Adoption potential of conservation agriculture in sub-saharan Africa

In a continent facing a fast increasing population, smallholder farming in Africa is exposed to double challenge: 1) to increase food production and, 2) to preserve natural resources. While conventional tillage-based agriculture has been held accountable for soil degradation, Conservation Agriculture (CA) based on minimal or no-tillage is increasingly seen as a promising alternative for highly productive and sustainable farming. Despite its potential, CA adoption rates in Africa, compared with other continents, have remained extremely low. While literature on adoption contraints is abundant, comprehensive, holistic frameworks and tools for explaining or predicting adoption are still lacking. In particular, such frameworks and tools could help in assessing systematically under which ecological, socio-economic and institutional conditions CA is best suited for smallholder farming in Africa and for its scaling up. The objective of this contribution therefore is to demonstrate how a newly developed Qualitative expert-based Assessment Tool (QAToCA) was applied in case studies across Malawi, Burkina Faso, and Zimbabwe; 1) to determine the Relative Adoption Potential (RAP) of CA, 2) to assess the institutional, agro-ecological, socio-economic and cultural influences on the RAP of CA, and 3) to determine the site-specific hindering and supporting factors to the RAP of CA for the different case studies. Results show that for the two south African case studies, Malawi has a high RAP for CA while Zimbabwe has a much lower potential. On the other hand the two case studies in south western and northern Burkina Faso both showed a relatively high adoption potential of CA. Major differences in adoption potential are explained by economic market incentives, prevailing institutional arrangements as well as some biophysical incentives. (Résumé d'auteur

Managing uncertainty: a review of food system scenario analysis and modelling

Complex socio-ecological systems like the food system are unpredictable, especially to long-term horizons such as 2050. In order to manage this uncertainty, scenario analysis has been used in conjunction with food system models to explore plausible future outcomes. Food system scenarios use a diversity of scenario types and modelling approaches determined by the purpose of the exercise and by technical, methodological and epistemological constraints. Our case studies do not suggest Malthusian futures for a projected global population of 9 billion in 2050; but international trade will be a crucial determinant of outcomes; and the concept of sustainability across the dimensions of the food system has been inadequately explored so far. The impact of scenario analysis at a global scale could be strengthened with participatory processes involving key actors at other geographical scales. Food system models are valuable in managing existing knowledge on system behaviour and ensuring the credibility of qualitative stories but they are limited by current datasets for global crop production and trade, land use and hydrology. Climate change is likely to challenge the adaptive capacity of agricultural production and there are important knowledge gaps for modelling research to address

A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models

Assessment of spatial variability of multiple ecosystem services in grasslands of different intensities

Grasslands provide multiple Ecosystem Services (ES) such as forage provision, carbon sequestration or habitat provision. Knowledge about the trade-offs between these ES is of great importance for grassland management. Yet, the outcome of different management strategies on ES provision is highly uncertain due to spatial variability. We aim to characterize the provision (level and spatial variability) of grassland ES under various management strategies. To do so, we combine empirical data for multiple ES with spatially explicit census data on land use intensities. We analyzed the variations of five ES (forage provision, climate regulation, pollination, biodiversity conservation and outdoor recreation) using data from biodiversity fieldwork, experimental plots for carbon as well as social network data from Flickr. These data were used to calculate the distribution of modelled individual and multiple ES values from different grassland management types in a Swiss case study region using spatial explicit information for 17,383 grassland parcels. Our results show that (1) management regime and intensity levels play an important role in ES provision but their impact depends on the ES. In general, extensive management, especially in pastures, favors all ES but forage provision, whereas intensive management favors only forage provision and outdoor recreation; (2) ES potential provision varies between parcels under the same management due to the influence of environmental drivers, related to topography and landscape structure; (3) there is a trade-offs between forage provision and other ES at the cantonal level but a synergy between forage provision and biodiversity conservation within the grassland categories, due to the negative impact of elevation on both ES. Information about multiple ES provision is key to support effective agri-environmental measures and information about the spatial variability can prevent uncertain outputs of decision-making processes

Validating the usefulness and calibration of a two-dimensional situation model of urgency-adaptability for cities responding to climate change — Taking Shenzhen as case study

Abstract Climate change is a major challenge for human sustainable and urban governance mode. A Two-Dimensional Urgency-Adaptability Situation Model for Cities Responding to Climate Change was constructed in this study to evaluate cities adaptation capacity to climate change. The model evaluated city adaptability in five aspects: social and economic development, disaster response, urban planning adaptation, science and technology and policy management. To verify the effectiveness of the model, Shenzhen was chosen as a case, which had a start in climate change adaptation as a developed coastal city in China. The result shows that Shenzhen should further focus on enhancing its urban planning adaptability in the aspects including green construction, planning and design, as well as city renovation and regeneration. The Urgency-Adaptability Situation Model helps to make policy suggestions aiming at enhancing the climate adaptability of cities.</jats:p

Policy relevance of three integrated assessment tools - A comparison with specific reference to agricultural policies

The Common Agricultural Policy (CAP), a system of market support instruments, direct income transfers, and rural development measures, has been put through an ongoing reform process in recent decades. This paper introduces three policy impact assessment tools (SIAT, SEAMLESS-IF, MEA-Scope tool) and analyses how these tools have responded to a number of challenges for integrated assessment modelling as reported in the international literature. Significant progress has been made with regard to modelling linkages whereas other challenges, particularly those related to issues of scale and uncertainty management, require further efforts. It is also analysed which CAP instruments are represented and what kinds of effects can be analysed at different scales. Market instruments and direct payments are comparatively well represented, while the ability to model rural development measures is mostly beyond the scope of these tools. Because each tool has found a different solution for coping with the common challenges of integrated assessment modelling, the choice of one of the tools for a particular application depends strongly on the policy questions being asked. The SIAT provides the big picture via its ability to represent broad changes in policy instruments with EU-wide cross-sector impacts. The most comprehensive analysis of agricultural policy instruments can be obtained with SEAMLESS-IF. The MEA-Scope tool complements the other two approaches with detailed regional profile

Adoption potential for conservation agriculture in Africa: A newly developed assessment approach (QAToCA) Applied in Kenya and Tanzania

Conservation agriculture (CA) is often promoted as a set of cropping practices to reduce soil erosion and maintain soil fertility, while decreasing production costs and increasing crop yields. However, CA adoption is extremely low in Africa. Most investigations on constraints of its adoption leave out (i) the characteristics of CA as an emerging innovation and (ii) the wider institutional context. A comprehensive self-assessment tool for a systematic evaluation of factors influencing the CA adoption process at the field, farm and regional scale in a variety of regional contexts in Africa is still lacking. In an attempt to fill this knowledge gap, this article presents the motivation, development and testing of a Qualitative expert Assessment Tool for CA adoption in Africa (QAToCA) and its application. QAToCA is directed to regional experts, research teams and managers of development projects with a focus on CA, and allows them to assess their CA activities along a systematic, expert-based list of questions and criteria. Specifically, it aims at assessing the adoption potential of CA under the varied agro-ecological, socio-economic, cultural and institutional conditions of Africa as well as the specific supporting and hindering factors influencing this process. As an example, its application in Kenya and Tanzania identified a relatively high CA adoption potential. The following factors, however, are noticed to require further improvement: accessibility of markets for CA products and inputs; adaptation of machinery and seeds to the CA practices; introduction of quality implementation measures; and a renewed motivation (interest) among CA service providers. Copyright © 2012 John Wiley &amp; Sons, Ltd. (Résumé d'auteur