Analysis of ammonia losses after field application of biogas slurries by an empirical model

Due to energy crises and stricter environmental regulations, renewable energy sources like bio‐methane produced by anaerobic digestion (biogas) become increasingly important. However, the application of slurries produced by biogas fermentation to agricultural land and subsequent ammonia emission may also create environmental risks to the atmosphere and to N‐limited ecosystems. Evaluating ammonia loss from agricultural land by model simulation is an important tool of agricultural‐systems analysis. The objective of this study was the systematical comparison of ammonia volatilization after application of two types of biogas slurries containing high amounts of energy crops in comparison with conventional animal slurries and to investigate the relative importance of factors affecting the emission process through an empirical model. A high number of ammonia‐loss field measurements were carried out in the years 2007/08 in biogas cropping systems in N Germany. The study consisted of simultaneous measurement of NH₃ losses from animal and biogas slurries in multiple‐plot field experiments with different N‐fertilization levels. The derived empirical model for the calculation of NH₃ losses based on explanatory variables gave good predictions of ammonia emission for both biogas and pig slurries. The root mean square error (RMSE) and mean bias error (MBE) of the empirical model for validation data were 2.19 kg N ha^–1 (rRMSE 29%) and –1.19 kg N ha^–1, respectively. Biogas slurries produced highest NH₃ emissions compared to the two animal slurries. In view of the explanatory variables included in the model, total NH$ _4^+ $ application rate, slurry type, temperature, precipitation, crop type, and leaf‐area index were important for ammonia‐volatilization losses.     

Levels of perfluorinated compounds in food and dietary intake of PFOS and PFOA in the Netherlands

This study presents concentrations of perfluorinated compounds in food and the dietary intake of perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) in The Netherlands. The concentrations of perfluorinated compounds in food were analyzed in pooled samples of foodstuffs randomly purchased in several Dutch retail store chains with nation-wide coverage. The concentrations analyzed for PFOS and PFOA were used to assess the exposure to these compounds in The Netherlands. As concentrations in drinking water in The Netherlands were missing for these compounds, conservative default concentrations of 7 pg/g for PFOS and 9 pg/g for PFOA, as reported by European Food Safety Authority, were used in the exposure assessment. In food, 6 out of 14 analyzed perfluorinated compounds could be quantified in the majority of the food categories (perfluoroheptanoic acid (PFHpA), PFOA, perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluoro-1-hexanesulfonate (PFHxS), and PFOS). The highest concentration of the sum of these six compounds was found in crustaceans (825 pg/g product, PFOS: 582 pg/g product) and in lean fish (481 pg/g product, PFOS: 308 pg/g product). Lower concentrations were found in beef, fatty fish, flour, butter, eggs, and cheese (concentrations between 20 and 100 pg/g product; PFOS, 29-82 pg/g product) and milk, pork, bakery products, chicken, vegetable, and industrial oils (concentration lower than 10 pg/g product; PFOS not detected). The median long-term intake for PFOS was 0.3 ng/kg bw/day and for PFOA 0.2 ng/kg bw/day. The corresponding high level intakes (99th percentile) were 0.6 and 0.5 ng/kg bw/day, respectively. These intakes were well below the tolerable daily intake values of both compounds (PFOS, 150 ng/kg bw/day; PFOA, 1500 ng/kg bw/day). The intake calculations quantified the contribution of drinking water to the PFOS and PFOA intake in The Netherlands. Important contributors of PFOA intake were vegetables/fruit and flour. Milk, beef, and lean fish were important contributors of PFOS intake.     

