Trace elements (TEs) are universally present in environmental media, including soil, but agriculture uses some materials that have increased TE concentrations. Some TEs (e.g., Cu, Se, and Zn) are added to animal feeds to ensure animal health. Similarly, TEs are present in micronutrient fertilizers. In the case of phosphate fertilizers, some TEs (e.g., Cd) may be inadvertently elevated because of the source rock used in the manufacturing. The key question for agriculture is "After decades of use, could these TE additions result in the deterioration of soil quality?" An early warning would allow the development of best management practices to slow or reverse this trend. This paper discusses a model that estimates future TE concentrations for the 2780 land area polygons composing essentially all of the agricultural land in Canada. The development of the model is discussed, as are various metrics to express the risk related to TE accumulation. The elements As, Cd, Cu, Pb, Se, and Zn are considered, with inputs from the atmosphere, fertilizers, manures, and municipal biosolids. In many cases, steady-state concentrations could be toxic, but steady state is far in the future. In 100 yr, the soil concentrations (Century soil concentrations) are estimated to be up to threefold higher than present background, an impact even if not a problematic impact. The geographic distribution reflects agricultural intensity. Contributions from micronutrient fertilizers are perhaps the most uncertain due to the limited data available on their use.

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Abstract.This paper reviews the progress made towards the restoration of Loch Leven, the largest lake in lowland Scotland, over the last 20years. In particular, the importance of direct regulation and of setting water quality objectives and targets. Various means of engaging with stakeholders and the general public are also considered. Success criteria and catchment management initiatives are described and briefly reviewed.

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Background: Modern, high-throughput biological experiments generate copious, heterogeneous, interconnected data sets. Research is dynamic, with frequently changing protocols, techniques, instruments, and file formats. Because of these factors, systems designed to manage and integrate modern biological data sets often end up as large, unwieldy databases that become difficult to maintain or evolve. The novel rule-based approach of the Ultra-Structure design methodology presents a potential solution to this problem. By representing both data and processes as formal rules within a database, an UltraStructure system constitutes a flexible framework that enables users to explicitly store domain knowledge in both a machine-and human-readable form. End users themselves can change the system's capabilities without programmer intervention, simply by altering database contents; no computer code or schemas need be modified. This provides flexibility in adapting to change, and allows integration of disparate, heterogenous data sets within a small core set of database tables, facilitating joint analysis and visualization without becoming unwieldy. Here, we examine the application of Ultra-Structure to our ongoing research program for the integration of large proteomic and genomic data sets (proteogenomic mapping).