Current agricultural management practices, such as heavy machinery and elevated fertilizer use, often lead to soil degradation, affecting crop growth and environmental quality. Improved integrated farm management is therefore needed for agriculture to intensify sustainably.
This project will develop a decision support system for stakeholders and policymakers and will test it on typical regions of North-western Europe. It will evaluate the overall benefits and trade-offs of farm management approaches on the quality of soil, environment, and crop growth, using a selection of sustainability indicators to assess impacts on soil compaction as well as carbon, phosphorus and nitrogen cycles.
Aim of the project
The aim of this PhD project is to develop decision support system (DSS) to evaluate the benefits and trade-offs of farm management strategies on agricultural production and environmental impacts quality while accounting for the spatial variation in agro-ecosystem properties. Impacts will focus on crop yields, soil quality in terms of the soil balance of C, N, and P and soil compaction, and losses of N and P affecting air and water.
A combined meta-analytical and process-based modelling approach will be used to quantify relationships between management and impacts. The focus is on the following aspects: (i) crop growth, (ii) soil carbon, nitrogen, phosphorus and compaction and (iii) nutrient losses to the environment. Existing sustainability indicators as well as target and critical values from literature will serve as evaluation criteria for the impacts of management strategies on the quality of crop growth, soil and environment. The next objective is to develop a flexible and spatially-explicit model framework, integrating the indicators and target values into a multi-criteria impact assessment. The multi-criteria analysis will use distance to target or critical values to evaluate the sustainability of a management practice. This is with the goals of maximizing agricultural intensification (e.g., fertilizer use efficiency, crop yields, land use) and minimizing negative environmental externalities.
The outcome of this project will be a decision-support framework that can select appropriate management options for typical soil crop combinations in temperate regions. The DSS will be tested on typical agricultural regions in the Netherlands and North-western Europe to evaluate agricultural management and provide case-study applications of the tool for decision-making. The DSS will be based on a unique combination of modelling approaches and meta regression results to enable the evaluation of a range of agricultural management practices for a range of agro-ecosystem properties. Meta-regression will be applied to assess the influence of agro-ecosystem properties on the management-impact relationships.