SHAMBA: Assessing Climate Change Mitigation in Agriculture in Malawi

By Nicholas Berry, Researcher in the School of GeoSciences, University of Edinburgh

This week marks the second week of the 38^th session of the Subsidiary Body for Scientific and Technological Advice (SBSTA) to the United Nations Framework Convention on Climate Change (UNFCCC), where one of the many topics on tap was land-based climate change mitigation efforts. Today Dr. Berry, who presented the SHAMBA tool at a CCAFS side event last week during the SBSTA, addresses the need to streamline the accounting of climate change mitigation projects in agricultural landscapes.
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Funding for smallholder agriculture can come from a variety of sources, including the sale of carbon credits or certified commodities, as well as more traditional environmental and development projects and initiatives. An increasing number of sources now link funding to performance. The reduction and removal of greenhouse gas emissions is a key factor in projects that target climate change mitigation finance, and is an important consideration for governments and funders supporting agricultural projects. When accounting for greenhouse gas emissions and removals there is a trade-off between the precision of estimates of mitigation benefits and the costs associated with monitoring them. This typically means that different approaches to monitoring mitigation benefits are used depending on the nature of the project. While this is a pragmatic solution, it has led to the proliferation of diverse accounting methodologies and presents difficulties for making comparisons across projects, particularly if the aims or funding sources for those projects differ.

To begin addressing this challenge, a team at the University of Edinburgh has developed the Small-Holder Agriculture Mitigation Benefit Assessment (SHAMBA) methodology to provide an approach to accounting for greenhouse gas emissions and removals from agricultural interventions that meets a broad range of accounting requirements. By employing process-based models for accumulation of carbon in soils, that can be parameterised with environmental data and information on how activities are carried out, the SHAMBA methodology has the flexibility to be implemented with input data at a resolution that is appropriate to the accounting purpose.

For projects where climate change mitigation is viewed as a co-benefit rather than the main aim of the project, the use of regional level environmental data and a description of how the agricultural practices are supposed to be carried out may be sufficient. A project trying to sell carbon offsets could use the same approach, but would require site-specific environmental data and information about how activities are carried out at a very local level. This means the same accounting approach can be used across a portfolio of projects that includes a variety of funding sources.

So far the SHAMBA methodology has been used with local data to estimate the mitigation benefit of climate-smart agriculture projects at 15 sites in Malawi and with regional level data as a component of the Integrated Assessment of Land Use Options for Climate Change Mitigation and Adaptation in Malawi (LTSI 2013). The methodology is currently under review for validation under the Plan Vivo Standard, which would make it available for use by community based projects throughout sub-Saharan Africa.

The SHAMBA methodology can be implemented in a user friendly interface that allows all users access to the information they require. Ecometrica is Our Ecosystem platform for discovering and sharing spatial data has been used for a prototype application for assessing the mitigation benefits of climate-smart agriculture in Malawi was presented last week at a side event to the UNFCCC SBSTA meeting in Bonn, hosted by the Climate Change, Agriculture and Food Security research programme of the CGIAR.

Read more
Berry, NJ and CM Ryan. 2013. Overcoming the Risk of Inaction from Emissions Uncertainty in Smallholder Agriculture. Environmental Research Letters 8: 011003.

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