A functional ecology approach to define a conceptual and participatory method for designing species mixtures: a case study on nitrogen cycling and weed control

In agriculture, species mixtures can provide ecosystem services and make agroecosystems more resilient. In particular, weed control and improved nitrogen cycling are much sought-after services provided by species mixtures. However, there is a lack of knowledge about the choice of species to mix to provide these services. Using different sources of knowledge, we therefore investigated the utilization of the Trait-Function-Service (TFS) approach of functional ecology as a way of representing the functioning of species mixtures in order to help in the choice of species. The novelty here is the use of a generalizable framework integrating empirical knowledge and scientific knowledge to establish the link between species traits and the ecosystem services they provide. Consequently, our objective is to (i) create functional trees that reflect how mixtures of species work to control weeds and improve nitrogen cycling; and (ii) identify the rules for assembling the traits that enable these two ecosystem services to be provided, which can be used to design mixtures. To do this, we organized four knowledge exchange workshops, two on weed control and two on improving nitrogen cycling. These workshops involved scientists, advisors, and farmers to mobilize their expertise. Our results show that the improvement of nitrogen cycling depends on the achievement of the meta-functions “favour and diversify the sources of nitrogen”, “reduce nitrogen losses” and “improve nitrogen use efficiency”. The weed control service is composed of the meta-functions “increase the competition towards the weeds” and “avoid weed germination/emergence”. We show that providing an ecosystem service depends on multiple traits and that the same trait can be important for providing different ecosystem services. The empirical knowledge of farmers can differ significantly from that of scientists. Integrating the knowledge of farmers into functional trees highlights that expert knowledge, derived from experience gained in specific contexts, can be decontextualized to produce generic knowledge.