The role of movement restrictions and pre-emptive destruction in the emergency control strategy against CSF outbreaks in domestic pigs

Classical swine fever (CSF) outbreaks in domestic pig herds lead to the implementation of standard control measures according to legislative regulations. Ideal outbreak control entails the swift and efficient culling of all pigs on premises detected positive for CSF virus. Often all pig holdings around the detected cases are pre-emptively destroyed to exclude transmission into the neighbourhood. In addition to these measures, zones are defined in which surveillance and protection measures are intensified to prevent further distant disease spread. In particular, all movements are prohibited within standstill areas. Standstill also excludes the transport of fattened pigs to slaughter. Historical outbreaks provide evidence of the success of this control strategy. However, the extent to which the individual strategy elements contribute to this success is unknown. Therefore, we applied a spatially and temporally explicit epidemic model to the problem. Its rule-based formulation is tailored to a one-by-one model implementation of existing control concepts. Using a comparative model analysis the individual contributions of single measures to overall control success were revealed. From the results of the model we concluded that movement restrictions had the dominant impact on strategy performance suggesting a reversal of the current conceptual thinking. Additional measures such as pre-emptive culling only became relevant under imperfect compliance with movement restrictions. The importance of movement restrictions for the overall control success illustrates the need for explicit consideration of this measure when contingency strategies are being amended (e.g. emergency vaccination) and associated risks assessed.     

Evaluation of a radiosity based light model for greenhouse cucumber canopies

Light distribution is a key factor of developmental and growth processes, and strongly depends on the foliage distribution which is affected, e.g., by the arrangement of the plants in the canopy. The precise simulation of the light distribution on organ level is an essential component for dynamical plant models which incorporate structural and physiological adaptions of plants to their environment. Combinations of static 3D plant models with 3D light models are used for analyzing the complex light distribution on leaf level in silico, but detailed measurements for evaluation of simulation results are almost non-existent. This study addressed the evaluation of a model on a high level of detail using individual leaf based light measurements in canopies of cucumber (Cucumis sativus L.). We combined a static 3D plant model derived from digitized plants on an individual organ scale with a mock-up of the surrounding canopy and a 3D radiosity based light distribution model. Variations of plant density and spacing were analyzed to cover a range of canopy architectures. An exclusion of components of the light environment by applying a shading encasement followed by a successive uncovering allowed investigating the scene under increasing levels of complexity. The combined 3D plant-light distribution approach allowed determining the interaction of the light directions and the canopy architecture as well as differences in the accuracy of the simulations. Depending on canopy architecture and shading treatment, the light distributions covered a range from exponentially shaped vertical gradients in encased treatments to nearly flat light profiles in nonencased conditions. In conclusion, simulations of leaf level PAR based on combinations of detailed 3D surfaced-based plant and light distribution models are suitable to derive light-induced physiological responses on organ level.     

Towards Commercial Production of Sponge Medicines

Sponges can provide potential drugs against many major world-wide occurring diseases. Despite the high potential of sponge derived drugs no sustainable production method has been developed. Thus far it is not fully understood why, when, where and how these metabolites are produced in sponges. For the near future sea-based sponge culture seems to be the best production method. However, for controlled production in a defined system it is better to develop in vitro production methods, like in vitro sponge culture or even better sponge cell culture, culture methods for symbionts or the transfer of production routes into another host. We still have insufficient information about the background of metabolite production in sponges. Before production methods are developed we should first focus on factors that can induce metabolite production. This could be done in the natural habitat by studying the relation between stress factors (such as predation) and the production of bioactive metabolites. The location of production within the sponge should be identified in order to choose between sponge cell culture and symbiont culture. Alternatively the biosynthetic pathways could be introduced into hosts that can be cultured. For this the biosynthetic pathway of metabolite production should be unraveled, as well as the genes involved. This review discusses the current state of sponge metabolite production and the steps that need to be taken to develop commercial production techniques. The different possible production techniques are also discussed.     

