Induction of porcine post-weaning multisystemic wasting syndrome (PMWS) in pigs from PMWS unaffected herds following mingling with pigs from PMWS-affected herds

In this paper we present the results from two experimental studies (I and II) investigating whether post-weaning multisystemic wasting syndrome (PMWS) can be induced in pigs from PMWS unaffected herds by mingling with pigs from PMWS-affected herds and to observe whether transportation and/or mingling of healthy pigs from unaffected herds could induce PMWS.The studies comprised pigs from 12 different herds. Eight herds had PMWS while four were unaffected. All 12 herds were found to be infected with PCV2. Pigs from PMWS-affected herds were mingled with pigs from unaffected herds in four separate compartments in both study I and study II. In addition, in study II, four groups of pigs from unaffected herds were included. Two groups with pigs transported and mingled from unaffected herds and two groups with pigs which were only transported. The PMWS diagnoses on the individual pigs were based on lymphoid depletion, histiocytic proliferation and the presence of giant cells or inclusion bodies together with the demonstration of PCV2 in lymphoid tissue.Healthy pigs, in both studies, developed PMWS 4–5 weeks after mingling with pigs clinically affected with PMWS. None of the pigs from unaffected herds which had no contact with pigs from PMWS-affected herds developed clinical signs of PMWS. Transportation and mingling of pigs from PMWS unaffected herds in combination or alone was insufficient to provoke PMWS.     

Remote sensing and forest inventories in Nordic countries – roadmap for the future

The Nordic countries have long traditions in forest inventory and remote sensing (RS). In sample-based national forest inventories (NFIs), utilization of aerial photographs started during the 1960s, satellite images during the 1980s, laser scanning during the 2000s, and photogrammetric point clouds during the 2010s. In forest management inventories (FMI), utilization of aerial photos started during the 1940s and laser scanning during the 2000s. However, so far, RS has mostly been used for map production and research rather than for estimation of regional parameters or inference on their accuracy. In recent years, the RS technology has been developing very fast. At the same time, the needs for information are constantly increasing. New technologies have created possibilities for cost-efficient production of accurate, large area forest data sets, which also will change the way forest inventories are done in the future. In this study, we analyse the state-of-the-art both in the NFIs and FMIs in the Nordic countries. We identify the benefits and drawbacks of different RS materials and data acquisition approaches with different user perspectives. Based on the analysis, we identify the needs for further development and emerging research questions. We also discuss alternatives for ownership of the data and cost-sharing between different actors in the field.     

Finding the appropriate level of complexity for a simulation model: An example with a forest growth model

The topic of model complexity is fundamental to model developers and model users. In this study, we investigate how over- and under-fitting of a driving function in a simulation model influences the predictive ability of the model. Secondly, we investigate whether model selection approaches succeed in selecting driving functions with the best predictive ability. We address these issues through an example with the forest simulator SORTIE-ND. Utilizing maximum likelihood methods and individual tree growth data we parameterize five growth functions of increasing complexity. We then incorporate each growth function into the simulation model SORTIE-ND and test predicted growth against independent data. Compared to the independent data, the simplest and the most complex growth functions had the poorest predictive ability while functions of intermediate complexity had the best predictive ability. The poor predictive ability of the simplest model is caused by poor approximation of the system while the poor predictive ability of the most complex model is caused by biased parameter estimates. A growth function of intermediate complexity was the most parsimonious model where error due to approximation and error due to estimation were simultaneously minimized. The model selection criteria AIC and BIC were found to select complex functions that were over-fitted according to the independent data comparison. BIC was closer to choosing the model that minimized prediction error than AIC. In this example, BIC is the more appropriate model selection criterion. It is important that both model developers and models users remember that more complex models do not always result in better predictive models.     

Genetic data from avian influenza and avian paramyxoviruses generated by the European network of excellence (EPIZONE) between 2006 and 2011--review and recommendations for surveillance

Since 2006, the members of the molecular epidemiological working group of the European "EPIZONE" network of excellence have been generating sequence data on avian influenza and avian paramyxoviruses from both European and African sources in an attempt to more fully understand the circulation and impact of these viruses. This review presents a timely update on the epidemiological situation of these viruses based on sequence data generated during the lifetime of this project in addition to data produced by other groups during the same period. Based on this information and putting it all into a European context, recommendations for continued surveillance of these important viruses within Europe are presented.     

