A Modelling Framework for Optimising Investment for the Australian Livestock Industry

Despite the scale and importance of the beef industry in the north of Australia, recent political and environmental disruptions have highlighted the vulnerability of the supply chain. Ensuring that the supply chain remains resilient to climatic events as well as to unexpected decisions by the stakeholders will require careful planning and investment in logistics. In this paper, we outline an integrated methodology based on tactical and operational dynamic models, for assessing the effect of changes in the supply chain. Emphasis is on the development of an optimisation model that covers the ow of cattle from properties to agistment farms and feedlots to abattoirs/ports, and the selection of rest areas (spelling yards) along the path. The model selects the optimal location of spelling yards along the road network, subject to budget, site capacity, and service requirements. We show preliminary results for a case study comprising Western Australia and the Northern Territory.Sociedad Argentina de Informática e Investigación Operativ

A Modelling Framework for Optimising Investment for the Australian Livestock Industry

Despite the scale and importance of the beef industry in the north of Australia, recent political and environmental disruptions have highlighted the vulnerability of the supply chain. Ensuring that the supply chain remains resilient to climatic events as well as to unexpected decisions by the stakeholders will require careful planning and investment in logistics. In this paper, we outline an integrated methodology based on tactical and operational dynamic models, for assessing the effect of changes in the supply chain. Emphasis is on the development of an optimisation model that covers the ow of cattle from properties to agistment farms and feedlots to abattoirs/ports, and the selection of rest areas (spelling yards) along the path. The model selects the optimal location of spelling yards along the road network, subject to budget, site capacity, and service requirements. We show preliminary results for a case study comprising Western Australia and the Northern Territory.Sociedad Argentina de Informática e Investigación Operativ

A Modelling Framework for Optimising Investment for the Australian Livestock Industry

Despite the scale and importance of the beef industry in the north of Australia, recent political and environmental disruptions have highlighted the vulnerability of the supply chain. Ensuring that the supply chain remains resilient to climatic events as well as to unexpected decisions by the stakeholders will require careful planning and investment in logistics. In this paper, we outline an integrated methodology based on tactical and operational dynamic models, for assessing the effect of changes in the supply chain. Emphasis is on the development of an optimisation model that covers the ow of cattle from properties to agistment farms and feedlots to abattoirs/ports, and the selection of rest areas (spelling yards) along the path. The model selects the optimal location of spelling yards along the road network, subject to budget, site capacity, and service requirements. We show preliminary results for a case study comprising Western Australia and the Northern Territory.Sociedad Argentina de Informática e Investigación Operativ

Climate change adaptation through planted forages in Southern Highlands, Tanzania

Smallholder farmers (SF) are the biggest food producers in Tanzania (TZ), where hetero- geneous mixed crop-livestock farming systems dominate agriculture (Fig 1). Feed scarcity and quality are major issues facing smallholder dairy farmers in Tanzania. Climate projections for Tanzania indicate increased length of dry seasons and severity of periodic droughts. These expected impacts will affect farm productivity, leaving farmers more vulnerable. The planting of improved grass and legume forages, if properly managed, has the potential to improve livestock productivity and resilience which can help SF adapt to climate chang

Yield gap analyses to estimate attainable bovine milk yields and evaluate options to increase production in Ethiopia and India

Livestock provides an important source of income and nourishment for around one billion rural households worldwide. Demand for livestock food products is increasing, especially in developing countries, and there are opportunities to increase production to meet local demand and increase farm incomes. Estimating the scale of livestock yield gaps and better understanding factors limiting current production will help to define the technological and investment needs in each livestock sector. The aim of this paper is to quantify livestock yield gaps and evaluate opportunities to increase dairy production in Sub-Saharan Africa and South Asia, using case studies from Ethiopia and India. We combined three different methods in our approach. Benchmarking and a frontier analysis were used to estimate attainable milk yields based on survey data. Household modelling was then used to simulate the effects of various interventions on dairy production and income. We tested interventions based on improved livestock nutrition and genetics in the extensive lowland grazing zone and highland mixed crop-livestock zones of Ethiopia, and the intensive irrigated and rainfed zones of India. Our analyses indicate that there are considerable yield gaps for dairy production in both countries, and opportunities to increase production using the interventions tested. In some cases, combined interventions could increase production past currently attainable livestock yields

