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- ItemLivestock in a changing climate: Production system transitions as an adaptation strategy for agriculture(Bristol : IOP Publishing, 2015) Weindl, Isabelle; Lotze-Campen, Hermann; Popp, Alexander; Müller, Christoph; Havlík, Petr; Herrero, Mario; Schmitz, Christoph; Rolinski, SusanneLivestock farming is the world's largest land use sector and utilizes around 60% of the global biomass harvest. Over the coming decades, climate change will affect the natural resource base of livestock production, especially the productivity of rangeland and feed crops. Based on a comprehensive impact modeling chain, we assess implications of different climate projections for agricultural production costs and land use change and explore the effectiveness of livestock system transitions as an adaptation strategy. Simulated climate impacts on crop yields and rangeland productivity generate adaptation costs amounting to 3% of total agricultural production costs in 2045 (i.e. 145 billion US$). Shifts in livestock production towards mixed crop-livestock systems represent a resource- and cost-efficient adaptation option, reducing agricultural adaptation costs to 0.3% of total production costs and simultaneously abating deforestation by about 76 million ha globally. The relatively positive climate impacts on grass yields compared with crop yields favor grazing systems inter alia in South Asia and North America. Incomplete transitions in production systems already have a strong adaptive and cost reducing effect: a 50% shift to mixed systems lowers agricultural adaptation costs to 0.8%. General responses of production costs to system transitions are robust across different global climate and crop models as well as regarding assumptions on CO2 fertilization, but simulated values show a large variation. In the face of these uncertainties, public policy support for transforming livestock production systems provides an important lever to improve agricultural resource management and lower adaptation costs, possibly even contributing to emission reduction.
- ItemReducing deforestation and improving livestock productivity: greenhouse gas mitigation potential of silvopastoral systems in Caquetá(Bristol : IOP Publ., 2019) Landholm, David M.; Pradhan, Prajal; Wegmann, Peter; Sánchez, Miguel A. Romero; Salazar, Juan Carlos Suárez; Kropp, Juergen P.Colombia's agriculture, forestry and other land use sector accounts for nearly half of its total greenhouse gas (GHG) emissions. The importance of smallholder deforestation is comparatively high in relation to its regional counterparts, and livestock agriculture represents the largest driver of primary forest depletion. Silvopastoral systems (SPSs) are presented as agroecological solutions that synergistically enhance livestock productivity, improve local farmers' livelihoods and hold the potential to reduce pressure on forest conversion. The department of Caquetá represents Colombia's most important deforestation hotspot. Targeting smallholder livestock farms through survey data, in this work we investigate the GHG mitigation potential of implementing SPSs for smallholder farms in this region. Specifically, we assess whether the carbon sequestration taking place in the soil and biomass of SPSs is sufficient to offset the per-hectare increase in livestock GHG emissions resulting from higher stocking rates. To address these questions we use data on livestock population characteristics and historic land cover changes reported from a survey covering 158 farms and model the carbon sequestration occurring in three different scenarios of progressively-increased SPS complexity using the CO2 fix model. We find that, even with moderate tree planting densities, the implementation of SPSs can reduce GHG emissions by 2.6 Mg CO2e ha−1 yr−1 in relation to current practices, while increasing agriculture productivity and contributing to the restoration of severely degraded landscapes.
- ItemA new climate dataset for systematic assessments of climate change impacts as a function of global warming(München : European Geopyhsical Union, 2012) Heinke, J.; Ostberg, S.; Schaphoff, S.; Frieler, K.; Müller, C.; Gerten, D.; Meinshausen, M.; Lucht, W.Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.
- ItemThe Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use(München : European Geopyhsical Union, 2012) Souty, F.; Brunelle, T.; Dumas, P.; Dorin, B.; Ciais, P.; Crassous, R.; Müller, C.; Bondeau, A.Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.
