Chemical composition observed over the mid-Atlantic and the detection of pollution signatures far from source regions

The atmospheric composition of the central North Atlantic region has been sampled using the FAAM BAe146 instrumented aircraft during the Intercontinental Transport of Ozone and Precursors (ITOP) campaign, part of the wider International Consortium for Atmospheric Research on Transport and Transformation (ICARTT). This paper presents an overview of the ITOP campaign. Between late July and early August 2004, twelve flights comprising 72 hours of measurement were made in a region from approximately 20 to 40°W and 33 to 47°N centered on Faial Island, Azores, ranging in altitude from 50 to 9000 m. The vertical profiles of O3 and CO are consistent with previous observations made in this region during 1997 and our knowledge of the seasonal cycles within the region. A cluster analysis technique is used to partition the data set into air mass types with distinct chemical signatures. Six clusters provide a suitable balance between cluster generality and specificity. The clusters are labeled as biomass burning, low level outflow, upper level outflow, moist lower troposphere, marine and upper troposphere. During this summer, boreal forest fire emissions from Alaska and northern Canada were found to provide a major perturbation of tropospheric composition in CO, PAN, organic compounds and aerosol. Anthropogenic influenced air from the continental boundary layer of the USA was clearly observed running above the marine boundary layer right across the mid-Atlantic, retaining high pollution levels in VOCs and sulfate aerosol. Upper level outflow events were found to have far lower sulfate aerosol, resulting from washout on ascent, but much higher PAN associated with the colder temperatures. Lagrangian links with flights of other aircraft over the USA and Europe show that such signatures are maintained many days downwind of emission regions. Some other features of the data set are highlighted, including the strong perturbations to many VOCs and OVOCs in this remote region.

A predictive model for early-warning of Septoria leaf blotch on winter wheat

Disease-weather relationships influencing Septoria leaf blotch (SLB) preceding growth stage (GS) 31 were identified using data from 12 sites in the UK covering 8 years. Based on these relationships, an early-warning predictive model for SLB on winter wheat was formulated to predict the occurrence of a damaging epidemic (defined as disease severity of 5% or > 5% on the top three leaf layers). The final model was based on accumulated rain > 3 mm in the 80-day period preceding GS 31 (roughly from early-February to the end of April) and accumulated minimum temperature with a 0A degrees C base in the 50-day period starting from 120 days preceding GS 31 (approximately January and February). The model was validated on an independent data set on which the prediction accuracy was influenced by cultivar resistance. Over all observations, the model had a true positive proportion of 0.61, a true negative proportion of 0.73, a sensitivity of 0.83, and a specificity of 0.18. True negative proportion increased to 0.85 for resistant cultivars and decreased to 0.50 for susceptible cultivars. Potential fungicide savings are most likely to be made with resistant cultivars, but such benefits would need to be identified with an in-depth evaluation.

The role of exotic plants in the invasion of Seychelles by the polyphagous insect Aleurodicus disperses: a phylogenetically controlled analysis

The accidental introduction of the spiralling whitefly, Aleurodicus dispersus Russell (Homoptera: Aleyrodidae) to Seychelles in late 2003 is exploited during early 2005 to study interactions between A. dispersus, native and exotic host plants and their associated arthropod fauna. The numbers of A. dispersus egg spirals and pupae, predator and herbivore taxa were recorded for eight related native/exotic pairs of host plants found on Mahe, the largest island in Seychelles. Our data revealed no significant difference in herbivore density (excluding A. dispersus) between related native and exotic plants, which suggests that the exotic plants do not benefit from 'enemy release'. There were also no differences in predator density, or combined species richness between native and exotic plants. Together these data suggest that 'biotic resistance' to invasion is also unlikely. Despite the apparent lack of differences in community structure significantly fewer A. dispersus egg spirals and pupae were found on the native plants than on the exotic plants. Additional data on A. dispersus density were collected on Cousin Island, a managed nature reserve in which exotic plants are carefully controlled. Significantly higher densities of A. dispersus were observed on Mahe, where exotic plants are abundant, than on Cousin. These data suggest that the rapid invasion of Seychelles by A. dispersus may largely be due to the high proportion of plant species that are both exotic and hosts of A. dispersus; no support was found for either the 'enemy release' or the 'biotic resistance' hypotheses.

