Cheap dates and the delusion of gratification: are votes sold or traded in the EU Council of Ministers?

Each year, small Member States receive a disproportionate share of the European Union's (EU's) budget. A prominent explanation for this is that Council decision-making involves a healthy dose of vote selling, whereby large Member States offer small states generous fiscal transfers in exchange for influence over policy. But nobody has investigated whether net budget contributors actually get anything for their money. In this paper I identify the vote selling model's observable implications and find virtually no evidence consistent with Council cash-for-votes exchanges. I also show that a compromise model – the leading model of EU decision-making to date – modified to incorporate vote selling does not outperform a standard one that assumes votes are traded rather than sold. Taken together, the results suggest that Council decision-making operates with little or no vote selling, and that regardless of whatever they think they might be buying, net budget contributors get little or nothing in return for their money. These findings call for further investigation into how Member States approach the issue of fiscal transfers, and into the factors other than formal voting weight that affect the power of actors engaged in EU decision-making.

Good practice in reviewing and publishing studies on herbal medicine, with special emphasis on traditional Chinese medicine and Chinese materia medica

Ethnopharmacological relevance: Studies on traditional Chinese medicine (TCM), like those of other systems of traditional medicine (TM), are very variable in their quality, content and focus, resulting in issues around their acceptability to the global scientific community. In an attempt to address these issues, an European Union funded FP7 consortium, composed of both Chinese and European scientists and named “Good practice in traditional Chinese medicine” (GP-TCM), has devised a series of guidelines and technical notes to facilitate good practice in collecting, assessing and publishing TCM literature as well as highlighting the scope of information that should be in future publications on TMs. This paper summarises these guidelines, together with what has been learned through GP-TCM collaborations, focusing on some common problems and proposing solutions. The recommendations also provide a template for the evaluation of other types of traditional medicine such as Ayurveda, Kampo and Unani. Materials and methods: GP-TCM provided a means by which experts in different areas relating to TCM were able to collaborate in forming a literature review good practice panel which operated through e-mail exchanges, teleconferences and focused discussions at annual meetings. The panel involved coordinators and representatives of each GP-TCM work package (WP) with the latter managing the testing and refining of such guidelines within the context of their respective WPs and providing feedback. Results: A Good Practice Handbook for Scientific Publications on TCM was drafted during the three years of the consortium, showing the value of such networks. A “deliverable – central questions – labour division” model had been established to guide the literature evaluation studies of each WP. The model investigated various scoring systems and their ability to provide consistent and reliable semi-quantitative assessments of the literature, notably in respect of the botanical ingredients involved and the scientific quality of the work described. This resulted in the compilation of (i) a robust scoring system and (ii) a set of minimum standards for publishing in the herbal medicines field, based on an analysis of the main problems identified in published TCM literature.

Coupled atmosphere-biophysics-hydrology models for environmental modeling

The formulation and implementation of LEAF-2, the Land Ecosystem–Atmosphere Feedback model, which comprises the representation of land–surface processes in the Regional Atmospheric Modeling System (RAMS), is described. LEAF-2 is a prognostic model for the temperature and water content of soil, snow cover, vegetation, and canopy air, and includes turbulent and radiative exchanges between these components and with the atmosphere. Subdivision of a RAMS surface grid cell into multiple areas of distinct land-use types is allowed, with each subgrid area, or patch, containing its own LEAF-2 model, and each patch interacts with the overlying atmospheric column with a weight proportional to its fractional area in the grid cell. A description is also given of TOPMODEL, a land hydrology model that represents surface and subsurface downslope lateral transport of groundwater. Details of the incorporation of a modified form of TOPMODEL into LEAF-2 are presented. Sensitivity tests of the coupled system are presented that demonstrate the potential importance of the patch representation and of lateral water transport in idealized model simulations. Independent studies that have applied LEAF-2 and verified its performance against observational data are cited. Linkage of RAMS and TOPMODEL through LEAF-2 creates a modeling system that can be used to explore the coupled atmosphere–biophysical–hydrologic response to altered climate forcing at local watershed and regional basin scales.

‘Victory in a Nuclear War? A Comparison of NATO and WTO War Aims and Strategies’

Given the danger of the unbearable catastrophe of nuclear war, NATO in the mid-1950s abandoned any war aim of achieving victory in an all-out war with the Soviet Union or the Warsaw Treaty Organisation. Instead, it adopted the war aim of a cease-fire or war termination. By contrast, the WTO clung on to the war aim of victory - expressed even in terms of the survival of slightly more Soviet citizens than NATO citizens, after unprecedented losses of life in nuclear exchanges - until the mid-1980s when under Gorbachev the concept of victory in nuclear war was abandoned.

A comprehensive benchmarking system for evaluating global vegetation models.

We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover, composition and 5 height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, 10 and are compared to scores based on the temporal or spatial mean value of the observations and a “random” model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), and the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global 15 vegetation models (DGVMs). SDBM reproduces observed CO2 seasonal cycles, but its simulation of independent measurements of net primary production (NPP) is too high. The two DGVMs show little difference for most benchmarks (including the interannual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified 20 several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change 25 impacts and feedbacks.

