Soil biodiversity: functions, threats and tools for policy makers

Human societies rely on the vast diversity of benefits provided by nature, such as food, fibres, construction materials, clean water, clean air and climate regulation. All the elements required for these ecosystem services depend on soil, and soil biodiversity is the driving force behind their regulation. With 2010 being the international year of biodiversity and with the growing attention in Europe on the importance of soils to remain healthy and capable of supporting human activities sustainably, now is the perfect time to raise awareness on preserving soil biodiversity. The objective of this report is to review the state of knowledge of soil biodiversity, its functions, its contribution to ecosystem services and its relevance for the sustainability of human society. In line with the definition of biodiversity given in the 1992 Rio de Janeiro Convention, soil biodiversity can be defined as the variation in soil life, from genes to communities, and the variation in soil habitats, from micro-aggregates to entire landscapes. Bio Intelligence Service, IRD, and NIOO, Report for European Commission (DG Environment

Changes in poverty and the stability of income distribution in Argentina: evidence from the 1990s via decompositions

From 1992 to 2001, despite its rapid economic growth during the early 1990s, Argentina experienced a period characterized by increasing income inequality and poverty. An axiomatically modified Datt-Ravallion decomposition, that separates changes in poverty rates into mean and inequality components, will illustrate how each of them has contributed to those changes. Contrary to the claims of much of the recent cross-country literature, income inequality does not appear stable in Argentina. Previous results are extended in two key ways. First, the empirical density function is used to calculate the inequality component, without assuming a particular functional form for the Lorenz curve. Second, both components are recomputed without the vaguely defined Datt-Ravallion residual, which improves interpretability.decomposition of changes in poverty, poverty measures, inequality and growth.

Integration of Cost andWork Breakdown Structures in the Management of Construction Projects

Scope management allows project managers to react when a project underperforms regarding schedule, budget, and/or quality at the execution stage. Scope management can also minimize project changes and budget omissions, as well as improve the accuracy of project cost estimates and risk responses. For scope management to be effective, though, it needs to rely on a robust work breakdown structure (WBS). A robust WBS hierarchically and faithfully reflects all project tasks and work packages so that projects are easier to manage. If done properly, the WBS also allows meeting the project objectives while delivering the project on time, on budget, and with the required quality. This paper analyzes whether the integration of a cost breakdown structure (CBS) can lead to the generation of more robust WBSs in construction projects. Over the last years, some international organizations have standardized and harmonized different cost classification systems (e.g., ISO 12006-2, ISO 81346-12, OmniClass, CoClass, UniClass). These cost databases have also been introduced into building information modeling (BIM) frameworks. We hypothesize that in BIM environments, if these CBSs are used to generate the project WBS, several advantages are gained such as sharper project definition. This enhanced project definition reduces project contradictions at both planning and execution stages, anticipates potential schedule and budget deviations, improves resource allocation, and overall it allows a better response to potential project risks. The hypothesis that the use of CBSs can generate more robust WBSs is tested by the response analysis of a questionnaire survey distributed among construction practitioners and project managers. By means of structural equation modeling (SEM), the correlation (agreement) and perception differences between two 250-respondent subsamples (technical project staff vs. project management staff) are also discussed. Results of this research support the use of CBSs by construction professionals as a basis to generate WBSs for enhanced project management (PM)

On the Effect of Semantically Enriched Context Models on Software Modularization

Many of the existing approaches for program comprehension rely on the linguistic information found in source code, such as identifier names and comments. Semantic clustering is one such technique for modularization of the system that relies on the informal semantics of the program, encoded in the vocabulary used in the source code. Treating the source code as a collection of tokens loses the semantic information embedded within the identifiers. We try to overcome this problem by introducing context models for source code identifiers to obtain a semantic kernel, which can be used for both deriving the topics that run through the system as well as their clustering. In the first model, we abstract an identifier to its type representation and build on this notion of context to construct contextual vector representation of the source code. The second notion of context is defined based on the flow of data between identifiers to represent a module as a dependency graph where the nodes correspond to identifiers and the edges represent the data dependencies between pairs of identifiers. We have applied our approach to 10 medium-sized open source Java projects, and show that by introducing contexts for identifiers, the quality of the modularization of the software systems is improved. Both of the context models give results that are superior to the plain vector representation of documents. In some cases, the authoritativeness of decompositions is improved by 67%. Furthermore, a more detailed evaluation of our approach on JEdit, an open source editor, demonstrates that inferred topics through performing topic analysis on the contextual representations are more meaningful compared to the plain representation of the documents. The proposed approach in introducing a context model for source code identifiers paves the way for building tools that support developers in program comprehension tasks such as application and domain concept location, software modularization and topic analysis

How complex climate networks complement eigen techniques for the statistical analysis of climatological data

Eigen techniques such as empirical orthogonal function (EOF) or coupled pattern (CP) / maximum covariance analysis have been frequently used for detecting patterns in multivariate climatological data sets. Recently, statistical methods originating from the theory of complex networks have been employed for the very same purpose of spatio-temporal analysis. This climate network (CN) analysis is usually based on the same set of similarity matrices as is used in classical EOF or CP analysis, e.g., the correlation matrix of a single climatological field or the cross-correlation matrix between two distinct climatological fields. In this study, formal relationships as well as conceptual differences between both eigen and network approaches are derived and illustrated using exemplary global precipitation, evaporation and surface air temperature data sets. These results allow to pinpoint that CN analysis can complement classical eigen techniques and provides additional information on the higher-order structure of statistical interrelationships in climatological data. Hence, CNs are a valuable supplement to the statistical toolbox of the climatologist, particularly for making sense out of very large data sets such as those generated by satellite observations and climate model intercomparison exercises.Comment: 18 pages, 11 figure

Distributions in motion: economic growth, inequality, and poverty dynamics

The joint determination of aggregate economic growth and distributional change has been studied empirically from at least three different perspectives. A macroeconomic approach that relies on cross-country data on poverty, inequality, and growth rates has generated some interesting stylized facts about the correlations between these variables, but has not shed much light on the underlying determinants."Meso-"and microeconomic approaches have fared somewhat better. The microeconomic approach, in particular, builds on the observation that growth, changes in poverty, and changes in inequality are simply different aggregations of information on the incidence of economic growth along the income distribution. This paper reviews the evolution of attempts to understand the nature of growth incidence curves, from the statistical decompositions associated with generalizations of the Oaxaca-Blinder method, to more recent efforts to generate"economically consistent"counterfactuals, drawing on structural, reduced-form, and computable general equilibrium models.Rural Poverty Reduction,Achieving Shared Growth,Inequality,Services&Transfers to Poor,Economic Theory&Research