TY - JOUR
T1 - Challenges and opportunities to capture dietary effects in on-farm greenhouse gas emissions models of ruminant systems
AU - Vibart, Ronaldo
AU - de Klein, Cecile
AU - Jonker, Arjan
AU - van der Weerden, Tony
AU - Bannink, André
AU - Bayat, Ali R.
AU - Crompton, Les
AU - Durand, Anais
AU - Eugène, Maguy
AU - Klumpp, Katja
AU - Kuhla, Björn
AU - Lanigan, Gary
AU - Lund, Peter
AU - Ramin, Mohammad
AU - Salazar, Francisco
PY - 2021/5
Y1 - 2021/5
N2 - This paper reviews existing on-farm GHG accounting models for dairy cattle systems and their ability to capture the effect of dietary strategies in GHG abatement. The focus is on methane (CH4) emissions from enteric and manure (animal excreta) sources and nitrous oxide (N2O) emissions from animal excreta. We identified three generic modelling approaches, based on the degree to which models capture diet-related characteristics: from ‘none’ (Type 1) to ‘some’ by combining key diet parameters with emission factors (EF) (Type 2) to ‘many’ by using process-based modelling (Type 3). Most of the selected on-farm GHG models have adopted a Type 2 approach, but a few hybrid Type 2 / Type 3 approaches have been developed recently that combine empirical modelling (through the use of CH4 and/or N2O emission factors; EF) and process-based modelling (mostly through rumen and whole tract fermentation and digestion). Empirical models comprising key dietary inputs (i.e., dry matter intake and organic matter digestibility) can predict CH4 and N2O emissions with reasonable accuracy. However, the impact of GHG mitigation strategies often needs to be assessed in a more integrated way, and Type 1 and Type 2 models frequently lack the biological foundation to do this. Only Type 3 models represent underlying mechanisms such as ruminal and total-tract digestive processes and excreta composition that can capture dietary effects on GHG emissions in a more biological manner. Overall, the better a model can simulate rumen function, the greater the opportunity to include diet characteristics in addition to commonly used variables, and thus the greater the opportunity to capture dietary mitigation strategies. The value of capturing the effect of additional animal feed characteristics on the prediction of on-farm GHG emissions needs to be carefully balanced against gains in accuracy, the need for additional input and activity data, and the variability encountered on-farm.
AB - This paper reviews existing on-farm GHG accounting models for dairy cattle systems and their ability to capture the effect of dietary strategies in GHG abatement. The focus is on methane (CH4) emissions from enteric and manure (animal excreta) sources and nitrous oxide (N2O) emissions from animal excreta. We identified three generic modelling approaches, based on the degree to which models capture diet-related characteristics: from ‘none’ (Type 1) to ‘some’ by combining key diet parameters with emission factors (EF) (Type 2) to ‘many’ by using process-based modelling (Type 3). Most of the selected on-farm GHG models have adopted a Type 2 approach, but a few hybrid Type 2 / Type 3 approaches have been developed recently that combine empirical modelling (through the use of CH4 and/or N2O emission factors; EF) and process-based modelling (mostly through rumen and whole tract fermentation and digestion). Empirical models comprising key dietary inputs (i.e., dry matter intake and organic matter digestibility) can predict CH4 and N2O emissions with reasonable accuracy. However, the impact of GHG mitigation strategies often needs to be assessed in a more integrated way, and Type 1 and Type 2 models frequently lack the biological foundation to do this. Only Type 3 models represent underlying mechanisms such as ruminal and total-tract digestive processes and excreta composition that can capture dietary effects on GHG emissions in a more biological manner. Overall, the better a model can simulate rumen function, the greater the opportunity to include diet characteristics in addition to commonly used variables, and thus the greater the opportunity to capture dietary mitigation strategies. The value of capturing the effect of additional animal feed characteristics on the prediction of on-farm GHG emissions needs to be carefully balanced against gains in accuracy, the need for additional input and activity data, and the variability encountered on-farm.
KW - dairy farm system
KW - diet
KW - feeding management
KW - effluent
KW - methane
KW - nitrous oxide
UR - http://www.scopus.com/inward/record.url?scp=85100219404&partnerID=8YFLogxK
U2 - 10.1016/j.scitotenv.2021.144989
DO - 10.1016/j.scitotenv.2021.144989
M3 - Review
C2 - 33485195
SN - 0048-9697
VL - 769
JO - Science of the Total Environment
JF - Science of the Total Environment
M1 - 144989
ER -