109 resultados para Heterotrophic bacteria in the Arctic
em CentAUR: Central Archive University of Reading - UK
Resumo:
The activities of the bacteria resident in the colon of companion animals can have an impact upon the health of the host. Our understanding of this microbial ecosystem is presently increasing due to the development of DNA-based microbiological tools that allow identification and enumeration of nonculturable microorganisms. These techniques are changing our view of the bacteria that live in the gut, and they are facilitating dietary-intervention approaches to modulate the colonic ecosystem. This is generally achieved by the feeding of either live bacteria (probiotics) or nondigestible oligosaccharides (prebiotics) that selectively feed the indigenous probiotics. Feeding studies with a Lactobacillus acidophilus probiotic have shown positive effects on carriage of Clostridium spp. in canines and on recovery from Campylobacter spp. infection in felines. Immune function was improved in both species. Prebiotic feeding studies with lactosucrose and fructo-oligosaccharides in both cats and dogs have shown positive effects on the microflora balance. Recently synbiotic forms (a probiotic together with a prebiotic) targeted at canines have been developed that show promise as dietary-intervention tools.
Resumo:
Ulcerative colitis is a severe, relapsing and remitting disease of the human large intestine characterised by inflammation of the mucosa and submucosa. The main site of disease is the sigmoid/rectal region of the large bowel but the aetiology remains unknown. There is considerable evidence to indicate that the components of the resident colonic microflora can play an important role in initiation of the disease. The present study was aimed at characterising the faecal microflora of ulcerative colitis patients in remission and active phases to determine profile differences. Faecal samples were obtained from 12 patients, 6 with active colitis and 6 in remission. The samples were analysed for populations of lactobacilli, bifidobacteria, clostridia, bacteroides, sulphate-reducing bacteria (SRB) and total bacteria using culture independent fluorescence in situ hybridisation (FISH). Lactobacillus-specific denaturing gradient gel electrophoresis (DGGE) was then performed to compare the species present. Numbers of lactobacilli were significantly lower (p<0.05) during the active phase of the disease but the other populations tested did not differ. DGGE analysis revealed that Lactobacillus salivarus, Lactobacillus manihotivorans and Pediococcus acidilactici were present in remission, but not during active inflammation. These results imply that a reduction in intestinal Lactobacillus species may be important in the initiation of ulcerative colitis.
Resumo:
Aim: To assess the effect of the growth promoter avilamycin on emergence and persistence of resistance in enteric bacteria in the pig. Methods and Results: Pigs ( treated with avilamycin for 3 months and controls) were challenged with multiresistant Salmonella Typhimurium DT104 and faecal counts were performed for enterococci, Escherichia coli, S. Typhimurium and Campylobacter ( before, during and 5 weeks post-treatment). Representative isolates were tested for antibiotic resistance and for the presence of resistance genes. Avilamycin-resistant Enterococci faecalis (speciated by PCR) were isolated from the treated pigs and continued to be detected for the first week after treatment had ceased. The avilamycin- resistance gene was characterized by PCR as the emtA gene and speciation by PCR. MIC profiling confirmed that more than one strain of Ent. faecalis carried this gene. There was no evidence of increased antimicrobial resistance in the E. coli, Salmonella and Campylobacter populations, although there was a higher incidence of tetB positive E. coli in the treated pigs than the controls. Conclusion: Although avilamycin selects for resistance in the native enterococci population of the pig, no resistant isolates were detected beyond 1 week post-treatment. This suggests that resistant isolates were unable to persist once selective pressure was removed and were out-competed by the sensitive microflora. Significance and Impact of the Study: Our data suggest the risk of resistant isolates becoming carcass contaminants and infecting humans could be minimized by introducing a withdrawal period after using avilamycin and prior to slaughter.
Resumo:
In contrast to prior studies showing a positive lapse-rate feedback associated with the Arctic inversion, Boé et al. reported that strong present-day Arctic temperature inversions are associated with stronger negative longwave feedbacks and thus reduced Arctic amplification in the model ensemble from phase 3 of the Coupled Model Intercomparison Project (CMIP3). A permutation test reveals that the relation between longwave feedbacks and inversion strength is an artifact of statistical self-correlation and that shortwave feedbacks have a stronger correlation with intermodel spread. The present comment concludes that the conventional understanding of a positive lapse-rate feedback associated with the Arctic inversion is consistent with the CMIP3 model ensemble.
