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Mathematical modeling for improved greenhouse gas balances, agro‐ecosystems, and policy development: lessons from the Australian experience
Author(s) -
Moore Andrew D.,
Eckard Richard J.,
Thorburn Peter J.,
Grace Peter R.,
Wang Enli,
Chen Deli
Publication year - 2014
Publication title -
wiley interdisciplinary reviews: climate change
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.678
H-Index - 75
eISSN - 1757-7799
pISSN - 1757-7780
DOI - 10.1002/wcc.304
Subject(s) - greenhouse gas , environmental science , environmental resource management , ecosystem , agriculture , environmental economics , computer science , ecology , economics , biology
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 This article is categorized under: Integrated Assessment of Climate Change > Applications of Integrated Assessment to Climate Change The Carbon Economy and Climate Mitigation > Policies, Instruments, Lifestyles, Behavior