Abstract: Forage-based livestock and dairy production are the economic backbone of agriculture in many northern countries. In northern Europe and eastern Canada, forage grasses are commonly grown intensively for silage and hay as a part of crop rotation. In those regions, timothy (Phleum pratense L.) is one of the most widely grown grass species. Models that simulate the development of yield and nutritive quality have been developed for timothy, but the performance of different models has not been compared so far.In this study, we compare the performance of the models BASGRA, CATIMO, and STICS for the  predictions of timothy yield at 7 sites located in Finland, Norway, Sweden, and Canada. In addition to yield, model predictions of additional variables, such as leaf area index, specific leaf area, and nutritive quality are gathered on a daily basis. Observed data will be used for two distinct calibrations: 1) Cultivar-specific and 2) ”global”, using all cultivars. The performance of the models will be tested by simulating all sites and years with both the 5 cultivar-specific parameter sets and the global parameter set.The first results of the comparison will be presented with a particular emphasis on dry matter yield predictions.The results will provide information about the uncertainties related to yield predictions of different timothy models and calibrations, the strengths and weaknesses of different modelling approaches, and the sensitivity of models to cultivar-specific parameters. 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

Abstract: A requirement for successful integration of soil, crop and economic models is a relevant interface of the three. Economic farming models deal with choice of crops, crop management during growing season and stock management after harvest. With detailed daily weather information the state of the soil might be simulated so that a suitable sowing date can be estimated. Moreover with rational beliefs with respect to future crop prices, and with a crop model which responds to management, the management during the growing season might be optimized with respect to choice of cultivar, fertilization and irrigation. So far, as reflected by Müller and Robertson (2014), predictions of future crop yields according to crop models take only to small extent such farmer responses into account, and might therefore overestimate the responses of crop harvests to climate.Comparison of soil, crop and economic simulations with observed weather and crop outcomes might lead to estimation/calibration of unobserved parameters in all models. Such exercises need generic soil, crop and economic models which do not leave modelling outcomes to the crop modeller’s or economist’s discretion. No Label