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Mitter, H.; Techen, A.-K.; Sinabell, F.; Helming, K.; Kok, K.; Priess, J.A.; Schmid, E.; Bodirsky, B.L.; Holman, I.; Lehtonen, H.; Leip, A.; Le Mouel, C.; Mathijs, E.; Mehdi, B.; Michetti, M.; Mittenzwei, K.; Mora, O.; Oygarden, L.; Reidsma, P.; Schaldach, R.; Schoenhart, M. |
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Title |
A protocol to develop Shared Socio-economic Pathways for European agriculture |
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Journal Article |
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Year |
2019 |
Publication |
Journal of Environmental Management |
Abbreviated Journal |
J. Environ. Manage. |
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Volume  |
252 |
Issue |
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Pages |
Unsp 109701 |
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Keywords |
EUR-Agri-SSP; Consistent storylines; Narrative; Integrated assessment; Social environmental system; Climate change; land-use change; global environmental-change; climate-change; scenario; development; transdisciplinary research; sustainability science; integrated-assessment; future; adaptation; framework |
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Abstract |
Moving towards a more sustainable future requires concerted actions, particularly in the context of global climate change. Integrated assessments of agricultural systems (IAAS) are considered valuable tools to provide sound information for policy and decision-making. IAAS use storylines to define socio-economic and environmental framework assumptions. While a set of qualitative global storylines, known as the Shared Socio-economic Pathways (SSPs), is available to inform integrated assessments at large scales, their spatial resolution and scope is insufficient for regional studies in agriculture. We present a protocol to operationalize the development of Shared Socio-economic Pathways for European agriculture – Eur-Agri-SSPs- to support IAAS. The proposed design of the storyline development process is based on six quality criteria: plausibility, vertical and horizontal consistency, salience, legitimacy, richness and creativity. Trade-offs between these criteria may occur. The process is science-driven and iterative to enhance plausibility and horizontal consistency. A nested approach is suggested to link storylines across scales while maintaining vertical consistency. Plausibility, legitimacy, salience, richness and creativity shall be stimulated in a participatory and interdisciplinary storyline development process. The quality criteria and process design requirements are combined in the protocol to increase conceptual and methodological transparency. The protocol specifies nine working steps. For each step, suitable methods are proposed and the intended level and format of stakeholder engagement are discussed. A key methodological challenge is to link global SSPs with regional perspectives provided by the stakeholders, while maintaining vertical consistency and stakeholder buy-in. We conclude that the protocol facilitates systematic development and evaluation of storylines, which can be transferred to other regions, sectors and scales and supports intercomparisons of IAAS. |
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2020-02-14 |
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0301-4797 |
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TradeM, ft_macsur |
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MA @ admin @ |
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5222 |
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Author |
Sandor, R.; Ehrhardt, F.; Grace, P.; Recous, S.; Smith, P.; Snow, V.; Soussana, J.-F.; Basso, B.; Bhatia, A.; Brilli, L.; Doltra, J.; Dorich, C.D.; Doro, L.; Fitton, N.; Grant, B.; Harrison, M.T.; Kirschbaum, M.U.F.; Klumpp, K.; Laville, P.; Leonard, J.; Martin, R.; Massad, R.-S.; Moore, A.; Myrgiotis, V.; Pattey, E.; Rolinski, S.; Sharp, J.; Skiba, U.; Smith, W.; Wu, L.; Zhang, Q.; Bellocchi, G. |
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Title |
Ensemble modelling of carbon fluxes in grasslands and croplands |
Type |
Journal Article |
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Year |
2020 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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Volume |
252 |
Issue |
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Pages |
107791 |
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Keywords |
C fluxes; croplands; grasslands; multi-model ensemble; multi-model; median (mmm); soil organic-carbon; greenhouse-gas emissions; climate-change impacts; crop model; data aggregation; use efficiency; n2o emissions; maize; yield; wheat; productivity |
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Abstract |
