Whole-farm Model Research Articles

69 The Holos model for estimating greenhouse gases and soil carbon: Characterizing regionalized beef farm model systems

Abstract The objective of this work is to characterize regionally representative beef farm systems that represent dominant or typical surveyed management practices for 11 beef-producing regions across Canada. This work fulfills two further purposes 1) to improve and expand the Holos model interface; and 2) to facilitate the estimation of greenhouse gas (GHG) emissions and soil carbon (C) changes on beef farms in different regions of Canada. Holos version 4 is the whole-farm model of Agriculture and Agri-Food Canada’s to estimate GHG emissions and changes in soil C on Canadian farms in response to shifts in management practices. Holos can be implemented in all 10 Canadian provinces and accounts for GHG emissions from crop and livestock production [enteric and manure methane (CH4), manure and soil N2O emissions], farm machines and infrastructure [on-farm energy carbon dioxide (CO2) emissions], as well as from the upstream production of some farm inputs (synthetic fertilizer and pesticides). The model is designed to utilize data readily available on the farm to answer, ‘What if?’ scenarios, whereby the user can test the effect of changing management practices on their whole-farm GHG budget. To reduce the data input burden on the user, Holos V4 has built-in model livestock systems for beef, dairy, swine and poultry production that characterize the dominant features of these operations in Canada at the national scale based on relevant literature/data and expert opinion. Regarding beef production, we have characterized regionally specific model beef farms for incorporation into Holos, one for each of 11 Canadian beef-producing regions. General characteristics and management practices for each farm were based on the 2011 Beef Farm Survey (Sheppard et al., 2015), which summarizes management information from 1,009 Canadian beef farms, combined with data from the Canadian Cow-Calf Cost of Production Network (Canfax 2023). Each regional farm includes cow-calf, backgrounding in confinement, backgrounding on pasture and finishing components, and considers all the specific feed (e.g., forage, grains, by-products) required for each stage of the beef cycle. These 11 model farms are simulated within the current Holos V4 model to explore the impacts of variation in beef management practices on farm GHG emissions across Canada and on soil C stocks on lands used to produce feed and graze cattle. An overview of the national-level dairy, swine and poultry components in Holos will be presented along with a more detailed perspective of whole-farm GHG budget and multi-decadal soil C dynamics in regionalized beef farms. The impact of management and environmental factors that lead to differences in GHG emissions and soil C stocks in beef farms will also be explored.

Modelling of on-farm greenhouse gas emissions from dual-purpose meat and wool sheep production in different geographical regions of Norway

The whole-farm model, HolosNorSheep, was developed to estimate net greenhouse gas emissions from dual purpose sheep production in Norway. The model adopted a cradle-to-farm gate system boundary and is based on the International Panel on Climate Change methodology and includes direct emissions from enteric and manure methane (CH4; GWP100=27), direct and indirect nitrous oxide (N2O; GWP100=273) from manure and soils, direct carbon dioxide (CO2) emissions from energy use and indirect CO2 emissions from the production of input factors. Soil carbon balance is calculated using the ICBM-model. Emission intensities (CO2-eq/kg product) for sheep carcass and greasy wool, was estimated for five geographical regions of Norway (East, West, South, Mid and North). The geographical regions varied considerably in climate, feed resources, days on pasture and herd/farm management. Estimated emission intensities per kg carcass and greasy wool varied from 23.5 to 19.9 (Mid region) to 26.8 and 22.8 kg CO2-eq (North region) respectively. The difference between the Mid and North region was mainly due to higher CO2 and N2O emissions from use of fuel and N-fertilizer in the North, where a short growth season, and thus reduced grass yields, are compensated by using greater land area. Based on the distribution of sheep in the regions, and the emission intensities in each region, weighted average emission intensities per kg carcass and greasy wool were estimated as 25.1 and 23.3 kg CO2-eq, respectively. Five alternative methods for the allocation of the co-products were compared with the amounts allocated to greasy wool ranging from 0 % when using no allocation (i.e., all emissions allocated to the sheep carcass), 11 % for economic allocation, 12 % for mass allocation, 19 % for biophysical allocation based on energy requirement up to 31 % for allocation based on protein mass. The emission intensity for wool was highly sensitive to the allocation method used (range from 0 to 61 kg CO2-eq per kg greasy wool), while the effect on sheep carcass was lower (range 19 to 28 kg CO2-eq per kg carcass). For production systems where meat is the main product, as in Norway, allocation should be based on biophysical allocation based on energy requirement.