Resumo:
The concentrations of sulfate, black carbon (BC) and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality and especially the high concentrations associated with Arctic Haze. In this study, we evaluate sulfate and BC concentrations from eleven different models driven with the same emission inventory against a comprehensive pan-Arctic measurement data set over a time period of 2 years (2008–2009). The set of models consisted of one Lagrangian particle dispersion model, four chemistry transport models (CTMs), one atmospheric chemistry-weather forecast model and five chemistry climate models (CCMs), of which two were nudged to meteorological analyses and three were running freely. The measurement data set consisted of surface measurements of equivalent BC (eBC) from five stations (Alert, Barrow, Pallas, Tiksi and Zeppelin), elemental carbon (EC) from Station Nord and Alert and aircraft measurements of refractory BC (rBC) from six different campaigns. We find that the models generally captured the measured eBC or rBC and sulfate concentrations quite well, compared to previous comparisons. However, the aerosol seasonality at the surface is still too weak in most models. Concentrations of eBC and sulfate averaged over three surface sites are underestimated in winter/spring in all but one model (model means for January–March underestimated by 59 and 37 % for BC and sulfate, respectively), whereas concentrations in summer are overestimated in the model mean (by 88 and 44 % for July–September), but with overestimates as well as underestimates present in individual models. The most pronounced eBC underestimates, not included in the above multi-site average, are found for the station Tiksi in Siberia where the measured annual mean eBC concentration is 3 times higher than the average annual mean for all other stations. This suggests an underestimate of BC sources in Russia in the emission inventory used. Based on the campaign data, biomass burning was identified as another cause of the modeling problems. For sulfate, very large differences were found in the model ensemble, with an apparent anti-correlation between modeled surface concentrations and total atmospheric columns. There is a strong correlation between observed sulfate and eBC concentrations with consistent sulfate/eBC slopes found for all Arctic stations, indicating that the sources contributing to sulfate and BC are similar throughout the Arctic and that the aerosols are internally mixed and undergo similar removal. However, only three models reproduced this finding, whereas sulfate and BC are weakly correlated in the other models. Overall, no class of models (e.g., CTMs, CCMs) performed better than the others and differences are independent of model resolution.
Resumo:
Temporal and spatial variability of aerosol optical depth (AOD) are examined using observations of direct solar radiation in the Eurasian Arctic for 1940-1990. AOD is estimated using empirical methods for 14 stations located between 66.2 degrees N and 80.6 degrees N, from the Kara Sea to the Chukchi Sea. While AOD exhibits a well-known springtime maximum and summertime minimum at all stations, atmospheric turbidity is higher in spring in the western (Kara-Laptev) part of the Eurasian Arctic. Between June and August, the eastern (East Siberian-Chukchi) sector experiences higher transparency than the western part. A statistically significant positive trend in AOD was observed in the Kara-Laptev sector between the late 1950s and the early 1930s predominantly in spring when pollution-derived aerosol dominates the Arctic atmosphere but not in the eastern sector. Although all stations are remote, those with positive trends are located closer to the anthropogenic sources of air pollution. By contrast, a widespread decline in AOD was observed between 1982 and 1990 in the eastern Arctic in spring but was limited to two sites in the western Arctic. These results suggest that the post-1982 decline in anthropogenic emissions in Europe and the former Soviet Union has had a limited effect on aerosol load in the Arctic. The post-1982 negative trends in AOD in summer, when marine aerosol is present in the atmosphere, were more common in the west. The relationships between AOD and atmospheric circulation are examined using a synoptic climatology approach. In spring, AOD depends primarily on the strength and direction of air flow. Thus strong westerly and northerly flows result in low AOD values in the East Siberian-Chukchi sector. By contrast, strong southerly flow associated with the passage of depressions results in high A OD in the Kara-Laptev sector and trajectory analysis points to the contribution of industrial regions of the sub-Arctic. In summer, low pressure gradient or anticyclonic conditions result in high atmospheric turbidity. The frequency of this weather type has declined significantly since the early 1980s in the Kara-Laptev sector, which partly explains the decline in summer AOD values. (c) 2004 Elsevier B.V. All rights reserved.