Airborne transmission of foot-and-mouth disease virus from Burnside Farm,Heddon-on-the-Wall,Northumberland, during the 2001 epidemic in the United Kingdom

The results of a detailed assessment of the atmospheric conditions when foot-and-mouth disease (FMD) virus was released from Burnside Farm, Heddon-on-the-Wall, Northumberland at the start of the 2001 epidemic in the UK are consistent with the hypothesis that the disease was spread to seven of the 12 farms in the immediate vicinity of the source by airborne virus, and airborne infection could not be ruled out for three other premises; the remaining two premises were unlikely to have been infected by airborne virus. The distances involved ranged from less than 1 km up to 9 km. One of the farms which was most probably infected by airborne virus from Burnside Farm was Prestwick Hall Farm, which is believed to have been key to the rapid spread of the disease throughout the country. In contrast, the results of detailed atmospheric modelling, based on a combination of clinical evidence from the field and laboratory experiments have shown that by assuming a relationship between the 24-hour average virus concentrations and subsequent infection, threshold infection levels were seldom reached at the farms close to Burnside Farm. However, significant short-term fluctuations in the concentration of virus can occur, and short-lived high concentrations may have increased the probability of infection and explain this discrepancy.     

Rooting of chrysanthemum cuttings. Influence of irradiance during stock plant growth and of decapitation and disbudding of cuttings

Stock plants of Chrysanthemum morifolium Ramat. cultivar ‘Improved Mefo’ were grown in a controlled-environment room at different levels of irradiance (9, 23, 53 or 90 W m^?2). After 3 weeks, cuttings were excised and rooted for 3 weeks at an irradiance of 16 W m^?2. Cuttings from stock plants grown at the highest irradiance had the highest number of roots, while cuttings from the lowest irradiance had the lowest number of roots.The importance of the presence of shoot meristems for root formation was investigated through disbudding and decapitation at different times after the excision of the cuttings. Removing the buds on the day of excision had no effect on the number of roots formed, while the removal of the buds on day 2 to day 5 after excision had a promotive effect. Removal later than 7 days after excision had no effect at all.The results are discussed from the point of view that an interaction between nutritional and hormonal factors regulates the process of root formation.     

IPM Strategies and Their Dilemmas Including an Introduction to www. eurowheat.org

Information about disease management in winter wheat （Triticum aestiva） in eight European countries was collated and analysed by scientists and extension workers within the European Network for the Durable Exploitation of Crop Protection Strategies （ENDURE）. This included information about specific disease thresholds, decision support systems, host varieties, disease prevalence and pathogen virulence. Major differences in disease prevalence and economic importance were observed. Septoria tritici blotch （Mycosphaerella graminicola） was recognized as the most yield reducing disease in countries with intensive wheat production, but also rust diseases （Puccinia striiformis and Puccinia triticina）, powdery mildew （Blumeria graminis） and Fusarium head blight （Fusarium spp.） were seen as serious disease problems. Examples of current integrated pest management （IPM） strategies in different countries have been reported. Disease management and fungicide use patterns showed major differences, with an average input equivalent to 2.3 full dose rates （TFI） in the UK and a TFI of 0.6 in Denmark. These differences are most likely due to a combination of different cropping systems, climatic differences, disease prevalence, and socio-economic factors. The web based information platform www.eurowheat.org was used for dissemination of information and results including information on control thresholds, cultural practices which can influence disease attack, fungicide efficacy, fungicide resistance, and pathogen virulence, which are all elements supporting 1PM for disease control in wheat. The platform is open to all users. The target groups of EuroWheat information are researchers, advisors, breeders, and similar partners dealing with disease management in wheat.     

Functions for estimating aboveground biomass of birch in Norway

A suite of regional allometric aboveground biomass functions were derived for Betula pubescens and Betula pendula for Norwegian conditions. The data consisted of 67 trees sampled throughout Norway. A total of 14 component functions were developed for total aboveground, total stem, stemwood, stem bark, live crown, live branch, leaf, and dead branch biomass using combinations of diameter at breast height and height as predictor variables. Application of the derived functions to existing local southern Norwegian mountain birch and regional Swedish biomass datasets indicated an overall good predictive ability of the developed functions. However, the functions produced slight underestimates, suggesting that the respective birch populations had differing biomass allocation patterns. When the developed functions were applied to Norwegian National Forest Inventory data, they produced slightly higher biomass stock and stock change estimates than what is obtained using existing Swedish functions. The higher estimates were evident in the north, central, and western part of Norway, while estimates were similar in southeastern Norway where growing conditions are most similar to Swedish conditions. The analysis indicates that the derived functions are the best available for regional birch biomass stock and stock change estimation in Norway.