Croplands and grasslands are agricultural systems that contribute to land–atmosphere exchanges of carbon (C). We evaluated and compared gross primary production (GPP), ecosystem respiration (RECO), net ecosystem exchange (NEE) of CO2, and two derived outputs – C use efficiency (CUE=-NEE/GPP) and C emission intensity (IntC= -NEE/Offtake [grazed or harvested biomass]). The outputs came from 23 models (11 crop-specific, eight grassland-specific, and four models covering both systems) at three cropping sites over several rotations with spring and winter cereals, soybean and rapeseed in Canada, France and India, and two temperate permanent grasslands in France and the United Kingdom. The models were run independently over multi-year simulation periods in five stages (S), either blind with no calibration and initialization data (S1), using historical management and climate for initialization (S2), calibrated against plant data (S3), plant and soil data together (S4), or with the addition of C and N fluxes (S5). Here, we provide a framework to address methodological uncertainties and contextualize results. Most of the models overestimated or underestimated the C fluxes observed during the growing seasons (or the whole years for grasslands), with substantial differences between models. For each simulated variable, changes in the multi-model median (MMM) from S1 to S5 was used as a descriptor of the ensemble performance. Overall, the greatest improvements (MMM approaching the mean of observations) were achieved at S3 or higher calibration stages. For instance, grassland GPP MMM was equal to 1632 g C m−2 yr-1 (S5) while the observed mean was equal to 1763 m-2 yr-1 (average for two sites). Nash-Sutcliffe modelling efficiency coefficients indicated that MMM outperformed individual models in 92.3 % of cases. Our study suggests a cautious use of large-scale, multi-model ensembles to estimate C fluxes in agricultural sites if some site-specific plant and soil observations are available for model calibration. The further development of crop/grassland ensemble modelling will hinge upon the interpretation of results in light of the way models represent the processes underlying C fluxes in complex agricultural systems (grassland and crop rotations including fallow periods). |
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2020-06-08 |
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LiveM |
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MA @ admin @ |
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5230 |
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Author |
Sanz-Cobena, A.; Misselbrook, T.H.; Hernaiz, P.; Vallejo, A. |
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Title |
Impact of rainfall to the effectiveness of pig slurry shallow injection method for NH3 mitigation in a Mediterranean soil |
Type |
Journal Article |
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Year |
2019 |
Publication |
Atmospheric Environment |
Abbreviated Journal |
Atm. Environ. |
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Volume |
216 |
Issue |
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Pages |
116913 |
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Keywords |
ammonia; micrometeorological method; slurry incorporation; trade-offs; nitrous oxide; mediterranean agroecosystems; nitrous-oxide emissions; field-applied manure; organic fertilizers; ammonia emissions; methane emissions; N2O emissions; animal manures; management; losses; grassland |
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Ammonia emission from fertilized cropping systems is an important concern for stakeholders, particularly in regions with high livestock densities producing large amounts of manure. Application of pig slurries can result in very large losses of N through NH3 volatilization, thus decreasing the N use efficiency (NUE) of the applied manure. Shallow incorporation has been shown to significantly abate these losses. In this field study, we assessed the impact of contrasting weather conditions on the effectiveness of shallow injection to abate NH3 emissions from pig slurry application to a Mediterranean soil. As potential trade-offs of NH3 abatement, greenhouse gas emissions were also measured under conditions of high soil moisture. Compared with surface application of slurry, shallow injection effectively and significantly decreased NH3 losses independently of weather conditions, but reductions of NH3 emission were greater after heavy rainfall. In contrast, under these conditions, shallow injection triggered higher emissions of N2O and CH4. Our findings reinforce the idea that any single-pollutant abatement strategy needs to be designed and assessed in a regional context and considering potential trade-offs in the form of other pollutants. |
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2020-06-08 |
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LiveM, ft_macsur |
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MA @ admin @ |
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5234 |
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Özkan Gülzari, Ş.; Vosough Ahmadi, B.; Stott, A.W. |
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Title |
Impact of subclinical mastitis on greenhouse gas emissions intensity and profitability of dairy cows in Norway |
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Journal Article |
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Year |
2018 |
Publication |
Preventive Veterinary Medicine |
Abbreviated Journal |
Preventive Veterinary Medicine |
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Volume |
150 |
Issue |
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Pages |
19-29 |
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Keywords |
Dairy cow; Dynamic programming; Greenhouse gas emissions intensity; Profitability; Subclinical mastitis; Whole farm modelling |
