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Kipling, R.P.; Saetnan, E.R.; Van den Pol-van Dasselaar, A.; Scollan, N.G. |
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Title |
Building modelling capacity for livestock systems: progress in LiveM |
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Conference Article |
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2014 |
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MACSUR provides an opportunity to connect disparate research groups and disciplines in livestock and grassland modelling. Within the livestock theme (LiveM) of MACSUR, grassland modelling capabilities have been significantly improved through joint modelling exercises, and grassland modellers have exploited their methodological overlaps with CropM to make important contributions to regional pilot studies. Animal health researchers have been contributing to the southern regional pilot, and modelling resources have been identified for livestock systems at the animal and farm-scales. Here, the priorities for the next steps for livestock and grassland modelling are discussed, and for the role of MACSUR in addressing the challenges facing the sector. While crop and grassland modelling deals with primary production, livestock modelling examines the complexity of secondary production. The unique position of livestock modelling presents challenges and opportunities. The diversity of livestock models (in scale and approach) makes model inter-comparisons and collaborative work challenging, while the range of variables involved in livestock systems provide many opportunities for increasing systemic efficiency and robustness to the impacts of climate change. Closer integration of experimental research and modelling teams also has the potential to increase the capability of livestock and grassland models to predict the impact of European adaptation strategies on livestock farming systems, and on the contribution of these systems to global food security. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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no |
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MA @ admin @ |
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5058 |
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Author |
Wolf, P.; Holz, K. |
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Title |
LandPaKT |
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Conference Article |
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2014 |
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LandPaKT (agricultural techniques: potentials and costs of greenhouse gas mitigation) is a joint project of the Leibniz Institute for Agricultural Engineering (ATB) and the Agricultural-Horticultural Faculty of the Humboldt University Berlin. Within the established graduate school LandPaKT, seven PhD students analyse the mitigation potentials and costs of greenhouse gas emissions systematically and merge them at the farm level. With the re-wetting of organic soils, the carbon sequestration in mineral soils depending on agricultural activities and the livestock husbandry, the most important sectors of agriculture are included in the analyses. With modelling and simulation approaches, single as well as combined measures are analysed with regard to their overall effect. Recommendations for the most-promising measures at farm level are deduced. Based on a farm model for water-use efficiency, developed within another ATB project (AgroHyd), LandPaKT aims to expand the model by greenhouse gas emissions. The graduate school started in May 2013.The increase of the global human population with the resulting increase in food demand accompanied by changed consumption patterns urgently calls for the exploitation of mitigation options in animal husbandry. Based on the Life Cycle Assessment (LCA) approach, methodological recommendations for carbon footprint analyses for dairy farming will be developed. Furthermore, the influence of different feeds and feeding strategies on greenhouse gas emission from dairy farming will be investigated. |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5095 |
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Popp, A.; Humpenöder, F.; Weindl, I.; Bodirsky, B.L.; Bonsch, M.; Lotze-Campen, H.; Müller, C.; Biewald, A.; Rolinski, S.; Stevanovic, M.; Dietrich, J.P. |
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Title |
Land-use protection for climate change mitigation |
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Journal Article |
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2014 |
Publication |
Nature Climate Change |
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Nat. Clim. Change |
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4 |
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12 |
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1095-1098 |
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avoided deforestation; forest conservation; carbon emissions; co2 emissions; productivity; scarcity; stocks; redd |
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Abstract |
Land-use change, mainly the conversion of tropical forests to agricultural land, is a massive source of carbon emissions and contributes substantially to global warming(1-3). Therefore, mechanisms that aim to reduce carbon emissions from deforestation are widely discussed, A central challenge is the avoidance of international carbon leakage if forest conservation is not implemented globally’’, Here, We show that forest conservation schemes, even if implemented globally, could lead to another type of carbon leakage by driving cropland expansion in non-forested areas that are not subject to forest conservation schemes (non-forest leakage). These areas have a smaller. but still considerable potential to store carbon(5,6). We show that a global forest policy could reduce carbon emissions by 77 Gt CO2, but would still allow for decreases in carbon stocks of non-forest land by 96 Gt CO2, until 2100 due to non-forest leakage effects. Furthermore; abandonment of agricultural hand and associated carbon uptake through vegetation regrowth is hampered. Effective mitigation measures thus require financing structures and conservation investments that cover the full range of carbon-rich ecosystems. However, our analysis indicates that greater agricultural productivity increases would be needed to compensate for such restrictions on agricultural expansion. |
