Rich and famous: recognition-based judgment in the Sunday Times rich list

Recognition as a cue to judgment in a novel, multi-option domain (the Sunday Times Rich List) is explored. As in previous studies, participants were found to make use of name recognition as a cue to the presumed wealth of individuals. Names that were recognized were judged to be the richest name from amongst the set presented at above chance levels. This effect persisted across situations in which more than one name was recognized; recognition was used as an inclusion criterion for the sub-set of names to be considered the richest of the set presented. However, when the question was reversed, and a “poorest” judgment was required, use of recognition as an exclusion criterion was observed only when a single name was recognized. Reaction times when making these judgments also show a distinction between “richest” and “poorest” questions with recognition of none of the options taking the longest time to judge in the “richest” question condition and full recognition of all the names presented taking longest to judge in the “poorest” question condition. Implications for decision-making using simple heuristics are discussed.

Predicted soil organic carbon stocks and changes in Jordan between 2000 and 2030 made using the GEFSOC modelling system

Estimates of soil organic carbon (SOC) stocks and changes under different land use systems can help determine vulnerability to land degradation. Such information is important for countries in and areas with high susceptibility to desertification. SOC stocks, and predicted changes between 2000 and 2030, were determined at the national scale for Jordan using The Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. For the purpose of this study, Jordan was divided into three natural regions (The Jordan Valley, the Uplands and the Badia) and three developmental regions (North, Middle and South). Based on this division, Jordan was divided into five zones (based on the dominant land use): the Jordan Valley, the North Uplands, the Middle Uplands, the South Uplands and the Badia. This information was merged using GIS, along with a map of rainfall isohyets, to produce a map with 498 polygons. Each of these was given a unique ID, a land management unit identifier and was characterized in terms of its dominant soil type. Historical land use data, current land use and future land use change scenarios were also assembled, forming major inputs of the modelling system. The GEFSOC Modelling System was then run to produce C stocks in Jordan for the years 1990, 2000 and 2030. The results were compared with conventional methods of estimating carbon stocks, such as the mapping based SOTER method. The results of these comparisons showed that the model runs are acceptable, taking into consideration the limited availability of long-term experimental soil data that can be used to validate them. The main findings of this research show that between 2000 and 2030, SOC may increase in heavily used areas under irrigation and will likely decrease in grazed rangelands that cover most of Jordan giving an overall decrease in total SOC over time if the land is indeed used under the estimated forms of land use. (C) 2007 Elsevier B.V. All rights reserved.

Modelled soil organic carbon stocks and changes in the Indo-Gangetic Plains, India from 1980 to 2030

The Global Environment Facility co-financed Soil Organic Carbon (GEFSOC) Project developed a comprehensive modelling system for predicting soil organic carbon (SOC) stocks and changes over time. This research is an effort to predict SOC stocks and changes for the Indian, Indo-Gangetic Plains (IGP), an area with a predominantly rice (Oryza sativa) - wheat (Triticum aestivum) cropping system, using the GEFSOC Modelling System and to compare output with stocks generated using mapping approaches based on soil survey data. The GEFSOC Modelling System predicts an estimated SOC stock for the IGP, India of 1.27, 1.32 and 1.27 Pg for 1990, 2000 and 2030, respectively, in the top 20 cm of soil. The SOC stock using a mapping approach based on soil survey data was 0.66 and 0.88 Pg for 1980 and 2000, respectively. The SOC stock estimated using the GEFSOC Modelling System is higher than the stock estimated using the mapping approach. This is due to the fact that while the GEFSOC System accounts for variation in crop input data (crop management), the soil mapping approach only considers regional variation in soil texture and wetness. The trend of overall change in the modelled SOC stock estimates shows that the IGP, India may have reached an equilibrium following 30-40 years of the Green Revolution. This can be seen in the SOC stock change rates. Various different estimation methods show SOC stocks of 0.57-1.44 Pg C for the study area. The trend of overall change in C stock assessed from the soil survey data indicates that the soils of the IGP, India may store a projected 1.1 Pg of C in 2030. (C) 2007 Elsevier B.V. All rights reserved.

Evaluating the century C model using long-term fertilizer trials in the Indo-Gangetic Plains, India

