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Özkan, S. (2015). The greenhouse gas emissions intensity of herds with mastitis (Vol. 5).
Abstract: Mastitis is an inflammatory disease of milking cows, causing production and economic losses in dairy farms. The main pathogens causing majority of the intramammary infections are Staphylococcus aureus, Streptococcus dysgalactiae, Escherichia coli and coagulase-negative Staphylococci. Here, we analysed the effect of mastitis on herd parameters such as milk yield, feed intake, replacement rate, gross margin and greenhouse gas emissions. The data were collected from the Norwegian Dairy Herd Recording System between 2010 and 2012. The farm data were recorded from 20 farms in Norway, based on health, fertility and breeding characteristics. SimHerd, a computer simulation model was used to estimate the impact of the observed levels of mastitis on herd parameters which were then fed into a whole farm model, HolosNor, to calculate the greenhouse gas emissions on the farm. The standard values provided in the SimHerd except for mastitis occurrence were applied in the scenario simulations. A further study is planned to parameterize each herd with specific herd characteristics in SimHerd so that herd specific estimates of the effect of mastitis on greenhouse gas emissions can be performed. No Label
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Doltra, J., Olesen, J. E., Báez, D., Louro, A., & Chirinda, N. (2015). Modeling nitrous oxide emissions from organic and conventional cereal-based cropping systems under different management, soil and climate factors. European Journal of Agronomy, 66, 8–20.
Abstract: Mitigation of greenhouse gas emissions from agriculture should be assessed across cropping systems and agroclimatic regions. In this study, we investigate the ability of the FASSET model to analyze differences in the magnitude of N2O emissions due to soil, climate and management factors in cereal-based cropping systems. Forage maize was grown in a conventional dairy system at Mabegondo (NW Spain) and wheat and barley in organic and conventional crop rotations at Foulum (NW Denmark). These two European sites represent agricultural areas with high and low to moderate emission levels, respectively. Field trials included plots with and without catch crops that were fertilized with either mineral N fertilizer, cattle slurry, pig slurry or digested manure. Non-fertilized treatments were also included. Measurements of N2O fluxes during the growing cycle of all the crops at both sites were performed with the static chamber method with more frequent measurements post-fertilization and biweekly measurements when high fluxes were not expected. All cropping systems were simulated with the FASSET version 2.5 simulation model. Cumulative soil seasonal N2O emissions were about ten-fold higher at Mabegondo than at Foulum when averaged across systems and treatments (8.99 and 0.71 kg N2O-N ha(-1), respectively). The average simulated cumulative soil N2O emissions were 9.03 and 1.71 kg N2O-N ha(-1) at Mabegondo and at Foulum, respectively. Fertilization, catch crops and cropping systems had lower influence on the seasonal soil N2O fluxes than the environmental factors. Overall, in its current version FASSET reproduced the effects of the different factors investigated on the cumulative seasonal soil N2O emissions but temporally it overestimated emissions from nitrification and denitrification on particular days when soil operations, ploughing or fertilization, took place. The errors associated with simulated daily soil N2O fluxes increased with the magnitude of the emissions. For resolving causes of differences in simulated and measured fluxes more intensive and temporally detailed measurements of N2O fluxes and soil C and N dynamics would be needed. (C) 2015 Elsevier B.V. All rights reserved.
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Quaranta, G. (2015). Model integration with economist perspectives (Vol. 6).
Abstract: Models integration and possible contrasts with up-scaling activities has received increasing attention in recent years especially with respect to the relationship between farm-economics and biophysical assessments. Current bio-economic models that analyse the trade-offs between farm income and interventions on eco-bio-environmental parameters such as maintenance of biodiversity, reduction of erosion and nitrate pollution and more, include static models. Agricultural systems are facing a series of threats, including climate change, land degradation, price volatility and intensification processes, which put their long-term sustainability into question. The University of Basilicata in collaboration with local representatives from various sectors of production in the Basilicata region of Southern Italy has developed an integrated study to define a model system to assess the dynamics at play in rural territories. The study tested the explanatory usefulness of resilience theory for the Basilicata agricultural social-ecological system, applying the adaptive cycle as a diagnostic tool to explore the dynamics and trajectories of change in the coupled social-ecological systems, and evaluating the performance of social, economic and social capitals, which are subject to the same dynamics. The use of dynamic analysis of the social, economic and natural capitals as the key to interpret the various phases of the adaptive cycle of the two agricultural systems proved a powerful tool in analysing the relationships between resilience and sustainable development in rural territories. The adoption of capitals and their inter-relations proved fundamental to the elaboration of adaptation strategies which were compatible with patterns of sustainability. The adaptive cycle heuristic, despite some methodological difficulties, remains useful to describe processes of change in rural socio-ecological systems. There could be enormous potential in adopting these instruments to help identify of the needs of different territories and help the framing and implementation of rural policies. No Label
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Kipling, R. (2015). Communicating Modelling (Vol. 4).
Abstract: No abstract. No Label
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Britz, W. (2015). Importance of considering crop management adaptation in CC impact studies: A Pan-European integrated assessment (Vol. 4).
Abstract: No abstract. No Label
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