As part of the EU funded AgriSpin project (www.agrispin.eu), which aimed at “creating space for innovations” in agriculture across Europe, this contribution addresses the above mentioned knowledge gaps by a. elaborating a generic typology appropriate to capture the variety of ISS, b. structuring selected innovations along the degree of technological change and coordination levels, and c.
The development of future food systems will depend on normative decisions taken at different levels by policymakers and stakeholders. Scenario modeling is an adequate tool for assessing the implications of such decisions, but for an enlightened debate, it is important to make explicit and transparent how such value-based decisions affect modeling results.
Invasive species such as Ambrosia (an annual weed) pose a biosecurity risk whose management depends on the knowledge, attitudes and practices of many stakeholders. It can therefore be considered a complex policy and risk governance problem. Complex policy problems are characterised by high uncertainty, multiple dimensions, interactions across different spatial and policy levels, and the involvement of a multitude of actors and organisations. This paper provides a conceptual framework for analysing the multi-level and multi-actor dimensions of Ambrosia management.
The paper takes a critical look at two key interventions identified to deliver the PAEPARD capacity strengthening strategy. Firstly, the training of a pool of agricultural innovation facilitators (AIF) to broker relations between relevant stakeholders for the consolidation of effective consortia. PAEPARD envisaged the role of AIF as to support both the face-to-face and virtual (via skype, email or social media) engagement of partners in capacity strengthening processes.
Ce document analyse de façon critique deux interventions majeures identifiées pour mettre en œuvre la stratégie de renforcement des capacités de PAEPARD. La première intervention est la formation d’un vivier de facilitateurs de l’innovation agricole (FIA) pour assurer une médiation entre les acteurs concernés et, ainsi, consolider des consortiums efficaces. PAEPARD prévoyait que les FIA encouragent l’engagement virtuel (par l’intermédiaire de Skype, d’e-mails ou des réseaux sociaux) et en personne des partenaires dans des processus de renforcement des capacités.
Despite efforts over recent years to improve the status of agriculture in sub-Saharan Africa, little change has been noted, due partially to the fact that efforts have come from individual entities, which had short-term funding or lacked the necessary expertise to scale up research outputs. Disconnect between researchers and end-users has further hindered the success of such efforts.
Malgré les efforts déployés ces dernières années pour améliorer la situation de l’agriculture en Afrique subsaharienne, peu de changements ont été observés. Cet insuccès est dû, en partie, au fait que ces efforts ont été consentis par diverses entités de petite taille, aux capacités de financement à court terme et sans l’expertise nécessaire pour diffuser les résultats de leurs travaux de recherche. De plus, ces initiatives ont aussi pâti de la déconnexion entre la recherche et les utilisateurs finaux.
Networks and organizations need to find ways to be more effective in pursuing their objectives and thus seek to “learn” to be able to respond, innovate and adapt to complex, changing social and environmental conditions, thus bringing about social change. An essential capacity for ARD (Agricultural Research for Development) partnerships is therefore the ability to reflect and learn. Learning is not simply about increasing knowledge and skills or changing attitudes; it is about making sense of complexity to act more effectively.
This brief illustrates the different forms of knowledge, and the ways to create and manage it.
The proof efficacy of the Integrated Agricultural Research for Development (IAR4D) was carried out in 2010, using the household income as the principal measure of impact on poverty reduction. This assessment did not take into consideration other variables that could affect livelihood outcomes.