Effect of pH, temperature and surface contact on the elaboration of fimbriae and flagella by Salmonella serotype Enteritidis

Survival of enteric pathogens exposed to various environmental stresses depends upon a number of protective responses, some of which are associated with induction of virulence determinants. Flagella and fimbriae are putative virulence determinants of Salmonella spp, and ELISAs specific for the detection of flagella and SEF21, SEF14 and SEF17 fimbriae were used to assess the effect of temperature and pH upon their elaboration by isolates of Salmonella serotype Enteritidis in planktonic growth and on the surface of two-dimensional gradient agar plates, For three phage type 4 isolates of Enteritidis of comparative clinical provenance, similar phenotypes for the elaboration of these surface antigens were observed. SEF14 fimbriae were elaborated in planktonic growth at 37 degrees C, but not 20 degrees C, at pH 4.77 and above but not at pH 4.04; whereas on agar gradient plates SEF14 fimbriae were elaborated poorly but with best yields at pH 4.04, SEF17 fimbriae were elaborated in planktonic growth at 20 degrees C, but not at 37 degrees C, at pH 6.18 and above but not at pH 5.09 or below; whereas on agar gradient plates SEF17 fimbriae were elaborated well even at pH 4.65, SEF21 fimbriae were expressed very poorly under all conditions tested, Planktonic growth at 37 degrees C induced least flagella whereas growth at 20 degrees C, and particularly surface growth at lower pH values, induced a 'hyper-flagellate' phenotype, Single colonies allowed to form on gradient agar plates were shown to generate different colonial morphologies which were dependent on initial pH. These results demonstrate that the physicochemical environment is an important determinant of bacterial response, especially the induction of putative virulence factors.

Increasing influence of heat stress on French maize yields from the 1960s to the 2030s

Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near-term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target.

In situ preservation of wetland heritage: hydrological and chemical change in the burial environment of the Somerset Levels, UK.

In Situ preservation is a core strategy for the conservation and management of waterlogged remains at wetland sites. Inorganic and organic remains can, however, quickly become degraded, or lost entirely, as a result of chemical or hydrological changes. Monitoring is therefore crucial in identifying baseline data for a site, the extent of spatial and or temporal variability, and in evaluating the potential impacts of these variables on current and future In Situ preservation potential. Since August 2009, monthly monitoring has taken place at the internationally important Iron Age site of Glastonbury Lake Village in the Somerset Levels, UK. A spatial, stratigraphic, and analytical approach to the analysis of sediment horizons and monitoring of groundwater chemistry, redox potential, water table depth and soil moisture (using TDR) was used to characterize the site. Significant spatial and temporal variability has been identified, with results from water-table monitoring and some initial chemical analysis from Glastonbury presented here. It appears that during dry periods parts of this site are at risk from desiccation. Analysis of the chemical data, in addition to integrating the results from the other parameters, is ongoing, with the aim of clarifying the risk to the entire site.

Projections of UV radiation changes in the 21st century: impact of ozone recovery and cloud effects

Monthly averaged surface erythemal solar irradiance (UV-Ery) for local noon from 1960 to 2100 has been derived using radiative transfer calculations and projections of ozone, temperature and cloud change from 14 chemistry climate models (CCM), as part of the CCMVal-2 activity of SPARC. Our calculations show the influence of ozone depletion and recovery on erythemal irradiance. In addition, we investigate UV-Ery changes caused by climate change due to increasing greenhouse gas concentrations. The latter include effects of both stratospheric ozone and cloud changes. The derived estimates provide a global picture of the likely changes in erythemal irradiance during the 21st century. Uncertainties arise from the assumed scenarios, different parameterizations – particularly of cloud effects on UV-Ery – and the spread in the CCM projections. The calculations suggest that relative to 1980, annually mean UV-Ery in the 2090s will be on average 12% lower at high latitudes in both hemispheres, 3% lower at mid latitudes, and marginally higher (1 %) in the tropics. The largest reduction (16 %) is projected for Antarctica in October. Cloud effects are responsible for 2–3% of the reduction in UV-Ery at high latitudes, but they slightly moderate it at mid-latitudes (1 %). The year of return of erythemal irradiance to values of certain milestones (1965 and 1980) depends largely on the return of column ozone to the corresponding levels and is associated with large uncertainties mainly due to the spread of the model projections. The inclusion of cloud effects in the calculations has only a small effect of the return years. At mid and high latitudes, changes in clouds and stratospheric ozone transport by global circulation changes due to greenhouse gases will sustain the erythemal irradiance at levels below those in 1965, despite the removal of ozone depleting substances.