- ItemHow the Selection of Training Data and Modeling Approach Affects the Estimation of Ammonia Emissions from a Naturally Ventilated Dairy Barn—Classical Statistics versus Machine Learning(Basel : MDPI AG, 2020) Hempel, Sabrina; Adolphs, Julian; Landwehr, Niels; Janke, David; Amon, ThomasEnvironmental protection efforts can only be effective in the long term with a reliable quantification of pollutant gas emissions as a first step to mitigation. Measurement and analysis strategies must permit the accurate extrapolation of emission values. We systematically analyzed the added value of applying modern machine learning methods in the process of monitoring emissions from naturally ventilated livestock buildings to the atmosphere. We considered almost 40 weeks of hourly emission values from a naturally ventilated dairy cattle barn in Northern Germany. We compared model predictions using 27 different scenarios of temporal sampling, multiple measures of model accuracy, and eight different regression approaches. The error of the predicted emission values with the tested measurement protocols was, on average, well below 20%. The sensitivity of the prediction to the selected training dataset was worse for the ordinary multilinear regression. Gradient boosting and random forests provided the most accurate and robust emission value predictions, accompanied by the second-smallest model errors. Most of the highly ranked scenarios involved six measurement periods, while the scenario with the best overall performance was: One measurement period in summer and three in the transition periods, each lasting for 14 days.
- ItemMethane Emission Characteristics of Naturally Ventilated Cattle Buildings(Basel : MDPI AG, 2020) Hempel, Sabrina; Willink, Diliara; Janke, David; Ammon, Christian; Amon, Barbara; Amon, ThomasThe mandate to limit global temperature rise calls for a reliable quantification of gaseous pollutant emissions as a basis for effective mitigation. Methane emissions from ruminant fermentation are of particular relevance in the context of greenhouse gas mitigation. The emission dynamics are so far insufficiently understood. We analyzed hourly methane emission data collected during contrasting seasons from two naturally ventilated dairy cattle buildings with concrete floor and performed a second order polynomial regression. We found a parabolic temperature dependence of the methane emissions irrespective of the measurement site and setup. The position of the parabola vertex varied when considering different hours of the day. The circadian rhythm of methane emissions was represented by the pattern of the fitted values of the constant term of the polynomial and could be well explained by feeding management and air flow conditions. We found barn specific emission minima at ambient temperatures around 10 °C to 15 °C. As this identified temperature optimum coincides with the welfare temperature of dairy cows, we concluded that temperature regulation of dairy cow buildings with concrete floor should be considered and further investigated as an emission mitigation measure. Our results further indicated that empirical modeling of methane emissions from the considered type of buildings with a second order polynomial for the independent variable air temperature can increase the accuracy of predicted long-term emission values for regions with pronounced seasonal temperature fluctuations
- ItemWater Use in Global Livestock Production—Opportunities and Constraints for Increasing Water Productivity([New York] : Wiley, 2020) Heinke, Jens; Lannerstad, Mats; Gerten, Dieter; Havlík, Petr; Herrero, Mario; Notenbaert, An Maria Omer; Hoff, Holger; Müller, ChristophIncreasing population, change in consumption habits, and climate change will likely increase the competition for freshwater resources in the future. Exploring ways to improve water productivity especially in food and livestock systems is important for tackling the future water challenge. Here we combine detailed data on feed use and livestock production with Food and Agriculture Organization of the United Nations (FAO) statistics and process-based crop-water model simulations to comprehensively assess water use and water productivity in the global livestock sector. We estimate that, annually, 4,387 km3 of blue and green water is used for the production of livestock feed, equaling about 41% of total agricultural water use. Livestock water productivity (LWP; protein produced per m3 of water) differs by several orders of magnitude between livestock types, regions, and production systems, indicating a large potential for improvements. For pigs and broilers, we identify large opportunities to increase LWP by increasing both feed water productivity (FWP; feed produced per m3 of water) and feed use efficiency (FUE; protein produced per kg of feed) through better crop and livestock management. Even larger opportunities to increase FUE exist for ruminants, while the overall potential to increase their FWP is low. Substantial improvements of FUE can be achieved for ruminants by supplementation with feed crops, but the lower FWP of these feed crops compared to grazed biomass limits possible overall improvements of LWP. Therefore, LWP of ruminants, unlike for pigs and poultry, does not always benefit from a trend toward intensification, as this is often accompanied by increasing crop supplementation.