Abstract: Models integration and possible contrasts with up-scaling activities has received increasing attention in recent years especially with respect to the relationship between farm-economics and biophysical assessments. Current bio-economic models that analyse the trade-offs between farm income and interventions on eco-bio-environmental parameters such as maintenance of biodiversity, reduction of erosion and nitrate pollution and more, include static models. Agricultural systems are facing a series of threats, including climate change, land degradation, price volatility and intensification processes, which put their long-term sustainability into question. The University of Basilicata in collaboration with local representatives from various sectors of production in the Basilicata region of Southern Italy has developed an integrated study to define a model system to assess the dynamics at play in rural territories. The study tested the explanatory usefulness of resilience theory for the Basilicata agricultural social-ecological system, applying the adaptive cycle as a diagnostic tool to explore the dynamics and trajectories of change in the coupled social-ecological systems, and evaluating the performance of social, economic and social capitals, which are subject to the same dynamics. The use of dynamic analysis of the social, economic and natural capitals as the key to interpret the various phases of the adaptive cycle of the two agricultural systems proved a powerful tool in analysing the relationships between resilience and sustainable development in rural territories. The adoption of capitals and their inter-relations proved fundamental to the elaboration of adaptation strategies which were compatible with patterns of sustainability. The adaptive cycle heuristic, despite some methodological difficulties, remains useful to describe processes of change in rural socio-ecological systems. There could be enormous potential in adopting these instruments to help identify of the needs of different territories and help the framing and implementation of rural policies. No Label

Abstract: This deliverable lays out the work as done as part of MACSUR CropM on data, with the  focus on improving data management and have shared data curation for future use. The  issue was tackled with help from the MACSUR central hub coordination in the form of Jason  Jargenson from University of Reading. The data management as proposed and  implemented in this deliverable is very much a bottom up process, in which partners in a  meeting in Spring 2013 in Aarhus investigated the best way forward for data management  across activities in CropM.As a follow up to this, the work was mainly divided in three  parts:  1. The  Open  Data  Journal  for  Agricultural  Research,  mainly  focused  on  long  term  data  archival  and  citation  of  data  sets,  as  input  and  outputs  to  the  modelling  work,  as  part  of  MACSUR,  lead  by  Wageningen  UR  2. The  Geonetwork  data  catalog  hosted  at  Aarhus  Universitet,  that  allows  for  operational  access  and  storage  of  data  sets  as  part  of  the  ongoing  work,  also  for  restricted  access  of  the  consortium,  and  as  a  first  step  to  visualization,  lead  by  Aarhus  Universitet.  3. The  work  on  rating  data  sets,  that  provides  a  tool  for  improving  data  set  access  in  an  early  phase  for  connecting  them  to  models,  lead  by  Reading  University.  At the end of the deliverable some next steps are giving for data activities in the context  of AgMIP and beyond. No Label

Abstract: This deliverable lays out the work as done as part of MACSUR CropM on data, with the focus on providing a web tool for visualization of model output. It was decided early on that not a specific MACSUR web tool would be developed as part of MACSUR for phase 1, and mostly results would be visualized in other available tools, such as the Global Yield Gap Atlas, which are recognised resources for visualizations. Only in relationship to the MACSUR Geonetwork data catalog hosted at Aarhus University some developments where started. Operationally speaking, most data was still being generated during phase 1, so there was not enough to visualize on specific websites and partners did not commit financial resources to their development, and only in kind was available. No Label