This training provides basic training in the use of R statistical software for statistical analysis. The training covers basic statistics with examples and exercises. Practical exercise is also included on modeling of plantation forests using data collected in the field.

The purpose of this training is to improve trainees knowledge and skills for measuring biomass and soil carbon stocks  as well as GHGs on agricultural landscape. Several methodological options for estimating carbon pools are available including harvest method, GHGs flux measurements, satellite/remote sensing, modelling, plotless method and plot method. Each method has its own merits and limitations. This training mainly focuses on plot carbon stocks estimation and GHGs estimation methods based on IPCC (2006) guideline. These are the most suitable, cost-effective, commonly adopted and familiar method. And also, it is commonly implemented on project-based scenarios and small-scale carbon pool estimates.  As carbon inventory is costly operation and not all carbon pools are relevant to all land-use categories, we focus on the carbon pools that are heavily affected by interventions. Accordingly, standing above and belowground biomasses estimations methods are considered. Deadwood and litter carbon stocks estimation methods are not accounted. This is due to deadwood and litter mostly account < 10% of the total biomass carbon stocks, and take a longer time for accumulation in the land uses. For instance, deadwood may occur largely in natural forests, but is rare in new plantations, agroforestry systems, soil conservation structures, grasslands and croplands. The training will consider the most relevant methodological requirements out of the standard biomass and soil carbon stocks accounting procedures recognized by biomass inventory and IPCC (2006). Some modifications are also done on methodological approaches based on the context of agricultural landscape management interventions.

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National Measuring, Reporting and Verification Capacity Building Towards Climate Resilient Development in Ethiopia.

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