The first project links farm nutrient use efficiency and social inequality. Low income farms have a history of poorly managing resources, leading to lower use efficiencies. However, few studies have quantified the links among resource-use efficiency and farm poverty or inequality levels.
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 the literature. Correlation analysis was applied to NUE data and GDP and GI. In order to better explain the impact of poverty and inequality in farms, the variables were also related to factors such as level of education and gender of farm manager and the level of farm technology.
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.
The second project, explores how adopting integrated crop/livestock farming systems, such as ‘Santa Fé’, may help to increase resource use efficiency and alleviate poverty and inequality. Novel aspects of integrated farms are assessed via synergetic modeling. It explores adopting integrated crop/livestock farming systems, such as ‘Santa Fé’, may help to increase resource use efficiency and alleviate poverty and inequality.
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.
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.
Funding: IIASA Postdoctoral Program
Program: Air Quality and Greenhouse Gases & Ecosystems Services and Management Programs
Dates: August 2015 – October 2016
Last edited: 07 November 2017
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