Pulse Brain · Growing Health Evidence Index
Peer-reviewed

Modelling biological N fixation and grass-legume dynamics with process-based biogeochemical models of varying complexity

Nuala Fitton, Marco Bindi, Lorenzo Brilli, Rogerio Cichota, Camila Dibari, Kathrin Fuchs, Olivier Huguenin‐Elie, Katja Klumpp, Mark Lieffering, A. Lüscher, Raphaël Martin, Russel McAuliffe, Lutz Merbold, Paul C. D. Newton, Robert M. Rees, Pete Smith, K. Topp, Val Snow

European Journal of Agronomy · 2019

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Summary

Grasslands comprised of grass-legume mixtures could become a substitute for nitrogen fertiliser through biological nitrogen fixation (BNF) which in turn can reduce nitrous oxide emissions directly from soils without negative impacts on productivity. Models can test how legumes can be used to meet environmental and production goals, but many models used to simulate greenhouse gas (GHG) emissions from grasslands have either a poor representation of grass-legume mixtures and BNF, or poor validation of these features. Our objective is to examine how such systems are currently represented in two process-based biogeochemical models, APSIM and DayCent, when compared against an experimental dataset with different grass-legume mixtures at three nitrogen (N) fertiliser rates. Here, we propose a nove

Source type
Peer-reviewed study
DOI
10.1016/j.eja.2019.03.008
Catalogue ID
SNmoef28zp-ekreq1
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