Crowd-Sourcing Management Activity Data to Drive GHG Emission Inventories in the Land Use Sector

Abstract:

Greenhouse gas (GHG) emissions from the land use sector constitute the largest source category for many countries in Africa. Enhancing C sequestration and reducing GHG emissions on managed lands in Africa has to potential to attract C financing to support adoption of more sustainable land management practices that, in addition to GHG mitigation, can provide co-benefits of more productive and climate-resilient agroecosystems. However, robust systems to measure and monitor C sequestration/GHG reductions are currently a significant barrier to attracting more C financing to land use-related mitigation efforts.

Anthropogenic GHG emissions are driven by a variety of environmental factors, including climate and soil attributes, as well as human-activities in the form of land use and management practices. GHG emission inventories typically use empirical or process-based models of emission rates that are driven by environmental and management variables. While a lack of field-based flux and C stock measurements are a limiting factor for GHG estimation, we argue that an even greater limitation may be availabiity of data on the management activities that influence flux rates, particularly in developing countries in Africa.

In most developed countries there is a well-developed infrastructure of agricultural statistics and practice surveys that can be used to drive model-based GHG emission estimations. However, this infrastructure is largely lacking in developing countries in Africa. While some activity data (e.g. land cover change) can be derived from remote sensing, many key data (e.g., N fertilizer practices, residue management, manuring) require input from the farmers themselves. The explosive growth in cellular technology, even in many of the poorest parts of Africa, suggests the potential for a new crowd-sourcing approach and direct engagement with farmers to ‘leap-frog’ the land resource information model of developed countries. Among the many benefits of this approach would be high resolution management data to support GHG inventories at multiple scales. We present an overall conceptual model for this approach and examples from on-going projects in Africa employing direct farmer engagement, cellular technology and apps to develop this information resource.