CD21 B cell populations are altered following subcutaneous scrapie inoculation in sheep

In order to gain a better understanding of the pathogenesis of scrapie in sheep an experimental model was developed to characterise immune system cells in the minutes following inoculation with scrapie-brain homogenate. Four 1-year-old susceptible (ARQ/ARQ) sheep were inoculated via the subcutaneous route at four different peripheral lymph node (LNs) drainage sites, at specific time points, prior to euthanasia of the sheep. The LNs were removed post-mortem at 30, 90, 180 and 300 min after inoculation. Flow cytometric triple-labelling was carried out on the LN cells and indicated that inoculation of scrapie-brain homogenate adjacent to a lymph node may delay or even inhibit the number of host CD21⁺ B cells expressed within the first 5 h. Immunohistochemistry was used to attempt detection of the abnormal form of prion protein (PrP^sc) in draining LNs adjacent to inoculation sites, with negative results at those time points.     

Measuring and enhancing the value of agricultural water in irrigated river basins

This paper provides an overview of the issues in and approaches to measuring and enhancing the value of agricultural water in large irrigated river basins. It develops a framework and a set of indicators for valuing agricultural water by looking into various dimensions and underlying key factors that influence the value of water at micro, meso and macro levels. The indicators are applied to recent, primary- and secondary-level empirical data from the Indus basin Irrigation system of Pakistan. In addition, the paper compiles recent estimates of the value of agricultural water from 40 settings in 23 countries. Finally, the paper outlines measures for enhancing the value of agricultural water. The paper makes four main points: (1) The popular productivity indicators based on crop output do not capture the full range of benefits and costs associated with agricultural water use. (2) The value of agricultural water may not be as low as it is generally perceived or estimated when all major uses and direct and indirect benefits of water at various levels are properly accounted for. (3) The value of water varies across time and space, and the value to stakeholders at various scales (farmer, system manager, basin planner and national policy maker) could be quite different. For example, the estimate of agricultural water value in the upper Indus basin in Pakistan varies from US$0.04/m³ at the farm scale to US$0.22/m³ at the national scale. The farm-scale value is more relevant, e.g., for agricultural water charging policies, but for water-sector investments and allocation decisions, the national-scale value is important. The decision-making processes related to water sector investments, allocations, management, and charging/cost recovery schemes could be potentially misguided if key dimensions of water value that are related to water availability and use, benefits/costs, and temporal and spatial aspects are not properly accounted for in valuation. (4) Efforts should be directed not only at increasing the productivity of water in terms of mass of output per unit of water, but also the overall benefits or value of water at various levels for larger growth and poverty alleviation impacts, considering the sustainability of the systems.

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Simulating the effects of using different types of species distribution data in reserve selection

In a perfect world, systematic conservation planning would use complete information on the distribution of biodiversity. However, information on most species is grossly incomplete. Two main types of distribution data are frequently used in conservation planning: observed and predicted distribution data. A fundamental question that planners face is - which kind of data is better under what circumstances? We used simulation procedures to analyse the effects of using different types of distribution data on the performance of reserve selection algorithms in scenarios using different reserve selection problems, amounts of species distribution known, conservation targets and costs. To compare these scenarios we used occurrence data from 25 amphibian and 41 reptile species of the Iberian Peninsula and assumed the available data represented the whole truth. We then sampled fractions of these data and either used them as they were, or converted them to modelled predicted distributions. This enabled us to build three other types of species distribution data sets commonly used in conservation planning: “predicted”, “transformed predicted” and “mixed”. Our results suggest that reserve selection performance is sensitive to the type of species distribution data used and that the most cost-efficient decision depends most on the reserve selection problem and on how much we have of the species distribution data. Choosing the most appropriate type of distribution data should start by evaluating the scenario circumstances. While there is no one best approach for every scenario, we discovered that using a mixed approach usually provides an acceptable compromise between species representation and cost.