Screening for Rift Valley fever infection in northern Somalia: a GIS based survey method to overcome the lack of sampling frame

Following repeated import bans imposed by Saudi Arabia on livestock originated from Somalia due to suspicion of Rift Valley fever (RVF) presence and the severe socio-economic consequences of this, it was imperative for the Somaliland government to carry out surveillance activities in order to determine the status of transboundary diseases in its territory. A GIS computer software (Arcview) was used to overcome the lack of lists of sampling sites due to the high mobility of pastoral nomadic herds in the study area. This method proved very convenient and flexible for the random selection of sampling sites and thus the compliance with the requirements by the World Organisation for Animal Health (OIE) for statistically valid methods if the surveillance outcome is to meet international recognition and acceptance. Screening in Somaliland in 2001 and in Puntland in 2003 which targeted mainly sheep and goats aged 1-2 years (97% of surveyed animals) revealed no signs compatible with the disease but an overall sero-prevalence of 2+/-0.02% (90/4570) and 5+/-0.3% (206/4050), respectively. The spatial distribution showed clusters of high sero-prevalence located mostly in the Nugal Valley. This trend was confirmed by the follow-up survey implemented in Somaliland in 2004 with a herd prevalence of 80+/-6% and a within-herd prevalence up to 50% located again in the Nugal Valley. This result suggests the maintenance and increase of RVF virus activity in the valley. In addition conditions favourable to the breeding and survival of the vector population and the high density of livestock make the Nugal Valley an area of high risk for a RVF outbreak where sentinel herds will be placed.     

Broad range 16S rRNA gene PCR compared to bacterial culture to confirm presumed synovial infection in horses

The objectives of the present study were to evaluate the accuracy of broad range 16S rRNA gene PCR compared to bacterial culture for the detection of synovial infection in horses. The study included 57 synovial fluid samples from horses with presumed synovial infection and a control group consisting of 31 synovial fluid samples originating from clinically normal horses and horses with aseptic synovial inflammation. All samples were analysed by 16S PCR with reverse line blot (RLB) hybridisation. Synovial fluid samples were cultured using conventional agar plate methods (APM) and/or blood culture medium (BCM). The results of the study showed a superior detection rate (89.5%) for 16S PCR with RLB. Bacterial culture had lower sensitivity, but highly acceptable detection rates (77.6%) were observed using BCM. APM had very low sensitivity (37.8%) and infection was never detected by plate isolation without positive incubation in BCM. The highest sensitivity (91.8%) for the detection of synovial infection was achieved when the results of incubation in BCM and 16S PCR were combined. For all the tests, the specificity was higher than 90%.     

Radar soundings of the subsurface of Mars

The martian subsurface has been probed to kilometer depths by the Mars Advanced Radar for Subsurface and Ionospheric Sounding instrument aboard the Mars Express orbiter. Signals penetrate the polar layered deposits, probably imaging the base of the deposits. Data from the northern lowlands of Chryse Planitia have revealed a shallowly buried quasi-circular structure about 250 kilometers in diameter that is interpreted to be an impact basin. In addition, a planar reflector associated with the basin structure may indicate the presence of a low-loss deposit that is more than 1 kilometer thick.     

Emerging viral zoonoses: frameworks for spatial and spatiotemporal risk assessment and resource planning

Spatial epidemiological tools are increasingly being applied to emerging viral zoonoses (EVZ), partly because of improving analytical methods and technologies for data capture and management, and partly because the demand is growing for more objective ways of allocating limited resources in the face of the emerging threat posed by these diseases. This review documents applications of geographical information systems (GIS), remote sensing (RS) and spatially-explicit statistical and mathematical models to epidemiological studies of EVZ.Landscape epidemiology uses statistical associations between environmental variables and diseases to study and predict their spatial distributions. Phylogeography augments epidemiological knowledge by studying the evolution of viral genetics through space and time. Cluster detection and early warning systems assist surveillance and can permit timely interventions. Advanced statistical models can accommodate spatial dependence present in epidemiological datasets and can permit assessment of uncertainties in disease data and predictions. Mathematical models are particularly useful for testing and comparing alternative control strategies, whereas spatial decision-support systems integrate a variety of spatial epidemiological tools to facilitate widespread dissemination and interpretation of disease data. Improved spatial data collection systems and greater practical application of spatial epidemiological tools should be applied in real-world scenarios.