Investigating the dynamics of resilience and greenhouse gas performance of pastoral cattle systems in southern Ethiopia

Highlights

• A model of a pastoral cattle system in Ethiopia was developed and used to investigate resilience.

• Four measures were analysed: livestock insurance; managed destocking; rangeland restoration; fodder planting.

• Destocking provides the biggest increase in production and profit, due to the way it changes the herd size and structure.

• Fodder planting and rangeland restoration increase production and profit. Insurance increases production but not profit.

• All of the measures increase the total GHG emissions but lead to little change in emissions intensity.

Abstract

CONTEXT

Pastoral and agro-pastoral (PAP) systems in East Africa face a range of challenges including increased climate variability. Various measures have been proposed to improve the resilience of pastoral/agro-pastoral (PAP) systems to drought. However, identifying the most effective measure for a given system and location is complicated, and tools are required to appraise measures on a consistent basis.

OBJECTIVE

This paper develops a model of a PAP system and uses it to assess the effects of four measures (Index-based livestock insurance, IBLI; Commercial destocking with an early warning system, EWS; Rangeland restoration, RR; Fodder planting, FP) on the resilience of the PAP system. It also quantifies the greenhouse gas (GHG) effects of the measures, thereby identifying potential trade-offs and synergies between the policy objectives of resilience and climate smart agriculture (CSA).

METHODS

A dynamic model of the Borena pastoral cattle system was developed to undertake the analysis. At its core is a herd model that calculates the changes in cattle population over time. Feed availability and drought occurrence affect fertility and mortality rates, which in turn determine the population and (meat and milk) production. A suite of indicators covering the three dimensions of CSA (increasing productivity, enhancing resilience and reducing GHG emissions) were developed, and used to compare the situation with and without measures.

RESULTS AND CONCLUSIONS

Destocking with an early warning system provides the biggest increases (relative to the no measure situation) in production and profit, due to the way it changes the herd size and structure. It maintains a larger herd than any of the other measures, and a greater proportion of the herd are adult females. Fodder planting and rangeland restoration provide moderate increases in production and profit. Index-based livestock insurance provides a moderate increase in protein production, but has no effect on profit, as it is designed to reduce risk rather than increase productivity or profit, at least in the short term.

All of the measures increase the total emissions relative to the no measure scenario. In terms of the three dimensions of climate-smart agriculture, IBLI leads to some improvements in productivity and resilience but leads to large increases in total emissions, and modest increases in emissions intensity (EI). EWS leads to large increases in productivity and resilience. However, it also leads to large increases in total emissions and a mixed effect on EI. FP and RR improve productivity and increase total emissions, while having little effect on EI or resilience.

SIGNIFICANCE

This paper illustrates the way in which systems dynamic model can be used to appraise measures designed to improve resilience. The result identify potential synergies and tensions between the goals of resilience and climate smart agriculture, and raises the question of whether fully climate-smart goals are viable in these systems.