Modelling biological processes under anaerobic conditions through integrating titrimetric and off-gas measurements - applied to EBPR systems

An innovative method for modelling biological processes under anaerobic conditions is presented and discussed. The method is based on titrimetric and off-gas measurements. Titrimetric data is recorded as the addition rate of hydroxyl ions or protons that is required to maintain pH in a bioreactor at a constant level. An off-gas analysis arrangement measures, among other things, the transfer rate of carbon dioxide. The integration of these signals results in a continuous signal which is solely related to the biological reactions. When coupled with a mathematical model of the biological reactions, the signal allows a detailed characterisation of these reactions, which would otherwise be difficult to achieve. Two applications of the method to the enhanced biological phosphorus removal processes are presented and discussed to demonstrate the principle and effectiveness of the method.

Phytotoxicity of surface waters of the Thames and Brisbane River Estuaries: A combined chemical analysis and bioassay approach for the comparison of two systems

The Thames Estuary, UK, and the Brisbane River, Australia, are comparable in size and catchment area. Both are representative of the large and growing number of the world's estuaries associated with major cities. Principle differences between the two systems relate to climate and human population pressures. In order to assess the potential phytotoxic impact of herbicide residues in the estuaries, surface waters were analysed with a PAM fluorometry-based bioassay that employs the photosynthetic efficiency (photosystem II quantum yield) of laboratory cultured microalgae, as an endpoint measure of phytotoxicity. In addition, surface waters were chemically analysed for a limited number of herbicides. Diuron atrazine and simazine were detected in both systems at comparable concentrations. In contrast, bioassay results revealed that whilst detected herbicides accounted for the observed phytotoxicity of Brisbane River extracts with great accuracy, they consistently explained only around 50% of the phytotoxicity induced by Thames Estuary extracts. Unaccounted for phytotoxicity in Thames surface waters is indicative of unidentified phytotoxins. The greatest phytotoxic response was measured at Charing Cross, Thames Estuary, and corresponded to a diuron equivalent concentration of 180 ng L-1. The study employs relative potencies (REP) of PSII impacting herbicides and demonstrates that chemical analysis alone is prone to omission of valuable information. Results of the study provide support for the incorporation of bioassays into routine monitoring programs where bioassay data may be used to predict and verify chemical contamination data, alert to unidentified compounds and provide the user with information regarding cumulative toxicity of complex mixtures. (c) 2005 Elsevier B.V. All rights reserved.

A complex systems approach to the value of ecological resources

A theory of value sits at the core of every school of economic thought and directs the allocation of resources to competing uses. Ecological resources complicate the modem neoclassical approach to determining value due to their complex nature, considerable non-market values and the difficulty in assigning property rights. Application of the market model through economic valuation only provides analytical solutions based on virtual markets, and neither the demand nor supply-side techniques of valuation can adequately consider the complex set of biophysical and ecological relations that lead to the provision of ecosystem goods and services. This paper sets out a conceptual framework for a complex systems approach to the value of ecological resources. This approach is based on there being both an intrinsic quality of ecological resources and a subjective evaluation by the consumer. Both elements are necessary for economic value. This conceptual framework points the way towards a theory of value that incorporates both elements, so has implications for principles by which ecological resources can be allocated. (c) 2005 Elsevier B.V. All rights reserved.

Trait physiology and crop modelling to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. We explore whether a crop growth and development modelling framework can link phenotype complexity to underlying genetic systems in a way that strengthens molecular breeding strategies. We use gene-to-phenotype simulation studies on sorghum to consider the value to marker-assisted selection of intrinsically stable QTLs that might be generated by physiological dissection of complex traits. The consequences on grain yield of genetic variation in four key adaptive traits – phenology, osmotic adjustment, transpiration efficiency, and staygreen – were simulated for a diverse set of environments by placing the known extent of genetic variation in the context of the physiological determinants framework of a crop growth and development model. It was assumed that the three to five genes associated with each trait, had two alleles per locus acting in an additive manner. The effects on average simulated yield, generated by differing combinations of positive alleles for the traits incorporated, varied with environment type. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages with gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies. We simulated a marker-assisted selection (MAS) breeding strategy based on the analyses of gene effects. When marker scores were allocated based on the contribution of gene effects to yield in a single environment, there was a wide divergence in rate of yield gain over all environments with breeding cycle depending on the environment chosen for the QTL analysis. It was suggested that knowledge resulting from trait physiology and modelling would overcome this dependency by identifying stable QTLs. The improved predictive power would increase the utility of the QTLs in MAS. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate QTLs.

Incorporating level set methods in Geographical Information Systems (GIS) for land-surface process modelling

Land-surface processes include a broad class of models that operate at a landscape scale. Current modelling approaches tend to be specialised towards one type of process, yet it is the interaction of processes that is increasing seen as important to obtain a more integrated approach to land management. This paper presents a technique and a tool that may be applied generically to landscape processes. The technique tracks moving interfaces across landscapes for processes such as water flow, biochemical diffusion, and plant dispersal. Its theoretical development applies a Lagrangian approach to motion over a Eulerian grid space by tracking quantities across a landscape as an evolving front. An algorithm for this technique, called level set method, is implemented in a geographical information system (GIS). It fits with a field data model in GIS and is implemented as operators in map algebra. The paper describes an implementation of the level set methods in a map algebra programming language, called MapScript, and gives example program scripts for applications in ecology and hydrology.