A Community-Level, Mesoscale Analysis of Fish Assemblage Structure in Shoreline Habitats of a Large River Using Multivariate Regression Trees.

The mesoscale (100–102 m) of river habitats has been identified as the scale that simultaneously offers insights into ecological structure and falls within the practical bounds of river management. Mesoscale habitat (mesohabitat) classifications for relatively large rivers, however, are underdeveloped compared with those produced for smaller streams. Approaches to habitat modelling have traditionally focused on individual species or proceeded on a species-by-species basis. This is particularly problematic in larger rivers where the effects of biological interactions are more complex and intense. Community-level approaches can rapidly model many species simultaneously, thereby integrating the effects of biological interactions while providing information on the relative importance of environmental variables in structuring the community. One such community-level approach, multivariate regression trees, was applied in order to determine the relative influences of abiotic factors on fish assemblages within shoreline mesohabitats of San Pedro River, Chile, and to define reference communities prior to the planned construction of a hydroelectric power plant. Flow depth, bank materials and the availability of riparian and instream cover, including woody debris, were the main variables driving differences between the assemblages. Species strongly indicative of distinctive mesohabitat types included the endemic Galaxias platei. Among other outcomes, the results provide information on the impact of non-native salmonids on river-dwelling Galaxias platei, suggesting a degree of habitat segregation between these taxa based on flow depth. The results support the use of the mesohabitat concept in large, relatively pristine river systems, and they represent a basis for assessing the impact of any future hydroelectric power plant construction and operation. By combing community classifications with simple sets of environmental rules, the multivariate regression trees produced can be used to predict the community structure of any mesohabitat along the reach.

Atmospheric Concentrations of Alternaria, Cladosporium, Ganoderma and Didymella Spores Monitored in Cork (Ireland) and Worcester (England) During the Summer of 2010

This study represents the first international intercomparison of fungal spore observations since 1990, focusing on atmospheric concentrations of Alternaria, Cladosporium, Ganoderma and Didymella spores. The campaigns were performed at sites located in Cork (Ireland) and Worcester (England) during summer 2010. Observations were made using Hirst-type volumetric spore traps and corresponding optical identification at the genus level by microscope. The measurements at both sites (including meteorological parameters) were compared and contrasted. The relationships between the fungal spore concentrations with selected meteorological parameters were investigated using statistical methods and multivariate regression trees (MRT). The results showed high correlations between the two sites with respect to daily variations. Statistically significant higher spore concentrations for Alternaria, Cladosporium and Ganoderma were monitored at the Worcester site. This result was most likely due to the differences in precipitation and local fungal spore sources at the two sites. Alternaria and Cladosporium reached their maxima a month earlier in Cork than in Worcester, and Didymella with Ganoderma peaked simultaneously with similar diurnal trends found for all the investigated spore types. MRT analysis helped to determine threshold values of the meteorological parameters that exerted most influence on the presence of spores: they were found to vary at the two sites. Our results suggest that the aeromycological profile is quite uniform over the British Isles, but a description of bioaerosols with respect to overall load and daily concentration can be quite diverse although the geographical difference between sites is relatively small. These variations in the concentrations therefore need to be explored at the national level

Forecasting Methodologies for Ganoderma Spore Concentration Using Combined Statistical Approaches and Model Evaluations

High concentration levels of Ganoderma spp. spores were observed in Worcester, UK, during 2006–2010.These basidiospores are known to cause sensitization due to the allergen content and their small dimensions. This enables them to penetrate the lower part of the respiratory tract in humans. Establishment of a link between occurring symptoms of sensitization to Ganoderma spp. and other basidiospores is challenging due to lack of information regarding spore concentration in the air. Hence, aerobiological monitoring should be conducted, and if possible extended with the construction of forecast models. Daily mean concentration of allergenic Ganoderma spp. spores in the atmosphere of Worcester was measured using 7-day volumetric spore sampler through five consecutive years. The relationships between the presence of spores in the air and the weather parameters were examined. Forecast models were constructed for Ganoderma spp. spores using advanced statistical techniques, i.e. multivariate regression trees and artificial neural networks. Dew point temperature along with maximumtemperature was the most important factor influencing the presence of spores in the air of Worcester. Based on these two major factors and several others of lesser importance, thresholds for certain levels of fungal spore concentration, i.e. low (0–49 s m−3), moderate(50–99 s m−3), high (100–149 s m−3) and very high (150and predicted values varied from rs=0.57 to rs=0.68).