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: In this paper we present an approach to sustainability management within partnerships between heterogenous actors. This multi-disciplinary approach is also relevant for the assessment of climate change adaptation and mitigation in the context of www.macsur.eu; and especially in areas with dairy farming hot-spots. Established approaches within this field such as Adaptive Co-Management and Social Learning focus on social-material interactions, feedback mechanisms, knowledge integration and institutional change as drivers in sustainable development. However, the role of micro-scale power dynamics as part of these processes have received less attention. In a case study of land-water management in a Danish water catchment, dominated by dairy farms, we analyze how dynamics of power within knowledge integration processes interacts with institutions at different scales. Thereby, we show ways in which power-knowledge dynamics shape development outcomes. Finally, we propose how increasing reflexivity of power-knowledge dynamics might contribute to institutional change and sustainable development. No Label

Abstract: Projected changes in temperature, rainfall and soil moisture could threaten agricultural land use and crop productivity in Europe, with major consequences for food security (Daccache et al., 2014). We assessed the projected impacts of climate change on the yield of seven crops (viz wheat, barley, maize, potato, sugar beet, rice and rye) in Europe using a systematic review (SR) and meta-analysis of data reported in 67 original publications from an initial screening of 1424 studies. Whilst similar studies exist for Africa and South Asia (Roudier et al., 2011; Knox et al., 2012), surprisingly, no such comparable synthesis has been undertaken for Europe. Our study focussed on the biophysical impacts of climate change on productivity (i.e. yield per unit area) and did not consider ‘food production’ as this is dependent on many ‘non-biophysical’ factors, such as international trade policy and world markets. The data relate to the projected mean yield variations for each crop type, for all crop models, all GCM models and all time slices.For Europe, most studies projected a positive impact on yield; the reported increases largely being due to rising atmospheric CO2 concentrations enhancing both productivity and resource use efficiencies. Overall, a mean yield increase of +14% was identified, but with large differences between individual crops (e.g. wheat +22%; potato +12%) and regions (e.g. northern Europe +17%; southern Europe +7%). It is important to note that projected yield data were not available for all crops in all regions, so lack of a significant response may in part be due to the absence, or limited number of studies for certain crops and/or regions. Furthermore, the results include all reported yield projections, for all time slices, for all GCM combinations (whether single or ensemble) and for all crop modelling approaches (whether based on simple statistical trends or more complex biophysical modelling approaches). This highlights the magnitude of variability that exists when all possible sources of uncertainty are included. Further statistical analyses were conducted to disaggregate the data by time slice, climate and crop model to identify which factors were likely to contribute most to yield variations and uncertainty.The SR showed that evidence of climate change impacts on crop yield in Europe is extensive for wheat, maize, sugar beet and potato but very limited for barley, rice and rye. Interpreting the reported yield observations was compounded by ‘effect modifiers’ or reasons for heterogeneity. These included different emission scenarios and climate ensembles, implicit assumptions regarding crop varieties, the agricultural systems studied, and assumed levels of mechanization and crop husbandry. Despite its limitations, the SR helps identify where further research should be targeted and regions where adaptation will be most needed. It confirms that climate change is likely to increase productivity of Europe’s major agricultural cropping systems, with more favourable impacts in northern and central Europe. No Label