DryArc Interface as a R4D framework for collaboration between CGIAR and FAO on Dryland Agriculture
The DryArc Initiative is a research partnership between eight CGIAR Research Centers that aims to strengthen the resilience of rural communities and agri-food systems across the global drylands of the Middle East and North Africa, South, Central, and West Asia as well as Sub-Saharan Africa, representing the DryArc region.
The four pillars of the DryArc action towards achieving the Sustainable Development Goals (SDGs) are:
- combining knowledge (local, regional, international) to design systemic innovations,
- accelerating scaling up of impactful target innovations,
- continuous integration of disruptive technologies,
- and enabling institutional environment (decision-making, M&E, absorptive capacity, investment).
COVER PHOTO CREDIT:
CTA ACP-EU / Clément Tardif
Chandrashekar Biradar
Head of Geoinformatics Units, International Center for Agricultural Research in Dry Areas (ICARDA)
Dr Biradar is a Principal Agroecosystems Scientist and Head of the Geoinformatics; Research Team Leader of GeoAgro and Digital Augmentation. His core expertise focus on the GeoAgro and citizens science for complex system research for accelerating sustainable agroecosystems. Dr. Biradar has multi-disciplinary educational backgrounds with BSc in Forestry/Agricultural sciences, MSc in Genetic Engineering, and PhD in Environmental Science and Space Applications, then Postdoctoral fellows in Earth Observation and Modelling. He pioneered multi-disciplinary approaches for quantification of agri-food systems, water/land productivity, and sustainable intensification. His current research focus on digital augmentation for revitalizing balanced agroecosystems. Dr. Biradar has authored and co-authored over 210 publications. He has received numerous awards and honors, including Best Team Initiative, Young Scientist, and Outstanding Scientist Awards. Dr Biradar is also Pioneer of biodiversity gardening and multi-layer farming.He has developed several resource efficient methods/models for vital food systems and support local biodiversity conservation at several scales and contexts.