Northern winter stratospheric temperature and ozone responses to ENSO inferred from an ensemble of Chemistry Climate Models

The connection between the El Ni˜no Southern Oscillation (ENSO) and the Northern polar stratosphere has been established from observations and atmospheric modeling. Here a systematic inter-comparison of the sensitivity of the modeled stratosphere to ENSO in Chemistry Climate Models (CCMs) is reported. This work uses results from a number of the CCMs included in the 2006 ozone assessment. In the lower stratosphere, the mean of all model simulations reports a warming of the polar vortex during strong ENSO events in February–March, consistent with but smaller than the estimate from satellite observations and ERA40 reanalysis. The anomalous warming is associated with an anomalous dynamical increase of column ozone north of 70� N that is accompanied by coherent column ozone decrease in the Tropics, in agreement with that deduced from the NIWA column ozone database, implying an increased residual circulation in the mean of all model simulations during ENSO. The spread in the model responses is partly due to the large internal stratospheric variability and it is shown that it crucially depends on the representation of the tropospheric ENSO teleconnection in the models.

Ensemble projections for wine production in the Douro Valley of Portugal

Wine production is largely governed by atmospheric conditions, such as air temperature and precipitation, together with soil management and viticultural/enological practices. Therefore, anthropogenic climate change is likely to have important impacts on the winemaking sector worldwide. An important winemaking region is the Portuguese Douro Valley, which is known by its world-famous Port Wine. The identification of robust relationships between atmospheric factors and wine parameters is of great relevance for the region. A multivariate linear regression analysis of a long wine production series (1932–2010) reveals that high rainfall and cool temperatures during budburst, shoot and inflorescence development (February-March) and warm temperatures during flowering and berry development (May) are generally favourable to high production. The probabilities of occurrence of three production categories (low, normal and high) are also modelled using multinomial logistic regression. Results show that both statistical models are valuable tools for predicting the production in a given year with a lead time of 3–4 months prior to harvest. These statistical models are applied to an ensemble of 16 regional climate model experiments following the SRES A1B scenario to estimate possible future changes. Wine production is projected to increase by about 10 % by the end of the 21st century, while the occurrence of high production years is expected to increase from 25 % to over 60 %. Nevertheless, further model development will be needed to include other aspects that may shape production in the future. In particular, the rising heat stress and/or changes in ripening conditions could limit the projected production increase in future decades.

Macroclimate and viticultural zoning in Europe: observed trends and atmospheric forcing

Temperature and precipitation are major forcing factors influencing grapevine phenology and yield, as well as wine quality. Bioclimatic indices describing the suitability of a particular region for wine production are a commonly used tool for viticultural zoning. For this research these indices were computed for Europe by using the E-OBS gridded daily temperature and precipitation data set for the period from 1950 to 2009. Results showed strong regional contrasts based on the different index patterns and reproduced the wide diversity of local conditions that largely explain the quality and diversity of grapevines being grown across Europe. Owing to the strong inter-annual variability in the indices, a trend analysis and a principal component analysis were applied together with an assessment of their mean patterns. Significant trends were identified in the Winkler and Huglin indices, particularly for southwestern Europe. Four statistically significant orthogonal modes of variability were isolated for the Huglin index (HI), jointly representing 82% of the total variance in Europe. The leading mode was largely dominant (48% of variance) and mainly reflected the observed historical long-term changes. The other 3 modes corresponded to regional dipoles within Europe. Despite the relevance of local and regional climatic characteristics to grapevines, it was demonstrated via canonical correlation analysis that the observed inter-annual variability of the HI was strongly controlled by the large-scale atmospheric circulation during the growing season (April to September).

