Airborne and Grain Dust Fungal Community Compositions Are Shaped Regionally by Plant Genotypes and Farming Practices.

Chronic exposure to airborne fungi has been associated with different respiratory symptoms and pathologies in occupational populations, such as grain workers. However, the homogeneity in the fungal species composition of these bioaerosols on a large geographical scale and the different drivers that shape these fungal communities remain unclear. In this study, the diversity of fungi in grain dust and in the aerosols released during harvesting was determined across 96 sites at a geographical scale of 560 km(2) along an elevation gradient of 500 m by tag-encoded 454 pyrosequencing of the internal transcribed spacer (ITS) sequences. Associations between the structure of fungal communities in the grain dust and different abiotic (farming system, soil characteristics, and geographic and climatic parameters) and biotic (wheat cultivar and previous crop culture) factors were explored. These analyses revealed a strong relationship between the airborne and grain dust fungal communities and showed the presence of allergenic and mycotoxigenic species in most samples, which highlights the potential contribution of these fungal species to work-related respiratory symptoms of grain workers. The farming system was the major driver of the alpha and beta phylogenetic diversity values of fungal communities. In addition, elevation and soil CaCO3 concentrations shaped the alpha diversity, whereas wheat cultivar, cropping history, and the number of freezing days per year shaped the taxonomic beta diversity of these communities.

Season, Vegetation Proximity and Building Age Shape the Indoor Fungal Communities' Composition at City-Scale.

Exposure to particular microbiome compositions in the built environment can affect human health and well-being. Identifying the drivers of these indoor microbial assemblages is key to controlling the microbiota of the built environment. In the present study, we used culture and metabarcoding of the fungal Internal Transcribed Spacer ribosomal RNA region to assess whether small-scale variation in the built environment influences the diversity, composition and structure of indoor air fungal communities between a heating and an unheated season. Passive dust collectors were used to collect airborne fungi from 259 dwellings representative of three major building periods and five building environments in one city-Lausanne (Vaud, Switzerland)-over a heating and an unheated period. A homogenous population (one or two people with an average age of 75 years) inhabited the households. Geographic information systems were used to assess detailed site characteristics (altitude, proximity to forest, fields and parks, proximity to the lake, and density of buildings and roads) for each building. Our analysis indicated that season was the factor that explained most of the variation in colonies forming unit (CFU) concentration and indoor mycobiome composition, followed by the period of building construction. Fungal assemblages were more diverse during the heating season than during the unheated season. Buildings with effective insulation had distinct mycobiome compositions from those built before 1975 - regardless of whether they were constructed with pre-1945 technology and materials or 1945 - 1974 ones. The urban landscape-as a whole-was a significant predictor of cultivable Penicillium load-the closer the building was to the lake, the higher the Penicillium load-but not of fungal community composition. Nevertheless, the relative abundance of eleven fungal taxa detected by metabarcoding decreased significantly with the urbanization gradient. When urban landscape descriptors were analyzed separately, the explanatory power of proximity to vegetation in shaping fungal assemblages become significant, indicating that land cover type had an influence on fungal community structure that was obscured by the effects of building age and sampling season. In conclusion, indoor mycobiomes are strongly modulated by season, and their assemblages are shaped by the effectiveness of building insulation, but are weakly influenced by the urban landscape.

Modelling functional landscape connectivity from genetic population structure: a new spatially explicit approach.

Functional connectivity between spatially disjoint habitat patches is a key factor for the persistence of species in fragmented landscapes. Modelling landscape connectivity to identify potential dispersal corridors requires information about those landscape features affecting dispersal. Here we present a new approach using spatial and genetic data of a highly fragmented population of capercaillie (Tetrao urogallus) in the Black Forest, Germany, to investigate effects of landscape structure on gene flow and to parameterize a spatially explicit corridor model for conservation purposes. Mantel tests and multiple regressions on distance matrices were employed to detect and quantify the effect of different landscape features on relatedness among individuals, while controlling for the effect of geographic distance. We extrapolated the results to an area-wide landscape permeability map and developed a new corridor model that incorporates stochasticity in simulating animal movement. The model was evaluated using both a partition of the data previously set apart and independent observation data of dispersing birds. Most land cover variables (such as coniferous forest, forest edges, agricultural land, roads, settlements) and one topographic variable (topographic exposure) were significantly correlated with gene flow. Although inter-individual relatedness inherently varies greatly and the variance explained by geographic distance and landscape structure was low, the permeability map and the corridor model significantly explained relatedness in the validation data and the spatial distribution of dispersing birds. Thus, landscape structure measurably affected within-population gene flow in the study area. By converting these effects into spatially explicit information our model enables localizing priority areas for the preservation or restoration of metapopulation connectivity.

Inferring recent migration rates from individual genotypes.

We present a novel and straightforward method for estimating recent migration rates between discrete populations using multilocus genotype data. The approach builds upon a two-step sampling design, where individual genotypes are sampled before and after dispersal. We develop a model that estimates all pairwise backwards migration rates (m(ij), the probability that an individual sampled in population i is a migrant from population j) between a set of populations. The method is validated with simulated data and compared with the methods of BayesAss and Structure. First, we use data for an island model and then we consider more realistic data simulations for a metapopulation of the greater white-toothed shrew (Crocidura russula). We show that the precision and bias of estimates primarily depend upon the proportion of individuals sampled in each population. Weak sampling designs may particularly affect the quality of the coverage provided by 95% highest posterior density intervals. We further show that it is relatively insensitive to the number of loci sampled and the overall strength of genetic structure. The method can easily be extended and makes fewer assumptions about the underlying demographic and genetic processes than currently available methods. It allows backwards migration rates to be estimated across a wide range of realistic conditions.

