Uncertainties in annual riverine phosphorus load estimation: Impact of load estimation methodology, sampling frequency, baseflow index and catchment population density

Models developed to identify the rates and origins of nutrient export from land to stream require an accurate assessment of the nutrient load present in the water body in order to calibrate model parameters and structure. These data are rarely available at a representative scale and in an appropriate chemical form except in research catchments. Observational errors associated with nutrient load estimates based on these data lead to a high degree of uncertainty in modelling and nutrient budgeting studies. Here, daily paired instantaneous P and flow data for 17 UK research catchments covering a total of 39 water years (WY) have been used to explore the nature and extent of the observational error associated with nutrient flux estimates based on partial fractions and infrequent sampling. The daily records were artificially decimated to create 7 stratified sampling records, 7 weekly records, and 30 monthly records from each WY and catchment. These were used to evaluate the impact of sampling frequency on load estimate uncertainty. The analysis underlines the high uncertainty of load estimates based on monthly data and individual P fractions rather than total P. Catchments with a high baseflow index and/or low population density were found to return a lower RMSE on load estimates when sampled infrequently than those with a tow baseflow index and high population density. Catchment size was not shown to be important, though a limitation of this study is that daily records may fail to capture the full range of P export behaviour in smaller catchments with flashy hydrographs, leading to an underestimate of uncertainty in Load estimates for such catchments. Further analysis of sub-daily records is needed to investigate this fully. Here, recommendations are given on load estimation methodologies for different catchment types sampled at different frequencies, and the ways in which this analysis can be used to identify observational error and uncertainty for model calibration and nutrient budgeting studies. (c) 2006 Elsevier B.V. All rights reserved.

Predicted soil organic carbon stocks and changes in Kenya between 1990 and 2030

Under the United Nations Framework Convention on Climate Change (UNFCCC), Non-Annex 1 countries such as Kenya are obliged to report green house gas (GHG) emissions from all sources where possible, including those from soils as a result of changes in land use or land management. At present, the convention encourages countries to estimate emissions using the most advanced methods possible, given the country circumstances and resources. Estimates of soil organic carbon (SOC) stocks and changes were made for Kenya using the Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. The tool conducts analysis using three methods: (1) the Century general ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The required datasets included: land use history, monthly mean precipitation, monthly mean minimum and maximum temperatures for all the agro-climatic zones of Kenya and historical vegetation cover. Soil C stocks of 1.4-2.0 Pg (0-20 cm), compared well with a Soil and Terrain (SOTER) based approach that estimated similar to .8-2.0 Pg (0-30 cm). In 1990 48% of the country had SOC stocks of < 18 t C ha(-1) and 20% of the country had SOC stocks of 18-30 t C ha(-1), whereas in 2000 56% of the country had SOC stocks of < 18 t C ha(-1) and 31% of the country had SOC stocks of 18-30 t C ha(-1). Conversion of natural vegetation to annual crops led to the greatest soil C losses. Simulations suggest that soil C losses remain substantial throughout the modelling period of 1990-2030. All three methods involved in the GEFSOC System estimated that there would be a net loss of soil C between 2000 and 2030 in Kenya. The decline was more marked with RothC than with Century or the IPCC method. In non-hydric soils the SOC change rates were more pronounced in high sandy soils compared to high clay soils in most land use systems. (C) 2007 Elsevier B.V. All rights reserved.

National and sub-national assessments of soil organic carbon stocks and changes: The GEFSOC modelling system

