Evaluation des inefficiences zootechnique et environnementale pour intensifier écologiquement les systèmes d’élevage tropicaux. Etude de cas à la Réunion

Greenhouse gas emission profiles of European livestock sectors

Animal production is responsible for 14.5% of total anthropogenic greenhouse gas (GHG) emissions. Approximately half of these emissions originate directly from animal production, whereas the other half comes from feed production. Animal breeding aims at improving animal production and efficient use of resources, which results in a reduction of environmental impacts. The objective of this study was to quantify the contribution of animal breeding to reducing the environmental impact of the four major livestock species in the Netherlands (with their animal product), namely broilers (meat), laying hens (eggs), pigs (meat) and dairy cattle (milk). This study comprised of a literature review and a quantitative assessment of the current environmental impact and the result of recent genetic improvements. For broiler meat, chicken eggs and pig meat the focus was laid on GHG emissions and nitrogen and phosphorus efficiency, whereas for dairy the focus was laid on enteric methane emissions, an important contributor to GHG emissions. Results show that breeding reduces environmental impacts of animal products by about 1% per year. This is achieved without specific selection on environmental traits, but as an indirect response through selection on increased (feed) efficiency.

Animal production is responsible for 14.5% of total anthropogenic greenhouse gas (GHG) emissions. Approximately half of these emissions originate directly from animal production, whereas the other half comes from feed production. Animal breeding aims at improving animal production and efficient use of resources, which results in a reduction of environmental impact. In this chapter we quantify the contribution of animal breeding to reducing the environmental impact of the four major livestock species in the Netherlands, namely laying hens, broilers and pigs (all monogastrics), and dairy cattle (ruminants). For eggs, and broiler and pig meat we focussed on GHG emissions and nitrogen and phosphorus efficiency, whereas for dairy we focussed on enteric methane emissions, an important contributor to GHG emissions. Results showed that current selection strategies on increased (feed) efficiency indirectly reduces environmental impact per unit of animal product by about 1% per year. If the aim is to directly select on environmental traits, recording of new traits is required; e.g., nitrogen and phosphorus contents of meat and eggs, and methane emission of individual dairy cows.

This project aimed to develop a dataset containing animal policies, production efficiencies, and greenhouse gas (GHG) emissions of a large number of sheep and beef farms, and to examine the relationships between farm management and farm physical constraints, and GHG emissions. We used the farm-scale model Farmax to estimate feed inventories, livestock policies and GHG emissions of 170 New Zealand sheep and beef farms. Emissions were calculated from Farmax outputs using Agricultural Inventory methodology. We used a quantitative approach to cluster farms based on physical constraints and management attributes. Mean annual biological GHG emissions from the modelled farms were 3,662 kg CO2 equivalents (CO2-e) per effective hectare, and ranged from 157 to 7,096 kg CO2-e/effective ha. As stocking rate and animal product (wool + net carcass weight) per effective hectare increased, GHG emissions increased. However, there was considerable variability in the data; farms with GHG emissions of approximately 4,000 kg CO2-e/effective ha had an almost three-fold difference in animal product (range 129 to 360 kg/effective ha). Our work provides a holistic assessment of the farm-scale drivers of GHG emissions and a comprehensive current state of affairs or baseline from which future trends in farm-scale GHG emissions can be established.

The accurate quantification of the carbon footprints of animal products and the related development of greenhouse gas (GHG) mitigation strategies are of interest to consumers, the general public, and the academic community. The objective of this review was to summarize recent advances in GHG emission quantification, life‐cycle assessment applications, and mitigation technologies for animal production in the USA, to assist the development of system‐based solutions for mitigation of GHG emissions from animal production. The GHG emissions from animal production mainly come from feed production, enteric fermentation, and manure management. Opportunities to mitigate emissions from feed production largely rely on continuous improvements in animal and feed production efficiency. This is in general agreement with the economic interest of the industry. To mitigate emissions from manure, many technologies can be chosen, depending on the given economic and regulatory environments. It is possible to minimize GHG emissions from manure through manure energy recovery when this is economically feasible. For enteric emissions, there are limited opportunities to reduce GHG emissions through dietary manipulation, feed management, or feed supplementations. Improving environmental stewardship of consumers and reducing food waste will reduce animal protein demand and are important bottom‐line strategies to mitigate GHG from animal production systems. © 2018 Society of Chemical Industry and John Wiley & Sons, Ltd.

