Soil carbon in the Jena Experiment from intensive sampling campaigns (only block 2 Main Experiment up to 1 m depth, year 2007)

This data set contains soil carbon measurements (Organic carbon, inorganic carbon, and total carbon; all measured in dried soil samples) from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Stratified soil sampling to a depth of 1 m was repeated in April 2007 (as had been done before sowing in April 2002). Three independent samples per plot were taken of all plots in block 2 using a motor-driven soil column cylinder (Cobra, Eijkelkamp, 8.3 cm in diameter). Soil samples were dried at 40°C and segmented to a depth resolution of 5 cm giving 20 depth subsamples per core. All samples were analyzed independently. All soil samples were passed through a sieve with a mesh size of 2 mm. Because of much higher proportions of roots in the soil, the samples in 2007 were further sieved to 1 mm according to common root removal methods. No additional mineral particles were removed by this procedure. Total carbon concentration was analyzed on ball-milled subsamples (time 4 min, frequency 30 s**-1) by an elemental analyzer at 1150°C (Elementaranalysator vario Max CN; Elementar Analysensysteme GmbH, Hanau, Germany). We measured inorganic carbon concentration by elemental analysis at 1150°C after removal of organic carbon for 16 h at 450°C in a muffle furnace. Organic carbon concentration was calculated as the difference between both measurements of total and inorganic carbon.

Soil carbon in the Jena Experiment (all blocks Main Experiment up to 30cm depth, year 2004)

This data set contains soil carbon measurements (Organic carbon, inorganic carbon, and total carbon; all measured in dried soil samples) from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Stratified soil sampling was performed in April 2004 to a depth of 30 cm. Three samples per plot were taken using a split tube sampler with an inner diameter of 4.8 cm (Eijkelkamp Agrisearch Equipment, Giesbeek, the Netherlands). Sampling locations were less than 30 cm apart from sampling locations in 2002. Soil samples were segmented into 5 cm depth segments in the field (resulting in six depth layers) and made into composite samples per depth. Subsequently, samples were dried at 40°C. All soil samples were passed through a sieve with a mesh size of 2 mm. Because of much higher proportions of roots in the soil, samples in years after 2002 were further sieved to 1 mm according to common root removal methods. No additional mineral particles were removed by this procedure. Total carbon concentration was analyzed on ball-milled subsamples (time 4 min, frequency 30 s**-1) by an elemental analyzer at 1150°C (Elementaranalysator vario Max CN; Elementar Analysensysteme GmbH, Hanau, Germany). We measured inorganic carbon concentration by elemental analysis at 1150°C after removal of organic carbon for 16 h at 450°C in a muffle furnace. Organic carbon concentration was calculated as the difference between both measurements of total and inorganic carbon.

Total nitrogen from solid phase in the Jena Experiment (Main Experiment up to 30cm depth, year 2006)

This data set contains measurements of total nitrogen from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Stratified soil sampling was performed in April 2006 to a depth of 30 cm. Three independent samples per plot were taken using a split tube sampler with an inner diameter of 4.8 cm (Eijkelkamp Agrisearch Equipment, Giesbeek, the Netherlands). Soil samples were segmented to a depth resolution of 5 cm in the field, giving six depth subsamples per core, and made into composite samples per depth. Sampling locations were less than 30 cm apart from sampling locations in other years. Samples were dried at 40°C. All soil samples were passed through a sieve with a mesh size of 2 mm. Because of much higher proportions of roots in the soil, the samples were further sieved to 1 mm according to common root removal methods. No additional mineral particles were removed by this procedure. Total nitrogen concentration was analyzed on ball-milled subsamples (time 4 min, frequency 30 s-1) by an elemental analyzer at 1150°C (Elementaranalysator vario Max CN; Elementar Analysensysteme GmbH, Hanau, Germany).

Chapter 4 A Review of the Availability of and Studies on Spatial Economic Data in Laos

Spatial data are being increasingly used in a wide range of disciplines, a fact that is clearly reflected in the recent trend to add spatial dimensions to the conventional social sciences. Economics is by no means an exception. On one hand, spatial data are indispensable to many branches of economics such as economic geography, new economic geography, or spatial economics. On the other hand, macroeconomic data are becoming available at more and more micro levels, so that academics and analysts take it for granted that they are available not only for an entire country, but also for more detailed levels (e.g. state, province, and even city). The term ‘spatial economics data’ as used in this report refers to any economic data that has spatial information attached. This spatial information can be the coordinates of a location at best or a less precise place name as is used to describe administrative units. Obviously, the latter cannot be used without a map of corresponding administrative units. Maps are therefore indispensible to the analysis of spatial economic data without absolute coordinates. The aim of this report is to review the availability of spatial economic data that pertains specifically to Laos and academic studies conducted on such data up to the present. In regards to the availability of spatial economic data, efforts have been made to identify not only data that has been made available as geographic information systems (GIS) data, but also those with sufficient place labels attached. The rest of the report is organized as follows. Section 2 reviews the maps available for Laos, both in hard copy and editable electronic formats. Section 3 summarizes the spatial economic data available for Laos at the present time, and Section 4 reviews and categorizes the many economic studies utilizing these spatial data. Section 5 give examples of some of the spatial industrial data collected for this research. Section 6 provides a summary of the findings and gives some indication of the direction of the final report due for completion in fiscal 2010.

