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Intercropping, by capitalizing on positive biodiversity–productivity relationships, represents a promising option to increase agricultural sustainability. However, the complexity and context-dependency of plant–plant interactions can make it challenging for farmers to find suitable crop combinations. Furthermore, intercropping is usually implemented with standard inter-row spacing and plant densities based on monoculture practices, which might not be the ideal configuration to maximize yield. Here we present a spatially-explicit yield analysis method based on plant ecological interaction models that allowed to optimize crop species combinations and spatial configurations for maximal yield in intercropped systems. We tested this method with three crop species, namely oat, lupine, and camelina. In a first step, field experiments in which crop density and adjacent crop type were varied provided us with indications on which species would compete more with each other. The results showed us that oat and camelina strongly competed with each other. In addition, the distance experiments allowed us to understand how the changes in yield associated with the presence of neighbors vary with distance. This allowed us to find the sets of parameters (identity of neighbors, sowing density, distances between individuals) that optimise intercrop yield (measured as Land Equivalent Ratio [LER]) for the three considered species. Specifically, we show that alternating rows of species led to higher LERs than a homogeneous species mixing, and that 3-species combinations are not necessarily more performant than the best 2-species combinations. In addition, we show that increasing the density of oat is generally beneficial for LER, while increasing the density of lupine is not. By modelling crop yield from simple and reproducible density and distance experiments, our results allow to optimize crop mixtures in terms of species combinations and spatial configurations, for maximal crop yield. [ABSTRACT FROM AUTHOR]

Recent meta-analyses demonstrate that intercropping can increase the land use efficiency of crop production by 20–30 % on average, indicating a strong potential contribution to sustainable intensification. However, there is substantial variability around this average: individual studies range from half to double the land productivity of monocrops. Legume-cereal intercrops and intercrops with high temporal niche separation tend to be more productive than the average, but these two combination types are not always suitable. There is a need to explore other possibilities to achieve productive intercrops. We explored whether two simple functional traits involved in radiation use, plant vegetative height and specific leaf area (SLA), could be used to predict intercrop productivity. Height and SLA together are associated with key plant life-history and resource economy strategies determining competitiveness and tolerance of competition, especially with regard to light, and could therefore be expected to underpin overyielding in intercrops. In the first year of our study, we grew crops as monocrops at one site in Kenya and measured their height and SLA. In the second year, we grew crops in monocrop, intercrop, and single plant treatments at two sites in Kenya and one site in Nigeria. Together, these treatments allowed us to identify whether each intercrop combination overyielded or underyielded, and whether any overyielding was driven by facilitation and/or differences in inter- vs intraspecific competition. We then related the strength of these interactions to the two traits. We found that intercrop grain yields varied in relation to the height and SLA of each species in the intercrop, but together these traits explained less than a third of variation in intercrop land equivalence ratios (LER). More variation could be explained by allowing for the effect of site, suggesting that the two traits interact with site conditions to determine yield. Biomass LERs responded differently to grain LERs, suggesting that plasticity in resource allocation in response to intercropping conditions may further influence yields. Our study found some evidence that combining species with traits indicating contrasting responses to competition (an avoidant species with a tolerant species) could increase resource use complementarity and thus intercrop overyielding. However, it was clear that other factors (such as additional traits, or the trait by site interaction) are needed to refine our understanding of intercrop productivity. A trait-based framework has potential to predict intercrop productivity, but simple measures of height and SLA alone are insufficient. • Intercrop yields vary from much lower than sole crops to much higher across different studies. • Plant traits may mediate competition and facilitation between intercrops, and predict yields. • Two simple traits, vegetative height and specific leaf area (SLA), explained some variance in yields. • Yields were higher when tall species with a low SLA were paired with short species with a high SLA. • Height and SLA alone cannot reliably predict intercrop yields: other traits should be explored. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms of community assembly may provide evidence to improve crop management, and in particular how weeds impact on crop yields. Focussing on plant functional traits and their diversity, we analysed a crop–weed interaction study with different levels of weed species and barley cultivar diversity to assess how weed species and barley cultivars respond to competition. Pre-emption of light resources by the taller barley did not impact on the weeds, with both weeds and barley showing similar order of magnitude shifts in height, specific leaf area and leaf dry matter content in response to crop–weed competition. These shifts were to a more conservative growth pattern, and suggest in this study a greater importance of below- than above-ground interactions in driving trait responses. The mixture of barley cultivars shifted the weeds to a more conservative growth pattern compared to the cultivar monocultures. The results indicate that cultivar mixtures could result in less need for weed control in arable fields, and possibly that the development of complementary cultivar mixtures could reinforce this effect. This confirms the results of other studies which show that mixtures either improve yields or make yields less variable in response to weed competition. [ABSTRACT FROM AUTHOR]