Increasing ewe genetic fecundity improves whole-farm production and reduces greenhouse gas emissions intensities: 1. Sheep production and emissions intensities

The goal of this review was to analyze published data on animal management practices that mitigate enteric methane (CH4) and nitrous oxide (N2O) emissions from animal operations. Increasing animal productivity can be a very effective strategy for reducing greenhouse gas (GHG) emissions per unit of livestock product. Improving the genetic potential of animals through planned cross-breeding or selection within breeds and achieving this genetic potential through proper nutrition and improvements in reproductive efficiency, animal health, and reproductive lifespan are effective approaches for improving animal productivity and reducing GHG emission intensity. In subsistence production systems, reduction of herd size would increase feed availability and productivity of individual animals and the total herd, thus lowering CH4 emission intensity. In these systems, improving the nutritive value of low-quality feeds for ruminant diets can have a considerable benefit on herd productivity while keeping the herd CH4 output constant or even decreasing it. Residual feed intake may be a tool for screening animals that are low CH4 emitters, but there is currently insufficient evidence that low residual feed intake animals have a lower CH4 yield per unit of feed intake or animal product. Reducing age at slaughter of finished cattle and the number of days that animals are on feed in the feedlot can significantly reduce GHG emissions in beef and other meat animal production systems. Improved animal health and reduced mortality and morbidity are expected to increase herd productivity and reduce GHG emission intensity in all livestock production systems. Pursuing a suite of intensive and extensive reproductive management technologies provides a significant opportunity to reduce GHG emissions. Recommended approaches will differ by region and species but should target increasing conception rates in dairy, beef, and buffalo, increasing fecundity in swine and small ruminants, and reducing embryo wastage in all species. Interactions among individual components of livestock production systems are complex but must be considered when recommending GHG mitigation practices.

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

The global animal food chain has a large contribution to the global anthropogenic greenhouse gas (GHG) emissions, but its share and sources vary highly across the world. However, the assessment of GHG emissions from livestock production is subject to various uncertainties, which have not yet been well quantified at large spatial scale. We assessed the uncertainties in the relations between animal production (milk, meat, egg) and the CO2, CH4, and N2O emissions in Africa, Latin America and the European Union, using the MITERRA-Global model. The uncertainties in model inputs were derived from time series of statistical data, literature review or expert knowledge. These model inputs and parameters were further divided into nine groups based on type of data and affected greenhouse gas. The final model output uncertainty and the uncertainty contribution of each group of model inputs to the uncertainty were quantified using a Monte Carlo approach, taking into account their spatial and cross-correlation. GHG emissions and their uncertainties were determined per livestock sector, per product and per emission source category. Results show large variation in the GHG emissions and their uncertainties for different continents, livestock sectors products or source categories. The uncertainty of total GHG emissions from livestock sectors is higher in Africa and Latin America than in the European Union. The uncertainty of CH4 emission is lower than that for N2O and CO2. Livestock parameters, CH4 emission factors and N emission factors contribute most to the uncertainty in the total model output. The reliability of GHG emissions from livestock sectors is relatively high (low uncertainty) at continental level, but could be lower at country level.

A whole farm systems analysis of greenhouse gas emissions of 60 Tasmanian dairy farms

One of the problematic sectors according to GHG (greenhouse gas) and ammonia (NH3) emission quantities is agriculture. Without endangering food production (and intensifying), GHG emissions come from all sources in animal husbandry. The aim of this study was to comprehensively reduce GHG emissions by applying a holistic process management model to one of the most popular cowsheds in Lithuania (260-seat boxing cowshed, cows are milked on site, computerized management of technological processes, productivity of 8600 kg of milk, barn system, and liquid manure). Considering the cow keeping technology applied on the farm, the equipment used, and the feed production and ration system, a model for the management of technological parameters of production processes was prepared for the farm. This model balanced trade-offs among animal welfare, cow productivity, production costs, and GHG and NH3 emissions. The aim of the research was the adaptation of the integrated model to fully control, manage, and optimize milk production processes through bio- and engineering innovations to implement climate-friendly feed production and feeding and feed rationing systems, to improve animal housing and working conditions, and to reduce GHG and NH3 emissions without increasing production costs. The environmental impact assessment was performed with SimaPro 9.1 process modeling software. Data from milk production, biomass cultivation, and feed preparation, transportation, and equipment were used from the Ecoinvent v3 database. Based on the LML-I calculation methodology, the effect of processes was determined. To quantify the potential emissions in the dairy farm, the emission factors were estimated using a life cycle assessment method per functional unit—1000 kg—of standardized milk. Grass silage, maize silage, and feed concentrate were found to account for the largest share of gas emissions—26.09% (107.39 kg CO2 eq. FU−1), 22.70% (93.44 kg CO2 eq. FU−1), and 21.85% (89.92 kg CO2 eq. FU−1) of the total CO2 emissions during the process, respectively. Considering the critical points of the classic SC scenario, the cultivation technology was adjusted, where 50% of N fertilizers were replaced by bioproducts (biological preparations). Both scenarios—classic SC (control variant) and Bio SC (variants using bioproducts)—were evaluated for comparison. The use of biopreparations in the categories reduced the environmental impact from 0.1% to 45.7% in dairy production technology grass silage, barley grain, hay production, and corn silage stocks. The carbon footprint of the sustainable bio-based milk production (0.393 kg CO2 eq. kg−1 FPCM (fat- and protein-adjusted milk)) was lower by 4.6% compared to the average Lithuanian classic dairy farm (0.412 kg CO2 eq. kg−1 FPCM). Based on this methodology, it is possible to assess many dairy farms and address critical points in an integrated way, which can help to improve the quality of dairy production and the environment.

