Session 1.8: Livestock and Grasslands
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Session 1.8: Oral Presentation
Title: Large scale impacts of grazing management under climate change
Authors: Susanne Rolinski1, I. Weindl1,2, J. Heinke1,3, B. L. Bodirksy1,3, A. Biewald1, C. Müller1, and H. Lotze-Campen1,4 1 RD Climate Impacts and Vulnerabilities, Potsdam Institute for Climate Impact Research, Potsdam, Germany, 2 Leibniz Institute for Agricultural Engineering Potsdam-Bornim, Potsdam, Germany, 3 Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia, 4 Humboldt University of Berlin, Berlin, Germany
Abstract: The potential of grasslands to sequester carbon and provide feed for livestock production depends on climatic conditions but also on management and grazing pressure. We use a global dynamic vegetation and agriculture model (LPJmL) to study spatially explicit feedbacks between grazing/mowing and primary productivity and impacts on soil carbon content under different management settings. Applying different animal densities as well as grazing durations, we quantify impacts on the carbon cycle due to climatic conditions and the grazing pressure and timing. Varying the density of grazing animals also enables to find local optimal densities which simultaneously enhance primary productivity and grass yield while maintaining soil carbon. We show that low animal densities increase grass productivity whereas high grazing pressure deteriorates the plants’ ability to recover. The global application of this concept provides information on potential grass yields under varying climatic conditions to explore options for sustainable pasture-based livestock production.
Title: Impact of climate change on the livestock component of mixed farming systems: modelling evidence from regional integrated assessments across sub-Saharan Africa and South Asia
Authors: Katrien Desceemaeker1, M. Zijlstra1, T. Ramilan2, T. Senda3, E.C. Timpong-Jones4, A. Nenkam5, M. Sajid6, S. Singh7, G. Baigorria8, M. Adam9, K. Shalander10, and A. Whitbread10 1 Wageningen University, Netherlands, 2 Massey University, New Zealand, 3 Matopos Research Insitute, Zimbabwe, 4 University of Ghana, Ghana, 5 ICRISAT, Mali, 6 USPCAS-AFS, Pakistan, 7 ICAR, India, 8 University of Nebraska-Lincoln, USA, 9 CIRAD-ICRISAT, Burkina Faso, 10 ICRISAT, India
Abstract: Mixed crop–livestock systems play an important role in global food production and livelihood provision of millions of rural households. Climate change is projected to alter the functioning and productivity of these systems. Although for many regions the impact of climate change is projected to be large, many uncertainties persist, in particular with respect to impacts on livestock and grazing components, whole-farm dynamics and heterogeneous farm populations. Using an integrated modelling framework we simulated fodder and grassland productivity for current and future climate scenarios. This data was subsequently used as input in a dynamic livestock model LIVSIM to investigate climate change impacts on animal productivity. The modelling framework simulates entire farm populations, thus capturing the effects of farm heterogeneity. Livestock-related output variables included milk production, herd dynamics, calving and offtake rates, and mortality rates. In integrated assessments, these livestock outputs are used in economic models at
the household level. The modelling approach was applied across four distinct regions, including southern Africa, West Africa, Pakistan and India. This allowed capturing a wide diversity in farming systems and climate scenarios. Also various adaptation options targeting the crop, animal or grazing land components of mixed crop-livestock systems were investigated. Strong impacts of climate change and adaptation packages on livestock productivity were found in particular where impacts on feed quantity and quality were large. The differences in outputs were attributed to differences in growth-defining and
growth-limiting factors across the four regions.
Session 1.8: Oral Presentation
Title: Modelling nitrogen dynamics including leaching in intensive crop rotations on productive organic-sandy soils after the break-up of grassland
Authors: Munir P. Hoffmann1, R. P. Rötter1, J. Isselstein2, M. Kayser2 1 Crop Production Systems in the Tropics, University of Göttingen, Germany, 2 Grassland Science, University of Göttingen, Germany
Abstract: Developing site-specific nutrient management strategies is one option, where crop growth models have demonstrated they can play a special role. Against this background we evaluated APSIM in a two-year field trial comparing two rotations (maize monoculture and barley-mustard-maize) and two mineral fertilizer regimes (zero and high, i.e 160 and 120 kg N ha-1 for maize, respectively for barley) on three productive organic-sandy soils in North-west Germany after the break-up of grassland. After calibration APSIM simulated the independent data well: biomass (RMSE 17%, Index of agreement (IA) 0.97), N uptake (20%, 0.91), Nmin 0-30cm (53%, 0.91), Nmin 0-90cm (69%, 0.89), soil water 0-30 cm (30%, 0.84), soil water 0-90 cm (17%, 0.87) and N-leaching (39%, 0.93). Subsequently, we applied the model to a long-term simulation experiment using the same design as in the evaluation trial.
For maize monoculture, no differences were simulated for biomass or N-uptake between zero and high fertilizer due to high mineralization so that even the high N-demand of 200 kg ha-1 was satisfied. However, N-leaching for the fertilized treatment was very high (two years total 369 N kg ha-1). In the barley-mustard-maize treatment barley biomass was 20% lower for the zero fertilizer. Leaching losses (249 kg ha-1) were lower in comparison to the monoculture due to the cover crop after barley; however, in the second year large losses were simulated after maize. Future research should address modelling of gaseous losses, a neglected topic that is crucial for advancing understanding of the N-dynamics in the system.