Preparing for, coping with and bouncing back after shocks. A nuanced resilience assessment for smallholder farms and farmers in Northern Ghana

ABSTRACTSmallholder farmers in Northern Ghana regularly face shocks, challenging the sustainability of their farms and livelihoods. Different farm households and household members may be differently affected and respond with different coping strategies. We combined whole-farm modelling and farmer consultations to investigate the vulnerability, buffer and adaptive capacity of three farm types in Northern Ghana towards severe climate, economic and social shocks. We further assessed intra-household differences in respective risk mitigation and coping strategies. Our model results indicate that the drought shock would most severely affect all farm types, drastically reducing their operating profits and soil organic matter balance. The medium resource endowed farm was most affected by shocks, but all farm types could enhance their capacity to recover by adopting technology packages for sustainable intensification. Gendered coping strategies included livestock sales, post-harvest storage, activating social networks, rice processing and the collection, processing and sales of wild nuts and fruits. Farmers reported to aim at becoming more resilient by increasing their herd size and expanding their farmland, thereby risking to increase rather than reduce the pressure on natural resources. New questions arise concerning the carrying capacity of local ecosystems and resilience at community and landscape level.

Integrating dual-purpose crops mitigates feedbase risk and facilitates improved lamb production systems across environments: a whole-farm modelling analysis

Context The winter feed gap is a common problem for livestock grazing systems worldwide, and changes to climate have made these deficits more unpredictable and extreme. Dual-purpose crops are an important tool in many southern Australian mixed crop–livestock systems to help fill the winter feed gap. Providing more reliable feed over winter can remove feed constraints and allow for earlier lambing in autumn with potential whole-farm system benefits. Aims We simulated a whole-farm livestock enterprise in the Agricultural Production Systems Simulator (APSIM) to examine the implications of spring- and autumn-lambing systems relying on a standard pasture-only feedbase compared with a farm where 25% of its grazed area is allocated to dual-purpose crops. Methods Twelve simulations were run across four locations in New South Wales, Australia, that varied in climatic conditions (both rainfall total and distribution) including two lambing systems (spring vs autumn) × two feedbase types (100% pasture vs 75% pasture and 25% dual-purpose crops) × three stocking densities. Key results For autumn-lambing systems, integrating dual-purpose crops helped to fill the winter feed gap and reduced supplement demand on average by ~28% compared with a pasture-only system. Compared with the standard pasture-only spring-lambing system, integrating dual-purpose crops into spring- and autumn-lambing systems more than doubled gross margin returns due to economic grain yield and lower supplement demand. A shift from spring- to autumn-lambing facilitated by dual-purpose crops also led to better reproductive performance of ewes in the subsequent year. In higher-rainfall, cooler environments, autumn-lambing systems with dual-purpose crops had the highest system gross margins, lowest economic risk and allowed for a safe increase in stocking density. In lower-rainfall, warmer environments, integration of dual-purpose crops into spring-lambing systems returned marginally higher gross margins than for the autumn-lambing system, but differences were less apparent at high stocking density. In lower-rainfall environments, dual-purpose crops helped to mitigate some of the economic risk, but the benefits were less clear. Conclusions We show dual-purpose crops can help fill the winter feed gap and support earlier lambing in autumn across a range of environments, especially in higher-rainfall cooler environments, with significant improvements in total farm gross margins. Implications Integrating dual-purpose crops will enable farmers to change their livestock system to mitigate their risks, reduce supplementary feeding and capitalise on other potential benefits, such as improved marketing and avoiding animal health problems.

