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, Andreas Lüscher, Raphaël Martin, Russel McAuliffe, Lutz Merbold, Paul Newton, RM Rees, Pete Smith, CFE Topp, Valerie Snow

*Corresponding author for this work

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Abstract

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 novel approach for coupling DayCent, a single species model to APSIM, a multi-species model, to increase the capability of DayCent when representing a range of grass-legume fractions. While dependent on specific assumptions, both models can capture the key aspects of the grass-legume growth, including biomass production and BNF and to correctly simulate the interactions between changing legume and grass fractions, particularly mixtures with a high clover fraction. Our work suggests that single species models should not be used for grass-legume mixtures beyond about 30% legume content, unless using a similar approach to that adopted here.
Original languageEnglish
Pages (from-to)58-66
Number of pages9
JournalEuropean Journal of Agronomy
Volume106
Early online date8 Apr 2019
DOIs
Publication statusPrint publication - May 2019

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fixation
grass
modeling
grassland
fertilizer
nitrogen
nitrous oxide
greenhouse gas
productivity
biomass
biological nitrogen fixation

Keywords

  • Nitrogen uptake
  • Species composition
  • Model variation
  • Overyielding

Cite this

Fitton, Nuala ; Bindi, Marco ; Brilli, Lorenzo ; Cichota, Rogerio ; Dibari, Camila ; Fuchs, Kathrin ; Huguenin-Elie, Olivier ; Klumpp, Katja ; Lieffering, Mark ; Lüscher, Andreas ; Martin, Raphaël ; McAuliffe, Russel ; Merbold, Lutz ; Newton, Paul ; Rees, RM ; Smith, Pete ; Topp, CFE ; Snow, Valerie. / Modelling biological N fixation and grass-legume dynamics with process-based biogeochemical models of varying complexity. In: European Journal of Agronomy. 2019 ; Vol. 106. pp. 58-66.
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abstract = "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 novel approach for coupling DayCent, a single species model to APSIM, a multi-species model, to increase the capability of DayCent when representing a range of grass-legume fractions. While dependent on specific assumptions, both models can capture the key aspects of the grass-legume growth, including biomass production and BNF and to correctly simulate the interactions between changing legume and grass fractions, particularly mixtures with a high clover fraction. Our work suggests that single species models should not be used for grass-legume mixtures beyond about 30{\%} legume content, unless using a similar approach to that adopted here.",
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author = "Nuala Fitton and Marco Bindi and Lorenzo Brilli and Rogerio Cichota and Camila Dibari and Kathrin Fuchs and Olivier Huguenin-Elie and Katja Klumpp and Mark Lieffering and Andreas L{\"u}scher and Rapha{\"e}l Martin and Russel McAuliffe and Lutz Merbold and Paul Newton and RM Rees and Pete Smith and CFE Topp and Valerie Snow",
year = "2019",
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Fitton, N, Bindi, M, Brilli, L, Cichota, R, Dibari, C, Fuchs, K, Huguenin-Elie, O, Klumpp, K, Lieffering, M, Lüscher, A, Martin, R, McAuliffe, R, Merbold, L, Newton, P, Rees, RM, Smith, P, Topp, CFE & Snow, V 2019, 'Modelling biological N fixation and grass-legume dynamics with process-based biogeochemical models of varying complexity', European Journal of Agronomy, vol. 106, pp. 58-66. https://doi.org/10.1016/j.eja.2019.03.008

Modelling biological N fixation and grass-legume dynamics with process-based biogeochemical models of varying complexity. / Fitton, Nuala; Bindi, Marco; Brilli, Lorenzo; Cichota, Rogerio ; Dibari, Camila; Fuchs, Kathrin ; Huguenin-Elie, Olivier; Klumpp, Katja; Lieffering, Mark; Lüscher, Andreas; Martin, Raphaël; McAuliffe, Russel ; Merbold, Lutz; Newton, Paul; Rees, RM; Smith, Pete; Topp, CFE; Snow, Valerie.

In: European Journal of Agronomy, Vol. 106, 05.2019, p. 58-66.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Modelling biological N fixation and grass-legume dynamics with process-based biogeochemical models of varying complexity

AU - Fitton, Nuala

AU - Bindi, Marco

AU - Brilli, Lorenzo

AU - Cichota, Rogerio

AU - Dibari, Camila

AU - Fuchs, Kathrin

AU - Huguenin-Elie, Olivier

AU - Klumpp, Katja

AU - Lieffering, Mark

AU - Lüscher, Andreas

AU - Martin, Raphaël

AU - McAuliffe, Russel

AU - Merbold, Lutz

AU - Newton, Paul

AU - Rees, RM

AU - Smith, Pete

AU - Topp, CFE

AU - Snow, Valerie

PY - 2019/5

Y1 - 2019/5

N2 - 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 novel approach for coupling DayCent, a single species model to APSIM, a multi-species model, to increase the capability of DayCent when representing a range of grass-legume fractions. While dependent on specific assumptions, both models can capture the key aspects of the grass-legume growth, including biomass production and BNF and to correctly simulate the interactions between changing legume and grass fractions, particularly mixtures with a high clover fraction. Our work suggests that single species models should not be used for grass-legume mixtures beyond about 30% legume content, unless using a similar approach to that adopted here.

AB - 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 novel approach for coupling DayCent, a single species model to APSIM, a multi-species model, to increase the capability of DayCent when representing a range of grass-legume fractions. While dependent on specific assumptions, both models can capture the key aspects of the grass-legume growth, including biomass production and BNF and to correctly simulate the interactions between changing legume and grass fractions, particularly mixtures with a high clover fraction. Our work suggests that single species models should not be used for grass-legume mixtures beyond about 30% legume content, unless using a similar approach to that adopted here.

KW - Nitrogen uptake

KW - Species composition

KW - Model variation

KW - Overyielding

U2 - 10.1016/j.eja.2019.03.008

DO - 10.1016/j.eja.2019.03.008

M3 - Article

VL - 106

SP - 58

EP - 66

JO - European Journal of Agronomy

JF - European Journal of Agronomy

SN - 1161-0301

ER -