There is a lot of interest in the contribution that agroforestry can make to reverse land degradation and create resilient multifunctional landscapes that provide a range of socio-economic benefits. The agroforestry research agenda has been characterized by approaches that promote a few priority tree species, within a restricted set of technological packages. These have often not spread widely beyond project sites, because they fail to take account of fine scale variation in farmer circumstances. New methods are needed to generate diverse sets of agroforestry options that can reconcile production and conservation objectives and embrace varying local conditions across large scaling domains. Here, we document a novel approach that couples local knowledge acquisition with structured stakeholder engagement to build an inclusive way of designing agroforestry options. We applied this approach in the eastern part of the Democratic Republic of Congo (DRC) where armed conflict, erratic governance and poverty have resulted in severe pressure on forests in the Virunga National Park, a global biodiversity hotspot. Around the park, natural resources and land are severely degraded, whereas most reforestation interventions have consisted of exotic monocultures dominated by Eucalyptus species grown as energy or timber woodlots mainly by male farmers with sufficient land to allocate some exclusively to trees. We found that structured stakeholder engagement led to a quick identification of a much greater diversity of trees (more than 70 species) to be recommended for use within varied field, farm and landscape niches, serving the interests of a much greater diversity of people, including women and marginalized groups. The process also identified key interventions to improve the enabling environment required to scale up the adoption of agroforestry. These included improving access to quality tree planting material, capacity strengthening within the largely non-governmental extension system, and collective action to support value capture from agroforestry products, through processing and market interventions. Integrating local and global scientific knowledge, coupled with facilitating broad-based stakeholder participation, resulted in shifting from reliance on a few priority tree species to promoting tree diversity across the Virunga landscape that could underpin more productive and resilient livelihoods. The approach is relevant for scaling up agroforestry more generally.

Rapid climatic and socio-economic changes challenge current agricultural R&D capacity. The necessary quantum leap in knowledge generation should build on the innovation capacity of farmers themselves. A novel citizen science methodology, triadic comparisons of technologies or tricot, was implemented in pilot studies in India, East Africa, and Central America. The methodology involves distributing a pool of agricultural technologies in different combinations of three to individual farmers who observe these technologies under farm conditions and compare their performance. Since the combinations of three technologies overlap, statistical methods can piece together the overall performance ranking of the complete pool of technologies. The tricot approach affords wide scaling, as the distribution of trial packages and instruction sessions is relatively easy to execute, farmers do not need to be organized in collaborative groups, and feedback is easy to collect, even by phone. The tricot approach provides interpretable, meaningful results and was widely accepted by farmers. The methodology underwent improvement in data input formats. A number of methodological issues remain: integrating environmental analysis, capturing gender-specific differences, stimulating farmers' motivation, and supporting implementation with an integrated digital platform. Future studies should apply the tricot approach to a wider range of technologies, quantify its potential contribution to climate adaptation, and embed the approach in appropriate institutions and business models, empowering participants and democratizing science.

In the past two decades, a growing body of work on research stations and farmers' fields in Southern Africa has provided evidence that fertilizer trees can improve the productivity of land, increase crop yields and contribute towards climate change mitigation and adaptation. In a recent issue of Experimental Agriculture, Coe et al. (2019) published analysis of risks associated with adopting agroforestry in Malawi. The article contains several factual inaccuracies about agroforestry and misinterpretations of earlier work. Our aim in this correspondence is, therefore, to point out the key problems, seek clarification from Coe and co-workers, and stimulate wider scientific debate on the perceived risks of adopting agroforestry.

Our paper ‘Loading the dice in favour of the farmer: reducing the risk of adopting agronomic innovations’ revealed mean increases but also large variation in the impact of four agroforestry practises on maize yield, as experienced by farmers in Malawi. This prompted a response from Sileshi and Akinnifesi that was critical of the data and methods used. Their main concern was that farmers did not necessarily manage crops identically in plots with and those without trees, so the yield differences that we measured may be partly caused by these differences in crop management. We argue here that it is valid and useful to look at the actual effect on crop yield of farmers having trees intercropped with maize, rather than controlling for how the crop is managed, because this is what happens in the real world. Farmers respond to having trees in their field by treating their crop differently, so this is part of the system response to having trees in fields. Attempts to eliminate this will result in measuring an artefact rather than the real impact of trees on crop yield. By doing this, we revealed important variation in the impact of trees on crop yield amongst farmers, and we argue that it is important to explore, assess and communicate to farmers and development actors the extent and implications of this variation. Understanding the contextual factors that determine who is likely to benefit most from an innovation and for whom it is less suitable can then be incorporated in scaling up, so that targeting of innovations and the appropriateness of messages given to farmers are continuously refined.