The use of biogeochemical models to evaluate mitigation of greenhouse gas emissions from managed grasslands

Renáta Sándor, Fiona Ehrhardt, Lorenzo Brilli, Marco Carozzi, Sylvie Recous, Pete Smith, Val Snow, Jean-François Soussana, Christopher D. Dorich, Kathrin Fuchs, Nuala Fitton, Kate Gongadze, Katja Klumpp, Mark Liebig, Raphaël Martin, Lutz Merbold, Paul C. D. Newton, Robert M. Rees, Susanne Rolinski, Gianni Bellocchi

Research output: Contribution to journalArticlepeer-review

41 Citations (Scopus)

Abstract

Simulation models quantify the impacts on carbon (C) and nitrogen (N) cycling in grassland systems caused by changes in management practices. To support agricultural policies, it is however important to contrast the responses of alternative models, which can differ greatly in their treatment of key processes and in their response to management. We applied eight biogeochemical models at five grassland sites (in France, New Zealand, Switzerland, United Kingdom and United States) to compare the sensitivity of modelled C and N fluxes to changes in the density of grazing animals (from 100% to 50% of the original livestock densities), also in combination with decreasing N fertilization levels (reduced to zero from the initial levels). Simulated multi-model median values indicated that input reduction would lead to an increase in the C sink strength (negative net ecosystem C exchange) in intensive grazing systems: −64 ± 74 g C m−2 yr−1 (animal density reduction) and −81 ± 74 g C m−2 yr−1 (N and animal density reduction), against the baseline of −30.5 ± 69.5 g C m−2 yr−1 (LSU [livestock units] ≥ 0.76 ha−1 yr−1). Simulations also indicated a strong effect of N fertilizer reduction on N fluxes, e.g. N2O-N emissions decreased from 0.34 ± 0.22 (baseline) to 0.1 ± 0.05 g N m−2 yr−1 (no N fertilization). Simulated decline in grazing intensity had only limited impact on the N balance. The simulated pattern of enteric methane emissions was dominated by high model-to-model variability. The reduction in simulated offtake (animal intake + cut biomass) led to a doubling in net primary production per animal (increased by 11.6 ± 8.1 t C LSU−1 yr−1 across sites). The highest N2O-N intensities (N2O-N/offtake) were simulated at mown and extensively grazed arid sites. We show the possibility of using grassland models to determine sound mitigation practices while quantifying the uncertainties associated with the simulated outputs.
Original languageEnglish
Pages (from-to)292-306
Number of pages15
JournalScience of the Total Environment
Volume642
Early online date12 Jun 2018
DOIs
Publication statusPublished - 15 Nov 2018

Bibliographical note

This work was undertaken by the CN-MIP project of the Joint Programming Initiative ‘FACCE’ (https://www.faccejpi.com) under the auspices of the Global Research Alliance for Agricultural Greenhouse Gases - Integrative Research Group (http://globalresearchalliance.org/research/integrative). The project, coordinated by the French National Institute for Agricultural Research (INRA) (ANR-13-JFAC-0001), received funding by the ‘FACCE’ Multi-partner Call on Agricultural Greenhouse Gas Research through its national financing bodies. The input of PS and NF contributes to projects with support from UK-NERC (U-GRASS: NE/M016900/1) and FACCE-JPI via Defra. VS and PN were funded by the New Zealand Government to support the objectives of the Livestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gases. FE acknowledges support through a grant from the French Environment and Energy Management Agency (ADEME, n° 12-60-C0023). KF and LM acknowledge funds received from the Swiss National Science Foundation (40FA40_154245/1 grant agreement) and from the Doc Mobility grant. Exchanges between French and Italian authors were supported by the Galileo programme (CLIMSOC: 39625XE for France, G18-631 for Italy).

We acknowledge Stephanie K. Jones, Kairsty Topp (Scotland's Rural College, EH9 3JG Edinburgh, United Kingdom) and Ute Skiba (Centre for Ecology and Hydrology Edinburgh, United Kingdom), who contributed to collecting the data used in this study for the G4 site. Lianhai Wu (Rothamsted Research, Sustainable Soil and Grassland Systems Department, United Kingdom) and Rich Conant (NREL, Colorado State University, Fort Collins, CO, USA) are also acknowledged for their contribution to the modelling work performed with SPACSYS and DayCent v4.5 2013, respectively.

Keywords

  • GHG emission intensity
  • Livestock density
  • Nitrogen fertilization
  • Process-based model
  • Sensitivity analysis

Fingerprint

Dive into the research topics of 'The use of biogeochemical models to evaluate mitigation of greenhouse gas emissions from managed grasslands'. Together they form a unique fingerprint.

Cite this