Abstract: We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

Abstract: This report is grounded on the hypotheses, methodologies and approaches for stakeholder mapping designed during the early stages of MACSUR and described in the previous report1. It describes the kind of activities conducted by the WPC6-3-4 MACSUR team and the emerging design of activities for the second phase of MACSUR (2015-2017). The designed process of strategic stakeholder mapping was implemented by some of the teams involved in the task and through hub initiatives. Key actions were the (i) development of suitable intermediary objects to engage with stakeholders, through the regional pilot case studies, (ii) the design and implementation of key events (we report here the case of the Agroscenari event at the case study scale, the national event between the MACSUR Italian partnership with Italian policy makers held in Rome in July 2014, the international stakeholder events at the MACSUR mid term meeting in Sassari (April 2014), and the one held in Bruxelles on 6 May 2015) and (iii) the process of stakeholder and stakeholding mapping at the case study scale. Results indicate that when dealing with high level stakeholders (e.g. institutional or large agro-food enterprises), occasional stakeholder events will only serve as opportunity for showcasing and possibly for a data collection useful for researchers, with almost no impact on the ongoing social learning process sought by the designed activities. At the case study scale, instead, the long term and ongoing activities can generate new spaces for mutual learning and knowledge hybridization, through a variety of mediating objects emerging from the continuous interactions. The lesson learned is that the engagement of high level stakeholders can be effective insofar they are somehow involved in the interactions with stakeholders at the case study scale, as this can provide a key experience leading to a change in understanding about the nature of the issues that can ultimately result into a change in practice. These results will be the basis for the design of new strategies for engaging EU policy makers and large agro-food energy representatives in the second phase of MACSUR. No Label

Abstract: Perception not only shapes knowledge but knowledge also shapes perception. Humans adapt to the natural world through a process of learning in which they interpret their sensory impressions in order to give meaning to their environment and act accordingly. In this research, we examined how farmers’ decision making is shaped in the context of changing climate. Using empirical data (face-to-face semi-structured interviews and questionnaires) on four Mediterranean farming systems from a case study located in Oristano (Sardinia, Italy) we sought to understand farmers’ perception of climate change and their behaviors in adjustment of farming practices. We found different perceptions among farmer groups were mainly associated with the different socio-cultural and institutional settings and perceived relationships between climate factors and impacts on each farming systems. The research findings on different perceptions among farmer groups can help to understand farmers’ current choices and attitudes of adaptation for supporting the development of appropriate adaptation strategies. In addition, the knowledge of socio-cultural and economic factors that lead to biases in climate perceptions can help to integrate climate communication into adaptation research for making sense of climate impacts and responses at farm level.