Characterization of energy flux partitioning in urban environments: links with surface seasonal properties

A better understanding of links between the properties of the urban environment and the exchange to the atmosphere is central to a wide range of applications. The numerous measurements of surface energy balance data in urban areas enable intercomparison of observed fluxes from distinct environments. This study analyzes a large database in two new ways. First, instead of normalizing fluxes using net all-wave radiation only the incoming radiative fluxes are used, to remove the surface attributes from the denominator. Second, because data are now available year-round, indices are developed to characterize the fraction of the surface (built; vegetation) actively engaged in energy exchanges. These account for shading patterns within city streets and seasonal changes in vegetation phenology; their impact on the partitioning of the incoming radiation is analyzed. Data from 19 sites in North America, Europe, Africa, and Asia (including 6-yr-long observation campaigns) are used to derive generalized surface–flux relations. The midday-period outgoing radiative fraction decreases with an increasing total active surface index, the stored energy fraction increases with an active built index, and the latent heat fraction increases with an active vegetated index. Parameterizations of these energy exchange ratios as a function of the surface indices [i.e., the Flux Ratio–Active Index Surface Exchange (FRAISE) scheme] are developed. These are used to define four urban zones that characterize energy partitioning on the basis of their active surface indices. An independent evaluation of FRAISE, using three additional sites from the Basel Urban Boundary Layer Experiment (BUBBLE), yields accurate predictions of the midday flux partitioning at each location.

Modelling fire and the terrestrial carbon balance

Four CO2 concentration inversions and the Global Fire Emissions Database (GFED) versions 2.1 and 3 are used to provide benchmarks for climate-driven modeling of the global land-atmosphere CO2 flux and the contribution of wildfire to this flux. The Land surface Processes and exchanges (LPX) model is introduced. LPX is based on the Lund-Potsdam-Jena Spread and Intensity of FIRE (LPJ-SPITFIRE) model with amended fire probability calculations. LPX omits human ignition sources yet simulates many aspects of global fire adequately. It captures the major features of observed geographic pattern in burnt area and its seasonal timing and the unimodal relationship of burnt area to precipitation. It simulates features of geographic variation in the sign of the interannual correlations of burnt area with antecedent dryness and precipitation. It simulates well the interannual variability of the global total land-atmosphere CO2 flux. There are differences among the global burnt area time series from GFED2.1, GFED3 and LPX, but some features are common to all. GFED3 fire CO2 fluxes account for only about 1/3 of the variation in total CO2 flux during 1997–2005. This relationship appears to be dominated by the strong climatic dependence of deforestation fires. The relationship of LPX-modeled fire CO2 fluxes to total CO2 fluxes is weak. Observed and modeled total CO2 fluxes track the El Niño–Southern Oscillation (ENSO) closely; GFED3 burnt area and global fire CO2 flux track the ENSO much less so. The GFED3 fire CO2 flux-ENSO connection is most prominent for the El Niño of 1997–1998, which produced exceptional burning conditions in several regions, especially equatorial Asia. The sign of the observed relationship between ENSO and fire varies regionally, and LPX captures the broad features of this variation. These complexities underscore the need for process-based modeling to assess the consequences of global change for fire and its implications for the carbon cycle.

Global vegetation and terrestrial carbon cycle changes after the last ice age

•In current models, the ecophysiological effects of CO2 create both woody thickening and terrestrial carbon uptake, as observed now, and forest cover and terrestrial carbon storage increases that took place after the last glacial maximum (LGM). Here, we aimed to assess the realism of modelled vegetation and carbon storage changes between LGM and the pre-industrial Holocene (PIH). •We applied Land Processes and eXchanges (LPX), a dynamic global vegetation model (DGVM), with lowered CO2 and LGM climate anomalies from the Palaeoclimate Modelling Intercomparison Project (PMIP II), and compared the model results with palaeodata. •Modelled global gross primary production was reduced by 27–36% and carbon storage by 550–694 Pg C compared with PIH. Comparable reductions have been estimated from stable isotopes. The modelled areal reduction of forests is broadly consistent with pollen records. Despite reduced productivity and biomass, tropical forests accounted for a greater proportion of modelled land carbon storage at LGM (28–32%) than at PIH (25%). •The agreement between palaeodata and model results for LGM is consistent with the hypothesis that the ecophysiological effects of CO2 influence tree–grass competition and vegetation productivity, and suggests that these effects are also at work today.

A comprehensive benchmarking system for evaluating global vegetation models

We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover; composition and height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, and are compared to scores based on the temporal or spatial mean value of the observations and a "random" model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global vegetation models (DGVMs). In general, the SDBM performs better than either of the DGVMs. It reproduces independent measurements of net primary production (NPP) but underestimates the amplitude of the observed CO2 seasonal cycle. The two DGVMs show little difference for most benchmarks (including the inter-annual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change impacts and feedbacks.