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English |
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1758-678x 1758-6798 |
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CropM, LiveM, TradeM |
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Call Number |
MA @ admin @ |
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4540 |
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Author |
Mansouri, M.; Dumont, B.; Leemans, V.; Destain, M.-F. |
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Title |
Bayesian methods for predicting LAI and soil water content |
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Journal Article |
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2014 |
Publication |
Precision Agriculture |
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Precision Agric. |
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15 |
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2 |
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184-201 |
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crop model; bayes; data assimilation; extended kalman filtering; particle filtering; variational filtering; leaf-area index; parameter-estimation; crop models; moisture; instruments; management; sensors; state |
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LAI of winter wheat (Triticum aestivum L.) and soil water content of the topsoil (200 mm) and of the subsoil (500 mm) were considered as state variables of a dynamic soil-crop system. This system was assumed to progress according to a Bayesian probabilistic state space model, in which real values of LAI and soil water content were daily introduced in order to correct the model trajectory and reach better future evolution. The chosen crop model was mini STICS which can reduce the computing and execution times while ensuring the robustness of data processing and estimation. To predict simultaneously state variables and model parameters in this non-linear environment, three techniques were used: extended Kalman filtering (EKF), particle filtering (PF), and variational filtering (VF). The significantly improved performance of the VF method when compared to EKF and PF is demonstrated. The variational filter has a low computational complexity and the convergence speed of states and parameters estimation can be adjusted independently. Detailed case studies demonstrated that the root mean square error of the three estimated states (LAI and soil water content of two soil layers) was smaller and that the convergence of all considered parameters was ensured when using VF. Assimilating measurements in a crop model allows accurate prediction of LAI and soil water content at a local scale. As these biophysical properties are key parameters in the crop-plant system characterization, the system has the potential to be used in precision farming to aid farmers and decision makers in developing strategies for site-specific management of inputs, such as fertilizers and water irrigation. |
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English |
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1385-2256 |
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Notes |
CropM, ftnotmacsur |
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Call Number |
MA @ admin @ |
Serial |
4629 |
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Author |
Kipling, R.P.; Scollan, N.G. |
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Title |
Livestock production and the feed challenge |
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Conference Article |
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Year |
2014 |
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It is predicted that world population will reach nine billion by 2050 (Godfray et al., 2010) with the biggest increases occurring in the developing world (Guyomard et al., 2013, Thornton, 2010). This growth is expected to dramatically increase the demand for meat and animal products (Tilman et al., 2002) with a requirement by 2050 for 73 % more meat and 58 % more milk than produced in 2010 (FAO, 2011). In order to meet this growing demand, the supply of livestock products must rise to an extent comparable with that of the ‘Green Revolution’ (Tilman et al., 2002). This must occur in the context of serious global challenges related to climate change, resource availability, inequality, and biodiversity loss. At present many European livestock production systems are heavily reliant on a small number of feed products to provide protein, with imported soya accounting for 55 % of the 2.6 million tonnes of plant-derived protein fed to animals in the UK. This reliance on a small number of imported products leaves supply vulnerable to economic and climatic change. There is increased research into alternatives to South American soybean in the European feed supply chain, including improving the nutritional and agronomic characteristics of such alternatives, and exploring the use of new sources of potential feed material. This presents an opportunity for collaboration between experimental researchers and modellers to investigate the potential impacts of alternative feeds on livestock system productivity, robustness to climate change and levels of GHG emissions. |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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Series Volume |
3(S) Sassari, Italy |
Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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Notes |
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Approved |
no |
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Call Number |
MA @ admin @ |
Serial |
5098 |
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