Stories 2 - MAgPIE stories #2

The Sub-Saharan Africa (SSA) region has experienced substantial population growth over the past decades while exhibiting weak governance, contributing to unsustainable agricultural production and land use. However, the importance of governance in improving food security and mitigating environmental degradation has been limited explored. Using an agro-economic dynamic optimization model, we investigate the impacts of governance performance on land use patterns, greenhouse gas (GHG) emissions, and food security in SSA region. Our findings underscore that improving governance performance could reduce emissions while ensure food security. Strong governance leads to less deforestation, further reducing GHG emissions in the Agriculture, Forestry, and Other Land Use (AFOLU) sector. Meanwhile, the scenario representing strong governance achieves higher crop yields, lower food prices and food expenditure, as well as improved self-sufficiency.

Fertilizer manufacturing subsidies (FMS) are recognized as an important factor contributing to China’s excessive fertilizer use by reducing fertilizer prices. In an effort to address this overuse, the Chinese government had phased out FMS by 2015. This study presents a comparative analysis of two environmental policies—fertilizer manufacturing subsidy removal and nitrogen taxation—on nitrogen pollution emissions and food security. Using an agro-economic land system model (MAgPIE), we find that imposing a nitrogen taxation is more effective for controlling nitrogen pollution emissions compared to FMS removal, based on nitrogen pollution reductions per unit cost. However, nitrogen taxation could lead to higher food prices and lower self-sufficiency, while FMS removal has marginal impacts on food security. An uncertainty analysis of fertilizer price is conducted through Monte Carlo simulation, highlighting the robustness of our model results.

I intend to start my PhD journey with MAgPIE as the primary tool, where my research will focus on regional spatial analysis aimed at mapping future land-use patterns, incorporating an analysis of the probability of adopting new agricultural innovations and their impacts on major climate indicators. This will involve integration of empirical analysis using data from national and global datasets, for India. A key part of my activities will be to identify the representation of feed baskets for India within MAgPIE and improve the accounting within the model. For this, I will be working on internal R packages (mruniverse, magclass, etc.) and try to improve the representation of feed baskets and livestock productivity in the model, for India. Through these ideas, combined with the modularity and spatio-temporal flexibility in MAgPIE, I seek to contribute valuable insights into the direction of sustainable agricultural practices in India.

MAgPIE was used for the update of the UN PRI’s Inevitable Policy Response (IPR) project, updating the modelling with the most recent changes in policy and demand. Materials available at: https://ipr.transitionmonitor.com/

Agricultural production costs make up less than half of total food prices for higher-income countries, and the farm share of food prices will likely further decrease globally. Added-value components such as transport, processing, marketing, and catering are of increasing importance in food value chains. Using a combined statistical and process-based modelling framework (the MAgPIE model), we derive and project the value-added component of food prices for 136 countries and 7 different food groups, for food-at-home and food-away-from-home. We confirm the declining importance of the producer share in consumer food prices across food products, and highlight the future evolution of consumer prices under a business-as-usual as well as a climate mitigation scenario.