The GEFSOC Project developed a system for estimating soil carbon (C) stocks and changes at the national and sub-national scale. As part of the development of the system, the Century ecosystem model was evaluated for its ability to simulate soil organic C (SOC) changes in environmental conditions in the Indo-Gangetic Plains, India (IGP). Two long-term fertilizer trials (LTFT), with all necessary parameters needed to run Century, were used for this purpose: a jute (Corchorus capsularis L.), rice (Oryza sativa L.) and wheat (Triticum aestivum L.) trial at Barrackpore, West Bengal, and a rice-wheat trial at Ludhiana, Punjab. The trials represent two contrasting climates of the IGP, viz. semi-arid, dry with mean annual rainfall (MAR) of < 800 mm and humid with > 1600 turn. Both trials involved several different treatments with different organic and inorganic fertilizer inputs. In general, the model tended to overestimate treatment effects by approximately 15%. At the semi-arid site, modelled data simulated actual data reasonably well for all treatments, with the control and chemical N + farm yard manure showing the best agreement (RMSE = 7). At the humid site, Century performed less well. This could have been due to a range of factors including site history. During the study, Century was calibrated to simulate crop yields for the two sites considered using data from across the Indian IGP. However, further adjustments may improve model performance at these sites and others in the IGP. The availability of more longterm experimental data sets (especially those involving flooded lowland rice and triple cropping systems from the IGP) for testing and validation is critical to the application of the model's predictive capabilities for this area of the Indian sub-continent. (C) 2007 Elsevier B.V. All rights reserved.

Simulating SOC changes in 11 land use change chronosequences from the Brazilian Amazon with RothC and Century models

Land use and land cover changes in the Brazilian Amazon have major implications for regional and global carbon (C) cycling. Cattle pasture represents the largest single use (about 70%) of this once-forested land in most of the region. The main objective of this study was to evaluate the accuracy of the RothC and Century models at estimating soil organic C (SOC) changes under forest-to-pasture conditions in the Brazilian Amazon. We used data from 11 site-specific 'forest to pasture' chronosequences with the Century Ecosystem Model (Century 4.0) and the Rothamsted C Model (RothC 26.3). The models predicted that forest clearance and conversion to well managed pasture would cause an initial decline in soil C stocks (0-20 cm depth), followed in the majority of cases by a slow rise to levels exceeding those under native forest. One exception to this pattern was a chronosequence in Suia-Missu, which is under degraded pasture. In three other chronosequences the recovery of soil C under pasture appeared to be only to about the same level as under the previous forest. Statistical tests were applied to determine levels of agreement between simulated SOC stocks and observed stocks for all the sites within the 11 chronosequences. The models also provided reasonable estimates (coefficient of correlation = 0.8) of the microbial biomass C in the 0-10 cm soil layer for three chronosequences, when compared with available measured data. The Century model adequately predicted the magnitude and the overall trend in delta C-13 for the six chronosequences where measured 813 C data were available. This study gave independent tests of model performance, as no adjustments were made to the models to generate outputs. Our results suggest that modelling techniques can be successfully used for monitoring soil C stocks and changes, allowing both the identification of current patterns in the soil and the projection of future conditions. Results were used and discussed not only to evaluate soil C dynamics but also to indicate soil C sequestration opportunities for the Brazilian Amazon region. Moreover, modelling studies in these 'forest to pasture' systems have important applications, for example, the calculation of CO, emissions from land use change in national greenhouse gas inventories. (0 2007 Elsevier B.V. All rights reserved.

Predicted soil organic carbon stocks and changes in the Brazilian Amazon between 2000 and 2030

Currently we have little understanding of the impacts of land use change on soil C stocks in the Brazilian Amazon. Such information is needed to determine impacts'6n the global C cycle and the sustainability of agricultural systems that are replacing native forest. The aim of this study was to predict soil carbon stocks and changes in the Brazilian Amazon during the period between 2000 and 2030, using the GEFSOC soil carbon (C) modelling system. In order to do so, we devised current and future land use scenarios for the Brazilian Amazon, taking into account: (i) deforestation, rates from the past three decades, (ii) census data on land use from 1940 to 2000, including the expansion and intensification of agriculture in the region, (iii) available information on management practices, primarily related to well managed pasture versus degraded pasture and conventional systems versus no-tillage systems for soybean (Glycine max) and (iv) FAO predictions on agricultural land use and land use changes for the years 2015 and 2030. The land use scenarios were integrated with spatially explicit soils data (SOTER database), climate, potential natural vegetation and land management units using the recently developed GEFSOC soil C modelling system. Results are presented in map, table and graph form for the entire Brazilian Amazon for the current situation (1990 and 2000) and the future (2015 and 2030). Results include soil organic C (SOC) stocks and SOC stock change rates estimated by three methods: (i) the Century ecosystem model, (ii) the Rothamsted C model and (iii) the intergovernmental panel on climate change (IPCC) method for assessing soil C at regional scale. In addition, we show estimated values of above and belowground biomass for native vegetation, pasture and soybean. The results on regional SOC stocks compare reasonably well with those based on mapping approaches. The GEFSOC system provided a means of efficiently handling complex interactions among biotic-edapho-climatic conditions (> 363,000 combinations) in a very large area (similar to 500 Mha) such as the Brazilian Amazon. All of the methods used showed a decline in SOC stock for the period studied; Century and RothC simulated values for 2030 being about 7% lower than those in 1990. Values from Century and RothC (30,430 and 25,000 Tg for the 0-20 cm layer for the Brazilian Amazon region were higher than those obtained from the IPCC system (23,400 Tg in the 0-30 cm layer). Finally; our results can help understand the major biogeochemical cycles that influence soil fertility and help devise management strategies that enhance the sustainability of these areas and thus slow further deforestation. (C) 2007 Elsevier B.V. All rights reserved.

