Volatile fatty acid evolution in biomass mixture composts prepared in open and closed bioreactors

In this study we observed the production of volatile fatty acids (VFAs) during the composting process of compost heaps in two different bioreactors (open and closed) at three different depths (0, 40 and 80 cm). The compost was prepared as a mixture of bio-waste, horse manure, grass and sawdust to ensure sufficient pH conditions in compost heaps. VFA contents in the composting materials were analysed weekly over 14–119 d. The degradation process was monitored, along with temperature, pH, total organic carbon, oxidizable carbon and mono- and oligosaccharides. VFA contents were evaluated with regard to the depth of the sample site in the compost heap and to conditions in the bioreactors. The maximum VFA occurrence was observed during the first 35 d; acetic and propionic acids in particular were determined to occur in each sample. Considerable variations in their formation and elimination were observed in the two bioreactors as well as at the various depths in the compost heaps. Significant correlations were found between individual VFAs, as well as between VFA concentrations and organic carbon contents.     

Afforestation Planning and Biodiversity Conservation: Predicting Effects on Habitat Functionality in Lithuania

Habitat re-creation is one of the multiple faces of biodiversity restoration and encompasses the attempts to reconstruct an ecosystem on severely disturbed sites with little left to restore. Afforestation of abandoned or marginal agricultural land is an important tool for the re-creation of forest ecosystems and re-establishment of functional habitat networks for the maintenance of biodiversity. This study was performed in the context of the Danish-Lithuanian project ‘Afforestation of abandoned agricultural land based on sustainable land use planning and environmentally sound forest management’. The study assessed how habitat re-creation as designed in alternative afforestation plans for two administrative regions in Lithuania will affect the functionality of the landscapes for bird species of conservation concern. Spatial analysis of the forest cover was performed under existing and proposed conditions using general landscape ecological principles concerning core and edge habitats as well as nearest-neighbour metrics. The results show that the use of general criteria may result in proportionally negative changes in the availability of some forest habitats relative to changes in total forest cover, thus leading to less significant improvements in the habitats of many naturally occurring (and even protected) species compared to what would be expected from changes in forest cover alone. To solve this dilemma it is suggested that the requirements of focal species and quantitative conservation objectives should be considered in a spatially explicit – each main forest type. It is concluded that to ensure functionality of habitat networks, knowledge and experience from the fields of landscape ecology and conservation biology should be more commonly incorporated into afforestation planning.     

Modelling the outcrossing between genetically modified and conventional maize with equation discovery

Many studies explore the feasibility of co-existence between genetically modified (GM) and conventional (non-GM) crops. An important research topic in these studies is the process of outcrossing, i.e., the process of gene flow via pollen flow from GM to non-GM crops. In this paper, we address a new modelling approach to define the environmentally driven processes of outcrossing for maize from existing empirical datasets. In particular, we use equation discovery methodology that combines background knowledge and empirical data from several studies. We induce models that predict the degree of outcrossing rate between the donor (GM) and the recipient (non-GM) maize field from the distance between the fields and the local wind characteristics (speed, direction and duration). This results in highly accurate models, for which both variables (distance and wind) are essential and of roughly equal importance.     

A GIS-based approach to spatio-temporal analysis of environmental pollution in urban areas: A case study of Prague's environment extended by LIDAR data

Environmental pollution of urban areas is one of key factors that state authorities and local agencies have to consider in the decision-making process. To find a compromise among many criteria, spatial analysis extended by geostatistical methods and dynamic models has to be carried out. In this case, spatial analysis includes processing of a wide range of air, water and soil pollution data and possibly noise assessment and waste management data. Other spatial inputs consist of data from remote sensing and GPS field measurements. Integration and spatial data management are carried out within the framework of a geographic information system (GIS). From a modeling point of view, GIS is used mainly for the preprocessing and postprocessing of data to be displayed in digital map layers and visualized in 3D scenes. Moreover, for preprocessing and postprocessing, deterministic and geostatistical methods (IDW, ordinary kriging) are used for spatial interpolation; geoprocessing and raster algebra are used in multi-criteria evaluation and risk assessment methods. GIS is also used as a platform for spatio-temporal analyses or for building relationships between the GIS database and stand-alone modeling tools. A case study is presented illustrating the application of spatial analysis to the urban areas of Prague. This involved incorporating environmental data from monitoring networks and field measurements into digital map layers. Extra data inputs were used to represent the 3D concentration fields of air pollutants (ozone, NO₂) measured by differential absorption LIDAR. ArcGIS was used to provide spatial data management and analysis, extended by modeling tools developed internally in the ArcObjects environment and external modules developed with MapObjects. Ordinary kriging methods were employed to predict ozone concentrations in selected 3D locations together with estimates of variability. Higher ozone concentrations were found above crossroads with their heavy traffic than above the surrounding areas. Ozone concentrations also varied with height above the digital elevation model. Processed data, spatial analysis and models are integrated within the framework of the GIS project, providing an approach that state and local authorities can use to address environmental protection issues.