Session 1.8: Oral Presentation
Title: Assessing simulation models for field scale projections of pasture GHG emissions and yields
Authors: Fiona Ehrhardt1, JF Soussana1, V. Snow2, R. Sandor3, R. McAuliffe2, G. Bellocchi3, and the consortium *
1 INRA, Paris, France, 2 AgResearch, Lincoln Research Centre, New Zealand, 3 INRA, Grassland Ecosystem Research, France, * L. Brilli, C. Doris, N. Fitton, M. Harrison, S. Jones, M. Kirschbaum, K. Klumpp, Mark Liebig, M. Lieffering, R. Martin, L. Merbold, A. Moore, V. Myrgiotis, P. Newton, S. Rolinski, L. Wu
Abstract: Over the last 30 years, simulation models have been extensively developed for agricultural greenhouse gas emissions (GHG) and soil carbon stock changes. Nevertheless, the predictive ability of these models has not been assessed and inter-compared and the use of ensemble, rather than single, models for projections has not been evaluated at international scale. The Soil C-N Group of the Global Research Alliance (GRA) on agricultural GHG has initiated an international model benchmarking and inter-comparison in this area for both crop and pasture models. An initial stock take has been conducted, resulting in the selection of datasets from five temperate grasslands and five arable crop rotation sites spanning four continents. A total of 24 models used in 11 countries for the prediction of GHG emissions in crop and grassland systems are contributing. These models have been benchmarked and inter-compared at these sites in a fully blind procedure. The study has been set up with five successive steps that gradually release information to the modeling groups, ranging from fully-blind application of the models to complete availability of the experimental measurements. Model simulations are compared to experimental measurements for crop yield and grassland dry-matter production, N2O emissions, soil C stocks and net CO2 exchanges. Results with temperate grasslands are presented, showing that multi-model estimates are more robust for projections of GHG emissions and removals than those from single models. Moreover, the sensitivity to climatic drivers of calibrated models has been analyzed within the grassland group of the AgMIP international program and projections of climatic impacts on GHG emissions are shown based on this ensemble. Based on these results, the use of
simulation models for field scale projections of current and future GHG emissions and removals from pastures is discussed.
17. Poster Presentation: Session 1.8
Title: Modeling Climate Change Impacts On Livestock Productivity In Semi-Arid Zimbabwe
Authors: Trinity Senda1 , K. Deschemaeker2 , S. H. K. Tui3 , P. Masikati4 , G. Sisito1 , O.
Crespo5 , and B. Francis6 1 Matopos Research Institute, Zimbabwe, 2 Plant production systems, Wageningen University, The Netherlands, 3 International Crops Research Institute for the Semi-arid Tropics (ICRISAT), Zimbabwe, 4 World Agroforestry Centre (ICRAF), Zambia, 5 Climate System Analysis Group, University of Cape Town,
South Africa, 6 Institute of Development Studies, Zimbabwe
Abstract: In semi-arid Zimbabwe livestock play a vital role in the livelihoods of small-scale farmers. Current productivity is low due to various inefficiencies, but there is a huge potential for farmers to obtain significant incomes from strategic sales and improved management. Climate variability and change are a threat, especially through negative impacts on the major fodder sources, such as rangelands and crop residues. This study used the LivSim model to simulate the impacts of climate variability and change on livestock productivity by taking into account the effects on the feed base. Model calibration was done based on local breed data from farms and experiments. The feed inputs consisted of grass from rangelands and crop residues from maize, sorghum and groundnut, obtained from crop modelling using Apsim and DSSAT. Different climate scenarios were created using two contrasting GCMs. Milk yield, offtake and mortality rates were simulated for a 30-year period for 160 households. The study also assessed the benefits of adaptation by including a forage legume (Mucuna pruriens) in rotation with maize, in addition to micro-dosing fertilizer on maize. The results indicated that in the hot and dry climate scenario, crop residue and rangeland production declined, leading to reduced livestock productivity. The adaptation package can mitigate the negative impacts of climate change on milk production, offtake and mortality. Farmers can thus reduce their vulnerability to climate change by increasing feed quantity and quality. Improved market access becomes essential for farmers to benefit from improved offtake and continued investment in adaptation packages.
18. Poster Presentation: Session 1.8
Title: Parameterizing LivSim for simulating growth of the Ghana shorthorn cattle
Authors: Eric Timpong-Jones1, B.S. Freduah1, S.G.K. Adiku1, A. Nenkam2, M. Adam3,T.
Ramilan4, and D.S. MacCarthy1 1 University of Ghana, College of Basic and Applied Sciences, School of Agriculture, Accra, Ghana, 2 International Crop Research Institute
for Semi-Arid Tropics, Mali, 3 CIRAD-INERA-ICRISAT, Burkina Faso, 4 Institute of Agriculture and Environment,Massey University, New Zealand
Abstract: An important component of the farming system in Ghana is livestock production. Livestock, especially cattle production is heavily dependent on rainfall for the production of forages to feed them. Projected increase in temperature and shifts in rainfall patterns due to climate change is expected to affect the level of livestock production and livelihood of the resource poor animal herders in Ghana. To gain insight into the livestock-climate nexus, we conducted a study in Tamale in the Northern region of Ghana to parameterize the LivSim (Livestock Simulator) model for the simulation of growth of the Ghana Shorthorn cattle. The main objective was to quantify milk and calf production by the various smallholder farmers in the community. A survey of 261 households out of which 96 owned livestock was conducted to obtain observed data on milk yield, calving frequencies, among others. Other data required by LivSIM such as the minimum and maximum bodyweights of both male and female Ghana Shorthorn were obtained from the literature. The number of cattle owned by the households interviewed ranged from 2-47 with majority having a herd size less than twelve. The herd composition was estimated to be 72% female and 28% male. Preliminary simulation results showed that the herd dynamics could be well captured for an initial period of 5 years, after which there was divergence between the simulated and the observed. Further current efforts are directed to the improvement in parameter values especially those relating to the potential growth rates and the compensatory growth rate.