Root architectural traits that increase topsoil foraging are advantageous for phosphorus acquisition but may incur tradeoffs for the acquisition of deep soil resources such as water. To examine this relationship, common bean genotypes contrasting for rooting depth were grown in the field and in the greenhouse with phosphorus stress, water stress and combined phosphorus and water stress. In the greenhouse, water and phosphorus availability were vertically stratified to approximate field conditions, with higher phosphorus in the upper layer and more moisture in the bottom layer. Under phosphorus stress, shallow-rooted genotypes grew best, whereas under drought stress, deeprooted genotypes grew best. In the combined stress treatment, the best genotype in the greenhouse had a dimorphic root system that permitted vigorous rooting throughout the soil profile. In the field, shallow-rooted genotypes surpassed deep-rooted genotypes under combined stress. This may reflect the importance of early vegetative growth in terminal drought environments. Our results support the hypothesis that root architectural tradeoffs exist for multiple resource acquisition, particularly when resources are differentially localised in the soil profile. Architectural plasticity and root dimorphism achieved through complementary growth of distinct root classes may be important means to optimise acquisition of multiple soil resources.

Crop adaptation to climate change requires accelerated crop variety introduction accompanied by recommendations to help farmers match the best variety with their field contexts. Existing approaches to generate these recommendations lack scalability and predictivity in marginal production environments. We tested if crowdsourced citizen science can address this challenge, producing empirical data across geographic space that, in aggregate, can characterize varietal climatic responses. We present the results of 12,409 farmer-managed experimental plots of common bean (Phaseolus vulgarisL.) in Nicaragua, durum wheat (Triticum durumDesf.) in Ethiopia, and bread wheat (Triticum aestivumL.) in India. Farmers collaborated as citizen scientists, each ranking the performance of three varieties randomly assigned from a larger set. We show that the approach can register known specific effects of climate variation on varietal performance. The prediction of variety performance from seasonal climatic variables was generalizable across growing seasons. We show that these analyses can improve variety recommendations in four aspects: reduction of climate bias, incorporation of seasonal climate forecasts, risk analysis, and geographic extrapolation. Variety recommendations derived from the citizen science trials led to important differences with previous recommendations.

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SUMMARYRapid 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.

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