Magic for the dead? The archaeology of magic in later medieval burials

THIS PAPER EXAMINES patterns in the placement of apotropaic objects and materials in high- to late-medieval burials in Britain (11th to 15th centuries). It develops an interdisciplinary classification to identify: (1) healing charms and protective amulets; (2) objects perceived to have occult natural power; (3) 'antique' items that were treated as possessing occult power; and (4) rare practices that may have been associated with the demonic magic of divination or sorcery. Making comparisons with amulets deposited in conversion-period graves of the 7th to 9th centuries it is argued that the placement of amulets with the dead was strategic to Christian belief, intended to transform or protect the corpse. The conclusion is that material traces of magic in later medieval graves have a connection to folk magic, performed by women in the care of their families, and drawing on knowledge of earlier traditions. This popular magic was integrated with Christian concerns and tolerated by local clergy, and was perhaps meant to heal or reconstitute the corpse, to ensure its reanimation on judgement day, and to protect the vulnerable dead on their journey through purgatory.

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.

Influence of foliar diseases and their control by fungicides on grain yield and quality in wheat

Twenty-eight field experiments on sandy-loam soils in the UK (1982-2003) are reviewed by relating the extension of the green area duration of the flag leaf (GLADF) by fungicides to effects on yield and quality of winter wheat. Over all experiments mean grain yield = 8.85t ha(-1) at 85% DM. With regards quality, mean values were: thousand grain weight (TGW) = 44.5 g; specific weight (SWT) = 76.9 kg hl(-1); crude protein concentration (CP (N x 5.7)) = 12.5 % DM; Hagberg falling number (HFN) = 285 s; and sodium dodecyl sulphate (SDS)-sedimentation volume = 69ml. For each day (d) that fungicides increased GLADF there were associated average increases in yield (0.144 1 ha(-1) d(-1), se 0.0049, df = 333), TGW (0.56 gd(-1), se = 0.017) and SWT (0.22 kg hl(-1) d(-1), se 0.011). Some curvature was evident in all these relationships. When GLADF was delayed beyond 700 degrees Cd after anthesis, as was possible in cool wet seasons, responses were curtailed, or less reliable. Despite this apparent terminal sink limitation, fungicide effects on sink size, eg endosperm cell numbers or maximum water mass per grain, were not prerequisites for large effects on grain yield, TGW or SWT. Fungicide effects on CP were variable. Although the average response of CP was negative (-0.029%DM/d; se = 0.00338), this depended on cultivar and disease controlled. Controlling biotrophs such as rusts, (Puccinia spp.) tended to increase CP, whereas controlling a more necrotrophic pathogen (Septoria tritici) usually reducedCP. Irrespective of pathogen controlled, delaying senescence of the flag leaf was associated with increased nitrogen yields in the grain (averaging 2.24 kg N ha-1 d(-1), se = 0.0848) due to both increased N uptake into the above ground crop, and also more efficient remobilisation of N from leaf laminas. When sulphur availability appeared to be adequate, fungicide x cultivar interactions were similar on S as for CP, although N:S ratios tended to decline (i.e. improve for bread making) when S. tritici was controlled. On average, SDS-sedimentation volume declined (-0. 18 ml/d, se = 0.027) with increased GLADF, broadly commensurate with the average effect on CP. Hagberg falling number decreased as fungicide increased GLADF (-2.73 s/d, se = 0.178), indicating an increase in alpha-amylase activity.

Low-cost optical tracking for immersive collaboration in the CAVE using the Wii remote

We present a novel way of interacting with an immersive virtual environment which involves inexpensive motion-capture using the Wii Remote®. A software framework is also presented to visualize and share this information across two remote CAVETM-like environments. The resulting applications can be used to assist rehabilitation by sending motion information across remote sites. The application’s software and hardware components are scalable enough to be used on desktop computer when home-based rehabilitation is preferred.

Measurement and prediction of the effect of students activities on airborne particulate concentration in a classroom.

Epidemiological studies have shown links between human exposure to indoor airborne particles and adverse health affects. Several recent studies have also reported that the classroom environment has an impact on students’ health and performance. In this study particle concentration in a university classroom is assessed experimentally for different occupancy periods. The mass concentrations of different particle size ranges (0.3 – 20 µm), and the three particulate matter fractions (PM10, PM2.5, and PM1) were measured simultaneously in a classroom with different occupancy periods including occupied and unoccupied periods in the University of Reading, UK, during the winter period of 2010. The results showed that students’ presence is a significant factor affecting particles concentration for the fractions above PM1 in the measured range of 0.3 to 20 µm. The resuspension of the three PM fractions was also determined in the study.