Timing of the outfield grazing season and finishing of lambs: A whole-farm modelling study of forage-based sheep production systems in Norway

Norwegian sheep production is based on the use of free outfield grazing resources in the mountains and forests in summer. Lamb prices are strongest at the beginning of the slaughter season in August and then begin to gradually decline, reaching a lower plateau in mid-October. Seasonal pricing provides incentives to get slaughter lambs to market early. The objective of this study was to examine how outfield summer pasture quality, time of collection from the outfields, and inclusion of annual forage crops in the diet of finishing lambs influence optimal farm plans and profitability in Norwegian forage-based sheep production systems at varying levels of farmland availability (varying from 15 to 25 ha with 20 ha as the basis). A linear programming model was developed for sheep production systems in the mountainous areas of Southern Norway. Input-output relationships incorporated into the model included data from field experiments with grasses for annual and perennial use, observed performance of lambs and ewes at pastures, a feed planning tool for the indoor season, and expert judgements. The model maximised total gross margin of farms with a housing capacity of 200 ewes. The results suggested that with more land available, drafting older and heavier lambs for slaughter was profitable. The lighter lambs at weaning were usually drafted much later and at the same or heavier carcass weights than the heavy lambs at weaning because of seasonal pricing. Higher quality outfield summer pastures increased lamb live weights at weaning. Annual profits improved considerably with rich summer pastures compared to poor summer pastures. Early collection was always less profitable than normal time of collection because greater prices for lambs sold could not offset losses from the additional feed costs incurred and a possibly smaller flock. Speeding up the growth rate of finishing lambs by offering annual forage crops in addition to grazed grass was usually more profitable than grass only. Only for rich summer pastures and normal time of collection at low land availability was use of annual forage crops unprofitable.

Simulation Model for Biogas Project Efficiency Maximization

A simulation method (SM), linear programming method (LPM), project evaluation methods (PEMs), and whole farm modeling (WFM) were applied to analyze the investment appeal of a biogas project on a Russian farm. The biogas project was evaluated for constant input parameters. The project efficiency evaluation procedure was elaborated to evaluate and maximize biogas investment project efficiency. The procedure to evaluate the project efficiency includes defining the optimal state of the farm for the situations “with project” and “without project.” The main elements for optimization are the equipment for anaerobic digestion, substrate blend structure, fertilizing plan, cost plan, and farm production structure. The optimization was fulfilled by simulation modeling (SM) and LPM. The situations “with project” and “without project” were compared by using PEMs, the main indicators of project efficiency: net present value (NPV), internal rate of return (IRR), payback period (PBP), and profitability index (PI). The optimal substrate blend structure was defined by the direct search method (DSM) to select the probe providing the highest NPV afterward. The procedure to maximize biogas project efficiency was applied to justify the benefits of biogas production on the farm under corresponding conditions and to work out the recommendations for businesses and municipalities.

65. Whole-farm modelling of dairy beef production systems

65. Whole-farm modelling of dairy beef production systems

Strategies to double milk production per farm in Argentina: Investment, economics and risk analysis

ContextDemand for dairy products is expected to continue driving intensification in dairy systems. Little is known about the productive and economic performance and risk of intensification strategies either within grazing systems or confinement dairy systems in Argentina.cu ObjectiveThis study investigated four strategies to double milk production for the average grazing dairy system of Argentina (BASE), using either grazing or confinement systems. Physical and economic performance and risk associated with each alternative was explored using a modelling approach. Investment of capital required to establish each alternative was estimated. MethodsFour scenarios that double milk production per farm from a BASE scenario were designed and modelled using a whole-farm model named e-Dairy: two grazing dairy systems with different milk yield per cow per year: GR6750 (6750 L/cow per year) and GR7500 (7500 L/cow per year) and two confinement systems, an open dry yard (DRYLOT) and a compost bedded pack (COMPOST). Stochastic budgeting was used to model the combined influence of variation in milk, price and crops yield. Outputs of the stochastic analysis are shown in the form of cumulative distribution functions (CDF). Results and conclusionsAll the intensification alternatives increased milk production per ha from 7800 L, in BASE system, to 18,209 and 26,758 L in grazing and confinement systems, respectively. Intensified scenarios required an investment of capital between two and three times higher than the BASE scenario. All scenarios had positive economic results. The BASE scenario showed both the lowest farm operating profit and the lowest return on assets ($99/ha per year and 4.1%, respectively). Intensified grazing systems had the highest return on assets (above 12%), while the COMPOST system showed the highest farm operating profit ($1121/ha per year) and the lowest return on assets (7.5%) of the intensification alternatives explored. According to stochastic simulations, the COMPOST and DRYLOT scenarios would expose farmers to a greater maximum loss than BASE and grazing scenarios when negative farm operating profit occurred. However, cumulative distribution functions of profit showed that they would have higher profit than BASE and grazing scenarios along most of the CDF curve. SignificanceFarmers who decide to intensify their systems will have higher profit compared with BASE scenario, but should be prepared to afford higher investment and also to cope with increased variability of profit under price or climate risk. If the switch from a BASE scenario was to be implemented at a national scale, it would impact on surplus milk that might cause significant changes beyond farm gate. Further research is required to investigate the environmental impact of intensification alternatives.

147 Use of Productivity Enhancing Technologies in Beef Steers Reduces Greenhouse Gas Emission Intensity

Abstract In the last decade, the cattle industry has witnessed increased demand from domestic and international markets for hormone and antibiotic free beef. However, the environmental consequences of switching from conventional production to “natural” beef have not been extensively examined. This study explored greenhouse gas (GHG) emissions estimated using a whole-farm model, Holos (www.agr.gc.ca/holos-ghg) with model inputs from a 2-year replicated study in which calves were managed from weaning to finishing with 6 treatments based on body weight and feeding strategy. Treatments included Heavy (H), which were directly finished, Medium (M), which were backgrounded prior to finishing, and Light (L), which were backgrounded and then grazed during the summer before being placed on a finishing diet. Each treatment was subdivided into two management practices: Conventional (CON) in which productivity enhancing technologies (PETs) were used (ionophores, steroid implants and beta-adrenergic agonists) and Natural (NAT) in which PETs were removed. Emission intensity (kg CO2e kg-1 boneless beef) of HNAT was 17.3 to 20.1% higher than HCON, MNAT was 20.3 to 20.5% higher than MCON and LNAT were 11.5–12.6% higher than LCON treatment. Conventional treatments, using PET’s, reduced GHG emissions, however grazing should be considered for its potential to store and promote carbon sequestration in perennial grasslands.

350 Nutrient Movement in the Environment: Confined versus Grazing Systems

Abstract Grazing systems perform multiple ecosystem services including food production, climate regulation, nutrient cycling, and erosion control. Ruminants can also express their natural behaviors on pasture, with recent research revealing that dairy cows were more motivated to go outside for grazing than stay indoors consuming fresh TMR offered immediately after the afternoon milking. In addition, consumers often associate grazing systems with “healthier and happier cows” and are willing to pay premiums for “grass-fed” dairy products. However, milk production and nutrient utilization generally decrease in pasture-based compared with confinement systems, which may reduce farm profitability depending on milk pay prices. It should be noted that there is limited research reporting milk N efficiency (milk N/N intake) or methane emissions in confined versus grazing dairy cows using data collected from the same experiments. Therefore, our overarching objective was to build data sets to compare nutrient utilization in dairy cows under confinement or grazing management where milk N efficiency or methane emissions or both were reported in the same study. Dietary strategies to mitigate methane emissions in grazing dairy systems such as the use of high-quality forages (e.g., brassicas, perennial ryegrass), concentrate and seaweed supplementation, and forage species and management will be explored. For instance, Jersey cows grazing forage canola offered at 40% of the total DM emitted 31% less methane than those kept indoors and fed TMR (419 vs. 289 g/d, respectively) in an experiment conducted at the University of New Hampshire. Methane yield and methane intensity also decreased (P < 0.001) by 29.3% and 23.4%, respectively, in the same study. Irish researchers reported that methane production (-37%), yield (-11.5%), and intensity (-13%) decreased significantly in Holstein-Friesian cows offered perennial ryegrass herbage versus TMR. Data from whole-farm models comparing confinement and grazing systems will be presented and discussed.

169 Estimating the Environmental Impact of Livestock Operations Using the Canadian Whole-farm Model Holos Developed for Canadian Farmers

Abstract The Holos model is a Canadian whole-farm model that uses IPCC Tier II emission factors to calculate greenhouse gas (GHG) emissions from Canadian farming systems. These Tier II emission factors are Canada-specific with respect to land-based nitrous oxide emission, but are universal with respect to the livestock calculation. Here, however, Tier II is limited to ruminant animals, as so far only Tier I models are available for monogastrics. The model is designed to permit farmers to enter readily available farm management information themselves in order to calculate GHG sources and management driven mitigation practices. The presentation will provide an overview of the model and its design (interface and algorithms), and will showcase some of the scientific studies (cradle-to-farmgate) that were accomplished using the Holos model for assessing the carbon footprint of Canadian beef and dairy production systems.

Whole-farm modelling of grazing dairy systems in Uruguay

CONTEXTModelling grazing dairy systems from the temperate hot-summer climate region of South America is challenging due to the absence of suitable whole-farm models developed or evaluated in this region. The use of whole-farm models developed in other regions represents an opportunity. However, the accuracy and precision of their predictions need to be assessed. OBJECTIVESThe present study evaluated the predictive ability of Farmax Dairy Pro, a whole-farm model developed in New Zealand, to simulate grazing dairy systems in Uruguay. METHODSData used for the model evaluation was obtained from a dairy farmlet study carried out in Uruguay. The study aimed to explore four intensification strategies based on increasing home-grown forage utilisation and milk output per hectare. The field experiment consisted of four farmlets using two feeding strategies: [Grass Maximum (GMAX) and Grass Fixed (GFIX), based on the amount of grazed herbage in the diet], and two cow genotypes [New Zealand (NZHF) or North American Holstein-Friesian (NAHF)]. The four farmlets were modelled with Farmax for two consecutive years. Model evaluation was performed using standard regression, dimensionless and error index statistics. The model was evaluated by comparing predicted versus observed monthly patterns of milk, milk fat, milk protein and milk solids (MS; milk fat + milk protein) yields, body condition score (BCS), body weight (BW), DM intake (DMI) and net pasture growth rate (PGR). An application of the model was demonstrated by modelling three scenarios for the GMAX-NZHF farmlet. RESULTS AND CONCLUSIONSThe predictive ability of Farmax was similar for the four farmlets modelled, including patterns over time, for all the variables evaluated. The model provided a robust prediction for monthly patterns of milk and milk components yields at a herd level for total DMI and PGR. The model had a moderate ability to predict monthly patterns of individual milk and milk components yields and BCS, and a poor ability to predict BW. The scenario modelling results indicate that the model could be used with confidence to simulate different farm system alternatives. Overall, the Farmax Dairy Pro model had the potential to provide adequate predictions for grazing dairy systems from Uruguay. SIGNIFICANCEThis model will allow the exploration of future intensification pathways for grazing dairy systems in Uruguay and the region, including changes in the forage sequence, stocking rate and calving season. Further adjustments of the model will expand the range of systems and latitudes for this model to be utilised.

Evaluating Three-Pillar Sustainability Modelling Approaches for Dairy Cattle Production Systems

Milk production in Europe is facing major challenges to ensure its economic, environmental, and social sustainability. It is essential that holistic concepts are developed to ensure the future sustainability of the sector and to assist farmers and stakeholders in making knowledge-based decisions. In this study, integrated sustainability assessment by means of whole-farm modelling is presented as a valuable approach for identifying factors and mechanisms that could be used to improve the three pillars (3Ps) of sustainability in the context of an increasing awareness of economic profitability, social well-being, and environmental impacts of dairy production systems (DPS). This work aims (i) to create an evaluation framework that enables quantitative analysis of the level of integration of 3P sustainability indicators in whole-farm models and (ii) to test this method. Therefore, an evaluation framework consisting of 35 indicators distributed across the 3Ps of sustainability was used to evaluate three whole-farm models. Overall, the models integrated at least 40% of the proposed indicators. Different results were obtained for each sustainability pillar by each evaluated model. Higher scores were obtained for the environmental pillar, followed by the economic and the social pillars. In conclusion, this evaluation framework was found to be an effective tool that allows potential users to choose among whole-farm models depending on their needs. Pathways for further model development that may be used to integrate the 3P sustainability assessment of DPS in a more complete and detailed way were identified.