Energy exchange in a dense urban environment Part II: impact of spatial heterogeneity of the surface

The centre of cities, characterised by spatial and temporal complexity, are challenging environments for micrometeorological research. This paper considers the impact of sensor location and heterogeneity of the urban surface on flux observations in the dense city centre of London, UK. Data gathered at two sites in close vicinity, but with different measurement heights, were analysed to investigate the influence of source area characteristics on long-term radiation and turbulent heat fluxes. Combining consideration of diffuse radiation and effects of specular reflections, the non-Lambertian urban surface is found to impact the measurements of surface albedo. Comparisons of observations from the two sites reveal that turbulent heat fluxes are similar under some flow conditions. However, they mostly observe processes at different scales due to their differing measurement heights, highlighting the critical impact of siting sensors in urban areas. A detailed source area analysis is presented to investigate the surface controls influencing the energy exchanges at the different scales

The role of dust in climate changes today, at the last glacial maximum and in the future.

Natural mineral aerosol (dust) is an active component of the climate system and plays multiple roles in mediating physical and biogeochemical exchanges between the atmosphere, land surface and ocean. Changes in the amount of dust in the atmosphere are caused both by changes in climate (precipitation, wind strength, regional moisture balance) and changes in the extent of dust sources caused by either anthropogenic or climatically induced changes in vegetation cover. Models of the global dust cycle take into account the physical controls on dust deflation from prescribed source areas (based largely on soil wetness and vegetation cover thresholds), dust transport within the atmospheric column, and dust deposition through sedimentation and scavenging by precipitation. These models successfully reproduce the first-order spatial and temporal patterns in atmospheric dust loading under modern conditions. Atmospheric dust loading was as much as an order-of-magnitude larger than today during the last glacial maximum (LGM). While the observed increase in emissions from northern Africa can be explained solely in terms of climate changes (colder, drier and windier glacial climates), increased emissions from other regions appear to have been largely a response to climatically induced changes in vegetation cover and hence in the extent of dust source areas. Model experiments suggest that the increased dust loading in tropical regions had an effect on radiative forcing comparable to that of low glacial CO2 levels. Changes in land-use are already increasing the dust loading of the atmosphere. However, simulations show that anthropogenically forced climate changes substantially reduce the extent and productivity of natural dust sources. Positive feedbacks initiated by a reduction of dust emissions from natural source areas on both radiative forcing and atmospheric CO2 could substantially mitigate the impacts of land-use changes, and need to be considered in climate change assessments.

Metaproteomics analysis reveals the adaptation process for the chicken gut microbiota

The animal gastrointestinal tract houses a large microbial community, the gut microbiota, that confers many benefits to its host, such as protection from pathogens and provision of essential metabolites. Metagenomic approaches have defined the chicken fecal microbiota in other studies, but here, we wished to assess the correlation between the metagenome and the bacterial proteome in order to better understand the healthy chicken gut microbiota. Here, we performed high-throughput sequencing of 16S rRNA gene amplicons and metaproteomics analysis of fecal samples to determine microbial gut composition and protein expression. 16 rRNA gene sequencing analysis identified Clostridiales, Bacteroidaceae, and Lactobacillaceae species as the most abundant species in the gut. For metaproteomics analysis, peptides were generated by using the Fasp method and subsequently fractionated by strong anion exchanges. Metaproteomics analysis identified 3,673 proteins. Among the most frequently identified proteins, 380 proteins belonged to Lactobacillus spp., 155 belonged to Clostridium spp., and 66 belonged to Streptococcus spp. The most frequently identified proteins were heat shock chaperones, including 349 GroEL proteins, from many bacterial species, whereas the most abundant enzymes were pyruvate kinases, as judged by the number of peptides identified per protein (spectral counting). Gene ontology and KEGG pathway analyses revealed the functions and locations of the identified proteins. The findings of both metaproteomics and 16S rRNA sequencing analyses are discussed.

Sunlit fractions on urban facets: impact of spatial resolution and approach

The extent of the surface area sunlit is critical for radiative energy exchanges and therefore for a wide range of applications that require urban land surface models (ULSM), ranging from human comfort to weather forecasting. Here a computational demanding shadow casting algorithm is used to assess the capability of a simple single-layer urban canopy model, which assumes an infinitely long rotating canyon (ILC), to reproduce sunlit areas on roof and roads over central London. Results indicate that the sunlit roads areas are well-represented but somewhat smaller using an ILC, while sunlit roofs areas are consistently larger, especially for dense urban areas. The largest deviations from real world sunlit areas are found for roofs during mornings and evenings. Indications that sunlit fractions on walls are overestimated using an ILC during mornings and evenings are found. The implications of these errors are dependent on the application targeted. For example, (independent of albedo) ULSMs used in numerical weather prediction applying ILC representation of the urban form will overestimate outgoing shortwave radiation from roofs due to the overestimation of sunlit fraction of the roofs. Complications of deriving height to width ratios from real world data are also discussed.