The Carbon Navigator: a decision support tool to reduce greenhouse gas emissions from livestock production systems

Murphy, Pat; Crosson, P.; O’Brien, D.; Schulte, Rogier P.O.

doi:10.1017/s1751731113000906

Cited by 26 publications

(15 citation statements)

References 10 publications

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“…Increased GSL may also result in changes to the environmental impacts of grazing with a trend towards lower greenhouse gas (GHG) emissions, but increased nitrate leaching (Webb et al . 2005; Murphy et al 2013). However, increased GSL may also result in increased exposure to helminth parasites, which may be associated with reduced milk yields (Charlier et al 2005; Verschave et al 2014), and decreased production efficiency, counterbalancing the benefits from reductions in GHG emissions (Kenyon et al 2013).…”

Section: Discussionmentioning

confidence: 99%

Predictions of future grazing season length for European dairy, beef and sheep farms based on regression with bioclimatic variables

et al. 2015

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SUMMARYGrazing season length (GSL) on grassland farms with ruminant production systems can influence farm economics, livestock disease transmission, environmental impact, milk and meat quality, and consumer choice. Bioclimatic variables are biologically meaningful climate variables that may enable predictions of the impact of future climate change on GSL on European farms. The present study investigated the spatial relationship between current GSL (months) measured by EUROSTAT on dairy, beef and sheep farms in 706, 774 and 878 regions, respectively, and bioclimatic variables. A stepwise multiple regression model revealed a highly significant association between observed GSL and bioclimatic variables across Europe. Mean GSL was positively associated with the mean temperature of the coldest quarter and isothermality, and negatively associated with precipitation in the wettest month. Extrapolating these relationships to future climate change scenarios, most European countries were predicted to have a net increase in GSL with the increase being largest (up to 2·5 months) in the north-east of Europe. However, there were also predictions of increased variability between regions and decreases in GSL of up to 1·5 months in some areas such as the west of France, the south-west of Norway and the west coast of Britain. The study quantified and mapped the potential impact of climate change on GSL for dairy, beef and sheep farms across Europe.

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Section: Discussionmentioning

confidence: 99%

Predictions of future grazing season length for European dairy, beef and sheep farms based on regression with bioclimatic variables

et al. 2015

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“…The analyses utilized national studies on GHG abatement options (e.g., Lanigan et al, 2018) to identify mitigation measures that could be applied on-farm. This was also determined using tools that provide decision support on mitigating beef farms' carbon footprint, for example, Teagasc/Bord Bia Carbon Navigator (Murphy et al, 2013). The outputs of the SWOT analyses were lists of GHG mitigation options suitable for each nation's beef production systems.…”

Section: Common Mitigation Planmentioning

confidence: 99%

LIFE BEEF CARBON: a common framework for quantifying grass and corn based beef farms’ carbon footprints

O’Brien

Herron

Andurand

et al. 2020

Animal

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Europe’s roadmap to a low-carbon economy aims to cut greenhouse gas (GHG) emissions 80% below 1990 levels by 2050. Beef production is an important source of GHG emissions and is expected to increase as the world population grows. LIFE BEEF CARBON is a voluntary European initiative that aims to reduce GHG emissions per unit of beef (carbon footprint) by 15% over a 10-year period on 2172 farms in four large beef-producing countries. Changes in farms beef carbon footprint are normally estimated via simulation modelling, but the methods current models apply differ. Thus, our initial goal was to develop a common modelling framework to estimate beef farms carbon footprint. The framework was developed for a diverse set of Western Europe farms located in Ireland, Spain, Italy and France. Whole farm and life cycle assessment (LCA) models were selected to quantify emissions for the different production contexts and harmonized. Carbon Audit was chosen for Ireland, Bovid-CO2 for Spain and CAP’2ER for France and Italy. All models were tested using 20 case study farms, that is, 5 per country and quantified GHG emissions associated with on-farm live weight gain. The comparison showed the ranking of beef systems gross carbon footprint was consistent across the three models. Suckler to weaning or store systems generally had the highest carbon footprint followed by suckler to beef systems and fattening beef systems. When applied to the same farm, Carbon Audit’s footprint estimates were slightly lower than CAP’2ER, but marginally higher than Bovid-CO2. These differences occurred because the models were adapted to a specific region’s production circumstances, which meant their emission factors for key sources; that is, methane from enteric fermentation and GHG emissions from concentrates were less accurate when used outside their target region. Thus, for the common modelling framework, region-specific LCA models were chosen to estimate beef carbon footprints instead of a single generic model. Additionally, the Carbon Audit and Bovid-CO2 models were updated to include carbon removal by soil and other environmental metrics included in CAP’2ER, for example, acidification. This allows all models to assess the effect carbon mitigation strategies have on other potential pollutants. Several options were identified to reduce beef farms carbon footprint, for example, improving genetic merit. These options were assessed for beef systems, and a mitigation plan was created by each nation. The cumulative mitigation effect of the LIFE BEEF CARBON plan was estimated to exceed the projects reduction target (−15%).

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“…In relation to their usefulness, farm-level sustainability indicators can be used to monitor farm activities to assist in decision-making and assess progress towards more sustainable farming (Vilain, 1997) and decision support and sustainability assessment tools based on indicators have been developed by researchers and private value-chain stakeholders (e.g. Murphy et al, 2013;de Olde et al, 2016). These indicators can be used to improve the understanding of the relationship between the environmental, economic and societal impacts of agricultural activities.…”

Section: Usefulness Of Farm-level Sustainability Indicatorsmentioning

confidence: 99%

Sustainability indicators for improved assessment of the effects of agricultural policy across the EU: Is FADN the answer?

Kelly

Latruffe²,

Desjeux³

et al. 2018

Ecological Indicators

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Policy reform of the CAP and society's expectations of agriculture have resulted in a growing need for improved information on the effectiveness of policy in achieving high-level objectives for more sustainable practice in agriculture. This is a high priority given its importance for consumers, public policy and private industry. Data collection programmes will need to adapt their scope if their information is to adequately address new information needs about high-level objectives. Assessment of sustainability at the farm level is hindered by the lack of data with which to derive appropriate, meaningful, and relevant indicators. This is particularly problematic for assessment of agricultural sustainability across the European Union (EU). Various databases exist at the EU scale regarding agricultural data sources and we identify one of these, the EU Farm Accountancy Data Network (FADN), as having considerable potential to assess farm-level sustainability at EU level. We critique several examples of published work that has attempted to assess agricultural sustainability using: FADN data alone; FADN data in combination with data from supplementary surveys, and; FADN data in combination with data from other EU databases. We conclude that the FADN would need to broaden its scope of data collection if it is to address the new information needs of policy, and we discuss the challenges in expanding FADN with a view towards wider farm-level assessment of sustainability. These include careful selection of indicators based on various criteria, the representativeness of the FADN, and the need to include new themes to address environmental, social, and animal welfare effects of policy.

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The Carbon Navigator: a decision support tool to reduce greenhouse gas emissions from livestock production systems

Cited by 26 publications

References 10 publications

Predictions of future grazing season length for European dairy, beef and sheep farms based on regression with bioclimatic variables

Predictions of future grazing season length for European dairy, beef and sheep farms based on regression with bioclimatic variables

LIFE BEEF CARBON: a common framework for quantifying grass and corn based beef farms’ carbon footprints

Sustainability indicators for improved assessment of the effects of agricultural policy across the EU: Is FADN the answer?

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