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Abstract |
Impaired animal health causes both productivity and profitability losses on dairy farms, resulting in inefficient use of inputs and increase in greenhouse gas (GHG) emissions produced per unit of product (i.e. emissions intensity). Here, we used subclinical mastitis as an exemplar to benchmark alternative scenarios against an economic optimum and adjusted herd structure to estimate the GHG emissions intensity associated with varying levels of disease. Five levels of somatic cell count (SCC) classes were considered namely 50,000 (i.e. SCC50), 200,000, 400,000, 600,000 and 800,000 cells/mL (milliliter) of milk. The effects of varying levels of SCC on milk yield reduction and consequential milk price penalties were used in a dynamic programming (DP) model that maximizes the profit per cow, represented as expected net present value, by choosing optimal animal replacement rates. The GHG emissions intensities associated with different levels of SCC were then computed using a farm-scale model (HolosNor). The total culling rates of both primiparous (PP) and multiparous (MP) cows for the five levels of SCC scenarios estimated by the model varied from a minimum of 30.9% to a maximum of 43.7%. The expected profit was the highest for cows with SCC200 due to declining margin over feed, which influenced the DP model to cull and replace more animals and generate higher profit under this scenario compared to SCC50. The GHG emission intensities for the PP and MP cows with SCC50 were 1.01 kg (kilogram) and 0.95 kg carbon dioxide equivalents (CO2e) per kg fat and protein corrected milk (FPCM), respectively, with the lowest emissions being achieved in SCC50. Our results show that there is a potential to reduce the farm GHG emissions intensity by 3.7% if the milk production was improved through reducing the level of SCC to 50,000 cells/mL in relation to SCC level 800,000 cells/mL. It was concluded that preventing and/or controlling subclinical mastitis consequently reduces the GHG emissions per unit of product on farm that results in improved profits for the farmers through reductions in milk losses, optimum culling rate and reduced feed and other variable costs. We suggest that further studies exploring the impact of a combination of diseases on emissions intensity are warranted. |
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0167-5877 |
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LiveM, ft_macsur |
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MA @ admin @ |
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5181 |
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Milford, A.B.; Le Mouel, C.; Bodirsky, B.L.; Rolinski, S. |
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Title |
Drivers of meat consumption |
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Journal Article |
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Year |
2019 |
Publication |
Appetite |
Abbreviated Journal |
Appetite |
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Volume |
141 |
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Unsp 104313 |
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Keywords |
Meat consumption; Nutrition transition; Climate change mitigation; Cross-country analysis; nutrition transition; food; sustainability; globalization; countries; future; health; income; price |
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Abstract |
Increasing global levels of meat consumption are a threat to the environment and to human health. To identify measures that may change consumption patterns towards more plant-based foods, it is necessary to improve our understanding of the causes behind the demand for meat. In this paper we use data from 137 different countries to identify and assess factors that influence meat consumption at the national level using a cross-country multivariate regression analysis. We specify either total meat or ruminant meat as the dependent variable and we consider a broad range of potential drivers of meat consumption. The combination of explanatory variables we use is new for this type of analysis. In addition, we estimate the relative importance of the different drivers. We find that income per capita followed by rate of urbanisation are the two most important drivers of total meat consumption per capita. Income per capita and natural endowment factors are major drivers of ruminant meat consumption per capita. Other drivers are Western culture, Muslim religion, female labour participation, economic and social globalisation and meat prices. The main identified drivers of meat demand are difficult to influence through direct policy intervention. Thus, acting indirectly on consumers’ preferences and consumption habits (for instance through information, education policy and increased availability of ready-made plant based products) could be of key importance for mitigating the rise of meat consumption per capita all over the world. |
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2020-02-14 |
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0195-6663 |
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TradeM, ft_macsur |
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MA @ admin @ |
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5224 |
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