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Get Free AccessMathematical models, such as the DNDC (DeNitrification DeComposition) model, are powerful tools that are increasingly being used to examine the potential impacts of management and climate change in agriculture. DNDC can simulate the processes responsible for production, consumption and transport of nitrous oxide (N2O). During the last 20 years DNDC has been modified and adapted by various research groups around the world to suit specific purposes and circumstances. In this paper we review the different versions of the DNDC model including models developed for different ecosystems, e.g. Forest-DNDC, Forest-DNDC-Tropica, regionalised for different areas of the world, e.g. NZ-DNDC, UK-DNDC, modified to suit specific crops, e.g. DNDC-Rice, DNDC-CSW or modularised e.g. Mobile-DNDC, Landscape-DNDC. A ‘family tree’ and chronological history of the DNDC model is presented, outlining the main features of each version. A literature search was conducted and a survey sent out to c. 1500 model users worldwide to obtain information on the use and development of DNDC. Survey results highlight the many strengths of DNDC including the comparative ease with which the DNDC model can be used and the attractiveness of the graphical user interface. Identified weaknesses could be rectified by providing a more comprehensive user manual, version control and increasing model transparency in collaboration with the Global Research Alliance Modelling Platform (GRAMP), which has much to offer the DNDC user community in terms of promoting the use of DNDC and addressing the deficiencies in the present arrangements for the models’ stewardship.
S. L. Gilhespy, Steven Anthony, L. M. Cardenas, David R. Chadwick, A. del Prado, Changsheng Li, T. H. Misselbrook, Robert M. Rees, William Salas, Alberto Sanz-Cobeña, Pete Smith, Emma L. Tilston, K. Topp, Sylvia H. Vetter, Jagadeesh Yeluripati (2014). First 20 years of DNDC (DeNitrification DeComposition): Model evolution. , 292, DOI: https://doi.org/10.1016/j.ecolmodel.2014.09.004.
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Type
Article
Year
2014
Authors
15
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1016/j.ecolmodel.2014.09.004
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