Synoptic-scale controls of persistent low temperature and icy weather over southern China in January 2008

In January 2008, central and southern China experienced persistent low temperatures, freezing rain, and snow. The large-scale conditions associated with the occurrence and development of these snowstorms are examined in order to identify the key synoptic controls leading to this event. Three main factors are identified: 1) the persistent blocking high over Siberia, which remained quasi-stationary around 65°E for 3 weeks, led to advection of dry and cold Siberian air down to central and southern China; 2) a strong persistent southwesterly flow associated with the western Pacific subtropical high led to enhanced moisture advection from the Bay of Bengal into central and southern China; and 3) the deep inversion layer in the lower troposphere associated with the extended snow cover over most of central and southern China. The combination of these three factors is likely responsible for the unusual severity of the event, and hence a long return period

Effect of Rht alleles on the tolerance of wheat grain set to high temperature and drought stress during booting and anthesis

Factorial pot experiments were conducted to compare the responses of GA-sensitive and GA-insensitive reduced height (Rht) alleles in wheat for susceptibility to heat and drought stress during booting and anthesis. Grain set (grains/spikelet) of near isogenic lines (NILs) was assessed following three day transfers to controlled environments imposing day temperatures (t) from 20 to 40°C. Transfers were during booting and/or anthesis and pots maintained at field capacity (FC) or had water withheld. Logistic responses (y = c/1+e-b(t -m)) described declining grain set with increasing t, and t5 was that fitted to give a 5% reduction in grain set. Averaged over NIL, t5 for anthesis at FC was 31.7±0.47°C (S.E.M, 26 d.f.). Drought at anthesis reduced t5 by <2°C. Maintaining FC at booting conferred considerable resistance to high temperatures (t5=33.9°C) but booting was particularly heat susceptible without water (t5 =26.5°C). In one background (cv. Mercia), for NILs varying at the Rht-D1 locus, there was progressive reduction in t5 with dwarfing and reduced gibberellic acid (GA) sensitivity (Rht-D1a, tall, 32.7±0.72; Rht-D1b, semi-dwarf, 29.5±0.85; Rht-D1c, severe dwarf, 24.2±0.72). This trend was not evident for the Rht-B1 locus, or for Rht-D1b in an alternative background (Maris Widgeon). The GA-sensitive severe dwarf Rht12 was more heat tolerant (t5=29.4±0.72) than the similarly statured GA-insensitive Rht-D1c. The GA-sensitive, semi-dwarfing Rht8 conferred greater drought tolerance in one experiment. Despite the effects of Rht-D1 alleles in Mercia on stress tolerance, the inconsistency of the effects over background and locus led to the conclusion that semi-dwarfing with GA-insensitivity did not necessarily increase sensitivity to stress at booting and flowering. In comparison to effects of semi-dwarfing alleles, responses to heat stress are much more dramatically affected by water availability and the precise growth stage at which the stress is experienced by the plants.

Representativity error for temperature and humidity using the Met Office high-resolution model

The observation-error covariance matrix used in data assimilation contains contributions from instrument errors, representativity errors and errors introduced by the approximated observation operator. Forward model errors arise when the observation operator does not correctly model the observations or when observations can resolve spatial scales that the model cannot. Previous work to estimate the observation-error covariance matrix for particular observing instruments has shown that it contains signifcant correlations. In particular, correlations for humidity data are more significant than those for temperature. However it is not known what proportion of these correlations can be attributed to the representativity errors. In this article we apply an existing method for calculating representativity error, previously applied to an idealised system, to NWP data. We calculate horizontal errors of representativity for temperature and humidity using data from the Met Office high-resolution UK variable resolution model. Our results show that errors of representativity are correlated and more significant for specific humidity than temperature. We also find that representativity error varies with height. This suggests that the assimilation scheme may be improved if these errors are explicitly included in a data assimilation scheme. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland.