SIMSDAIRY: A modelling framework to identify sustainable dairy farms in the UK. Framework description and test for organic systems and N fertiliser optimisation

Prado, A. del; Misselbrook, Tom; Chadwick, David R.; Hopkins, A.; Dewhurst, Richard J.; Davison, Paul; Butler, Allan; Schröder, J.J.; Scholefield, D.

doi:10.1016/j.scitotenv.2011.05.050

Cited by 74 publications

(66 citation statements)

References 110 publications

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“…When manure is removed from storage and applied to cropland, NH 3 may be volatilised until the manure is incorporated into the soil and N 2 O emissions can follow as a function of site conditions (e.g. Rotz et al, 2012) and application method (Del Prado et al, 2011a). Petersen et al (this issue) includes a specific section on manure modelling.…”

Section: Components Of Farm Ghg Modelsmentioning

confidence: 99%

“…Pasture production is generally predicted as a function of soil water and N availabilities and weather. Pasture availability can be modelled using a range in complexity from assigned empirical data to mechanistic plant growth simulations with soil moisture, ambient temperature and solar radiation as drivers (Del Prado et al, 2011a;Rotz et al, 2012). The actual amount consumed is limited to potential animal intake or the available forage, whichever is less.…”

Section: Feed Productionmentioning

confidence: 99%

“…Foley et al, 2011; O 0 Brien et al, 2012a and2012b) or relating NH 3 volatilisation losses to silage DM loss (e.g. Schils et al, 2006;Del Prado et al, 2011a). Silage effluent losses of up to 4% of the total farm emission (including secondary emissions) have been estimated .…”

Section: Soil Carbonmentioning

confidence: 99%

“…Farm models generally simulate enteric CH 4 using empirical models derived from statistical analyses (e.g. Olesen et al, 2006;Del Prado et al, 2011a). The simplest form relates animal dry matter (DM) intake or metabolisable energy intake and CH 4 output (Mills et al, 2003) and others may include fatty acid profiles (Giger-Reverdin et al, 2003).…”

Section: Components Of Farm Ghg Modelsmentioning

confidence: 99%

“…animal products with increased nutritional value) and services (e.g. increased biodiversity levels) may be determined (Del Prado et al, 2011a) as some non-market attributes may eventually become valuable in monetary terms either by market pressures or regulatory-driven incentives (e.g. payments for ecosystem services).…”

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confidence: 99%

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Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems

Prado

Crosson

Olesen

et al. 2013

Animal

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The farm level is the most appropriate scale for evaluating options for mitigating greenhouse gas (GHG) emissions, because the farm represents the unit at which management decisions in livestock production are made. To date, a number of whole farm modelling approaches have been developed to quantify GHG emissions and explore climate change mitigation strategies for livestock systems. This paper analyses the limitations and strengths of the different existing approaches for modelling GHG mitigation by considering basic model structures, approaches for simulating GHG emissions from various farm components and the sensitivity of GHG outputs and mitigation measures to different approaches. Potential challenges for linking existing models with the simulation of impacts and adaptation measures under climate change are explored along with a brief discussion of the effects on other ecosystem services.Keywords: adaptation, farm-models, greenhouse gases, mitigation, ruminants ImplicationsWhole-farm models are valuable tools to study the feedback and feedforward interactions between mitigation of greenhouse gas (GHG) emissions and adaptation to climate change for ruminant-based production systems. All of the processes affecting GHG emissions and farm productivity involve the cycling of C and N within the farm, most of which will be affected by climate change. However, not all farm models include such responses to climatic drivers, and there is a need for further development and testing of the models under diverse climatic conditions. Modelling of the complex interactions between farm components and the environment, including the socio-economic aspects, is instrumental for providing strategic direction to the development of climate and food-related policies. Despite the contribution of nontemperate livestock systems to total global GHG emissions, there is a dearth of specific farm models to assess GHG emissions from these regions. Modelling of soil carbon (C) fluxes is still largely absent or very simplified in many studies even though soil C has the potential to be the largest source or sink of C for grassland-based livestock systems. IntroductionAccording to The Food and Agriculture Organization (FAO) (Steinfeld et al., 2006) livestock production systems contribute about 18% of global anthropogenic greenhouse gas (GHG) emissions. Livestock is also currently one of the fastest growing agricultural subsectors in developing countries (Thornton, 2010), with projections indicating that by 2050 worldwide animal production is expected to increase by 80% compared with 2005 (Alexandratos andBruinsma, 2012). Although demand for non-ruminant meat has been increasing more rapidly than that for ruminant meats and, consequently, the importance of grasslands in livestock production and trade has been declining, increased milk and beef demand, potentially produced via grassland-based systems, is expected to increase (Fiala, 2008;Thornton, 2010). It is thus projected that the global annual growth rate of beef until 2050 will be 1.2%, clos...

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Section: Components Of Farm Ghg Modelsmentioning

confidence: 99%

Section: Feed Productionmentioning

confidence: 99%

Section: Soil Carbonmentioning

confidence: 99%

Section: Components Of Farm Ghg Modelsmentioning

confidence: 99%

mentioning

confidence: 99%

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Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems

Prado

Crosson

Olesen

et al. 2013

Animal

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Assessing the performance of commercial farms in England and Wales: Lessons for supporting the sustainable intensification of agriculture

Firbank

Elliott

Field

et al. 2018

Food and Energy Security

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Understanding the trade‐offs between yield, ecosystem services, and other societal benefits is a fundamental prerequisite for the sustainable intensification of agriculture. Here, we develop and test an holistic approach to assessing farm performance across production, social, financial, and environmental dimensions. A longlist of potential indicators was reduced to a smaller subset of Headline Indicators, covering financial performance, levels of food production (standardized in terms of energy content), social characteristics of the farmer (including age, level of education, and degree of business cooperation), hours worked on the farm and provision of public access, and environmental quality (including impacts on climate regulation and water quality). A new index for biodiversity was created and validated, based on land use and management. Data were collected from 59 English and Welsh farms, using a questionnaire structured to be similar to the UK Farm Business Survey. Data were analyzed per farm and per unit area. The main overall variation in Headline Indicators was due to positive relationships between production, profitability and predicted levels of nitrate and GHG emissions, while social variables and biodiversity were generally unrelated to production. Cereal production was associated with relatively low levels of GHG emissions per unit of food production. There were strong differences in indicator profiles between farm types. Such metrics have value in helping understand how best to drive sustainable intensification, especially as it should involve reducing the pollution footprint of food production.

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Food Footprint as a Measure of Sustainability for Grazing Dairy Farms

Rojas-Downing

Nejadhashemi

Elahi

et al. 2018

Environmental Management

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SIMSDAIRY: A modelling framework to identify sustainable dairy farms in the UK. Framework description and test for organic systems and N fertiliser optimisation

Cited by 74 publications

References 110 publications

Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems

Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems

Assessing the performance of commercial farms in England and Wales: Lessons for supporting the sustainable intensification of agriculture

Food Footprint as a Measure of Sustainability for Grazing Dairy Farms

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