Mass effects mediate coexistence in competing shrews.

Recent developments in metacommunity theory have raised awareness that processes occurring at regional scales might interfere with local dynamics and affect conditions for the local coexistence of competing species. Four main paradigms are recognized in this context (namely, neutral, patch-dynamics, species-sorting, and mass-effect), which differ according to the role assigned to ecological or life-history differences among competing species, as well as to the relative time scale of regional vs. local dynamics. We investigated the patterns of regional and local coexistence of two species of shrews (Crocidura russula and Sorex coronatus) sharing a similar diet (generalist insectivores) over four generations, in a spatially structured habitat at the altitudinal limit of their distributions. Local populations were small, and regional dynamics were strong, with high rates of extinction and recolonization. Niche analysis revealed significant habitat differentiation on a few important variables, including temperature and availability of winter resting sites. In sites suitable for both species, we found instances of local coexistence with no evidence of competitive exclusion. Patterns of temporal succession did not differ from random, with no suggestion of a colonization-competition trade-off. Altogether, our data provide support for the mass-effect paradigm, where regional coexistence is mediated by specialization on different habitat types, and local coexistence by rescue effects from source sites. The strong regional dynamics and demographic stochasticity, together with high dispersal rates, presumably contributed to mass effects by overriding local differences in specific competitive abilities.

Hospital disaster preparedness in Switzerland.

STUDY OBJECTIVE: Hospital preparedness is an essential component of any developed health care system. However, there is no national legislation in Switzerland. The objective of this inquiry was to establish the geographic distribution, availability and characteristics of hospital preparedness across Switzerland. METHODS: A questionnaire regarding hospital preparedness in 2006 was addressed to all heads responsible for emergency departments (ED). The survey was initiated in 2007 and finalised in 2012. RESULTS: Of the 138 ED, 122 (88%) returned the survey. Eighty nine EDs (82%) had a disaster plan. CONCLUSIONS: Our study identified an insufficient rate of hospitals in which emergency physicians reported a disaster plan. The lack of national or cantonal legislation regulating disaster preparedness may be partially responsible for this.

State of Emergency Medicine in Switzerland: a national profile of emergency departments in 2006.

BACKGROUND: Emergency departments (EDs) are an essential component of any developed health care system. There is, however, no national description of EDs in Switzerland. Our objective was to establish the number and location of EDs, patient visits and flow, medical staff and organization, and capabilities in 2006, as a benchmark before emergency medicine became a subspecialty in Switzerland. METHODS: In 2007, we started to create an inventory of all hospital-based EDs with a preliminary list from the Swiss Society of Emergency and Rescue Medicine that was improved with input from ED physicians nationwide. EDs were eligible if they offered acute care 24 h per day, 7 days per week. Our goal was to have 2006 data from at least 80% of all EDs. The survey was initiated in 2007 and the 80% threshold reached in 2012. RESULTS: In 2006, Switzerland had a total of 138 hospital-based EDs. The number of ED visits was 1.475 million visits or 20 visits per 100 inhabitants. The median number of visits was 8,806 per year; 25% of EDs admitted 5,000 patients or less, 31% 5,001-10,000 patients, 26% 10,001-20,000 patients, and 17% >20,000 patients per year. Crowding was reported by 84% of EDs with >20,000 visits/year. Residents with limited experience provided care for 77% of visits. Imaging was not immediately available for all patients: standard X-ray within 15 min (70%), non-contrast head CT scan within 15 min (38%), and focused sonography for trauma (70%); 67% of EDs had an intensive care unit within the hospital, and 87% had an operating room always available. CONCLUSIONS: Swiss EDs were significant providers of health care in 2006. Crowding, physicians with limited experience, and the heterogeneity of emergency care capabilities were likely threats to the ubiquitous and consistent delivery of quality emergency care, particularly for time-sensitive conditions. Our survey establishes a benchmark to better understand future improvements in Swiss emergency care.

Modeling habitat suitability for complex species distributions by environmental-distance geometric mean.

This paper presents a new habitat suitability modeling method whose main properties are as follows: (1) It is based on the density of observation points in the environmental space, which enables it to fit complex distributions (e.g. nongaussian, bimodal, asymmetrical, etc.). (2) This density is modeled by computing the geometric mean to all observation points, which we show to be a good trade-off between goodness of fit and prediction power. (3) It does not need any absence information, which is generally difficult to collect and of dubious reliability. (4) The environmental space is represented either by an expert-selection of standardized variables or the axes of a factor analysis [in this paper we used the Ecological Niche Factor Analysis (ENFA)]. We first explain the details of the geometric mean algorithm and then we apply it to the bearded vulture (Gypaetus barbatus) habitat in the Swiss Alps. The results are compared to those obtained by the "median algorithm" and tested by jack-knife cross-validation. We also discuss other related algorithms (BIOCLIM, HABITAT, and DOMAIN). All these analyses were implemented into and performed with the ecology-oriented GIS software BIOMAPPER 2.0.The results show the geometric mean to perform better than the median algorithm, as it produces a tighter fit to the bimodal distribution of the bearded vulture in the environmental space. However, the "median algorithm" being quicker, it could be preferred when modeling more usual distribution.