Social and Environmental Inequalities Approached in the Rural World

In search for links between farm nutrient use efficiency and social inequality

Introduction

Low income farms have a history of poorly managing resources, leading to lower use efficiencies. However, few studies have quantified the links or causalities among resource use efficiency and farm poverty or inequality levels.

Methods

Survey data for gross domestic product (GDP) and Gini Index (GI) from census databases will be used and farm-level nitrogen use efficiency (NUE) data will be taken from scientific peer-reviewed literature. Analysis of correlation will be applied to NUE data and GDP and GI. In order to better explain the impact of poverty and inequality in farms, the variables will also be related to factors such as level of education and gender of farm manager and the level of farm technology.

Preliminary results

A non-linear decay of NUE vs. increasing GDP was observed using the pooled data sets (Figure1). However, this trend was not present in individual geopolitical regions, highlighting the need to increase the level of disaggregation within regions and countries.

Figure 1. Scatter plots for country level Nitrogen Use Efficiency (NUE, %) versus GDP for 80% of the world (overall) and by geopolitical region.

Modeling integrated farms: optimizing resource use, pollution control, and cost/benefit

Introduction

Adopting integrated crop/livestock farming systems, such as ‘Santa Fé’, may help to increase resource use efficiency and alleviate poverty and inequality. In this study, novel aspects of integrated farms are assessed via synergetic modeling.

Methods

Computational models for feed intake and nutrient supply of ruminants (RUMINANT) and soil-plant nutrient flows (Environmental Policy Integrated Model—EPIC) are concomitantly used to test the effects of novel forage types and better yielding breeding varieties of beef and dairy cattle.

Figure 2. Representation of synergetic relation between modeling tools for improved account of integrated farms.

Expected outcome

Outputs will be fed into the IIASA Global Biosphere Management Model (GLOBIOM), for enhanced accuracy of greenhouse gas emissions mitigation costs and land use change estimates.

Last edited: 02 March 2016