Modelling ecosystem services of diversified agriculture 

Monocropping, the agricultural practice of growing a singular crop species on the same land every year, produces high yields at lower costs. Yet, growing just one species of crop on many acres of land can damage the soil, increase fertilizer demand, create pest problems, and damage the environment.

Diversified agriculture can lead to more sustainable systems, providing a range of services to society beyond agricultural production. Crop diversification, such as intercropping and cultivar mixtures, can stabilize the productivity of cropping systems, optimize the use of resources, and reduce negative environmental impacts and loss of biodiversity.

Modelling can be used to better understand the agricultural management of diverse systems and especially about how to integrate them into cropping systems to attain the ecosystem services targeted.

In a new article published in in silico Plants, INRAE researcher Dr. Noémie Gaudio and colleagues argue that a single modelling approach is not sufficient to capture the multiple processes and system components  critical to understand complex and diversified agroecosystems. Instead, they advocate for developing modelling solutions that borrows the strengths of different model types (e.g., process-based models and qualitative models).

In the article, the authors present a variety of examples of coupled modelling solutions to upscale models from local interactions to ecosystem services. These solutions depend upon the diversity of ecosystem services targeted and the extent of the temporal scale (e.g., instantaneous, daily, crop-cycle, rotation or long-term) and spatial resolution (e.g., plant, field or landscape, along with its multiple cultivated and uncultivated components) at which these services are developed.

According to the authors, those are not the only considerations combining models. Strategies to combine models should be identified according to the objectives of the study. Example of study objectives are: to understand the relative contributions of primary ecological processes to crop mixtures, to quantify impacts of the environment and agricultural practices, and to assess the resulting ecosystem services.

Because direct coupling of models is rarely feasible across all scales, the authors identified three alternative strategies for upscaling models from local interactions to ecosystem services:

• Inverse modelling, which connects models by identifying input parameters from simulated data from other models,
• Metamodelling, which connects models by developing a simpler model of outputs from a more complex model, and
• Hybrid modelling, which connects models by combining the strengths of existing models in a new model. The goal is to perform hierarchical modelling at multiple scales by including only the level of detail required to represent the critical processes involved in targeted outputs of the system.

The authors point out that reusing and coupling existing models faces several methodological and technical challenges. The need to support collaborative and distributed model design, reproducibility, and dissemination was addressed using Jupyter notebooks in a previous Botany One post.

The authors conclude by emphasizing that many outcomes of diversified agroecosystems remain to be explored, both experimentally and through the heuristic use of modelling. The practice of combining models to address plant diversity and predict ecosystem services at different scales is uncommon, but critical to support the spatial and temporal prediction of the many systems that could be designed.

READ THE ARTICLE:

Noémie Gaudio, Gaëtan Louarn, Romain Barillot, Clémentine Meunier, Rémi Vezy, Marie Launay, Exploring complementarities between modelling approaches that enable upscaling from plant community functioning to ecosystem services as a way to support agroecological transition, in silico Plants, 2021;, diab037, https://doi.org/10.1093/insilicoplants/diab037

This manuscript is part of in silico Plant’s Functional Structural Plant Model special issue.