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Author |
Hutchings, N.J.; Özkan Gülzari, Ş.; de Haan, M.; Sandars, D. |
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Title |
How do farm models compare when estimating greenhouse gas emissions from dairy cattle production |
Type |
Journal Article |
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Year |
2018 |
Publication |
Animal |
Abbreviated Journal |
Animal |
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Volume  |
12 |
Issue |
10 |
Pages |
2171-2180 |
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Keywords |
dairy cattle; farm-scale; model; greenhouse gas; Future Climate Scenarios; Systems-Analysis; Milk-Production; Crop; Production; Mitigation; Intensity; Impacts |
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Abstract |
The European Union Effort Sharing Regulation (ESR) will require a 30% reduction in greenhouse gas (GHG) emissions by 2030 compared with 2005 from the sectors not included in the European Emissions Trading Scheme, including agriculture. This will require the estimation of current and future emissions from agriculture, including dairy cattle production systems. Using a farm-scale model as part of a Tier 3 method for farm to national scales provides a more holistic and informative approach than IPCC (2006) Tier 2 but requires independent quality control. Comparing the results of using models to simulate a range of scenarios that explore an appropriate range of biophysical and management situations can support this process by providing a framework for placing model results in context. To assess the variation between models and the process of understanding differences, estimates of GHG emissions from four farm-scale models (DailyWise, FarmAC, HolosNor and SFARMMOD) were calculated for eight dairy farming scenarios within a factorial design consisting of two climates (cool/dry and warm/wet) x two soil types (sandy and clayey) x two feeding systems (grass only and grass/maize). The milk yield per cow, follower cow ratio, manure management system, nitrogen (N) fertilisation and land area were standardised for all scenarios in order to associate the differences in the results with the model structure and function. Potential yield and application of available N in fertiliser and manure were specified separately for grass and maize. Significant differences between models were found in GHG emissions at the farm-scale and for most contributory sources, although there was no difference in the ranking of source magnitudes. The farm-scale GHG emissions, averaged over the four models, was 10.6 t carbon dioxide equivalents (CO(2)e)/ha per year, with a range of 1.9 t CO(2)e/ha per year. Even though key production characteristics were specified in the scenarios, there were still significant differences between models in the annual milk production per ha and the amounts of N fertiliser and concentrate feed imported. This was because the models differed in their description of biophysical responses and feedback mechanisms, and in the extent to which management functions were internalised. We conclude that comparing the results of different farm-scale models when applied to a range of scenarios would build confidence in their use in achieving ESR targets, justifying further investment in the development of a wider range of scenarios and software tools. |
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2019-01-07 |
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English |
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ISSN |
1751-7311 |
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TradeM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
5212 |
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Author |
Mandryk, M.; Reidsma, P.; Kanellopoulos, A.; Groot, J.C.J.; van Ittersum, M.K. |
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Title |
The role of farmers’ objectives in current farm practices and adaptation preferences: a case study in Flevoland, the Netherlands |
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Journal Article |
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Year |
2014 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg Environ Change |
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Volume |
14 |
Issue |
4 |
Pages |
1463-1478 |
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Keywords |
multi-criteria decision-making; multi-objective optimization; agriculture; arable farm; vegetable farms; climate-change; south uruguay; land-use; design; agriculture; model; management; options; systems |
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Abstract |
The diversity in farmers’ objectives and responses to external drivers is usually not considered in integrated assessment studies that investigate impacts and adaptation to climate and socio-economic change. Here, we present an approach to assess how farmers’ stated objectives relate to their currently implemented practices and to preferred adaptation options, and we discuss what this implies for assessments of future changes. We based our approach on a combination of multi-criteria decision-making methods. We consistently assessed the importance of farmers’ objectives and adaptation preferences from what farmers say (based on interviews), from what farmers actually do (by analysing current farm performance) and from what farmers want (through a selected alternative farm plan). Our study was performed for six arable farms in Flevoland, a province in the Netherlands. Based on interviews with farmers, we reduced the long list of possible objectives to the most important ones. The objectives we assessed included maximization of economic result and soil organic matter, and minimization of gross margin variance, working hours and nitrogen balance. In our sample, farmers’ stated preferences in objectives were often not fully reflected in realized farming practices. Adaptation preferences of farmers largely resembled their current performance, but generally involved a trend towards stated preferences. Our results suggest that in Flevoland, although farmers do have more objectives, in practical decision-making they focus on economic result maximization, while for strategic decision-making they account for objectives influencing long-term performance and indicators associated with sustainability, in this case soil organic matter. |
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2016-10-31 |
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1436-3798 1436-378x |
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CropM |
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Call Number |
MA @ admin @ |
Serial |
4794 |
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Author |
Dumont, B.; Basso, B.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
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Title |
Systematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions |
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Journal Article |
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Year |
2015 |
Publication |
Precision Agriculture |
Abbreviated Journal |
Precision Agric. |
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Volume |
16 |
Issue |
4 |
Pages |
361-384 |
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Keywords |
