Know more

Objectives

Species mixtures under many production situation provide benefits in terms of yield and yield stability, but the benefits vary substantially according to the choice of species, their spatio-temporal arrangement, and their management. Mixtures are not always more productive and resilient than sole crops.

Models and experiments are needed to identify under which conditions, and with which species combinations and management mixing is beneficial.

WP5 will use heterogeneous plant population models, based on functional-structural plant models for single plants, and mixed species crop models to predict the performance of species mixtures considering a range of EU weather conditions, soil types and climate change scenarios. WP5 will assess yield performance and inter-annual stability of species mixtures and identify optimised species trait combinations to guide plant breeding (WP4). WP5 will analyse the efficiency of species mixtures to control weeds under diverse crop management practices and cropping systems and to increase resilience to climate change.

Modelling in WP5 aims to identify management practices and species assemblages that are well adapted to a wide range of European pedo-climatic conditions under current and future climates.

Synergies among models and interaction with other ReMIX WPs

A variety of species mixtures models with different temporal and spatial scales of resolution will be used in WP5 to address aims and objectives at different spatial and temporal scales:

-          Mechanistic models with a specific version for intercrops that will be developed in WP2 (new intercrop Functional Structural Plant Modelling - FSPM) and WP3 (FlorSys model; Colbach et al., 2014a)

-          Existing process-based crop models like STICS (Brisson et al., 2004) and

-          Recently developed process-based models specifically designed for heterogeneous intercrop systems (Gou et al., 2016)

-          A qualitative .model to represent the impact of intercropping on multiple pests (IPSIM; Aubertot and Robin, 2013).

WP5 is central to the project as it will scale up field results from WP1, WP2, WP3 and WP4 to deliver novel knowledge on choices of combinations of species and varieties, management practices and spatial designs of mixtures to identify profitable and feasible practices in WP6:

-          Farmers’ experiences and needs (WP1) will provide inspiration for designing in silico experiments that are relevant to stakeholders

-          Experiments (WP2-4) will provide data for parameterisation (e.g. species traits) as well as data for evaluating model performance (yields and growth dynamics under varying conditions) under a wide range of pedo-climatic conditions.

-          Modelling and simulation activities will contribute to feeding the ReMIX tool box and the main findings will be summarized in technical and practical booklets (WP6).

ReMIX partners held a modelling workshop in Wageningen in September 2017 to create synergies between the partners involved in WP5 and find links with other WPs, such as WP2 and WP4.

Identify by simulation the efficient plant traits and species trait complementarities to guide plant breeding, spatial arrangement and species assemblages

WP5 aims to identify trait combinations that confer high yields in mixed crops, and that can thus serve as phenotypic markers in breeding. Functional Structural Plant Modelling (FSPM) will be used to investigate how different traits interact to determine yield in heterogeneous plant populations consisting of two species, one of which is a legume. A generic FSPM is developed for some of the key species in ReMIX. This FSPM should be able to handle variation in multiple traits. Collaboration with WP4 will be developed in this task, as WP4 will conduct the necessary experiments for measuring the genetic variation in traits that will be explored in the modelling effort. WP4 and WP5 partners have already agreed on a list of key traits that need to be measured to feed the FSP modelling. 

Optimizing by simulation the efficacy species mixtures for weed control

Partners have reviewed the cropping systems already simulated with the FLORSYS model. They also reviewed the corresponding indicators of weed impact on crop production and biodiversity. Similarly, partners have set up a list of observations and measurements on weed phenology that should be performed on field experiments in order to improve the FLORSYS and other weed models used by partners.

In collaboration with partners in WP3, FLORSYS simulations were run over several hundreds of cropping systems (mostly with single crops) from 7 French regions in order to identify crop traits that reduce weed-caused yield loss.

In the frame of this task, the results of models with different complexity will be compared as will their ability to simulate weed population dynamics and related damage in different cropping systems. In this analysis, the FLORSYS model will be used as a benchmark.

The main results in this task have been:

-          An analysis of the role of different life cycle stages and their potential contribution to ecological weed management. This analysis reveals the sensitivity of different life cycle stages of a weed and to what extent this sensitivity depends on the characteristic traits of a weed species.

-          An analysis to determine whether synergies between different cultural control measures exist and can be exploited to formulate adequate weed control strategies.

-          An extension of the FLORSYS basic weed population model to allow for the inclusion of crop rotations.

Simulating the effect of climate change and climate variability scenarios on species mixtures

A meeting was organized in Avignon in November 2017 to discuss the current status and future improvements of the STICS intercrop model. Researchers at the University of Hohenheim and INRA will work on the source code of the model and exchange their modifications. A literature review on the performance of species mixtures under climate change was made. First simulations were made to evaluate the effect of CO₂ on the performance of a pea-barley intercrop.