Closing yield gaps in smallholder goat production systems in Ethiopia and India

Small ruminants such as goats are an important source of income for smallholder farmers in South Asia and Sub Saharan Africa: they may be kept as a stepping stone to owning larger and higher-value animals such as cattle or buffalo, or provide a more-profitable and less-risky alternative in marginal or densely populated areas where access to feed resources are limited. However, smallholder goat production in these areas is often low due to low growth and reproduction rates and high animal mortality. The aim of this study was to investigate the potential for different intervention packages to increase yields and profitability of goat meat production in Ethiopia and India. Packages were based on improved nutrition, reduced flock mortality from improved control of health and diseases, and replacing indigenous livestock with improved goat breeds. Household modelling was used to simulate the effects of interventions on goat production and household income in the extensive lowland grazing zone and highland mixed crop-livestock zones of Ethiopia, and the extensive arid zone of India. Our analysis showed that there are opportunities to increase goat meat production in both countries. Reproduction, liveweight gain and survival rates can be increased through better nutrition, genetics and healthcare, but the biggest increase in production and profits occurred when multiple interventions were combined. Importantly, interventions resulting in the biggest increases in goat meat production or number of animals sold did not always give the highest profits

Additive impacts of climate-smart agriculture practices in mixed crop-livestock systems in Burkina Faso

Smallholder farmers of Northern Burkina Faso have important development opportunities, but they will haveto cope with the effects of climate variability and change. In four farms representative of the area, crop andanimal production, income and food security indicators have been simulated, with all combinations of fourinterventions: i) Optimized crop residue collection; ii) Improved allocation of existing feeds, iii) Cropfertilization; iv) Animal supplementation. The modeling framework we used is based on three existingdynamic livestock (Livsim), crop (Apsim) and household (IAT) models. To assess the impacts of climatevariability, a 99 years current climate series has been generated with the climate generator Marksim. Thesimulations show that collecting crop residues improves significantly the food security indicator (FS) in onefarm because it enables the development of cattle production (FS +135%), whereas the effects are moderate in the three other farms (FS <10%). Low amounts of fertilizer have a significant effect (FS +15%), but thesimulations show decreasing yield returns and the higher downside risk in the bad years. Improved feedallocation strategies with available resources have a positive effect (FS +9%), which is as important assupplementation with additional feeds. The impacts of the tested interventions are additive and synergistic,because increased crop residues production with fertilization creates opportunities for optimized feeding. As a consequence, in the four farms, the highest income and kilocalorie production (up to 53% compared to current farmer practices) are obtained with a combination of interventions enhancing synergies between the crop and the livestock systems. The household yearly probability to be food secure also increases by up to +26%, suggesting an increased resiliency toward climate variability. We conclude that the best options for adapting mixed crop-livestock systems might be found in the synergies between their components, rather than in single interventions

Assessing potential climate change impacts in smallholder systems in Burkina Faso

Understanding how climate change might impact agricultural systems at a household level is crucial in the development of adaptation strategies. In this study we assessed the sensitivity of four different types of smallholder mixed crop-livestock systems in Burkina Faso, to the potential impacts of climate change, based on the changes in household income and kilocalorie production. The four systems with different levels of resource endowment were simulated over 99 years using a whole farm model (APSFarm-LivSim), under current and future climate. The climate data for current climate variability and the climate change scenario were generated using the MarkSim™ tool. For future scenarios, we used the ensemble means of 17 global circulation models (CMIP5 data) for 2050, and IPCC scenario RCP 8.5. Under the projected climate scenario, average annual rainfall is expected to increase from 607mm to 674 mm (+11%). Additionally, average temperature is likely to increase by 2.6°C. Overall, these changes in climate showed to negatively affect crop yields, particularly cowpea (-25%), millet (-15%) and groundnuts (-5%); while sorghum and maize did not show significant changes in yields. At the household level, income and kilocalorie production were reduced by up to 17% and 13%, respectively, in a market-oriented household with a relatively smaller area per capita. Furthermore, we introduced two levels of fertilization in the simulation (+30 +60 Kg/N/Ha). The simulation showed that fertilizers have a positive impact on yields under current climate; however this effect decreases under the climate change scenario. For example, when adding 60 Kg/N/Ha, average maize yields increased by 145% under the current climate scenario, but only by 105% under the projected climate change scenario. This suggests that climate change might limit the potential of the farms to increase productivity