Soil organic carbon (SOC) plays a vital role in ecosystem function, determining soil fertility, water holding capacity and susceptibility to land degradation. In addition, SOC is related to atmospheric CO, levels with soils having the potential for C release or sequestration, depending on land use, land management and climate. The United Nations Convention on Climate Change and its Kyoto Protocol, and other United Nations Conventions to Combat Desertification and on Biodiversity all recognize the importance of SOC and point to the need for quantification of SOC stocks and changes. An understanding of SOC stocks and changes at the national and regional scale is necessary to further our understanding of the global C cycle, to assess the responses of terrestrial ecosystems to climate change and to aid policy makers in making land use/management decisions. Several studies have considered SOC stocks at the plot scale, but these are site specific and of limited value in making inferences about larger areas. Some studies have used empirical methods to estimate SOC stocks and changes at the regional scale, but such studies are limited in their ability to project future changes, and most have been carried out using temperate data sets. The computational method outlined by the Intergovernmental Panel on Climate Change (IPCC) has been used to estimate SOC stock changes at the regional scale in several studies, including a recent study considering five contrasting eco regions. This 'one step' approach fails to account for the dynamic manner in which SOC changes are likely to occur following changes in land use and land management. A dynamic modelling approach allows estimates to be made in a manner that accounts for the underlying processes leading to SOC change. Ecosystem models, designed for site scale applications can be linked to spatial databases, giving spatially explicit results that allow geographic areas of change in SOC stocks to be identified. Some studies have used variations on this approach to estimate SOC stock changes at the sub-national and national scale for areas of the USA and Europe and at the watershed scale for areas of Mexico and Cuba. However, a need remained for a national and regional scale, spatially explicit system that is generically applicable and can be applied to as wide a range of soil types, climates and land uses as possible. The Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System was developed in response to this need. The GEFSOC system allows estimates of SOC stocks and changes to be made for diverse conditions, providing essential information for countries wishing to take part in an emerging C market, and bringing us closer to an understanding of the future role of soils in the global C cycle. (C) 2007 Elsevier B.V. All rights reserved.

Greening the United Nations' Human Development Index?

The Human Development Index (HDI) introduced by the United Nations Development Programme (UNDP) in 1990 has helped facilitate widespread debate amongst development researchers, practitioners and policy makers. The HDI is an aggregate index, calculated on an annual basis by the UNDP and published in its Human Development Reports, comprising measures of three components deemed by them to be central to development: W income (the gross domestic product per capita), (ii) education (adult literacy rate) and (iii) health (life expectancy at birth). The results of calculating the HDI are typically presented as country/regional league tables, and provide a quick means for policy makers and others to judge performance. Perhaps partly because of the relative simplicity of the index, the HDI has managed to achieve a level of acceptance and use amongst politicians and policy makers that has yet to emerge with any indicator of sustainability. Indeed, despite its existence for 11 years, including nine years after the Rio Earth Summit, the HDI has not even been modified to take on board wider issues of sustainability. This paper will critically examine the potential for 'greening' the HDI so as to include environmental and resource-consumption dimensions. Copyright (C) 2003 John Wiley & Sons, Ltd and ERP Environment.

For better or for worse, till the human development index do us part?

This paper describes the results of research intended to explore the volatility inherent in the United Nations Development Programme's (UNDP) Human Development Index (HDI). The HDI is intended to be a simple and transparent device for comparing progress in human development, and is an aggregate of life expectancy, education and GDP per capita. Values of the HDI for each country are presented in the Human Development Reports (HDRs), the first being published in 1990. However, while the methodology is consistent for all countries in each year there are notable differences between years that make temporal comparisons of progress difficult. The paper presents the results of recalculating the HDI for a simplified sample of 114 countries using various methodologies employed by the UNDP. The results are a set of deviations of recalculated HDI ranks compared to the original ranks given in the HDRs. The volatility that can result from such recalculation is shown to be substantial (+/-10-15 ranks), yet reports in the popular press are frequently sensitive to movements of only a few ranks. Such movement can easily be accounted for by changes in the HDI methodology rather than genuine progress in human development. While the HDRs often carry warnings about the inadvisability of such year-on-year comparisons, it is argued that the existence of such a high-profile index and the overt presentation within league tables do encourage such comparison. Assuming that the HDI will be retained as a focal point within the HDRs, then it is suggested that greater focus be upon more meaningful and robust categories of human development (e.g. low, medium and high) rather than league tables where shifts of a few places, perhaps as a result of nothing more than a methodological or data artefact, may be highlighted in the press and by policy makers. (C) 2003 Elsevier Science B.V. All rights reserved.