Industrial agglomeration in Costa Rica : a descriptive analysis

This paper investigates the current situation of industrial agglomeration in Costa Rica, utilizing firm-level panel data for the period 2008-2012. We calculated Location Quotient and Theil Index based on employment by industry and found that 14 cantons have the industrial agglomerations for 9 industries. The analysis is in line with the nature of specific industries, the development of areas of concentration around free zones, and the evolving participation of Costa Rica in GVCs.

A method to incorporate the effect of taxonomic uncertainty on multivariate analyses of ecological data

Researchers in ecology commonly use multivariate analyses (e.g. redundancy analysis, canonical correspondence analysis, Mantel correlation, multivariate analysis of variance) to interpret patterns in biological data and relate these patterns to environmental predictors. There has been, however, little recognition of the errors associated with biological data and the influence that these may have on predictions derived from ecological hypotheses. We present a permutational method that assesses the effects of taxonomic uncertainty on the multivariate analyses typically used in the analysis of ecological data. The procedure is based on iterative randomizations that randomly re-assign non identified species in each site to any of the other species found in the remaining sites. After each re-assignment of species identities, the multivariate method at stake is run and a parameter of interest is calculated. Consequently, one can estimate a range of plausible values for the parameter of interest under different scenarios of re-assigned species identities. We demonstrate the use of our approach in the calculation of two parameters with an example involving tropical tree species from western Amazonia: 1) the Mantel correlation between compositional similarity and environmental distances between pairs of sites, and; 2) the variance explained by environmental predictors in redundancy analysis (RDA). We also investigated the effects of increasing taxonomic uncertainty (i.e. number of unidentified species), and the taxonomic resolution at which morphospecies are determined (genus-resolution, family-resolution, or fully undetermined species) on the uncertainty range of these parameters. To achieve this, we performed simulations on a tree dataset from southern Mexico by randomly selecting a portion of the species contained in the dataset and classifying them as unidentified at each level of decreasing taxonomic resolution. An analysis of covariance showed that both taxonomic uncertainty and resolution significantly influence the uncertainty range of the resulting parameters. Increasing taxonomic uncertainty expands our uncertainty of the parameters estimated both in the Mantel test and RDA. The effects of increasing taxonomic resolution, however, are not as evident. The method presented in this study improves the traditional approaches to study compositional change in ecological communities by accounting for some of the uncertainty inherent to biological data. We hope that this approach can be routinely used to estimate any parameter of interest obtained from compositional data tables when faced with taxonomic uncertainty.

Automated attribute inference in complex service workflows based on sharing analysis

The properties of data and activities in business processes can be used to greatly facilítate several relevant tasks performed at design- and run-time, such as fragmentation, compliance checking, or top-down design. Business processes are often described using workflows. We present an approach for mechanically inferring business domain-specific attributes of workflow components (including data Ítems, activities, and elements of sub-workflows), taking as starting point known attributes of workflow inputs and the structure of the workflow. We achieve this by modeling these components as concepts and applying sharing analysis to a Horn clause-based representation of the workflow. The analysis is applicable to workflows featuring complex control and data dependencies, embedded control constructs, such as loops and branches, and embedded component services.

Evidence that the Plant Host Synthesizes the Heme Moiety of Leghemoglobin in Root Nodules1

Although it is well established that the plant host encodes and synthesizes the apoprotein for leghemoglobin in root nodules, the source of the heme moiety has been uncertain. We recently found that the transcript for coproporphyrinogen III oxidase, one of the later enzymes of heme synthesis, is highly elevated in soybean (Glycine max L.) nodules compared with roots. In this study we measured enzyme activity and carried out western-blot analysis and in situ hybridization of mRNA to investigate the levels during nodulation of the plant-specific coproporphyrinogen oxidase and four other enzymes of the pathway in both soybean and pea (Pisum sativum L.). We compared them with the activity found in leaves and uninfected roots. Our results demonstrate that all of these enzymes are elevated in the infected cells of nodules. Because these are the same cells that express apoleghemoglobin, the data strongly support a role for the plant in the synthesis of the heme moiety of leghemoglobin.

Analysis of genetic instability during mammary tumor progression using a novel selection-based assay for in vivo mutations in a bacteriophage lambda transgene target.

