This paper suggests how the United Nations Convention to Combat Desertification (UNCCD) community can progressively make use of a flexible framework of analytical approaches that have been recently developed by scientific research. This allows a standardized but flexible use of indicator sets adapted to specific objectives or desertification issues relevant for implementing the Convention. Science has made progress in understanding major issues and proximate causes of dryland degradation such that indicator sets can be accordingly selected from the wealth of existing and documented indicator systems. The selection and combination should be guided according to transparent criteria given by existing indicator frameworks adapted to desertification conceptual frameworks such as the Dryland Development Paradigm and can act as a pragmatic entry point for selecting area-and theme-specific sets of indicators from existing databases. Working on different dryland sub-types through a meaningful stratification is proposed to delimit and characterize affected areas beyond the national level. Such stratification could be achieved by combining existing land use information with additional biophysical and socio-economic data sets, allowing indicator-based monitoring and assessment to be embedded in a framework of specific dryland degradation issues and their impacts on key ecosystem services.

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<p>Coffee is one of the most important agri-food systems from a global economic point of view. Most of the production takes place on small and medium-sized farms and is the main source of income for many rural families in several developing countries. Areas suitable for coffee production are very biodiverse and ecologically important, thus negative impacts should be minimized.<br />Coffee production requires special environmental and climatic conditions. Current and future climate changes could cause problems for a sustainable production and result in lower yields. To overcome these problems, it is necessary to investigate the effectiveness of possible adaptation measures, such as intercropping with other tree species that can provide more shade to coffee plants and favour environmental sustainability. <br />In order to study how such modifications could improve the resilience and sustainability of coffee production, the use of process-based models can be very useful. The DynACof model was developed specifically to simulate coffee farming systems, including phenological development, physiological processes related to flower and fruit production, carbon allocation, the effect of water availability, light and temperature, as well as management. We tested the DynACof model on some study areas in Mexico, Brasil and Rwanda and verified that the yield predictions were in line with the observations. We then developed a modelling tool where the model can be applied to entire geographical areas in a spatially explicit manner, using global climatic and soil datasets.<br />We used this tool to simulate yields in Latin America and Africa, both for the period 1985-2014 and for the period 2036-2065 using climate projections. Comparing the two periods, the model predicts a decrease in yields of about 28% in Latin America and about 12% in Africa. We then simulated specific management options (e.g. agroforestry shading vs intensive monocropping) to assess their efficacy in enhancing environmental sustainability and resilience to climate risks. These impact analyses will be crossed with socio-economic indicators for a more comprehensive climate risk assessment to support adaptation recommendations.</p>