor activity and a heightened response to dopamine (DA) antagonists. The aim of this study was to investigate brain DA neurochemistry in the DVD model. Methods: We examined cerebrums and striatal tissue from neonates and a variety of brain tissues from the remaining littermates at adulthood. DA, DOPAC, HVA, serotonin and 5HIAA were analysed by HPLC. Single point comparisons for DA1, DA2 and NMDA receptors were also assessed in these tissues. Results: Significant increases in DA and HVA were found in brains from DVD deplete neonates (P=0.01). However, DA and its metabolites were not increased in either the neonate or adult striatum, however there was a trend towards increased DA and its metabolites in the accumbens (P=0.1). Receptor densities were unaffected by prenatal vitamin D levels. Conclusions: Although the effect of maternal diet appears to increase DA production and turnover in neonatal brain, this does not persist into adulthood. Thus other factors must underlie the increased locomotor activity noted in these animals. Future experiments will concentrate on monitoring accumbens and striatal DA release and turnover using microdialysis in pharmacologically challenged behavioural paradigms. References: Eyles D, Brown J; Mackay-Sim A, McGrath J, Feron F. (2003) Vitamin D3 and brain development. Neuroscience 118 (3) 641–653. Burne T, McGrath J, Eyles D, Mackay-Sim A. Behavioural characterization of vitamin D receptor knockout mice. (2005) Behavioural Brain Res: 157 299–308.

What does the animal model teach us about the effects of physical activity on growing bone?

Experiments to design physical activity programs that optimize their osteogenic potential are difficult to accomplish in humans. The aim of this article is to review the contributions that animal studies have made to knowledge of the loading conditions that are osteogenic to the skeleton during growth, as well as to consider to what extent animal studies fail to provide valid models of physical activity and skeletal maturation. Controlled loading studies demonstrate that static loads are ineffective, and that bone formation is threshold driven and dependent on strain rate, amplitude, and duration of loading. Only a few loading cycles per session are required, and distributed bouts are more osteogenic than sessions of long duration. Finally, animal models fail to inform us of the most appropriate ways to account for the variations in biological maturation that occur in our studies of children and adolescents, requiring the use of techniques for studying human growth and development.

Imitating the neighbours: vocal dialect matching in a mimic-model system

Vocal mimicry provides a unique system for investigating song learning and cultural evolution in birds. Male lyrebirds produce complex vocal displays that include extensive and accurate mimicry of many other bird species. We recorded and analysed the songs of the Albert's lyrebird (Menura alberti) and its most commonly imitated model species, the satin bowerbird (Ptilonorhynchus violaceus), at six sites in southeast Queensland, Australia. We show that each population of lyrebirds faithfully reproduces the song of the local population of bowerbirds. Within a population, lyrebirds show less variation in song structure than the available variation in the songs of the models. These results provide the first quantitative evidence for dialect matching in the songs of two species that have no direct ecological relationship.

Robustness of mathematical models for biological systems

The robustness of mathematical models for biological systems is studied by sensitivity analysis and stochastic simulations. Using a neural network model with three genes as the test problem, we study robustness properties of synthesis and degradation processes. For single parameter robustness, sensitivity analysis techniques are applied for studying parameter variations and stochastic simulations are used for investigating the impact of external noise. Results of sensitivity analysis are consistent with those obtained by stochastic simulations. Stochastic models with external noise can be used for studying the robustness not only to external noise but also to parameter variations. For external noise we also use stochastic models to study the robustness of the function of each gene and that of the system.