Closing sustainability gaps on family farms: Combining on-farm co-innovation and model-based explorations

In Uruguay sustainability of family farm systems is threatened by soil degradation, low yields and excessive workloads resulting in low labour productivity, low family income and high erosion rates. The productive and environmental performances of most Uruguayan family farms are well below levels achievable with current resource availability. This paper aims to show the productive and environmental improvements simultaneously possible by addressing resource management and organization of the farm system as a whole. We report results from two learning cycles on 4 case study farms and address their interdependence. The first cycle involved on-farm re-design in a co-innovation process that led to significant improvements in the performance of the case study farms. The insights gained during co-innovation work were used to parameterize a bio-economic whole-farm model to explore the space for further performance improvement and to inform future co-innovation processes. The two learning cycles characterized three farm performance levels: the initial farm performance (IniFP), representing the state of the farm at the start of co-innovation, the improved farm performance (ImpFP) at the end of co-innovation, and the attainable farm performance (AttFP) estimated with the FarmImages model. Difference between ImpFP and AttFP represent the sustainability gap. After three years of co-innovation, family income on the four farms improved by 16 to 350%, while labour productivity increased by 11% to 214%. Model explorations showed that significant further improvement in socio-economic results was possible while maintaining soil erosion under the tolerance level. The strategies identified differed among the four farms depending on their resource endowment and the technologies available, confirming the need for a systemic perspective and tailor-made solutions. We show how an inclusive whole-farm approach comprising co-innovation and model-based explorations contributes to connecting scientific insights with practical contextualization to close sustainability gaps on family farms.

173 Greenhouse gas emissions and land use associated with the removal of growth-enhancing technologies from backgrounding and finishing cattle in Canada: A case study

Abstract Greenhouse gas emissions from backgrounding and finishing cattle with and without the use of growth-enhancing technologies (GET) were estimated using a whole-farm model, Holos (www.agr.gc.ca/holos-ghg). Model inputs were obtained from a four-year performance study using heifers (H) and steers (S) with six treatments (n = 40 hd treatment-1 yr-1): 1) H control (HCon); 2) H implanted (HTBA); 3) H melengestrol acetate (HMGA); 4) S control (SCon); 5) S implanted (STBA); and 6) S implanted + ractopamine hydrochloride (SRAC; conducted in the last two years). All cattle were finished to achieve a consistent number of days on feed (DOF; n = 233 ± 8). Lighter finish weights were observed for HCon and SCon. As a result, DOF were adjusted (-1 to 65 d) to achieve the same final weight as GET-treated cattle. Total emissions (kg CO2e head-1) were greater for Hcon_AdjHTBA (2967 ± 183) and HCon_AdjHMGA (2766 ± 84), than HTBA (2897 ± 184) and HMGA (2730 ± 81). Similarly, total emissions (kg CO2e head-1) for SCon_AdjSTBA (3169 ± 192) and SCon_AdjSRAC (3252 ± 202) were greater than STBA (2998 ± 153) and SRAC (3097 ± 185), respectively. On an intensity basis, (kg CO2e kg slaughter weight-1), emissions from GET-treated cattle [HTBA (4.49 ± 0.19), HMGA (4.39 ± 0.13), STBA (4.28 ± 0.17), and SRAC (4.31 ± 0.25)] were lower than HCon_AdjHTBA (4.60 ± 0.21), HCon_AdjHMGA (4.45 ± 0.18), SCon_AdjSTBA (4.52 ± 0.23), and SCon_AdjSRAC (4.52 ± 0.28), respectively. Furthermore, land-use (ha 100 kg slaughter weight-1) was reduced for GET-treated cattle (HTBA (0.068 ± 0.001), HMGA (0.067 ± 0.001), STBA (0.066 ± 0.001), and SRAC (0.067 ± 0.000)) compared to HCon_AdjTBA (0.071 ± 0.001), HCon_AdjMGA (0.069 ± 0.002), SCon_AdjTBA (0.072 ± 0.002), and SCon_AdjRAC (0.0073 ± 0.001), respectively. This study demonstrates that GETs can reduce the environmental footprint of beef cattle.