Resumo:
There are significant discrepancies between observational datasets of Arctic sea ice concentrations covering the last three decades, which result in differences of over 20% in Arctic summer sea ice extent/area and 5%–10% in winter. Previous modeling studies have shown that idealized sea ice anomalies have the potential for making a substantial impact on climate. In this paper, this theory is further developed by performing a set of simulations using the third Hadley Centre Coupled Atmospheric Model (HadAM3). The model was driven with monthly climatologies of sea ice fractions derived from three of these records to investigate potential implications of sea ice inaccuracies for climate simulations. The standard sea ice climatology from the Met Office provided a control. This study focuses on the effects of actual inaccuracies of concentration retrievals, which vary spatially and are larger in summer than winter. The smaller sea ice discrepancies in winter have a much larger influence on climate than the much greater summer sea ice differences. High sensitivity to sea ice prescription was observed, even though no SST feedbacks were included. Significant effects on surface fields were observed in the Arctic, North Atlantic, and North Pacific. Arctic average surface air temperature anomalies in winter vary by 2.5°C, and locally exceed 12°C. Arctic mean sea level pressure varies by up to 5 mb locally. Anomalies extend to 45°N over North America and Eurasia but not to lower latitudes, and with limited changes in circulation above the boundary layer. No statistically significant impact on climate variability was simulated, in terms of the North Atlantic Oscillation. Results suggest that the uncertainty in summer sea ice prescription is not critical but that winter values require greater accuracy, with the caveats that the influences of ocean–sea ice feedbacks were not included in this study.
Resumo:
The Arctic is an important region in the study of climate change, but monitoring surface temperatures in this region is challenging, particularly in areas covered by sea ice. Here in situ, satellite and reanalysis data were utilised to investigate whether global warming over recent decades could be better estimated by changing the way the Arctic is treated in calculating global mean temperature. The degree of difference arising from using five different techniques, based on existing temperature anomaly dataset techniques, to estimate Arctic SAT anomalies over land and sea ice were investigated using reanalysis data as a testbed. Techniques which interpolated anomalies were found to result in smaller errors than non-interpolating techniques. Kriging techniques provided the smallest errors in anomaly estimates. Similar accuracies were found for anomalies estimated from in situ meteorological station SAT records using a kriging technique. Whether additional data sources, which are not currently utilised in temperature anomaly datasets, would improve estimates of Arctic surface air temperature anomalies was investigated within the reanalysis testbed and using in situ data. For the reanalysis study, the additional input anomalies were reanalysis data sampled at certain supplementary data source locations over Arctic land and sea ice areas. For the in situ data study, the additional input anomalies over sea ice were surface temperature anomalies derived from the Advanced Very High Resolution Radiometer satellite instruments. The use of additional data sources, particularly those located in the Arctic Ocean over sea ice or on islands in sparsely observed regions, can lead to substantial improvements in the accuracy of estimated anomalies. Decreases in Root Mean Square Error can be up to 0.2K for Arctic-average anomalies and more than 1K for spatially resolved anomalies. Further improvements in accuracy may be accomplished through the use of other data sources.
Resumo:
A present day control integration performed with the Hadley Centre's coupled climate model HadGEM1.2 experiences a large salinity bias in the Arctic Ocean when compared to in situ observations. Such a large salinity bias may have implications for both Arctic and Atlantic Ocean circulation. Large differences are seen between the runoff in HadGEM and the observations from the Global Runoff Data Centre, in particular in the Lena catchment, which could account for this salinity bias. We suggest that this discrepancy in runoff is, at least in part, due to a lack of snow accumulation in the model. The model climatology is very different to those obtained by remote sensing, such as the Global Snow Water Equivalent Climatology (NSIDC) and GlobSnow (ESA).