SAFE—A hierarchical framework for assessing the sustainability of agricultural systems

Sustainable development and the definition of indicators to assess progress towards sustainability have become a high priority in scientific research and on policy agendas. In this paper, we propose a consistent and comprehensive framework of principles, criteria and indicators (PC&I) for sustainability assessment of agricultural systems, referred to as the Sustainability Assessment of Farming and the Environment (SAFE) framework. In addition we formulate consistent and objective approaches for indicator identification and selection. The framework is designed for three spatial levels: the parcel level, the farm level and a higher spatial level that can be the landscape, the region or the state. The SAFE framework is hierarchical as it is composed of principles, criteria, indicators and reference values in a structured way. Principles are related to the multiple functions of the agro-ecosystem, which go clearly beyond the production function alone. The multifunctional character of the agro-ecosystem encompasses the three pillars of sustainability: the environmental, economic and social pillars. Indicators and reference values are the end-products of the framework. They are the operational tools that are used for evaluating the sustainability of the agro-ecosystems. The proposed analytical framework is not intended to find a common solution for sustainability in agriculture as a whole, but to serve as an assessment tool for the identification, the development and the evaluation of agricultural production systems, techniques and policies.     

A data support infrastructure for Clean Development Mechanism forestry implementation: an inventory perspective from Cameroon

Clean Development Mechanism (CDM) forestry project development requires highly multi-disciplinary and multiple-source information that can be complex, cumbersome and costly to acquire. Yet developing countries in which CDM projects are created and implemented are often data poor environments and unable to meet such complex information requirements. Using Cameroon as an example, the present paper explores the structure of an enabling host country data support infrastructure for CDM forestry implementation, and also assesses the supply potential of current forestry information. Results include a conceptual data model of CDM project data needs; the list of meso- and macro-level data and information requirements (Demand analysis); and an inventory of relevant data available in Cameroon (Supply analysis). From a comparison of demand and supply, we confirm that data availability and the relevant infrastructure for data or information generation is inadequate for supporting carbon forestry at the micro, meso and macro-levels in Cameroon. The results suggest that current CDM afforestation and reforestation information demands are almost impenetrable for local communities in host countries and pose a number of cross-scale barriers to project adoption. More importantly, we identify proactive regulatory, institutional and capacity building policy strategies for forest data management improvements that could enhance biosphere carbon management uptake in poor countries. CDM forestry information research needs are also highlighted.