Fodder beet to support early and late lactation milk production from pasture, is it worth the risk?

High yielding crops such as maize (Zea mays L.) and fodder beet (FB; Beta vulgaris L), are commonly used to extend lactation and increase animal productivity from pastoral dairy systems. Financial modelling to compare costs and benefits of different crops is useful for decision making, but such modelling often fails to account for potential animal health risks which can be associated with feeding supplements. A multi-component, whole-farm modelling approach was used to predict milk solids (MS, milk fat + protein) production and the economic farm surplus (EFS: operating surplus – adjustments) between 2016 and 2018 for an irrigated farm in Canterbury (South Island) and a non-irrigated farm in the Waikato (North Island), of New Zealand. The financial risk of the dairy business was measured using the ratio between mean return on assets (ROA) minus an assumed 5% risk-free ROA, and the standard deviation of ROA was calculated from 300 combinations of climate, milk, and feed price, land appreciation, and interest rate. Four scenarios of autumn and spring supplementation of pasture were considered at each geographical location; imported maize silage (Base), a crop of maize silage grown on the milking platform (MSC; area used to produce milk), a crop of FB grown on the milking platform (FBC), and a FB crop with an outbreak of acute (1% stock fatality) and subacute ruminal acidosis (5% decline of feed intake) across the entire herd (FBAC). The MSC scenario improved EFS by 5.8% compared with Base in both the irrigated and the dryland system. The predicted response to MSC reflected greater milk production, lower feed expenses, and shorter crop rotation, compared with either Base, FBC, or FBAC. While FBC increased EFS by 4.8% compared with Base under irrigation, EFS was similar to Base under dryland conditions ($2711 and $2759/ha, respectively). The limited advantage of growing FB under dryland conditions reflect reduced herbage supply due to the extended crop duration of FB compared with maize silage. Model predictions suggest that FBAC will increase the financial risk by reducing milk production and EFS by 6.5% (irrigated) and 7.1% (dryland) compared with Base. In the absence of any adverse health risks, farm performance from the FBC scenario was comparable to that of MSC under irrigated conditions. However, in dryland conditions, and when the potential economic cost of acute and sub-acute ruminal acidosis is considered, there is little advantage to growing FB on the milking platform.

Demonstration and Testing of the Improved Shelterbelt Component in the Holos Model

Using a participatory approach, the shelterbelt component of Canada’s whole-farm model Holos was upgraded from an age-determined to a circumference-determined (at breast height) calculation using a multi-stem averaging approach. The model interface was developed around the idea that a shelterbelt could have multiple rows, and a variable species composition within each row. With this, the model calculates the accumulated aboveground carbon in the standing biomass and a lookup table of modelled tree growth is used to add estimates of the belowground carbon. Going from an initial interface that asks for the current state, the model also incorporates an option of past and future shelterbelt plantings. In order to test the model’s suitability, we measured diverse shelterbelts (evergreen, deciduous, shrub type) in southern Saskatchewan, Canada representing commonly planted woody species. By making use of Caragana, Green Ash, Colorado Spruce, Siberian Elm, and a mixed Caragana/Green Ash tree rows, we tested how many tree circumference measurements would be required to yield a representative average. Later, these results were incorporated in the Holos model to calculate the accumulated above- and below-ground carbon in each shelterbelt type.