Genetic instability is thought to be responsible for the numerous genotypic changes that occur during neoplastic transformation and metastatic progression. To explore the role of genetic instability at the level of point mutations during mammary tumor development and malignant progression, we combined transgenic mouse models of mutagenesis detection and oncogenesis. Bitransgenic mice were generated that carried both a bacteriophage lambda transgene to assay mutagenesis and a polyomavirus middle T oncogene, mammary gland-targeted expression of which led to metastatic mammary adenocarcinomas. We developed a novel assay for the detection of mutations in the lambda transgene that selects for phage containing forward mutations only in the lambda cII gene, using an hfl- bacterial host. In addition to the relative ease of direct selection, the sensitivity of this assay for both spontaneous and chemically induced mutations was comparable to the widely used mutational target gene, lambda lacI, making the cII assay an attractive alternative for mutant phage recovery for any lambda-based mouse mutagenesis assay system. The frequencies of lambda cII- mutants were not significantly different in normal mammary epithelium, primary mammary adenocarcinomas, and pulmonary metastases. The cII mutational spectra in these tissues consisted mostly of G/C-->A/T transitions, a large fraction of which occurred at CpG dinucleotides. These data suggest that, in this middle T oncogene model of mammary tumor progression, a significant increase in mutagenesis is not required for tumor development or for metastatic progression.

Coreferentiality: A New Method for the Hypothesis-Based Analysis of Phenotypes Characterized by Multivariate Data

Many multifactorial biologic effects, particularly in the context of complex human diseases, are still poorly understood. At the same time, the systematic acquisition of multivariate data has become increasingly easy. The use of such data to analyze and model complex phenotypes, however, remains a challenge. Here, a new analytic approach is described, termed coreferentiality, together with an appropriate statistical test. Coreferentiality is the indirect relation of two variables of functional interest in respect to whether they parallel each other in their respective relatedness to multivariate reference data, which can be informative for a complex effect or phenotype. It is shown that the power of coreferentiality testing is comparable to multiple regression analysis, sufficient even when reference data are informative only to a relatively small extent of 2.5%, and clearly exceeding the power of simple bivariate correlation testing. Thus, coreferentiality testing uses the increased power of multivariate analysis, however, in order to address a more straightforward interpretable bivariate relatedness. Systematic application of this approach could substantially improve the analysis and modeling of complex phenotypes, particularly in the context of human study where addressing functional hypotheses by direct experimentation is often difficult.

Involvement and detachment in David Cameron and Ed Miliband’s political discourse. An analysis of deictic shields on the pronoun ‘I’ in UK 2015 General Election news interviews

The goal of my study is to investigate the relationship between selected deictic shields on the pronoun ‘I’ and the involvement/detachment dichotomy in a sample of television news interviews. I focus on the use of personal pronouns in political discourse. Drawing upon Caffi’s (2007) classification of mitigating devices into bushes, hedges and shields, I focus on deictic shields on the pronoun ‘I’: I examine the way a selection of ‘I’-related deictic shields is employed in a collection of news interviews broadcast during the electoral campaign prior to the UK 2015 General Election. My purpose is to uncover the frequencies of each of the linguistic items selected and the pragmatic functions of those linguistic items in the involvement/detachment dichotomy. The research is structured as follows. Chapter 1 provides an account of previous studies on the three main areas of research: speech event analysis, institutional interaction and the news interview, and the UK 2015 General Election television programmes. Chapter 2 is centred on the involvement/detachment dichotomy: I provide an overview of nonlinguistic and linguistic features of involvement and detachment at all levels of sentence structure. Chapter 3 contains a detailed account of the data collection and data analysis process. Chapter 4 provides an accurate description of results in three steps: quantitative analysis, qualitative analysis and discussion of the pragmatic functions of the selected linguistic features of involvement and detachment. Chapter 5 includes a brief summary of the investigation, reviews the main findings, and indicates limitations of the study and possible inputs for further research. The results of the analysis confirm that, while some of the linguistic items examined point toward involvement, others have a detaching effect. I therefore conclude that deictic shields on the pronoun ‘I’ permit the realisation of the involvement/detachment dichotomy in the speech genre of the news interview.

Using linked data to evaluate medical and financial outcomes of motor vehicle crashes in Connecticut.

Federal Highway Administration, Washington, D.C.

Using linked data to evaluate severity and outcome of injury by type of object struck (first object struck only) for motor vehicle crashes in Connecticut.

Federal Highway Administration, Washington, D.C.

Control charts as a tool in data quality improvement.

Mode of access: Internet.

Guide to reporting highway statistics: procedures for the compilation, analysis and reporting of: state motor-fuel, motor-vehicle, driver-license and motor-carrier data; highway finance data of state and local governments.

Mode of access: Internet.