A modeling study was carried out into pea-barley intercropping in northern Europe. The two objectives were (a) to compare pea-barley intercropping to sole cropping in terms of grain and nitrogen yield amounts and stability, and (b) to explore options for managing pea-barley intercropping systems in order to maximize the biomass produced and the grain and nitrogen yields according to the available resources, such as light, water and nitrogen. The study consisted of simulations taking into account soil and weather variability among three sites located in northern European countries (Denmark, United Kingdom and France), and using 10 years of weather records. A preliminary stage evaluated the STICS intercrop model's ability to predict grain and nitrogen yields of the two species, using a 2-year dataset from trials conducted at the three sites. The work was carried out in two phases, (a) the model was run to investigate the potentialities of intercrops as compared to sole crops, and (b) the model was run to explore options for managing pea-barley intercropping, asking the following three questions: i) in order to increase light capture, would it be worth delaying the sowing dates of one species? ii) how to manage sowing density and seed proportion of each species in the intercrop to improve total grain yield and N use efficiency? iii) how to optimize the use of nitrogen resources by choosing the most suitable preceding crop and/or the most appropriate soil? It was found that (1) intercropping made better use of environmental resources as regards yield amount and stability than sole cropping, with a noticeable site effect, (2) pea growth in intercrops was strongly linked to soil moisture, and barley yield was determined by nitrogen uptake and light interception due to its height relative to pea, (3) sowing barley before pea led to a relative grain yield reduction averaged over all three sites, but sowing strategy must be adapted to the location, being dependent on temperature and thus latitude, (4) density and species proportions had a small effect on total grain yield, underlining the interspecific offset in the use of environmental growth resources which led to similar total grain yields whatever the pea-barley design, and (5) long-term strategies including mineralization management through organic residue supply and rotation management were very valuable, always favoring intercrop total grain yield and N accumulation.
A generic crop model (STICS) was adapted (STICS–Grassland) to model growth, yield, and environmental impacts of grasslands in France. It is a semimechanistic model combining equations of physiological processes and mathematical relationships between processes in a daily time step. The Information et Suivi Objectif des Prairies (ISOP; Grassland Information and Objective Survey) application was developed to estimate and map the real‐time status of grass growth and forage production in the 200 forage regions of France, to help decision makers anticipate forage availability in case of severe deficits. Initially, the model could not simulate long, severe droughts typical of Mediterranean regions when plant and tiller densities are significantly reduced. A tiller density module models the dynamics of tiller death during droughts. Since STICS is based on the concept of a mean plant (tiller) covering the whole field, variability was introduced through a γ law distribution of transpiration deficit by tiller, a threshold value imposing desiccation, and death to tillers reaching this level. Its second part generates incomplete or total recovery of tiller density through new tillering in the next wet season. Species and contrasting groups of cultivars within species can be characterized with a limited number of parameters.
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