Using aircraft measurements to determine the refractive index of Saharan dust during the DODO Experiments

Much uncertainty in the value of the imaginary part of the refractive index of mineral dust contributes to uncertainty in the radiative effect of mineral dust in the atmosphere. A synthesis of optical, chemical and physical in-situ aircraft measurements from the DODO experiments during February and August 2006 are used to calculate the refractive index mineral dust encountered over West Africa. Radiative transfer modeling and measurements of broadband shortwave irradiance at a range of altitudes are used to test and validate these calculations for a specific dust event on 23 August 2006 over Mauritania. Two techniques are used to determine the refractive index: firstly a method combining measurements of scattering, absorption, size distributions and Mie code simulations, and secondly a method using composition measured on filter samples to apportion the content of internally mixed quartz, calcite and iron oxide-clay aggregates, where the iron oxide is represented by either hematite or goethite and clay by either illite or kaolinite. The imaginary part of the refractive index at 550 nm (ni550) is found to range between 0.0001 i to 0.0046 i, and where filter samples are available, agreement between methods is found depending on mineral combination assumed. The refractive indices are also found to agree well with AERONET data where comparisons are possible. ni550 is found to vary with dust source, which is investigated with the NAME model for each case. The relationship between both size distribution and ni550 on the accumulation mode single scattering albedo at 550 nm (ω0550) are examined and size distribution is found to have no correlation to ω0550, while ni550 shows a strong linear relationship with ω0550. Radiative transfer modeling was performed with different models (Mie-derived refractive indices, but also filter sampling composition assuming both internal and external mixing). Our calculations indicate that Mie-derived values of ni550 and the externally mixed dust where the iron oxide-clay aggregate corresponds to the goethite-kaolinite combination result in the best agreement with irradiance measurements. The radiative effect of the dust is found to be very sensitive to the mineral combination (and hence refractive index) assumed, and to whether the dust is assumed to be internally or externally mixed.

Calculating the exclusion probability and paternity index for X-chromosomal loci in the presence of substructure

There has been recent interest in the use of X-chromosomal loci for forensic and relatedness testing casework, with many authors developing new X-linked short tandem repeat (STR) loci suitable for forensic use. Here we present formulae for two key quantities in paternity testing, the average probability of exclusion and the paternity index, which are suitable for Xchromosomal loci in the presence of population substructure.

Revisiting youden’s index as a useful measure of the misclassification error in meta-analysis of diagnostic studies

The paper considers meta-analysis of diagnostic studies that use a continuous score for classification of study participants into healthy or diseased groups. Classification is often done on the basis of a threshold or cut-off value, which might vary between studies. Consequently, conventional meta-analysis methodology focusing solely on separate analysis of sensitivity and specificity might be confounded by a potentially unknown variation of the cut-off value. To cope with this phenomena it is suggested to use, instead, an overall estimate of the misclassification error previously suggested and used as Youden’s index and; furthermore, it is argued that this index is less prone to between-study variation of cut-off values. A simple Mantel–Haenszel estimator as a summary measure of the overall misclassification error is suggested, which adjusts for a potential study effect. The measure of the misclassification error based on Youden’s index is advantageous in that it easily allows an extension to a likelihood approach, which is then able to cope with unobserved heterogeneity via a nonparametric mixture model. All methods are illustrated at hand of an example on a diagnostic meta-analysis on duplex doppler ultrasound, with angiography as the standard for stroke prevention.

A benchmark method for global optimization problems in structure determination from powder diffraction data

Quasi-Newton-Raphson minimization and conjugate gradient minimization have been used to solve the crystal structures of famotidine form B and capsaicin from X-ray powder diffraction data and characterize the chi(2) agreement surfaces. One million quasi-Newton-Raphson minimizations found the famotidine global minimum with a frequency of ca 1 in 5000 and the capsaicin global minimum with a frequency of ca 1 in 10 000. These results, which are corroborated by conjugate gradient minimization, demonstrate the existence of numerous pathways from some of the highest points on these chi(2) agreement surfaces to the respective global minima, which are passable using only downhill moves. This important observation has significant ramifications for the development of improved structure determination algorithms.

