Aggarwal, P. K., A. Jarvis, B. M. Campbell, R. B. Zougmoré, A. Khatri-Chhetri, S. J. Vermeulen, A. Loboguerrero, L. S. Sebastian, J. Kinyangi, O. Bonilla-Findji, M. Radeny, J. Recha, D. Martinez-Baron, J. Ramirez-Villegas, S. Huyer, P. Thornton, E. Wollenberg, J. Hansen, P. Alvarez-Toro, A. Aguilar-Ariza, D. Arango-Londoño, V. Patiño-Bravo, O. Rivera, M. Ouedraogo and B. Tan Yen. 2018. The climate-smart village approach: framework of an integrative strategy for scaling up adaptation options in agriculture. Ecology and Society 23(1):14. https://doi.org/10.5751/ES-09844-230114

Agricultural productivity and growth in Mali are under threat from erratic rainfall, resulting in more frequent dry years. The national economy is vulnerable to climate change due to 50% of the gross domestic product coming from the agricultural sector and 75% of the population living in rural areas. The Climate-Smart Agriculture (CSA) concept arises from a need to provide innovative solutions towards the complex and integrated goals of increasing yields, improving resilience, and promoting a low emissions agricultural sector. A major challenge for policymakers to operationalize CSA is the identification, valuation (cost-benefit), and subsequent prioritization of climate-smart options and portfolios (groups of CSA options) for investment. This paper presents the process, results, and lessons learned from a yearlong pilot of the Climate-Smart Agriculture Prioritization Framework (CSA-PF) in Mali. Key national and international stakeholders participated in the co-development and prioritization of two CSA portfolios and related action plans for the Malian Sudanese zone. Initial steps towards outcomes of the process include inclusion of prioritized CSA practices in ongoing development projects and prompting discussion of modifications of future calls for agricultural development proposals by regional donors

• A geospatial cloud-based system GeoFarmer was designed and developed. • GeoFarmer can be used as smart-monitoring system for agricultural projects. • It provides tools for interactive feedback loops between platform users. • Results and lessons learned from five pilots illustrate the flexibility of GeoFarmer.

The upland rice (UR) cropped area in Brazil has decreased in the last decade. Importantly, a portion of this decrease can be attributed to the current UR breeding programme strategy, according to which direct grain yield selection is targeted primarily to the most favourable areas. New strategies for more-efficient crop breeding under non-optimal conditions are needed for Brazil’s UR regions. Such strategies should include a classification of spatio-temporal yield variations in environmental groups, as well as a determination of prevalent drought types and their characteristics (duration, intensity, phenological timing, and physiological effects) within those environmental groups. This study used a process-based crop model to support the Brazilian UR breeding programme in their efforts to adopt a new strategy that accounts for the varying range of environments where UR is currently cultivated. Crop simulations based on a commonly grown cultivar (BRS Primavera) and statistical analyses of simulated yield suggested that the target population of environments can be divided into three groups of environments: a highly favorable environment (HFE, 19% of area), a favorable environment (FE, 44%), and least favourable environment (LFE, 37%). Stress-free conditions dominated the HFE group (69% likelihood) and reproductive stress dominated the LFE group (68% likelihood), whereas reproductive and terminal drought stress were found to be almost equally likely to occur in the FE group. For the best and worst environments, we propose specific adaptation focused on the representative stress, while for the FE, wide adaptation to drought is suggested. ‘Weighted selection’ is also a possible strategy for the FE and LFE environment groups.

Much of the literature examining the role of gender in processes of climate change adaptation in the agricultural sector has focused primarily on differences between male and female farmers, implicitly treating men and women as homogenous groups. Where heterogeneity exists within these groups which impacts climate change adaptation efforts and outcomes, an understanding of such intersectionalities is vital to the design of effective and equitable policy. The objective of this study is to investigate whether interaction effects among socio-economic factors are meaningful drivers of observed differences among female farmers in their adoption of climate-smart agricultural (CSA) practices, as well as their use of climate information and financial services. This study employs data from farmer surveys in three Climate-Smart Villages in Latin America, analyzed using ordinal logistic regression and canonical correspondence analysis. The results indicate that important interaction effects are present: the relationship between higher educational attainment and increased adoption of CSA practices, for example, is conditional on the degree of livelihood diversification. The relationship between greater educational attainment and increased use of climate forecasts is likewise conditional on age. These results suggest the need for researchers and policymakers to anticipate potential intersectionalities when designing research efforts and development interventions.

The main purpose of this work was analyzing how an innovation platform can foster and provide a basis for multi-actor collaboration in order to enable climate-smart agriculture (CSA) implementation at the local level. Using a mix of social (interactions between stakeholders, knowledge changes, adoption of practices) and technical indicators (income, fulfillment of caloric requirements of the household, farm resource use, planned biodiversity or greenhouse gas emission changes), we monitored the collaboration between an NGO, local civil authorities, associations, and farmers that aimed to achieve a common goal linked to the participatory and contextualized development of CSA in Colombia. We found that multiple stakeholder engagements led to improved interactions between members of the platform and their local environment, a proactive participation in the platform meetings and a significant increase in farmer knowledge levels on the challenges posed by climate change and the resultant extreme events. The platform also facilitated the adoption of best-bet practices that contribute towards CSA when farmers both diversify their production and decrease the use of mineral fertilizers. Our findings suggest that innovation platforms can facilitate the collective understanding and use of CSA options corresponding to local conditions and priorities.