Simplifying a complex computer model: Sensitivity analysis and metamodelling of an 3D individual-based crop-weed canopy model

Colas, Floriane; Gauchi, Jean-Pierre; Villerd, Jean; Colbach, Nathalie

doi:10.1016/j.ecolmodel.2021.109607

Cited by 4 publications

(2 citation statements)

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“…Compared to the complex FlorSys environment (Colas et al, 2021) the ODE approach is easy to handle. The implementation of stochastic elements concerning growth rates, allocation of weed seeds and weed emergence mimics the high level of variation in nature.…”

Section: B a Figurementioning

confidence: 99%

“…The mechanistic FlorSys model "virtual field" can partly cover this aspect (Colbach et al, 2021). While FLORSYS is very powerful, it is complex and requires a large number of parameters (Colas et al, 2021). An alternative approach is the use of coupled differential equations, which have a long tradition for modelling plant-plant interactions (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Modelling individual plants’ growth: competition of Viola arvensis and wheat

von Redwitz,

Lepke,

Richter

2024

Front. Agron.

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IntroductionCompetition by weeds is a severe threat to agricultural crops. While these days the broadcast of herbicides over the entire field is common praxis, new technologies promise to reduce chemical output by reducing the area sprayed. The maximum precision would be a single plant treatment. This precision will allow a single plant management, which requires single plant management decisions, which is far beyond the possibilities of current praxis. A plant specific management decision can only be made on the basis of a model simulation.Materials and methodsA simulation model was developed to evaluate the effect of spatially explicit weed management covering interaction between single plants. The governing equations consist of coupled nonlinear differential equations for growth and competition of crop and weed plants in a spatial setting i.e. a coordinate is assigned to each plant. The mutual interaction is determined by the parameters strength and range of competition. Furthermore, an experiment was carried out parallel to the development of the model involving wheat and Viola arvensis (Murr.), in which coordinates and growth curves for a large number of plants (~600) were recorded allowing for a reasonable parameterization of the model.Results and discussionThe model is able to evaluate spatially explicit management measures such as weed strip control based on the height growth of single plants. The model is capable of evaluating a variety of control measures such as the frequency and spatial allocation of treatments. In particular, the effect of the width of a treatment zone around the rows of the crop was simulated.ConclusionIn future, the developed model could be extended to a decision support system for single plant weed management. Making decisions plant-by-plant, allows to orchestrate the weed management in a way that takes into account competing goals in plant protection: yield and biodiversity.

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Section: B a Figurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modelling individual plants’ growth: competition of Viola arvensis and wheat

von Redwitz,

Lepke,

Richter

2024

Front. Agron.

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Global Sensitivity Analysis Using Polynomial Chaos Expansion on the Grassmann Manifold

Bazyleva

Garibay

Roy

2023

Lecture Notes in Computer Science

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Exploring complementarities between modelling approaches that enable upscaling from plant community functioning to ecosystem services as a way to support agroecological transition

et al. 2021

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Promoting plant diversity through crop mixtures is a mainstay of the agroecological transition. Modelling this transition requires considering both plant-plant interactions and plants’ interactions with abiotic and biotic environments. Modelling crop mixtures enables designing ways to use plant diversity to provide ecosystem services, as long as they include crop management as input. A single modelling approach is not sufficient, however, and complementarities between models may be critical to consider the multiple processes and system components involved at different and relevant spatial and temporal scales. In this article, we present different modelling solutions implemented in a variety of examples to upscale models from local interactions to ecosystem services. We highlight that modelling solutions (i.e. coupling, metamodelling, inverse or hybrid modelling) are built according to modelling objectives (e.g. understand the relative contributions of primary ecological processes to crop mixtures, quantify impacts of the environment and agricultural practices, assess the resulting ecosystem services) rather than to the scales of integration. Many outcomes of multispecies agroecosystems remain to be explored, both experimentally and through the heuristic use of modelling. Combining models to address plant diversity and predict ecosystem services at different scales remains rare but is critical to support the spatial and temporal prediction of the many systems that could be designed.

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Simplifying a complex computer model: Sensitivity analysis and metamodelling of an 3D individual-based crop-weed canopy model

Cited by 4 publications

References 52 publications

Modelling individual plants’ growth: competition of Viola arvensis and wheat

Modelling individual plants’ growth: competition of Viola arvensis and wheat

Global Sensitivity Analysis Using Polynomial Chaos Expansion on the Grassmann Manifold

Exploring complementarities between modelling approaches that enable upscaling from plant community functioning to ecosystem services as a way to support agroecological transition

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