nitrogen management; climatic variability; lars-wg weather generator; stics soil-crop model; pearson system; probability risk assessment; crop model stics; fertilizer nitrogen; generic model; wheat yield; maize; simulation; skewness; field; agriculture; scenarios |
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Abstract |
At the plot level, crop simulation models such as STICS have the potential to evaluate risk associated with management practices. In nitrogen (N) management, however, the decision-making process is complex because the decision has to be taken without any knowledge of future weather conditions. The objective of this paper is to present a general methodology for assessing yield variability linked to climatic uncertainty and variable N rate strategies. The STICS model was coupled with the LARS-Weather Generator. The Pearson system and coefficients were used to characterise the shape of yield distribution. Alternatives to classical statistical tests were proposed for assessing the normality of distributions and conducting comparisons (namely, the Jarque-Bera and Wilcoxon tests, respectively). Finally, the focus was put on the probability risk assessment, which remains a key point within the decision process. The simulation results showed that, based on current N application practice among Belgian farmers (60-60-60 kgN ha(-1)), yield distribution was very highly significantly non-normal, with the highest degree of asymmetry characterised by a skewness value of -1.02. They showed that this strategy gave the greatest probability (60 %) of achieving yields that were superior to the mean (10.5 t ha(-1)) of the distribution. |
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English |
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ISSN |
1385-2256 |
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Notes |
CropM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
4519 |
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Author |
Fan, F.; Henriksen, C.B.; Porter, J. |
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Title |
Valuation of ecosystem services in organic cereal crop production systems with different management practices in relation to organic matter input |
Type |
Journal Article |
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Year |
2016 |
Publication |
Ecosystem Services |
Abbreviated Journal |
Ecosystem Services |
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Volume |
22 |
Issue |
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Pages |
117-127 |
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Keywords |
soil physical-properties; carbon sequestration; microbial biomass; farming systems; nitrogen mineralization; earthworm populations; straw; incorporation; economic valuation; agricultural soils; different tillage; Organic farming; Ecosystem services; Economic valuation; Management; Informed decision making |
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Abstract |
As the degradation of global ecosystem services (ES) continues in the last five decades, maintaining or even enhancing the ES of agro-ecosystem is one of the approaches to mitigate the global ES loss. This study provides the first estimate of an economic valuation of ES provided by organic cereal crop production systems with different management practices in relation to organic matter input (low, medium and high). Our results show that organic matter inputs significantly affect the total ES value on organic cereal crop production systems. The system with high organic matter input has the highest gross total ES value (US$ 1969 ha(-1) yr(-1)), followed by the low organic matter input system (US$ 1688 ha(-1) yr(-1)), and the lowest ES value are found in the medium organic matter input system (US$ 1492 ha(-1) yr(-1)). Organic matter inputs have strong positive relationship with non-marketable ES values, while this relationship was not found in marketable ES values. Monetizing the ES can be used by land managers and policy makers to adjust management practices in terms of organic matter input in cereal production system with a long term goal for sustainable agriculture. |
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2017-01-12 |
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2212-0416 |
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Notes |
CropM, ft_MACSUR |
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Call Number |
MA @ admin @ |
Serial |
4934 |
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Author |
Waha, K.; Müller, C.; Bondeau, A.; Dietrich, J.P.; Kurukulasuriya, P.; Heinke, J.; Lotze-Campen, H. |
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Title |
Adaptation to climate change through the choice of cropping system and sowing date in sub-Saharan Africa |
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Journal Article |
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Year |
2013 |
Publication |
Global Environmental Change |
Abbreviated Journal |
Glob. Environ. Change |
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Volume |
23 |
Issue |
1 |
Pages |
130-143 |
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Keywords |
multiple cropping; sequential cropping systems; crop modelling; agricultural management; adaptation options; global vegetation model; future food-production; rainy-season; west-africa; agriculture; yield; maize; soil; variability; heat |
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Abstract |
Multiple cropping systems provide more harvest security for farmers, allow for crop intensification and furthermore influence ground cover, soil erosion, albedo, soil chemical properties, pest infestation and the carbon sequestration potential. We identify the traditional sequential cropping systems in ten sub-Saharan African countries from a survey dataset of more than 8600 households. We find that at least one sequential cropping system is traditionally used in 35% of all administrative units in the dataset, mainly including maize or groundnuts. We compare six different management scenarios and test their susceptibility as adaptation measure to climate change using the dynamic global vegetation model for managed land LPJmL. Aggregated mean crop yields in sub-Saharan Africa decrease by 6-24% due to climate change depending on the climate scenario and the management strategy. As an exception, some traditional sequential cropping systems in Kenya and South Africa gain by at least 25%. The crop yield decrease is typically weakest in sequential cropping systems and if farmers adapt the sowing date to changing climatic conditions. Crop calorific yields in single cropping systems only reach 40-55% of crop calorific yields obtained in sequential cropping systems at the end of the 21st century. The farmers’ choice of adequate crops, cropping systems and sowing dates can be an important adaptation strategy to climate change and these management options should be considered in climate change impact studies on agriculture. (C) 2012 Elsevier Ltd. All rights reserved. |
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2016-10-31 |
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English |
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Abbreviated Series Title |
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Edition |
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ISSN |
0959-3780 |
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CropM |
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Call Number |
MA @ admin @ |
Serial |
4823 |
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