Interacting effects of fertilization, mowing and grazing on plant species diversity of 1500 grasslands in Germany differ between regions

The relationship of different types of grassland use with plant species richness and composition (functional groups of herbs, legumes, and grasses) has so far been studied at small regional scales or comprising only few components of land use. We comprehensively studied the relationship between abandonment, fertilization, mowing intensity, and grazing by different livestock types on plant diversity and composition of 1514 grassland sites in three regions in North-East, Central and South-West Germany. We further considered environmental site conditions including soil type and topographical situation. Fertilized grasslands showed clearly reduced plant species diversity (−15% plant species richness, −0.1 Shannon diversity on fertilized grasslands plots of 16 m2) and changed composition (−3% proportion of herb species), grazing had the second largest effects and mowing the smallest ones. Among the grazed sites, the ones grazed by sheep had higher than average species richness (+27%), and the cattle grazed ones lower (−42%). Further, these general results were strongly modulated by interactions between the different components of land use and by regional context: land-use effects differed largely in size and sometimes even in direction between regions. This highlights the importance of comparing different regions and to involve a large number of plots when studying relationships between land use and plant diversity. Overall, our results show that great caution is necessary when extrapolating results and management recommendations to other regions.

Detection of the ADP-ribosyltransferase toxin gene (cdtA) and its activity in Clostridium difficile isolates from Equidae

Clostridium difficile is an antibiotic-associated emerging pathogen of humans and animals. Thus far three toxins of C. difficile have been described: an enterotoxin (ToxA), a cytotoxin (ToxB) and an ADP-ribosyltransferase (CDT). In the present work we describe the first isolation of CDT producing C. difficile from Equidae with gastro-intestinal disease. Out of 17 C. difficile strains isolated from Equidae, 11 were positive for the genes tcdA and tcdB encoding ToxA and ToxB. In addition four of these 11 isolates were positive for the cdtA gene encoding the catalytic subunit of the ADP-ribosyltransferase CDT. Interestingly none of the isolates derived from canines (41 isolates) and felines (4 isolates) harboured the cdtA gene. In C. difficile field isolates which contained the cdtA gene, ADP-ribosyltransferase activity could also be detected in culture supernatants indicating expression and secretion of CDT. All strains were associated with intestinal disorders, but no association was found for the occurrence of toxins with a specific clinical diagnosis.

Target genes for virulence assessment of Escherichia coli isolates from water, food and the environment

The widespread species Escherichia coli includes a broad variety of different types, ranging from highly pathogenic strains causing worldwide outbreaks of severe disease to avirulent isolates which are part of the normal intestinal flora or which are well characterized and safe laboratory strains. The pathogenicity of a given E. coli strain is mainly determined by specific virulence factors which include adhesins, invasins, toxins and capsule. They are often organized in large genetic blocks either on the chromosome ('pathogenicity islands'), on large plasmids or on phages and can be transmitted horizontally between strains. In this review we summarize the current knowledge of the virulence attributes which determine the pathogenic potential of E. coli strains and the methodology available to assess the virulence of E. coli isolates. We also focus on a recently developed procedure based on a broad-range detection system for E. coli-specific virulence genes that makes it possible to determine the potential pathogenicity and its nature in E. coli strains from various sources. This makes it possible to determine the pathotype of E. coli strains in medical diagnostics, to assess the virulence and health risks of E. coli contaminating water, food and the environment and to study potential reservoirs of virulence genes which might contribute to the emergence of new forms of pathogenic E. coli.

Paleoclimate data-model comparison and the role of climate forcings over the past 1500 years

The past 1500 years provide a valuable opportunity to study the response of the climate system to external forcings. However, the integration of paleoclimate proxies with climate modeling is critical to improving the understanding of climate dynamics. In this paper, a climate system model and proxy records are therefore used to study the role of natural and anthropogenic forcings in driving the global climate. The inverse and forward approaches to paleoclimate data–model comparison are applied, and sources of uncertainty are identified and discussed. In the first of two case studies, the climate model simulations are compared with multiproxy temperature reconstructions. Robust solar and volcanic signals are detected in Southern Hemisphere temperatures, with a possible volcanic signal detected in the Northern Hemisphere. The anthropogenic signal dominates during the industrial period. It is also found that seasonal and geographical biases may cause multiproxy reconstructions to overestimate the magnitude of the long-term preindustrial cooling trend. In the second case study, the model simulations are compared with a coral δ18O record from the central Pacific Ocean. It is found that greenhouse gases, solar irradiance, and volcanic eruptions all influence the mean state of the central Pacific, but there is no evidence that natural or anthropogenic forcings have any systematic impact on El Niño–Southern Oscillation. The proxy climate relationship is found to change over time, challenging the assumption of stationarity that underlies the interpretation of paleoclimate proxies. These case studies demonstrate the value of paleoclimate data–model comparison but also highlight the limitations of current techniques and demonstrate the need to develop alternative approaches.