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WIREs Clim Change
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Mathematical modeling for improved greenhouse gas balances, agro‐ecosystems, and policy development: lessons from the Australian experience

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If the land sector is to make significant contributions to mitigating anthropogenic greenhouse gas (GHG) emissions in coming decades, it must do so while concurrently expanding production of food and fiber. In our view, mathematical modeling will be required to provide scientific guidance to meet this challenge. In order to be useful in GHG mitigation policy measures, models must simultaneously meet scientific, software engineering, and human capacity requirements. They can be used to understand GHG fluxes, to evaluate proposed GHG mitigation actions, and to predict and monitor the effects of specific actions; the latter applications require a change in mindset that has parallels with the shift from research modeling to decision support. We compare and contrast 6 agro‐ecosystem models (FullCAM, DayCent, DNDC, APSIM, WNMM, and AgMod), chosen because they are used in Australian agriculture and forestry. Underlying structural similarities in the representations of carbon flows though plants and soils in these models are complemented by a diverse range of emphases and approaches to the subprocesses within the agro‐ecosystem. None of these agro‐ecosystem models handles all land sector GHG fluxes, and considerable model‐based uncertainty exists for soil C fluxes and enteric methane emissions. The models also show diverse approaches to the initialisation of model simulations, software implementation, distribution, licensing, and software quality assurance; each of these will differentially affect their usefulness for policy‐driven GHG mitigation prediction and monitoring. Specific requirements imposed on the use of models by Australian mitigation policy settings are discussed, and areas for further scientific development of agro‐ecosystem models for use in GHG mitigation policy are proposed. WIREs Clim Change 2014, 5:735–752. doi: 10.1002/wcc.304

Comparison of enteric methane emissions (as grams of methane per kilogram of dry matter intake) predicted by a number of different models. See text for details.
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Pools and flows of soil organic carbon that are followed in a range of agro‐ecosystem models. Green boxes indicate pools of undecomposed plant residues (‘fresh organic matter’); blue boxes indicate pools of decomposer organisms; gray pools indicate humus or humus‐like organic matter; and white boxes denote recalcitrant (inert or very slowly‐decomposing) organic matter. The AgMod model combines fresh organic matter and composers in a single ‘fast’ pool. Arrows denote flows of soil organic carbon between pools or the release of carbon dioxide to the atmosphere. The expected residence time of carbon in each pool under reference conditions (soil clay content 0.20, 15°C, optimal moisture and pH, and residue C:N ratio of 40) is shown in years. Modeled residence times will generally be longer—by varying amounts—because the models have different modifier functions for soil temperature and moisture. Note that WNMM has recently been modified to include a soil charcoal pool.
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The Carbon Economy and Climate Mitigation > Policies, Instruments, Lifestyles, Behavior
Integrated Assessment of Climate Change > Applications of IA to Climate Change

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