Abstract: Farm-scale models quantify the cycling of nitrogen (N) and carbon (C) so are powerful tools for assessing the impact of management-related decisions on greenhouse gas (GHG) emissions, especially on dairy cattle farms, where the internal cycling is particularly important. Farm models range in focus (economic, environmental) and the detail with which they represent C and N cycling. We compared four models from this range in terms of on-farm production and emissions of GHGs, using standardized scenarios. The models compared were SFarMod, DairyWise, FarmAC and HolosNor. The scenarios compared were based on two soil types (sandy clay versus heavy clay), two roughage systems (grass only versus grass and maize), and two climate types (Eindhoven versus Santander). Standard farm characteristics were; area (50 ha), milk yield (7000 kg/head/year), fertiliser (275 kg N and 150 kg N/ha/year for grass and maize, respectively). Potential yields for grass 10t dry matter (DM)/ha/year in both areas, maize 14 t DM/ha/ year in Eindhoven and 18t DM/ha/ year in Santander. The import of animal feed and the export/import manure and forages was minimized. Similar total farm direct GHG emissions for all models disguised a variation between models in the contribution of the different on-farm sources. There were large differences between models in the predictions of indirect GHG emission from nitrate leaching. Results could be explained by differences between models in the assumptions made and detail with which underlying processes were represented. We conclude that the choice of an appropriate farm model is highly dependent upon the role it should play and the context within which it will operate, so the current diversity of farm models will continue into the future. No Label

Abstract: Feed crop cultivation dominates land use in North Savo region where the value of dairy milk and beef production is approx. 70 % of the total value of agricultural production. Grass silage is produced on cultivated grasslands through grass-cereal rotations. There are restricted or no markets for silage. Dairy and beef farms, directly dependent on the quantity and quality of silage, are vulnerable to adverse weather conditions. Long-term viability of farming is dependent on the long-term productivity development of feed crop production, and ability to cope with adverse weather conditions, affecting both quality and quantity of feed. Adaptation challenges include more frequent wet and dry conditions, increased pest and disease pressure, and overwintering problems, affecting quantity and quality of grass and cereals harvests. More frequent wet conditions are combined with larger farm size, higher axle loads of heavy machinery, increased risk of soil compaction, and high timeliness costs due to rapidly deteriorating feed quality if not harvested at the right time. Some solutions impose new investments and high costs. Results from bio-physical modeling show a clear need for new cultivars better suited in future climate. Various other solutions discussed with the farmers and extension specialists include improved maintenance of drainage and soil structure, to be promoted by crop rotation, soil improvements such as liming, as well as better crop protection. However, higher grass yields may be realized without considerably increased inter-annual yield variability. Needed long-term investments may thus lead to increased productivity under favorable market and policy conditions. No Label

Abstract: Fertilized crops and livestock management are the main anthropogenic sources of ammonia (NH3). Ammonia emissions imply a N loss from cropping systems and have negative effects on ecosystems and human health. In Africa, it is believed that a substantial proportion of NH3 emissions results from widespread livestock management, whereas inorganic fertilizers might be of low importance. However, there is a lack of information on the mechanisms underlying the NH3 emissions derived from livestock management. Use of passive sampling approaches may enhance our knowledge on NH3 emissions by allowing systematic ecosystem investigations at a low cost; however, these techniques have not been critically evaluated for the Tropics. The main goals of our study are 1) to assess the livestock influence on the emissions of NH3 in tropical ecosystems and 2) the evaluation of experimental techniques for estimation of NH3 emissions, which could be further implemented in Africa without investment in sophisticated analytical equipment.The study was carried out in October 2014 at the farm of ILRI (Nairobi, Kenya). Ammonia fluxes from a fenced plot occupied by a herd of cows during daytime was estimated by both 1) the micrometeorological mass balance integrated horizontal flux (IHF) method and 2) the Eddy-covariance (EC) technique (using a sonic anemometer and a highly sensitive fast response NH3 trace gas monitor). Passive flux samplers (PFS) internally coated with oxalic acid were installed at different heights in 1 central and 3 background masts. PFS were exchanged every 2 days and NH3 trapped was measured colorimetrically. Soil N2O emissions were also estimated by manual chambers every 48 h along with inorganic N contents in the topsoil.Contrary to our expectations, NH3 cow’s presence did not triggered NH3 emissions. Both IHF and EC showed very low NH3 emission values along the experiment, although sensitivity varied among methods (about 100 and 30 ng NH3 m-2 s-1 as obtained by the IHF method and EC, respectively). Heavy rainfall events (˃120 mm) may be responsible for lowered NH3 volatilization. Low soil nitrate concentrations, (<0.5 mg kg-1), suggested predominant N leaching after rainfall. Soil N2O emissions were negligible, showing a maximum of only 4.5 µg N-N2O m-2 h-1 during the first day. These preliminary results represent the first dataset of NH3 emissions under controlled conditions in tropical Africa, and provide the basis for further assessments of NH3 emissions and evaluations of techniques under different ecosystems and management scenarios. No Label