Geoarchaeological investigations of midden-formation processes in the early to late Neolithic levels at Catalhoyuk, Turkey ca. 8550-8370 cal BP.

Anthropogenic midden deposits are remarkably well preserved at the Neolithic settlement of atalhöyük and provide significant archaeological information on the types and nature of activities occurring at the site. To decipher their complex stratigraphy and to investigate formation processes, a combination of geoarchaeological techniques was used. Deposits were investigated from the early ceramic to late Neolithic levels, targeting continuous sequences to examine high resolution and broader scale changes in deposition. Thin-section micromorphology combined with targeted phytolith and geochemical analyses indicates they are composed of a diverse range of ashes and other charred and siliceous plant materials, with inputs of decayed plants and organic matter, fecal waste, and sedimentary aggregates, each with diverse depositional pathways. Activities identified include in situ burning, with a range of different fuel types that may be associated with different activities. The complexity and heterogeneity of the midden deposits, and thus the necessity of employing an integrated microstratigraphic approach is demonstrated, as a prerequisite for cultural and palaeoenvironmental reconstructions.

Natural genetic variation in caesium (Cs) accumulation by Arabidopsis thaliana

Ingestion of caesium (Cs) radioisotopes poses a health risk to humans. Crop varieties that accumulate less Cs in their edible tissues may provide a useful countermeasure. This study was performed to determine whether quantitative genetics on a model plant (Arabidopsis thaliana) might inform such 'safe'-crop strategies. Arabidopsis accessions and recombinant inbred lines (RILs), from Landsberg erecta (Ler) x Cape Verdi Island (Cvi), Ler x Columbia (Col), and Niederzenz (Nd) x Col mapping populations, were grown on agar supplemented with subtoxic levels of Cs. Shoot Cs concentration varied up to three-fold, and shoot f. wt varied up to 25-fold within populations. The heritability of growth and Cs accumulation traits ranged from 0.06 to 0.28. Four quantitative trait loci (QTL) accounted for > 80 of the genetic contribution to the total phenotypic variation in shoot Cs concentration in the Ler x Col population. QTL identified in this study, in particular, QTL co-localizing to the top and bottom regions of Chromosomes I and V in two different mapping populations, are amenable to positional cloning and, through collinearity, may inform selection or breeding strategies for the development of 'safe' crops.

Quantifying uncertainty in remotely sensed land cover maps

Remotely sensed land cover maps are increasingly used as inputs into environmental simulation models whose outputs inform decisions and policy-making. Risks associated with these decisions are dependent on model output uncertainty, which is in turn affected by the uncertainty of land cover inputs. This article presents a method of quantifying the uncertainty that results from potential mis-classification in remotely sensed land cover maps. In addition to quantifying uncertainty in the classification of individual pixels in the map, we also address the important case where land cover maps have been upscaled to a coarser grid to suit the users’ needs and are reported as proportions of land cover type. The approach is Bayesian and incorporates several layers of modelling but is straightforward to implement. First, we incorporate data in the confusion matrix derived from an independent field survey, and discuss the appropriate way to model such data. Second, we account for spatial correlation in the true land cover map, using the remotely sensed map as a prior. Third, spatial correlation in the mis-classification characteristics is induced by modelling their variance. The result is that we are able to simulate posterior means and variances for individual sites and the entire map using a simple Monte Carlo algorithm. The method is applied to the Land Cover Map 2000 for the region of England and Wales, a map used as an input into a current dynamic carbon flux model.

Predicting early data revisions to US GDP and the effects of releases on equity markets

The effects of data uncertainty on real-time decision-making can be reduced by predicting early revisions to US GDP growth. We show that survey forecasts efficiently anticipate the first-revised estimate of GDP, but that forecasting models incorporating monthly economic indicators and daily equity returns provide superior forecasts of the second-revised estimate. We consider the implications of these findings for analyses of the impact of surprises in GDP revision announcements on equity markets, and for analyses of the impact of anticipated future revisions on announcement-day returns.