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Agroforestry systems comprise trees and crops, or trees and pastures within the same field. Globally, they cover approximately 1 billion hectares of land and contribute to the livelihoods of over 900 million people. Agroforestry systems have the capacity to sequester large quantities of carbon (C) in both soil and biomass. However, these systems have not yet been fully considered in the approach to C accounting developed by the Intergovernmental Panel on Climate Change, largely due to the high diversity of agroforestry systems and scarcity of relevant data. Our literature review identified a total of 72 scientific, peer-reviewed articles associated with biomass C storage (50) and with soil organic carbon (SOC) (122), containing a total of 542 observations (324 and 218, respectively). Based on a synthesis of the reported observations, we are presenting a set of Tier 1 coefficients for biomass C storage for each of the eight main agroforestry systems identified, including alley cropping, fallows, hedgerows, multistrata, parklands, shaded perennial-crop, silvoarable and silvopastoral systems, disaggregated by climate and region. Using the same agroforestry classification, we are presenting a set of stock change factors ( F _LU ) and SOC accumulation/loss rates for three main land use changes (LUCs): cropland to agroforestry; forest to agroforestry; and grassland to agroforestry. Globally, the mean SOC stock change factors (± confidence intervals) were estimated to be 1.25 ± 0.04, 0.89 ± 0.07, and 1.19 ± 0.10, for the three main LUCs, respectively. However, these average coefficients hide huge disparities across and within different climates, regions, and types of agroforestry systems, highlighting the necessity to adopt the more disaggregated coefficients provided herein. We encourage national governments to synthesize data from local field experiments to generate country-specific factors for more robust estimation of biomass and SOC storage.

Landscape scale quantification enables farmers to pool resources and expertise. However, the problem remains of how to quantify these gains. This article considers current greenhouse gas (GHG) quantification methods that can be used in a landscape scale analysis in terms of relevance to areas dominated by smallholders in developing countries. In landscape scale carbon accounting frameworks, measurements are an essential element. Sampling strategies need careful design to account for all pools/fluxes and to ensure judicious use of resources. Models can be used to scale-up measurements and fill data gaps. In recent years a number of accessible models and calculators have been developed which can be used at the landscape scale in developing country areas. Some are based on the Intergovernmental Panel on Climate Change (IPCC) method and others on dynamic ecosystem models. They have been developed for a range of different purposes and therefore vary in terms of accuracy and usability. Landscape scale assessments of GHGs require a combination of ground sampling, use of data from census, remote sensing (RS) or other sources and modelling. Fitting of all of these aspects together needs to be performed carefully to minimize uncertainties and maximize the use of scarce resources. This is especially true in heterogeneous landscapes dominated by smallholders in developing countries.

This letter is intended to help potential users select the most appropriate calculator for a landscape-scale greenhouse gas (GHG) assessment of activities for agriculture and forestry. Eighteen calculators were assessed. These calculators were designed for different aims and to be used in different geographical areas and they use slightly different accounting methodologies. The classification proposed is based on the main aim of the assessment: raising awareness, reporting, project evaluation or product assessment. When the aims have been clearly formulated, the most suitable calculator can be selected from the comparison tables, taking account of the geographical area and the scope of the calculation as well as the time and skills required for the calculation. The main issues for interpreting GHG assessments are discussed, highlighting the difficulty of comparing the results obtained from different calculators, mainly owing to differences in scope, calculation methods and reporting units. A major problem is the poor accounting for land use change; the calculators are usually able to account satisfactorily for other emission sources. One of the main challenges at landscape-scale level is to produce a realistic assessment of the various production systems as the uncertainty levels are very high. The results should always give some indication of the link between GHG emissions and the productivity of the area, although no single indicator is able to encompass all the services produced by agriculture and forestry (e.g. food, goods, landscape value and revenue).