Abstract
A simple soil carbon model, the Introductory Carbon Balance Model (ICBM), is useful for projecting soil C dynamics in temperate and tropical land-use systems. A spreadsheet-based version of ICBM is presented, with an emphasis on African and short-and long term projections under variable conditions (climate, crops, soil). ICBM has two compartments, young and old soil C, and five parameters, intended to project soil C dynamics in a 30-year perspective even when detailed data are lacking. Information necessary is a rough estimate of annual carbon input to soil, a coarse measure of residue quality and some information about climate. If basic weather station data and water-related soil properties are available, more exact projections can be made. Typically, the model is used for answering questions such as: (1) If crop residues are returned to the field, how much will soil carbon increase after 30 years? (2) With limited local data available, will rough estimates (climate zone and crop yield etc) still make projections possible? Compared with more complex models, this approach is rapid and simple and yet still gives accurate results. The model is available as an Excel® spreadsheet, and which projections can be made and effects of different agricultural treatments can be compared. Here, agricultural field experiments in Africa are used to show how ICBM rapidly can be parameterized for conditions different from those it was originally calibrated for, and how projections can be made from this base parameterization. Concepts behind modeling approaches, as well as possible improvements, are also discussed. Key words: Soil carbon, agriculture, modeling, carbon sequestration, Africa.
Highlights
This paper presents a spreadsheet-based version of Introductory Carbon Balance Model (ICBM) in order to aid soil scientists and managers of long-term experiments, with an emphasis on African conditions, with short-and long term projections under variable conditions
Soil carbon and its dynamics has been recognized for a long time as a crucial soil component for example, (Tenney and Waksman, 1929; Henin and Dupuis, 1945), but with the recognition of soils as sources/sinks for the greenhouse gas CO2, there has been a major surge in the development of soil carbon modeling
A variety of models have been used to simulate soil carbon dynamics within African agricultural field experiments, including RothC (Diels et al, 2004; Farage et al, 2007b; Kamoni et al, 2007) and Century (Woomer, 1993; Tschakert et al, 2004; Farage et al, 2007a; Kamoni et al, 2007), but Agricultural Production Systems Simulator (APSIM) (Micheni et al, 2004) and other models have been applied. The complexity of these models are related to the number of storage pools used to simulate soil carbon dynamics, and naturally to how many and how complex drivers are included in the model
Summary
This paper presents a spreadsheet-based version of Introductory Carbon Balance Model (ICBM) in order to aid soil scientists and managers of long-term experiments, with an emphasis on African conditions, with short-and long term projections under variable conditions (climate, cropping system and soil types). A variety of models have been used to simulate soil carbon dynamics within African agricultural field experiments, including RothC (Diels et al, 2004; Farage et al, 2007b; Kamoni et al, 2007) and Century (Woomer, 1993; Tschakert et al, 2004; Farage et al, 2007a; Kamoni et al, 2007), but Agricultural Production Systems Simulator (APSIM) (Micheni et al, 2004) and other models have been applied. A spreadsheet-based version of ICBM is presented and intended to assist soil scientists and managers of longterm experiments, with emphasis on African conditions interested in soil C projections using limited climate, cropping systems and soil type data This tool is aimed towards non-modelers, with the intent of providing a rapid means of producing estimates of impacts from various future management scenarios or to assess the sensitivity of existing long-term data in response to various experimental treatments. This provided a common basis for comparing modeling results and ease of use to these other approaches
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