Measuring productivity growth when technological change is biased - a new index and an application to UK agriculture

Productivity growth is conventionally measured by indices representing discreet approximations of the Divisia TFP index under the assumption that technological change is Hicks-neutral. When this assumption is violated, these indices are no longer meaningful because they conflate the effects of factor accumulation and technological change. We propose a way of adjusting the conventional TFP index that solves this problem. The method adopts a latent variable approach to the measurement of technical change biases that provides a simple means of correcting product and factor shares in the standard Tornqvist-Theil TFP index. An application to UK agriculture over the period 1953-2000 demonstrates that technical progress is strongly biased. The implications of that bias for productivity measurement are shown to be very large, with the conventional TFP index severely underestimating productivity growth. The result is explained primarily by the fact that technological change has favoured the rapidly accumulating factors against labour, the factor leaving the sector. (C) 2004 Elsevier B.V. All rights reserved.

A cross-taxonomic index for quantifying the health of farmland biodiversity

P>1. The development of sustainable, multi-functional agricultural systems involves reconciling the needs of agricultural production with the objectives for environmental protection, including biodiversity conservation. However, the definition of sustainability remains ambiguous and it has proven difficult to identify suitable indicators for monitoring progress towards, and the successful achievement of, sustainability. 2. In this study, we show that a trait-based approach can be used to assess the detrimental impacts of agricultural change to a broad range of taxonomic groupings and derive a standardised index of farmland biodiversity health, built around an objective of achieving stable or increasing populations in all species associated with agricultural landscapes. 3. To demonstrate its application, we assess the health of UK farmland biodiversity relative to this goal. Our results suggest that the populations of two-thirds of 333 plant and animal species assessed are unsustainable under current UK agricultural practices. 4. We then explore the potential benefits of an agri-environment scheme, Entry Level Stewardship (ELS), to farmland biodiversity in the UK under differing levels of risk mitigation delivery. We show that ELS has the potential to make a significant contribution to progress towards sustainability targets but that this potential is severely restricted by current patterns of scheme deployment. 5.Synthesis and applications: We have developed a cross-taxonomic sustainability index which can be used to assess both the current health of farmland biodiversity and the impacts of future agricultural changes relative to quantitative biodiversity targets. Although biodiversity conservation is just one of a number of factors that must be considered when defining sustainability, we believe our cross-taxonomic index has the potential to be a valuable tool for guiding the development of sustainable agricultural systems.

The agri-environmental Footprint Index

The Agri-Environmental Footprint project is developing a common methodology for assessing the environmental impact of European agri-environment schemes. The Agri-Environmental Footprint Index (AFI) has been constructed as a customisable approach. It is a farm-level index that aggregates the measurement of agri-environmental indicators. Farm-level impact scores can be aggregated at a regional level to track temporal change and/or to provide comparisons of the success (or otherwise) of an agri-environment scheme.

Conceptual development of a harmonised method for tracking change and evaluating policy in the agri-environment: The Agri-environmental Footprint Index

An aggregated farm-level index, the Agri-environmental Footprint Index (AFI), based on multiple criteria methods and representing a harmonised approach to evaluation of EU agri-environmental schemes is described. The index uses a common framework for the design and evaluation of policy that can be customised to locally relevant agri-environmental issues and circumstances. Evaluation can be strictly policy-focused, or broader and more holistic in that context-relevant assessment criteria that are not necessarily considered in the evaluated policy can nevertheless be incorporated. The Index structure is flexible, and can respond to diverse local needs. The process of Index construction is interactive, engaging farmers and other relevant stakeholders in a transparent decision-making process that can ensure acceptance of the outcome, help to forge an improved understanding of local agri-environmental priorities and potentially increase awareness of the critical role of farmers in environmental management. The structure of the AFI facilitates post-evaluation analysis of relative performance in different dimensions of the agri-environment, permitting identification of current strengths and weaknesses, and enabling future improvement in policy design. Quantification of the environmental impact of agriculture beyond the stated aims of policy using an 'unweighted' form of the AFI has potential as the basis of an ongoing system of environmental audit within a specified agricultural context. (C) 2009 Elsevier Ltd. All rights reserved.