Mitigation of greenhouse gas emissions from beef cattle production systems

ABSTRACT The whole-farm model HolosNorBeef was used to estimate the efficiency of GHG emission mitigation strategies in Norwegian beef cattle herds. Various mitigation scenarios, involving female reproductive performance (i.e. calf mortality rate and the number of calves produced per cow per year), production efficiency of young bulls for slaughter (i.e. age at slaughter and carcass weight), and supplementation of an inhibitor currently reported as promising for enteric methane (CH4) inhibition (3-nitrooxypropanol; 3-NOP) was investigated in herds of British and Continental breeds. Reducing calf mortality and increasing the number of produced calves per cow per year both reduced emission intensities by 3% across breeds. Continental breeds showed greater potential of reducing emission intensities due to increased carcass production. Combining mitigation options in a best case scenario reduced the total emissions by 11.7% across breeds. The emission intensities could be further reduced by 8.3% with the use of 3-NOP.

An environmental assessment of grass-based dairy production in the northeastern United States

Demand for grass-based dairy production, which relies heavily on grazing and use of forage crops, is growing in the United States, primarily due to reported human health benefits of the milk produced as well as perceived environmental and animal welfare benefits. We used a whole-farm model to evaluate environmental footprints of all-grass, grass supplemented with grain, and confinement dairy production systems in the temperate climate of the northeastern U.S. Model results were depicted per unit of farmland and per unit of milk produced to provide alternate perspectives from the viewpoint of land management and commodity production. For most environmental indicators, the grass-based systems had smaller environmental impacts per unit of farmland but larger impacts per unit of milk produced compared to confinement fed systems. To verify the simulation of grass-based operations, eight dairy farms - ranging from herds that were grazed and fed only forage to herds that received some grain supplementation - were surveyed and modeled. Due to variation in climate, soil characteristics and management practices, a comparison of the two grass-based farm types showed no significant differences in environmental impacts. Farms of the same size using each production strategy along with a more traditional confinement production system were then simulated using the same climate and soil conditions for a better comparison. Predicted nitrogen and phosphorus losses to the environment, fossil energy use, water use, and greenhouse gas emissions were less from the grass-based farms compared to the confinement operation. Due to lower milk production on the grass-based dairies, nutrient losses and greenhouse gas emissions expressed per unit of milk produced were generally greater than those of the confinement system. Within the grass-based dairy systems, the system that supplemented with grain had slightly lower nitrogen and phosphorus losses per unit of farmland compared to the grass-only system, and much lower losses and emissions when expressed per unit of milk produced. Total production cost was less for the all-grass dairy than the grass with grain dairy. With a greater milk price, the all-grass system provided greater profitability per unit of land used and per unit of milk produced compared to the confinement farm of similar size. These data indicate that grass-based dairy farms can provide environmental benefits to a local watershed, but due to a lower efficiency in milk production, they may increase the aggregate environmental impacts of regional and global supply chains.

Variability in greenhouse gas emission intensity of semi-intensive suckler cow beef production systems

Emission intensities from beef production vary both among production systems (countries) and farms within a country depending upon use of natural resources and management practices. A whole-farm model developed for Norwegian suckler cow herds, HolosNorBeef, was used to estimate GHG emissions from 27 commercial beef farms in Norway with Angus, Hereford, and Charolais cattle. HolosNorBeef considers direct emissions of methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2) from on-farm livestock production and indirect N2O and CO2 emissions associated with inputs used on the farm. The corresponding soil carbon (C) emissions are estimated using the Introductory Carbon Balance Model (ICBM). The farms were distributed across Norway with varying climate and natural resource bases. The estimated emission intensities ranged from 22.5 to 45.2 kg CO2 equivalents (eq) (kg carcass)−1. Enteric CH4 was the largest source, accounting for 44% of the total GHG emissions on average, dependent on dry matter intake (DMI). Soil C was the largest source of variation between individual farms and accounted for 6% of the emissions on average. Variation in GHG intensity among farms was reduced and farms within region East, Mid and North re-ranked in terms of emission intensities when soil C was excluded. Ignoring soil C, estimated emission intensities ranged from 21.5 to 34.1 kg CO2 eq (kg carcass)−1. High C loss from farms with high initial soil organic carbon (SOC) content warrants further examination of the C balance of permanent grasslands as a potential mitigation option for beef production systems.