<p> It has been widely reported that although IPCC methodologies appropriate for national-level accounting purposes, they lack the farm level resolution and holistic approach required for whole-farm systems analysis. The importance of evaluating greenhouse gas (GHG) emissions from crop production, animal farming and agroforestry within the whole farm setting is being realized as more important than evaluating these emissions in isolation. Thus, whole-farm systems modelling is widely used for farm-level analysis. Here we compare three whole-farm models e.g. FarmSim, Holos and IFSM to simulate the effect of management practices on GHG emissions at the whole farm level and evaluate the carbon sequestration and methane oxidation potential of afforestation as a compensation mechanism for the mitigation of farm-level GHG emissions. Ideally, we would also want information on model performance in predicting GHG emissions in future climatic scenarios. Initial results indicate that these models can accurately predict CO<sub>2</sub> emissions but the accuracy of these models for predicting methane (CH<sub>4</sub>) and nitrous oxide (N<sub>2</sub>O) emissions is quite low. We found that the most prominent drivers for GHG emissions in a whole farm setting were the enteric CH<sub>4</sub> from animal farming and N<sub>2</sub>O emissions from soil management in cropland.  Thus, the low prediction accuracy for CH<sub>4</sub> and N<sub>2</sub>O emissions in whole-farm models may introduce substantial errors into GHG inventories and lead to incorrect mitigation recommendations, which necessitates further fine-tuning of these models. Efforts are ongoing to integrate carbon sequestration and soil methane oxidation potential of farm-level afforestation in the whole farm models. There are indications that afforestation can be an effective mitigation strategy. The variation we found in farm system parameters, and the inherent uncertainties associated with emissions of CH<sub>4</sub> and N<sub>2</sub>O can have substantial implications for reported agricultural emissions requiring uncertainty or sensitivity analysis in any modelling approach. Although there is considerable variation among the quality of farm data, boundary assumptions, the emission factors used we suggest that whole-farm systems models are an appropriate tool to develop and measure GHG mitigation strategies for the European farmed landscape.</p>

A review of whole farm systems models of greenhouse gas emissions from beef and dairy cattle production systems

BackgroundSocietal pressures exist to reduce greenhouse gas (GHG) emissions from farm animals, especially in beef cattle. Both total GHG and GHG emissions per unit of product decrease as productivity increases. Limitations of previous studies on GHG emissions are that they generally describe feed intake inadequately, assess the consequences of selection on particular traits only, or examine consequences for only part of the production chain. Here, we examine GHG emissions for the whole production chain, with the estimated cost of carbon included as an extra cost on traits in the breeding objective of the production system.MethodsWe examined an example beef production system where economic merit was measured from weaning to slaughter. The estimated cost of the carbon dioxide equivalent (CO2-e) associated with feed intake change is included in the economic values calculated for the breeding objective traits and comes in addition to the cost of the feed associated with trait change. GHG emission effects on the production system are accumulated over the breeding objective traits, and the reduction in GHG emissions is evaluated, for different carbon prices, both for the individual animal and the production system.ResultsMultiple-trait selection in beef cattle can reduce total GHG and GHG emissions per unit of product while increasing economic performance if the cost of feed in the breeding objective is high. When carbon price was $10, $20, $30 and $40/ton CO2-e, selection decreased total GHG emissions by 1.1, 1.6, 2.1 and 2.6% per generation, respectively. When the cost of feed for the breeding objective was low, selection reduced total GHG emissions only if carbon price was high (~ $80/ton CO2-e). Ignoring the costs of GHG emissions when feed cost was low substantially increased emissions (e.g. 4.4% per generation or ~ 8.8% in 10 years).ConclusionsThe ability to reduce GHG emissions in beef cattle depends on the cost of feed in the breeding objective of the production system. Multiple-trait selection will reduce emissions, while improving economic performance, if the cost of feed in the breeding objective is high. If it is low, greater growth will be favoured, leading to an increase in GHG emissions that may be undesirable.

Infectious Diseases, Livestock, and Climate: A Vicious Cycle?