Abstract: This special issue includes a sub-set of papers developed in the context of the three-years (2013-16) research project “IC-FAR – Linking long term observatories with crop system modelling for a better understanding of climate change impact and adaptation strategies for Italian cropping systems” (www.icfar.it), funded by the Italian Ministry of Education, University and Research. IC-FAR collects the legacy of some three-four generations of researchers, members of the Italian Society of Agronomy, that from the 1960ies onward established long term agro-ecosystem experiments (LTAE) in various Italian locations, to address a wide range of agronomy research questions. A lot of the results from these LTAE were not yet published or were published as grey literature or in Italian and almost always as a single-site, single-experiment outcome.

Abstract: Impact of climate change on crop growth, groundwater recharge and nitrogen leaching in winter wheat production in Germany was assessed using the agro-ecosystem model HERMES with a downscaled (WETTREG) climate change scenario A1B from the ECHAM5 global circulation model. Three alternative algorithms describing the impact of atmospheric CO2 concentration on crop growth (a simple Farquhar-type algorithm, a combined light-use efficiency – maximum assimilation approach and a simple scaling of the maximum assimilation rate) in combination with a Penman-Monteith approach which includes a simple stomata conduction model for evapotranspiration under changing CO2 concentrations were compared within the framework of the HERMES model. The effect of differences in regional climate change, site conditions and different CO2 algorithms on winter wheat yield, groundwater recharge and nitrogen leaching was assessed in 22 regional simulation case studies across Germany. Results indicate that the effects of climate change on wheat production will vary across Germany due to different regional expressions of climate change projection. Predicted yield changes between the reference period (1961-1990) and a future period (2021-2050) range from -0.4 t ha(-1), -0.8 t ha(-1) and -0.6 t ha(-1) at sites in southern Germany to +0.8 t ha(-1), +0.6 t ha(-1) and +0.8 t ha(-1) at coastal regions for the three CO2 algorithms, respectively. On average across all regions, a relative yield change of +0.9%, +3.0%, and +6.0%, respectively, was predicted for Germany. In contrast, a decrease of -11.6% was predicted without the consideration of a CO2 effect. However, simulated yield changes differed even within regions as site conditions had a strong influence on crop growth. Particularly, groundwater-affected sites showed a lower vulnerability to increasing drought risk. Groundwater recharge was estimated to change correspondingly to changes in precipitation. The consideration of the CO2 effect on transpiration in the model led to a prediction of higher rates of annual deep percolation (+16 mm on average across all sites), which was due to higher water-use efficiency of the crops. In contrast to groundwater recharge, simulated nitrogen leaching varied with the choice of the photosynthesis algorithm, predicting a slight reduction in most of the areas. The results underline the necessity of high-resolution data for model-based regional climate change impact assessment and development of adaptation measures. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: The sustainable development of agricultural systems is currently challenged by many complex agro-environmental issues. These are characterized by an incomplete understanding of the situation and the problems that arise, and the conflicting opinions that result, issues over boundaries that are often difficult to define, and controversy over the multiple goals and uncertain outcomes. Added to these characteristics, we also have the slow and often inadequate uptake and implementation of research outcomes in this complex, real world. In order to improve sustainability of agro-ecosystems, agronomic research must move away from the linear research approaches and extension practices adopted so far that have focused purely on biophysical agro-ecosystems. The theoretical operational space of agronomic research must be transformed by considering agronomic issues as part of a broader social-agro-ecosystem. One aspect of this transformation is the inclusion of knowledge collected on a local level with the participation of farmers on the ground. The integration of local experiential knowledge with traditional agronomic research is by necessity based on the participation of many different stakeholders and there can be no single blueprint for how best to develop and use the input received. However, agronomists and policy advisors require general guidelines drawn up from actual experience in order to accelerate positive agronomic change. We address this need through a comparative analysis of two case studies; one involves multi-stakeholder research in a cropping system in the dairy district of Arborea, Sardinia, Italy. The central question was: How can high crop production be maintained while also achieving the EU target water quality and minimizing the production costs? The second case is a multi-stakeholder soil health project from south-eastern Australia. Here the central question was: How can soil decline be prevented and reversed in this district, and soils made more resilient to future challenges? The Social Learning for the Integrated Management and sustainable use of water (SLIM) framework, a useful heuristic tool for exploring the dynamics of transformational change, guided the analysis of the case studies. Within this framework, a key indicator of success is the emergence of new knowledge from the creation of new spaces for learning between researchers and local stakeholders. The Italian case study appears to have been the most successful in this sense, as opportunities for joint exploration of research data allowed new potential farming responses to the central question to emerge. The multi-stakeholder processes in the Australian case focused more on providing public openings for individual learning, and missed the opportunity for new knowledge to emerge through joint exploration. We conclude that participatory approaches may enable transformative practice through knowledge integration, but that this process is not an automatic outcome of increased community participation.