Development of an Agricultural Primary Productivity Decision Support Model: A Case Study in France

Abstract

Agricultural soils provide society with several functions, one of which is primary productivity. This function is defined as the capacity of a soil to supply nutrients and water and to produce plant biomass for human use, providing food, feed, fiber, and fuel. For farmers, the productivity function delivers an economic basis and is a prerequisite for agricultural sustainability. Our study was designed to develop an agricultural primary productivity decision support model. To obtain a highly accurate decision support model that helps farmers and advisors to assess and manage the provision of the primary productivity soil function on their agricultural fields, we addressed the following specific objectives: (i) to construct a qualitative decision support model to assess the primary productivity soil function at the agricultural field level; (ii) to carry out verification, calibration, and sensitivity analysis of this model; and (iii) to validate the model based on empirical data. The result is a hierarchical qualitative model consisting of 25 input attributes describing soil properties, environmental conditions, cropping specifications, and management practices on each respective field. An extensive dataset from France containing data from 399 sites was used to calibrate and validate the model. The large amount of data enabled data mining to support model calibration. The accuracy of the decision support model prior to calibration supported by data mining was ∼40%. The data mining approach improved the accuracy to 77%. The proposed methodology of combining decision modeling and data mining proved to be an important step forward. This iterative approach yielded an accurate, reliable, and useful decision support model for the assessment of the primary productivity soil function at the field level. This can assist farmers and advisors in selecting the most appropriate crop management practices. Embedding this decision support model in a set of complementary models for four adjacent soil functions, as endeavored in the H2020 LANDMARK project, will help take the integrated sustainability of arable cropping systems to a new level.

Modeling of Soil Functions for Assessing Soil Quality: Soil Biodiversity and Habitat Provisioning

“…In conclusion, the present DEX model predictions of the SB function are converging to the current and combined expert judgements of the SB function. In this way, quantification of the SB function, together with the quantification of the other four soil functions (Schröder et al, 2016;Sandén et al, 2019; and described elsewhere in this issue) is better placed in our attempts to optimize the multiple soil functions in agricultural landscapes, and hence the multifaceted role of soils to deliver a bundle of ecosystem services for farmers and citizens, and supporting land management and policy toward a more sustainable society.…”

Assessing the Climate Regulation Potential of Agricultural Soils Using a Decision Support Tool Adapted to Stakeholders' Needs and Possibilities

“…The model has been developed in the framework of the Horizon 2020 Landmark project, which aims to improve knowledge of the functions performed by European agricultural soils, while developing tools to assess the trade-offs between different soil functions. To achieve this, similar models have been developed for other soil functions: primary productivity (Sandén et al, 2019a), soil biodiversity and habitat provision (van Leeuwen et al, 2019), water regulation (Delgado et al, submitted) and nutrient recycling (Schröder et al, 2016). These separate models are brought together into a tool that assesses the extent to which agricultural soils perform these different soil functions (Debeljak et al, 2019).…”

A Field-Scale Decision Support System for Assessment and Management of Soil Functions

“…Finally, the ratio between the number of correctly predicted soil function performance levels and the total number of estimations was calculated. Different validation criteria were formulated for each soil function due to the differences in the availability and quality of empirical data Sandén et al, 2019;Delgado et al, unpublished 2 ;Van de Broek et al, unpublished 1 ). The data used for validation were not used for model calibration.…”

“…By doing so, the sensitivity of the outputs for changes in the input data has been increased. The detailed descriptions of each model are provided in separate papers in this issue Sandén et al, 2019;Delgado et al, unpublished 2 ;Van de Broek et al, unpublished 1 ). The model for nutrient cycling was developed earlier and published by Schröder et al (2016).…”

“…Primary productivity, as the top attribute, integrates the sub-models, which leads to an assessment of the capacity of a soil to produce biomass. A detailed description of the primary productivity model is given in Sandén et al (2019).…”